Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping

2012 ◽  
Vol 126 (3) ◽  
pp. 693-710 ◽  
Author(s):  
Gregory L. Berger ◽  
Shuyu Liu ◽  
Marla D. Hall ◽  
Wynse S. Brooks ◽  
Shiaoman Chao ◽  
...  
2015 ◽  
Vol 134 (1) ◽  
pp. 28-39 ◽  
Author(s):  
Inka Gawenda ◽  
Patrick Thorwarth ◽  
Torsten Günther ◽  
Frank Ordon ◽  
Karl J. Schmid

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Chihiro Endo ◽  
Todd A. Johnson ◽  
Ryoko Morino ◽  
Kazuyuki Nakazono ◽  
Shigeo Kamitsuji ◽  
...  

2021 ◽  
Author(s):  
NITIKA SANDHU ◽  
Amandeep Kaur ◽  
Mehak Sethi ◽  
Satinder Kaur ◽  
Varinderpal Singh ◽  
...  

Abstract Nitrogen is one of the most important macronutrients for crop growth and metabolism. To identify marker-trait associations for complex NUE-related agronomic traits, field experiments were conducted on nested synthetic wheat introgression libraries at three nitrogen input levels across two seasons. The introgression libraries were genotyped using the 35K Axiom® Wheat Breeder’s Array and genetic diversity and population structure were examined. Significant phenotypic variation was observed across genotypes, treatments and their interactions across seasons for all the 22 traits measured. Significant positive correlations were observed among grain yield and yield attributing traits and root traits. Across seasons, a total of 233 marker-trait associations (MTAs) associated with fifteen traits of interest at differential levels of nitrogen (N0, N60 and N120) were detected using 9,474 genome-wide single nucleotide polymorphism (SNP) markers. Of these, 45 MTAs for 10 traits in the N0 treatment, 100 MTAs for 11 traits in the N60 treatment and 88 MTAs for 11 traits in the N120 treatment were detected. We identified putative candidate genes underlying the significant MTAs which were associated directly or indirectly with various biological processes, cellular component organization and molecular functions involving improved plant growth and grain yield. In addition, the top 10 lines based on N response and grain yield across seasons and treatments were identified. The identification and introgression of superior alleles/donors improving NUE while maintaining grain yield may open new avenues in designing next-generation nitrogen efficient high yielding wheat varieties.


Plant Disease ◽  
2014 ◽  
Vol 98 (5) ◽  
pp. 599-606 ◽  
Author(s):  
Gregory Berger ◽  
Andrew Green ◽  
Piyum Khatibi ◽  
Wynse Brooks ◽  
Luciana Rosso ◽  
...  

Fusarium head blight (FHB), caused by Fusarium graminearum, is one of the most serious diseases impacting the U.S. barley (Hordeum vulgare) industry. The mycotoxin deoxynivalenol (DON), produced by the pathogen, renders grain unmarketable if concentrations exceed threshold values set for end-use markets. Development of cultivars with improved FHB resistance and reduced DON accumulation is necessary to ensure minimal losses. Elite hulled and hulless genotypes developed by the Virginia Tech winter barley breeding program were screened in inoculated, mist-irrigated FHB nurseries over 2 years at two locations in Virginia to validate resistance levels over years and locations. Results demonstrated that barley genotypes varied significantly for resistance to FHB and DON accumulation. The hulled ‘Nomini’, hulless ‘Eve’, and hulless line VA06H-48 were consistently resistant across locations to both FHB and DON accumulation. Screening the genotypes with molecular markers on chromosomes 2H and 6H for FHB and DON revealed quantitative trait loci regions which may confer resistance in the Virginia Tech germplasm. Ongoing and future work with mapping populations seeks to identify novel regions for resistance to FHB and DON accumulation unique to the Virginia Tech breeding program.


Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 559
Author(s):  
Ashutosh Kumar Yadav ◽  
Aruna Kumar ◽  
Nitasha Grover ◽  
Ranjith Kumar Ellur ◽  
Haritha Bollinedi ◽  
...  

