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In biology, phylogenetics ( /faɪlɵdʒɪˈnɛtɪks/) is the study of evolutionary relation among groups of organisms (e.g. species, populations), which is discovered through molecular sequencing data and morphological data matrices. The term phylogenetics derives from the Greek terms phyle (φυλή) and phylon (φῦλον), denoting "tribe" and "race";^[1] and the term genetikos (γενετικός), denoting "relative to birth", from genesis (γένεσις) "origin" and "birth".^[2]

Taxonomy, the classification, identification, and naming of organisms, is richly informed by phylogenetics, but remains methodologically and logically distinct.^[3] The fields of phylogenetics and taxonomy overlap in the science of phylogenetic systematics — one methodology, cladism (also cladistics) shared derived characters (synapomorphies) used to create ancestor-descendant trees (cladograms) and delimit taxa (clades).^[4][5] In biological systematics as a whole, phylogenetic analyses have become essential in researching the evolutionary tree of life.

Construction of a phylogenetic tree[link]

Evolution is regarded as a branching process, whereby populations are altered over time and may speciate into separate branches, hybridize together, or terminate by extinction. This may be visualized in a phylogenetic tree.

The problem posed by phylogenetics is that genetic data are only available for living taxa, and the fossil records (osteometric data) contains less data and more-ambiguous morphological characters.^[6] A phylogenetic tree represents a hypothesis of the order in which evolutionary events are assumed to have occurred.

Cladistics is the current method of choice to infer phylogenetic trees. The most commonly-used methods to infer phylogenies include parsimony, maximum likelihood, and MCMC-based Bayesian inference. Phenetics, popular in the mid-20th century but now largely obsolete, uses distance matrix-based methods to construct trees based on overall similarity, which is often assumed to approximate phylogenetic relationships. All methods depend upon an implicit or explicit mathematical model describing the evolution of characters observed in the species included, and are usually used for molecular phylogeny, wherein the characters are aligned nucleotide or amino acid sequences.

Grouping of organisms[link]

Phylogenetic groups, or taxa, can be monophyletic, paraphyletic, or polyphyletic.

There are some terms that describe the nature of a grouping in such trees. For instance, all birds and reptiles are believed to have descended from a single common ancestor, so this taxonomic grouping (yellow in the diagram below) is called monophyletic. "Modern reptile" (cyan in the diagram) is a grouping that contains a common ancestor, but does not contain all descendants of that ancestor (birds are excluded). This is an example of a paraphyletic group. A grouping such as warm-blooded animals would include only mammals and birds (red/orange in the diagram) and is called polyphyletic because the members of this grouping do not include the most recent common ancestor.

Molecular phylogenetics[link]

The evolutionary connections between organisms are represented graphically through phylogenetic trees. Due to the fact that evolution takes place over long periods of time that cannot be observed directly, biologists must reconstruct phylogenies by inferring the evolutionary relationships among present-day organisms. Fossils can aid with the reconstruction of phylogenies; however, fossil records are often too poor to be of good help. Therefore, biologists tend to be restricted with analysing present-day organisms to identify their evolutionary relationships. Phylogenetic relationships in the past were reconstructed by looking at phenotypes, often anatomical characteristics. Today, molecular data, which includes protein and DNA sequences, are used to construct phylogenetic trees.^[7]

The overall goal of National Science Foundation's Assembling the Tree of Life activity (AToL) is to resolve evolutionary relationships for large groups of organisms throughout the history of life, with the research often involving large teams working across institutions and disciplines. Investigators are typically supported for projects in data acquisition, analysis, algorithm development and dissemination in computational phylogenetics and phyloinformatics. For example, RedToL aims at reconstructing the Red Algal Tree of Life.

