|MOORE, JESSICA - COLORADO STATE UNIVERSITY|
|MANMATHAN, HARISH - COLORADO STATE UNIVERSITY|
|ANDERSON, VICTORIA - COLORADO STATE UNIVERSITY|
|POLAND, JESSE - KANSAS STATE UNIVERSITY|
|HALEY, SCOTT - COLORADO STATE UNIVERSITY|
Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/17/2016
Publication Date: 6/16/2017
Citation: Moore, J.K., Manmathan, H.K., Anderson, V.A., Poland, J.A., Morris, C.F., Haley, S.D. 2017. Improving genomic prediction for pre-harvest sprouting tolerance in wheat by weighting large-effect quantitative trait loci. Crop Science. 57:1315-1324.
Interpretive Summary: Pre-harvest sprouting (PHS) refers to the germination of a wheat kernel in a mature spike prior to harvest. It usually occurs after periods of prolonged rainfall and high humidity. Besides causing a reduction in grain yield, PHS can be detrimental to end-use quality leading to smaller bread loaf volumes or sticky crumb grain. This reduction in yield and quality leads to economic losses for the farmer as well as those in the milling and baking industry. Worldwide, an estimated one billion dollars are lost each year as a result of PHS so reducing PHS carries a significant economic benefit. Improving tolerance to pre-harvest sprouting (PHST) has been a challenge for breeders because of its quantitative inheritance and the laborious and costly phenotyping procedures for reliable assessment. It is also difficult to breed for PHST in winter wheat as the time between harvest and planting is often shorter than the time required to phenotype and make selection decisions for accomplishing PHST. Using molecular markers to screen for PHST would be helpful in addressing this problem. The specific objectives of this research were: i) use genome-wide markers to identify QTL for PHST in an association panel of hard winter wheat genotypes; ii) develop a GS model to predict PHST in winter wheat; iii) determine if modeling kernel color or PHST-QTL as fixed effects could improve prediction accuracy of the genomic specific model, and iv) determine the effect of marker number on model accuracy.
Technical Abstract: Pre-harvest sprouting (PHS) is a major problem in wheat (Triticum aestivum L.) that occurs when grains in a mature spike germinate prior to harvest, resulting in reduced yield, quality, and grain sale price. Improving PHS tolerance (PHST) is a challenge to wheat breeders because it is quantitatively inherited and tedious to score. Genomic selection (GS) is particularly useful for predicting phenotypes that are costly and time-consuming to assess. In our study single nucleotide polymorphism (SNP) markers obtained by genotyping-by-sequencing (GBS) were used to identify significant marker trait associations and develop predictive models for PHST. A panel of 1118 breeding lines and cultivars (genotypes) representative of U.S. Great Plains hard winter wheat germplasm was scored for PHST over multiple years. A genome-wide association approach was used to identify quantitative trait loci (QTL) within the panel. Two primary factors were examined for their influence on model accuracy: the effect of including identified QTL and kernel color as fixed effects in the model, and increasing marker number. Model accuracy did not improve with kernel color information but weighting QTL increased predictive accuracy. Thus, the combination of marker assisted and genomic selection outperformed all other methods. Optimum marker number was reached at 4,000 SNPs. Overall, model accuracies were promising (0.49 to 0.62), confirming effectiveness of GS for predicting PHST in wheat.