Welcome to the I Can't Sleep Podcast,
Where I read random articles from across the web to bore you to sleep with my soothing voice.
I'm your host Benjamin Boster,
And today's episode is from a Wikipedia article titled Phylogenetics.
In biology,
Phylogenetics is the study of the evolutionary history of life using genetics,
Which is known as phylogenetic inference.
It establishes the relationship between organisms with the empirical data and observed heritable traits of DNA sequences,
Protein,
Amino acid sequences,
And morphology.
The results are a phylogenetic tree,
A diagram setting the hypothetical relationships between organisms and their evolutionary history.
The tips of a phylogenetic tree can be living taxa or fossils,
Which represent the present time or end of an evolutionary lineage,
Respectively.
A phylogenetic diagram can be rooted or unrooted.
A rooted tree diagram indicates the hypothetical common ancestor of the tree.
An unrooted tree diagram,
A network,
Makes no assumption about the ancestral line and does not show the origin or root of the taxa in question,
Or the direction of inferred evolutionary transformations.
In addition to their use for inferring phylogenetic patterns among taxa,
Phylogenetic analyses are often employed to represent relationships among genes or individual organisms.
Such uses have become central to understanding biodiversity,
Evolution,
Ecology,
And genomes.
Phylogenetics is a component of systematics that uses similarities and differences of the characteristics of species to interpret their evolutionary relationships and origins.
It focuses on whether the characteristics of a species reinforce a phylogenetic inference that had diverged from the most recent common ancestor of a taxonomic group.
In the field of cancer research,
Phylogenetics can be used to study the clonal evolution of tumors and molecular chronology,
Predicting and showing how cell populations vary throughout the progression of the disease and during treatment,
Using whole genome sequencing techniques.
The evolutionary processes behind cancer progression are quite different from those in most species and are important to phylogenetic inference.
These differences manifest in several areas.
The types of aberrations that occur,
The rates of mutation,
The high heterogeneity variability of tumor cell subclones,
And the absence of genetic recombination.
Phylogenetics can also aid in drug design and discovery.
It allows scientists to organize species and can show which species are likely to have inherited particular traits that are medically useful,
Such as producing biologically active compounds,
Those that have effects on the human body.
For example,
In drug discovery,
Venom-producing animals are particularly useful.
Venoms from these animals produce several important drugs,
E.
G.
ACE inhibitors and prialt zirconatide.
To find new venoms,
Scientists turn to phylogenetics to screen for closely related species that may have the same useful traits.
The phylogenetic tree shows which species of fish have an origin of venom and related fish that may contain the trait.
Using this approach in studying venomous fish,
Biologists are able to identify the fish species that may be venomous.
Biologists have used this approach in many species,
Such as snakes and lizards.
In forensic science,
Phylogenetic tools are useful to assess DNA evidence for court cases.
The simple phylogenetic tree of viruses A through E shows the relationship between viruses,
E.
G.
All viruses are descendants of virus A.
Taxonomy is the identification,
Naming,
And classification of organisms.
Compared to systemization,
Classification emphasizes whether a species has characteristics of a taxonomic group.
The Linnaean classification system,
Developed in the 1700s by Carolus Linnaeus,
Is the foundation for modern classification methods.
This classification relies on an organism's phenotype,
Or physical characteristics,
To group an organized species.
With the emergence of biochemistry,
Organism classifications are now usually based on phylogenetic data,
And many systematists contend that only monophyletic taxa should be recognized as named groups.
The degree to which classification depends on inferred evolutionary history differs depending on the school of taxonomy.
Phonetics ignores phylogenetic speculation altogether,
Trying to represent the similarity between organisms instead.
Cladistics,
Phylogenetic systematics,
Tries to reflect phylogeny in its classifications by only recognizing groups based on shared,
Derived characteristics.
Evolutionary taxonomy tries to take into account both the branching pattern and degree of difference to find a compromise between them.
Usual methods of phylogenetic inference involve computational approaches implementing the optimality criteria and methods of parsimony,
Maximum likelihood,
ML,
And MCMC-based Bayesian inference.
All these depend upon an implicit or explicit mathematical model describing the evolution of characters observed.