Ernst Haeckel's recapitulation theory[link]

Genealogical tree suggested by Haeckel (1866)

During the late 19th century, Ernst Haeckel's recapitulation theory, or biogenetic law, was widely accepted. This theory was often expressed as "ontogeny recapitulates phylogeny", i.e. the development of an organism exactly mirrors the evolutionary development of the species. Haeckel's early version of this hypothesis [that the embryo mirrors adult evolutionary ancestors] has since been rejected, and the hypothesis amended as the embryo's development mirroring embryos of its evolutionary ancestors. Most modern biologists recognize numerous connections between ontogeny and phylogeny, explain them using evolutionary theory, or view them as supporting evidence for that theory. Donald I. Williamson suggested that larvae and embryos represented adults in other taxa that have been transferred by hybridization (the larval transfer theory).^[8][9] However, Williamson's views do not represent mainstream thought in molecular biology,^[10] and there is a significant body of evidence against the larval transfer theory.^[11]

Gene transfer[link]

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 gene transfer or lateral gene transfer occurs when genes jump between unrelated organisms, a common phenomenon in prokaryotes; a good example of this is the acquired antibiotic resistance as a result of gene exchange between some bacteria and development of multidrug resistant bacterial species.

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.

Carl Woese came up with the three-domain theory of life (eubacteria, archaea and eukaryota) based on his discovery that the genes encoding ribosomal RNA are ancient and distributed over all lineages of life with little or no horizontal gene transfer. Therefore, rRNAs are commonly recommended as molecular clocks for reconstructing phylogenies.

This has been particularly useful for the phylogeny of microorganisms, to which the species concept does not apply and which are too morphologically simple to be classified based on phenotypic traits.

Taxon sampling and phylogenetic signal[link]

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, it has been proposed 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 the more robust is the resulting phylogenetic tree.^[12]

This may be partly due to the breaking up of long branches. It has been argued that this is an important reason to incorporate data from fossils into phylogenies where possible. Of course, phylogenetic data that include fossil taxa are generally based on morphology, rather than DNA data. Using simulations, Derrick Zwickl and David Hillis^[13] found that increasing taxon sampling in phylogenetic inference has a positive effect on the accuracy of phylogenetic analyses.

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 related organisms tend to resemble each other with respect to their genetic material or phenotypic traits.^[14] Ultimately, however, 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. The best result an empirical systematist can hope to attain is a tree with branches well-supported by the available evidence.

Importance of missing data[link]

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

Role of fossils[link]

Because many morphological characters involve embryological or soft-tissue characters that cannot be fossilized, and the interpretation of fossils is more ambiguous than living taxa, it is sometimes difficult to incorporate fossil data into phylogenies. 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]

Molecular phylogenies can reveal rates of diversification, but in order to track rates of origination, extinction and patterns in diversification, fossil data must be incorporated.^[18] Molecular techniques assume a constant rate of diversification, which is rarely likely to be true; in some (but by no means all) cases, the assumptions inherent in interpreting the fossil record (e.g. a complete and unbiased record) are closer to being true than the assumption of a constant rate, making fossil insights more accurate than molecular reconstructions.^[18]

Homoplasy weighting[link]

Certain characters are more likely to be evolved convergently than others; logically, such characters should be given less weight in the reconstruction of a tree.^[19] Unfortunately the only objective way to determine convergence is by the construction of a tree – a somewhat circular method. Even so, weighting homoplasious characters does indeed lead to better-supported trees.^[19] 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, although because wings are often lost secondarily, their absence does not exclude a taxon from the group.^[20]

See also[link]

Evolutionary biology portal

References[link]

Further reading[link]

• Schuh, R. T. and A. V. Z. Brower. 2009. Biological Systematics: principles and applications (2nd edn.) ISBN 978-0-8014-4799-0

External links[link]

• 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
• What Genomes Can Tell Us About the Past – lecture on phylogenetics by Sydney Brenner
• 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. Ref.
• PhylomeDB: A public database hosting thousands of gene phylogenies ranging many different species.Ref.

• A published teaching exercising for demonstrating the process of molecular phylogenetics.

Jonathan A. Eisen is an American evolutionary biologist, currently working at University of California, Davis.^[4][5] His academic research is in the fields of evolutionary biology, genomics and microbiology and he is the academic editor-in-chief of the open-access journal PLoS Biology.^[6][7]

In 2011 Eisen was awarded the Benjamin Franklin Award (Bioinformatics) for promoting open access in the life sciences.^[8]

Eisen together with Nick Barton, Derek E.G. Briggs, David B. Goldstein, and Nipam H. Patel is an author of the undergraduate textbook, Evolution, that integrates molecular biology, genomics, and human genetics with traditional evolutionary studies.^[1] According to Google Scholar^[9] his most cited peer-reviewed papers are on the genome sequence of Plasmodium falciparum,^[10] sequencing the Sargasso Sea ^[11] and a paper on the genome of Thermotoga maritima.^[12]

Prior to working at UC Davis he was an Investigator at The Institute for Genomic Research.

