scholarly journals POPULATION STRUCTURE AND GENOME-WIDE ASSOCIATION ANALYSIS FOR SALINITY TOLERANCE IN BREAD WHEAT USING SNP, SSR AND SCOT MARKER ASSAYS

2020 ◽  
Vol 28 (3) ◽  
pp. 871-884
Author(s):  
Alsamman Alsamman ◽  
S.D. Ibrahim ◽  
Mohamed Rashed ◽  
Ayman Atta ◽  
M.S. Ahmed ◽  
...  
Keyword(s):  
Population Structure ◽  
Bread Wheat ◽  
Association Analysis ◽  
Salinity Tolerance ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Scot Marker ◽  
Genome Wide

scholarly journals Genome-wide association analysis of chickpea germplasms differing for salinity tolerance based on DArTseq markers

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260709
Author(s):  
Shaimaa Mahmoud Ahmed ◽  
Alsamman Mahmoud Alsamman ◽  
Abdulqader Jighly ◽  
Mohamed Hassan Mubarak ◽  
Khaled Al-Shamaa ◽  
...  
Keyword(s):  
Association Analysis ◽  
Salinity Tolerance ◽  
Field Experiments ◽  
Agricultural Research ◽  
Gene Annotation ◽  
Genome Wide Association ◽  
Grain Legume ◽  
Genome Wide Association Analysis ◽  
New Genes ◽  
Genome Wide

Soil salinity is significant abiotic stress that severely limits global crop production. Chickpea (Cicer arietinum L.) is an important grain legume that plays a substantial role in nutritional food security, especially in the developing world. This study used a chickpea population collected from the International Center for Agricultural Research in the Dry Area (ICARDA) genebank using the focused identification of germplasm strategy. The germplasm included 186 genotypes with broad Asian and African origins and genotyped with 1856 DArTseq markers. We conducted phenotyping for salinity in the field (Arish, Sinai, Egypt) and greenhouse hydroponic experiments at 100 mM NaCl concentration. Based on the performance in both hydroponic and field experiments, we identified seven genotypes from Azerbaijan and Pakistan (IGs: 70782, 70430, 70764, 117703, 6057, 8447, and 70249) as potential sources for high salinity tolerance. Multi-trait genome-wide association analysis (mtGWAS) detected one locus on chromosome Ca4 at 10618070 bp associated with salinity tolerance under hydroponic and field conditions. In addition, we located another locus specific to the hydroponic system on chromosome Ca2 at 30537619 bp. Gene annotation analysis revealed the location of rs5825813 within the Embryogenesis-associated protein (EMB8-like), while the location of rs5825939 is within the Ribosomal Protein Large P0 (RPLP0). Utilizing such markers in practical breeding programs can effectively improve the adaptability of current chickpea cultivars in saline soil. Moreover, researchers can use our markers to facilitate the incorporation of new genes into commercial cultivars.

Genome-wide association analysis of resistance to wheat spindle streak mosaic virus in bread wheat

2018 ◽  
Vol 68 (3) ◽  
pp. 609-616 ◽  
Author(s):  
D. Hourcade ◽  
M. Bogard ◽  
M. Bonnefoy ◽  
F. Savignard ◽  
F. Mohamadi ◽  
...  
Keyword(s):  
Mosaic Virus ◽  
Bread Wheat ◽  
Association Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Genome Wide

scholarly journals A Population Structure and Genome‐Wide Association Analysis on the USDA Soybean Germplasm Collection

2015 ◽  
Vol 8 (3) ◽  
Author(s):  
Nonoy Bandillo ◽  
Diego Jarquin ◽  
Qijian Song ◽  
Randall Nelson ◽  
Perry Cregan ◽  
...  
Keyword(s):  
Population Structure ◽  
Association Analysis ◽  
Germplasm Collection ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Soybean Germplasm ◽  
Genome Wide

scholarly journals Population structure and genome-wide association analysis for frost tolerance in oat using continuous SNP array signal intensity ratios

2016 ◽  
Vol 129 (9) ◽  
pp. 1711-1724 ◽  
Author(s):  
Giorgio Tumino ◽  
Roeland E. Voorrips ◽  
Fulvia Rizza ◽  
Franz W. Badeck ◽  
Caterina Morcia ◽  
...  
Keyword(s):  
Population Structure ◽  
Association Analysis ◽  
Signal Intensity ◽  
Snp Array ◽  
Frost Tolerance ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Genome Wide ◽  
Intensity Ratios

scholarly journals Genome-wide association analysis of Mexican bread wheat landraces for resistance to yellow and stem rust

