Alignment Uncertainty and Genomic Analysis

Wong, Karen M.; Suchard, Marc A.; Huelsenbeck, John P.

doi:10.1126/science.1151532

Cited by 365 publications

(300 citation statements)

References 23 publications

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“…We used Spearman's rank correlation to determine if the following characteristics of the sequence data were correlated with the P values from the LRTs: (i) average GC content at the third position; (ii) average overall GC content; (iii) transition/transversion ratio (kappa); and (iv) d N tree length. The gappiness of an alignment could introduce potential biases in our results (17,18), so we also looked for correlations between the P values from the LRTs and two metrics to assess coverage in our alignments: (i) gap percent (gapPCT), or the sum of the number of gaps in each sequence in an alignment divided by the sum of the total number of sites in all of the sequences in an alignment; and (ii) an alignment quality score (described in SI Text). Only a few of these characteristics of the data were significantly correlated (P < 0.05) with the P values of the LRTs, but all correlations were very weak (range of Spearman's rho = −0.1-0.06, for all tests; Dataset S2).…”

Section: Heterogeneous Patterns Of Molecular Evolution Among Bee Linementioning

confidence: 99%

Genes involved in convergent evolution of eusociality in bees

Woodard

Fischman

Venkat³

et al. 2011

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

202

225

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Eusociality has arisen independently at least 11 times in insects. Despite this convergence, there are striking differences among eusocial lifestyles, ranging from species living in small colonies with overt conflict over reproduction to species in which colonies contain hundreds of thousands of highly specialized sterile workers produced by one or a few queens. Although the evolution of eusociality has been intensively studied, the genetic changes involved in the evolution of eusociality are relatively unknown. We examined patterns of molecular evolution across three independent origins of eusociality by sequencing transcriptomes of nine socially diverse bee species and combining these data with genome sequence from the honey bee Apis mellifera to generate orthologous sequence alignments for 3,647 genes. We found a shared set of 212 genes with a molecular signature of accelerated evolution across all eusocial lineages studied, as well as unique sets of 173 and 218 genes with a signature of accelerated evolution specific to either highly or primitively eusocial lineages, respectively. These results demonstrate that convergent evolution can involve a mosaic pattern of molecular changes in both shared and lineage-specific sets of genes. Genes involved in signal transduction, gland development, and carbohydrate metabolism are among the most prominent rapidly evolving genes in eusocial lineages. These findings provide a starting point for linking specific genetic changes to the evolution of eusociality. social evolution | social insects | sociogenomics | molecular phylogenetics

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Section: Heterogeneous Patterns Of Molecular Evolution Among Bee Linementioning

confidence: 99%

Genes involved in convergent evolution of eusociality in bees

Woodard

Fischman

Venkat³

et al. 2011

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

202

225

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“…Accurate multiple sequence alignment is a fundamental step in recovering a reliable phylogeny (Mullan 2002;Wong et al 2008). In theory, the order in which residues are aligned (i.e., amino-to-carboxy or carboxy-to-amino direction) should yield identical sequence alignments.…”

Section: Effect Of Alignment Orientation On Phylogenetic Supertree Rementioning

confidence: 99%

Reconstructing the Fungal Tree of Life Using Phylogenomics and a Preliminary Investigation of the Distribution of Yeast Prion-Like Proteins in the Fungal Kingdom

2011

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We have used three independent phylogenomic approaches (concatenated alignments, single-, and multigene supertrees) to reconstruct the fungal tree of life (FTOL) using publicly available fungal genomes. This is the first time multi-gene families have been used in fungal supertree reconstruction and permits us to use up to 66% of the 1,001,217 genes in our fungal database. Our analyses show that different phylogenomic datasets derived from varying clustering criteria and alignment orientation do not have a major effect on phylogenomic supertree reconstruction. Overall the resultant phylogenomic trees are relatively congruent with one another and successfully recover the major fungal phyla, subphyla and classes. We find that where incongruences do occur, the inferences are usually poorly supported. Within the Ascomycota phylum, our phylogenies reconstruct monophyletic Saccharomycotina and Pezizomycotina subphyla clades and infer a sister group relationship between these to the exclusion of the Taphrinomycotina. Within the Pezizomycotina subphylum, all three phylogenies infer a sister group relationship between the Leotiomycetes and Sordariomycetes classes. However, there is conflict regarding the relationships with the Dothideomycetes and Eurotiomycetes classes. Within the Basidiomycota phylum, supertrees derived from singleand multi-gene families infer a sister group relationship between the Pucciniomycotina and Agaricomycotina subphyla while the concatenated phylogeny infers a poorly supported relationship between the Agaricomycotina and Ustilagomycotina. The reconstruction of a robust FTOL is important for future fungal comparative analyses. We illustrate this point by performing a preliminary investigation into the phyletic distribution of yeast prion-like proteins in the fungal kingdom.

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“…The interaction between MSA and the accuracy of phylogenetic inference continues to be a major source of bias and uncertainty in phylogenetic and phylogenomic studies (Wong et al 2008; Hossain et al The improved accuracy in pairwise distance estimates carries through to tree inference, with the trees calculated from our pair-HMM inferred distance matrix being more accurate than standard pairwise methods the overwhelming majority of the time, especially at larger evolutionary distances. For closely related sequences, this improvement may be attributable to incorporating indel information, whereas for more distantly related sequences the incorporation of alignment uncertainty is also very important.…”

Section: Discussionmentioning

confidence: 97%

Phylogenetic Tree Estimation With and Without Alignment: New Distance Methods and Benchmarking

Bogusz

Whelan

2016

Syst Biol

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Abstract.-Phylogenetic tree inference is a critical component of many systematic and evolutionary studies. The majority of these studies are based on the two-step process of multiple sequence alignment followed by tree inference, despite persistent evidence that the alignment step can lead to biased results. Here we present a two-part study that first presents PaHMMTree, a novel neighbor joining-based method that estimates pairwise distances without assuming a single alignment. We then use simulations to benchmark its performance against a wide-range of other phylogenetic tree inference methods, including the first comparison of alignment-free distance-based methods against more conventional tree estimation methods. Our new method for calculating pairwise distances based on statistical alignment provides distance estimates that are as accurate as those obtained using standard methods based on the true alignment. Pairwise distance estimates based on the two-step process tend to be substantially less accurate. This improved performance carries through to tree inference, where PaHMM-Tree provides more accurate tree estimates than all of the pairwise distance methods assessed. For close to moderately divergent sequence data we find that the two-step methods using statistical inference, where information from all sequences is included in the estimation procedure, tend to perform better than PaHMM-Tree, particularly full statistical alignment, which simultaneously estimates both the tree and the alignment. For deep divergences we find the alignment step becomes so prone to error that our distance-based PaHMM-Tree outperforms all other methods of tree inference. Finally, we find that the accuracy of alignment-free methods tends to decline faster than standard two-step methods in the presence of alignment uncertainty, and identify no conditions where alignment-free methods are equal to or more accurate than standard phylogenetic methods even in the presence of substantial alignment error. [Alignment-free; distance-based phylogenetics; pair Hidden Markov Models; phylogenetic inference; statistical alignment.]

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Alignment Uncertainty and Genomic Analysis

Cited by 365 publications

References 23 publications

Genes involved in convergent evolution of eusociality in bees

Genes involved in convergent evolution of eusociality in bees

Reconstructing the Fungal Tree of Life Using Phylogenomics and a Preliminary Investigation of the Distribution of Yeast Prion-Like Proteins in the Fungal Kingdom

Phylogenetic Tree Estimation With and Without Alignment: New Distance Methods and Benchmarking

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