系統発生

関: phyletic、phylogenetic、phylogeny

WordNet

of or relating to the evolutionary development of organisms; "phylogenetic development" (同)phyletic

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(生物の)系統発生[学]

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出典(authority):フリー百科事典『ウィキペディア（Wikipedia）』「2014/08/01 21:21:10」(JST)

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In biology, phylogenetics /faɪlɵdʒɪˈnɛtɪks/ is the study of evolutionary relationships among groups of organisms (e.g. species, populations), which are discovered through molecular sequencing data and morphological data matrices. The term phylogenetics derives from the Greek terms phylé (φυλή) and phylon (φῦλον), denoting "tribe", "clan", "race"^[1] and the adjectival form, genetikós (γενετικός), of the word genesis (γένεσις) "origin", "source", "birth".^[2] The result of phylogenetic studies is a hypothesis about the evolutionary history of taxonomic groups: their phylogeny.^[3]

Evolution is a process whereby populations are altered over time and may split into separate branches, hybridize together, or terminate by extinction. The evolutionary branching process may be depicted as a phylogenetic tree, and the place of each of the various organisms on the tree is based on a hypothesis about the sequence in which evolutionary branching events occurred. In historical linguistics, similar concepts are used with respect to relationships between languages; and in textual criticism with stemmatics.

Phylogenetic analyses have become essential to research on the evolutionary tree of life. For example, the RedToL aims at reconstructing the Red Algal Tree of Life. The National Science Foundation sponsors a project called the Assembling the Tree of Life (AToL) activity. The goal of this project is to determine evolutionary relationships across large groups of organisms throughout the history of life. The research on this project often involves large teams working across institutions and disciplines, and typically provides support to investigators working on computational phylogenetics and phyloinformatics tasks, including data acquisition, analysis, and algorithm development and dissemination.

Taxonomy--the classification, identification, and naming of organisms--is usually richly informed by phylogenetics, but remains a methodologically and logically distinct discipline.^[4] The degree to which taxonomies depend on phylogenies differs depending on the school of taxonomy: phenetics ignores phylogeny altogether, trying to represent the similarity between organisms instead; cladistics (phylogenetic systematics) tries to reproduce phylogeny in its classification without loss of information; evolutionary taxonomy tries to find a compromise between them in order to represent stages of evolution.

1 Construction of a phylogenetic tree
2 Limitations and workarounds
- 2.1 Homoplasy
- 2.2 Horizontal gene transfer
- 2.3 Taxon sampling
- 2.4 Phylogenetic signal
- 2.5 Continuous characters
- 2.6 Missing data
3 The role of fossils
4 History of phylogenetics
- 4.1 Ernst Haeckel's recapitulation theory
- 4.2 Timeline of key events
5 See also
6 References
7 Further reading
8 External links

Construction of a phylogenetic tree

The scientific methods of phylogenetics are often grouped under the term cladistics. The most common ones are parsimony, maximum likelihood (ML), and MCMC-based Bayesian inference. All methods depend upon an implicit or explicit mathematical model describing the evolution of characters observed in the species included; all can be, and are, used for molecular data, wherein the characters are aligned nucleotide or amino acid sequences, and all but maximum likelihood (see below) can be, and are, used for phenotypic (morphological, chemical, and physiological) data (also called classical or traditional data).

Phenetics, popular in the mid-20th century but now largely obsolete, uses distance matrix-based methods to construct trees based on overall similarity in morphology or other observable traits (i.e. in the phenotype, not the DNA), which was often assumed to approximate phylogenetic relationships.

A comprehensive step-by-step protocol on constructing phylogenetic tree, including DNA/Amino Acid contiguous sequence assembly, multiple sequence alignment, model-test (testing best-fitting substitution models) and phylogeny reconstruction using Maximum Likelihood and Bayesian Inference, is available at Nature Protocol ^[5]

Prior to 1990, phylogenetic inferences were generally presented as narrative scenarios. Such methods are legitimate, but often ambiguous and hard to test.^[6]^[7]^[8]

Limitations and workarounds

Ultimately, there is no way to measure whether a particular phylogenetic hypothesis is accurate or not, unless the true relationships among the taxa being examined are already known (which may happen with bacteria or viruses under laboratory conditions). The best result an empirical phylogeneticist can hope to attain is a tree with branches that are well supported by the available evidence. Several potential pitfalls have been identified:

