Person: Jianyu Wu
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Jianyu Wu
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Jianyu Wu
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0000-0002-9090-2512 6 results
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- Natural variation in maize gene ZmSBR1 confers seedling resistance to Fusarium verticillioides(Elsevier B.V., 2024) Yunxia Song; Peipei Ma; Jingyang Gao; Chaopei Dong; Zhao Wang; Yifan Luan; Jiafa Chen; Doudou Sun; Pei Jing; Xuecai Zhang; Weibin Song; Zijian Zhou; Jianyu Wu
Publication - Enhancing maize's nitrogen-fixing potential through ZmSBT3, a gene suppressing mucilage secretion(Wiley, 2023) Jingyang Gao; Peijiang Feng; Jingli Zhang; Chaopei Dong; Zhao Wang; Mingxiang Chen; Zhongliang Yu; Bowen Zhao; Xin Hou; Huijuan Wang; Zhaokun Wu; Jemim, R.S.; Haidong Yu; Doudou Sun; Pei Jing; Jiafa Chen; Weibin Song; Xuecai Zhang; Zijian Zhou; Jianyu Wu
Publication - Linkage mapping and genome-wide association study reveals conservative QTL and candidate genes for Fusarium rot resistance in maize(BioMed Central, 2020) Yabin Wu; Zijian Zhou; Chaopei Dong; Jiafa Chen; Junqiang Ding; Xuecai Zhang; Cong Mu; Yuna Chen; Xiaopeng Li; Huimin Li; Yanan Han; Ruixia Wang; Xiaodong Sun; Jingjing Li; Xiaodong Dai; Weibin Song; Wei Chen; Jianyu Wu
Publication - Genome-wide association study and QTL mapping reveal genomic loci associated with Fusarium ear rot resistance in tropical maize germplasm(Genetics Society of America, 2016) Jiafa Chen; Shrestha, R.; Junqiang Ding; Hongjian Zheng; Chunhua Mu; Jianyu Wu; Mahuku, G.Fusarium ear rot (FER) incited by Fusarium verticillioides is a major disease of maize that reduces grain quality globally. Host resistance is the most suitable strategy for managing the disease. We report the results of genome-wide association study (GWAS) to detect alleles associated with increased resistance to FER in a set of 818 tropical maize inbred lines evaluated in three environments. Association tests performed using 43,424 single-nucleotide polymorphic (SNPs) markers identified 45 SNPs and 15 haplotypes that were significantly associated with FER resistance. Each associated SNP locus had relatively small additive effects on disease resistance and accounted for 1–4% of trait variation. These SNPs and haplotypes were located within or adjacent to 38 candidate genes, 21 of which were candidate genes associated with plant tolerance to stresses, including disease resistance. Linkage mapping in four biparental populations to validate GWAS results identified 15 quantitative trait loci (QTL) associated with F. verticillioides resistance. Integration of GWAS and QTL to the maize physical map showed eight colocated loci on chromosomes 2, 3, 4, 5, 9, and 10. QTL on chromosomes 2 and 9 are new. These results reveal that FER resistance is a complex trait that is conditioned by multiple genes with minor effects. The value of selection on identified markers for improving FER resistance is limited; rather, selection to combine small effect resistance alleles combined with genomic selection for polygenic background for both the target and general adaptation traits might be fruitful for increasing FER resistance in maize.
Publication - Genomic dissection of leaf angle in maize (Zea mays L.) using a four-way cross mapping population(Public Library of Science, 2015) Junqiang Ding; Luyan Zhang; Jiafa Chen; Xiantang Li; Yongming Li; Hongliang Cheng; Rongrong Huang; Bo Zhou; Zhimin Li; Jiankang Wang; Jianyu WuIncreasing grain yield by the selection for optimal plant architecture has been the key focus in modern maize breeding. As a result, leaf angle, an important determinant of plant architecture, has been significantly improved to adapt to the ever-increasing plant density in maize production over the past several decades. To extend our understanding on the genetic mechanisms of leaf angle in maize, we developed the first four-way cross mapping population, consisting of 277 lines derived from four maize inbred lines with varied leaf angles. The four-way cross mapping population together with the four parental lines were evaluated for leaf angle in two environments. In this study, we reported linkage maps built in the population and quantitative trait loci (QTL) on leaf angle detected by inclusive composite interval mapping (ICIM). ICIM applies a two-step strategy to effectively separate the cofactor selection from the interval mapping, which controls the background additive and dominant effects at the same time. A total of 14 leaf angle QTL were identified, four of which were further validated in near-isogenic lines (NILs). Seven of the 14 leaf angle QTL were found to overlap with the published leaf angle QTL or genes, and the remaining QTL were unique to the four-way population. This study represents the first example of QTL mapping using a four-way cross population in maize, and demonstrates that the use of specially designed four-way cross is effective in uncovering the basis of complex and polygenetic trait like leaf angle in maize.
Publication - Quantitative trait locus mapping with background control in genetic populations of clonal F1 and double cross(Wiley, 2015) Luyan Zhang; Huihui Li; Junqiang Ding; Jianyu Wu; Jiankang WangIn this study, we considered five categories of molecular markers in clonal F1 and double cross populations, based on the number of distinguishable alleles and the number of distinguishable genotypes at the marker locus. Using the completed linkage maps, incomplete and missing markers were imputed as fully informative markers in order to simplify the linkage mapping approaches of quantitative trait genes. Under the condition of fully informative markers, we demonstrated that dominance effect between the female and male parents in clonal F1 and double cross populations can cause the interactions between markers. We then developed an inclusive linear model that includes marker variables and marker interactions so as to completely control additive effects of the female and male parents, as well as the dominance effect between the female and male parents. The linear model was finally used for background control in Inclusive Composite Interval Mapping (ICIM) of QTL. The efficiency of ICIM was demonstrated by extensive simulations and by comparisons with simple interval mapping, multiple-QTL models and composite interval mapping. Finally, ICIM was applied in one actual double cross population to identify QTL on days to silking in maize.
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