Genetic Mapping of Quantitative Trait Loci Associated with Important Agronomic Traits in the Spring Wheat (Triticum aestivum L.) Cross ‘Louise’ × ‘Penawawa’

Abstract

Understanding the genetic factors underlying agronomic traits in common wheat (Triticum aestivum L.) is essential to making gains from selection during the breeding process. A set of 188 recombinant inbred lines (RILs) from a ‘Louise’ × ‘Penawawa’ mapping population was grown for two crop years at two locations in the Pacific Northwest region of the United States to identify quantitative trait loci (QTL) associated with seedling growth habit, leaf color, plant height, flowering date, maturity date, grain volume weight, grain protein content, and grain yield. Quantitative trait loci for flowering date and maturity date were associated with the Ppd‐D1 gene for photoperiod insensitivity. Variation in the QTL for plant height was dependent on location and year and localized to chromosome 2D and 3B. A QTL for leaf color was identified on chromosome 2B. Seedling growth habit mapped to chromosome 2D, and a significant QTL for grain volume weight was detected on chromosome 1B. Quantitative trait loci were identified for grain yield; however, some of these QTL were associated with other known QTL for pest resistance, seedling growth habit, or photoperiod insensitivity. Flowering date, maturity date, and plant height were significantly correlated, which resulted from the pleiotropic effects of the Ppd‐D1 gene. The identification of agronomic QTL, and the correlations between and among them, is the first step toward making gains from selection using molecular marker‐assisted selection for these important agronomic traits.

Chromosomes 3B and 4D are associated with several milling and baking quality traits in a soft white spring wheat (Triticum aestivum L.) population

“…The clustering of QTL on chromosome 3B also may be a pleiotropic effect of the grain yield (Carter et al 2011) and grain protein concentration QTL found in the similar region. We detected the well-known negative correlation between grain yield and protein content, although it was moderate in our study.…”

“…Penawawa also is known to carry a null allele for GBSS on chromosome 4A, which makes it a ''partial-waxy'' wheat . These two parents also contrast for other disease and agronomic traits that are discussed elsewhere (Carter et al 2009(Carter et al , 2011.…”

“…A second objective was to use the data previously reported for agronomic traits (Carter et al 2011) to determine genetic correlations among agronomic and quality traits in this population.…”

Past, Present and Future Molecular Approaches to Improve Yield in Wheat

“…For example, molecular markers such as SSR and DArT have been used to detect QTLs for fusarium head blight (FHB) resistance, which can further be implemented in breeding studies [14]. Since 2007, a number of research studies have been taken to identify QTLs related to yield based on diferent mapping populations such as kernel length, kernel width, spike length, spike number, the grain number of spike, sterile spikelet number per spike, fertile spikelet number per spike, and thousand kernel weight [15][16][17][18][19][20][21][22]. However, the development of molecular markers and their applications in breeding have been relatively diicult in wheat because of its three closely related subgenomes and a large genome size consisted of high amounts (80%) of repetitive sequences.…”

On Estimation of Genotypic Correlations and Their Standard Errors by Multivariate REML using the MIXED Procedure of the SAS System

“…One of the purposes of the macros is to provide standard errors of genotypic correlation estimates, which would be cumbersome to derive manually by the so‐called delta method based on a fit of an unstructured variance–covariance structure for genotypic effects. The macros are easy to use and are now widely employed by plant breeders (e.g., see Gustafson and de Leon, 2010; Khanal et al, 2011; Carter et al, 2011).…”