scholarly journals Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

2019 ◽  
Author(s):  
Waseem Hussain ◽  
Malachy Campbell ◽  
Diego Jarquin ◽  
Harkamal Walia ◽  
Gota Morota
Keyword(s):  
Linear Model ◽  
Bread Wheat ◽  
Generalized Linear Model ◽  
Genome Wide Association Study ◽  
Mean Value ◽  
Genome Wide Association ◽  
Variance Heterogeneity ◽  
Epistatic Interactions ◽  
Genome Wide ◽  
The Mean

AbstractGenome-wide association mapping identifies quantitative trait loci (QTL) that influence the mean differences between the marker genotypes for a given trait. While most loci influence the mean value of a trait, certain loci, known as variance heterogeneity QTL (vQTL) determine the variability of the trait instead of the mean trait value (mQTL). In the present study, we performed a variance heterogeneity genome-wide association study (vGWAS) for grain cadmium (Cd) concentration in bread wheat. We used double generalized linear model and hierarchical generalized linear model to identify vQTL associated with grain Cd. We identified novel vQTL regions on chromosomes 2A and 2B that contribute to the Cd variation and loci that affect both mean and variance heterogeneity (mvQTL) on chromosome 5A. In addition, our results demonstrated the presence of epistatic interactions between vQTL and mvQTL, which could explain variance heterogeneity. Overall, we provide novel insights into the genetic architecture of grain Cd concentration and report the first application of vGWAS in wheat. Moreover, our findings indicated that epistasis is an important mechanism underlying natural variation for grain Cd concentration.

scholarly journals Variance heterogeneity genome‐wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Waseem Hussain ◽  
Malachy T. Campbell ◽  
Diego Jarquin ◽  
Harkamal Walia ◽  
Gota Morota
Keyword(s):  
Bread Wheat ◽  
Variance Heterogeneity ◽  
Epistatic Interactions ◽  
Genome Wide

scholarly journals Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yousef Rahimi ◽  
Mohammad Reza Bihamta ◽  
Alireza Taleei ◽  
Hadi Alipour ◽  
Pär K. Ingvarsson
Keyword(s):  
Bread Wheat ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Wheat Varieties ◽  
Data Set ◽  
Protein Coding ◽  
Genome Wide

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

scholarly journals Exploring the Genetic Architecture of Root-Related Traits in Mediterranean Bread Wheat Landraces by Genome-Wide Association Analysis

Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 613 ◽  
Author(s):  
Rubén Rufo ◽  
Silvio Salvi ◽  
Conxita Royo ◽  
Jose Soriano
Keyword(s):  
Molecular Markers ◽  
Bread Wheat ◽  
Root Development ◽  
Genome Wide Association Study ◽  
Abiotic Stress Tolerance ◽  
Genome Wide Association ◽  
Mediterranean Countries ◽  
Genome Wide ◽  
A Genome ◽  
Wheat Landraces

Background: Roots are essential for drought adaptation because of their involvement in water and nutrient uptake. As the study of the root system architecture (RSA) is costly and time-consuming, it is not generally considered in breeding programs. Thus, the identification of molecular markers linked to RSA traits is of special interest to the breeding community. The reported correlation between the RSA of seedlings and adult plants simplifies its assessment. Methods: In this study, a panel of 170 bread wheat landraces from 24 Mediterranean countries was used to identify molecular markers associated with the seminal RSA and related traits: seminal root angle, total root number, root dry weight, seed weight and shoot length, and grain yield (GY). Results: A genome-wide association study identified 135 marker-trait associations explaining 6% to 15% of the phenotypic variances for root related traits and 112 for GY. Fifteen QTL hotspots were identified as the most important for controlling root trait variation and were shown to include 31 candidate genes related to RSA traits, seed size, root development, and abiotic stress tolerance (mainly drought). Co-location for root related traits and GY was found in 17 genome regions. In addition, only four out of the fifteen QTL hotspots were reported previously. Conclusions: The variability found in the Mediterranean wheat landraces is a valuable source of root traits to introgress into adapted phenotypes through marker-assisted breeding. The study reveals new loci affecting root development in wheat.

scholarly journals Identification of Quantitative Trait Loci for Leaf Rust and Stem Rust Seedling Resistance in Bread Wheat Using a Genome-Wide Association Study

Plants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 74
Author(s):  
Alibek Zatybekov ◽  
Yuliya Genievskaya ◽  
Aralbek Rsaliyev ◽  
Akerke Maulenbay ◽  
Gulbahar Yskakova ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Leaf Rust ◽  
Bread Wheat ◽  
Stem Rust ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

