New alignment-based sequence extraction software (ALiBaSeq) and its utility for deep level phylogenetics

Alexander Knyshov; Eric R L Gordon; Christiane Weirauch

doi:10.7717/peerj.11019

New alignment-based sequence extraction software (ALiBaSeq) and its utility for deep level phylogenetics

PeerJ. 2021 Mar 31:9:e11019. doi: 10.7717/peerj.11019. eCollection 2021.

Authors

Alexander Knyshov¹, Eric R L Gordon², Christiane Weirauch¹

Affiliations

¹ Department of Entomology, University of California, Riverside, Riverside, CA, USA.
² Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA.

Abstract

Despite many bioinformatic solutions for analyzing sequencing data, few options exist for targeted sequence retrieval from whole genomic sequencing (WGS) data with the ultimate goal of generating a phylogeny. Available tools especially struggle at deep phylogenetic levels and necessitate amino-acid space searches, which may increase rates of false positive results. Many tools are also difficult to install and may lack adequate user resources. Here, we describe a program that uses freely available similarity search tools to find homologs in assembled WGS data with unparalleled freedom to modify parameters. We evaluate its performance compared to other commonly used bioinformatics tools on two divergent insect species (>200 My) for which annotated genomes exist, and on one large set each of highly conserved and more variable loci. Our software is capable of retrieving orthologs from well-curated or unannotated, low or high depth shotgun, and target capture assemblies as well or better than other software as assessed by recovering the most genes with maximal coverage and with a low rate of false positives throughout all datasets. When assessing this combination of criteria, ALiBaSeq is frequently the best evaluated tool for gathering the most comprehensive and accurate phylogenetic alignments on all types of data tested. The software (implemented in Python), tutorials, and manual are freely available at https://github.com/AlexKnyshov/alibaseq.

Keywords: Alignment; BLAST; HMMER; OrthoDB; Orthology; Phylogenomics; UCE.

Grants and funding

This work was supported by the National Science Foundation (grant number 1655769 to Christiane Weirauch). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.