Comparing performances of different statistical models and multiple threshold methods in a nested association mapping population of wheat.

Nested association mapping (NAM) populations emerged as a multi-parental strategy that combines the high statistical power of biparental linkage mapping with greater allelic richness of association mapping. Several statistical models have been developed for marker-trait associations (MTAs) in genome-wide association studies (GWAS), which ranges from simple to increasingly complex models. These statistical models vary in their performance for detecting real association with the avoidance of false positives and false negatives.

Association mapping reveals a reciprocal virulence/avirulence locus within diverse US Pyrenophora teres f. maculata isolates.

Background: Spot form net blotch (SFNB) caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata (Ptm) is an economically important disease of barley that also infects wheat. Using genetic analysis to characterize loci in Ptm genomes associated with virulence or avirulence is an important step to identify pathogen effectors that determine compatible (virulent) or incompatible (avirulent) interactions with cereal hosts.

Classification and Regression Models for Genomic Selection of Skewed Phenotypes: A Case for Disease Resistance in Winter Wheat ( L.).

Most genomic prediction models are linear regression models that assume continuous and normally distributed phenotypes, but responses to diseases such as stripe rust (caused by f. sp. tritici) are commonly recorded in ordinal scales and percentages.

Comparison of Single-Trait and Multi-Trait Genome-Wide Association Models and Inclusion of Correlated Traits in the Dissection of the Genetic Architecture of a Complex Trait in a Breeding Program.

Unknown genetic architecture makes it difficult to characterize the genetic basis of traits and associated molecular markers because of the complexity of small effect quantitative trait loci (QTLs), environmental effects, and difficulty in phenotyping. Seedling emergence of wheat ( L.) from deep planting, has a poorly understood genetic architecture, is a vital factor affecting stand establishment and grain yield, and is historically correlated with coleoptile length.

Comparison of genomic selection models for exploring predictive ability of complex traits in breeding programs.

Traits with a complex unknown genetic architecture are common in breeding programs. However, they pose a challenge for selection due to a combination of complex environmental and pleiotropic effects that impede the ability to create mapping populations to characterize the trait's genetic basis. One such trait, seedling emergence of wheat (Triticum aestivum L.