Phonetics,
Popular in the mid-20th century but now largely obsolete,
Used distance-matrix-based methods to construct trees based on overall similarity in morphology or similar observable traits,
I.
E.
In the phenotype or the overall similarity of DNA,
Not the DNA sequence,
Which was often assumed to approximate phylogenetic relationships.
Prior to 1950,
Phylogenetic inferences were generally presented as narrative scenarios.
Such methods are often ambiguous and lack explicit criteria for evaluating alternative hypotheses.
In phylogenetic analysis,
Taxon sampling selects a small group of taxon to represent the evolutionary history of its broader population.
This process is also known as stratified sampling or clade-based sampling.
The practice occurs given limited resources to compare and analyze every species within a target population.
Based on the representative group selected,
The construction and accuracy of phylogenetic trees vary,
Which impacts derived phylogenetic inferences.
Unavailable datasets,
Such as an organism's incomplete DNA and protein amino acid sequences in genome databases,
Directly restrict taxonomic sampling.
Consequently,
A significant source of error within phylogenetic analysis occurs due to inadequate taxon samples.
Accuracy may be improved by increasing the number of genetic samples within its monophyletic group.
Conversely,
Increasing sampling from outgroups extraneous to the target stratified population may decrease accuracy.
Long branch attraction is an attributed theory for this occurrence,
Where non-related branches are incorrectly classified together,
Insinuating a shared evolutionary history.
There are debates if increasing the number of taxa sampled improves phylogenetic accuracy more than increasing the number of genes sampled per taxon.
Differences in each method's sampling impacts the number of nucleotide sites utilized in a sequence alignment,
Which may contribute to disagreements.
For example,
Phylogenetic trees constructed utilizing a more significant number of total nucleotides are generally more accurate,
As supported by phylogenetic trees bootstrapping replicability from random sampling.
The graphic presented in Taxon Sampling Bioinformatics and Phylogenomics compares the correctness of phylogenetic trees generated using fewer taxa and more sites per taxon on the x-axis to more taxa and fewer sites per taxon on the y-axis.
With fewer taxa,
More genes are sampled amongst the taxonomic group.
In comparison,
With more taxa added to the taxonomic sampling group,
Fewer genes are sampled.
Each method has the same total number of nucleotide sites sampled.
Furthermore,
The dotted line represents a one-to-one accuracy between the two sampling methods.
As seen in the graphic,
Most of the plotted points are located below the dotted line,
Which indicates gravitation toward increased accuracy when sampling fewer taxa with more sites per taxon.
The research performed utilizes four different phylogenetic tree construction models to verify the theory.
Neighbor Joining,
NJ,
Minimum Evolution,
ME,
Unweighted Maximum Parsimony,
MP,
And Maximum Likelihood,
ML.
In the majority of models,
Sampling fewer taxon with more sites per taxon demonstrated higher accuracy.
Generally,
With the alignment of a relatively equal number of total nucleotide sites,
Sampling more genes per taxon has higher bootstrapping replicability than sampling more taxa.
However,
Unbalanced datasets within genomic databases make increasing the gene comparison per taxon in uncommonly sampled organisms increasingly difficult.
The term phylogeny derives from the germ phylogenia,
Introduced by Heckel in 1866,
And the Darwinian approach to classification became known as the phyletic approach.
It can be traced back to Aristotle,
Who wrote in his Posterior Analytics,
We may assume the superiority sateres paribus,
Other things being equal,
Of the demonstration which derives from fewer postulates or hypotheses.
The modern concept of phylogenetics evolved primarily as a disproof of a previously widely accepted theory.
During the late 19th century,
Ernst Heckel's recapitulation theory,
Or biogenetic fundamental law,
Was widely popular.
It was often expressed as,
Ontogeny recapitulates phylogeny,
I.
E.
,
The development of a single organism during its lifetime,
From germ to adult,
Successively mirrors the adult stages of successive ancestors of the species to which it belongs.
But this theory has long been rejected.
Instead,
Ontogeny evolves.
The phylogenetic history of a species cannot be read directly from its ontogeny,
As Heckel thought would be possible,
But characters from the 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 Points Fourteenth century Lex parsimoniae,
Parsimony principle,
William of Ockham,
English philosopher,
Theologian,
And Franciscan friar,
But the idea actually goes back to Aristotle as a precursor concept.
