Evolutionary biology

@article{openalexw2591687711,
    author = "de Beer, G. R.",
    title = "Evolution. Essays on aspects of evolutionary biology.",
    year = "1938",
    url = "https://openalex.org/W2591687711",
    openalex = "W2591687711"
}

@misc{ehrilch1963the1,
    author = "Ehrilch, P. R. and Holm, R. W",
    title = "The process of evolution",
    year = "1963",
    howpublished = "New York, McGraw-Hill, 347 p",
    note = "talkorigins\_source = {true}; raw\_reference = {Ehrilch, P. R., and Holm, R. W., 1963, The process of evolution: New York, McGraw-Hill, 347 p.}"
}

@misc{erlich1967evolutionary2,
    author = "Erlich, P. and Birch, L. C",
    title = "Evolutionary history and population biology",
    year = "1967",
    howpublished = "Nature, v. 214, p. 349-352",
    note = "talkorigins\_source = {true}; raw\_reference = {Erlich, P., and Birch, L. C., 1967, Evolutionary history and population biology: Nature, v. 214, p. 349-352.}"
}

The general maximum likelihood approach to the statistical estimation of phylogenies is outlined, for data in which there are a number of discrete states for each character. The details of the maximum likelihood method will depend on the details of the probabilistic model of evolution assumed. There are a very large number of possible models of evolution. For a few of the simpler models, the calculation of the likelihood of an evolutionary tree is outlined. For these models, the maximum likelihood tree will be the same as the “most parsimonious” (or minimum-steps) tree if the probability of change during the evolution of the group is assumed a priori to be very small. However, most sets of data require too many assumed state changes per character to be compatible with this assumption. Farris (1973) has argued that maximum likelihood and parsimony methods are identical under a much less restrictive set of assumptions. It is argued that the present methods are preferable to his, and a counterexample to his argument is presented. An algorithm which enables rapid calculation of the likelihood of a phylogeny is described.

@article{doi101093sysbio223240,
    author = "Felsenstein, Joe",
    title = "Maximum Likelihood and Minimum-Steps Methods for Estimating Evolutionary Trees from Data on Discrete Characters",
    year = "1973",
    journal = "Systematic Biology",
    abstract = "The general maximum likelihood approach to the statistical estimation of phylogenies is outlined, for data in which there are a number of discrete states for each character. The details of the maximum likelihood method will depend on the details of the probabilistic model of evolution assumed. There are a very large number of possible models of evolution. For a few of the simpler models, the calculation of the likelihood of an evolutionary tree is outlined. For these models, the maximum likelihood tree will be the same as the “most parsimonious” (or minimum-steps) tree if the probability of change during the evolution of the group is assumed a priori to be very small. However, most sets of data require too many assumed state changes per character to be compatible with this assumption. Farris (1973) has argued that maximum likelihood and parsimony methods are identical under a much less restrictive set of assumptions. It is argued that the present methods are preferable to his, and a counterexample to his argument is presented. An algorithm which enables rapid calculation of the likelihood of a phylogeny is described.",
    url = "https://doi.org/10.1093/sysbio/22.3.240",
    doi = "10.1093/sysbio/22.3.240",
    openalex = "W2157001909"
}

@article{doi101111j155856461975tb00851x,
    author = "Felsenstein, Joseph",
    title = "THE GENETIC BASIS OF EVOLUTIONARY CHANGE",
    year = "1975",
    journal = "Evolution",
    url = "https://doi.org/10.1111/j.1558-5646.1975.tb00851.x",
    doi = "10.1111/j.1558-5646.1975.tb00851.x",
    openalex = "W1547248981"
}

@book{gould1977eternal4,
    author = "Gould, S. J",
    title = "Eternal Metaphors of Paleontology, in Hallam, A., ed., Patterns of Evolution as Illustrated by the Fossil Record",
    year = "1977",
    publisher = "Amsterdam, Elsevier, p. 1-26",
    note = "talkorigins\_source = {true}; raw\_reference = {Gould, S. J., 1977, Eternal Metaphors of Paleontology, in Hallam, A., ed., Patterns of Evolution as Illustrated by the Fossil Record: Amsterdam, Elsevier, p. 1-26.}"
}

@misc{gould1977punctuated6,
    author = "Gould, S. J. and Eldredge, N",
    title = "Punctuated Equilibria",
    year = "1977",
    howpublished = "The Tempo and Mode of Evolution Reconsidered: Paleobiology, v. 3, p. 115-151",
    note = "talkorigins\_source = {true}; raw\_reference = {Gould, S. J., and Eldredge, N., 1977, Punctuated Equilibria: The Tempo and Mode of Evolution Reconsidered: Paleobiology, v. 3, p. 115-151.}"
}

Felsenstein, J. (Department of Genetics, University of Washington, Seattle, Washington 98195) 1978. The number of evolutionary trees. Syst. Zool. 27:27–33.—A simple method of counting the number of possible evolutionary trees is presented. The trees are assumed to be rooted, with labelled tips but unlabelled root and unlabelled interior nodes. The method allows multifurcations as well as bifurcations. It makes use of a simple recurrence relation for T(n,m), the number of trees with n labelled tips and m unlabelled interior nodes. A table of the total number of trees is presented up to n = 22. There are 282,137,824 different trees having 10 tip species, and over 8.87 × 1023 different trees having 20 tip species. The method is extended to count trees some of whose interior nodes may be labelled. The principal uses of these numbers will be to double-check algorithms and notation systems, and to frighten taxonomists.

@article{doi1023072412810,
    author = "Felsenstein, Joseph",
    title = "The Number of Evolutionary Trees",
    year = "1978",
    journal = "Systematic Zoology",
    abstract = "Felsenstein, J. (Department of Genetics, University of Washington, Seattle, Washington 98195) 1978. The number of evolutionary trees. Syst. Zool. 27:27–33.—A simple method of counting the number of possible evolutionary trees is presented. The trees are assumed to be rooted, with labelled tips but unlabelled root and unlabelled interior nodes. The method allows multifurcations as well as bifurcations. It makes use of a simple recurrence relation for T(n,m), the number of trees with n labelled tips and m unlabelled interior nodes. A table of the total number of trees is presented up to n = 22. There are 282,137,824 different trees having 10 tip species, and over 8.87 × 1023 different trees having 20 tip species. The method is extended to count trees some of whose interior nodes may be labelled. The principal uses of these numbers will be to double-check algorithms and notation systems, and to frighten taxonomists.",
    url = "https://doi.org/10.2307/2412810",
    doi = "10.2307/2412810",
    openalex = "W2043887813"
}

@misc{futuyma1979evolutionary3,
    author = "Futuyma, D. J",
    title = "Evolutionary Biology",
    year = "1979",
    howpublished = "Sunderland, Mass., Sinauer Associates",
    note = "talkorigins\_source = {true}; raw\_reference = {Futuyma, D. J., 1979, Evolutionary Biology: Sunderland, Mass., Sinauer Associates.}"
}

@article{doi101007bf01731581,
    author = "Kimura, Motoo",
    title = "A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences",
    year = "1980",
    journal = "Journal of Molecular Evolution",
    url = "https://doi.org/10.1007/bf01731581",
    doi = "10.1007/bf01731581",
    openalex = "W2065461553",
    references = "doi101007bf01653945, doi101007bf01732067, doi101007bf01732340, doi101016b9781483232119500097, doi101016s0021925817401566, doi101038217624a0, doi101038267275a0, doi101038scientificamerican117998, doi101073pnas7172848, doi101126science1643881788"
}

@misc{gould1980is5,
    author = "Gould, S. J",
    title = "Is a new and general theory of evolution emerging?",
    year = "1980",
    howpublished = "Paleobiology, v. 6, p. 119-130",
    note = "talkorigins\_source = {true}; raw\_reference = {Gould, S. J., 1980, Is a new and general theory of evolution emerging?: Paleobiology, v. 6, p. 119-130.}"
}

@article{doi101007bf01734359,
    author = "Felsenstein, Joseph",
    title = "Evolutionary trees from DNA sequences: A maximum likelihood approach",
    year = "1981",
    journal = "Journal of Molecular Evolution",
    url = "https://doi.org/10.1007/bf01734359",
    doi = "10.1007/bf01734359",
    openalex = "W2102424972",
    references = "doi101007bf01659159, doi101007bf01797451, doi101093sysbio223240, doi101093sysbio274401, doi101111j155856461965tb01722x, doi101111j251761611977tb01600x, doi101126science1553760279, doi101159000152448, doi1023072412810, doi1023072412923, openalexw2341059552, openalexw3141390961"
}

With the aim of analyzing and interpreting data on DNA polymorphism obtained by DNA sequencing or restriction enzyme technique, a mathematical theory on the expected evolutionary relationship among DNA sequences (nucleons) sampled is developed under the assumption that the evolutionary change of nucleons is determined solely by mutation and random genetic drift. The statistical property of the number of nucleotide differences between randomly chosen nucleons and that of heterozygosity or nucleon diversity is investigated using this theory. These studies indicate that the estimates of the average number of nucleotide differences and nucleon diversity have a large variance, and a large part of this variance is due to stochastic factors. Therefore, increasing sample size does not help reduce the variance significantly The distribution of sample allele (nucleomorph) frequencies is also studied, and it is shown that a small number of samples are sufficient in order to know the distribution pattern.

@article{doi101093genetics1052437,
    author = "Tajima, Fumio",
    title = "EVOLUTIONARY RELATIONSHIP OF DNA SEQUENCES IN FINITE POPULATIONS",
    year = "1983",
    journal = "Genetics",
    abstract = "With the aim of analyzing and interpreting data on DNA polymorphism obtained by DNA sequencing or restriction enzyme technique, a mathematical theory on the expected evolutionary relationship among DNA sequences (nucleons) sampled is developed under the assumption that the evolutionary change of nucleons is determined solely by mutation and random genetic drift. The statistical property of the number of nucleotide differences between randomly chosen nucleons and that of heterozygosity or nucleon diversity is investigated using this theory. These studies indicate that the estimates of the average number of nucleotide differences and nucleon diversity have a large variance, and a large part of this variance is due to stochastic factors. Therefore, increasing sample size does not help reduce the variance significantly The distribution of sample allele (nucleomorph) frequencies is also studied, and it is shown that a small number of samples are sufficient in order to know the distribution pattern.",
    url = "https://doi.org/10.1093/genetics/105.2.437",
    doi = "10.1093/genetics/105.2.437",
    openalex = "W1928220195",
    references = "doi1010160040580972900354, doi1010160040580974900252, doi1010160040580975900209, doi101017s000186780003994x, doi101073pnas7763605, doi101093genetics1032287, doi101093genetics893583, doi101093genetics971145, doi101111j155856461983tb05528x, doi1023072408186"
}

(Uploaded by Plazi for the Bat Literature Project) No abstract provided.

@article{doi101146annureves18110187001321,
    author = "Charlesworth, Deborah and Charlesworth, Brian",
    title = "INBREEDING DEPRESSION AND ITS EVOLUTIONARY CONSEQUENCES",
    year = "1987",
    journal = "Annual Review of Ecology and Systematics",
    abstract = "(Uploaded by Plazi for the Bat Literature Project) No abstract provided.",
    url = "https://doi.org/10.1146/annurev.es.18.110187.001321",
    doi = "10.1146/annurev.es.18.110187.001321",
    openalex = "W2167243456",
    references = "doi101017s0305004100015644, doi101073pnas4211855, doi101111j155856461975tb00851x, doi105962bhltitle122451, doi107312steb94536, openalexw2062594085"
}

@book{doi107312nei92038,
    author = "Nei, Masatoshi",
    title = "Molecular Evolutionary Genetics",
    year = "1987",
    booktitle = "Columbia University Press eBooks",
    url = "https://doi.org/10.7312/nei-92038",
    doi = "10.7312/nei-92038",
    openalex = "W93588716"
}

@article{doi101007bf02100115,
    author = "Kishino, Hirohisa and Hasegawa, Masami",
    title = "Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea",
    year = "1989",
    journal = "Journal of Molecular Evolution",
    url = "https://doi.org/10.1007/bf02100115",
    doi = "10.1007/bf02100115",
    openalex = "W2037667459",
    references = "doi101007978146121694015, doi101007bf01731581, doi101007bf01734101, doi101007bf01734359, doi101007bf02101694, doi1010160016003259903680, doi101093sysbio274401, doi101109tac19741100705, doi101111j155856461985tb00420x, doi101126science15838051200, doi101214aoms1177729694, doi1023072412923, doi107312nei92038, sarich1967immunological"
}

All extant organisms are though to be classified into three primary kingdoms, eubacteria, eukaryotes, and archaebacteria. The molecular evolutionary studies on the origin and evolution of archaebacteria to date have been carried out by inferring a molecular phylogenetic tree of the primary kingdoms based on comparison of a single molecule from a variety of extant species. From such comparison, it was not possible to derive the exact evolutionary relationship among the primary kingdoms, because the root of the tree could not be determined uniquely. To overcome this difficulty, we compared a pair of duplicated genes, elongation factors Tu and G, and the alpha and beta subunits of ATPase, which are thought to have diverged by gene duplication before divergence of the primary kingdoms. Using each protein pair, we inferred a composite phylogenetic tree with two clusters corresponding to different proteins, from which the evolutionary relationship of the primary kingdoms is determined uniquely. The inferred composite trees reveal that archaebacteria are more closely related to eukaryotes than to eubacteria for all the cases. By bootstrap resamplings, this relationship is reproduced with probabilities of 0.96, 0.79, 1.0, and 1.0 for elongation factors Tu and G and for ATPase subunits alpha and beta, respectively. There are also several lines of evidence for the close sequence similarity between archaebacteria and eukaryotes. Thus we propose that this tree topology represents the general evolutionary relationship among the three primary kingdoms.