Homoplasy

Certain characters are more likely to evolve convergently than others; logically, such characters should be given less weight in the reconstruction of a tree.^[9] Weights in the form of a model of evolution can be inferred from sets of molecular data, so that maximum likelihood or Bayesian methods can be used to analyze them. For molecular sequences, this problem is exacerbated when the taxa under study have diverged substantially. As time since the divergence of two taxa increase, so does the probability of multiple substitutions on the same site, or back mutations, all of which result in homoplasies. For morphological data, unfortunately, the only objective way to determine convergence is by the construction of a tree – a somewhat circular method. Even so, weighting homoplasious characters^[how?] does indeed lead to better-supported trees.^[9] Further refinement can be brought by weighting changes in one direction higher than changes in another; for instance, the presence of thoracic wings almost guarantees placement among the pterygote insects because, although wings are often lost secondarily, there is no evidence that they have been gained more than once.^[10]

Horizontal gene transfer

In general, organisms can inherit genes in two ways: vertical gene transfer and horizontal gene transfer. Vertical gene transfer is the passage of genes from parent to offspring, and horizontal (also called lateral) gene transfer occurs when genes jump between unrelated organisms, a common phenomenon especially in prokaryotes; a good example of this is the acquired antibiotic resistance as a result of gene exchange between various bacteria leading to multi-drug-resistant bacterial species. There have also been well-documented cases of horizontal gene transfer between eukaryotes.

Horizontal gene transfer has complicated the determination of phylogenies of organisms, and inconsistencies in phylogeny have been reported among specific groups of organisms depending on the genes used to construct evolutionary trees. The only way to determine which genes have been acquired vertically and which horizontally is to parsimoniously assume that the largest set of genes that have been inherited together have been inherited vertically; this requires analyzing a large number of genes.

Taxon sampling

Owing to the development of advanced sequencing techniques in molecular biology, it has become feasible to gather large amounts of data (DNA or amino acid sequences) to infer phylogenetic hypotheses. For example, it is not rare to find studies with character matrices based on whole mitochondrial genomes (~16,000 nucleotides, in many animals). However, simulations have shown that it is more important to increase the number of taxa in the matrix than to increase the number of characters, because the more taxa there are, the more accurate and more robust is the resulting phylogenetic tree.^[11]^[12] This may be partly due to the breaking up of long branches.

Phylogenetic signal

Another important factor that affects the accuracy of tree reconstruction is whether the data analyzed actually contain a useful phylogenetic signal, a term that is used generally to denote whether a character evolves slowly enough to have the same state in closely related taxa as opposed to varying randomly. Tests for phylogenetic signal exist.^[13]

Continuous characters

Morphological characters that sample a continuum may contain phylogenetic signal, but are hard to code as discrete characters. Several methods have been used, one of which is gap coding, and there are variations on gap coding.^[14] In the original form of gap coding:^[14]

group means for a character are first ordered by size. The pooled within-group standard deviation is calculated … and differences between adjacent means … are compared relative to this standard deviation. Any pair of adjacent means is considered different and given different integer scores … if the means are separated by a "gap" greater than the within-group standard deviation … times some arbitrary constant.

If more taxa are added to the analysis, the gaps between taxa may become so small that all information is lost. Generalized gap coding works around that problem by comparing individual pairs of taxa rather than considering one set that contains all of the taxa.^[14]

Missing data

In general, the more data that are available when constructing a tree, the more accurate and reliable the resulting tree will be. Missing data are no more detrimental than simply having fewer data, although the impact is greatest when most of the missing data are in a small number of taxa. Concentrating the missing data across a small number of characters produces a more robust tree.^[15]

The role of fossils

Because many characters involve embryological, or soft-tissue or molecular characters that (at best) hardly ever fossilize, and the interpretation of fossils is more ambiguous than that of living taxa, extinct taxa almost invariably have higher proportions of missing data than living ones. However, despite these limitations, the inclusion of fossils is invaluable, as they can provide information in sparse areas of trees, breaking up long branches and constraining intermediate character states; thus, fossil taxa contribute as much to tree resolution as modern taxa.^[16] Fossils can also constrain the age of lineages and thus demonstrate how consistent a tree is with the stratigraphic record;^[17] stratocladistics incorporates age information into data matrices for phylogenetic analyses.

