Identification of Novel Quantitative Trait Nucleotides and Candidate Genes for Bacterial Wilt Resistance in Tobacco (Nicotiana tabacum L.) Using Genotyping-by-Sequencing and Multi-Locus Genome-Wide Association Studies
文献类型： 外文期刊
作者： Lai, Ruiqiang 1 ; Ikram, Muhammad 1 ; Li, Ronghua 1 ; Xia, Yanshi 1 ; Yuan, Qinghua 2 ; Zhao, Weicai 3 ; Zhang, Zhenchen 2 ; Siddique, Kadambot H. M. 4 ; Guo, Peiguo 1 ;
作者机构： 1.Guangzhou Univ, Sch Life Sci, Int Crop Res Ctr Stress Resistance, Guangzhou, Peoples R China
2.Guangdong Acad Agr Sci, Crop Res Inst, Guangzhou, Peoples R China
3.Nanxiong Res Inst Guangdong Tobacco Co Ltd, Nanxiong, Peoples R China
4.Univ Western Australia, UWA Inst Agr, UWA Sch Agr & Environm, Perth, WA, Australia
关键词： tobacco germplasm; bacterial wilt resistance; SNP; genome-wide association analysis; quantitative trait nucleotide; superior alleles
期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：6.627； 五年影响因子：7.255 ）
ISSN： 1664-462X
年卷期： 2021 年 12 卷
页码：
收录情况： SCI
摘要： Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco. However, its genetic foundations are not fully understood. In this study, we identified 126,602 high-quality single-nucleotide polymorphisms (SNPs) in 94 tobacco accessions using genotyping-by-sequencing (GBS) and a 94.56 KB linkage disequilibrium (LD) decay rate for candidate gene selection. The population structure analysis revealed two subpopulations with 37 and 57 tobacco accessions. Four multi-locus genome-wide association study (ML-GWAS) approaches identified 142 quantitative trait nucleotides (QTNs) in E1-E4 and the best linear unbiased prediction (BLUP), explaining 0.49-22.52% phenotypic variance. Of these, 38 novel stable QTNs were identified across at least two environments/methods, and their alleles showed significant TBW-DI differences. The number of superior alleles associated with TBW resistance for each accession ranged from 4 to 24; eight accessions had more than 18 superior alleles. Based on TBW-resistant alleles, the five best cross combinations were predicted, including MC133 x Ruyuan No. 1 and CO258 x ROX28. We identified 52 candidate genes around 38 QTNs related to TBW resistance based on homologous functional annotation and KEGG enrichment analysis, e.g., CYCD3;2, BSK1, Nitab4.5_0000641g0050, Nitab4.5_0000929g0030. To the best of our knowledge, this is the first comprehensive study to identify QTNs, superior alleles, and their candidate genes for breeding TBW-resistant tobacco varieties. The results provide further insight into the genetic architecture, marker-assisted selection, and functional genomics of TBW resistance, improving future breeding efforts to increase crop productivity.
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