Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data

Abstract

Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on e.g. sequence similarity between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here we present Sex Assignment Through Coverage (SATC), a method to identify sample sex and sex-linked scaffolds from NGS data. The method only requires a scaffold level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: i) male and female individuals and ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is open source and freely available at https://github.com/popgenDK/SATC