Cavagnaro Pablo F, Cavagnaro Juan B, Lemes José L, Masuelli Ricardo W, Passera Carlos B
Laboratorio de Biología Molecular-INTA, EEA La Consulta, CONICET, Facultad de Ciencias Agrarias, Universidad Nacional de Cuyo, Mendoza, Argentina.
Genome. 2006 Aug;49(8):906-18. doi: 10.1139/g06-060.
We assessed the genetic diversity in Trichloris crinita (Poaceae) varieties from South America, using AFLPs, morphological characters, and quantitative agronomic traits. Owing to the importance of this species for range grazing, we first characterized the varieties based on forage productivity. Biomass production varied 9 fold among the materials evaluated. Analysis of AFLP fingerprints allowed the discrimination of all varieties with a few selected primer combinations. Pair-wise genetic similarities, using marker data, ranged from 0.31 to 0.92 (Jaccard coefficients). Marker-based unweighted pair group method with arithmetic averaging (UPGMA) cluster analysis did not show geographical clustering, but rather grouped the varieties according to their biomass production. We identified 18 markers associated with biomass production, of which 8 showed complete correlation (r = 1.00) with this trait. These DNA markers can be used to assist selection for high forage productivity in T. crinita. Cluster analysis using morphological and quantitative characters revealed 4 distinct groups of varieties, clearly separated according to their biomass yield. The variables foliage height and basal diameter were strongly correlated with biomass production and these phenotypic markers can be used to select productive plants. The relations among the varieties based on AFLP data were significantly correlated with those based on agronomic and morphological characters, suggesting that the 2 systems give similar estimates of genetic relations among the varieties.
我们利用扩增片段长度多态性(AFLP)、形态特征和定量农艺性状,评估了来自南美洲的三毛草(禾本科)品种的遗传多样性。鉴于该物种对放牧的重要性,我们首先根据牧草生产力对这些品种进行了特征描述。在所评估的材料中,生物量产量差异达9倍。对AFLP指纹图谱的分析表明,使用少数选定的引物组合就能区分所有品种。基于标记数据的成对遗传相似性范围为0.31至0.92(杰卡德系数)。基于标记的算术平均不加权成对群法(UPGMA)聚类分析并未显示出地理聚类,而是根据生物量产量对品种进行了分组。我们鉴定出18个与生物量产量相关的标记,其中8个与该性状完全相关(r = 1.00)。这些DNA标记可用于辅助选择三毛草中高牧草生产力的品种。利用形态和定量特征进行的聚类分析揭示了4个不同的品种组,根据它们的生物量产量明显分开。叶高和基部直径这两个变量与生物量产量密切相关,这些表型标记可用于选择高产植株。基于AFLP数据的品种间关系与基于农艺和形态特征的关系显著相关,这表明这两种系统对品种间遗传关系的估计相似。