Genomic prediction and genome-wide association studies of flour yield and alveograph quality traits using advanced winter wheat breeding material

dc.creatorKristensen, P.S.
dc.creatorJensen, J.
dc.creatorAndersen, J.P.
dc.creatorGuzman, C.
dc.creatorOrabi, J.
dc.creatorJahoor, A.
dc.date2019-12-16T15:09:39Z
dc.date2019-12-16T15:09:39Z
dc.date2019
dc.date.accessioned2023-07-17T20:05:10Z
dc.date.available2023-07-17T20:05:10Z
dc.identifier2073-4425
dc.identifierhttps://hdl.handle.net/10883/20547
dc.identifier10.3390/genes10090669
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7512358
dc.descriptionUse of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines.
dc.descriptionart. 669
dc.formatPDF
dc.languageEnglish
dc.publisherMDPI
dc.relationhttps://www.mdpi.com/2073-4425/10/9/669/s1
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dc.rightsOpen Access
dc.source9
dc.source10
dc.sourceGenes
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectWHEAT
dc.subjectPLANT BREEDING
dc.subjectBAKING CHARACTERISTICS
dc.subjectFLOURS
dc.subjectMARKER-ASSISTED SELECTION
dc.titleGenomic prediction and genome-wide association studies of flour yield and alveograph quality traits using advanced winter wheat breeding material
dc.typeArticle
dc.typePublished Version
dc.coverageBasel (Switzerland)


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