five

Table 1_Mining candidate genes for maize plant height based on a GWAS, Meta-QTL, and WGCNA.xlsx

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/Table_1_Mining_candidate_genes_for_maize_plant_height_based_on_a_GWAS_Meta-QTL_and_WGCNA_xlsx/29380109
下载链接
链接失效反馈
官方服务:
资源简介:
IntroductionIn maize, plant height (PH) is one of the most important agronomic traits that directly influences planting density and yield. Therefore, identifying candidate genes related to PH will help manipulate maize yield indirectly. MethodsThe present research carried out a genome-wide association study (GWAS) of PH using a natural population of 580 maize inbred lines. Further, after collecting the published transcriptome data of maize B73, tissue-specific gene co-expression modules related to PH were generated using weighted gene co-expression network analysis (WGCNA). Furthermore, a meta-analysis of the already reported PH-related quantitative trait loci (QTLs). ResultsThe integrated analysis of the results based on the different approaches screened three candidate genes: Zm00001d031796, encoding AP2-EREBP transcription factor 172; Zm00001d009918, encoding Phytochrome A-associated F-box protein; and Zm00001d042454, encoding plastid specific ribosomal protein 4.
创建时间:
2025-06-23
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