Analysis of population structure and genetic diversity in low-variance Saimaa ringed seals using low-coverage whole-genome sequence data

• Published in: STAR protocols 2023-12, Vol.4 (4), p.102567-102567, Article 102567
• Main Authors: Olkkonen, Emmi, Löytynoja, Ari
• Format: Article
• Language: English
• Subjects: Animals; Evolutionary Biology; Genetic Variation - genetics; Genome - genetics; Genomics; Genomics - methods; Protocol; Seals, Earless - genetics; Sequence Analysis
• ISSN: 2666-1667; 2666-1667
• DOI: 10.1016/j.xpro.2023.102567

This protocol demonstrates how a fragmented reference genome and low-coverage sequencing data can be efficiently utilized for population genetic analyses of a species with highly reduced genetic diversity. Focusing on endangered Saimaa ringed seals, we detail the steps for data preparation and conventional analyses and then extend the latter by combining genomic and geospatial data. In addition, we introduce coancestry as a measure of genetic identity and describe accessible tools for the quantification of across-genome variation in genetic diversity. For complete details on the use and execution of this protocol, please refer to Löytynoja et al. (2023).1 [Display omitted] •Tailored analyses for low-coverage and low-variance whole-genome variation data•Measurement of genetic similarity by computing coancestry of shared genomic blocks•Approaches for combining and visualizing genomic and geospatial data•An accessible technique for calculation of water distances between samples Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. This protocol demonstrates how a fragmented reference genome and low-coverage sequencing data can be efficiently utilized for population genetic analyses of a species with highly reduced genetic diversity. Focusing on endangered Saimaa ringed seals, we detail the steps for data preparation and conventional analyses and then extend the latter by combining genomic and geospatial data. In addition, we introduce coancestry as a measure of genetic identity and describe accessible tools for the quantification of across-genome variation in genetic diversity.