Genetic Diversity And Core Collection Construction Of Tobacco Germplasm Resources

China is a major country with rich tobacco (Nicotiana tabacum L.) germplasm resources. There are over5,300tobacco germplasms conserved in the national tobacco germplasm resources platform. The conservation of tobacco germplasm resources comes first in the world. Such a large collection is obviously unfavorable to germplasm’s further collection, evaluation, research and utilization. Therefore, it is of great significance to develop tobacco core collection for further collection of tobacco resources, discovering excellent germplasm resources and tobacco genetic breeding. The key to constructing a core collection is to accurately assess the genetic similarities among different accessions and employ an appropriate sampling strategy. This thesis was launched in following three aspects:screening optimal sampling strategy by comparing the genetic variation captured by subsets which were developed by different sampling strategies based on the agronomic traits of tobacco; comparing the diversity indices among core subset based on three different types data combination with SRAP molecular marker; ascertaining the final core collection by integrating the agronomic traits and the SRAP loci which were associated with the agronomic traits. The main contents and conclusions of this study were summarized as follows:1.805tobacco accessions from Guizhou Tobacco Institute were evaluated in field experiment in Fuquan and Jinsha of Guizhou province in2006. The genetic variations of12agronomic traits were analyzed by the mixed linear model approach using a genetic model with genotypic, environment and genotype by environment interaction effects. And the genotypic values of each accession were predicted by the adjusted unbiased prediction (AUP). Mahalanobis distance among accessions based on predicted genotypic values were used in following clustering. A serial of subsets were sampled by different combining schemes of five hierarchical clustering methods (single, complete, centroid. UPGMA and Ward’s method), two sampling strategies (preferred sampling and deviation sampling) and five sampling proportions (5%-30%). The genetic variations of agronomic traits were compared among different subsets in terms of mean, variance, range and coefficient of variation. The results showed that:the subsets sampled by the deviations sampling strategies could not well represent the initial collection, while the prefferd samling is favourable to maintaining accessions with exetreme genotypic values; the centroid linkage was best for developing tobacco core collection, which could capture the most gentic diversity of agronomic traits; the genetic diversity of subset sampled by the centroid method combined with preferred strategy reached the greatest at the ratio of10%. The representation and validation of the core collection was examined visually by the accession distribution pattern in the plot established by the first two principal components, as well as by the correlation coefficients in terms of magnitude and significance between the core and the initial collections. The results showed that the initial collection was well represented by the core collection of81accessions.2.608tobacco accessions with complete data sets of agronomic traits and SRAP molecular markers were analyzed. Under7sampling proportions (10%-40%). three kinds of subsets were sampled by optimal constructing strategies (centroid method combined with preferred sampling) based on agronomic traits, molecular markers and both integration, respectively. These subsets were evaluated in terms of genetic diversity of molecular information and agronomic characters. The results showed that: the subset of molecular markers could not accurately estimate the genetic redundancy of agronomic traits:the subsets had higher molecular diversity at the expense of the loss of genetic variation of agronomic traits; conversely, subsets of agronomic traits could increase genetic variation of agronomic characters but couldn’t the molecular diversity; subsets based on the integrated information could simultaneously improve the genetic diversity of agronomic traits and molecular markers; on this basis, Jaccard, Nei&Li and SM (simple match) genetic distances were compared, the result demonstrated the subsets based on SM genetic distances could not represent the original population in agronomic traits, while Jaccard and Nei&Li genetic distance had no distinct difference for construction of tobacco core collection3. In order to screen the molecular markers closely associated with tobacco agronomic traits, association analysis was performed between the genotyping data of17primer pair and agronomic traits on608tobacco cultivars. The population was firstly analyzed and then association analysis was conducted by TASSEL3.0GLM program. The results indicated that:the tobacco population in present study consists of twelve subpopulations;401SRAP loci associated with agronomic traits were screened out from718loci; the number of association loci varied a lot for different combination of primer pairs; some loci were found to associate simultaneously with multiple traits, which might be the genetic reason of correlation among traits or pleiotropic phenomena; in order to compare the effects of different loci on the construction of core collection, three core subsets were developed by combing the agronomic traits with all SRAP loci, association loci and unrelated loci, respectively. The results showed that all three subsets could well represent the initial collection; the genetic diversity of the subset based on the association loci was higher than that of the other two.