@article{doi101073pnas86239355,
    author = "Iwabe, Naoyuki and Kuma, K and Hasegawa, M. and Osawa, S. and Miyata, Takaki",
    title = "Evolutionary relationship of archaebacteria, eubacteria, and eukaryotes inferred from phylogenetic trees of duplicated genes.",
    year = "1989",
    journal = "Proceedings of the National Academy of Sciences",
    abstract = "All extant organisms are though to be classified into three primary kingdoms, eubacteria, eukaryotes, and archaebacteria. The molecular evolutionary studies on the origin and evolution of archaebacteria to date have been carried out by inferring a molecular phylogenetic tree of the primary kingdoms based on comparison of a single molecule from a variety of extant species. From such comparison, it was not possible to derive the exact evolutionary relationship among the primary kingdoms, because the root of the tree could not be determined uniquely. To overcome this difficulty, we compared a pair of duplicated genes, elongation factors Tu and G, and the alpha and beta subunits of ATPase, which are thought to have diverged by gene duplication before divergence of the primary kingdoms. Using each protein pair, we inferred a composite phylogenetic tree with two clusters corresponding to different proteins, from which the evolutionary relationship of the primary kingdoms is determined uniquely. The inferred composite trees reveal that archaebacteria are more closely related to eukaryotes than to eubacteria for all the cases. By bootstrap resamplings, this relationship is reproduced with probabilities of 0.96, 0.79, 1.0, and 1.0 for elongation factors Tu and G and for ATPase subunits alpha and beta, respectively. There are also several lines of evidence for the close sequence similarity between archaebacteria and eukaryotes. Thus we propose that this tree topology represents the general evolutionary relationship among the three primary kingdoms.",
    url = "https://doi.org/10.1073/pnas.86.23.9355",
    doi = "10.1073/pnas.86.23.9355",
    openalex = "W1991207390",
    references = "doi1010160378111988903344, doi101038331184a0, doi101038scientificamerican117998, doi101073pnas74115088, doi101073pnas81123786, doi101073pnas86124569, doi101093oxfordjournalsmolbeva040454, doi101093oxfordjournalsmolbeva040455, doi101111j174966321987tb40596x, doi101128mr5122212711987"
}

This review deals with the following seven aspects of vertebrate skeletogenic and odontogenic tissues. 1. The evolutionary sequence in which the tissues appeared amongst the lower craniate taxa. 2. The topographic association between skeletal (cartilage, bone) and dental (dentine, cement, enamel) tissues in the oldest vertebrates of each major taxon. 3. The separate developmental origin of the exo- and endoskeletons. 4. The neural-crest origin of cranial skeletogenic and odontogenic tissues in extant vertebrates. 5. The neural-crest origin of trunk dermal skeletogenic and odontogenic tissues in extant vertebrates. 6. The developmental processes that control differentiation of skeletogenic and odontogenic tissues in extant vertebrates. 7. Maintenance of developmental interactions regulating skeletogenic/odontogenic differentiation across vertebrate taxa. We derive twelve postulates, eight relating to the earliest vertebrate skeletogenic and odontogenic tissues and four relating to the development of these tissues in extant vertebrates and extrapolate the developmental data back to the evolutionary origin of vertebrate skeletogenic and odontogenic tissues. The conclusions that we draw from this analysis are as follows. 8. The dermal exoskeleton of thelodonts, heterostracans and osteostracans consisted of dentine, attachment tissue (cement or bone), and bone. 9. Cartilage (unmineralized) can be inferred to have been present in heterostracans and osteostracans, and globular mineralized cartilage was present in Eriptychius, an early Middle Ordovician vertebrate unassigned to any established group, but assumed to be a stem agnathan. 10. Enamel and possibly also enameloid was present in some early agnathans of uncertain affinities. The majority of dentine tubercles were bare. 11. The contemporaneous appearance of cellular and acellular bone in heterostracans and osteostracans during the Ordovician provides no clue as to whether one is more primitive than the other. 12. We interpret aspidin as being developmentally related to the odontogenic attachment tissues, either closer to dentine or a form of cement, rather than as derived from bone. 13. Dentine is present in the stratigraphically oldest (Cambrian) assumed vertebrate fossils, at present some only included as Problematica, and is cladistically primitive, relative to bone. 14. The first vertebrate exoskeletal skeletogenic ability was expressed as denticles of dentine. 15. Dentine, the bone of attachment associated with dentine, the basal bone to which dermal denticles are fused and cartilage of the Ordovician agnathan dermal exoskeleton were all derived from the neural crest and not from mesoderm. Therefore the earliest vertebrate skeletogenic/odontogenic tissues were of neural-crest origin.(ABSTRACT TRUNCATED AT 400 WORDS)

@article{doi101111j1469185x1990tb01427x,
    author = "Smith, Moya Meredith and Hall, Brian K.",
    title = "DEVELOPMENT AND EVOLUTIONARY ORIGINS OF VERTEBRATE SKELETOGENIC AND ODONTOGENIC TISSUES",
    year = "1990",
    journal = "Biological reviews/Biological reviews of the Cambridge Philosophical Society",
    abstract = "This review deals with the following seven aspects of vertebrate skeletogenic and odontogenic tissues. 1. The evolutionary sequence in which the tissues appeared amongst the lower craniate taxa. 2. The topographic association between skeletal (cartilage, bone) and dental (dentine, cement, enamel) tissues in the oldest vertebrates of each major taxon. 3. The separate developmental origin of the exo- and endoskeletons. 4. The neural-crest origin of cranial skeletogenic and odontogenic tissues in extant vertebrates. 5. The neural-crest origin of trunk dermal skeletogenic and odontogenic tissues in extant vertebrates. 6. The developmental processes that control differentiation of skeletogenic and odontogenic tissues in extant vertebrates. 7. Maintenance of developmental interactions regulating skeletogenic/odontogenic differentiation across vertebrate taxa. We derive twelve postulates, eight relating to the earliest vertebrate skeletogenic and odontogenic tissues and four relating to the development of these tissues in extant vertebrates and extrapolate the developmental data back to the evolutionary origin of vertebrate skeletogenic and odontogenic tissues. The conclusions that we draw from this analysis are as follows. 8. The dermal exoskeleton of thelodonts, heterostracans and osteostracans consisted of dentine, attachment tissue (cement or bone), and bone. 9. Cartilage (unmineralized) can be inferred to have been present in heterostracans and osteostracans, and globular mineralized cartilage was present in Eriptychius, an early Middle Ordovician vertebrate unassigned to any established group, but assumed to be a stem agnathan. 10. Enamel and possibly also enameloid was present in some early agnathans of uncertain affinities. The majority of dentine tubercles were bare. 11. The contemporaneous appearance of cellular and acellular bone in heterostracans and osteostracans during the Ordovician provides no clue as to whether one is more primitive than the other. 12. We interpret aspidin as being developmentally related to the odontogenic attachment tissues, either closer to dentine or a form of cement, rather than as derived from bone. 13. Dentine is present in the stratigraphically oldest (Cambrian) assumed vertebrate fossils, at present some only included as Problematica, and is cladistically primitive, relative to bone. 14. The first vertebrate exoskeletal skeletogenic ability was expressed as denticles of dentine. 15. Dentine, the bone of attachment associated with dentine, the basal bone to which dermal denticles are fused and cartilage of the Ordovician agnathan dermal exoskeleton were all derived from the neural crest and not from mesoderm. Therefore the earliest vertebrate skeletogenic/odontogenic tissues were of neural-crest origin.(ABSTRACT TRUNCATED AT 400 WORDS)",
    url = "https://doi.org/10.1111/j.1469-185x.1990.tb01427.x",
    doi = "10.1111/j.1469-185x.1990.tb01427.x",
    openalex = "W2104126911",
    references = "doi10100797814615696887, doi101007bf02058654, doi1010160012160683903184, doi101017cbo9780511897948, doi101017s0016756800082856, doi101017s0080456800035237, doi101038282831a0, doi101038282833a0, doi101038scientificamerican0779122, doi10108002724634198110011886, doi10108002724634198410012014, doi101086413055, doi101093aesa323657, doi101111j109636421986tb00876x, doi101111j146363951940tb00339x, doi101111j146364091979tb00640x, doi101111j146364091980tb00660x, doi101111j1469185x1973tb01005x, doi101111j150239311983tb01993x, doi101111j150239311986tb00741x, doi101126science15737951472, doi101126science2204594268, doi101130gsab3153, doi1023072413259, doi1023072413454, doi1023072992444, doi105962bhltitle5752, doi105962bhltitle82144, halstead1969calcified, halstead1979agnathans, openalexw115975037, openalexw251296685, openalexw2591687711, openalexw2732375649, openalexw587905045"
}

A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C++ and is intended to be used on IBM and IBM-compatible personal computers. In this program, various methods for estimating evolutionary distances from nucleotide and amino acid sequence data, three different methods of phylogenetic inference (UPGMA, neighborjoining and maximum parsimony) and two statistical tests of topological differences are included. For the maximum parsimony method, new algorithms of branch-and-bound and heuristic searches are implemented. In addition, MEGA computes statistical quantities such as nucleotide and amino acid frequencies, transition/transversion biases, codon frequencies (codon usage tables), and the number of variable sites in specified segments in nucleotide and amino acid sequences. Advanced on-screen sequence data and phylogenetictree editors facilitate publication-quality outputs with a wide range of printers. Integrated and interactive designs, on-line context-sensitive helps, and a text-file editor make MEGA easy to use.

@article{doi101093bioinformatics102189,
    author = "Kumar, Sudhir and Tamura, Koichiro and Nei, Masatoshi",
    title = "MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers",
    year = "1994",
    journal = "Computer applications in the biosciences",
    abstract = "A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C++ and is intended to be used on IBM and IBM-compatible personal computers. In this program, various methods for estimating evolutionary distances from nucleotide and amino acid sequence data, three different methods of phylogenetic inference (UPGMA, neighborjoining and maximum parsimony) and two statistical tests of topological differences are included. For the maximum parsimony method, new algorithms of branch-and-bound and heuristic searches are implemented. In addition, MEGA computes statistical quantities such as nucleotide and amino acid frequencies, transition/transversion biases, codon frequencies (codon usage tables), and the number of variable sites in specified segments in nucleotide and amino acid sequences. Advanced on-screen sequence data and phylogenetictree editors facilitate publication-quality outputs with a wide range of printers. Integrated and interactive designs, on-line context-sensitive helps, and a text-file editor make MEGA easy to use.",
    url = "https://doi.org/10.1093/bioinformatics/10.2.189",
    doi = "10.1093/bioinformatics/10.2.189",
    openalex = "W2097403532"
}

Preface The Enteric Bacterial Cell and the Age of Bacteria Variations on a Theme by Escherichia Part I: Molecular Architecture and Assembly of Cell Parts (11 chapters) Part II: Metabolism and General Physiology (58 chapters) Part III: Utilization of Energy for Cell Activities (7 chapters) Part IV: Regulation of Gene Expression (19 chapters) Part V: Growth of Cells and Cultures (12 chapters) Part VI: Genome, Genetics and Evolution (40 chapters) Part VII: Molecular Pathogenesis (7 chapters)

@book{openalexw1512810258,
    author = "Neidhardt, Frederick C.",
    title = "Escherichia coli and Salmonella:cellular and molecular biology",
    year = "1996",
    booktitle = "ASM Press eBooks",
    abstract = "Preface The Enteric Bacterial Cell and the Age of Bacteria Variations on a Theme by Escherichia Part I: Molecular Architecture and Assembly of Cell Parts (11 chapters) Part II: Metabolism and General Physiology (58 chapters) Part III: Utilization of Energy for Cell Activities (7 chapters) Part IV: Regulation of Gene Expression (19 chapters) Part V: Growth of Cells and Cultures (12 chapters) Part VI: Genome, Genetics and Evolution (40 chapters) Part VII: Molecular Pathogenesis (7 chapters)",
    openalex = "W1512810258"
}

Every form of behaviour is shaped by trial and error. Such stepwise adaptation can occur through individual learning or through natural selection, the basis of evolution. Since the work of Maynard Smith and others, it has been realised how game theory can model this process. Evolutionary game theory replaces the static solutions of classical game theory by a dynamical approach centred not on the concept of rational players but on the population dynamics of behavioural programmes. In this book the authors investigate the nonlinear dynamics of the self-regulation of social and economic behaviour, and of the closely related interactions between species in ecological communities. Replicator equations describe how successful strategies spread and thereby create new conditions which can alter the basis of their success, i.e. to enable us to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions which punctuate evolution. In short, evolutionary game theory describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.

@book{doi101017cbo9781139173179,
    author = "Hofbauer, Josef and Sigmund, Karl",
    title = "Evolutionary Games and Population Dynamics",
    year = "1998",
    booktitle = "Cambridge University Press eBooks",
    abstract = "Every form of behaviour is shaped by trial and error. Such stepwise adaptation can occur through individual learning or through natural selection, the basis of evolution. Since the work of Maynard Smith and others, it has been realised how game theory can model this process. Evolutionary game theory replaces the static solutions of classical game theory by a dynamical approach centred not on the concept of rational players but on the population dynamics of behavioural programmes. In this book the authors investigate the nonlinear dynamics of the self-regulation of social and economic behaviour, and of the closely related interactions between species in ecological communities. Replicator equations describe how successful strategies spread and thereby create new conditions which can alter the basis of their success, i.e. to enable us to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions which punctuate evolution. In short, evolutionary game theory describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.",
    url = "https://doi.org/10.1017/cbo9781139173179",
    doi = "10.1017/cbo9781139173179",
    openalex = "W2085728653",
    references = "doi101007978146847862422, doi1010160040580977900429, doi101038119012b0, doi101086282272, doi1023071578, doi1023072965538, doi1023074549, doi1023075530, doi105962bhltitle4489"
}

@article{doi10103832160,
    author = "Blaxter, Mark and Ley, Paul De and Garey, James R. and Liu, Leo X. and Scheldeman, Patsy and Vierstraete, Andy and Vanfleteren, Jacques R. and Mackey, Laura Y. and Dorris, Mark and Frisse, L.M. and Vida, J. T. and Thomas, W. Kelley",
    title = "A molecular evolutionary framework for the phylum Nematoda",
    year = "1998",
    journal = "Nature",
    url = "https://doi.org/10.1038/32160",
    doi = "10.1038/32160",
    openalex = "W2170946319",
    references = "doi101007978364260458421, doi101038387489a0, doi10107997808519942150000, doi101093bioinformatics105569, doi101093molbevmsab120, doi101093sysbio274401, doi101126science11536722, doi101144gsjgs15420265, doi1023072412923, doi1023073221805, openalexw1596387560"
}

We describe the nonvolant mammal fauna of the Rio Juruá of the western Amazon of Brazil, based on collections made during a year-long survey of the river. We, along with our colleagues Drs. Claude Gascon and Carlos Peres, designed the field project to examine the effects of the river on the differentiation among terrestrial vertebrates (mammals, birds, and amphibians and reptiles) at both the community and population levels. This monograph examines only the patterns of geographic variation and community structure of the small-bodied mammals. Species inventories were made at 16 primary trapping localities divided into eight pairs of cross-river sites, with two pairs in each of four regions from near the mouth to the headwaters of the Rio Juruá. A total of 81 species of nonvolant mammals were obtained, including nine new to science. Four of these are described herein; the others have been described elsewhere. We used a standardized trapping protocol to assess community structure at each of the 16 localities that included terrestrial and canopy trap stations in floodplain (várzea) and upland (terra firme) forest formations. Supplemental trapping was done in secondary habitats at all sites. We describe these sites, the trap effort expended, and the placement of trap stations relative to local habitats. We also describe each species of marsupial, sciurid rodent, murid rodent, and echimyid rodent encountered; comment on their systematics; and summarize aspects of habitat use, life history, geographic distribution, and geographic differentiation based on morphological and molecular traits. We examine patterns of differentiation in the mitochondrial cytochrome-b gene for samples of 41 of the 45 species of marsupials and rodents obtained within the Rio Juruá Basin, and discuss these patterns from the perspective of the entire Amazon and, in some cases, the Mata Atlântica of coastal Brazil. We also examine patterns of community organization within the Rio Juruá basin and throughout Amazonia, drawing attention to the geographic distribution of what appear to be major faunal units that are independent of habitat differences. Finally, we use principles of phylogeography to analyze patterns of geographic differentiation among the nonvolant mammals with regard to the Riverine Barrier Hypothesis. We show that, while there are few examples of taxa for which the Rio Juruá is apparently a barrier, most taxa either are largely undifferentiated throughout the basin or are sharply divided into reciprocally monophyletic mtDNA haplotype clades separable into upriver and downriver units. We argue that the concordance in the geographic placement of clade boundaries suggests a common history; moreover, both the age of these clades and their geographic position in relation to underlying geological features suggest that landform evolution has been an important, but underappreciated component of diversification within western Amazonia.

