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Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits
Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706724/ https://www.ncbi.nlm.nih.gov/pubmed/33203765 http://dx.doi.org/10.1101/gr.258301.119 |
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author | Ruiz-Arenas, Carlos Cáceres, Alejandro López, Marcos Pelegrí-Sisó, Dolors González, Josefa González, Juan R. |
author_facet | Ruiz-Arenas, Carlos Cáceres, Alejandro López, Marcos Pelegrí-Sisó, Dolors González, Josefa González, Juan R. |
author_sort | Ruiz-Arenas, Carlos |
collection | PubMed |
description | Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits. |
format | Online Article Text |
id | pubmed-7706724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77067242021-06-01 Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits Ruiz-Arenas, Carlos Cáceres, Alejandro López, Marcos Pelegrí-Sisó, Dolors González, Josefa González, Juan R. Genome Res Method Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits. Cold Spring Harbor Laboratory Press 2020-12 /pmc/articles/PMC7706724/ /pubmed/33203765 http://dx.doi.org/10.1101/gr.258301.119 Text en © 2020 Ruiz-Arenas et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Method Ruiz-Arenas, Carlos Cáceres, Alejandro López, Marcos Pelegrí-Sisó, Dolors González, Josefa González, Juan R. Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title | Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title_full | Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title_fullStr | Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title_full_unstemmed | Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title_short | Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
title_sort | identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706724/ https://www.ncbi.nlm.nih.gov/pubmed/33203765 http://dx.doi.org/10.1101/gr.258301.119 |
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