GenErode: a bioinformatics pipeline to investigate genome erosion in endangered and extinct species

BMC Bioinformatics

Marianne Dehasque¹  Love Dalén¹  Johanna von Seth¹  David Díez-del-Molino¹  Nicolas Dussex¹  David W. G. Stanton¹  Edana Lord¹  Payam Emami Khoonsari²  Verena E. Kutschera²  Marcin Kierczak³  Björn Nystedt³  Tom van der Valk³ 

[1] Centre for Palaeogenetics;Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University;Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University;

关键词: Bioinformatics;    Temporal genomic erosion;    Conservation genomics;    Whole genome re-sequencing data;    Endangered species;    Reproducibility;   

DOI  :  10.1186/s12859-022-04757-0

来源: DOAJ

【 摘 要 】

Abstract Background Many wild species have suffered drastic population size declines over the past centuries, which have led to ‘genomic erosion’ processes characterized by reduced genetic diversity, increased inbreeding, and accumulation of harmful mutations. Yet, genomic erosion estimates of modern-day populations often lack concordance with dwindling population sizes and conservation status of threatened species. One way to directly quantify the genomic consequences of population declines is to compare genome-wide data from pre-decline museum samples and modern samples. However, doing so requires computational data processing and analysis tools specifically adapted to comparative analyses of degraded, ancient or historical, DNA data with modern DNA data as well as personnel trained to perform such analyses. Results Here, we present a highly flexible, scalable, and modular pipeline to compare patterns of genomic erosion using samples from disparate time periods. The GenErode pipeline uses state-of-the-art bioinformatics tools to simultaneously process whole-genome re-sequencing data from ancient/historical and modern samples, and to produce comparable estimates of several genomic erosion indices. No programming knowledge is required to run the pipeline and all bioinformatic steps are well-documented, making the pipeline accessible to users with different backgrounds. GenErode is written in Snakemake and Python3 and uses Conda and Singularity containers to achieve reproducibility on high-performance compute clusters. The source code is freely available on GitHub ( https://github.com/NBISweden/GenErode ). Conclusions GenErode is a user-friendly and reproducible pipeline that enables the standardization of genomic erosion indices from temporally sampled whole genome re-sequencing data.

【 授权许可】

Unknown