Genome-Wide Association Studies for Pasmo Resistance in Flax (Linum usitatissimum L.)

Abstract

Pasmo is one of the most widespread diseases threatening flax production. To identify genetic regions associated with pasmo resistance (PR), a genome-wide association study was performed on 370 accessions from the flax core collection. Evaluation of pasmo severity was performed in the field from 2012 to 2016 in Morden, MB, Canada. Genotyping-by-sequencing has identified 258,873 single nucleotide polymorphisms (SNPs) distributed on all 15 flax chromosomes. Marker-trait associations were identified using ten different statistical models. A total of 692 unique quantitative trait nucleotides (QTNs) associated with 500 putative quantitative trait loci (QTL) were detected from six phenotypic PR datasets (five individual years and average across years). Different QTNs were identified with various statistical models and from individual PR datasets, indicative of the complementation between analytical methods and/or genotype × environment interactions of the QTL effects. The single-locus models tended to identify large-effect QTNs while the multi-loci models were able to detect QTNs with smaller effects. Among the putative QTL, 67 had large effects (3–23%), were stable across all datasets and explained 32–64% of the total variation for PR in the various datasets. Forty-five of these QTL spanned 85 resistance gene analogs including a large toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (TNL) type gene cluster on chromosome 8. The number of QTL with positive-effect or favorite alleles (NPQTL) in accessions was significantly correlated with PR (R2 = 0.55), suggesting that these QTL effects are mainly additive. NPQTL was also significantly associated with morphotype (R2 = 0.52) and major QTL with positive effect alleles were present in the fiber type accessions. The 67 large effect QTL are suited for marker-assisted selection and the 500 QTL for effective genomic prediction in PR molecular breeding.

Mapping Quantitative Trait Loci onto Chromosome-Scale Pseudomolecules in Flax

“…QTL mapping software tools can detect multiple quantitative trait nucleotides (QTNs) from a small region that may be grouped into the same QTL or a QTN cluster based on the LD between markers [14]. QTNs detected in different populations cannot be grouped based on population-dependent marker LD.…”

“…In all 14 publications reporting flax QTL, only 67 newly reported pasmo QTL and 46 QTNs associated with seed length, seed weight and 1000-seed weight were based on the RCPs [14,30]. Therefore, the mapping of the remaining 200 QTL onto the RCPs was performed.…”

“…46 and 9 in Table 3) [17,26]. [14,30]. Two fusarium wilt QTL [24] were not included because of incomplete information.…”

“…Some co-located QTL may lead to their pleiotropic effects on multiple traits. Thirteen genomic regions that had at least three identical or co-located QTL were observed (yellow highlights in Figure 1 and Table 3) [14,30]. Two fusarium wilt QTL [24] were not included because of incomplete information.…”

“…The resolution of current QTL mapping or GWAS technologies is insufficient to pin QTL to accurate locations of genes or genetic features controlling traits. A simple approach for predicting candidate genes is to investigate the annotated genes in the vicinity of QTL, such as a window of 200 kb flanking the QTL [14,20]. Our ability to position most of the previously reported QTL to the RCPs makes it possible to perform an overall genome-wide candidate gene scan along chromosomes.…”