Statistics and Truth in Phylogenomics

Kumar, Sudhir; Filipski, Alan; Battistuzzi, Fabia U.; Pond, Sergei L. Kosakovsky; Tamura, Koichiro

doi:10.1093/molbev/msr202

Cited by 241 publications

(216 citation statements)

References 178 publications

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“…After quality filtering, 312 E. coli isolates (221 UPEC and 91 bacteremia isolates) remained in this analysis. Phylogenomic reconstruction (Delsuc et al 2005;Kumar et al 2012) of genomic data was robust (Fig. 1), with likelihood values approaching one for most nodes (Supplemental Fig.…”

Section: Phylogenomic Analysismentioning

confidence: 95%

Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains

Salipante¹,

et al. 2014

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Large-scale bacterial genome sequencing efforts to date have provided limited information on the most prevalent category of disease: sporadically acquired infections caused by common pathogenic bacteria. Here, we performed whole-genome sequencing and de novo assembly of 312 blood-or urine-derived isolates of extraintestinal pathogenic (ExPEC) Escherichia coli, a common agent of sepsis and community-acquired urinary tract infections, obtained during the course of routine clinical care at a single institution. We find that ExPEC E. coli are highly genomically heterogeneous, consistent with pangenome analyses encompassing the larger species. Investigation of differential virulence factor content and antibiotic resistance phenotypes reveals markedly different profiles among lineages and among strains infecting different body sites. We use high-resolution molecular epidemiology to explore the dynamics of infections at the level of individual patients, including identification of possible person-to-person transmission. Notably, a limited number of discrete lineages caused the majority of bloodstream infections, including one subclone (ST131-H30) responsible for 28% of bacteremic E. coli infections over a 3-yr period. We additionally use a microbial genome-wide-association study (GWAS) approach to identify individual genes responsible for antibiotic resistance, successfully recovering known genes but notably not identifying any novel factors. We anticipate that in the near future, whole-genome sequencing of microorganisms associated with clinical disease will become routine. Our study reveals what kind of information can be obtained from sequencing clinical isolates on a large scale, even well-characterized organisms such as E. coli, and provides insight into how this information might be utilized in a healthcare setting.

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Section: Phylogenomic Analysismentioning

confidence: 95%

Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains

Salipante¹,

et al. 2014

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“…Adequately addressing those questions demands phylogenetically informative datasets and computational approaches that can effectively extract information contained in the molecular data (Liu et al, 2015b). Over the past few years, genome-scale sequence data have become increasingly available for phylogenetic studies (Edwards et al, 2007;Casci, 2011;Kumar et al, 2012;Song et al, 2012;Jarvis et al, 2014;Xi et al, 2014). Meanwhile, the complexity of genome-scale data imposes a tremendous challenge on developing probabilistic models to account for heterogeneity of phylogenomic data (Edwards, 2009).…”

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confidence: 99%

Coalescent methods for estimating species trees from phylogenomic data

Liu

2015

J of Sytematics Evolution

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Genome-scale sequence data have become increasingly available in the phylogenetic studies for understanding the evolutionary histories of species. However, it is challenging to develop probabilistic models to account for heterogeneity of phylogenomic data. The multispecies coalescent model describes gene trees as independent random variables generated from a coalescence process occurring along the lineages of the species tree. Since the multispecies coalescent model allows gene trees to vary across genes, coalescent-based methods have been popularly used to account for heterogeneous gene trees in phylogenomic data analysis. In this paper, we summarize and evaluate the performance of coalescent-based methods for estimating species trees from genomescale sequence data. We investigate the effects of deep coalescence and mutation on the performance of species tree estimation methods. We found that the coalescent-based methods perform well in estimating species trees for a large number of genes, regardless of the degree of deep coalescence and mutation. The performance of the coalescent methods is negatively correlated with the lengths of internal branches of the species tree.

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“…For instance, different genes may generate conflicting phylogenetic trees and still show high bootstrap values in combined analyses [10,11]. Thus, it is virtually impossible to detect conflicts among individual genes by relying on a single combined analysis [51,52].…”

Section: Number Of Sitesmentioning

confidence: 99%

“…Phylogenomics, a dream just a few decades ago, is now changing the face of molecular phylogenetics. It is a revolution second only to the introduction of molecules in the field of phylogenetics in the 1960's.However, the availability of large number of sequences is not necessarily associated with an accurate estimation of phylogenies, due to analytical errors associated with very large sets of sequence data [10][11][12]. Hence, the contentious matter of molecular marker sampling is inhibiting this new breakthrough.…”

mentioning

confidence: 99%

Selecting Molecular Markers for a Specific Phylogenetic Problem

Russo¹,

Aguiar²,

Àlex³

et al. 2017

MOJPB

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Submit Manuscript | http://medcraveonline.com of new technologies and the subsequent accessibility of refined methods due to cost reduction contributed to an immeasurable expansion of molecular facilities worldwide [1]. The rate of sequence submission has recently intensified for three primary reasons: the numerous and successful DNA barcoding projects [2,3], the advent of Next Generation Sequencing [4] and the subsequent decrease in prices for molecular sequencing services [5].As a consequence, genetic data repositories such as GenBank have been doubling in size every 18 months [6], rising from 606 sequences in the first 1982 release to close to 200 million sequences in the 218 th release in February 2017. Molecular data from more than 260 thousand nominal species is now widely accepted as a paramount source of biological information in all life sciences [7]. This is an exciting time. Many long existing controversies are in the process of being resolved by an unparalleled amount of data [6,8,9]. Phylogenomics, a dream just a few decades ago, is now changing the face of molecular phylogenetics. It is a revolution second only to the introduction of molecules in the field of phylogenetics in the 1960's.However, the availability of large number of sequences is not necessarily associated with an accurate estimation of phylogenies, due to analytical errors associated with very large sets of sequence data [10][11][12]. Hence, the contentious matter of molecular marker sampling is inhibiting this new breakthrough. Different genes may yield strikingly contradictory topological patterns for a given diversity group [13,14]. Thus, the selection of suitable markers is critical in obtaining accurate estimates, but it is not a straightforward task. In this review, we aim to provide some guidelines for newcomers weighing the suitability of particular molecular markers for a given phylogenetic problem. Homology in Molecular MarkersIn phylogenetic reconstruction, as in comparative biology studies, the single most important concern lies in the matter of homology, a concept that occupies a central position in evolutionary biology [15]. Homology is a qualitative term, defined by equivalence of parts due to inherited common origin [16][17][18].Homology has been more recently defined as the relationship that binds all states of a single character and sets them apart from the states of other characters, supporting the logical equivalence of the notions of homology and synapomorphy (for review see [19]). The comparison of homologous sequences is critical in a phylogenetic analysis, because only homologous characters may reveal the actual phylogenetic pattern.Nevertheless, a number of authors erroneously refer to homology as a synonym for similarity. Molecular biologists are particularly prone to this error, as they assert that 'two sequences share 70% homology' (for reviews on this problem see [15,20]). Two sequences might show 70% similarity, if 7 out of 10 aligned base pairs are identical between them.In molecular sequences, the high...

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Statistics and Truth in Phylogenomics

Cited by 241 publications

References 178 publications

Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains

Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains

Coalescent methods for estimating species trees from phylogenomic data

Selecting Molecular Markers for a Specific Phylogenetic Problem

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