@article{doi1012060003009020002440001motrja20co2,
    author = "Patton, James L. and SILVA, MARIA NAZARETH F. DA and Malcolm, Jay R.",
    title = "MAMMALS OF THE RIO JURUÁ AND THE EVOLUTIONARY AND ECOLOGICAL DIVERSIFICATION OF AMAZONIA",
    year = "2000",
    journal = "Bulletin of the American Museum of Natural History",
    abstract = "We describe the nonvolant mammal fauna of the Rio Juruá of the western Amazon of Brazil, based on collections made during a year-long survey of the river. We, along with our colleagues Drs. Claude Gascon and Carlos Peres, designed the field project to examine the effects of the river on the differentiation among terrestrial vertebrates (mammals, birds, and amphibians and reptiles) at both the community and population levels. This monograph examines only the patterns of geographic variation and community structure of the small-bodied mammals. Species inventories were made at 16 primary trapping localities divided into eight pairs of cross-river sites, with two pairs in each of four regions from near the mouth to the headwaters of the Rio Juruá. A total of 81 species of nonvolant mammals were obtained, including nine new to science. Four of these are described herein; the others have been described elsewhere. We used a standardized trapping protocol to assess community structure at each of the 16 localities that included terrestrial and canopy trap stations in floodplain (várzea) and upland (terra firme) forest formations. Supplemental trapping was done in secondary habitats at all sites. We describe these sites, the trap effort expended, and the placement of trap stations relative to local habitats. We also describe each species of marsupial, sciurid rodent, murid rodent, and echimyid rodent encountered; comment on their systematics; and summarize aspects of habitat use, life history, geographic distribution, and geographic differentiation based on morphological and molecular traits. We examine patterns of differentiation in the mitochondrial cytochrome-b gene for samples of 41 of the 45 species of marsupials and rodents obtained within the Rio Juruá Basin, and discuss these patterns from the perspective of the entire Amazon and, in some cases, the Mata Atlântica of coastal Brazil. We also examine patterns of community organization within the Rio Juruá basin and throughout Amazonia, drawing attention to the geographic distribution of what appear to be major faunal units that are independent of habitat differences. Finally, we use principles of phylogeography to analyze patterns of geographic differentiation among the nonvolant mammals with regard to the Riverine Barrier Hypothesis. We show that, while there are few examples of taxa for which the Rio Juruá is apparently a barrier, most taxa either are largely undifferentiated throughout the basin or are sharply divided into reciprocally monophyletic mtDNA haplotype clades separable into upriver and downriver units. We argue that the concordance in the geographic placement of clade boundaries suggests a common history; moreover, both the age of these clades and their geographic position in relation to underlying geological features suggest that landform evolution has been an important, but underappreciated component of diversification within western Amazonia.",
    url = "https://doi.org/10.1206/0003-0090(2000)244<0001:motrja>2.0.co;2",
    doi = "10.1206/0003-0090(2000)244<0001:motrja>2.0.co;2",
    openalex = "W2135738065",
    references = "doi101093molbevmsab120, doi101111j155856461988tb04164x"
}

s.kumar@asu.edu

@article{doi101093bioinformatics17121244,
    author = "Kumar, Sudhir and Tamura, Koichiro and Jakobsen, Ingrid B. and Nei, Masatoshi",
    title = "MEGA2: molecular evolutionary genetics analysis software",
    year = "2001",
    journal = "Bioinformatics",
    abstract = "s.kumar@asu.edu",
    url = "https://doi.org/10.1093/bioinformatics/17.12.1244",
    doi = "10.1093/bioinformatics/17.12.1244",
    openalex = "W2156434383",
    references = "doi101007bf00173196, doi101093bioinformatics102189, doi101093oso97801951358480010001, doi101093oxfordjournalsmolbeva040259, doi102307jctvcm4gbm10, openalexw2002446259"
}

In addition to altering global ecology, technology and human population growth also affect evolutionary trajectories, dramatically accelerating evolutionary change in other species, especially in commercially important, pest, and disease organisms. Such changes are apparent in antibiotic and human immunodeficiency virus (HIV) resistance to drugs, plant and insect resistance to pesticides, rapid changes in invasive species, life-history change in commercial fisheries, and pest adaptation to biological engineering products. This accelerated evolution costs at least $33 billion to $50 billion a year in the United States. Slowing and controlling arms races in disease and pest management have been successful in diverse ecological and economic systems, illustrating how applied evolutionary principles can help reduce the impact of humankind on evolution.

@article{doi101126science29355361786,
    author = "Palumbi, Stephen R.",
    title = "Humans as the World's Greatest Evolutionary Force",
    year = "2001",
    journal = "Science",
    abstract = "In addition to altering global ecology, technology and human population growth also affect evolutionary trajectories, dramatically accelerating evolutionary change in other species, especially in commercially important, pest, and disease organisms. Such changes are apparent in antibiotic and human immunodeficiency virus (HIV) resistance to drugs, plant and insect resistance to pesticides, rapid changes in invasive species, life-history change in commercial fisheries, and pest adaptation to biological engineering products. This accelerated evolution costs at least $33 billion to $50 billion a year in the United States. Slowing and controlling arms races in disease and pest management have been successful in diverse ecological and economic systems, illustrating how applied evolutionary principles can help reduce the impact of humankind on evolution.",
    url = "https://doi.org/10.1126/science.293.5536.1786",
    doi = "10.1126/science.293.5536.1786",
    openalex = "W2117753850"
}

▪ Abstract Contributions from the field of population biology hold promise for understanding and managing invasiveness; invasive species also offer excellent opportunities to study basic processes in population biology. Life history studies and demographic models may be valuable for examining the introduction of invasive species and identifying life history stages where management will be most effective. Evolutionary processes may be key features in determining whether invasive species establish and spread. Studies of genetic diversity and evolutionary changes should be useful for understanding the potential for colonization and establishment, geographic patterns of invasion and range expansion, lag times, and the potential for evolutionary responses to novel environments, including management practices. The consequences of biological invasions permit study of basic evolutionary processes, as invaders often evolve rapidly in response to novel abiotic and biotic conditions, and native species evolve in response to the invasion.

@article{doi101146annurevecolsys32081501114037,
    author = "Sakai, Ann K. and Allendorf, Fred W. and Holt, Jodie S. and Lodge, David M. and Molofsky, Jane and With, Kimberly A. and Baughman, Syndallas and Cabin, Robert J. and Cohen, Joel E. and Ellstrand, Norman C. and McCauley, David E. and O’Neil, Pamela and Parker, Ingrid M. and Thompson, John N. and Weller, Stephen G.",
    title = "The Population Biology of Invasive Species",
    year = "2001",
    journal = "Annual Review of Ecology and Systematics",
    abstract = "▪ Abstract Contributions from the field of population biology hold promise for understanding and managing invasiveness; invasive species also offer excellent opportunities to study basic processes in population biology. Life history studies and demographic models may be valuable for examining the introduction of invasive species and identifying life history stages where management will be most effective. Evolutionary processes may be key features in determining whether invasive species establish and spread. Studies of genetic diversity and evolutionary changes should be useful for understanding the potential for colonization and establishment, geographic patterns of invasion and range expansion, lag times, and the potential for evolutionary responses to novel environments, including management practices. The consequences of biological invasions permit study of basic evolutionary processes, as invaders often evolve rapidly in response to novel abiotic and biotic conditions, and native species evolve in response to the invasion.",
    url = "https://doi.org/10.1146/annurev.ecolsys.32.081501.114037",
    doi = "10.1146/annurev.ecolsys.32.081501.114037",
    openalex = "W2112388438",
    references = "doi1010079781489972149, doi1010079789400958517, doi1010160169534794902488, doi101016s0169534701021012, doi101023a1010086329619, doi10103835016000, doi101086282697, doi101126science28754591770, doi101146annurevecolsys27183, doi1015159781400881376, doi1018900012965819990801455tecoci20co2, doi1018901051076120000100689bicegc20co2, doi1023072257385, doi1023072529912, doi105962bhltitle27468, openalexw2169917233"
}

@article{doi101016s0169534702025545,
    author = "Lee, Carol Eunmi",
    title = "Evolutionary genetics of invasive species",
    year = "2002",
    journal = "Trends in Ecology \& Evolution",
    url = "https://doi.org/10.1016/s0169-5347(02)02554-5",
    doi = "10.1016/s0169-5347(02)02554-5",
    openalex = "W2155928419",
    references = "doi101038sjhdy6886170, doi101073pnas97137043, doi101073pnas97137051, doi101111j155856461951tb02788x, doi101126science2925517673, doi1016410006356820000500053eaecon23co2, doi1023072261425, doi1023072265769, doi1023072412809, doi104159harvard9780674865327, openalexw1554403518, openalexw1584633894"
}

@book{doi102307jctvjsf433,
    author = "Gould, Stephen Jay",
    title = "The Structure of Evolutionary Theory",
    year = "2002",
    booktitle = "Harvard University Press eBooks",
    url = "https://doi.org/10.2307/j.ctvjsf433",
    doi = "10.2307/j.ctvjsf433",
    openalex = "W4300925890"
}

With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.

@article{doi101093bib52150,
    author = "Kumar, Sudhir",
    title = "MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment",
    year = "2004",
    journal = "Briefings in Bioinformatics",
    abstract = "With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.",
    url = "https://doi.org/10.1093/bib/5.2.150",
    doi = "10.1093/bib/5.2.150",
    openalex = "W2146396346",
    references = "doi101007bf01731581, doi101007bf02407308, doi101016b9781483232119500097, doi101093bioinformatics17121244, doi101093genetics1233585, doi101093nar22224673, doi101093nar25173389, doi101093oso97801951358480010001, doi101093oxfordjournalsmolbeva040023, doi101093oxfordjournalsmolbeva040259, doi101093oxfordjournalsmolbeva040343, doi101093oxfordjournalsmolbeva040410, doi101093oxfordjournalsmolbeva040454, doi101093oxfordjournalsmolbeva040771, doi101111j155856461985tb00420x, doi1023072408678, doi1023072412074, doi105860choice392183, openalexw2032279931, openalexw3217097258"
}

(1) We show that ML under the assumption of molecular clock is still computationally intractable (NP-hard). (2) We show that not only is it computationally intractable to find the exact ML tree, even approximating the logarithm of the ML for any multiplicative factor smaller than 1.00175 is computationally intractable. (3) We develop an algorithm for approximating log-likelihood under the condition that the input sequences are sparse. It employs any approximation algorithm for parsimony, and asymptotically achieves the same approximation ratio. We note that ML reconstruction for sparse inputs is still hard under this condition, and furthermore many real datasets satisfy it.

@article{doi101093bioinformaticsbti1027,
    author = "Chor, Benny and Tuller, Tamir",
    title = "Maximum likelihood of evolutionary trees: hardness and approximation",
    year = "2005",
    journal = "Computer applications in the biosciences",
    abstract = "(1) We show that ML under the assumption of molecular clock is still computationally intractable (NP-hard). (2) We show that not only is it computationally intractable to find the exact ML tree, even approximating the logarithm of the ML for any multiplicative factor smaller than 1.00175 is computationally intractable. (3) We develop an algorithm for approximating log-likelihood under the condition that the input sequences are sparse. It employs any approximation algorithm for parsimony, and asymptotically achieves the same approximation ratio. We note that ML reconstruction for sparse inputs is still hard under this condition, and furthermore many real datasets satisfy it.",
    url = "https://doi.org/10.1093/bioinformatics/bti1027",
    doi = "10.1093/bioinformatics/bti1027",
    openalex = "W2101464940"
}

The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.

