Dissecting the Meiotic Recombination Patterns in a Brassica napus Double Haploid Population Using 60K SNP Array

Int J Mol Sci. 2023 Feb 24;24(5):4469. doi: 10.3390/ijms24054469.

Abstract

Meiotic recombination not only maintains the stability of the chromosome structure but also creates genetic variations for adapting to changeable environments. A better understanding of the mechanism of crossover (CO) patterns at the population level is useful for crop improvement. However, there are limited cost-effective and universal methods to detect the recombination frequency at the population level in Brassica napus. Here, the Brassica 60K Illumina Infinium SNP array (Brassica 60K array) was used to systematically study the recombination landscape in a double haploid (DH) population of B. napus. It was found that COs were unevenly distributed across the whole genome, and a higher frequency of COs existed at the distal ends of each chromosome. A considerable number of genes (more than 30%) in the CO hot regions were associated with plant defense and regulation. In most tissues, the average gene expression level in the hot regions (CO frequency of greater than 2 cM/Mb) was significantly higher than that in the regions with a CO frequency of less than 1 cM/Mb. In addition, a bin map was constructed with 1995 recombination bins. For seed oil content, Bin 1131 to 1134, Bin 1308 to 1311, Bin 1864 to 1869, and Bin 2184 to 2230 were identified on chromosomes A08, A09, C03, and C06, respectively, which could explain 8.5%, 17.3%, 8.6%, and 3.9% of the phenotypic variation. These results could not only deepen our understanding of meiotic recombination in B. napus at the population level, and provide useful information for rapeseed breeding in the future, but also provided a reference for studying CO frequency in other species.

Keywords: Brassica 60K array; Brassica napus; CO frequency; crossover; recombination.

MeSH terms

  • Brassica napus* / genetics
  • Chromosome Mapping / methods
  • Genome, Plant
  • Haploidy
  • Plant Breeding
  • Quantitative Trait Loci