scholarly journals Genome Wide Association Studies to Dissect Genetic Factors Conferring Sheath Blight Resistance in Rice (Oryza sativa L.)

2021 ◽  
pp. 90-100
Author(s):  
Mahantesh . ◽  
K. Ganesamurthy ◽  
Sayan Das ◽  
R. Saraswathi ◽  
C. Gopalakrishnan ◽  
...  
Keyword(s):  
Association Study ◽  
Linear Model ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Sheath Blight ◽  
Genome Wide Association ◽  
Blight Resistance ◽  
P Value ◽  
Genome Wide ◽  
Sheath Blight Resistance

Rice Sheath blight (ShB) is one of the most serious fungal diseases caused by Rhizoctonia solani. Breeding for sheath blight resistance has been ineffective exercise so far, mainly because of lack of good number of reliable sources of resistance in rice germplasm. In this context our studies indicated that the lines Tetep, Jasmine 85 and MTU 9992 confer resistant to moderately resistant reaction against the pathogen. The current investigation was carried out to dissect the genetic factors governing resistance to sheath blight through genome wide association study (GWAS) from the mapping populations developed by design where in, each of the resistant parents were crossed to three to four highly susceptible parents to generate eleven populations (Jasmine 85XTN1, Jasmine 85XSwarnaSub1, Jasmine 85XII32B, Jasmine 85XIR54, TetepXTN1, TetepXSwarnaSub1, TetepXII32B, TetepXIR54, MTU 9992XTN1, MTU 9992XII32B and MTU 9992XIRBB4). A total of 1545 Recombinant inbred lines (RILs) derived from eleven crosses were used for the study. During rainy 2020 the F7 RILs were screened for their reaction to Sheath blight in two hot spot locations. The genotyping was done with Illumina platform having 6564 SNP markers. Genome wide association study was done with two models Generalized Linear Model (GLM) and Mixed Linear Model (MLM). Results clearly indicate the superiority of MLM over GLM in correcting the population structure. With MLM model, in Jasmine 85 half-sib populations with 565 RILs analyzed, five QTLs (Quantitative Trait Loci) were detected on Chr1, Chr3, Chr9, Chr10 and Chr11 with –log10 (P-Value) more than 3. In TETEP half-sib populations with 714 RILs examined, seven QTLs were observed on Chr1, Chr2, Chr5, Chr6, Chr7, Chr8, and Chr11 with –log10 (P-Value) more than 4. Whereas in MTU 9992 half-sib populations with 266 RILs studied, three novel QTLs were identified on Chr2, Chr6 and Chr11 with –log10 (P-Value) more than 3. Some of these QTLs were reported by researches earlier. In the current research, some novel QTLs were detected in Jasmine 85 (Chr10) and Tetep (Chr2, Chr5 and Chr6) apart from three new QTLs discovered in MTU 9992. The results facilitated to have better understanding of the genetic basis for sheath blight resistance in rice. Pyramiding all the QTL identified so far into a susceptible varieties is complicated affair as resistance is governed by not only several large effect QTLs but also medium to small effect QTLs as well, hence genomic selection approach could be rewarding for breeding for sheath blight resistance.

scholarly journals Identification of genetic factors controlling phosphorus utilization efficiency in wheat by genome-wide association study with principal component analysis

2020 ◽  
Author(s):  
Luqman Bin Safdar ◽  
Muhammad Jawad Umer ◽  
Fakhrah Almas ◽  
Siraj Uddin ◽  
Qurra-tul-Ain Safdar ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Genetic Factors ◽  
Genome Wide Association Study ◽  
Principal Component ◽  
Utilization Efficiency ◽  
Genome Wide Association ◽  
Genome Wide ◽  
P Utilization ◽  
P Utilization Efficiency

ABSTRACTDespite the economic importance of P utilization efficiency, information on genetic factors underlying this trait remains elusive. To address that, we performed a genome-wide association study in a spring wheat diversity panel ranging from landraces to elite varieties. We evaluated the phenotype variation for P utilization efficiency in controlled conditions and genotype variation using wheat 90K SNP array. Phenotype variables were transformed into a smaller set of uncorrelated principal components that captured the most important variation data. We identified two significant loci associated with both P utilization efficiency and the 1st principal component on chromosomes 3A and 4A: qPE1-3A and qPE2-4A. Annotation of genes at these loci revealed 53 wheat genes, among which 6 were identified in significantly enriched pathways. The expression pattern of these 6 genes indicated that TraesCS4A02G481800, involved in pyruvate metabolism and TCA cycle, had a significantly higher expression in the P efficient variety under limited P conditions. Further characterization of these loci and candidate genes can help stimulate P utilization efficiency in wheat.KEY MESSAGEWe report two new loci for P utilization efficiency on chromosomes 3A and 4A of wheat. The prioritized candidate genes at these loci can be investigated by molecular biology techniques to improve P efficiency in wheat and grass relatives.

