2017 journal article
Linkage map construction and QTL analysis for internal heat necrosis in autotetraploid potato
THEORETICAL AND APPLIED GENETICS, 130(10), 2045–2056.
MeSH headings : Chromosome Mapping; Genetic Linkage; Hot Temperature / adverse effects; Necrosis / genetics; Plant Tubers; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Solanum tuberosum / genetics; Tetraploidy
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
A tetraploid potato population was mapped for internal heat necrosis (IHN) using the Infinium ® 8303 potato SNP array, and QTL for IHN were identified on chromosomes 1, 5, 9 and 12 that explained 28.21% of the variation for incidence and 25.3% of the variation for severity. This research represents a significant step forward in our understanding of IHN, and sets the stage for future research focused on testing the utility of these markers in additional breeding populations. Internal heat necrosis (IHN) is a significant non-pathogenic disorder of potato tubers and previous studies have identified AFLP markers linked to IHN susceptibility in the tetraploid, B2721 potato mapping population. B2721 consists of an IHN susceptible×resistant cross: Atlantic×B1829-5. We developed a next-generation SNP-based linkage map of this cross using the Infinium ® 8303 SNP array and conducted additional QTL analyses of IHN susceptibility in the B2721 population. Using SNP dosage sensitive markers, linkage maps for both parents were simultaneously analyzed. The linkage map contained 3427 SNPs and totaled 1397.68 cM. QTL were detected for IHN on chromosomes 1, 5, 9, and 12 using LOD permutation thresholds and colocation of high LOD scores across multiple years. Genetic effects were modeled for each putative QTL. Markers associated with a QTL were regressed in models of effects for IHN incidence and severity for all years. In the full model, the SNP markers were shown to have significant effects for IHN (p < 0.0001), and explained 28.21% of the variation for incidence and 25.3% of the variation for severity. We were able to utilize SNP dosage information to identify and model the effects of putative QTL, and identify SNP loci associated with IHN resistance that need to be confirmed. This research represents a significant step forward in our understanding of IHN, and sets the stage for future research focused on testing the utility of these markers in additional breeding populations.