Accounting For Alignment Uncertainty in Phylogenomics

Wu, Martin; Chatterji, Sourav; Eisen, Jonathan A.

doi:10.1371/journal.pone.0030288

Cited by 178 publications

(158 citation statements)

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“…In spite of a large body of literature investigating the utility of MSA filtering, the particular circumstances under which filtering is beneficial remain ambiguous (Castresana, 2000;Talavera and Castresana, 2007;Schloss, 2010;Penn et al, 2010;Jordan and Goldman, 2012;Privman et al, 2012;Wu et al, 2012;Spielman et al, 2014). Here, we find that masking residues based on biological information regarding protein structure can greatly improve phylogenetic fit ( Table 2), indicating that residue filtering, at least in this circumstance, successfully increased phylogenetic signal.…”

Section: Structurally-aware Msa Strongly Improves Phylogenetic Inferencementioning

confidence: 70%

Comprehensive, structurally-curated alignment and phylogeny of vertebrate biogenic amine receptors

Spielman

Kumar

Wilke

2014

Preprint

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Biogenic amine receptors play critical roles in regulating behavior and physiology, particularly within the central nervous system, in both vertebrates and invertebrates. These receptors belong to the G-protein coupled receptor (GPCR) family and interact with endogenous bioamine ligands, such as dopamine, serotonin, and epinephrine, and they are targeted by a wide array of pharmaceuticals. Despite these receptors' clear clinical and biological importance, their evolutionary history remains poorly characterized. In particular, the relationships among biogenic amine receptors and any specific evolutionary constraints acting within distinct receptor subtypes are largely unknown. To advance and facilitate studies in this receptor family, we have constructed a comprehensive, high-quality, structurally-curated sequence alignment of vertebrate biogenic amine receptors. We demonstrate that aligning GPCR sequences without considering structure produces an alignment with substantial error, whereas a structurally-aware approach greatly improves alignment accuracy. Moreover, we show that phylogenetic inference with our structurally-curated alignment offers dramatic improvements over a structurally-naive alignment. Using the structural alignment and its corresponding phylogeny, we deduce novel biogenic amine receptor relationships and uncover previously unrecognized lineage-specific receptor clades. Moreover, we find that roughly 1% of the 3039 sequences in our final alignment are either misannotated or unclassified, and we propose updated classifications for these receptors. We release our comprehensive alignment and its corresponding phylogeny as a resource for future research into the evolution and diversification of biogenic amine receptors.

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Section: Structurally-aware Msa Strongly Improves Phylogenetic Inferencementioning

confidence: 70%

Comprehensive, structurally-curated alignment and phylogeny of vertebrate biogenic amine receptors

Spielman

Kumar

Wilke

2014

Preprint

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“…Hence, a recent study (Tan et al 2015) suggests that commonly used software for automated filtering alignments decreases single-gene phylogeny accuracy, in contradiction with a previous study (Wu et al 2012). Although more work is needed to solve this point, the filtering is easier to justify in supermatrix phylogenomics, since the increase of stochastic error observed in single-gene phylogeny is naturally overcome when numerous genes are concatenated.…”

Section: Reducing Alignment Errorsmentioning

confidence: 85%

Section: Reducing Alignment Errorsmentioning

confidence: 99%

“…In this strategy, implemented in FSA (Bradley et al 2009), PSAR (Kim & Ma 2011) and ZORRO (Wu et al 2012), alternative alignments used to measure residue-pairing stability are obtained by a probabilistic sampling based on an approximation of the alignment posterior distribution (i.e., the better the alignment, the higher its probability of appearing in the sampling). This approach has the advantage of relying on a well-defined probabilistic framework, to allow for an efficient implementation (since alternative alignments are not built from scratch) and to provide filtered alignments leading to better phylogenies (Wu et al 2012).Most of the above-mentioned methods attribute an elementary score to each residue pairing of the alignment, which can be turned into an elementary score per residue (e.g., using the average score of residue pairings containing a given residue). By considering the score of all residues of a given site, they can attribute a site score as done by Gblocks, but they can also consider the score of all residues in a given sequence.…”

