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Predicting recombination frequency from map distance
Map distance is one of the key measures in genetics and indicates the expected number of crossovers between two loci. Map distance is estimated from the observed recombination frequency using mapping functions, the most widely used of those, Haldane and Kosambi, being developed at the time when the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981558/ https://www.ncbi.nlm.nih.gov/pubmed/36566319 http://dx.doi.org/10.1038/s41437-022-00585-3 |
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author | Kivikoski, Mikko Rastas, Pasi Löytynoja, Ari Merilä, Juha |
author_facet | Kivikoski, Mikko Rastas, Pasi Löytynoja, Ari Merilä, Juha |
author_sort | Kivikoski, Mikko |
collection | PubMed |
description | Map distance is one of the key measures in genetics and indicates the expected number of crossovers between two loci. Map distance is estimated from the observed recombination frequency using mapping functions, the most widely used of those, Haldane and Kosambi, being developed at the time when the number of markers was low and unobserved crossovers had a substantial effect on the recombination fractions. In contemporary high-density marker data, the probability of multiple crossovers between adjacent loci is negligible and different mapping functions yield the same result, that is, the recombination frequency between adjacent loci is equal to the map distance in Morgans. However, high-density linkage maps contain an interpretation problem: the map distance over a long interval is additive and its association with recombination frequency is not defined. Here, we demonstrate with high-density linkage maps from humans and stickleback fishes that the inverses of Haldane’s and Kosambi’s mapping functions systematically underpredict recombination frequencies from map distance. To remedy this, we formulate a piecewise function that yields more accurate predictions of recombination frequency from map distance. Our results demonstrate that the association between map distance and recombination frequency is context-dependent and without a universal solution. |
format | Online Article Text |
id | pubmed-9981558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-99815582023-03-04 Predicting recombination frequency from map distance Kivikoski, Mikko Rastas, Pasi Löytynoja, Ari Merilä, Juha Heredity (Edinb) Article Map distance is one of the key measures in genetics and indicates the expected number of crossovers between two loci. Map distance is estimated from the observed recombination frequency using mapping functions, the most widely used of those, Haldane and Kosambi, being developed at the time when the number of markers was low and unobserved crossovers had a substantial effect on the recombination fractions. In contemporary high-density marker data, the probability of multiple crossovers between adjacent loci is negligible and different mapping functions yield the same result, that is, the recombination frequency between adjacent loci is equal to the map distance in Morgans. However, high-density linkage maps contain an interpretation problem: the map distance over a long interval is additive and its association with recombination frequency is not defined. Here, we demonstrate with high-density linkage maps from humans and stickleback fishes that the inverses of Haldane’s and Kosambi’s mapping functions systematically underpredict recombination frequencies from map distance. To remedy this, we formulate a piecewise function that yields more accurate predictions of recombination frequency from map distance. Our results demonstrate that the association between map distance and recombination frequency is context-dependent and without a universal solution. Springer International Publishing 2022-12-24 2023-03 /pmc/articles/PMC9981558/ /pubmed/36566319 http://dx.doi.org/10.1038/s41437-022-00585-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kivikoski, Mikko Rastas, Pasi Löytynoja, Ari Merilä, Juha Predicting recombination frequency from map distance |
title | Predicting recombination frequency from map distance |
title_full | Predicting recombination frequency from map distance |
title_fullStr | Predicting recombination frequency from map distance |
title_full_unstemmed | Predicting recombination frequency from map distance |
title_short | Predicting recombination frequency from map distance |
title_sort | predicting recombination frequency from map distance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981558/ https://www.ncbi.nlm.nih.gov/pubmed/36566319 http://dx.doi.org/10.1038/s41437-022-00585-3 |
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