A bioinformatic toolkit to simultaneously identify sex and sex‐linked regions. (30th October 2021)

• Record Type: Journal Article
• Authors: Darolti, Iulia; Mank, Judith E.
• Is Part Of: Molecular ecology resources. Volume 22:Number 2(2022)
• Page Start: 455
• Page End: 457
• Publication Date: 2021-10-30
• Subjects: genomics -- non‐model species -- sex chromosomes -- short read sequencing; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.13530
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract : Sex chromosomes are strange things, and often exhibit unusual patterns of diversity, rates of evolution, and gene regulation (Bachtrog et al., 2011, Mank, 2013). These unique features mean that although sex chromosomes are often a relatively small proportion of the genome, they are best identified and assessed separately from the autosomal majority when carrying out genomic analyses. However, identifying and partitioning genomic regions into sex‐linked and autosomal in non‐model species can often be quite difficult. In this issue of Molecular Ecology Resources, Nursyifa et al. (2021) provide a useful method that combines sequencing depth information with clustering models to assign sex to samples at the same time as identifying sex‐linked scaffolds. This method gives robust results even with more challenging or low‐quality data, and thus is particularly promising in studies of non‐model organisms.