Eisen and his work is routinely discussed in the scientific and popular press. Examples include a New York Times article on the Genomic Encyclopedia of Bacteria and Archaea in 2009 ^[13] and extensive coverage of work on searching for a "fourth domain" of life ^{[14] [15]}. In addition, Eisen's blogging and microblogging work is frequently written about including for example ^{[16] [17] [18]}. His brother Michael Eisen is also a biologist.

Selected Publications[link]

• Wu, D.; Hugenholtz, P.; Mavromatis, K.; Pukall, R. �D.; Dalin, E.; Ivanova, N. N.; Kunin, V.; Goodwin, L. et al. (2009). "A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea". Nature 462 (7276): 1056–1060. Bibcode 2009Natur.462.1056W. DOI:10.1038/nature08656. PMC 3073058. PMID 20033048. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3073058.  edit
• Eisen, J. A.; MacCallum, C. J. (2009). "Genomics of Emerging Infectious Disease: A PLoS Collection". PLoS Biology 7 (10): e1000224. DOI:10.1371/journal.pbio.1000224. PMC 2757914. PMID 19855830. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2757914.  edit
• Eisen, J. A. (2007). "Environmental Shotgun Sequencing: Its Potential and Challenges for Studying the Hidden World of Microbes". PLoS Biology 5 (3): e82. DOI:10.1371/journal.pbio.0050082. PMC 1821061. PMID 17355177. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1821061.  edit
• Eisen, J. A.; Coyne, R. S.; Wu, M.; Wu, D.; Thiagarajan, M.; Wortman, J. R.; Badger, J. H.; Ren, Q. et al. (2006). "Macronuclear Genome Sequence of the Ciliate Tetrahymena thermophila, a Model Eukaryote". PLoS Biology 4 (9): e286. DOI:10.1371/journal.pbio.0040286. PMC 1557398. PMID 16933976. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1557398.  edit
• Wu, D.; Daugherty, S. C.; Van Aken, S. E.; Pai, G. H.; Watkins, K. L.; Khouri, H.; Tallon, L. J.; Zaborsky, J. M. et al. (2006). "Metabolic Complementarity and Genomics of the Dual Bacterial Symbiosis of Sharpshooters". PLoS Biology 4 (6): e188. DOI:10.1371/journal.pbio.0040188. PMC 1472245. PMID 16729848. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1472245.  edit
• Seshadri, R.; Adrian, L.; Fouts, D.; Eisen, J.; Phillippy, A.; Methe, B.; Ward, N.; Nelson, W. et al. (2005). "Genome Sequence of the PCE-Dechlorinating Bacterium Dehalococcoides ethenogenes". Science 307 (5706): 105–108. DOI:10.1126/science.1102226. PMID 15637277.  edit
• Venter, J. C.; Remington, K.; Heidelberg, J.; Halpern, A.; Rusch, D.; Eisen, J.; Wu, D.; Paulsen, I. et al. (2004). "Environmental Genome Shotgun Sequencing of the Sargasso Sea". Science 304 (5667): 66–74. Bibcode 2004Sci...304...66V. DOI:10.1126/science.1093857. PMID 15001713.  edit
• Ward, N.; Larsen, Ø.; Sakwa, J.; Bruseth, L.; Khouri, H.; Durkin, A. S.; Dimitrov, G.; Jiang, L. et al. (2004). "Genomic Insights into Methanotrophy: The Complete Genome Sequence of Methylococcus capsulatus (Bath)". PLoS Biology 2 (10): e303. DOI:10.1371/journal.pbio.0020303. PMC 517821. PMID 15383840. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=517821.  edit
• Wu, M.; Sun, L. V.; Vamathevan, J.; Riegler, M.; Deboy, R.; Brownlie, J. C.; McGraw, E. A.; Martin, W. et al. (2004). "Phylogenomics of the Reproductive Parasite Wolbachia pipientis wMel: A Streamlined Genome Overrun by Mobile Genetic Elements". PLoS Biology 2 (3): e69. DOI:10.1371/journal.pbio.0020069. PMC 368164. PMID 15024419. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=368164.  edit
