論文ID: 19067
Leaf chemistry traits are some of the key factors influencing tobacco quality, which can be significantly reduced by lower chemical components in cured leaf. To improve tobacco quality through breeding, genetic diversity analysis, population structure analysis, and genome-wide association studies were performed in a panel of 347 tobacco germplasms and the markers associated with five leaf chemistry traits, including total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NIC), and total potassium (TP) contents were identified. Four groups were classified at a genetic distance of 0.316 by genetic diversity analysis based on coefficient parameter NEI72 using a program NTSYS-pc2.10e, whereas four well-differentiated subpopulations were postulated in the 347 tobacco accessions. A total of 47 target trait-associated SNPs was detected in at least three environments as well as the best linear unbiased predictions (BLUPs) across all environments, among which two, two, four, six, and one highly suggestive associated SNPs were repeatedly detected in all environments and BLUPs for TS, RS, TN, NIC, and TP, respectively. On the basis of the phenotypic effects of the alleles corresponding to suggestive associated SNPs, five tobacco accessions harboring favorable alleles with elite phenotypic performance in leaf chemistry traits were identified. The results could facilitate quality tobacco breeding for higher leaf chemistry trait contents through molecular marker-assisted approaches.
