MRLR: unraveling high-resolution meiotic recombination by linked reads.

Motivation: Meiotic recombination facilitates the transmission of exchanged genetic material between homologous chromosomes and plays a crucial role in increasing the genetic variations in eukaryotic organisms. In humans, thousands of crossover events have been identified by genotyping related family members. However, most of these crossover regions span tens to hundreds of kb, which is not sufficient resolution to accurately identify the crossover breakpoints in a typical trio family.

Results: We have developed MRLR, a software using 10X linked reads to identify crossover events at a high resolution. By reconstructing the gamete genome, MRLR only requires a trio family dataset and can efficiently discover the crossover events. Using MRLR, we revealed a fine-scale pattern of crossover regions in six human families. From the two closest heterozygous alleles around the crossovers, we determined that MRLR achieved a median resolution 4.5 kb. This method can delineate a genome-wide landscape of crossover events at a precise scale, which is important for both functional and genomic features analysis of meiotic recombination.

Availability And Implementation: MRLR is freely available at https://github.com/ChongLab/MRLR, implemented in Perl.

Supplementary Information: Supplementary data are available at Bioinformatics online.