In recent years, leaf rust (LR) and stem rust (SR) have become a serious threat to bread wheat production in Kazakhstan. Most local cultivars are susceptible to these rusts, which has affected their yield and quality. The development of new cultivars with high productivity and LR and SR disease resistance, including using marker-assisted selection, is becoming an important priority in local breeding projects. Therefore, the search for key genetic factors controlling resistance in all plant stages, including the seedling stage, is of great significance. In this work, we applied a genome-wide association study (GWAS) approach using 212 local bread wheat accessions that were phenotyped for resistance to specific races of Puccinia triticina Eriks. (Pt) and Puccinia graminis f. sp. tritici (Pgt) at the seedling stages. The collection was genotyped using a 20 K Illumina iSelect SNP assay, and 11,150 polymorphic SNP markers were selected for the association mapping. Using a mixed linear model, we identified 11 quantitative trait loci (QTLs) for five out of six specific races of Pt and Pgt. The comparison of the results from this GWAS with those from previously published work showed that nine out of eleven QTLs for LR and SR resistance had been previously reported in a GWAS study at the adult plant stages of wheat growth. Therefore, it was assumed that these nine common identified QTLs were effective for all-stage resistance to LR and SR, and the two other QTLs appear to be novel QTLs. In addition, five out of these nine QTLs that had been identified earlier were found to be associated with yield components, suggesting that they may directly influence the field performance of bread wheat. The identified QTLs, including novel QTLs found in this study, may play an essential role in the breeding process for improving wheat resistance to LR and SR.

scholarly journals Genome-wide association study of flowering time reveals complex genetic heterogeneity and epistatic interactions in rice

2020 ◽  
Author(s):  
Chang Liu ◽  
Yuan Tu ◽  
Shiyu Liao ◽  
Xiangkui Fu ◽  
Xingming Lian ◽  
...  
Keyword(s):  
Association Study ◽  
Flowering Time ◽  
Genetic Heterogeneity ◽  
Mixed Models ◽  
Genome Wide Association Study ◽  
Heading Date ◽  
Genome Wide Association ◽  
Epistatic Interactions ◽  
Genome Wide ◽  
Wide Range

AbstractSince domestication, rice has cultivated in a wide range of latitudes with different day lengths. Selection of diverse natural variations in heading date and photoperiod sensitivity is critical for adaptation of rice to different geographical environments. To unravel the genetic architecture underlying natural variation of rice flowering time, we conducted a genome wide association study (GWAS) using several association analysis strategies with a diverse worldwide collection of 529 O. sativa accessions. Heading date was investigated in three environments under long-day or short-day conditions, and photosensitivity was evaluated. By dividing the whole association panel into subpopulations and performing GWAS with both linear mixed models and multi-locus mixed-models, we revealed hundreds of significant loci harboring novel candidate genes as well as most of the known flowering time genes. In total, 127 hotspots were detected in at least two GWAS. Universal genetic heterogeneity was found across subpopulations. We further detected abundant interactions between GWAS loci, especially in indica. Functional gene families were revealed from enrichment analysis of the 127 hotspots. The results demonstrated a rich of genetic interactions in rice flowering time genes and such epistatic interactions contributed to the large portions of missing heritability in GWAS. It suggests the increased complexity of genetic heterogeneity might discount the power of increasing the sample sizes in GWAS.

scholarly journals Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ripa Akter Sharmin ◽  
Benjamin Karikari ◽  
Fangguo Chang ◽  
G.M. Al Amin ◽  
Mashiur Rahman Bhuiyan ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Linear Model ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Mixed Linear Model ◽  
Genome Wide Association ◽  
Flooding Tolerance ◽  
Genome Wide ◽  
Germination Stage

Abstract Background Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage. Results In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation. Conclusions Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

scholarly journals Genome‐wide association study of six quality traits reveals the association of theTaRPP13L1gene with flour colour in Chinese bread wheat

2019 ◽  
Vol 17 (11) ◽  
pp. 2106-2122 ◽  
Author(s):  
Jianhui Chen ◽  
Fuyan Zhang ◽  
Chunjiang Zhao ◽  
Guoguo Lv ◽  
Congwei Sun ◽  
...  
Keyword(s):  
Association Study ◽  
Bread Wheat ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Quality Traits ◽  
Genome Wide ◽  
Flour Colour
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