Nematode gene annotation by machine-learning-assisted proteotranscriptomics enables proteome-wide evolutionary analysis

Abstract

Nematodes encompass more than 24,000 described species, which were discovered in almost every ecological habitat, and make up >80% of metazoan taxonomic diversity in soils. The last common ancestor of nematodes is believed to date back to ∼650–750 million years, generating a large and phylogenetically diverse group to be explored. However, for most species high-quality gene annotations are incomprehensive or missing. Combining short-read RNA sequencing with mass spectrometry–based proteomics and machine-learning quality control in an approach called proteotranscriptomics, we improve gene annotations for nine genome-sequenced nematode species and provide new gene annotations for three additional species without genome assemblies. Emphasizing the sensitivity of our methodology, we provide evidence for two hitherto undescribed genes in the model organismCaenorhabditis elegans. Extensive phylogenetic systems analysis using this comprehensive proteome annotation provides new insights into evolutionary processes of this metazoan group.

AlexandrusPS: A User-Friendly Pipeline for the Automated Detection of Orthologous Gene Clusters and Subsequent Positive Selection Analysis

“…We successfully applied AlexandrusPS to protein-coding genes on a genome scale to investigate positive selection in a phylogeny of 12 nematode species and obtained highly interesting results ( Ceron-Noriega et al 2023 ). We believe that this implementation will empower many more researchers to explore positive selection in any species of interest.…”

“…With this methodology, we enable increasingly efficient processing of large volumes of OGCs with augmenting amounts of available CPUs, making the pipeline optimally adjusted to run in HPC environments. We used AlexandrusPS for a positive selection analysis, including three of the nematode proteotranscriptomes ( Caenorhabditis elegans , Caenorhabditis briggsae , and Caenorhabditis inopinata ) established in Ceron-Noriega et al (2023) on a tabletop PC with 20 CPUs and on an HPC system with 128 CPUs and could reduce computation time from 12.3 to 2.5 h, emphasizing the added value of using the pipeline on an HPC.…”

“…AlexandrusPS was successfully applied to perform a large-scale positive selection analysis using proteotranscriptomics data across 12 nematode species, including 77,000 protein sequences, resulting in 5,400 one-to-one orthologous groups, including orthologs from at least 3 species ( Ceron-Noriega et al 2023 ). This extensive phylogenetic analysis was executed on a tabletop PC with a processor of 8 cores/16 hyperthreads (8 Gb RAM each) and finished within 7 days.…”