He introduced the concept of Ockham's razor,
Which is a problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements.
Though he did not use these exact words,
The principle can be summarized as,
Entities must not be multiplied beyond necessity.
The principle advocates that when presented with competing hypotheses about the same prediction,
One should prefer the one that requires fewest assumptions.
1763 Bayesian Probability,
Rev.
Thomas Bayes,
A precursor concept.
Bayesian probability began a resurgence in the 1950s,
Allowing scientists in the computing field to pair traditional Bayesian statistics with other more modern techniques.
It is now used as a blanket term for several related interpretations of probability as an amount of epistemic confidence.
18th century Pierre Simon,
Marquis de Laplace,
Perhaps first to use ML,
Maximum likelihood,
Precursor concept.
His work gave way to the Laplace distribution,
Which can be directly linked to least absolute deviations.
1809 Evolutionary Theory,
Philosophie Zoologique,
Jean-Baptiste Lamacq.
Precursor concept,
Foreshadowed in the 17th century and 18th century 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.
Also foreshadowed by some early Greek philosophers,
Such as Anazimander in the 6th century BC and the Adamists of the 5th century BC,
Who proposed rudimentary theories of evolution.
1837 Darwin's notebooks show an evolutionary tree.
1840 American geologist Edward Hitchcock published what is considered to be the first paleontological tree of life.
Many critiques,
Modifications,
And explanations would follow.
1843 Distinction between homology and analogy.
The latter now referred to as homoplasy.
Richard Owen,
Precursor Concept.
Homology is a term used to characterize the similarity of features that can be parsimoniously explained by common ancestry.
Homoplasy is the term used to describe a feature that has been gained or lost independently and separate lineages over the course of evolution.
1858 Paleontologist Heinrich Georg Braun,
1800-1862,
Published a hypothetical tree to illustrating the paleontological arrival of new similar species following the extinction of an older species.
Braun did not propose a mechanism responsible for such phenomena.
Precursor Concept.
1858 Collaboration of evolutionary theory.
Darwin and Wallace,
Also in Origin of Species by Darwin the following year.
Precursor Concept.
1868 Ernst Haeckel first publishes his phylogeny-based evolutionary tree.
Precursor Concept.
Haeckel introduces the now improved recapitulation theory.
He introduced the term cladus as a taxonomic category just below subphylum.
1893 Dolo's Law of Character State Irreversibility.
Precursor Concept.
Dolo's Law of Irreversibility states that an organism never comes back exactly to its previous state due to the indestructible nature of the past.
It always retains some trace of the transitional stages through which it has passed.
1912 ML Maximum Likelihood Recommended,
Analyzed,
And Popularized by Ronald Fisher.
Precursor Concept.
Fisher is one of the main contributors to the early 20th century revival of Darwinism and has been called the greatest of Darwin's successors for his contributions to the revision of the theory of evolution and his use of mathematics to combine Mendelian genetics and natural selection in the 20th century modern synthesis.
1921 Tilliard uses term phylogenetic and distinguishes between archaic and specialized characters in his classification system.
1940 Lucien Coyneau coined the term clade in 1940.
He uses it for evolutionary branching.
1947 Bernhard Rensch introduced the term cladogenesis in his German book Evolution Above the Species Level.
1949 Jack Knife resampling,
Maurice Kenoui,
Foreshadowed in 46 by Mahalanibus and extended in 58 by Tukey.
Precursor Concept.
1950 Willy Hennig's classic formalization.
Hennig is considered the founder of phylogenetic systematics and published his first works in German of this year.
He also asserted a version of the parsimony principle stating that the presence of amorphous characters in different species is always reason for suspecting kinship and that their origin by convergence should not be presumed a priori.
This has been considered a foundation view of phylogenetic inference.
1952 William Wagner's ground plan divergence method.
1957 Julian Huxley adopted Rensch's terminology as cladogenesis with a full definition.
Cladogenesis I have taken over directly from Rensch to denote all splitting from subspeciation through adaptive radiation to the divergence of phyla and kingdoms.
With it he introduced the word clades defining it as cladogenesis results in the formation of delimitable monophyletic units which may be called clades.
