scholarly journals Genome-Wide Association Mapping and Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize

2019 ◽  
Vol 9 ◽  
Author(s):  
Yibing Yuan ◽  
Jill E. Cairns ◽  
Raman Babu ◽  
Manje Gowda ◽  
Dan Makumbi ◽  
...  
2016 ◽  
Vol 170 (4) ◽  
pp. 2187-2203 ◽  
Author(s):  
Rik Kooke ◽  
Willem Kruijer ◽  
Ralph Bours ◽  
Frank Becker ◽  
André Kuhn ◽  
...  

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ningthaipuilu Longmei ◽  
Gurjit Kaur Gill ◽  
Pervez Haider Zaidi ◽  
Ramesh Kumar ◽  
Sudha Krishnan Nair ◽  
...  

Abstract Background Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. Results An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. Conclusions The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.


Author(s):  
Chalermpol Phumichai ◽  
Pornsak Aiemnaka ◽  
Piyaporn Nathaisong ◽  
Sirikan Hunsawattanakul ◽  
Phasakorn Fungfoo ◽  
...  

2016 ◽  
Vol 213 (3) ◽  
pp. 1346-1362 ◽  
Author(s):  
Manus P. M. Thoen ◽  
Nelson H. Davila Olivas ◽  
Karen J. Kloth ◽  
Silvia Coolen ◽  
Ping-Ping Huang ◽  
...  

2011 ◽  
Vol 44 (1) ◽  
pp. 32-39 ◽  
Author(s):  
Xuehui Huang ◽  
Yan Zhao ◽  
Xinghua Wei ◽  
Canyang Li ◽  
Ahong Wang ◽  
...  

2017 ◽  
Author(s):  
Siraj Ismail Kayondo ◽  
Dunia Pino Del Carpio ◽  
Roberto Lozano ◽  
Alfred Ozimati ◽  
Marnin Wolfe ◽  
...  

AbstractCassava (Manihot esculenta Crantz), a key carbohydrate dietary source for millions of people in Africa, faces severe yield loses due to two viral diseases: cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). The completion of the cassava genome sequence and the whole genome marker profiling of clones from African breeding programs (www.nextgencassava.org) provides cassava breeders the opportunity to deploy additional breeding strategies and develop superior varieties with both farmer and industry preferred traits. Here the identification of genomic segments associated with resistance to CBSD foliar symptoms and root necrosis as measured in two breeding panels at different growth stages and locations is reported. Using genome-wide association mapping and genomic prediction models we describe the genetic architecture for CBSD severity and identify loci strongly associated on chromosomes 4 and 11. Moreover, the significantly associated region on chromosome 4 colocalises with a Manihot glaziovii introgression segment and the significant SNP markers on chromosome 11 are situated within a cluster of nucleotide-binding site leucine-rich repeat (NBS-LRR) genes previously described in cassava. Overall, predictive accuracy values found in this study varied between CBSD severity traits and across GS models with Random Forest and RKHS showing the highest predictive accuracies for foliar and root CBSD severity scores.


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