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0246015
Author(s):  
Prashant Vikram ◽  
Deepmala Sehgal ◽  
Achala Sharma ◽  
Sridhar Bhavani ◽  
Priyanka Gupta ◽  
...  
Keyword(s):  
Bread Wheat ◽  
Association Analysis ◽  
Stem Rust ◽  
Principal Component ◽  
Genome Wide Association ◽  
Additive Interaction ◽  
Genome Wide Association Analysis ◽  
Genome Wide ◽  
Core Set ◽  
Wheat Landraces

Deploying under-utilized landraces in wheat breeding has been advocated to accelerate genetic gains in current era of genomics assisted breeding. Mexican bread wheat landraces (Creole wheats) represent an important resource for the discovery of novel alleles including disease resistance. A core set of 1,098 Mexican landraces was subjected to multi-location testing for rust diseases in India, Mexico and Kenya. The landrace core set showed a continuous variation for yellow (YR) and stem rust (SR) disease severity. Principal component analysis differentiated Mexican landraces into three groups based on their respective collection sites. Linkage disequilibrium (LD) decay varied from 10 to 32 Mb across chromosomes with an averge of 23Mb across whole genome. Genome-wide association analysis revealed marker-trait associations for YR resistance in India and Mexico as well as for SR resistance in Kenya. In addition, significant additive-additive interaction effects were observed for both YR and SR resistance including genomic regions on chromosomes 1BL and 3BS, which co-locate with pleiotropic genes Yr29/Lr46/Sr58/Pm39/Ltn2 and Sr2/Yr30/Lr27, respectively. Study reports novel genomic associations for YR (chromosomes 1AL, 2BS, and 3BL) and SR (chromosomes 2AL, 4DS, and 5DS). The novel findings in Creole wheat landraces can be efficiently utilized for the wheat genetic improvement.

scholarly journals Population Structure and Genome‐Wide Association Analysis of Bruchid Resistance in Ethiopian Common Bean Genotypes

Crop Science ◽  
2019 ◽  
Vol 59 (4) ◽  
pp. 1504-1515
Author(s):  
Shiferaw G. Tigist ◽  
Rob Melis ◽  
Julia Sibiya ◽  
Assefa B. Amelework ◽  
Gemechu Keneni ◽  
...  
Keyword(s):  
Population Structure ◽  
Common Bean ◽  
Association Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Bruchid Resistance ◽  
Genome Wide

scholarly journals 10 Can single-step genome-wide association analysis (ssGWAA) account for population structure?

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 9-10
Author(s):  
Enrico Mancin
Keyword(s):  
Population Structure ◽  
Beef Cattle ◽  
Dairy Cattle ◽  
Association Analysis ◽  
Single Step ◽  
Genome Wide Association ◽  
Relationship Matrix ◽  
Cattle Population ◽  
Genome Wide Association Analysis ◽  
Genome Wide

Abstract Several methods are available for genome-wide association analysis, including the classical GWAA (cGWAA) based on fixed, single-SNP regression; efficient mixed-model association expedited (EMMAX) that fits single-SNP regressions together with a relationship matrix to account for population structure; and single-step GWAA (ssGWAA) where all data, including non-genotyped animals, are used. The objectives of this study were to: 1) investigate the ability of ssGWAA to account for population structure and correctly identify quantitative trait nucleotides (QTN); and 2) compare ssGWAA with cGWAA and EMMAX. Three simulated datasets were used, which mimic fish, beef cattle, and dairy cattle populations. The fish population was composed of 2,040 fish, out of which 1,040 were genotyped and had phenotypes for a trait with heritability of 0.25. The beef cattle population had 6,010 animals in the pedigree, but only 1,500 with phenotypes (h2 = 0.35) and genotypes. Lastly, the dairy cattle population had 40,800 pedigreed animals, of which 20,000 females had phenotypes (h2 = 0.32) and 2,400 males were genotyped. All phenotypes, pedigree, and genotypes were used in ssGWAA, whereas only genotypes and phenotypes were used in cGWAA and EMMAX for the fish and beef cattle analyses. For the dairy cattle analysis using the last two methods, deregressed proofs had to be used instead of phenotypes. The ability to correctly identify QTN and the number of statistically significant SNP (P < 0.05/number of SNP) was assessed among methods. In all populations, cGWAA was able to identify some of the strongest QTN but showed a large number of false positives. EMMAX and ssGWAA did not show false associations and correctly identified the top QTN, with more signals observed in ssGWAA. The ssGWAA accounts for population structure and is a proper association method, especially for livestock populations where sparse genotyping is a reality and phenotypes may not be recorded in genotyped animals.

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