RecView: an interactive R application for viewing and locating recombination positions using pedigree data

Abstract

Recombination generates new haplotypes and disconnects linked genes thereby increasing the efficiency of selection and the adaptive potential. Quantifying the recombination landscape, i.e., the recombination rate variation along chromosomes, is important for understanding how evolutionary processes such as selection and drift are acting on genes and chromosomes. Here, we present RecView, an interactive R application, designed to view and locate recombination positions along chromosomes using whole-genome genotype data of a three-generation pedigree. RecView visualises the grandparent-of-origin of all informative alleles along each chromosome of the offspring in the pedigree. It also infers putative recombination positions with two algorithms, one based on change in the proportion of the alleles with specific grandparent-of-origin, and one on the degree of continuity of alleles with the same grandparent-of-origin, along the chromosome. Putative recombination positions are given in base pairs together with an estimated error based on the local density of informative alleles. We demonstrate the applicability of RecView using sequencing data of one 120 Mb-large chromosome of one offspring (and its four grandparents and two parents) of a passerine bird, the great reed warbler (Acrocephalus arundinaceus). On this chromosome, we detected five recombination events, three on the paternal chromosome and two on the maternal chromosome with both algorithms. To evaluate how sensitive the analysis is for SNP density, we downsampled our data to 10% of the original dataset. In conclusion, we provide an easy-to-use and highly effective application for viewing and locating recombination positions along chromosomes in small pedigrees. RecView and test data are available on GitHub (https://github.com/HKyleZhang/RecView.git).

Male-biased recombination at chromosome ends in a songbird revealed by precisely mapping crossover positions

“…For viewing and locating crossovers (COs), we used RecView , an R package that we recently developed specifically for segregation analysis of SNPs in three-generation pedigrees (Zhang and Hansson 2023). RecView requires two input files, one providing the order and orientation of the scaffolds of the reference genome, and one providing the genotype data of the individuals.…”

“…RecView requires two input files, one providing the order and orientation of the scaffolds of the reference genome, and one providing the genotype data of the individuals. The genotype files for the autosomes and the Z chromosome were generated by extracting genotypes from the VCF files using vcftools (command: vcftools --gzvcf [vcf file] --extract-FORMAT-info GT --stdout > [output file]), and converting the data using the make_012gt() function in RecView (for a description of the input files, see Zhang and Hansson 2023).…”

“…In the RecView ShinyApp, we seleted the Cumulative Continuity Score (CCS) algorithm with a threshold of 50 (represented with CCS50) to locate the positions of putative COs (for a description of CCS, see Zhang and Hansson 2023). We conducted a manual examination of all CO positions and detected a few artefacts where identical CO positions occurred in more than one offspring and always coincided with scaffold borders.…”

“…To achieve this, we sequenced the genomes of the individuals in the pedigree, mapped the reads to the reference genome of the great reed warbler (Sigeman et al 2021), and called SNPs. Then, we employed the newly developed RecView R package (Zhang and Hansson 2023) to analyse the genome-wide SNP data, allowing us to examine the segregation patterns at each SNP in the pedigree and pinpoint recombination positions between genomic regions inherited from different grandparents. Previous studies have indicated significant heterochiasmy in the great reed warbler, with females exhibiting nearly twice the recombination rate compared to males (Hansson et al 2005; Dawson et al 2007).…”