• Eisen, J.; Fraser, C. (2003). "Phylogenomics: intersection of evolution and genomics". Science 300 (5626): 1706–1707. Bibcode 2003Sci...300.1706E. DOI:10.1126/science.1086292. PMID 12805538.  edit
• Read, T. D.; Peterson, S. N.; Tourasse, N.; Baillie, L. W.; Paulsen, I. T.; Nelson, K. E.; Tettelin, H.; Fouts, D. E. et al. (2003). "The genome sequence of Bacillus anthracis Ames and comparison to closely related bacteria". Nature 423 (6935): 81–86. DOI:10.1038/nature01586. PMID 12721629.  edit
• Gardner, M. J.; Hall, N.; Fung, E.; White, O.; Berriman, M.; Hyman, R. W.; Carlton, J. M.; Pain, A. et al. (2002). "Genome sequence of the human malaria parasite Plasmodium falciparum". Nature 419 (6906): 498–511. DOI:10.1038/nature01097. PMID 12368864.  edit
• Béjà, O.; Suzuki, M. T.; Heidelberg, J. F.; Nelson, W. C.; Preston, C. M.; Hamada, T.; Eisen, J. A.; Fraser, C. M. et al. (2002). "Unsuspected diversity among marine aerobic anoxygenic phototrophs". Nature 415 (6872): 630. DOI:10.1038/415630a. PMID 11832943.  edit
• Ward, N.; Eisen, J.; Fraser, C.; Stackebrandt, E. (2001). "Sequenced strains must be saved from extinction". Nature 414 (6860): 148–148. DOI:10.1038/35102737. PMID 11700527.  edit
• Eisen, J. A. (2001). "Microbiology: Gastrogenomics". Nature 409 (6819): 463–466. DOI:10.1038/35054158. PMID 11206526.  edit
• Salzberg, S. L.; White, O.; Peterson, J.; Eisen, J. (2001). "Microbial Genes in the Human Genome: Lateral Transfer or Gene Loss?". Science 292 (5523): 1903–1906. DOI:10.1126/science.1061036. PMID 11358996.  edit
• The Arabidopsis Genome Initiative, I. (2000). "Analysis of the genome sequence of the flowering plant Arabidopsis thaliana". Nature 408 (6814): 796–815. DOI:10.1038/35048692. PMID 11130711.  edit
• Fraser, C. M.; Heidelberg, J. F.; Eisen, J. A.; Nelson, W. C.; Clayton, R. A.; Gwinn, M. L.; Dodson, R. J.; Haft, D. H. et al. (2000). "DNA sequence of both chromosomes of the cholera pathogen Vibrio cholerae". Nature 406 (6795): 477–483. DOI:10.1038/35020000. PMID 10952301.  edit
• Fraser, C. M.; Eisen, J. A.; Salzberg, S. L. (2000). "Microbial genome sequencing". Nature 406 (6797): 799–803. DOI:10.1038/35021244. PMID 10963611.  edit
• Lin, X.; Kaul, S.; Rounsley, S.; Shea, T. P.; Benito, M. I.; Town, C. D.; Fujii, C. Y.; Mason, T. et al. (1999). "Sequence and analysis of chromosome 2 of the plant Arabidopsis thaliana". Nature 402 (6763): 761–768. DOI:10.1038/45471. PMID 10617197.  edit
• White, O.; Eisen, J.; Heidelberg, J.; Hickey, E.; Peterson, J.; Dodson, R.; Haft, D.; Gwinn, M. et al. (1999). "Genome sequence of the radioresistant bacterium Deinococcus radiodurans R1". Science 286 (5444): 1571–1577. DOI:10.1126/science.286.5444.1571. PMID 10567266.  edit
• Fraser, C. M.; Nelson, K. E.; Clayton, R. A.; Gill, S. R.; Gwinn, M. L.; Dodson, R. J.; Haft, D. H.; Hickey, E. K. et al. (1999). "Evidence for lateral gene transfer between Archaea and bacteria from genome sequence of Thermotoga maritima". Nature 399 (6734): 323–329. Bibcode 1999Natur.399..323N. DOI:10.1038/20601. PMID 10360571.  edit

References[link]

External links[link]

• Jonathan Eisen on Twitter
• Jonathan Eisen's "Tree of Life" Blog
• Lab Web Page
• Jonathan Eisen's Mendeley Page

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