@article{doi101093molbevmsj030,
    author = "Huson, Daniel H. and Bryant, David",
    title = "Application of Phylogenetic Networks in Evolutionary Studies",
    year = "2005",
    journal = "Molecular Biology and Evolution",
    abstract = "The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.",
    url = "https://doi.org/10.1093/molbev/msj030",
    doi = "10.1093/molbev/msj030",
    openalex = "W2055298722",
    references = "doi101016s0169534700020267, doi101038nrg929, doi10108010635150390235520, doi101093bioinformaticsbtg180, doi101093molbevmsi111, doi101093sysbio463523, doi101111j155856461985tb00420x"
}

Abstract Recent studies have documented rates of evolution of ecologically important phenotypes sufficiently fast that they have the potential to impact the outcome of ecological interactions while they are underway. Observations of this type go against accepted wisdom that ecological and evolutionary dynamics occur at very different time scales. While some authors have evaluated the rapidity of a measured evolutionary rate by comparing it to the overall distribution of measured evolutionary rates, we believe that ecologists are mainly interested in rapid evolution because of its potential to impinge on ecological processes. We therefore propose that rapid evolution be defined as a genetic change occurring rapidly enough to have a measurable impact on simultaneous ecological change. Using this definition we propose a framework for decomposing rates of ecological change into components driven by simultaneous evolutionary change and by change in a non‐evolutionary factor (e.g. density dependent population dynamics, abiotic environmental change). Evolution is judged to be rapid in this ecological context if its contribution to ecological change is large relative to the contribution of other factors. We provide a worked example of this approach based on a theoretical predator–prey interaction [Abrams, P. & Matsuda, H. (1997). Evolution, 51, 1740], and find that in this system the impact of prey evolution on predator per capita growth rate is 63% that of internal ecological dynamics. We then propose analytical methods for measuring these contributions in field situations, and apply them to two long‐term data sets for which suitable ecological and evolutionary data exist. For both data sets relatively high rates of evolutionary change have been found when measured as character change in standard deviations per generation (haldanes). For Darwin's finches evolving in response to fluctuating rainfall [Grant, P.R. & Grant, B.R. (2002). Science, 296, 707], we estimate that evolutionary change has been more rapid than ecological change by a factor of 2.2. For a population of freshwater copepods whose life history evolves in response to fluctuating fish predation [Hairston, N.G. Jr & Dillon, T.A. (1990). Evolution, 44, 1796], we find that evolutionary change has been about one quarter the rate of ecological change – less than in the finch example, but nevertheless substantial. These analyses support the view that in order to understand temporal dynamics in ecological processes it is critical to consider the extent to which the attributes of the system under investigation are simultaneously changing as a result of rapid evolution.

@article{doi101111j14610248200500812x,
    author = "Hairston, Nelson G. and Ellner, Stephen P. and Geber, Monica A. and Yoshida, Takehito and Fox, Jennifer",
    title = "Rapid evolution and the convergence of ecological and evolutionary time",
    year = "2005",
    journal = "Ecology Letters",
    abstract = "Abstract Recent studies have documented rates of evolution of ecologically important phenotypes sufficiently fast that they have the potential to impact the outcome of ecological interactions while they are underway. Observations of this type go against accepted wisdom that ecological and evolutionary dynamics occur at very different time scales. While some authors have evaluated the rapidity of a measured evolutionary rate by comparing it to the overall distribution of measured evolutionary rates, we believe that ecologists are mainly interested in rapid evolution because of its potential to impinge on ecological processes. We therefore propose that rapid evolution be defined as a genetic change occurring rapidly enough to have a measurable impact on simultaneous ecological change. Using this definition we propose a framework for decomposing rates of ecological change into components driven by simultaneous evolutionary change and by change in a non‐evolutionary factor (e.g. density dependent population dynamics, abiotic environmental change). Evolution is judged to be rapid in this ecological context if its contribution to ecological change is large relative to the contribution of other factors. We provide a worked example of this approach based on a theoretical predator–prey interaction [Abrams, P. \& Matsuda, H. (1997). Evolution, 51, 1740], and find that in this system the impact of prey evolution on predator per capita growth rate is 63\% that of internal ecological dynamics. We then propose analytical methods for measuring these contributions in field situations, and apply them to two long‐term data sets for which suitable ecological and evolutionary data exist. For both data sets relatively high rates of evolutionary change have been found when measured as character change in standard deviations per generation (haldanes). For Darwin's finches evolving in response to fluctuating rainfall [Grant, P.R. \& Grant, B.R. (2002). Science, 296, 707], we estimate that evolutionary change has been more rapid than ecological change by a factor of 2.2. For a population of freshwater copepods whose life history evolves in response to fluctuating fish predation [Hairston, N.G. Jr \& Dillon, T.A. (1990). Evolution, 44, 1796], we find that evolutionary change has been about one quarter the rate of ecological change – less than in the finch example, but nevertheless substantial. These analyses support the view that in order to understand temporal dynamics in ecological processes it is critical to consider the extent to which the attributes of the system under investigation are simultaneously changing as a result of rapid evolution.",
    url = "https://doi.org/10.1111/j.1461-0248.2005.00812.x",
    doi = "10.1111/j.1461-0248.2005.00812.x",
    openalex = "W1541870771",
    references = "doi10100797894010058529, doi1010160169534787900280, doi101023a1013311015886, doi101038nature01767, doi101093aibsbulletin2214b, doi101126science1070315, doi101126science2224620159, doi101126science2925517673, doi1015159781400885695, doi101890030788, doi1023071435536, doi1023071445906, doi1023074785, doi105860choice306153"
}

▪ Abstract Niche conservatism is the tendency of species to retain ancestral ecological characteristics. In the recent literature, a debate has emerged as to whether niches are conserved. We suggest that simply testing whether niches are conserved is not by itself particularly helpful or interesting and that a more useful focus is on the patterns that niche conservatism may (or may not) create. We focus specifically on how niche conservatism in climatic tolerances may limit geographic range expansion and how this one type of niche conservatism may be important in (a) allopatric speciation, (b) historical biogeography, (c) patterns of species richness, (d) community structure, (e) the spread of invasive, human-introduced species, (f) responses of species to global climate change, and (g) human history, from 13,000 years ago to the present. We describe how these effects of niche conservatism can be examined with new tools for ecological niche modeling.

@article{doi101146annurevecolsys36102803095431,
    author = "Wiens, John J. and Graham, Catherine H.",
    title = "Niche Conservatism: Integrating Evolution, Ecology, and Conservation Biology",
    year = "2005",
    journal = "Annual Review of Ecology Evolution and Systematics",
    abstract = "▪ Abstract Niche conservatism is the tendency of species to retain ancestral ecological characteristics. In the recent literature, a debate has emerged as to whether niches are conserved. We suggest that simply testing whether niches are conserved is not by itself particularly helpful or interesting and that a more useful focus is on the patterns that niche conservatism may (or may not) create. We focus specifically on how niche conservatism in climatic tolerances may limit geographic range expansion and how this one type of niche conservatism may be important in (a) allopatric speciation, (b) historical biogeography, (c) patterns of species richness, (d) community structure, (e) the spread of invasive, human-introduced species, (f) responses of species to global climate change, and (g) human history, from 13,000 years ago to the present. We describe how these effects of niche conservatism can be examined with new tools for ecological niche modeling.",
    url = "https://doi.org/10.1146/annurev.ecolsys.36.102803.095431",
    doi = "10.1146/annurev.ecolsys.36.102803.095431",
    openalex = "W2113375225",
    references = "doi101016jtree200409011, doi101016s0169534702000447, doi101017cbo9780511623387, doi101093oso97801985491780010001, doi101111j001438202004tb00461x, doi101111j109583122001tb01368x, doi101126science27953592115, doi101126science28554311265, doi101126science7701342, doi101146annurevecolsys33010802150448, doi101146annurevecolsys34012103144032, doi1023071444927, doi1023071933500, doi1023073515466, doi105860choice332720, openalexw2037503630, openalexw2273605253"
}

Ecological changes in the phenology and distribution of plants and animals are occurring in all well-studied marine, freshwater, and terrestrial groups. These observed changes are heavily biased in the directions predicted from global warming and have been linked to local or regional climate change through correlations between climate and biological variation, field and laboratory experiments, and physiological research. Range-restricted species, particularly polar and mountaintop species, show severe range contractions and have been the first groups in which entire species have gone extinct due to recent climate change. Tropical coral reefs and amphibians have been most negatively affected. Predator-prey and plant-insect interactions have been disrupted when interacting species have responded differently to warming. Evolutionary adaptations to warmer conditions have occurred in the interiors of species' ranges, and resource use and dispersal have evolved rapidly at expanding range margins. Observed genetic shifts modulate local effects of climate change, but there is little evidence that they will mitigate negative effects at the species level.

@article{doi101146annurevecolsys37091305110100,
    author = "Parmesan, Camille",
    title = "Ecological and Evolutionary Responses to Recent Climate Change",
    year = "2006",
    journal = "Annual Review of Ecology Evolution and Systematics",
    abstract = "Ecological changes in the phenology and distribution of plants and animals are occurring in all well-studied marine, freshwater, and terrestrial groups. These observed changes are heavily biased in the directions predicted from global warming and have been linked to local or regional climate change through correlations between climate and biological variation, field and laboratory experiments, and physiological research. Range-restricted species, particularly polar and mountaintop species, show severe range contractions and have been the first groups in which entire species have gone extinct due to recent climate change. Tropical coral reefs and amphibians have been most negatively affected. Predator-prey and plant-insect interactions have been disrupted when interacting species have responded differently to warming. Evolutionary adaptations to warmer conditions have occurred in the interiors of species' ranges, and resource use and dispersal have evolved rapidly at expanding range margins. Observed genetic shifts modulate local effects of climate change, but there is little evidence that they will mitigate negative effects at the species level.",
    url = "https://doi.org/10.1146/annurev.ecolsys.37.091305.110100",
    doi = "10.1146/annurev.ecolsys.37.091305.110100",
    openalex = "W2135858501",
    references = "doi1010160169534794902488, doi10103835079180, doi101038369448a0, doi101038382146a0, doi101038386698a0, doi101038nature01286, doi101038nature04095, doi101038nature04246, doi101071mf99078, doi101093aesa492190, doi101126science28954872068, doi101126science2925517673, doi1023071939337, doi1023071940431, doi105860choice301495, openalexw1500291103, openalexw2151235472"
}

Making Sense of Evolution explores contemporary evolutionary biology, focusing on the elements of theories-selection, adaptation, and species-that are complex and open to multiple possible interpretations, many of which are incompatible with one another and with other accepted practices in the discipline. Particular experimental methods, for example, may demand one understanding of selection, while the application of the same concept to another area of evolutionary biology could necessitate a very different definition. Spotlighting these conceptual difficulties and presenting alternate theoretical interpretations that alleviate this incompatibility, Massimo Pigliucci and Jonathan Kaplan intertwine scientific and philosophical analysis to produce a coherent picture of evolutionary biology. Innovative and controversial, Making Sense of Evolution encourages further development of the Modern Synthesis and outlines what might be necessary for the continued refinement of this evolving field.

@book{openalexw1524234678,
    author = "Pigliucci, Massimo and Kaplan, Jonathan Michael",
    title = "Making Sense of Evolution: The Conceptual Foundations of Evolutionary Biology",
    year = "2006",
    abstract = "Making Sense of Evolution explores contemporary evolutionary biology, focusing on the elements of theories-selection, adaptation, and species-that are complex and open to multiple possible interpretations, many of which are incompatible with one another and with other accepted practices in the discipline. Particular experimental methods, for example, may demand one understanding of selection, while the application of the same concept to another area of evolutionary biology could necessitate a very different definition. Spotlighting these conceptual difficulties and presenting alternate theoretical interpretations that alleviate this incompatibility, Massimo Pigliucci and Jonathan Kaplan intertwine scientific and philosophical analysis to produce a coherent picture of evolutionary biology. Innovative and controversial, Making Sense of Evolution encourages further development of the Modern Synthesis and outlines what might be necessary for the continued refinement of this evolving field.",
    url = "https://openalex.org/W1524234678",
    openalex = "W1524234678"
}

We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).

@article{doi101093molbevmsm092,
    author = "Tamura, Koichiro and Dudley, Joel T. and Nei, M and Kumar, Sudhir",
    title = "MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) Software Version 4.0",
    year = "2007",
    journal = "Molecular Biology and Evolution",
    abstract = "We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).",
    url = "https://doi.org/10.1093/molbev/msm092",
    doi = "10.1093/molbev/msm092",
    openalex = "W2125121305",
    references = "doi101007bf01733904, doi101073pnas0404206101, doi101093bib52150, doi101093bioinformaticsbtm239, doi101093nar22224673, doi101093oxfordjournalsmolbeva025625, doi101093oxfordjournalsmolbeva040023, doi101093oxfordjournalsmolbeva040454, openalexw1588193375"
}

Summary Natural and human mediated perturbations present challenges to the fate of populations but fuel contemporary evolution (evolution over humanly observable time‐scales). Here we ask if such evolution is sufficient to make the difference between population extinction and persistence. To answer this question requires a shift from the usual focus on trait evolution to the emergent ‘eco‐evolutionary’ dynamics that arise through interactions of evolution, its fitness consequences and population abundance. By combining theory, models and insights from empirical studies of contemporary evolution, we provide an assessment of three contexts: persistence of populations in situ, persistence of colonising populations, and persistence under gene flow and in metapopulations. Contemporary evolution can likely rescue some, but not all, populations facing environmental change. Populations may fail partly because of the demographic cost of selection. Contemporary evolution that initiates positive population growth, such as selective founding processes, may create a ‘persistence vortex’ that overcomes the problems of small populations. Complex, even shifting, relationships between gene flow and adaptation may aid the persistence of subpopulations as well as the persistence and expansion of metapopulations. An eco‐evolutionary perspective suggests that we expand our focus beyond the acute problems of threatened populations and growing invasions, to consider how contemporary evolutionary mechanics contribute to such problems in the first place or affect their resolution.

@article{doi101111j13652435200701278x,
    author = "Kinnison, Michael T. and Hairston, Nelson G.",
    title = "Eco‐evolutionary conservation biology: contemporary evolution and the dynamics of persistence",
    year = "2007",
    journal = "Functional Ecology",
    abstract = "Summary Natural and human mediated perturbations present challenges to the fate of populations but fuel contemporary evolution (evolution over humanly observable time‐scales). Here we ask if such evolution is sufficient to make the difference between population extinction and persistence. To answer this question requires a shift from the usual focus on trait evolution to the emergent ‘eco‐evolutionary’ dynamics that arise through interactions of evolution, its fitness consequences and population abundance. By combining theory, models and insights from empirical studies of contemporary evolution, we provide an assessment of three contexts: persistence of populations in situ, persistence of colonising populations, and persistence under gene flow and in metapopulations. Contemporary evolution can likely rescue some, but not all, populations facing environmental change. Populations may fail partly because of the demographic cost of selection. Contemporary evolution that initiates positive population growth, such as selective founding processes, may create a ‘persistence vortex’ that overcomes the problems of small populations. Complex, even shifting, relationships between gene flow and adaptation may aid the persistence of subpopulations as well as the persistence and expansion of metapopulations. An eco‐evolutionary perspective suggests that we expand our focus beyond the acute problems of threatened populations and growing invasions, to consider how contemporary evolutionary mechanics contribute to such problems in the first place or affect their resolution.",
    url = "https://doi.org/10.1111/j.1365-2435.2007.01278.x",
    doi = "10.1111/j.1365-2435.2007.01278.x",
    openalex = "W2118992195",
    references = "doi101038nature02121, doi101093oso97801985406630010001, doi101098rstb19900188, doi101126science2925517673, doi101126science3420403, doi101126science3576198, doi1018901051076120000100689bicegc20co2, doi1023072259756, doi1023074549, doi105962bhltitle27468, openalexw2037503630"
}

BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.

