scholarly journals Impact of heat and drought stresses on grain nutrient content in chickpea: Genome-wide marker-trait associations for protein, Fe and Zn

2021 ◽  
pp. 104688
Author(s):  
Srinivasan Samineni ◽  
Mahesh D Mahendrakar ◽  
Nidhi shankar ◽  
Avinalappa Hotti ◽  
Uttam Chand ◽  
...  
Keyword(s):  
Nutrient Content ◽  
Genome Wide ◽  
Trait Associations

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 ◽  
...  
Keyword(s):  
Virginia Tech ◽  
Winter Barley ◽  
Genome Wide ◽  
Trait Associations

scholarly journals Genome-wide association study in Japanese females identifies fifteen novel skin-related trait associations

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Chihiro Endo ◽  
Todd A. Johnson ◽  
Ryoko Morino ◽  
Kazuyuki Nakazono ◽  
Shigeo Kamitsuji ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Related Trait ◽  
Trait Associations

scholarly journals Genetic Dissection Uncovers Genome Wide Marker-Trait Associations for Plant Growth, Yield and Yield Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

2021 ◽  
Author(s):  
NITIKA SANDHU ◽  
Amandeep Kaur ◽  
Mehak Sethi ◽  
Satinder Kaur ◽  
Varinderpal Singh ◽  
...  
Keyword(s):  
Plant Growth ◽  
Grain Yield ◽  
Field Experiments ◽  
Agronomic Traits ◽  
Growth Yield ◽  
Snp Markers ◽  
Synthetic Wheat ◽  
Wheat Varieties ◽  
Genome Wide ◽  
Trait Associations

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.

scholarly journals Genome-Wide Association Study Reveals Marker–Trait Associations for Early Vegetative Stage Salinity Tolerance in Rice

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 559
Author(s):  
Ashutosh Kumar Yadav ◽  
Aruna Kumar ◽  
Nitasha Grover ◽  
Ranjith Kumar Ellur ◽  
Haritha Bollinedi ◽  
...  
Keyword(s):  
Salt Tolerance ◽  
Association Study ◽  
Salinity Tolerance ◽  
Genome Wide Association Study ◽  
Genomic Region ◽  
Seedling Stage ◽  
Genome Wide Association ◽  
High Yield ◽  
Genome Wide ◽  
Trait Associations

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.

scholarly journals Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

2021 ◽  
Vol 12 ◽  
Author(s):  
Nitika Sandhu ◽  
Amandeep Kaur ◽  
Mehak Sethi ◽  
Satinder Kaur ◽  
Varinderpal-Singh ◽  
...  
Keyword(s):  
Plant Growth ◽  
Grain Yield ◽  
Field Experiments ◽  
Agronomic Traits ◽  
Growth Yield ◽  
Snp Markers ◽  
Synthetic Wheat ◽  
Wheat Varieties ◽  
Genome Wide ◽  
Trait Associations

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.

scholarly journals A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247824
Author(s):  
Morteza Shabannejad ◽  
Mohammad-Reza Bihamta ◽  
Eslam Majidi-Hervan ◽  
Hadi Alipour ◽  
Asa Ebrahimi
Keyword(s):  
Drought Stress ◽  
Genomic Selection ◽  
Bread Wheat ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Terminal Drought ◽  
Genome Wide ◽  
Best Linear Unbiased ◽  
Terminal Drought Stress ◽  
Trait Associations

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.

scholarly journals The role of gene expression on human sexual dimorphism: too early to call

2020 ◽  
Author(s):  
Eleonora Porcu ◽  
Annique Claringbould ◽  
Kaido Lepik ◽  
Tom G. Richardson ◽  
Federico A. Santoni ◽  
...  
Keyword(s):  
Sexual Dimorphism ◽  
Complex Traits ◽  
Causal Effect ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome ◽  
Specific Trait ◽  
Trait Associations

AbstractThe genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS–associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits.To explore this scenario, we performed a genome-wide analysis of sex-specific whole blood RNA-seq eQTLs from 3,447 individuals. Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-specific cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-specific eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-specific trait-associations. Power analyses using real eQTL- and causal effect sizes showed that millions of samples would be necessary to observe sex-specific trait associations that are fully driven by sex-specific cis-eQTLs. Compensatory effects may further hamper their detection. In line with this observation, we confirmed that the sex-specific trait-associations detected so far are not driven by sex-specific cis-eQTLs.

scholarly journals GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals

2019 ◽  
Vol 48 (D1) ◽  
pp. D927-D932 ◽  
Author(s):  
Dongmei Tian ◽  
Pei Wang ◽  
Bixia Tang ◽  
Xufei Teng ◽  
Cuiping Li ◽  
...  
Keyword(s):  
Genetic Research ◽  
Cultivated Plants ◽  
High Quality ◽  
Japanese Apricot ◽  
Web Interfaces ◽  
Plant Trait ◽  
Genome Wide ◽  
Wide Range ◽  
Trait Ontology ◽  
Trait Associations

Abstract GWAS Atlas (https://bigd.big.ac.cn/gwas/) is a manually curated resource of genome-wide variant-trait associations for a wide range of species. Unlike existing related resources, it features comprehensive integration of a high-quality collection of 75 467 variant-trait associations for 614 traits across 7 cultivated plants (cotton, Japanese apricot, maize, rapeseed, rice, sorghum and soybean) and two domesticated animals (goat and pig), which were manually curated from 254 publications. We integrated these associations into GWAS Atlas and presented them in terms of variants, genes, traits, studies and publications. More importantly, all associations and traits were annotated and organized based on a suite of ontologies (Plant Trait Ontology, Animal Trait Ontology for Livestock, etc.). Taken together, GWAS Atlas integrates high-quality curated GWAS associations for animals and plants and provides user-friendly web interfaces for data browsing and downloading, accordingly serving as a valuable resource for genetic research of important traits and breeding application.

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