Gonçalves L S A, Rodrigues R, Amaral A T, Karasawa M, Sudré C P
Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, RJ, Brasil.
Genet Mol Res. 2008;7(4):1289-97. doi: 10.4238/vol7-4gmr526.
Use of multivariate statistical algorithms is considered an important strategy to quantify genetic similarity. Local varieties and traditional (heirloom) seeds of genotypes are key sources of genetic variation. The Universidade Estadual do Norte Fluminense (UENF), Rio de Janeiro, Brazil, has a tomato gene bank with accessions that have been maintained for more than 40 years. We compared various algorithms to estimate genetic distances and quantify the genetic divergence of 40 tomato accessions of this collection, based on separate and joint analyses of discrete and continuous variables. Differences in continuous variables and discrete and joint analyses were calculated based on the Mahalanobis, Cole Rodgers and Gower distances. Although opinions differ regarding the validity of joint analysis of discrete and continuous data, we found that analyzing a larger number of variables together is viable and can help in the discrimination of accessions; the information that is generated is relevant and promising for both, the accessions conservation and the use of genetic resources in breeding programs.
使用多元统计算法被认为是量化遗传相似性的重要策略。地方品种和传统（传家宝）基因型种子是遗传变异的关键来源。巴西里约热内卢的北弗卢米嫩塞州立大学（UENF）拥有一个番茄基因库，其中的种质已经保存了40多年。我们基于对离散变量和连续变量的单独及联合分析，比较了各种算法以估计40份该基因库番茄种质的遗传距离并量化其遗传差异。连续变量以及离散变量和联合分析中的差异是根据马氏距离、科尔·罗杰斯距离和戈氏距离计算得出的。尽管对于离散数据和连续数据的联合分析的有效性存在不同观点，但我们发现一起分析更多变量是可行的，并且有助于区分种质；所产生的信息对于种质保存和育种计划中遗传资源的利用都是相关且有前景的。
