Abstract
As recombination plays an important role in evolution, its estimation and the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating population recombination rates based on genotyping or sequence data that involves a sequential multiscale change point estimator. Our method also permits demography to be taken into account. It uses several summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R‐package LDJump, which is freely available at https://github.com/PhHermann/LDJump.
Highlights
Recombination is a process during meiosis starting with the formation of DNA double-strand breaks (DSBs) and resulting in an exchange of genetic material between homologous chromosomes [Baudat et al, 2013]
We introduced a new method called LDJump to estimate heterogeneous recombination rates along chromosomes from population genetic data
We provide detailed comparisons of our method with the recent reversible jump Markov chain Monte Carlo (MCMC) methods LDhat(2) and LDhelmet as well as the regression based method FastEPRR
Summary
Recombination is a process during meiosis starting with the formation of DNA double-strand breaks (DSBs) and resulting in an exchange of genetic material between homologous chromosomes [Baudat et al, 2013]. The process leads to the formation of new haplotypes and increases the genetic variability in populations. Meiotic recombination is a tightly regulated process dened mostly by a methyltransferase protein called PR domain zinc nger protein 9 (PRDM9) in most mammals (reviewed in [Baudat et al, 2013, Tiemann-Boege et al, 2017]). PRDM9 binds to a certain sequence motif (Myers motif) with its zinc nger array and recruits the DSB machinery (SPO11) to the hotspot (reviewed in [Tiemann-Boege et al, 2017]). Molecular and evolutionary mechanisms of the process of recombination can be better unaCC-BY-NC-ND 4.0 International license
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