Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias (CCTA), UENF, Campos dos Goytacazes, Rio de Janeiro, Brazil.
Bayer, Coxilha, Rio Grande do Sul, Brazil.
PLoS One. 2019 Jun 25;14(6):e0218552. doi: 10.1371/journal.pone.0218552. eCollection 2019.
The identification of the genes responsible for complex traits is highly promising to accelerate crop breeding, but such information is still limited for popcorn. Thus, in the present study, a mixed linear model-based association analysis (MLMA) was applied for six important popcorn traits: plant and ear height, 100-grain weight, popping expansion, grain yield and expanded popcorn volume per hectare. To this end, 196 plants of the open-pollinated popcorn population UENF-14 were sampled, selfed (S1), and then genotyped with a panel of 10,507 single nucleotide polymorphisms (SNPs) markers distributed throughout the genome. The six traits were studied under two environments [Campos dos Goytacazes-RJ (ENV1) and Itaocara-RJ (ENV2)] in an incomplete block design. Based on the phenotypic data of the S1 progenies and on the genetic characteristics of the parents, the MLMA was performed. Thereafter, genes annotated in the MaizeGDB platform were screened for potential linkage disequilibrium with the SNPs associated to the six evaluated traits. Overall, seven and eight genes were identified as associated with the traits in ENV1 and ENV2, respectively, and proteins encoded by these genes were evaluated for their function. The results obtained here contribute to increase knowledge on the genetic architecture of the six evaluated traits and might be used for marker-assisted selection in breeding programs.
鉴定负责复杂性状的基因对于加速作物育种非常有希望，但这种信息对于爆米花仍然有限。因此，在本研究中，应用基于混合线性模型的关联分析（MLMA）来分析六个重要的爆米花性状：株高和穗高、百粒重、爆花膨胀率、籽粒产量和每公顷爆开的爆米花体积。为此，从开放授粉的爆米花群体 UENF-14 中采集了 196 株植物进行自交（S1），然后用分布在整个基因组的 10,507 个单核苷酸多态性（SNP）标记进行基因分型。在不完全区组设计下，在两个环境[Campos dos Goytacazes-RJ（ENV1）和 Itaocara-RJ（ENV2）]下研究了这六个性状。根据 S1 后代的表型数据和父母的遗传特征，进行了 MLMA。然后，在 MaizeGDB 平台上注释的基因被筛选出来，以寻找与六个评估性状相关的 SNP 之间的潜在连锁不平衡。总体而言，在 ENV1 和 ENV2 中分别鉴定出七个和八个与性状相关的基因，并且评估了这些基因编码的蛋白质的功能。这里获得的结果有助于增加对六个评估性状遗传结构的了解，并可能用于育种计划中的标记辅助选择。
