Skip to Main content Skip to Navigation
Journal articles

Detecting sex-linked genes using genotyped individuals sampled in natural populations

Jos Käfer 1, * Nicolas Lartillot 2 Gabriel a B Marais 1 Franck Picard 3 
* Corresponding author
1 Sexe et évolution
PEGASE - Département PEGASE [LBBE]
3 Statistique en grande dimension pour la génomique
PEGASE - Département PEGASE [LBBE]
Abstract : We propose a method, SDpop, able to infer sex-linkage caused by recombination suppression typical of sex chromosomes. The method is based on the modeling of the allele and genotype frequencies of individuals of known sex in natural populations. It is implemented in a hierarchical probabilistic framework, accounting for different sources of error. It allows statistical testing for the presence or absence of sex chromosomes, and detection of sex-linked genes based on the posterior probabilities in the model. Furthermore, for gametologous sequences, the haplotype and level of nucleotide polymorphism of each copy can be inferred, as well as the divergence between them. We test the method using simulated data, as well as data from both a relatively recent and an old sex chromosome system (the plant Silene latifolia and humans), and show that, for most cases, robust predictions are obtained with 5 to 10 individuals per sex.
Document type :
Journal articles
Complete list of metadata
Contributor : Lauriane Pillet Connect in order to contact the contributor
Submitted on : Friday, June 4, 2021 - 7:37:54 PM
Last modification on : Sunday, September 25, 2022 - 3:53:34 AM
Long-term archiving on: : Sunday, September 5, 2021 - 9:05:01 PM


Files produced by the author(s)





Jos Käfer, Nicolas Lartillot, Gabriel a B Marais, Franck Picard. Detecting sex-linked genes using genotyped individuals sampled in natural populations. Genetics, Genetics Society of America, 2021, 218 (2), ⟨10.1093/genetics/iyab053⟩. ⟨hal-03250679⟩



Record views


Files downloads