Futschik, A. | Search bioRxiv

bioRxiv2018

Length asymmetry and heterozygosity strongly influences the evolution of poly-A microsatellites at meiotic recombination hotspots

Meiotic recombination has strong, but poorly understood, effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products to characterize the transmission and evolution of polymorphic poly-A repeats at a human recombination hotspot. We show that length asymmetry between heterozygous poly-As plays a key role in the recombination outcome and their transmission. A difference of 10 As (9A/19A) elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, asymmetry also influences STR transmission: the shorter allele is transmitted more frequently (deletion bias) at the asymmetric STR (9A/19A), while the longer allele is favored (insertion bias) at the site with a small STR length difference (6A/7A). Finally, potentially due to this opposing insertion/deletion driven evolution, we find that poly-As are enriched at human recombination hotspots predominantly with short poly-As, possibly influencing open chromatin regions that in turn can activate hotspots.

evolutionary biology↗

bioRxiv2017

LDJump: Estimating Variable Recombination Rates from Population Genetic Data

As recombination plays an important role in evolution, its estimation, as well as, the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating historical recombination along a chromosome that involves a sequential multiscale change point estimator. Our method also permits to take demography into account. It uses a composite likelihood estimate and other 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 from https://github.com/PhHermann/LDJump.

bioinformatics↗