five

Transcriptome analysis and identification of candidate genes associated with husk number in maize

收藏
中国科学数据2026-03-27 更新2026-04-25 收录
下载链接:
https://www.sciengine.com/AA/doi/10.3724/SP.J.1006.2026.53058
下载链接
链接失效反馈
官方服务:
资源简介:
Husk number is a key trait influencing the suitability of maize varieties for mechanical grain harvesting. To investigate the molecular mechanisms and candidate genes associated with husk number, the multi-husk inbred line YD97 and the few-husk inbred line YD132 were used as experimental materials. Transcriptome sequencing was conducted on husk tissues collected at the seven-leaf stage and the silking stage. Using YD97 as the control and YD132 as the sample, a total of 4089 differentially expressed genes (DEGs) were identified, including 1979 upregulated and 2150 downregulated genes. K-means clustering grouped these DEGs into eight distinct clusters. Gene ontology (GO) enrichment analysis showed that the DEGs were primarily involved in responses to stimuli, amino acid transport, auxin response, branch morphogenesis, nitrogen compound metabolism, and cell cycle processes. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that the DEGs were significantly enriched in pathways related to photosynthesis, plant hormone signal transduction, starch and sucrose metabolism, and motor proteins. Notably, the plant hormone signal transduction pathway—particularly the auxin signaling pathway—appears to play a critical role in the morphogenesis of maize husk number. Furthermore, two candidate genes, Zm00001eb156610 (encoding glutamate synthase 2) and Zm00001eb275220 (encoding a protein S-acyltransferase), were identified by integrating transcriptome sequencing, QTL mapping, candidate gene association analysis, and quantitative real-time PCR validation across husk tissues from 25 maize inbred lines. These findings contribute to a better understanding of the molecular mechanisms regulating husk number in maize and provide valuable insights for its genetic improvement.
创建时间:
2026-03-27
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作