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confidence: 99%

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Pitfalls in supermatrix phylogenomics

Piégay

Vienne

Ranwez

et al. 2017

EJT

104

122

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Abstract. In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted "the end of incongruence", it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here "data errors", it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices European Journal of Taxonomy 283: 1-25 (2017) 2 and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.Keywords. Phylogenomics, supermatrix, systematic error, data quality, incongruence. From phylogenetics to phylogenomicsThe last two decades have seen significant changes taking place in the practice of phylogenetic inference from molecular data. These changes have mostly been triggered by the ever-increasing size of the datasets being assembled and analysed in the form of supermatrices of concatenated genes (Driskell et al. 2004). The evolution of the size and shape of these datasets, thanks to new technological advances in DNA amplification and sequencing, has been associated with different phases in the field of phylogenetic inference ( Fig. 1). In the early days of molecular phylogenetics based on PCR amplification and manual Sanger sequencing of a handful of genes for a limited number of taxa, the field laid somewhat in the "uncertainty zone" dominated by stochastic error, even if some naïve over-interpretations did occur. Then, the development of automated Sanger sequencing typically led to a few standard genes (e.g., SSU rRNA, elongation factors, RNA polymerases) being sequenced for a large number of taxa, projecting the field into the "irresolution zone" with only limited information available to resolve a large number of nodes. Yet, at that time the focus was not on resolving large-scale phylogenetic relationships, rather than on identifying species or strains by molecular means, which eventually gave rise to the field of DNA barcoding (Hebert et al. 2003). The first genome sequences from model organisms reverted the situation, with few taxa being sequenced for their entire set of genes causing a sort of "inconsis...

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“…Maximum likelihood phylogeny was calculated using the RAxML algorithm (Stamatakis, 2006), with the GTR þ G model for nucleotide substitution and empirical base frequencies (Rodriguez et al, 1990). Columns in the final alignment were weighted based on alignment ambiguity using the ZORRO algorithm (Wu et al, 2012), and 50 replicate tree searches were performed to find the optimal tree topology. Node confidence was determined using the rapid bootstrap option in RAxML, with 500 bootstrap replicates.…”

Section: Dna Extractionmentioning

confidence: 99%

Loss in microbial diversity affects nitrogen cycling in soil

et al. 2013

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Microbial communities have a central role in ecosystem processes by driving the Earth's biogeochemical cycles. However, the importance of microbial diversity for ecosystem functioning is still debated. Here, we experimentally manipulated the soil microbial community using a dilution approach to analyze the functional consequences of diversity loss. A trait-centered approach was embraced using the denitrifiers as model guild due to their role in nitrogen cycling, a major ecosystem service. How various diversity metrics related to richness, eveness and phylogenetic diversity of the soil denitrifier community were affected by the removal experiment was assessed by 454 sequencing. As expected, the diversity metrics indicated a decrease in diversity in the 1/10 3 and 1/10 5 dilution treatments compared with the undiluted one. However, the extent of dilution and the corresponding reduction in diversity were not commensurate, as a dilution of five orders of magnitude resulted in a 75% decrease in estimated richness. This reduction in denitrifier diversity resulted in a significantly lower potential denitrification activity in soil of up to 4-5 folds. Addition of wheat residues significantly increased differences in potential denitrification between diversity levels, indicating that the resource level can influence the shape of the microbial diversityfunctioning relationship. This study shows that microbial diversity loss can alter terrestrial ecosystem processes, which suggests that the importance of functional redundancy in soil microbial communities has been overstated.

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Accounting For Alignment Uncertainty in Phylogenomics

Cited by 178 publications

References 49 publications

Comprehensive, structurally-curated alignment and phylogeny of vertebrate biogenic amine receptors

Comprehensive, structurally-curated alignment and phylogeny of vertebrate biogenic amine receptors

Pitfalls in supermatrix phylogenomics

Loss in microbial diversity affects nitrogen cycling in soil

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