Lu Yantian, Ding Yongfu, Xu Can, Chen Shubin, Xia Chunlan, Zhang Li, Sang Zhiqing, Zhang Zhanqin
Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832000, China.
Plants (Basel). 2025 Jul 22;14(15):2250. doi: 10.3390/plants14152250.
Enhancing quality traits is a primary objective in silage maize breeding programs. The use of genome-wide association studies (GWAS) for quality traits, in combination with the integration of genetic resources, presents an opportunity to identify crucial genomic regions and candidate genes influencing silage maize quality. In this study, a GWAS was conducted on 580 inbred lines of silage maize, and a meta-analysis was performed on 477 quantitative trait loci (QTLs) from 34 studies. The analysis identified 27 significant single nucleotide polymorphisms (SNPs) and 87 consensus QTLs (cQTLs), with 7 cQTLs associated with multiple quality traits. By integrating the SNPs identified through association mapping, one SNP was found to overlap with the cQTL interval related to crude protein, neutral detergent fiber, and starch content. Furthermore, enrichment analysis predicted 300 and 5669 candidate genes through GWAS and meta-analysis, respectively, highlighting pathways such as cellular metabolism, the biosynthesis of secondary metabolites, ribosome function, carbon metabolism, protein processing in the endoplasmic reticulum, and amino acid biosynthesis. The examination of 13 candidate genes from three co-located regions revealed as a cytochrome P450 family gene, while the other 2 genes primarily encode proteins involved in stress responses and other biological pathways. In conclusion, this research presents a methodology combining GWAS and meta-analysis to identify genomic regions and potential genes influencing quality traits in silage maize. These findings serve as a foundation for the identification of significant QTLs and candidate genes crucial for improving silage maize quality.
提高品质性状是青贮玉米育种计划的主要目标。将全基因组关联研究（GWAS）用于品质性状，并结合遗传资源整合，为识别影响青贮玉米品质的关键基因组区域和候选基因提供了契机。在本研究中，对580个青贮玉米自交系进行了GWAS，并对来自34项研究的477个数量性状位点（QTL）进行了荟萃分析。该分析鉴定出27个显著的单核苷酸多态性（SNP）和87个一致性QTL（cQTL），其中7个cQTL与多个品质性状相关。通过整合关联定位鉴定出的SNP，发现一个SNP与粗蛋白、中性洗涤纤维和淀粉含量相关的cQTL区间重叠。此外，富集分析分别通过GWAS和荟萃分析预测了300个和5669个候选基因，突出了细胞代谢、次生代谢物生物合成、核糖体功能、碳代谢、内质网中的蛋白质加工和氨基酸生物合成等途径。对来自三个共定位区域的13个候选基因的检测显示，其中一个基因是细胞色素P450家族基因，而其他2个基因主要编码参与应激反应和其他生物途径的蛋白质。总之，本研究提出了一种结合GWAS和荟萃分析的方法，以识别影响青贮玉米品质性状的基因组区域和潜在基因。这些发现为鉴定对提高青贮玉米品质至关重要的显著QTL和候选基因奠定了基础。
