Identifying chromosomal subpopulations based on their recombination histories advances the study of the genetic basis of phenotypic traits
- Carlos Ruiz-Arenas1,2,7,
- Alejandro Cáceres3,4,5,7,
- Marcos López1,2,
- Dolors Pelegrí-Sisó3,4,5,
- Josefa González6 and
- Juan R. González3,4,5
- 1Genetics Unit, Universitat Pompeu Fabra, Barcelona 08003, Spain;
- 2Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona 08003, Spain;
- 3Instituto de Salud Global de Barcelona, Barcelona 08003, Spain;
- 4Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain;
- 5CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona 08003, Spain;
- 6Institute of Evolutionary Biology (CSIC-UPF), Barcelona 08003, Spain
Abstract
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.
Footnotes
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↵7 Co-first authors.
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.258301.119.
- Received October 16, 2019.
- Accepted October 22, 2020.
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/.
