Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/023358

SEX-DETector: a probabilistic approach to uncover sex chromosomes in non-model organisms

Aline Muyle·Jos Kafer·Niklaus Zemp·Sylvain Mousset·Franck Picard·Gabriel AB Marais
View original source ↗Export metadata ↓

Abstract

Data deposition: During the review process, the SEX-DETector galaxy workflow and associated test datasets are made available on the public galaxy.prabi.fr server. The data as well as the tool interface are visible to anonymous users, but to use them, you should register for an account (\"user Register\"), and import the data library \"SEX-DETector\" (\"Shared Data Data Libraries\") into your history. More instructions can be found in the \"readme\" file in this library. The user manual for SEX-DETector is available here: https://lbbe.univ-lyon1.fr/Download-5251.html?lang=en.\n\nPaper submitted as a Genome Resource.\n\nWe propose a probabilistic framework to infer autosomal and sex-linked genes from RNA-seq data of a cross for any sex chromosome type (XY, ZW, UV). Sex chromosomes (especially the nonrecombining and repeat-dense Y, W, U and V) are notoriously difficult to sequence. Strategies have been developed to obtain partially assembled sex chromosome sequences. However, most of them remain difficult to apply to numerous non-model organisms, either because they require a reference genome, or because they are designed for evolutionarily old systems. Sequencing a cross (parents and progeny) by RNA-seq to study the segregation of alleles and infer sex-linked genes is a cost-efficient strategy, which also provides expression level estimates. However, the lack of a proper statistical framework has limited a broader application of this approach. Tests on empirical data show that our method identifies many more sex-linked genes than existing pipelines, while making reliable inferences for downstream analyses. Simulations suggest few individuals are needed for optimal results. For species with unknown sex-determination system, the method can assess the presence and type (XY versus ZW) of sex chromosomes through a model comparison strategy. The method is particularly well optimised for sex chomosomes of young or intermediate age, which are expected in thousands of yet unstudied lineages. Any organism, including non-model ones for which nothing is known a priori, that can be bred in the lab, is suitable for our method. SEX-DETector is made freely available to the community through a Galaxy workflow.

Source connections

Explore related subjects

GeneticsPreprint

Keep this discovery

BibTeXRIS

Aline Muyle, Jos Kafer, Niklaus Zemp, Sylvain Mousset, Franck Picard, Gabriel AB Marais. 2015-07-27. SEX-DETector: a probabilistic approach to uncover sex chromosomes in non-model organisms. https://doi.org/10.1101/023358

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2016

Rapid evolution of primate type 2 immune response factors linked to asthma susceptibility

Host immunity pathways evolve rapidly in response to antagonism by pathogens. Microbial infections can also trigger excessive inflammation that contributes to diverse autoimmune disorders including asthma, lupus, diabetes, and arthritis. Definitive links between immune system evolution and human autoimmune disease remain unclear. Here we provide evidence that several components of the type 2 immune response pathway have been subject to recurrent positive selection in the primate lineage. Notably, rapid evolution of the central immune regulator IL13 corresponds to a polymorphism linked to asthma susceptibility in humans. We also find evidence of accelerated amino acid substitutions as well as repeated gene gain and loss events among eosinophil granule proteins, which act as toxic antimicrobial effectors that promote asthma pathology by damaging airway tissues. These results support the hypothesis that evolutionary conflicts with pathogens promote tradeoffs for increasingly robust immune responses during animal evolution. Our findings are also consistent with the view that natural selection has contributed to the spread of autoimmune disease alleles in humans.

Genetics↗
bioRxiv2016

Single Cell Expression Data Reveal Human Genes that Escape X-Chromosome Inactivation

Sex chromosomes pose an inherent genetic imbalance between genders. In mammals, one of the females X-chromosomes undergoes inactivation (Xi). Indirect measurements estimate that about 20% of Xi genes completely or partially escape inactivation. The identity of these escapee genes and their propensity to escape inactivation remain unsolved. A direct method for identifying escapees was applied by quantifying differential allelic expression from single cells. RNA-Seq fragments were assigned to informative SNPs which were labeled by the appropriate parental haplotype. This method was applied for measuring allelic specific expression from Chromosome-X (ChrX) and an autosomal chromosome as a control. We applied the protocol for measuring biallelic expression from ChrX to 104 primary fibroblasts. Out of 215 genes that were considered, only 13 genes (6%) were associated with biallelic expression. The sensitivity of escapees' identification was increased by combining SNP mapping for parental diploid genomes together with RNA-Seq from clonal single cells (25 lymphoblasts). Using complementary protocols, referred to as strict and relaxed, we confidently identified 25 and 31escapee genes, respectively. When pooled versions of 30 and 100 cells were used, <50% of these genes were revealed. We assessed the generality of our protocols in view of an escapee catalog compiled from indirect methods. The overlap between the escapee catalog and the genes list from this study is statistically significant (P-value of E-07). We conclude that single cells expression data are instrumental for studying X-inactivation with an improved sensitivity. Finally, our results support the emerging notion of the non-deterministic nature of genes that escape X-chromosome inactivation.

Genetics↗
bioRxiv2016

Frequency of mosaicism points towards mutation-prone early cleavage cell divisions.

It has recently become possible to directly estimate the germ-line de novo mutation (dnm) rate by sequencing the whole genome of father-mother-offspring trios, and this has been conducted in human1-5, chimpanzee6, mice7, birds8 and fish9. In these studies dnms are typically defined as variants that are heterozygous in the offspring while being absent in both parents. They are assumed to have occurred in the germ-line of one of the parents and to have been transmitted to the offspring via the sperm cell or oocyte. This definition assumes that detectable mosaicism in the parent in which the mutation occurred is negligible. However, instances of detectable mosaicism or premeiotic clusters are well documented in humans and other organisms, including ruminants10-12. We herein take advantage of cattle pedigrees to show that as much as [~]30% to [~]50% of dnms present in a gamete may occur during the early cleavage cell divisions in males and females, respectively, resulting in frequent detectable mosaicism and a high rate of sharing of multiple dnms between siblings. This should be taken into account to accurately estimate the mutation rate in cattle and other species.

Genetics↗