History of phylogenetics

The term "phylogeny" derives from the German Phylogenie, introduced by Haeckel in 1866.^[18]

Ernst Haeckel's recapitulation theory

During the late 19th century, Ernst Haeckel's recapitulation theory, or "biogenetic fundamental law", was widely accepted. It was often expressed as "ontogeny recapitulates phylogeny", i.e. the development of an organism successively mirrors the adult stages of successive ancestors of the species to which it belongs. This theory has long been rejected. In fact, ontogeny evolves – the phylogenetic history of a species cannot be read directly from its ontogeny, as Haeckel thought would be possible, but characters from ontogeny can be (and have been) used as data for phylogenetic analyses; the more closely related two species are, the more apomorphies their embryos share.

Timeline of key events

Branching tree diagram from Heinrich Georg Bronn'swork,(1858)

Phylogenetic tree suggested by Haeckel(1866)

1300s, lex parsimoniae (parsimony principle), William of Ockam, English philosopher, theologian, and Franciscan monk, but the idea actually goes back to Aristotle, precursor concept
1763, Bayesian probability, Rev. Thomas Bayes,^[19] precursor concept
1700s, Pierre Simon (Marquis de Laplace), perhaps 1st to use ML (maximum likelihood), precursor concept
1809, evolutionary theory, Philosophie Zoologique, Jean-Baptiste de Monet (chevalier de Lamarck), precursor concept, foreshadowed in the 1600s and 1700s by Voltaire, Descartes, and Leibniz, with Leibniz even proposing evolutionary changes to account for observed gaps suggesting that many species had become extinct, others transformed, and different species that share common traits may have at one time been a single race,^[20] also foreshadowed by some early Greek philosophers such as Anaximander in the 6th century BC and the atomists of the 5th century BC, who proposed rudimentary theories of evolution ^[21]
1837, Darwin's notebooks show an evolutionary tree^[22]
1843, distinction between homology and analogy (the latter now referd to as homoplasy), Richard Owen, precursor concept
1858, Paleontologist Heinrich Georg Bronn (1800–1862) published a hypothetical tree to illustrating the paleontological "arrival" of new, similar species following the extinction of an older species. Bronn did not propose a mechanism responsible for such phenomena, precursor concept. ^[23]
1858, elaboration of evolutionary theory, Darwin and Wallace,^[24] also in Origin of Species by Darwin the following year, precursor concept
1860, Heinrich Georg Bronn translates and oversees the publication of Origin of Species into German ^[25]
1866, Ernst Haeckel, first publishes his phylogeny-based evolutionary tree, precursor concept
1893, Dollo's Law of Character State Irreversibility,^[26] precursor concept
1912, ML recommended, analyzed, and popularized by Ronald Fisher, precursor concept
1921, Tillyard uses term "phylogenetic" and distinguishes between archaic and specialized characters in his classification system^[27]
1940, term "clade" coined by Lucien Cuénot
1949, jackknife, Maurice Quenouille (foreshadowed in '46 by Mahalanobis and extended in '58 by Tukey), precursor concept
1950, Willi Hennig's classic formalization ^[28]
1952, William Wagner's groundplan divergence method ^[29]
1953, "cladogenesis" coined ^[30]
1960, "cladistic" coined by Cain and Harrison ^[31]
1963, 1st attempt to use ML (maximum likelihood) for phylogenetics, Edwards and Cavalli-Sforza ^[32]
1965
- Camin-Sokal parsimony, 1st parsimony (optimization) criterion and 1st computer program/algorithm for cladistic analysis both by Camin and Sokal ^[33]
- character compatibility method, also called clique analysis, introduced independently by Camin and Sokal (loc. cit.) and E.O. Wilson ^[34]
1966
- English translation of Hennig ^[35]
- "cladistics" and "cladogram" coined (Webster's, loc. cit.)
1969
- dynamic and successive weighting, James Farris ^[36]
- Wagner parsimony, Kluge and Farris ^[37]
- CI (consistency index), Kluge and Farris ^[37]
- introduction of pairwise compatibility for clique analysis, Le Quesne ^[38]
1970, Wagner parsimony generalized by Farris ^[39]
1971
- Fitch parsimony, Fitch ^[40]
- NNI (nearest neighbour interchange), 1st branch-swapping search strategy, developed independently by Robinson ^[41] and Moore et al.
- ME (minimum evolution), Kidd and Sgaramella-Zonta ^[42] (it is unclear if this is the pairwise distance method or related to ML as Edwards and Cavalli-Sforza call ML "minimum evolution".)
1972, Adams consensus, Adams ^[43]
1974, 1st successful application of ML to phylogenetics (for nucleotide sequences), Neyman ^[44]
1976, prefix system for ranks, Farris ^[45]
1977, Dollo parsimony, Farris ^[46]
1979
- Nelson consensus, Nelson ^[47]
- MAST (maximum agreement subtree)((GAS)greatest agreement subtree), a consensus method, Gordon ^[48]
- bootstrap, Bradley Efron, precursor concept ^[49]
1980, PHYLIP, 1st software package for phylogenetic analysis, Felsenstein
1981
- majority consensus, Margush and MacMorris ^[50]
- strict consensus, Sokal and Rohlf ^[51]
- 1st computationally efficient ML algorithm, Felsenstein ^[52]
1982
- PHYSIS, Mikevich and Farris
- branch and bound, Hendy and Penny ^[53]
1985
- 1st cladistic analysis of eukaryotes based on combined phenotypic and genotypic evidence Diana Lipscomb ^[54]
- 1st issue of Cladistics
- 1st phylogentic application of bootstrap, Felsenstein ^[55]
- 1st phylogenetic application of jackknife, Scott Lanyon ^[56]
1986, MacClade, Maddison and Maddison
1987, neighbor-joining method Saitou and Nei ^[57]
1988, Hennig86 (version 1.5), Farris
1989
- RI (retention index), RCI (rescaled consistency index), Farris ^[58]
- HER (homoplasy excess ratio), Archie ^[59]
1990
- combinable components (semi-strict) consensus, Bremer ^[60]
- SPR (subtree pruning and regrafting), TBR (tree bisection and reconnection), Swofford and Olsen^[61]
1991
- DDI (data decisiveness index), Goloboff ^[62]^[63]
- 1st cladistic analysis of eukaryotes based only on phenotypic evidence, Lipscomb
1993, implied weighting Goloboff ^[64]
1994, Bremer support (decay index), Bremer ^[65]
1994, reduced consensus: RCC (reduced cladistic consensus) for rooted trees, Wilkinson ^[66]
1995, reduced consensus RPC (reduced partition consensus) for unrooted trees, Wilkinson ^[67]
1996, 1st working methods for BI (Bayesian Inference)independently developed by Li,^[68] Mau,^[69] and Rannalla and Yang ^[70] and all using MCMC (Markov chain-Monte Carlo)
1998, TNT (Tree Analysis Using New Technology), Goloboff, Farris, and Nixon
1999, Winclada, Nixon
2003, symmetrical resampling, Goloboff ^[71]

