Association Mapping of Agronomic QTLs in U.S. Spring Barley Breeding Germplasm

Pauli, Duke; Muehlbauer, Gary J.; Smith, Kevin P.; Cooper, B.; Hole, David; Obert, D. E.; Ullrich, S. E.; Blake, T. K.

doi:10.3835/plantgenome2013.11.0037

Cited by 58 publications

(76 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Marker genotypes were imputed using the expectation maximization algorithm implemented in the rrBLUP package in R (Endelman, 2011). This marker set and genetic map (Muñoz-Amatriaín et al, 2011) have been used in studies of genomewide selection, association mapping, and population genetics of North American barley germplasm (Lorenz et al, 2012;Pauli et al, 2014;Poets et al, 2016). To infer genetic map positions, we first obtained physical and genetic map information on 3072 array-based SNPs developed during the Barley Coordinated Agricultural Project (BCAP) (Close et al, 2009).…”

Section: Training Populationmentioning

confidence: 99%

Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program

Neyhart

Smith

2019

Crop Science

Self Cite

View full text Add to dashboard Cite

Predicting the genetic variance among progeny from a cross—prior to making said cross—would be a valuable metric for plant breeders to discriminate among possible parent combinations. The use of genomewide markers and simulated populations is one proposed method for making such predictions. Our objective was to assess the predictive ability of this method for three relevant quantitative traits within a breeding program regularly using genomewide selection. Using a training population of two‐row barley (Hordeum vulgare L.) lines, we predicted the mean (μ), genetic variance (VG), and superior progeny mean (μSP, mean of the best 10% of lines) of 330,078 possible parent combinations for Fusarium head blight (FHB) severity, heading date, and plant height. Twenty‐seven of these combinations were chosen to develop biparental populations, which were subsequently phenotyped for the same traits. We found that the predictive abilities (rMP) for μ and μSP were moderate to high (rMP = 0.46–0.69), whereas those for VG were lower (rMP = 0.01–0.48). Unsurprisingly, predictive ability was likely a function of trait heritability, as rMP estimates for heading date (the most heritable trait) were highest, and rMP estimates for FHB severity (the least heritable trait) were lowest. We observed strong negative bias when predicting VG (on average −83 to −96%), but the relative consistency of this bias across validation families indicates that it may have little impact when selecting crosses. We concluded that accurate predictions of VG and μSP are feasible, but as with any implementation of genomewide selection, reliable phenotypic data are critical.

show abstract

Section: Training Populationmentioning

confidence: 99%

Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program

Neyhart

Smith

2019

Crop Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…Fusarium head blight (FHB), caused primarily by Fusarium graminearum Schwabe, is one of the most serious diseases of barley in the midwestern United States. Yield in barley, as in other crops, is a complex trait that is controlled by many loci across the genome (Hayes et al, 1993;Zhu et al, 1999;Pauli et al, 2014). Resistance to FHB and DON concentration is quantitatively inherited, and QTL associated with these traits have been identified on all barley chromosomes (de la Pena et al, 1999;Ma et al, 2000;Mesfin et al, 2003;Dahleen et al, 2003;Massman et al, 2011).…”

Section: Genomic Selection Performs Similarly To Phenotypic Selectionmentioning

confidence: 99%

Genomic Selection Performs Similarly to Phenotypic Selection in Barley

Sallam

Smith

2016

Crop Science

Self Cite

View full text Add to dashboard Cite

Genomic selection uses marker‐based predictions to improve and accelerate the breeding process. Numerous studies have investigated the accuracy of genomic predictions; however, few studies have directly compared genomic and phenotypic selection. We compared genomic and phenotypic selection in five sets of selection candidates from a barley breeding program. In each set, about 96 breeding lines were genotyped with 1536 single nucleotide polymorphism (SNP) markers and phenotyped for yield, Fusarium head blight (FHB) severity, and deoxynivalenol (DON) concentration. A set of 168 lines and the same set of SNP markers were used to train a prediction model and predict the performance of the selection candidates using ridge regression best linear unbiased prediction. The best‐performing 10% of the breeding lines in each selection candidate set were selected using both methods and revaluated in several trials. We found similar significant response to selection using genomic and phenotypic selection for FHB severity and DON concentration, and no significant response for yield using either method. For all traits, genomic selection significantly increased genetic similarity compared with the selection candidates. In addition, genomic selection, compared with phenotypic selection, resulted in an increase in the frequency of favorable alleles. Three indirect selection methods for DON concentration, (predicted FHB severity, empirical FHB severity, and predicted DON concentration) performed similarly to direct phenotypic selection for DON, but differed considerably in cost. We conclude that the use of genomic selection for yield and FHB breeding in barley should result in gains from response to selection that are similar to the gains obtained using phenotypic selection, but with a shorter breeding cycle time and lower cost.

show abstract

“…The germplasm studied here is composed of germplasm, which was clustered according to inflorescence type, geographic origin, and breeding history. Previous studies also indicated spike morphology (two‐rowed versus six‐rowed), geographic origin, domestication or breeding history, growth habits and vernalization requirements (winter versus spring) as the major cluster factors of barley germplasm . This study also revealed a considerable level of overlap in ICARDA germplasm with NDSU lines at one end and to Ethiopian breeding lines at the other end.…”

Section: Discussionmentioning

confidence: 98%

Association and genome analyses to propose putative candidate genes for malt quality traits

et al. 2018

View full text Add to dashboard Cite

BACKGROUND We studied the genetics of nine malt quality traits using association genetics in a panel of North Dakota, ICARDA, and Ethiopian barley lines. Grain samples harvested from Bekoji in 2011 and 2012 were used. RESULTS The mapping panel revealed strong population structure explained by inflorescence‐type, geographic origin, and breeding history. North Dakota germplasm were superior in malt quality traits and they can be donors to improve malt quality properties. We identified 106 marker‐trait associations (MTAs) for the nine traits, representing 81 genomic regions across all barley chromosomes. Chromosomes 3H, 5H, and 7H contained most of the MTAs (58.5%). Nearly 18.5% of these genomic regions contained two to three malt quality traits. Within ±250 kb of 81 genomic regions, we recovered 348 barley genes, with some potential impacting malt quality. These include invertase, β‐fructofuranosidase, α‐glucosidase, serine carboxypeptidase, and bidirectional sugar transporter SWEET14‐like protein. Eighteen of these genes were also previously reported in the Hordeum Toolbox, and 17 of them highly expressed during the germination process. CONCLUSION The results from this study invite further follow‐up functional characterization experiments to relate the genes with individual malt quality traits with higher confidence. It also provides germplasm resources for malt barley improvement. © 2018 Society of Chemical Industry

show abstract

Association Mapping of Agronomic QTLs in U.S. Spring Barley Breeding Germplasm

Cited by 58 publications

References 73 publications

Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program

Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program

Genomic Selection Performs Similarly to Phenotypic Selection in Barley

Association and genome analyses to propose putative candidate genes for malt quality traits

Contact Info

Product

Resources

About