Assessment of phylogenomic and orthology approaches for phylogenetic inference

Dutilh, Bas E.; Noort, Vera van; Heijden, R. T. J. M. van der; Boekhout, Teun; Snel, Berend; Huynen, Martijn A.

doi:10.1093/bioinformatics/btm015

Cited by 66 publications

(51 citation statements)

References 67 publications

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“…However, the BBB model implies two crucial aspects of these trees that are both compatible with empirical data: i) the deep internal branches of gene trees are strongly compressed as dictated by the rapidity of evolution during inflationary phases, and ii) in general, there is no reason for the topologies of the trees for individual genes to be the same in their deep parts, given the rampant reassortment and recombination of genetic elements during the inflationary phases (although, toward the end of an inflationary stage, some gene combinations would become relatively stable, rendering a degree of coherence on some of the gene trees). An implication of these notions is that concatenation of protein sequences in an attempt to enhance the signal and resolve deep phylogenies, a common approach in genome-wide phylogenetic analysis [22,99,100], is a highly suspect practice at best.…”

Section: Discussionmentioning

confidence: 99%

The Biological Big Bang model for the major transitions in evolution

Koonin

2007

Biol Direct

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Background: Major transitions in biological evolution show the same pattern of sudden emergence of diverse forms at a new level of complexity. The relationships between major groups within an emergent new class of biological entities are hard to decipher and do not seem to fit the tree pattern that, following Darwin's original proposal, remains the dominant description of biological evolution. The cases in point include the origin of complex RNA molecules and protein folds; major groups of viruses; archaea and bacteria, and the principal lineages within each of these prokaryotic domains; eukaryotic supergroups; and animal phyla. In each of these pivotal nexuses in life's history, the principal "types" seem to appear rapidly and fully equipped with the signature features of the respective new level of biological organization. No intermediate "grades" or intermediate forms between different types are detectable. Usually, this pattern is attributed to cladogenesis compressed in time, combined with the inevitable erosion of the phylogenetic signal.

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Section: Discussionmentioning

confidence: 99%

The Biological Big Bang model for the major transitions in evolution

Koonin

2007

Biol Direct

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“…There is no single, optimal method to define the age of a gene. Considering that new genes typically emerge as a result of gene duplication, one of the more sophisticated approaches includes evolutionary reconstructions that map each duplication to a specific branch in the corresponding species tree and consider that branch the ''birth date'' of the gene in question (36,37). However, this approach is both labor-consuming and error-prone, so we used a more straightforward (and cruder) procedure for partitioning genes into age classes.…”

Section: Age Classes Of Eukaryotic Genes and Their Distinct Featuresmentioning

confidence: 99%

The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages

Wolf

Novichkov²,

Karev³

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

215

214

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The evolutionary rates of protein-coding genes in an organism span, approximately, 3 orders of magnitude and show a universal, approximately log-normal distribution in a broad variety of species from prokaryotes to mammals. This universal distribution implies a steady-state process, with identical distributions of evolutionary rates among genes that are gained and genes that are lost. A mathematical model of such process is developed under the single assumption of the constancy of the distributions of the propensities for gene loss (PGL). This model predicts that genes of different ages, that is, genes with homologs detectable at different phylogenetic depths, substantially differ in those variables that correlate with PGL. We computationally partition protein-coding genes from humans, flies, and Aspergillus fungus into age classes, and show that genes of different ages retain the universal log-normal distribution of evolutionary rates, with a shift toward higher rates in ''younger'' classes but also with a substantial overlap. The only exception involves human primate-specific genes that show a heavy tail of rapidly evolving genes, probably owing to gene annotation artifacts. As predicted, the gene age classes differ in characteristics correlated with PGL. Compared with ''young'' genes (e.g., mammal-specific human ones), ''old'' genes (e.g., eukaryotespecific), on average, are longer, are expressed at a higher level, possess a higher intron density, evolve slower on the short time scale, and are subject to stronger purifying selection. Thus, genome evolution fits a simple model with approximately uniform rates of gene gain and loss, without major bursts of genomic innovation.gene age ͉ gene expression ͉ genome evolution ͉ intron density

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“…First, one classical problem of metagenomics and metatranscriptomics-based gene targeting is the difficulty of assigning observed functions to specific taxa (Dutilh et al 2007). However, recent increases in obtainable sequence read length and assembled fragments have resulted in major improvements.…”

Section: Pitfalls To Current Multi-omics Methods and Ways Around The mentioning

confidence: 99%

The multi-omics promise in context: from sequence to microbial isolate

Gutleben

Mares

Elsas

et al. 2017

Critical Reviews in Microbiology

176

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The numbers and diversity of microbes in ecosystems within and around us is unmatched, yet most of these microorganisms remain recalcitrant to in vitro cultivation. Various high-throughput molecular techniques, collectively termed multi-omics, provide insights into the genomic structure and metabolic potential as well as activity of complex microbial communities. Nonetheless, pure or defined cultures are needed to (1) decipher microbial physiology and thus test multiomics-based ecological hypotheses, (2) curate and improve database annotations and (3) realize novel applications in biotechnology. Cultivation thus provides context. In turn, we here argue that multi-omics information awaits integration into the development of novel cultivation strategies. This can build the foundation for a new era of omics information-guided microbial cultivation technology and reduce the inherent trial-and-error search space. This review discusses how information that can be extracted from multi-omics data can be applied for the cultivation of hitherto uncultured microorganisms. Furthermore, we summarize groundbreaking studies that successfully translated information derived from multi-omics into specific media formulations, screening techniques and selective enrichments in order to obtain novel targeted microbial isolates. By integrating these examples, we conclude with a proposed workflow to facilitate future omics-aided cultivation strategies that are inspired by the microbial complexity of the environment. ARTICLE HISTORY

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Assessment of phylogenomic and orthology approaches for phylogenetic inference

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 66 publications

References 67 publications

The Biological Big Bang model for the major transitions in evolution

The Biological Big Bang model for the major transitions in evolution

The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages

The multi-omics promise in context: from sequence to microbial isolate

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