References

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External links

Look up phylogenetics in Wiktionary, the free dictionary.

The Tree of Life
Interactive Tree of Life
PhyloCode
ExploreTree
UCMP Exhibit Halls: Phylogeny Wing
Willi Hennig Society
Filogenetica.org in Spanish
PhyloPat, Phylogenetic Patterns
SplitsTree, program for computing phylogenetic trees and unrooted phylogenetic networks
Dendroscope, program for drawing phylogenetic trees and rooted phylogenetic networks
Phylogenetic inferring on the T-REX server
Mesquite
NCBI – Systematics and Molecular Phylogenetics
Sydney Brenner's seminars: "What Genomes Can Tell Us About the Past"
Mikko's Phylogeny Archive
Who is Who in Phylogenetic Networks research papers related to the phylogenetic network
Phylogenetic Reconstruction from Gene-Order Data
ETE: A Python Environment for Tree Exploration This is a programming library to analyze, manipulate and visualize phylogenetic trees. See: Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni (2010). "ETE: A python Environment for Tree Exploration". BMC Bioinformatics 11: 24. doi:10.1186/1471-2105-11-24. PMC 2820433. PMID 20070885.
PhylomeDB: A public database hosting thousands of gene phylogenies ranging many different species. See: Huerta-Cepas, J.; Capella-Gutierrez, S.; Pryszcz, L. P.; Denisov, I.; Kormes, D.; Marcet-Houben, M.; Gabaldón, T. (2010). "PhylomeDB v3.0: An expanding repository of genome-wide collections of trees, alignments and phylogeny-based orthology and paralogy predictions". Nucleic Acids Research 39 (Database issue): D556–60. doi:10.1093/nar/gkq1109. PMC 3013701. PMID 21075798.
Lents, N. H.; Cifuentes, O. E.; Carpi, A. (2010). "Teaching the Process of Molecular Phylogeny and Systematics: A Multi-Part Inquiry-Based Exercise". Cell Biology Education 9 (4): 513. doi:10.1187/cbe.09-10-0076.