@article{doi101186147121487214,
    author = "Drummond, Alexei J. and Rambaut, Andrew",
    title = "BEAST: Bayesian evolutionary analysis by sampling trees",
    year = "2007",
    journal = "BMC Evolutionary Biology",
    abstract = "BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.",
    url = "https://doi.org/10.1186/1471-2148-7-214",
    doi = "10.1186/1471-2148-7-214",
    openalex = "W2110835349",
    references = "doi101007bf00160154, doi101007bf02101694, doi101007bf02101990, doi101016b9781483227344500176, doi101016s0169534703002167, doi10106311699114, doi101073pnas6341088, doi10108010635150290102456, doi101093bioinformatics178754, doi101093biomet57197, doi101093molbevmsi103, doi101093oxfordjournalsmolbeva003974, doi101093oxfordjournalsmolbeva025892, doi101093oxfordjournalsmolbeva040153, doi101126science1101074, doi101371journalpbio0040088, rambaut1998estimating"
}

Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer–algae chemostats; alewife–zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife–zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.

@article{doi101098rstb20090012,
    author = "Post, David M. and Palkovacs, Eric P.",
    title = "Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play",
    year = "2009",
    journal = "Philosophical Transactions of the Royal Society B Biological Sciences",
    abstract = "Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer–algae chemostats; alewife–zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife–zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.",
    url = "https://doi.org/10.1098/rstb.2009.0012",
    doi = "10.1098/rstb.2009.0012",
    openalex = "W2113720451",
    references = "doi101007978146124018114, doi101016b0122268652001759, doi101016s016953470102198x, doi101086282400, doi101111j13652435200701275x, doi101111j13652435200701278x, doi101111j13652435200701289x, doi101126science150369228, doi101146annurevecolsys31179, doi1015159781400847266, doi1023071312990, doi1023073545850, doi107208chicago97802261186970010001, openalexw1973833797, openalexw2040817479"
}

Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about ‘eco-evolutionary dynamics’ brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.

@article{doi101098rstb20090027,
    author = "Pelletier, Fanie and Garant, Dany and Hendry, Andrew P.",
    title = "Eco-evolutionary dynamics",
    year = "2009",
    journal = "Philosophical Transactions of the Royal Society B Biological Sciences",
    abstract = "Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about ‘eco-evolutionary dynamics’ brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.",
    url = "https://doi.org/10.1098/rstb.2009.0027",
    doi = "10.1098/rstb.2009.0027",
    openalex = "W4241722143",
    references = "doi101098rstb20090012, doi102307177366"
}

The increasing availability of phylogenetic data, computing power and informatics tools has facilitated a rapid expansion of studies that apply phylogenetic data and methods to community ecology. Several key areas are reviewed in which phylogenetic information helps to resolve long-standing controversies in community ecology, challenges previous assumptions, and opens new areas of investigation. In particular, studies in phylogenetic community ecology have helped to reveal the multitude of processes driving community assembly and have demonstrated the importance of evolution in the assembly process. Phylogenetic approaches have also increased understanding of the consequences of community interactions for speciation, adaptation and extinction. Finally, phylogenetic community structure and composition holds promise for predicting ecosystem processes and impacts of global change. Major challenges to advancing these areas remain. In particular, determining the extent to which ecologically relevant traits are phylogenetically conserved or convergent, and over what temporal scale, is critical to understanding the causes of community phylogenetic structure and its evolutionary and ecosystem consequences. Harnessing phylogenetic information to understand and forecast changes in diversity and dynamics of communities is a critical step in managing and restoring the Earth's biota in a time of rapid global change.

@article{doi101111j14610248200901314x,
    author = "Cavender‐Bares, Jeannine and Kozak, Kenneth H. and Fine, Paul V. A. and Kembel, Steven W.",
    title = "The merging of community ecology and phylogenetic biology",
    year = "2009",
    journal = "Ecology Letters",
    abstract = "The increasing availability of phylogenetic data, computing power and informatics tools has facilitated a rapid expansion of studies that apply phylogenetic data and methods to community ecology. Several key areas are reviewed in which phylogenetic information helps to resolve long-standing controversies in community ecology, challenges previous assumptions, and opens new areas of investigation. In particular, studies in phylogenetic community ecology have helped to reveal the multitude of processes driving community assembly and have demonstrated the importance of evolution in the assembly process. Phylogenetic approaches have also increased understanding of the consequences of community interactions for speciation, adaptation and extinction. Finally, phylogenetic community structure and composition holds promise for predicting ecosystem processes and impacts of global change. Major challenges to advancing these areas remain. In particular, determining the extent to which ecologically relevant traits are phylogenetically conserved or convergent, and over what temporal scale, is critical to understanding the causes of community phylogenetic structure and its evolutionary and ecosystem consequences. Harnessing phylogenetic information to understand and forecast changes in diversity and dynamics of communities is a critical step in managing and restoring the Earth's biota in a time of rapid global change.",
    url = "https://doi.org/10.1111/j.1461-0248.2009.01314.x",
    doi = "10.1111/j.1461-0248.2009.01314.x",
    openalex = "W2102384105",
    references = "doi1010160006320792912013, doi101016jppees200710001, doi101016jtree200409011, doi101038nature02403, doi10108010635150802302427, doi101086282505, doi101086282687, doi101093aibsbulletin2214b, doi101098rspb20080630, doi101111j14610248200701020x, doi101111j155856461964tb01674x, doi101111j15585646200800317x, doi101126science2304728895, doi101126science2354785167, doi101126science27953592115, doi101146annurevecolsys311343, doi101146annurevecolsys33010802150448, doi1015159781400881376, doi101722611310, doi1023071435536, doi1023071446122, doi1023072259756, doi1023073071998, doi1023073544421, doi1023074549, doi105860choice432194, doi105962bhltitle56234, doi107208chicago97802261186970010001, openalexw2273605253"
}

Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework containing among others evo-devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that--like its predecessor--will probably take decades to complete.

@article{doi101111j17496632200904578x,
    author = "Pigliucci, Massimo",
    title = "An Extended Synthesis for Evolutionary Biology",
    year = "2009",
    journal = "Annals of the New York Academy of Sciences",
    abstract = "Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework containing among others evo-devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that--like its predecessor--will probably take decades to complete.",
    url = "https://doi.org/10.1111/j.1749-6632.2009.04578.x",
    doi = "10.1111/j.1749-6632.2009.04578.x",
    openalex = "W2007542899",
    references = "doi101017cbo9780511498541, doi101017s0080456800012163, doi10106313050879, doi101093aibsbulletin2214b, doi101093oso97801951223430010001, doi101111j13652435200701283x, doi1015159780691183978018, doi101722611310, doi1023072217783, doi105860choice422215, doi107312steb94536, openalexw1524234678, openalexw3135630760"
}

Today's scientists are facing the enormous challenge of predicting how climate change will affect species distributions and species assemblages. To do so, ecologists are widely using phenomenological models of species distributions that mainly rely on the concept of species niche and generally ignore species' demography, species' adaptive potential, and biotic interactions. This review examines the potential role of the emerging synthetic discipline of evolutionary community ecology in improving our understanding of how climate change will alter future distribution of biodiversity. We review theoretical and empirical advances about the role of niche evolution, interspecific interactions, and their interplay in altering species geographic ranges and community assembly. We discuss potential ways to integrate complex feedbacks between ecology and evolution in ecological forecasting. We also point at a number of caveats in our understanding of the eco-evolutionary consequences of climate change and highlight several challenges for future research.

@article{doi101146annurevecolsys102209144628,
    author = "Lavergne, Sébastien and Mouquet, Nicolas and Thuiller, Wilfried and Ronce, Ophélie",
    title = "Biodiversity and Climate Change: Integrating Evolutionary and Ecological Responses of Species and Communities",
    year = "2010",
    journal = "Annual Review of Ecology Evolution and Systematics",
    abstract = "Today's scientists are facing the enormous challenge of predicting how climate change will affect species distributions and species assemblages. To do so, ecologists are widely using phenomenological models of species distributions that mainly rely on the concept of species niche and generally ignore species' demography, species' adaptive potential, and biotic interactions. This review examines the potential role of the emerging synthetic discipline of evolutionary community ecology in improving our understanding of how climate change will alter future distribution of biodiversity. We review theoretical and empirical advances about the role of niche evolution, interspecific interactions, and their interplay in altering species geographic ranges and community assembly. We discuss potential ways to integrate complex feedbacks between ecology and evolution in ecological forecasting. We also point at a number of caveats in our understanding of the eco-evolutionary consequences of climate change and highlight several challenges for future research.",
    url = "https://doi.org/10.1146/annurev-ecolsys-102209-144628",
    doi = "10.1146/annurev-ecolsys-102209-144628",
    openalex = "W2170175048",
    references = "doi101038nature01286, doi10108010635150802302427, doi101093oso97801985052350010001, doi101098rstb20090012, doi101111j13652435200701275x, doi101111j13652435200701278x, doi101111j13652435200701289x, doi101111j14610248200500792x, doi101111j14610248200500812x, doi101146annurevecolsys110308120159, doi101146annurevecolsys110308120317, doi101146annurevecolsys311343, doi101146annurevecolsys37091305110100, doi1015159780691206912, doi1023072260079, doi1023073071998, doi105860choice185809, doi105962bhltitle59991, openalexw2045291252, openalexw2151235472"
}

@article{doi101007s1095601193009,
    author = "Nehm, Ross H. and Ha, Minsu and Mayfield, Elijah",
    title = "Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations",
    year = "2011",
    journal = "Journal of Science Education and Technology",
    url = "https://doi.org/10.1007/s10956-011-9300-9",
    doi = "10.1007/s10956-011-9300-9",
    openalex = "W2074360952",
    references = "openalexw1524234678"
}

Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a 'taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408,315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.

@article{doi101038ismej2011139,
    author = "McDonald, Daniel and Price, Morgan N. and Goodrich, Julia K. and Nawrocki, Eric P. and DeSantis, Todd Z. and Probst, Alexander J. and Andersen, Gary L. and Knight, Rob and Hugenholtz, Philip",
    title = "An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea",
    year = "2011",
    journal = "The ISME Journal",
    abstract = "Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a 'taxonomy to tree' approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408,315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75\% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.",
    url = "https://doi.org/10.1038/ismej.2011.139",
    doi = "10.1038/ismej.2011.139",
    openalex = "W2154026962",
    references = "doi101371journalpone0009490, doi1073260003481911154487, doi1073260003481911253913"
}

@article{doi101038nature09670,
    author = "Hoffmann, Ary A. and Sgrò, Carla M.",
    title = "Climate change and evolutionary adaptation",
    year = "2011",
    journal = "Nature",
    url = "https://doi.org/10.1038/nature09670",
    doi = "10.1038/nature09670",
    openalex = "W2008951609",
    references = "doi101038nature01286, doi101098rspb20081957, doi101111j1365294x200703428x, doi101111j14610248200801277x, doi101126science1070315, doi101146annurevecolsys110308120159, doi101146annurevecolsys271237"
}

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.

@article{doi101093molbevmsr121,
    author = "Tamura, Koichiro and Peterson, Daniel G. and Peterson, Nora and Stecher, Glen and Nei, M and Kumar, Sudhir",
    title = "MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods",
    year = "2011",
    journal = "Molecular Biology and Evolution",
    abstract = "Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.",
    url = "https://doi.org/10.1093/molbev/msr121",
    doi = "10.1093/molbev/msr121",
    openalex = "W2132632499",
    references = "doi101007bf01734359, doi101007bf02101694, doi10108010635150390235520, doi10108010635150490522304, doi101093bioinformatics149817, doi101093bioinformaticsbtl446, doi101093biomet762297, doi101093oso97801951358480010001, doi101093oxfordjournalsmolbeva040023, doi101093oxfordjournalsmolbeva040454, doi101093sysbiosyq010, doi101111j155856461985tb00420x, doi101186147121055113, openalexw3217097258"
}

The effect of ecological change on evolution has long been a focus of scientific research. The reverse--how evolutionary dynamics affect ecological traits--has only recently captured our attention, however, with the realization that evolution can occur over ecological time scales. This newly highlighted causal direction and the implied feedback loop--eco-evolutionary dynamics--is invigorating both ecologists and evolutionists and blurring the distinction between them. Despite some recent relevant studies, the importance of the evolution-to-ecology pathway across systems is still unknown. Only an extensive research effort involving multiple experimental approaches-particularly long-term field experiments--over a variety of ecological communities will provide the answer.

@article{doi101126science1193954,
    author = "Schoener, Thomas W.",
    title = "The Newest Synthesis: Understanding the Interplay of Evolutionary and Ecological Dynamics",
    year = "2011",
    journal = "Science",
    abstract = "The effect of ecological change on evolution has long been a focus of scientific research. The reverse--how evolutionary dynamics affect ecological traits--has only recently captured our attention, however, with the realization that evolution can occur over ecological time scales. This newly highlighted causal direction and the implied feedback loop--eco-evolutionary dynamics--is invigorating both ecologists and evolutionists and blurring the distinction between them. Despite some recent relevant studies, the importance of the evolution-to-ecology pathway across systems is still unknown. Only an extensive research effort involving multiple experimental approaches-particularly long-term field experiments--over a variety of ecological communities will provide the answer.",
    url = "https://doi.org/10.1126/science.1193954",
    doi = "10.1126/science.1193954",
    openalex = "W2083310645",
    references = "doi101007978940100585212, doi101016s0169534798013780, doi101038nature02430, doi101038nrg1877, doi101086282160, doi101086510633, doi101111j13652435200701275x, doi101111j13652435200701278x, doi101111j13652435200701289x, doi101111j14610248200500812x, doi101111j14610248200801179x, doi101111j155856461983tb00236x, doi101111j155856461999tb04550x, doi101126science2224620159, doi101146annurevecolsys31179, doi1023072408842, doi105860choice455580"
}

Fifty years ago, Ernst Mayr published a hugely influential paper on the nature of causation in biology, in which he distinguished between proximate and ultimate causes. Mayr equated proximate causation with immediate factors (for example, physiology) and ultimate causation with evolutionary explanations (for example, natural selection). He argued that proximate and ultimate causes addressed different questions and were not alternatives. Mayr's account of causation remains widely accepted today, with both positive and negative ramifications. Several current debates in biology (for example, over evolution and development, niche construction, cooperation, and the evolution of language) are linked by a common axis of acceptance/rejection of Mayr's model of causation. We argue that Mayr's formulation has acted to stabilize the dominant evolutionary paradigm against change but may now hamper progress in the biological sciences.

