Genetic Dissection of Quantitative Resistance to Common Rust (Puccinia sorghi) in Tropical Maize (Zea mays L.) by Combined Genome-Wide Association Study, Linkage Mapping, and Genomic Prediction

Ren, Jiaojiao; Li, Zhimin; Wu, Penghao; Zhang, Ao; Liu, Yubo; Hu, Guanghui; Cao, Sen; Qu, Jingtao; Dhliwayo, Thanda; Zheng, Hongjian; Olsen, Michael; Prasanna, B. M.; Vicente, Félix San; Zhang, Xuecai

doi:10.3389/fpls.2021.692205

Cited by 22 publications

(24 citation statements)

References 45 publications

(76 reference statements)

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“…In comparison between LD analysis results and other studies, the value of distance was larger than that in other studies. In tropical maize, the average LD decay distance across all 10 chromosomes was 8.14 kb [ 25 ]. In subtropical maize, the average decay distance of the LD across all chromosomes was about 5–10 kb at r 2 = 0.2 [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Dang

Guan²,

Zheng³

et al. 2023

Plants

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Sweet corn and waxy corn has a better taste and higher accumulated nutritional value than regular maize, and is widely planted and popularly consumed throughout the world. Plant height (PH), ear height (EH), and tassel branch number (TBN) are key plant architecture traits, which play an important role in improving grain yield in maize. In this study, a genome-wide association study (GWAS) and genomic prediction analysis were conducted on plant architecture traits of PH, EH, and TBN in a fresh edible maize population consisting of 190 sweet corn inbred lines and 287 waxy corn inbred lines. Phenotypic data from two locations showed high heritability for all three traits, with significant differences observed between sweet corn and waxy corn for both PH and EH. The differences between the three subgroups of sweet corn were not obvious for all three traits. Population structure and PCA analysis results divided the whole population into three subgroups, i.e., sweet corn, waxy corn, and the subgroup mixed with sweet and waxy corn. Analysis of GWAS was conducted with 278,592 SNPs obtained from resequencing data; 184, 45, and 68 significantly associated SNPs were detected for PH, EH, and TBN, respectively. The phenotypic variance explained (PVE) values of these significant SNPs ranged from 3.50% to 7.0%. The results of this study lay the foundation for further understanding the genetic basis of plant architecture traits in sweet corn and waxy corn. Genomic selection (GS) is a new approach for improving quantitative traits in large plant breeding populations that uses whole-genome molecular markers. The marker number and marker quality are essential for the application of GS in maize breeding. GWAS can choose the most related markers with the traits, so it can be used to improve the predictive accuracy of GS.

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Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Dang

Guan²,

Zheng³

et al. 2023

Plants

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“…Two BAG family genes were detected during the GO:0006915//apoptotic process and GO:0015979//photosynthesis. Three genes ( GRMZM5G851490 , GRMZM2G077752 , and GRMZM2G114893 ) were detected during the GO:0006915//apoptotic process and are involved in stem processes, leaf senescence, and resistance to common rust (Puccinia sorghi), respectively, in maize [ 81 , 82 , 83 ].…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Profiling of Alternative Splicing and Gene Fusion during Rice Black-Streaked Dwarf Virus Stress in Maize (Zea mays L.)

Zhou

Zhang

et al. 2022

Genes

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Rice black-streaked dwarf virus (RBSDV) causes maize rough dwarf disease (MRDD), which is a viral disease that significantly affects maize yields worldwide. Plants tolerate stress through transcriptional reprogramming at the alternative splicing (AS), transcriptional, and fusion gene (FG) levels. However, it is unclear whether and how AS and FG interfere with transcriptional reprogramming in MRDD. In this study, we performed global profiling of AS and FG on maize response to RBSDV and compared it with transcriptional changes. There are approximately 1.43 to 2.25 AS events per gene in maize infected with RBSDV. GRMZM2G438622 was only detected in four AS modes (A3SS, A5SS, RI, and SE), whereas GRMZM2G059392 showed downregulated expression and four AS events. A total of 106 and 176 FGs were detected at two time points, respectively, including six differentially expressed genes and five differentially spliced genes. The gene GRMZM2G076798 was the only FG that occurred at two time points and was involved in two FG events. Among these, 104 GOs were enriched, indicating that nodulin-, disease resistance-, and chloroplastic-related genes respond to RBSDV stress in maize. These results provide new insights into the mechanisms underlying post-transcriptional and transcriptional regulation of maize response to RBSDV stress.

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“…Genome-wide association study (GWAS), which is based on genetic linkage disequilibrium (LD) in a panel including a large number of genotypes representing broadly natural variations, has been used as an alternative approach for exploring the molecular basis and identifying SNPs of complex quantitative traits ( Yu and Buckler, 2006 ). In maize, GWAS has been successfully utilized to identify numerous candidate loci/genes controlling disease resistance, such as head smut ( Wang et al., 2012 ) common rust ( Kibe et al., 2020 ; Ren et al., 2021 ), rough dwarf ( Zhao et al., 2021 ), ear rot ( Guo et al., 2020 ), gray leaf spot ( Mammadov et al., 2015 ), etc. For SCR, eight SNPs were identified as significant loci using GWAS with a panel of 164 maize inbred lines in previous studies ( Souza Camacho et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…( Gowda et al., 2015 ) successfully modeled the resistance of lethal necrosis disease in tropical maize germplasm with ridge regression best linear unbiased prediction (RRBLUP). For common rust, GP accuracies observed in the GWAS panel and Doubled Haploid (DH) population were 0.61 and 0.51 ( Ren et al., 2021 ). For goss’s wilt, the GP model was trained with an accuracy of 0.69 ( Cooper et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

Cheng²,

Guo³

et al. 2023

Front. Plant Sci.

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Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding.

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Genetic Dissection of Quantitative Resistance to Common Rust (Puccinia sorghi) in Tropical Maize (Zea mays L.) by Combined Genome-Wide Association Study, Linkage Mapping, and Genomic Prediction

Cited by 22 publications

References 45 publications

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Genome-Wide Profiling of Alternative Splicing and Gene Fusion during Rice Black-Streaked Dwarf Virus Stress in Maize (Zea mays L.)

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

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