Identification and Fine-Mapping of a Novel QTL qMrdd2 Conferring Resistance to Maize Rough Dwarf Disease

Plant Disease ◽  
2021 ◽  
Author(s):  
Zhennan Xu ◽  
Feifei Wang ◽  
Zhiqiang Zhou ◽  
Qingchang Meng ◽  
Yanping Chen ◽  
...  

Maize rough dwarf disease (MRDD), caused by a virus, seriously affects maize quality and yield worldwide. MRDD can be most effectively controlled with disease-resistant hybrids of corn. Here, MRDD-resistant (Qi319) and -susceptible (Ye478) parental inbred maize lines and their 314 recombinant inbred lines (RILs) that were derived from a cross between them were evaluated across three environments. A stable resistance QTL, qMrdd2, was identified and mapped using BLUP values to a 0.55 Mb region between the markers MK807 and MK811 on chromosome 2 (B73 RefGen_v3), which was found to explain 8.6 to 11.0% of the total phenotypic variance in MRDD resistance. We validated the effect of qMrdd2 using a chromosome segment substitution line (CSSL) that was derived from a cross between maize inbred Qi319 as the MRDD resistance donor and Ye478 as the recipient. Disease severity index of the CSSL haplotype II harboring qMrdd2 was significantly lower than that of the susceptible parent Ye478. Subsequently, we fine-mapped qMrdd2 to a 315 kb region flanked by the markers RD81 and RD87 by testing recombinant-derived progeny using selfed backcrossed families. In this study, we identified a novel QTL for MRDD-resistance by combining the RIL and CSSL populations, which can be used to breed for MRDD resistant varieties of maize. Keywords: Maize, Maize rough dwarf disease, QTL, Fine-mapping, Recombinant inbred line, Chromosome segment substitution line.

2020 ◽  
Author(s):  
Zhennan Xu ◽  
Feifei Wang ◽  
Zhiqiang Zhou ◽  
Qingchang Meng ◽  
Yanping Chen ◽  
...  

Abstract Background: Maize rough dwarf disease (MRDD) is a disease caused by a virus that seriously affects maize yield and quality worldwide. Rice black streaked dwarf virus (RBSDV) in the Fijivirus genus in the Reoviridae family causes MRDD in maize. Typical MRDD symptoms of include severe dwarfing of plants, shortening of internodes. MRDD resistance is a complex trait that is quantitatively inherited and is controlled by several quantitative trait loci (QTL). MRDD is most efficiently controlled by the cultivation of disease-resistant corn hybrids. Results: Disease resistance in the MRDD-resistant Qi319 and -susceptible Ye478 parental inbred lines and the 314 recombinant inbred lines (RILs) that were derived from a cross between them was evaluated across three environments. A stable resistance QTL, qMrdd2 , which explained 8.64 to 11.02% of the total phenotypic variance in MRDD resistance, was identified repeatedly and was mapped using BLUP values to a 0.55-Mb region between the markers MK807 and MK811 on chromosome 2. We validated the effect of qMrdd2 using a chromosome segment substitution line population that were derived from a cross between maize inbred Qi319 as the resistance donor and Ye478 as the recipient. The disease-severity index (DSI) of CSSL haplotype II harboring qMrdd2 was significantly lower than the DSI of susceptible parent Ye478 ( P < 0.05). Mapping results using CSSLs were consistent with localization interval determined using RILs. The qMrdd2 locus acted with an additive effect but no significant dominant gene action in conferring MRDD resistance. We fine-mapped qMrdd2 locus into a 315-kb region flanked by the markers RD81 and RD87 by testing recombinant-derived progeny using selfed backcrossed families. Conclusions: qMrdd2 is a recently discovered QTL from Qi319 for resistance to MRDD with an additive effect but no significant dominant gene action for MRDD resistance. qMrdd2 was fine-mapped to a 315-kb interval on maize chromosome 2. Introgression of the MRDD resistance allele at the qMrdd2 locus of CSSL haplotype 2 using linked markers umc1824 and bnlg125 will be useful for maize breeding to reduce yield losses caused by MRDD. Keywords: Maize, Maize rough dwarf disease, QTL, Fine-mapping, RIL;CSSL.


2015 ◽  
Vol 134 (4) ◽  
pp. 437-445 ◽  
Author(s):  
Qingyuan He ◽  
Hongyan Yang ◽  
Shihua Xiang ◽  
Dong Tian ◽  
Wubin Wang ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Quanwei Lu ◽  
Xianghui Xiao ◽  
Juwu Gong ◽  
Pengtao Li ◽  
Yan Zhao ◽  
...  

Fiber length is an important determinant of fiber quality, and it is a quantitative multi-genic trait. Identifying genes associated with fiber length is of great importance for efforts to improve fiber quality in the context of cotton breeding. Integrating transcriptomic information and details regarding candidate gene regions can aid in candidate gene identification. In the present study, the CCRI45 line and a chromosome segment substitution line (CSSL) with a significantly higher fiber length (MBI7747) were utilized to establish F2 and F2:3 populations. Using a high-density genetic map published previously, six quantitative trait loci (QTLs) associated with fiber length and two QTLs associated with fiber strength were identified on four chromosomes. Within these QTLs, qFL-A07-1, qFL-A12-2, qFL-A12-5, and qFL-D02-1 were identified in two or three environments and confirmed by a meta-analysis. By integrating transcriptomic data from the two parental lines and through qPCR analyses, four genes associated with these QTLs including Cellulose synthase-like protein D3 (CSLD3, GH_A12G2259 for qFL-A12-2), expansin-A1 (EXPA1, GH_A12G1972 for qFL-A12-5), plasmodesmata callose-binding protein 3 (PDCB3, GH_A12G2014 for qFL-A12-5), and Polygalacturonase (At1g48100, GH_D02G0616 for qFL-D02-1) were identified as promising candidate genes associated with fiber length. Overall, these results offer a robust foundation for further studies regarding the molecular basis for fiber length and for efforts to improve cotton fiber quality.


2018 ◽  
Vol 178 (2) ◽  
pp. 612-625 ◽  
Author(s):  
Jie Chen ◽  
Jilin Wang ◽  
Wei Chen ◽  
Wenqiang Sun ◽  
Meng Peng ◽  
...  

2018 ◽  
Vol 9 (1) ◽  
pp. 189-201 ◽  
Author(s):  
Luis O. Lopez-Zuniga ◽  
Petra Wolters ◽  
Scott Davis ◽  
Teclemariam Weldekidan ◽  
Judith M. Kolkman ◽  
...  

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