@article{doi101126science1210879,
    author = "Laland, Kevin N. and Sterelny, Kim and Odling‐Smee, John and Hoppitt, William and Uller, Tobias",
    title = "Cause and Effect in Biology Revisited: Is Mayr’s Proximate-Ultimate Dichotomy Still Useful?",
    year = "2011",
    journal = "Science",
    abstract = "Fifty years ago, Ernst Mayr published a hugely influential paper on the nature of causation in biology, in which he distinguished between proximate and ultimate causes. Mayr equated proximate causation with immediate factors (for example, physiology) and ultimate causation with evolutionary explanations (for example, natural selection). He argued that proximate and ultimate causes addressed different questions and were not alternatives. Mayr's account of causation remains widely accepted today, with both positive and negative ramifications. Several current debates in biology (for example, over evolution and development, niche construction, cooperation, and the evolution of language) are linked by a common axis of acceptance/rejection of Mayr's model of causation. We argue that Mayr's formulation has acted to stabilize the dominant evolutionary paradigm against change but may now hamper progress in the biological sciences.",
    url = "https://doi.org/10.1126/science.1210879",
    doi = "10.1126/science.1210879",
    openalex = "W1964687630",
    references = "doi101016jevolhumbehav201008001, doi101017cbo9781139164856, doi101017s0140525x0999094x, doi101098rstb20090012, openalexw2591687711"
}

http://www.megasoftware.net/.

@article{doi101093bioinformaticsbts507,
    author = "Kumar, Sudhir and Stecher, Glen and Peterson, Daniel S. and Tamura, Koichiro",
    title = "MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis",
    year = "2012",
    journal = "Bioinformatics",
    abstract = "http://www.megasoftware.net/.",
    url = "https://doi.org/10.1093/bioinformatics/bts507",
    doi = "10.1093/bioinformatics/bts507",
    openalex = "W2121552166"
}

MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/.

@article{doi101093nargkr1293,
    author = "Wang, Yupeng and Tang, Haibao and DeBarry, Jeremy D. and Tan, Xu and Li, Jun and Wang, Xuewen and Lee, Taeyoung and Jin, H. and Marler, Barry S. and Guo, Hui and Kissinger, Jessica C. and Paterson, A. H.",
    title = "MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity",
    year = "2012",
    journal = "Nucleic Acids Research",
    abstract = "MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/.",
    url = "https://doi.org/10.1093/nar/gkr1293",
    doi = "10.1093/nar/gkr1293",
    openalex = "W2020134788",
    references = "doi101006jmbi19909999, doi101038nature06148, doi101038nature09916, doi101093oxfordjournalsmolbeva040410, doi101093sysbiosyq010, doi101146annurevgenet341401"
}

When Charles Darwin formulated the central principles of evolutionary biology in the Origin of Species in 1859 and the architects of the Modern Synthesis integrated these principles with population genetics almost a century later, the principal if not the sole objects of evolutionary biology were multicellular eukaryotes, primarily animals and plants. Before the advent of efficient gene sequencing, all attempts to extend evolutionary studies to bacteria have been futile. Sequencing of the rRNA genes in thousands of microbes allowed the construction of the three- domain "ribosomal Tree of Life" that was widely thought to have resolved the evolutionary relationships between the cellular life forms. However, subsequent massive sequencing of numerous, complete microbial genomes revealed novel evolutionary phenomena, the most fundamental of these being: (1) pervasive horizontal gene transfer (HGT), in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment) of the Tree of Life concept, (2) Lamarckian-type inheritance that appears to be critical for antivirus defense and other forms of adaptation in prokaryotes, and (3) evolution of evolvability, i.e., dedicated mechanisms for evolution such as vehicles for HGT and stress-induced mutagenesis systems. In the non-cellular part of the microbial world, phylogenomics and metagenomics of viruses and related selfish genetic elements revealed enormous genetic and molecular diversity and extremely high abundance of viruses that come across as the dominant biological entities on earth. Furthermore, the perennial arms race between viruses and their hosts is one of the defining factors of evolution. Thus, microbial phylogenomics adds new dimensions to the fundamental picture of evolution even as the principle of descent with modification discovered by Darwin and the laws of population genetics remain at the core of evolutionary biology.

@article{doi103389fcimb201200119,
    author = "Koonin, Eugene V. and Wolf, Yuri I.",
    title = "Evolution of microbes and viruses: a paradigm shift in evolutionary biology?",
    year = "2012",
    journal = "Frontiers in Cellular and Infection Microbiology",
    abstract = {When Charles Darwin formulated the central principles of evolutionary biology in the Origin of Species in 1859 and the architects of the Modern Synthesis integrated these principles with population genetics almost a century later, the principal if not the sole objects of evolutionary biology were multicellular eukaryotes, primarily animals and plants. Before the advent of efficient gene sequencing, all attempts to extend evolutionary studies to bacteria have been futile. Sequencing of the rRNA genes in thousands of microbes allowed the construction of the three- domain "ribosomal Tree of Life" that was widely thought to have resolved the evolutionary relationships between the cellular life forms. However, subsequent massive sequencing of numerous, complete microbial genomes revealed novel evolutionary phenomena, the most fundamental of these being: (1) pervasive horizontal gene transfer (HGT), in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment) of the Tree of Life concept, (2) Lamarckian-type inheritance that appears to be critical for antivirus defense and other forms of adaptation in prokaryotes, and (3) evolution of evolvability, i.e., dedicated mechanisms for evolution such as vehicles for HGT and stress-induced mutagenesis systems. In the non-cellular part of the microbial world, phylogenomics and metagenomics of viruses and related selfish genetic elements revealed enormous genetic and molecular diversity and extremely high abundance of viruses that come across as the dominant biological entities on earth. Furthermore, the perennial arms race between viruses and their hosts is one of the defining factors of evolution. Thus, microbial phylogenomics adds new dimensions to the fundamental picture of evolution even as the principle of descent with modification discovered by Darwin and the laws of population genetics remain at the core of evolutionary biology.},
    url = "https://doi.org/10.3389/fcimb.2012.00119",
    doi = "10.3389/fcimb.2012.00119",
    openalex = "W2105364540",
    references = "doi101038nrmicro1750, doi10106313050879, doi101073pnas74115088, doi101073pnas87124576, doi101084jem792137, doi101093aibsbulletin2214b, doi101722611310, doi103929ethzb000667478, doi105962bhltitle27468"
}

@article{doi101016janbehav201212031,
    author = "Snell‐Rood, Emilie C.",
    title = "An overview of the evolutionary causes and consequences of behavioural plasticity",
    year = "2013",
    journal = "Animal Behaviour",
    url = "https://doi.org/10.1016/j.anbehav.2012.12.031",
    doi = "10.1016/j.anbehav.2012.12.031",
    openalex = "W1968021996",
    references = "doi101007bf02763457, doi101111j1469185x201000164x, doi101126science2114485887"
}

The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.

@article{doi101093molbevmst197,
    author = "Tamura, Koichiro and Stecher, Glen and Peterson, Daniel S. and Filipski, Alan and Kumar, Sudhir",
    title = "MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0",
    year = "2013",
    journal = "Molecular Biology and Evolution",
    abstract = "The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.",
    url = "https://doi.org/10.1093/molbev/mst197",
    doi = "10.1093/molbev/mst197",
    openalex = "W2152207030",
    references = "doi101038scientificamerican117998, doi101073pnas1213199109, doi101093bib52150, doi101093bioinformatics102189, doi101093bioinformatics17121244, doi101093bioinformaticsbts507, doi101093molbevmsr121, doi101093oso97801951358480010001, doi101126science1211028, openalexw3217097258"
}

@article{doi101016jtree201406005,
    author = "Carlson, Stephanie M. and Cunningham, Curry J. and Westley, Peter A. H.",
    title = "Evolutionary rescue in a changing world",
    year = "2014",
    journal = "Trends in Ecology \& Evolution",
    url = "https://doi.org/10.1016/j.tree.2014.06.005",
    doi = "10.1016/j.tree.2014.06.005",
    openalex = "W2053063524",
    references = "doi10100703064746897, doi101016jtree200709008, doi101016s0169534702024977, doi101016s0169534799016833, doi101038415680a, doi101093aesa383396, doi101098rstb20120085, doi101111eva12137, doi101111j13652435200701278x, doi101126science29355361786, doi1023071935620, doi1023073547011"
}

@article{doi101038nsmb2879,
    author = "Swarts, Daan C. and Makarova, Kira S. and Wang, Yanli and Nakanishi, Kotaro and Ketting, René F. and Koonin, Eugene V. and Patel, Dinshaw J. and van der Oost, John",
    title = "The evolutionary journey of Argonaute proteins",
    year = "2014",
    journal = "Nature Structural \& Molecular Biology",
    url = "https://doi.org/10.1038/nsmb.2879",
    doi = "10.1038/nsmb.2879",
    openalex = "W2068056297",
    references = "doi101093nargkt157"
}

Viruses were defined as one of the two principal types of organisms in the biosphere, namely, as capsid-encoding organisms in contrast to ribosome-encoding organisms, i.e., all cellular life forms. Structurally similar, apparently homologous capsids are present in a huge variety of icosahedral viruses that infect bacteria, archaea, and eukaryotes. These findings prompted the concept of the capsid as the virus "self" that defines the identity of deep, ancient viral lineages. However, several other widespread viral "hallmark genes" encode key components of the viral replication apparatus (such as polymerases and helicases) and combine with different capsid proteins, given the inherently modular character of viral evolution. Furthermore, diverse, widespread, capsidless selfish genetic elements, such as plasmids and various types of transposons, share hallmark genes with viruses. Viruses appear to have evolved from capsidless selfish elements, and vice versa, on multiple occasions during evolution. At the earliest, precellular stage of life's evolution, capsidless genetic parasites most likely emerged first and subsequently gave rise to different classes of viruses. In this review, we develop the concept of a greater virus world which forms an evolutionary network that is held together by shared conserved genes and includes both bona fide capsid-encoding viruses and different classes of capsidless replicons. Theoretical studies indicate that selfish replicons (genetic parasites) inevitably emerge in any sufficiently complex evolving ensemble of replicators. Therefore, the key signature of the greater virus world is not the presence of a capsid but rather genetic, informational parasitism itself, i.e., various degrees of reliance on the information processing systems of the host.

@article{doi101128mmbr0004913,
    author = "Koonin, Eugene V. and Dolja, Valerian V.",
    title = "Virus World as an Evolutionary Network of Viruses and Capsidless Selfish Elements",
    year = "2014",
    journal = "Microbiology and Molecular Biology Reviews",
    abstract = {Viruses were defined as one of the two principal types of organisms in the biosphere, namely, as capsid-encoding organisms in contrast to ribosome-encoding organisms, i.e., all cellular life forms. Structurally similar, apparently homologous capsids are present in a huge variety of icosahedral viruses that infect bacteria, archaea, and eukaryotes. These findings prompted the concept of the capsid as the virus "self" that defines the identity of deep, ancient viral lineages. However, several other widespread viral "hallmark genes" encode key components of the viral replication apparatus (such as polymerases and helicases) and combine with different capsid proteins, given the inherently modular character of viral evolution. Furthermore, diverse, widespread, capsidless selfish genetic elements, such as plasmids and various types of transposons, share hallmark genes with viruses. Viruses appear to have evolved from capsidless selfish elements, and vice versa, on multiple occasions during evolution. At the earliest, precellular stage of life's evolution, capsidless genetic parasites most likely emerged first and subsequently gave rise to different classes of viruses. In this review, we develop the concept of a greater virus world which forms an evolutionary network that is held together by shared conserved genes and includes both bona fide capsid-encoding viruses and different classes of capsidless replicons. Theoretical studies indicate that selfish replicons (genetic parasites) inevitably emerge in any sufficiently complex evolving ensemble of replicators. Therefore, the key signature of the greater virus world is not the presence of a capsid but rather genetic, informational parasitism itself, i.e., various degrees of reliance on the information processing systems of the host.},
    url = "https://doi.org/10.1128/mmbr.00049-13",
    doi = "10.1128/mmbr.00049-13",
    openalex = "W2007786086",
    references = "doi101016jplrev201206001, doi103389fcimb201200119"
}

We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.

@article{doi101371journalpcbi1003537,
    author = "Bouckaert, Remco and Heled, Joseph and Kühnert, Denise and Vaughan, Tim and Wu, Chieh‐Hsi and Xie, Dong and Suchard, Marc A. and Rambaut, Andrew and Drummond, Alexei J.",
    title = "BEAST 2: A Software Platform for Bayesian Evolutionary Analysis",
    year = "2014",
    journal = "PLoS Computational Biology",
    abstract = "We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.",
    url = "https://doi.org/10.1371/journal.pcbi.1003537",
    doi = "10.1371/journal.pcbi.1003537",
    openalex = "W2026062398",
    references = "doi101007bf01731581, doi101007bf01734359, doi101007bf02101694, doi101093molbevmsi103, doi101093molbevmsp274, doi101093molbevmss075, doi101093oxfordjournalsmolbeva040023, doi101186147121487214, doi101371journalpbio0040088, openalexw1593676244"
}

@article{doi101038nrmicro3569,
    author = "Makarova, Kira S. and Wolf, Yuri I. and Alkhnbashi, Omer S. and Costa, Fabrizio and Shah, Shiraz A. and Saunders, Sita J. and Barrangou, Rodolphe and Brouns, Stan J. J. and Charpentier, Emmanuelle and Haft, Daniel H. and Horvath, Philippe and Moineau, Sylvain and Mojica, Francisco J. M. and Terns, Rebecca M. and Terns, Michael P. and White, Malcolm F. and Yakunin, Alexander F. and Garrett, Roger A. and van der Oost, John and Backofen, Rolf and Koonin, Eugene V.",
    title = "An updated evolutionary classification of CRISPR–Cas systems",
    year = "2015",
    journal = "Nature Reviews Microbiology",
    url = "https://doi.org/10.1038/nrmicro3569",
    doi = "10.1038/nrmicro3569",
    openalex = "W2199695484",
    references = "doi101016jmolcel201403011, doi101038nature09523, doi101038nature09886, doi101038nature10886, doi101038nbt2842, doi101038nrmicro2577, doi101093nargkt157, doi101099mic0280480, doi101126science1138140, doi101126science1159689, doi101126science1165771, doi101126science1225829, doi10118617456150442, doi103389fcimb201200119"
}

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

@article{doi101093molbevmsw054,
    author = "Kumar, Sudhir and Stecher, Glen and Tamura, Koichiro",
    title = "MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets",
    year = "2016",
    journal = "Molecular Biology and Evolution",
    abstract = "We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.",
    url = "https://doi.org/10.1093/molbev/msw054",
    doi = "10.1093/molbev/msw054",
    openalex = "W2311203695",
    references = "doi101073pnas1213199109, doi101093bioinformatics102189, doi101093bioinformaticsbts507, doi101093molbevmst197, doi101093molbevmsv037, doi101093nargks1219, doi101093nargkt1209, doi101093oxfordjournalsmolbeva040023, doi101093oxfordjournalsmolbeva040454, doi101186147121055113"
}

The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree.