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 alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112,117)

2017 ◽  
Author(s):  
Toni-Kim Clarke ◽  
Mark J. Adams ◽  
Gail Davies ◽  
David M. Howard ◽  
Lynsey S. Hall ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
P Value ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Overlap

AbstractAlcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well known genetic variants in alcohol metabolizing genes, e.g. ALDH2, ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112,117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 8 independent loci. These include SNPs in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and 2 loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, PXDN, CADM2 and TNFRSF11A. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (CRHR1, DRD2), and genes previously associated with alcohol consumption (AUTS2). GCTA-GREML analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (S.E.=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation between male and female alcohol consumption was 0.73 (S.E.=0.09, p-value = 1.37 x 10−16). Using LD score regression, genetic overlap was found between alcohol consumption and schizophrenia (rG=0.13, S.E=0.04), HDL cholesterol (rG=0.21, S.E=0.05), smoking (rG=0.49, S.E=0.06) and various anthropometric traits (e.g. Overweight, rG=-0.19, S.E.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies 4 novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.

PARALLEL MULTI-PROPOSAL AND MULTI-CHAIN MCMC FOR CALCULATING P-VALUE OF GENOME-WIDE ASSOCIATION STUDY

2013 ◽  
Vol 23 (03) ◽  
pp. 1350008 ◽  
Author(s):  
DI ZHAO ◽  
SHENGHUA NI
Keyword(s):  
Monte Carlo ◽  
Association Study ◽  
High Performance ◽  
Genome Wide Association Study ◽  
Convergence Condition ◽  
Genome Wide Association ◽  
P Value ◽  
The Novel ◽  
Genome Wide ◽  
Multiple Chain

In this paper, by the novel idea of integrating multiple-proposal algorithm and multiple-chain algorithm by parallel computing, we develop a highly efficient sampler for approximating statistical distributions: parallel Multi-proposal and Multi-chain Markov Chain Monte Carlo (pMPMC3), and we illustrate the high performance of this sampler by calculating P-value (odds ratio significance) for Genome Wide Association Study (GWAS). Computational results show that, by setting the convergence condition as the standard deviation of P-value is less than 10−3, pMPMC3 with 4 proposals and 4 chains obtains a convergent P-value within 106 iterations, while the conventional method Monte Carlo simulation does not obtain convergent P-values even in 107 iterations. We also test pMPMC3 by changing the number of chains, the number of proposals and the size of the dataset on a cluster with maximum 600 processes, the algorithm scales well.

scholarly journals Identification of New Resistance Loci Against Sheath Blight Disease in Rice Through Genome-Wide Association Study

Rice Science ◽  
2019 ◽  
Vol 26 (1) ◽  
pp. 21-31 ◽  
Author(s):  
Zongxiang Chen ◽  
Zhiming Feng ◽  
Houxiang Kang ◽  
Jianhua Zhao ◽  
Tianxiao Chen ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Sheath Blight ◽  
Genome Wide Association ◽  
Sheath Blight Disease ◽  
Genome Wide ◽  
Blight Disease

scholarly journals Identification of QTN and Candidate Gene for Seed-flooding Tolerance in Soybean [Glycine max (L.) Merr.] using Genome-Wide Association Study (GWAS)

Genes ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 957 ◽  
Author(s):  
Yu ◽  
Chang ◽  
Lv ◽  
Sharmin ◽  
Wang ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Gene ◽  
Linear Model ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Gene Annotation ◽  
Mixed Linear Model ◽  
Genome Wide Association ◽  
Flooding Tolerance ◽  
Genome Wide

Seed-flooding stress is one of the major abiotic constraints severely affecting soybean yield and quality. Understanding the molecular mechanism and genetic basis underlying seed-flooding tolerance will be of greatly importance in soybean breeding. However, very limited information is available about the genetic basis of seed-flooding tolerance in soybean. The present study performed Genome-Wide Association Study (GWAS) to identify the quantitative trait nucleotides (QTNs) associated with three seed-flooding tolerance related traits, viz., germination rate (GR), normal seedling rate (NSR) and electric conductivity (EC), using a panel of 347 soybean lines and the genotypic data of 60,109 SNPs with MAF > 0.05. A total of 25 and 21 QTNs associated with all three traits were identified via mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) in three different environments (JP14, HY15, and Combined). Among these QTNs, three major QTNs, viz., QTN13, qNSR-10 and qEC-7-2, were identified through both methods MLM and mrMLM. Interestingly, QTN13 located on Chr.13 has been consistently identified to be associated with all three studied traits in both methods and multiple environments. Within the 1.0 Mb physical interval surrounding the QTN13, nine candidate genes were screened for their involvement in seed-flooding tolerance based on gene annotation information and available literature. Based on the qRT-PCR and sequence analysis, only one gene designated as GmSFT (Glyma.13g248000) displayed significantly higher expression level in all tolerant genotypes compared to sensitive ones under flooding treatment, as well as revealed nonsynonymous mutation in tolerant genotypes, leading to amino acid change in the protein. Additionally, subcellular localization showed that GmSFT was localized in the nucleus and cell membrane. Hence, GmSFT was considered as the most likely candidate gene for seed-flooding tolerance in soybean. In conclusion, the findings of the present study not only increase our knowledge of the genetic control of seed-flooding tolerance in soybean, but will also be of great utility in marker-assisted selection and gene cloning to elucidate the mechanisms of seed-flooding tolerance.

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