An Expanded Maize Gene Expression Atlas based on RNA Sequencing and its Use to Explore Root Development

生物 转录组 基因 RNA序列 遗传学 基因表达谱 计算生物学 拟南芥 植物遗传学 DNA微阵列 基因表达 基因表达调控 突变体
作者
Scott Stelpflug,Rajandeep S. Sekhon,Brieanne Vaillancourt,Candice N. Hirsch,C. Robin Buell,Natalia de León,Shawn M. Kaeppler
出处
期刊:The Plant Genome [Crop Science Society of America]
卷期号:9 (1) 被引量:409
标识
DOI:10.3835/plantgenome2015.04.0025
摘要

Comprehensive and systematic transcriptome profiling provides valuable insight into biological and developmental processes that occur throughout the life cycle of a plant. We have enhanced our previously published microarray‐based gene atlas of maize ( Zea mays L.) inbred B73 to now include 79 distinct replicated samples that have been interrogated using RNA sequencing (RNA‐seq). The current version of the atlas includes 50 original array‐based gene atlas samples, a time‐course of 12 stalk and leaf samples postflowering, and an additional set of 17 samples from the maize seedling and adult root system. The entire dataset contains 4.6 billion mapped reads, with an average of 20.5 million mapped reads per biological replicate, allowing for detection of genes with lower transcript abundance. As the new root samples represent key additions to the previously examined tissues, we highlight insights into the root transcriptome, which is represented by 28,894 (73.2%) annotated genes in maize. Additionally, we observed remarkable expression differences across both the longitudinal (four zones) and radial gradients (cortical parenchyma and stele) of the primary root supported by fourfold differential expression of 9353 and 4728 genes, respectively. Among the latter were 1110 genes that encode transcription factors, some of which are orthologs of previously characterized transcription factors known to regulate root development in Arabidopsis thaliana (L.) Heynh., while most are novel, and represent attractive targets for reverse genetics approaches to determine their roles in this important organ. This comprehensive transcriptome dataset is a powerful tool toward understanding maize development, physiology, and phenotypic diversity.
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