@article{doi101093nargkw408,
    author = "Ashkenazy, Haim and Abadi, Shiran and Martz, Eric and Chay, Ofer and Mayrose, Itay and Pupko, Tal and Ben‐Tal, Nir",
    title = "ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules",
    year = "2016",
    journal = "Nucleic Acids Research",
    abstract = "The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree.",
    url = "https://doi.org/10.1093/nar/gkw408",
    doi = "10.1093/nar/gkw408",
    openalex = "W2376573086",
    references = "doi101006jmbi19909999, doi101006jmbi19931626, doi101007bf02498640, doi101016s0022283605803602, doi101038nmeth2109, doi101093bioinformaticsbtl158, doi101093bioinformaticsbts565, doi101093molbevmsn067, doi101093molbevmsr121, doi101093molbevmst010, doi101093nar281235, doi101093oxfordjournalsmolbeva040752, doi101109tac19741100705"
}

Adaptive immunity had been long thought of as an exclusive feature of animals. However, the discovery of the CRISPR-Cas defense system, present in almost half of prokaryotic genomes, proves otherwise. Because of the everlasting parasite-host arms race, CRISPR-Cas has rapidly evolved through horizontal transfer of complete loci or individual modules, resulting in extreme structural and functional diversity. CRISPR-Cas systems are divided into two distinct classes that each consist of three types and multiple subtypes. We discuss recent advances in CRISPR-Cas research that reveal elaborate molecular mechanisms and provide for a plausible scenario of CRISPR-Cas evolution. We also briefly describe the latest developments of a wide range of CRISPR-based applications.

@article{doi101126scienceaad5147,
    author = "Mohanraju, Prarthana and Makarova, Kira S. and Zetsche, Bernd and Zhang, Feng and Koonin, Eugene V. and van der Oost, John",
    title = "Diverse evolutionary roots and mechanistic variations of the CRISPR-Cas systems",
    year = "2016",
    journal = "Science",
    abstract = "Adaptive immunity had been long thought of as an exclusive feature of animals. However, the discovery of the CRISPR-Cas defense system, present in almost half of prokaryotic genomes, proves otherwise. Because of the everlasting parasite-host arms race, CRISPR-Cas has rapidly evolved through horizontal transfer of complete loci or individual modules, resulting in extreme structural and functional diversity. CRISPR-Cas systems are divided into two distinct classes that each consist of three types and multiple subtypes. We discuss recent advances in CRISPR-Cas research that reveal elaborate molecular mechanisms and provide for a plausible scenario of CRISPR-Cas evolution. We also briefly describe the latest developments of a wide range of CRISPR-based applications.",
    url = "https://doi.org/10.1126/science.aad5147",
    doi = "10.1126/science.aad5147",
    openalex = "W2502856725",
    references = "doi101016jmolcel201403011, doi101093nargkt157, doi107554elife03401"
}

Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae.

@article{doi101371journalppat1005574,
    author = "Buck, Christopher B. and Doorslaer, Koenraad Van and Peretti, Alberto and Geoghegan, Eileen M. and Tisza, Michael J. and An, Ping and Katz, Joshua P. and Pipas, James M. and McBride, Alison A. and Camus, Alvin C. and McDermott, Alexa J. and Dill, Jennifer A. and Delwart, Eric and Ng, Terry F. F. and Farkas, Kata and Austin, Charlotte and Kraberger, Simona and Davison, William and Pastrana, Diana V. and Varsani, Arvind",
    title = "The Ancient Evolutionary History of Polyomaviruses",
    year = "2016",
    journal = "PLoS Pathogens",
    abstract = "Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae.",
    url = "https://doi.org/10.1371/journal.ppat.1005574",
    doi = "10.1371/journal.ppat.1005574",
    openalex = "W2337421297",
    references = "doi101371journalpone0108277"
}

Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae.

@article{openalexw3143678695,
    author = "Buck, CB and Van Doorslaer, K and Peretti, A and Geoghegan, EM and Tisza, MJ and An, P and Katz, JP and Pipas, JM and McBride, AA and Camus, AC and McDermott, AJ and Dill, JA and Delwart, E and Ng, TFF and Farkas, K and Austin, C and Kraberger, S and Davison, W and Pastrana, DV and Varsani, A",
    title = "The Ancient Evolutionary History of Polyomaviruses",
    year = "2016",
    journal = "D-Scholarship@Pitt (University of Pittsburgh)",
    abstract = "Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae.",
    openalex = "W3143678695",
    references = "doi101371journalpone0108277"
}

Evolution of bacteria and archaea involves an incessant arms race against an enormous diversity of genetic parasites. Accordingly, a substantial fraction of the genes in most bacteria and archaea are dedicated to antiparasite defense. The functions of these defense systems follow several distinct strategies, including innate immunity; adaptive immunity; and dormancy induction, or programmed cell death. Recent comparative genomic studies taking advantage of the expanding database of microbial genomes and metagenomes, combined with direct experiments, resulted in the discovery of several previously unknown defense systems, including innate immunity centered on Argonaute proteins, bacteriophage exclusion, and new types of CRISPR-Cas systems of adaptive immunity. Some general principles of function and evolution of defense systems are starting to crystallize, in particular, extensive gain and loss of defense genes during the evolution of prokaryotes; formation of genomic defense islands; evolutionary connections between mobile genetic elements and defense, whereby genes of mobile elements are repeatedly recruited for defense functions; the partially selfish and addictive behavior of the defense systems; and coupling between immunity and dormancy induction/programmed cell death.

@article{doi101146annurevmicro090816093830,
    author = "Koonin, Eugene V. and Makarova, Kira S. and Wolf, Yuri I.",
    title = "Evolutionary Genomics of Defense Systems in Archaea and Bacteria",
    year = "2017",
    journal = "Annual Review of Microbiology",
    abstract = "Evolution of bacteria and archaea involves an incessant arms race against an enormous diversity of genetic parasites. Accordingly, a substantial fraction of the genes in most bacteria and archaea are dedicated to antiparasite defense. The functions of these defense systems follow several distinct strategies, including innate immunity; adaptive immunity; and dormancy induction, or programmed cell death. Recent comparative genomic studies taking advantage of the expanding database of microbial genomes and metagenomes, combined with direct experiments, resulted in the discovery of several previously unknown defense systems, including innate immunity centered on Argonaute proteins, bacteriophage exclusion, and new types of CRISPR-Cas systems of adaptive immunity. Some general principles of function and evolution of defense systems are starting to crystallize, in particular, extensive gain and loss of defense genes during the evolution of prokaryotes; formation of genomic defense islands; evolutionary connections between mobile genetic elements and defense, whereby genes of mobile elements are repeatedly recruited for defense functions; the partially selfish and addictive behavior of the defense systems; and coupling between immunity and dormancy induction/programmed cell death.",
    url = "https://doi.org/10.1146/annurev-micro-090816-093830",
    doi = "10.1146/annurev-micro-090816-093830",
    openalex = "W2602907179",
    references = "doi101007s0023900400463, doi101016jcell201402001, doi101038nature04160, doi101038nmicrobiol201648, doi101038nrmicro1750, doi101038nrmicro2315, doi101038nrmicro2577, doi101038nrmicro3569, doi101126science1102513, doi101126scienceaaf5573, doi10118617456150442, doi103109104092382011600437, doi103389fcimb201200119"
}

@incollection{doi101016b9780124095489105482,
    author = "Pigeon, Gabriel and Pelletier, Fanie",
    title = "Eco-Evolutionary Dynamics",
    year = "2018",
    booktitle = "Elsevier eBooks",
    url = "https://doi.org/10.1016/b978-0-12-409548-9.10548-2",
    doi = "10.1016/b978-0-12-409548-9.10548-2",
    openalex = "W2153615431",
    references = "doi101098rstb20090012, doi101111j13652435200701289x, doi1018900012965820000810642alhvac20co2"
}

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

@article{doi101093molbevmsy096,
    author = "Kumar, Sudhir and Stecher, Glen and Li, Michael and Knyaz, Christina and Tamura, Koichiro",
    title = "MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms",
    year = "2018",
    journal = "Molecular Biology and Evolution",
    abstract = "The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.",
    url = "https://doi.org/10.1093/molbev/msy096",
    doi = "10.1093/molbev/msy096",
    openalex = "W2799524357",
    references = "doi101093bioinformatics17121244, doi101093molbevmsw054"
}

@article{doi101038s4155901908808,
    author = "Visser, Marcel E. and Gienapp, Phillip",
    title = "Evolutionary and demographic consequences of phenological mismatches",
    year = "2019",
    journal = "Nature Ecology \& Evolution",
    url = "https://doi.org/10.1038/s41559-019-0880-8",
    doi = "10.1038/s41559-019-0880-8",
    openalex = "W2939724619",
    references = "doi101098rstb20100148"
}

@article{doi101038s415790190299x,
    author = "Makarova, Kira S. and Wolf, Yuri I. and Iranzo, Jaime and Shmakov, Sergey and Alkhnbashi, Omer S. and Brouns, Stan J. J. and Charpentier, Emmanuelle and Cheng, David R. and Haft, Daniel H. and Horvath, Philippe and Moineau, Sylvain and Mojica, Francisco J. M. and Scott, David and Shah, Shiraz A. and Šikšnys, Virginijus and Terns, Michael P. and Venclovas, Česlovas and White, Malcolm F. and Yakunin, Alexander F. and Yan, Winston X. and Zhang, Feng and Garrett, Roger A. and Backofen, Rolf and van der Oost, John and Barrangou, Rodolphe and Koonin, Eugene V.",
    title = "Evolutionary classification of CRISPR–Cas systems: a burst of class 2 and derived variants",
    year = "2019",
    journal = "Nature Reviews Microbiology",
    url = "https://doi.org/10.1038/s41579-019-0299-x",
    doi = "10.1038/s41579-019-0299-x",
    openalex = "W2995081665",
    references = "doi101038nature21031, doi101038nrmicro3569, doi101038s4157901800762, doi101146annurevmicro090816093830"
}

The Molecular Evolutionary Genetics Analysis (MEGA) software enables comparative analysis of molecular sequences in phylogenetics and evolutionary medicine. Here, we introduce the macOS version of the MEGA software. This new version eliminates the need for virtualization and emulation programs previously required to use MEGA on Apple computers. MEGA for macOS utilizes memory and computing resources efficiently for conducting evolutionary analyses on macOS. It has a native Cocoa graphical user interface that is programmed to provide a consistent user experience across macOS, Windows, and Linux. MEGA for macOS is available from www.megasoftware.net free of charge.

@article{doi101093molbevmsz312,
    author = "Stecher, Glen and Tamura, Koichiro and Kumar, Sudhir",
    title = "Molecular Evolutionary Genetics Analysis (MEGA) for macOS",
    year = "2019",
    journal = "Molecular Biology and Evolution",
    abstract = "The Molecular Evolutionary Genetics Analysis (MEGA) software enables comparative analysis of molecular sequences in phylogenetics and evolutionary medicine. Here, we introduce the macOS version of the MEGA software. This new version eliminates the need for virtualization and emulation programs previously required to use MEGA on Apple computers. MEGA for macOS utilizes memory and computing resources efficiently for conducting evolutionary analyses on macOS. It has a native Cocoa graphical user interface that is programmed to provide a consistent user experience across macOS, Windows, and Linux. MEGA for macOS is available from www.megasoftware.net free of charge.",
    url = "https://doi.org/10.1093/molbev/msz312",
    doi = "10.1093/molbev/msz312",
    openalex = "W2999168229",
    references = "doi101093molbevmsw054"
}

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

@article{doi101002evl3154,
    author = "Waldvogel, Ann‐Marie and Feldmeyer, Barbara and Rolshausen, Gregor and Expósito‐Alonso, Moisés and Rellstab, Christian and Kofler, Robert and Möck, Thomas and Schmid, Karl and Schmitt, Imke and Bataillon, Thomas and Savolainen, Outi and Bergland, Alan O. and Flatt, Thomas and Guillaume, Frédéric and Pfenninger, Markus",
    title = "Evolutionary genomics can improve prediction of species’ responses to climate change",
    year = "2020",
    journal = "Evolution Letters",
    abstract = "Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.",
    url = "https://doi.org/10.1002/evl3.154",
    doi = "10.1002/evl3.154",
    openalex = "W3000026902",
    references = "doi101016jtree201406005"
}

Viruses are integral components of all ecosystems and microbiomes on Earth. Through pervasive infections of their cellular hosts, viruses can reshape microbial community structure and drive global nutrient cycling. Over the past decade, viral sequences identified from genomes and metagenomes have provided an unprecedented view of viral genome diversity in nature. Since 2016, the IMG/VR database has provided access to the largest collection of viral sequences obtained from (meta)genomes. Here, we present the third version of IMG/VR, composed of 18 373 cultivated and 2 314 329 uncultivated viral genomes (UViGs), nearly tripling the total number of sequences compared to the previous version. These clustered into 935 362 viral Operational Taxonomic Units (vOTUs), including 188 930 with two or more members. UViGs in IMG/VR are now reported as single viral contigs, integrated proviruses or genome bins, and are annotated with a new standardized pipeline including genome quality estimation using CheckV, taxonomic classification reflecting the latest ICTV update, and expanded host taxonomy prediction. The new IMG/VR interface enables users to efficiently browse, search, and select UViGs based on genome features and/or sequence similarity. IMG/VR v3 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

