Nested Association Mapping of Stem Rust Resistance in Wheat Using Genotyping by Sequencing

Abstract

We combined the recently developed genotyping by sequencing (GBS) method with joint mapping (also known as nested association mapping) to dissect and understand the genetic architecture controlling stem rust resistance in wheat (Triticum aestivum). Ten stem rust resistant wheat varieties were crossed to the susceptible line LMPG-6 to generate F6 recombinant inbred lines. The recombinant inbred line populations were phenotyped in Kenya, South Africa, and St. Paul, Minnesota, USA. By joint mapping of the 10 populations, we identified 59 minor and medium-effect QTL (explained phenotypic variance range of 1% - 20%) on 20 chromosomes that contributed towards adult plant resistance to North American Pgt races as well as the highly virulent Ug99 race group. Fifteen of the 59 QTL were detected in multiple environments. No epistatic relationship was detected among the QTL. While these numerous small- to medium-effect QTL are shared among the families, the founder parents were found to have different allelic effects for the QTL. Fourteen QTL identified by joint mapping were also detected in single-population mapping. As these QTL were mapped using SNP markers with known locations on the physical chromosomes, the genomic regions identified with QTL could be explored more in depth to discover candidate genes for stem rust resistance. The use of GBS-derived de novo SNPs in mapping resistance to stem rust shown in this study could be used as a model to conduct similar marker-trait association studies in other plant species.

Fig 1. Distributions for disease coefficient of infection (CI) and their respective transformed datasets for stem rust in each of the four environments.

The Pearson’s correlations are represented as follows: “r1” between the coefficient of infection (CI) values and square root transformed data; and “r2” between the square root transformed data and data adjusted for trial differences. “W” represents the Shapiro-Wilk test statistic between the coefficient of infection (CI) values and square root transformed data.

Fig 2. Segregation distortion of loci across each RIL mapping population.

Chromosome names and the—log(p) value for SNP markers in respective chromosomes for each population is shown.

Fig 3. Number of recombination events per chromosome in the joint map (gray bar) relative to the average number of recombinations per chromosome in all 10 populations.

Fig 4. Chromosomes with APR QTL to stem rust detected by the joint inclusive composite interval mapping (JICIM) method.

Multiple QTL in green color on a given chromosome are hypothesized to be a single QTL.

Fig 5. Heat map of additive effect estimates of alleles contributed by the 10 founder lines at the QTL for resistance to Pgt races.

QTL (columns) are named according to McIntosh et al. [89] with their chromosomal positions after the underscore (_) symbol. The allelic effect estimates for each founder allele (rows) are color coded by increments in the allelic effect estimate (legend). Each block represents the environments where the QTL were detected, as labeled.