Levy Karin, E. | Search bioRxiv

bioRxiv2020

A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Changes in complex phenotypes, such as pathogenicity levels, trophic lifestyle, and habitat shifts are brought on by multiple genomic changes: sub- and neofunctionalization, loss of function, and levels of gene expression. Thus, detecting the signature of selection in coding sequences and associating it with shifts in phenotypic state can unveil the genes underlying complex traits. Phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. These methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that transitions in phenotypic states have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the SEMG2 gene in polygynandrous species of primates compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from free-living to an endosymbiotic lifestyle.

evolutionary biology↗

bioRxiv2019

MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics

BackgroundMetagenomics is revolutionizing the study of microorganisms and their involvement in biological, biomedical, and geochemical processes, allowing us to investigate by direct sequencing a tremendous diversity of organisms without the need for prior cultivation. Unicellular eukaryotes play essential roles in most microbial communities as chief predators, decomposers, phototrophs, bacterial hosts, symbionts and parasites to plants and animals. Investigating their roles is therefore of great interest to ecology, biotechnology, human health, and evolution. However, the generally lower sequencing coverage, their more complex gene and genome architectures, and a lack of eukaryote-specific experimental and computational procedures have kept them on the sidelines of metagenomics. ResultsMetaEuk is a toolkit for high-throughput, reference-based discovery and annotation of protein-coding genes in eukaryotic metagenomic contigs. It performs fast searches with 6-frame-translated fragments covering all possible exons and optimally combines matches into multi-exon proteins. We used a benchmark of seven diverse, annotated genomes to show that MetaEuk is highly sensitive even under conditions of low sequence similarity to the reference database. To demonstrate MetaEuks power to discover novel eukaryotic proteins in large-scale metagenomic data, we assembled contigs from 912 samples of the Tara Oceans project. MetaEuk predicted >12,000,000 protein-coding genes in eight days on ten 16-core servers. Most of the discovered proteins are highly diverged from known proteins and originate from very sparsely sampled eukaryotic supergroups. ConclusionThe open-source (GPLv3) MetaEuk software (https://github.com/soedinglab/metaeuk) enables large-scale eukaryotic metagenomics through reference-based, sensitive taxonomic and functional annotation.

bioinformatics↗