Abstract
Gene copy number variation (CNV) is increasingly implicated in control of complex trait networks, particularly in polyploid plants like rapeseed (Brassica napus L.) with an evolutionary history of genome restructuring. Here we performed sequence capture to assay nucleotide variation and CNV in a panel of central flowering time regulatory genes across a species-wide diversity set of 280 B. napus accessions. The genes were chosen based on prior knowledge from Arabidopsis thaliana and related Brassica species. Target enrichment was performed using the Agilent SureSelect technology, followed by Illumina sequencing. A bait (probe) pool was developed based on results of a preliminary experiment with representatives from different B. napus morphotypes. A very high mean target coverage of ~670x allowed reliable calling of CNV, single nucleotide polymorphisms (SNPs) and insertion-deletion (InDel) polymorphisms. No accession exhibited no CNV, and at least one homolog of every gene we investigated showed CNV in some accessions. Some CNV appear more often in specific morphotypes, indicating a role in diversification.
Highlights
Background & SummaryPolyploid genomes present major challenges for DNA sequence analysis due to their high redundancy
Duplications are events where genetic regions are copied to another locus, meaning that the affected region increases in copy number, whereas deletions involve a loss of genetic regions from the genome and decrease the copy number of the genes therein
Changes in the frequency of genes or other genomic loci due to duplications, deletions and homeologous non-reciprocal translocations (HNRTs) are collectively described as copy number variation (CNV)
Summary
Polyploid genomes present major challenges for DNA sequence analysis due to their high redundancy. Changes in the frequency of genes or other genomic loci due to duplications, deletions and HNRTs are collectively described as copy number variation (CNV). Different methodologies have been proposed for the detection of CNVs, either based on hybridization arrays or on next-generation sequencing (NGS) technologies[3] As the latter deliver additional information like SNPs and InDels, they are better suited to unravel causal variants for trait variation[16]. For cost-effective application of DNA resequencing on large panels of genotypes, the sequencing power should be focused on regions of interest, like exomes or groups of genes This can be done by prior enrichment for loci of interest by hybridization with probes or baits, and different commercial solutions are available for this[17]. An accompanying publication describes the biological implications of the data[15]
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