Department of Agricultural Science and Technology, Kenyatta University, Nairobi 43844-00100, Kenya.
International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.
Genes (Basel). 2019 Dec 23;11(1):16. doi: 10.3390/genes11010016.
Maize lethal necrosis (MLN), caused by co-infection of maize chlorotic mottle virus and sugarcane mosaic virus, can lead up to 100% yield loss. Identification and validation of genomic regions can facilitate marker assisted breeding for resistance to MLN. Our objectives were to identify marker-trait associations using genome wide association study and assess the potential of genomic prediction for MLN resistance in a large panel of diverse maize lines. A set of 1400 diverse maize tropical inbred lines were evaluated for their response to MLN under artificial inoculation by measuring disease severity or incidence and area under disease progress curve (AUDPC). All lines were genotyped with genotyping by sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability estimates were moderate to high. GWAS revealed 32 significantly associated SNPs for MLN resistance (at < 1.0 × 10). For disease severity, these significantly associated SNPs individually explained 3-5% of the total phenotypic variance, whereas for AUDPC they explained 3-12% of the total proportion of phenotypic variance. Most of significant SNPs were consistent with the previous studies and assists to validate and fine map the big quantitative trait locus (QTL) regions into few markers' specific regions. A set of putative candidate genes associated with the significant markers were identified and their functions revealed to be directly or indirectly involved in plant defense responses. Genomic prediction revealed reasonable prediction accuracies. The prediction accuracies significantly increased with increasing marker densities and training population size. These results support that MLN is a complex trait controlled by few major and many minor effect genes.
玉米坏死性萎蔫病(MLN)是由玉米褪绿斑驳病毒和甘蔗花叶病毒共同感染引起的,可导致高达 100%的产量损失。鉴定和验证基因组区域可以促进对 MLN 抗性的标记辅助选择。我们的目标是使用全基因组关联研究来鉴定标记与性状的关联,并评估基因组预测在大量不同玉米品系中对 MLN 抗性的潜力。
一组 1400 种不同的热带玉米自交系在人工接种下进行了 MLN 抗性评估,通过测量病情严重度或发病率以及病情进展曲线下的面积(AUDPC)来评估。所有品系均采用测序(GBS)SNP 进行基因型分型。所有性状的表型变异均显著,遗传力估计值为中等到高度。
GWAS 发现了 32 个与 MLN 抗性显著相关的 SNP(<1.0×10)。对于病情严重度,这些显著相关的 SNP 单独解释了 3-5%的总表型方差,而对于 AUDPC,它们解释了 3-12%的总表型方差比例。大多数显著 SNP 与先前的研究一致,并有助于验证和将大的数量性状位点(QTL)区域精细映射到少数标记的特定区域。确定了与显著标记相关的一组推定候选基因,并揭示了它们的功能直接或间接地参与了植物防御反应。
基因组预测显示出合理的预测准确性。随着标记密度和训练群体规模的增加,预测准确性显著提高。这些结果支持 MLN 是由少数主要基因和许多次要效应基因控制的复杂性状。