English Journal

Ecology and biotechnological potential of the thermophilic fermentative Coprothermobacter spp.

Gagliano MC1, Braguglia CM1, Petruccioli M2, Rossetti S3.
FEMS microbiology ecology.FEMS Microbiol Ecol.2015 May;91(5). pii: fiv018. doi: 10.1093/femsec/fiv018. Epub 2015 Feb 14.
Thermophilic bacteria have been isolated from several terrestrial, marine and industrial environments. Anaerobic digesters treating organic wastes are often an important source of these microorganisms, which catalyze a wide array of metabolic processes. Moreover, organic wastes are primarily compose
PMID 25764466

Is there room for improving the nutraceutical composition of apple?

Farneti B1, Masuero D, Costa F, Magnago P, Malnoy M, Costa G1, Vrhovsek U, Mattivi F.
Journal of agricultural and food chemistry.J Agric Food Chem.2015 Mar 18;63(10):2750-9. doi: 10.1021/acs.jafc.5b00291. Epub 2015 Mar 9.
In this study, we assessed the main bioactive compounds of a broad apple germplasm collection, composed by 247 accessions of wild (97) and domesticated (150) species. Among the stilbenes, trans- and cis-piceid were found to be ubiquitary components of both wild and cultivated apples. Apple was sugge
PMID 25723891

Molecular evolution of cytochrome bd oxidases across proteobacterial genomes.

Degli Esposti M1, Rosas-Pérez T2, Servín-Garcidueñas LE2, Bolaños LM2, Rosenblueth M2, Martínez-Romero E2.
Genome biology and evolution.Genome Biol Evol.2015 Feb 16;7(3):801-20. doi: 10.1093/gbe/evv032.
This work is aimed to resolve the complex molecular evolution of cytochrome bd ubiquinol oxidase, a nearly ubiquitous bacterial enzyme that is involved in redox balance and bioenergetics. Previous studies have created an unclear picture of bd oxidases phylogenesis without considering the existence o
PMID 25688108

Japanese Journal

Diversification of Lignin Supramolecular Structure during the Evolution of Plants

寺島典二
Mokuzai Gakkaishi 59(2), 65-80, 2013
… The causes of the complicated heterogeneity of lignin SMS can be understood reasonably well from the viewpoints of evolutionary biology and polymer chemistry: "ontogenesis recapitulates phylogenesis", and growing of lignin SMS is controlled by the supply of monolignols and polymerization conditions provided by previously deposited polysaccharides. …
NAID 130004469032

結核菌と結核症の考古学 : その発生から世界流行まで

岩井和郎,前田伸司,村瀬良朗
結核 85(5), 465-475, 2010-05-15
NAID 10030262866

NKp44 expression, phylogenesis and function in non-human primate NK cells

DE MARIA Andrea,UGOLOTTI Elisabetta,RUTJENS Erik,MAZZA Stefania,RADIC Luana,FARAVELLI Alessandro,KOOPMAN Gerrit,DI MARCO Eddi,COSTA Paola,ENSOLI Barbara,CAFARO Aurelio,CRISTINA MINGARI Maria,MORETTA Lorenzo,HEENEY Jonathan,BIASSONI Roberto
International immunology 21(3), 245-255, 2009-03-01
NAID 10025384687

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リンク元	「phylogenetic」「phylogeny」「系統発生」「phyletic」

「phylogenetic」

　　[★]

系統発生の、系統学の、系統学的な、系統的な

関: genealogical、genealogy、phyletic、phylogenesis、phylogenetically、phylogenic、phylogenically、phylogeny、systematic、systematically

「phylogeny」

　　[★]

系統発生、系統樹、系統発生学、系統学

関: genealogical、genealogical tree、genealogy、phyletic、phyletic tree、phylogenesis、phylogenetic、phylogenetic tree、phylogram

「系統発生」

　　[★]

英: phylogenesis、phylogeny、phylogenetic、phyletic
関: 系統学、系統学的、系統樹、系統的、系統発生学; 発生

「phyletic」

　　[★]

系統発生の

関: phylogenesis、phylogenetic、phylogeny

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phylogenesis