Kumar Shivendra, Ambreen Heena, Variath Murali T, Rao Atmakuri R, Agarwal Manu, Kumar Amar, Goel Shailendra, Jagannath Arun
Department of Botany, University of Delhi New Delhi, India.
Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute New Delhi, India.
Front Plant Sci. 2016 Oct 19;7:1554. doi: 10.3389/fpls.2016.01554. eCollection 2016.
Safflower ( L.) is a dryland oilseed crop yielding high quality edible oil. Previous studies have described significant phenotypic variability in the crop and used geographical distribution and phenotypic trait values to develop core collections. However, the molecular diversity component was lacking in the earlier collections thereby limiting their utility in breeding programs. The present study evaluated the phenotypic variability for 12 agronomically important traits during two growing seasons (2011-12 and 2012-13) in a global reference collection of 531 safflower accessions, assessed earlier by our group for genetic diversity and population structure using AFLP markers. Significant phenotypic variation was observed for all the agronomic traits in the representative collection. Cluster analysis of phenotypic data grouped the accessions into five major clusters. Accessions from the Indian Subcontinent and America harbored maximal phenotypic variability with unique characters for a few traits. MANOVA analysis indicated significant interaction between genotypes and environment for both the seasons. Initially, six independent core collections (CC1-CC6) were developed using molecular marker and phenotypic data for two seasons through POWERCORE and MSTRAT. These collections captured the entire range of trait variability but failed to include complete genetic diversity represented in 19 clusters reported earlier through Bayesian analysis of population structure (BAPS). Therefore, we merged the three POWERCORE core collections (CC1-CC3) to generate a composite core collection, CartC1 and three MSTRAT core collections (CC4-CC6) to generate another composite core collection, CartC2. The mean difference percentage, variance difference percentage, variable rate of coefficient of variance percentage, coincidence rate of range percentage, Shannon's diversity index, and Nei's gene diversity for CartC1 were 11.2, 43.7, 132.4, 93.4, 0.47, and 0.306, respectively while the corresponding values for CartC2 were 9.3, 58.8, 124.6, 95.8, 0.46, and 0.301. Each composite core collection represented the complete range of phenotypic and genetic variability of the crop including 19 BAPS clusters. This is the first report describing development of core collections in safflower using molecular marker data with phenotypic values and geographical distribution. These core collections will facilitate identification of genetic determinants of trait variability and effective utilization of the prevalent diversity in crop improvement programs.
红花(Carthamus tinctorius L.)是一种旱地油料作物,可产出高品质食用油。先前的研究描述了该作物显著的表型变异性,并利用地理分布和表型性状值来构建核心种质库。然而,早期的种质库缺乏分子多样性成分,从而限制了它们在育种计划中的效用。本研究在两个生长季节(2011 - 12年和2012 - 13年)对531份红花种质的全球参考种质库中12个重要农艺性状的表型变异性进行了评估,我们团队之前已使用AFLP标记对其进行了遗传多样性和群体结构评估。在代表性种质库中,所有农艺性状均观察到显著的表型变异。对表型数据进行聚类分析,将种质分为五个主要类群。来自印度次大陆和美洲的种质具有最大的表型变异性,且有一些性状具有独特特征。多变量方差分析表明,两个季节的基因型与环境之间均存在显著交互作用。最初,通过POWERCORE和MSTRAT软件,利用两个季节的分子标记和表型数据构建了六个独立的核心种质库(CC1 - CC6)。这些种质库涵盖了性状变异的整个范围,但未包含通过群体结构的贝叶斯分析(BAPS)先前报道的19个类群中所代表的完整遗传多样性。因此,我们将三个POWERCORE核心种质库(CC1 - CC3)合并以生成一个复合核心种质库CartC1,将三个MSTRAT核心种质库(CC4 - CC6)合并以生成另一个复合核心种质库CartC2。CartC1的平均差异百分比、方差差异百分比、变异系数变量率百分比、范围重合率百分比、香农多样性指数和奈氏基因多样性分别为11.2、43.7、132.4、93.4、0.47和0.306,而CartC2的相应值分别为9.3、58.8、124.6、95.8、0.46和0.301。每个复合核心种质库都代表了该作物表型和遗传变异的完整范围,包括19个BAPS类群。这是第一份描述利用分子标记数据结合表型值和地理分布构建红花核心种质库的报告。这些核心种质库将有助于鉴定性状变异的遗传决定因素,并在作物改良计划中有效利用现有的多样性。