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High temperature is a common stress, which influences the growth and reproduction of plants. Maize is one of the most important crops all over the world. However, heat stress reduces significantly the yield and quality of maize. Therefore, it is important to illuminate molecular mechanism of maize response to heat stress. To estimate genes related to heat stress, we analyzed the transcriptome of maize in response to heat stress. In this study, six cDNA libraries were constructed form total RNA isolated from leaves of maize. A total of 35,209,446 and 35,205,472 clean reads were generated from CK (Control condition) and HTP (Heat stress condition) treatments, respectively. The results showed that 1857 DEGs were identified in maize after heat stress (1029 up-regulated and 828 down-regulated). KEGG pathway enrichment analysis for DEGs indicated that protein processing in endoplasmic reticulum pathways play a central role in maize response to heat stress. In addition, in the present study, 167 putative TFs were identified, which belong to various TF families (e.g., MYB, AP2-EREBP, b-ZIP, bHLH, NAC and WRKY), and may be associated with heat stress response of maize. This research may contribute to understand the molecular mechanism of maize inbred line B73 response to heat stress, which is beneficial for developing maize cultivars to improve yield and quality.
Pubmed ID: 30641208
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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