Abstract
Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits. To date, a total of 313 QTL for 31 quantitative traits have been reported in 14 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, the scaffold sequences, or the pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but the most used ones were simple sequence repeats (SSRs) or single nucleotide polymorphisms (SNPs). To uniquely map the SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules, methods with several scripts and database files were developed to locate PCR- and SNP-based markers onto the same reference, co-locate QTL, and scan genome-wide candidate genes. Using these methods, 195 out of 200 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters; the candidate genes that co-located with these QTL clusters were also predicted. The methods and tools presented in this article facilitate marker re-mapping to a new reference, genome-wide QTL analysis, candidate gene scanning, and breeding applications in flax and other crops.
Highlights
Most traits of importance in plant breeding are quantitative and controlled by polygenes with minor effects on phenotypes
quantitative trait loci (QTL) can be identified by two main approaches: linkage mapping (LM) and association mapping (AM) or genome-wide association study (GWAS) [2]
We developed several utility tools, including scripts for mapping PCR- and single nucleotide polymorphisms (SNPs)-based QTL onto the release of the chromosome-scale pseudomolecules (RCPs), grouping QTL in terms of a predefined window size, and performing genome-wide candidate gene analysis
Summary
Most traits of importance in plant breeding are quantitative and controlled by polygenes with minor effects on phenotypes. With the development of molecular markers and high-throughput genotyping techniques, individual polygenic loci on chromosomes and their effects on phenotypes can be detected and estimated using statistical genomics approaches. Such polygenic loci on chromosomes are called quantitative trait loci (QTL). AM uses a more diverse genetic panel to overcome the phenotypic diversity limitation of bi-parental populations This diversity limitation may include natural germplasm collections, or, more often, panels including germplasm accessions and breeding lines, or multi-parent populations such as nested association mapping (NAM) [4,5,6] and multi-parent advanced generation intercross (MAGIC) populations [7,8,9,10]. QTL can be exploited for gene cloning, marker-assisted breeding, and genomic selection or prediction
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