@article{doi101093nargkaa946,
    author = "Roux, Simon and Páez-Espino, David and Chen, I-Min A. and Palaniappan, Krishna and Ratner, Anna and Chu, Ken and Reddy, T. B. K. and Nayfach, Stephen and Schulz, Frederik and Call, Lee and Neches, Russell Y. and Woyke, Tanja and Ivanova, Natalia and Eloe‐Fadrosh, Emiley A. and Kyrpides, Nikos C.",
    title = "IMG/VR v3: an integrated ecological and evolutionary framework for interrogating genomes of uncultivated viruses",
    year = "2020",
    journal = "Nucleic Acids Research",
    abstract = "Viruses are integral components of all ecosystems and microbiomes on Earth. Through pervasive infections of their cellular hosts, viruses can reshape microbial community structure and drive global nutrient cycling. Over the past decade, viral sequences identified from genomes and metagenomes have provided an unprecedented view of viral genome diversity in nature. Since 2016, the IMG/VR database has provided access to the largest collection of viral sequences obtained from (meta)genomes. Here, we present the third version of IMG/VR, composed of 18 373 cultivated and 2 314 329 uncultivated viral genomes (UViGs), nearly tripling the total number of sequences compared to the previous version. These clustered into 935 362 viral Operational Taxonomic Units (vOTUs), including 188 930 with two or more members. UViGs in IMG/VR are now reported as single viral contigs, integrated proviruses or genome bins, and are annotated with a new standardized pipeline including genome quality estimation using CheckV, taxonomic classification reflecting the latest ICTV update, and expanded host taxonomy prediction. The new IMG/VR interface enables users to efficiently browse, search, and select UViGs based on genome features and/or sequence similarity. IMG/VR v3 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG\_VR.",
    url = "https://doi.org/10.1093/nar/gkaa946",
    doi = "10.1093/nar/gkaa946",
    openalex = "W3097008984",
    references = "doi101128mmbr0006119"
}

The microbiome shapes many host traits, yet the biology of microbiomes challenges traditional evolutionary models. Here, we illustrate how integrating the microbiome into quantitative genetics can help untangle complexities of host-microbiome evolution. We describe two general ways in which the microbiome may affect host evolutionary potential: by shifting the mean host phenotype and by changing the variance in host phenotype in the population. We synthesize the literature across diverse taxa and discuss how these scenarios could shape the host response to selection. We conclude by outlining key avenues of research to improve our understanding of the complex interplay between hosts and microbiomes.

@article{doi101038s4146702125315x,
    author = "Henry, Lucas P. and Bruijning, Marjolein and Forsberg, Simon K. G. and Ayroles, Julien F.",
    title = "The microbiome extends host evolutionary potential",
    year = "2021",
    journal = "Nature Communications",
    abstract = "The microbiome shapes many host traits, yet the biology of microbiomes challenges traditional evolutionary models. Here, we illustrate how integrating the microbiome into quantitative genetics can help untangle complexities of host-microbiome evolution. We describe two general ways in which the microbiome may affect host evolutionary potential: by shifting the mean host phenotype and by changing the variance in host phenotype in the population. We synthesize the literature across diverse taxa and discuss how these scenarios could shape the host response to selection. We conclude by outlining key avenues of research to improve our understanding of the complex interplay between hosts and microbiomes.",
    url = "https://doi.org/10.1038/s41467-021-25315-x",
    doi = "10.1038/s41467-021-25315-x",
    openalex = "W3195370685",
    references = "doi101016jcell201409053, doi101016jtree201101009, doi101016jzool201802004, doi101038nature11550, doi101038nature12820, doi101038nature25973, doi101038nm4517, doi101038nrg3182, doi101038nrmicro201787, doi101073pnas1218525110, doi101111j13652435200701283x, doi103389fcimb201200119"
}

Abstract The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.

@article{doi101093molbevmsab120,
    author = "Tamura, Koichiro and Stecher, Glen and Kumar, Sudhir",
    title = "MEGA11: Molecular Evolutionary Genetics Analysis Version 11",
    year = "2021",
    journal = "Molecular Biology and Evolution",
    abstract = "Abstract The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.",
    url = "https://doi.org/10.1093/molbev/msab120",
    doi = "10.1093/molbev/msab120",
    openalex = "W4251751280",
    references = "doi101073pnas1213199109, doi101093bib52150, doi101093bioinformatics102189, doi101093bioinformatics17121244, doi101093molbevmsr121, doi101093molbevmst197, doi101093molbevmsw054, doi101093molbevmsy096, doi101093molbevmsz312, doi101126science1211028"
}

Since the early 1990s, ecologists and evolutionary biologists have aggregated primary research using meta-analytic methods to understand ecological and evolutionary phenomena. Meta-analyses can resolve long-standing disputes, dispel spurious claims, and generate new research questions. At their worst, however, meta-analysis publications are wolves in sheep's clothing: subjective with biased conclusions, hidden under coats of objective authority. Conclusions can be rendered unreliable by inappropriate statistical methods, problems with the methods used to select primary research, or problems within the primary research itself. Because of these risks, meta-analyses are increasingly conducted as part of systematic reviews, which use structured, transparent, and reproducible methods to collate and summarise evidence. For readers to determine whether the conclusions from a systematic review or meta-analysis should be trusted - and to be able to build upon the review - authors need to report what they did, why they did it, and what they found. Complete, transparent, and reproducible reporting is measured by 'reporting quality'. To assess perceptions and standards of reporting quality of systematic reviews and meta-analyses published in ecology and evolutionary biology, we surveyed 208 researchers with relevant experience (as authors, reviewers, or editors), and conducted detailed evaluations of 102 systematic review and meta-analysis papers published between 2010 and 2019. Reporting quality was far below optimal and approximately normally distributed. Measured reporting quality was lower than what the community perceived, particularly for the systematic review methods required to measure trustworthiness. The minority of assessed papers that referenced a guideline (~16%) showed substantially higher reporting quality than average, and surveyed researchers showed interest in using a reporting guideline to improve reporting quality. The leading guideline for improving reporting quality of systematic reviews is the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Here we unveil an extension of PRISMA to serve the meta-analysis community in ecology and evolutionary biology: PRISMA-EcoEvo (version 1.0). PRISMA-EcoEvo is a checklist of 27 main items that, when applicable, should be reported in systematic review and meta-analysis publications summarising primary research in ecology and evolutionary biology. In this explanation and elaboration document, we provide guidance for authors, reviewers, and editors, with explanations for each item on the checklist, including supplementary examples from published papers. Authors can consult this PRISMA-EcoEvo guideline both in the planning and writing stages of a systematic review and meta-analysis, to increase reporting quality of submitted manuscripts. Reviewers and editors can use the checklist to assess reporting quality in the manuscripts they review. Overall, PRISMA-EcoEvo is a resource for the ecology and evolutionary biology community to facilitate transparent and comprehensively reported systematic reviews and meta-analyses.

@article{doi101111brv12721,
    author = "O’Dea, Rose E. and Lagisz, Malgorzata and Jennions, Michael D. and Koricheva, Julia and Noble, Daniel W. A. and Parker, Timothy and Gurevitch, Jessica and Page, Matthew J. and Stewart, Gavin and Moher, David and Nakagawa, Shinichi",
    title = "Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension",
    year = "2021",
    journal = "Biological reviews/Biological reviews of the Cambridge Philosophical Society",
    abstract = "Since the early 1990s, ecologists and evolutionary biologists have aggregated primary research using meta-analytic methods to understand ecological and evolutionary phenomena. Meta-analyses can resolve long-standing disputes, dispel spurious claims, and generate new research questions. At their worst, however, meta-analysis publications are wolves in sheep's clothing: subjective with biased conclusions, hidden under coats of objective authority. Conclusions can be rendered unreliable by inappropriate statistical methods, problems with the methods used to select primary research, or problems within the primary research itself. Because of these risks, meta-analyses are increasingly conducted as part of systematic reviews, which use structured, transparent, and reproducible methods to collate and summarise evidence. For readers to determine whether the conclusions from a systematic review or meta-analysis should be trusted - and to be able to build upon the review - authors need to report what they did, why they did it, and what they found. Complete, transparent, and reproducible reporting is measured by 'reporting quality'. To assess perceptions and standards of reporting quality of systematic reviews and meta-analyses published in ecology and evolutionary biology, we surveyed 208 researchers with relevant experience (as authors, reviewers, or editors), and conducted detailed evaluations of 102 systematic review and meta-analysis papers published between 2010 and 2019. Reporting quality was far below optimal and approximately normally distributed. Measured reporting quality was lower than what the community perceived, particularly for the systematic review methods required to measure trustworthiness. The minority of assessed papers that referenced a guideline (\textasciitilde 16\%) showed substantially higher reporting quality than average, and surveyed researchers showed interest in using a reporting guideline to improve reporting quality. The leading guideline for improving reporting quality of systematic reviews is the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Here we unveil an extension of PRISMA to serve the meta-analysis community in ecology and evolutionary biology: PRISMA-EcoEvo (version 1.0). PRISMA-EcoEvo is a checklist of 27 main items that, when applicable, should be reported in systematic review and meta-analysis publications summarising primary research in ecology and evolutionary biology. In this explanation and elaboration document, we provide guidance for authors, reviewers, and editors, with explanations for each item on the checklist, including supplementary examples from published papers. Authors can consult this PRISMA-EcoEvo guideline both in the planning and writing stages of a systematic review and meta-analysis, to increase reporting quality of submitted manuscripts. Reviewers and editors can use the checklist to assess reporting quality in the manuscripts they review. Overall, PRISMA-EcoEvo is a resource for the ecology and evolutionary biology community to facilitate transparent and comprehensively reported systematic reviews and meta-analyses.",
    url = "https://doi.org/10.1111/brv.12721",
    doi = "10.1111/brv.12721",
    openalex = "W3158015415",
    references = "doi101016jbiocon201506006, doi101038s4155901704025"
}

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

@article{doi101128cmr0005019,
    author = "Baquero, F. and Martínez, J. L. and Lanza, V. F. and Rodríguez-Beltrán, J. and Galán, J. C. and Millán, A. San and Cantón, R. and Coque, T. M.",
    title = "Evolutionary Pathways and Trajectories in Antibiotic Resistance",
    year = "2021",
    journal = "Clinical Microbiology Reviews",
    abstract = {Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.},
    url = "https://doi.org/10.1128/cmr.00050-19",
    doi = "10.1128/cmr.00050-19",
    openalex = "W3175889552",
    references = "doi101002bies201000127, doi101007bf01731581, doi101016jscitotenv201301032, doi101038nrmicro3028, doi101073pnas9563140, doi101093oso97801985459960010001, doi101098rstb19520012, doi101126science1227079, doi101128cmr0008817, doi101128microbiolspecplas00392014, doi101128mmbr0001610, doi101371journalpgen1000713, doi102307jctvjsf433, doi103389fcimb201200119"
}

changes (e.g., horizontal gene transfer). Finally, we synthesize how observed microbial assemblages are the dynamic outcome of both successful and unsuccessful dispersal events of taxa and discuss these concepts in line with the literature, thus enabling a richer appreciation of this process in microbiome research.

@article{doi103389fmicb2022855859,
    author = "Custer, Gordon and Bresciani, Luana and Dini‐Andreote, Francisco",
    title = "Ecological and Evolutionary Implications of Microbial Dispersal",
    year = "2022",
    journal = "Frontiers in Microbiology",
    abstract = "changes (e.g., horizontal gene transfer). Finally, we synthesize how observed microbial assemblages are the dynamic outcome of both successful and unsuccessful dispersal events of taxa and discuss these concepts in line with the literature, thus enabling a richer appreciation of this process in microbiome research.",
    url = "https://doi.org/10.3389/fmicb.2022.855859",
    doi = "10.3389/fmicb.2022.855859",
    openalex = "W4226315715",
    references = "doi101111ele13568, doi101128cmr0005019"
}

@article{doi101038s41579023009025,
    author = "Sanz‐García, Fernando and Gil‐Gil, Teresa and Laborda, Pablo and Blanco, Paula and Ochoa-Sánchez, Luz Edith and Baquero, Fernando and Martínez, José Luis and Hernando‐Amado, Sara",
    title = "Translating eco-evolutionary biology into therapy to tackle antibiotic resistance",
    year = "2023",
    journal = "Nature Reviews Microbiology",
    url = "https://doi.org/10.1038/s41579-023-00902-5",
    doi = "10.1038/s41579-023-00902-5",
    openalex = "W4377090310",
    references = "doi101128cmr0005019"
}

We introduce the 12th version of the Molecular Evolutionary Genetics Analysis (MEGA12) software. This latest version brings many significant improvements by reducing the computational time needed for selecting optimal substitution models and conducting bootstrap tests on phylogenies using maximum likelihood (ML) methods. These improvements are achieved by implementing heuristics that minimize likely unnecessary computations. Analyses of empirical and simulated datasets show substantial time savings by using these heuristics without compromising the accuracy of results. MEGA12 also links-in an evolutionary sparse learning approach to identify fragile clades and associated sequences in evolutionary trees inferred through phylogenomic analyses. In addition, this version includes fine-grained parallelization for ML analyses, support for high-resolution monitors, and an enhanced Tree Explorer. MEGA12 can be downloaded from https://www.megasoftware.net.

@article{doi101093molbevmsae263,
    author = "Kumar, Sudhir and Stecher, Glen and Suleski, Michael and Sanderford, Maxwell and Sharma, Sudip and Tamura, Koichiro",
    title = "MEGA12: Molecular Evolutionary Genetic Analysis Version 12 for Adaptive and Green Computing",
    year = "2024",
    journal = "Molecular Biology and Evolution",
    abstract = "We introduce the 12th version of the Molecular Evolutionary Genetics Analysis (MEGA12) software. This latest version brings many significant improvements by reducing the computational time needed for selecting optimal substitution models and conducting bootstrap tests on phylogenies using maximum likelihood (ML) methods. These improvements are achieved by implementing heuristics that minimize likely unnecessary computations. Analyses of empirical and simulated datasets show substantial time savings by using these heuristics without compromising the accuracy of results. MEGA12 also links-in an evolutionary sparse learning approach to identify fragile clades and associated sequences in evolutionary trees inferred through phylogenomic analyses. In addition, this version includes fine-grained parallelization for ML analyses, support for high-resolution monitors, and an enhanced Tree Explorer. MEGA12 can be downloaded from https://www.megasoftware.net.",
    url = "https://doi.org/10.1093/molbev/msae263",
    doi = "10.1093/molbev/msae263",
    openalex = "W4405670661",
    references = "doi101073pnas1213199109, doi101093molbevmsab120"
}