Department of Plant Breeding and Genetics, Assam Agricultural University, Jorhat, Assam, 785013, India.
ICAR - Indian Institute of Millets Research, Rajendranagar, Hyderabad, Telangana, 500 030, India.
BMC Plant Biol. 2024 Nov 5;24(1):1043. doi: 10.1186/s12870-024-05754-6.
Forage sorghum is a highly valued crop in livestock feed production due to its versatility, adaptability, high productivity, and resilience under adverse environmental conditions, making it a crucial option for sustainable forage production. This study aimed to investigate ninety-five forage sorghum genotypes and identify the marker - trait associations (MTAs) in adaptive traits, including yield and flowering through genome-wide association studies (GWAS).
Using 41,854 polymorphic SNPs, a GWAS involving the GLM, MLM, and FarmCPU models was performed to analyse fourteen adaptive traits. The population structure revealed the presence of two subpopulation groups. Linkage disequilibrium (LD) plots showed varying degrees of LD decay across the chromosomes, with an average LD decay of 19.49 kbp. Twelve common significant QTNs, encoding 17 putative candidate genes, were simultaneously co-detected and studied by at least two or more GWAS methods. Three QTNs were associated to days to 50% flowering; two each to leaf-to-stem ratio and number of nodes per plant; and one each to plant height, leaf width, number of leaves per plant, stem girth, and internodal length. Six candidate genes were associated with days to 50% flowering, two each with leaf width, stem girth, leaf-to-stem ratio, and number of nodes per plant, and one each with plant height, number of leaves per plant, and internodal length.
FarmCPU was identified as the most suitable and effective among all the models for controlling both false positives and false negatives. Further in-depth analysis of the newly discovered QTNs may lead to the identification of new candidate genes for the trait of interest. These studies elucidate gene functions and could transform forage sorghum breeding through marker-assisted selection and transgenic approaches, accelerating the development of superior forage sorghum varieties and enhancing global food security.
饲用高粱是一种在畜牧业生产中非常有价值的作物,因为它具有多功能性、适应性、高生产力和在不利环境条件下的弹性,使其成为可持续饲料生产的重要选择。本研究旨在调查 95 种饲用高粱基因型,并通过全基因组关联研究(GWAS)鉴定适应性性状(包括产量和开花)中的标记-性状关联(MTAs)。
利用 41854 个多态性 SNP,使用 GLM、MLM 和 FarmCPU 模型进行了全基因组关联分析,以分析 14 种适应性性状。群体结构显示存在两个亚群。连锁不平衡(LD)图谱显示,不同染色体的 LD 衰减程度不同,平均 LD 衰减为 19.49 kbp。12 个常见的显著 QTN,编码 17 个潜在的候选基因,通过至少两种或更多的 GWAS 方法同时被共同检测和研究。三个 QTN 与 50%开花天数相关;两个 QTN 与叶茎比和植物节点数相关;一个 QTN 与株高、叶宽、每株叶片数、茎粗和节间长度相关。六个候选基因与 50%开花天数相关,两个 QTN 与叶宽、茎粗、叶茎比和植物节点数相关,一个 QTN 与株高、每株叶片数和节间长度相关。
FarmCPU 被确定为所有模型中最适合和有效的模型,可控制假阳性和假阴性。对新发现的 QTN 进行进一步深入分析,可能会发现感兴趣性状的新候选基因。这些研究阐明了基因功能,并可通过标记辅助选择和转基因方法促进饲用高粱的改良,加速优良饲用高粱品种的开发,提高全球粮食安全。