Detecting sex-linked genes using genotyped individuals sampled in natural populations
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/23331 |
Resumo: | 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 |
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7160 |
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Detecting sex-linked genes using genotyped individuals sampled in natural populationssex chromosomespopulation genomicsprobabilistic inferencehierarchical modelWe 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 sexs.n.Repositório da Universidade de LisboaKafer, JosLartillot, NicolasMarais, Gabriel A.B.Picard, Franck2023-02-01T01:30:27Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/23331engKäfer J, Lartillot N, Marais GAB, Picard F. Detecting sex-linked genes using genotyped individuals sampled in natural populations. Genetics. 2021 Jun 24;218(2):iyab05310.1093/genetics/iyab053info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:52:52Zoai:www.repository.utl.pt:10400.5/23331Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:07:35.423750Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
title |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
spellingShingle |
Detecting sex-linked genes using genotyped individuals sampled in natural populations Kafer, Jos sex chromosomes population genomics probabilistic inference hierarchical model |
title_short |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
title_full |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
title_fullStr |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
title_full_unstemmed |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
title_sort |
Detecting sex-linked genes using genotyped individuals sampled in natural populations |
author |
Kafer, Jos |
author_facet |
Kafer, Jos Lartillot, Nicolas Marais, Gabriel A.B. Picard, Franck |
author_role |
author |
author2 |
Lartillot, Nicolas Marais, Gabriel A.B. Picard, Franck |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Kafer, Jos Lartillot, Nicolas Marais, Gabriel A.B. Picard, Franck |
dc.subject.por.fl_str_mv |
sex chromosomes population genomics probabilistic inference hierarchical model |
topic |
sex chromosomes population genomics probabilistic inference hierarchical model |
description |
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 |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z 2023-02-01T01:30:27Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/23331 |
url |
http://hdl.handle.net/10400.5/23331 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Käfer J, Lartillot N, Marais GAB, Picard F. Detecting sex-linked genes using genotyped individuals sampled in natural populations. Genetics. 2021 Jun 24;218(2):iyab053 10.1093/genetics/iyab053 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
s.n. |
publisher.none.fl_str_mv |
s.n. |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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