AUTHOR=Lai Ruiqiang , Ikram Muhammad , Li Ronghua , Xia Yanshi , Yuan Qinghua , Zhao Weicai , Zhang Zhenchen , Siddique Kadambot H. M. , Guo Peiguo 

TITLE=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

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.744175

DOI=10.3389/fpls.2021.744175

ISSN=1664-462X

ABSTRACT=Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco and controlled by multi-genes. However, their genetic architectures or bases 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 to E4 and BLUP, explaining 0.49–22.52% phenotypic variance. Of these, 38 novel-stable QTNs were identified across at least two environments and/or 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, such as MC133 × Ruyuan No. 1, CO258 × 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 best of our knowledge, this is the first comprehensive study to identify the 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 gain higher productivity.