Arthur Kane and Jeffrey Ainsworth Harrison coined cladistic to mean evolutionary relationship.
First attempt to use ML maximum likelihood for phylogenetics.
Edwards and Cavalli-Sforza.
Kammen-Sokol parsimony,
First parsimony,
Optimization criterion and first computer program algorithm for cladistic analysis both by Kammen and Sokol.
Character compatibility method also called clique analysis introduced independently by Kammen and Sokol and E.
O.
Wilson.
1966 English translation of Hennig.
Cladistics and cladogram coined.
1969 Dynamic and successive weighting,
James Ferris.
Wagner parsimony,
Kluge and Ferris.
CI,
Consistency index,
Kluge and Ferris.
Introduction of pair ways compatibility for clique analysis,
Lukezna.
1970 Wagner parsimony generalized by Ferris.
1971 First successful application of ML maximum likelihood to phylogenetics for protein sequences,
Nyman.
Fitch parsimony,
Walter M.
Fitch.
These gave way to the most basics of maximum parsimony.
Fitch is known for his work on reconstructing phylogenetic trees from protein and DNA sequences.
His definition of orthologous sequences has been referenced in many research publications.
NNI,
Nearest neighbor interchange.
First branch swapping search strategy developed independently by Robinson and Moore et al.
ME,
Minimum evolution.
Kidd and Zgarmela Zonta.
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.
1976 Prefix system for ranks,
Ferris.
1977 Dolo parsimony,
Ferris.
1979 Nelson consensus,
Nelson.
MAST,
Maximum agreement subtree.
GAS,
Greatest agreement subtree.
A consensus method,
Gordon.
Bootstrap,
Bradley Efron.
Precursor concept.
1980,
Philip.
First software package for phylogenetic analysis.
Joseph Felsenstein.
A free computational phylogenetics package of programs for inferring evolutionary trees,
Phylogenes.
One such example tree created by Philip called A drawgram generates rooted trees.
1981 Majority consensus,
Margish and McMorris.
Strict consensus,
Sokol and Rolfe.
First computational efficiency ML,
Maximum likelihood algorithm.
Felsenstein created the Felsenstein maximum likelihood method used for the inference of phylogeny which evaluates a hypothesis about evolutionary history in terms of the probability that the proposed model and the hypothesized history would give rise to the observed data set.
1982 Fisis,
Mickiewicz and Ferris.
Branch and bound,
Hendy and Penny.
1985 First cladistic analysis of eukaryotes based on combined phenotypic and genotypic evidence.
Diana Lipscomb.
First issue of cladistics.
First phylogenetic application of bootstrap.
Felsenstein.
First phylogenetic application of jackknife.
Scott Lanyon.
1986 McClade,
Madison and Madison.
1987 Neighbor joining method.
Setu and Ney.
1988 Hennig 86 version 1.
5,
Ferris.
Bremmer support.
Decay index,
Bremmer.
1989 Ri retention index.
Rci rescaled consistency index,
Ferris.
Her homoplasy excess ratio,
Archie.
1990 Combinable components,
Semi-strict consensus,
Bremmer.
SPR,
Subtree pruning and regrafting.
TBR,
Tree bisection and reconnection.
Swilford and Olson.
1991 DDI,
Dated decisiveness index,
Golobov.
First cladistic analysis of eukaryotes based only on phenotypic evidence,
Lipscomb.
1993 Implied weighting,
Golobov.
1994 Reduced consensus.
RCC,
Reduced cladistic consensus for rooted trees,
Wilkinson.
1995 Reduced consensus.
RPC,
Reduced partition consensus for unrooted trees,
Wilkinson.
1986 First working methods for BI,
Bayesian inference.
Independently developed by Li,
Mao and Ranalla and Yang.
And all using MCMC,
Markov Chain Monte Carlo.
1998 TNT,
Tree analysis using new technology,
Golobov,
Ferris and Nixon.
1999 Winclada,
Nixon.
2003 Symmetrical resampling,
Golobov.
2004-2005 Similarity metric,
Using an approximation of Kolmogorov complexity,
Or NCD.
Normalized compression distance,
Li et al.
Kilabresi and Vitani.
