Genomic selection (GS) has revolutionized breeding for quantitative traits in plants, offering potential to optimize resource allocation in breeding programs and increase genetic gain per unit of time. Modern high‐density single nucleotide polymorphism (SNP) arrays comprising up to several hundred thousand markers provide a user‐friendly technology to characterize the genetic constitution of whole populations and for implementing GS in breeding programs. However, GS does not build upon detailed genotype profiling facilitated by maximum marker density. With extensive genome‐wide linkage disequilibrium (LD) being a common characteristic of breeding pools, fewer representative markers from available high‐density genotyping platforms could be sufficient to capture the association between a genomic region and a phenotypic trait. To examine the effects of reduced marker density on genomic prediction accuracy, we collected data on three traits across 2 yr in a panel of 203 homozygous Chinese semiwinter rapeseed ( Brassica napus L.) inbred lines, broadly encompassing allelic variability in the Asian B. napus genepool. We investigated two approaches to selecting subsets of markers: a trait‐dependent strategy based on genome‐wide association study (GWAS) significance thresholds and a trait‐independent method to detect representative tag SNPs. Prediction accuracies were evaluated using cross‐validation with ridge‐regression best linear unbiased predictions (rrBLUP). With semiwinter rapeseed as a model species, we demonstrate that low‐density marker sets comprising a few hundred to a few thousand markers enable high prediction accuracies in breeding populations with strong LD comparable to those achieved with high‐density arrays. Our results are valuable for facilitating routine application of cost‐efficient GS in breeding programs.

Plants in temperate areas evolved vernalisation requirement to avoid pre-winter flowering. In Brassicaceae, a period of extended cold reduces the expression of the flowering inhibitor FLOWERING LOCUS C (FLC) and paves the way for the expression of downstream flowering regulators. As with all polyploid species of the Brassicaceae, the model allotetraploid Brassica napus (rapeseed, canola) is highly duplicated and carries 9 annotated copies of Bna.FLC. To investigate whether these multiple homeologs and paralogs have retained their original function in vernalisation or undergone subfunctionalisation, we compared the expression patterns of all 9 copies between vernalisation-dependent (biennial, winter type) and vernalisation-independent (annual, spring type) accessions, using RT-qPCR with copy-specific primers and RNAseq data from a diversity set. Our results show that only 3 copies – Bna.FLC.A03b, Bna.FLC.A10 and to some extent Bna.FLC.C02 – are differentially expressed between the two growth types, showing that expression of the other 6 copies does not correlate with growth type. One of those 6 copies, Bna.FLC.C03b, was not expressed at all, indicating a pseudogene, while three further copies, Bna.FLC.C03a and Bna.FLC.C09ab, did not respond to cold treatment. Sequence variation at the COOLAIR binding site of Bna.FLC.A10 was found to explain most of the variation in gene expression. However, we also found that Bna.FLC.A10 expression is not fully predictive of growth type.

Combining ability is crucial for parent selection in crop hybrid breeding. Many studies have attempted to provide reliable and quick methods to identify genome regions in parental lines correlating with improved hybrid performance. The local haplotype patterns surrounding densely spaced DNA markers include a large amount of genetic information, and analysis of the relationships between haplotypes and hybrid performance can provide insight into the underlying genome regions which might contribute to enhancing combining ability. Here, we generated 24,403 single-copy, genome-wide SNP loci and calculated the general combining ability (GCA) of 950 hybrids from a diverse panel of 475 pollinators of spring-type canola inbred lines crossed with two testers for days to flowering (DTF) and seed glucosinolate content (GSL). We performed a genome-wide analysis of the haplotypes and detected eight and seven haplotype regions that were significantly associated with the GCA values for DTF and seed GSL, respectively. Additionally, two haplotype blocks containing orthologs of flowering time genes FLOWERING LOCUS T (FT) and FLOWERING LOCUS C (FLC) on chromosome A02 showed additive epistatic interactions influencing flowering time. Moreover, two homoeologous haplotype regions on chromosomes A02 and C02 corresponded to major quantitative trait loci (QTL) for GSL which showed additive effects related to reduction of seed GSL in F1 hybrids. Our study showed that haplotype analysis has the potential to substantially improve the efficiency of hybrid breeding programs.