Rice germplasm is a rich resource for discovering genes associated with salt tolerance. In the current study, a set of 96 accessions were evaluated for seedling stage salinity tolerance and its component traits. Significant phenotypic variation was observed among the genotypes for all the measured traits and eleven accessions with high level of salt tolerance at seedling stage were identified. The germplasm set comprised of three sub-populations and genome-wide association study (GWAS) identified a total of 23 marker–trait associations (MTAs) for traits studied. These MTAs were located on rice chromosomes 1, 2, 5, 6, 7, 9, and 12 and explained the trait phenotypic variances ranging from 13.98 to 29.88 %. Twenty-one MTAs identified in this study were located either in or near the previously reported quantitative trait loci (QTLs), while two MTAs namely, qSDW2.1 and qSNC5 were novel. A total of 18 and 13 putative annotated candidate genes were identified in a genomic region spanning ~200 kb around the MTAs qSDW2.1 and qSNC5, respectively. Some of the important genes underlying the novel MTAs were OsFBA1,OsFBL7, and mTERF which are known to be associated with salinity tolerance in crops. These MTAs pave way for combining salinity tolerance with high yield in rice genotypes through molecular breeding.


2021 ◽  
Vol 12 ◽  
Author(s):  
Nitika Sandhu ◽  
Amandeep Kaur ◽  
Mehak Sethi ◽  
Satinder Kaur ◽  
Varinderpal-Singh ◽  
...  

Nitrogen is one of the most important macronutrients for crop growth and metabolism. To identify marker-trait associations for complex nitrogen use efficiency (NUE)-related agronomic traits, field experiments were conducted on nested synthetic wheat introgression libraries at three nitrogen input levels across two seasons. The introgression libraries were genotyped using the 35K Axiom® Wheat Breeder's Array and genetic diversity and population structure were examined. Significant phenotypic variation was observed across genotypes, treatments, and their interactions across seasons for all the 22 traits measured. Significant positive correlations were observed among grain yield and yield-attributing traits and root traits. Across seasons, a total of 233 marker-trait associations (MTAs) associated with fifteen traits of interest at different levels of nitrogen (N0, N60, and N120) were detected using 9,474 genome-wide single nucleotide polymorphism (SNP) markers. Of these, 45 MTAs for 10 traits in the N0 treatment, 100 MTAs for 11 traits in the N60 treatment, and 88 MTAs for 11 traits in the N120 treatment were detected. We identified putative candidate genes underlying the significant MTAs which were associated directly or indirectly with various biological processes, cellular component organization, and molecular functions involving improved plant growth and grain yield. In addition, the top 10 lines based on N response and grain yield across seasons and treatments were identified. The identification and introgression of superior alleles/donors improving the NUE while maintaining grain yield may open new avenues in designing next generation nitrogen-efficient high-yielding wheat varieties.


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247824
Author(s):  
Morteza Shabannejad ◽  
Mohammad-Reza Bihamta ◽  
Eslam Majidi-Hervan ◽  
Hadi Alipour ◽  
Asa Ebrahimi

The present study aimed to improve the accuracy of genomic prediction of 16 agronomic traits in a diverse bread wheat (Triticum aestivum L.) germplasm under terminal drought stress and well-watered conditions in semi-arid environments. An association panel including 87 bread wheat cultivars and 199 landraces from Iran bread wheat germplasm was planted under two irrigation systems in semi-arid climate zones. The whole association panel was genotyped with 9047 single nucleotide polymorphism markers using the genotyping-by-sequencing method. A number of 23 marker-trait associations were selected for traits under each condition, whereas 17 marker-trait associations were common between terminal drought stress and well-watered conditions. The identified marker-trait associations were mostly single nucleotide polymorphisms with minor allele effects. This study examined the effect of population structure, genomic selection method (ridge regression-best linear unbiased prediction, genomic best-linear unbiased predictions, and Bayesian ridge regression), training set size, and type of marker set on genomic prediction accuracy. The prediction accuracies were low (-0.32) to moderate (0.52). A marker set including 93 significant markers identified through genome-wide association studies with P values ≤ 0.001 increased the genomic prediction accuracy for all traits under both conditions. This study concluded that obtaining the highest genomic prediction accuracy depends on the extent of linkage disequilibrium, the genetic architecture of trait, genetic diversity of the population, and the genomic selection method. The results encouraged the integration of genome-wide association study and genomic selection to enhance genomic prediction accuracy in applied breeding programs.


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