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

Aline Muyle, Jos Käfer, Niklaus Zemp, Sylvain Mousset, Franck Picard, Gabriel AB Marais
doi: https://doi.org/10.1101/023358
Aline Muyle
1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS/Université Lyon 1, Villeurbanne, France
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  • For correspondence: aline.muyle@univ-lyon1.fr
Jos Käfer
1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS/Université Lyon 1, Villeurbanne, France
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Niklaus Zemp
2ETH Zurich, Institute of Integrative Biology, Universitàtstrasse 16, 8092 ZUrich, Switzerland
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Sylvain Mousset
1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS/Université Lyon 1, Villeurbanne, France
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Franck Picard
1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS/Université Lyon 1, Villeurbanne, France
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Gabriel AB Marais
1Laboratoire de Biométrie et Biologie Evolutive (UMR 5558), CNRS/Université Lyon 1, Villeurbanne, France
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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.

Paper submitted as a Genome Resource.

We 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.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 05, 2016.
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SEX-DETector: a probabilistic approach to uncover sex chromosomes in non-model organisms
Aline Muyle, Jos Käfer, Niklaus Zemp, Sylvain Mousset, Franck Picard, Gabriel AB Marais
bioRxiv 023358; doi: https://doi.org/10.1101/023358
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SEX-DETector: a probabilistic approach to uncover sex chromosomes in non-model organisms
Aline Muyle, Jos Käfer, Niklaus Zemp, Sylvain Mousset, Franck Picard, Gabriel AB Marais
bioRxiv 023358; doi: https://doi.org/10.1101/023358

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