Mining for low-nitrogen tolerance genes by integrating meta-analysis and large-scale gene expression data from maize
Mining for low-nitrogen tolerance genes by integrating meta-analysis and large-scale gene expression data from maize
复制标题
整合Meta分析和大规模玉米基因表达数据挖掘耐低氮基因
DOI：
10.1007/s10681-015-1481-5
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发表时间：
2015-11-01
期刊：
影响因子：
1.9
通讯作者：
Gao, Shibin
中科院分区：
文献类型：
--
作者：
Luo, Bowen;Tang, Haitao;Gao, Shibin
Nitrogen (N) is the most important macronutrient for plant growth and development. Hence, understanding genetic architectures and functional genes involved in the response to N deficiency can greatly facilitate the development of low-N-tolerant cultivars. In this study, we collected 212 quantitative trait loci (QTL) of agronomically important traits under low-N stress conditions in maize. We then identified 21 consensus QTL (cQTL) strongly induced for low-N tolerance after excluding overlapping cQTL containing QTL simultaneously identified in meta-analyses of studies performed under other environmental conditions. Among the 21 cQTL, 30 candidate maize genes were identified from maize large-scale differential expression data derived from analyses of low-N stress, and the 12 most important maize orthologs were identified using homologous BLAST analyses of genes with known functions in N use efficiency in model plants. Furthermore, maize orthologs associated with low-N tolerance and metabolism were also predicted using large-scale expression data from other model plants. The present genetic loci and candidate genes indicate the molecular mechanisms of low-N tolerance in maize and may provide information for QTL fine mapping and molecular marker-assisted selection.
