Zeng Yukang, Xu Xiaoming, Jiang Jiale, Lin Shaohang, Fan Zehui, Meng Yao, Maimaiti Atikaimu, Wu Penghao, Ren Jiaojiao
College of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
PLoS One. 2025 May 22;20(5):e0323140. doi: 10.1371/journal.pone.0323140. eCollection 2025.
Maize is an important food crop worldwide. The length, width, and area of leaves are crucial traits of plant architecture and further influencing plant density, photosynthesis, and crop yield. To dissect the genetic architecture of leaf length, leaf width, and leaf area, a multi-parents doubled haploid (DH) population was used for genome-wide association study (GWAS) and genomic selection (GS). The length, width, and area of the first leaf above the uppermost ear, the uppermost ear leaf, and the first leaf below the uppermost ear were evaluated in multi-environment trials. Using BLINK and FarmCPU for GWAS, 19 significant single nucleotide polymorphisms (SNPs) on chromosomes 1, 2, 5, 6, 8, 9, and 10 were associated with leaf length, 49 SNPs distributed over all 10 chromosomes were associated with leaf width, and 37 SNPs distributed on all 10 chromosomes except for chromosome 3 were associated with leaf area. The phenotypic variation explained (PVE) by each QTL ranged from 0.05% to 27.46%. Fourteen pleiotropic SNPs were detected by at least two leaf-related traits. A total of 57 candidate genes were identified for leaf-related traits, of which 44 were annotated with known functions. Candidate genes Zm00001d032866, Zm00001D022209, and Zm00001d001980 are involved in leaf senescence. Zm00001d026130, Zm00001d002429, Zm00001d023225, and Zm00001d046767 play important roles in leaf development. GS analysis showed that when 60% of the total genotypes was used as the training population and 3000 SNPs were used for prediction, moderate prediction accuracy was obtained for leaf length, leaf width, and leaf area. The prediction accuracy would be improved by using top significantly associated SNPs for GS. The current study provides a better understanding of the genetic basis of leaf length, leaf width, and leaf area, and valuable information for improving plant architecture by implementing GS.
玉米是全球重要的粮食作物。叶片的长度、宽度和面积是植物株型的关键性状，进而影响种植密度、光合作用和作物产量。为了解析叶片长度、宽度和面积的遗传结构，利用一个多亲本加倍单倍体（DH）群体进行全基因组关联研究（GWAS）和基因组选择（GS）。在多环境试验中对最上部雌穗上方的第一片叶、最上部雌穗叶和最上部雌穗下方的第一片叶的长度、宽度和面积进行了评估。使用BLINK和FarmCPU进行GWAS分析，在第1、2、5、6、8、9和10号染色体上发现19个显著单核苷酸多态性（SNP）与叶片长度相关，分布在所有10条染色体上的49个SNP与叶片宽度相关，分布在除第3号染色体外的所有10条染色体上的37个SNP与叶片面积相关。每个QTL解释的表型变异（PVE）范围为0.05%至27.46%。至少两个与叶片相关的性状检测到14个多效性SNP。共鉴定出57个与叶片相关性状的候选基因，其中44个具有已知功能注释。候选基因Zm00001d032866、Zm00001D022209和Zm00001d001980参与叶片衰老过程。Zm00001d026130、Zm00001d002429、Zm00001d023225和Zm00001d046767在叶片发育中起重要作用。GS分析表明，当使用60%的总基因型作为训练群体并使用3000个SNP进行预测时，对于叶片长度、宽度和面积可获得中等预测准确性。通过使用GS中最显著相关的SNP可提高预测准确性。本研究为更好地理解叶片长度、宽度和面积的遗传基础提供了依据，并为通过实施GS改善植物株型提供了有价值的信息。
