Identifying Clusters of High Confidence Homologies in Multiple Sequence Alignments

Abstract

Multiple sequence alignment (MSA) is ubiquitous in evolution and bioinformatics. MSAs are usually taken to be a known and fixed quantity on which to perform downstream analysis despite extensive evidence that MSA accuracy and uncertainty affect results. These errors are known to cause a wide range of problems for downstream evolutionary inference, ranging from false inference of positive selection to long branch attraction artifacts. The most popular approach to dealing with this problem is to remove (filter) specific columns in the MSA that are thought to be prone to error. Although popular, this approach has had mixed success and several studies have even suggested that filtering might be detrimental to phylogenetic studies. We present a graph-based clustering method to address MSA uncertainty and error in the software Divvier (available at https://github.com/simonwhelan/Divvier), which uses a probabilistic model to identify clusters of characters that have strong statistical evidence of shared homology. These clusters can then be used to either filter characters from the MSA (partial filtering) or represent each of the clusters in a new column (divvying). We validate Divvier through its performance on real and simulated benchmarks, finding Divvier substantially outperforms existing filtering software by retaining more true pairwise homologies calls and removing more false positive pairwise homologies. We also find that Divvier, in contrast to other filtering tools, can alleviate long branch attraction artifacts induced by MSA and reduces the variation in tree estimates caused by MSA uncertainty.

A kleptoplastidic dinoflagellate and the tipping point between transient and fully integrated plastid endosymbiosis

“…And third, we reconstructed phylogenies for all haptophyte-derived genes already known from Karenia/Karlodinium to see if any predate the divergence of these hosts. To identify gene transfers with high confidence, we curated a comprehensive database of eukaryotes and prokaryotes and refined all initial phylogenies with recently developed sequence filtering and alignment methods (31)(32)(33). All analyses included RSD transcriptomes that were either cleaned of prey sequences using a P. antarctica transcriptome ("RSDallclean noPhaeo"), or without cleaning ("RSD Temp01").…”

Evolutionary Models for the Diversification of Placental Mammals Across the KPg Boundary

“…Homology errors in alignments will be propagated in all subsequent steps (e.g., phylogeny reconstruction, estimation of divergence dates) and should be avoided. Ongoing efforts to develop new methods to screen genomic alignments (e.g., Ali et al, 2019) for such errors should reduce this source of error moving forward. It is also important for authors to make all gene alignments available so that ad hoc criteria used to exclude genes (or regions thereof) can be evaluated by other researchers.…”

Phylogenomic Insights into the Origin of Primary Plastids

“…To aid in the identification of contaminants and paralogs, several prokaryotic and eukaryotic homologs from reference genomes were added. Gene sets were masked and aligned as specified above, and filtered with Divvier (option '-partial'), which implements an HMM-based parametric model that allows removing residues from alignment columns that lack strong homology evidence (Ali et al 2019). Gene trees were inferred using RAxML v.8.2.4 (Stamatakis 2014) underLG+G4 and 100 rapid bootstrap replicates; visualized for the identification of obvious paralogs and contaminants, which were removed along with duplicated taxa from the original (pre-PREQUAL) orthologus sets.…”

“…To understand the effect of alignment filtering in resolving the eukaryotic tree, we performed an empirical comparison between: (i) untrimmed data, (ii) the probabilistic algorithm Divvier (Ali et al 2019), and (iii) BMGE, a commonly used block trimming method. In agreement with Tan et al (2015), we found that untrimmed gene alignments retained more phylogenetic signal (lower nRF to the concatenated tree) than blocktrimmed alignments ( Supplementary Fig.…”