Genome-wide identification and comparative expression analysis of LEA genes in watermelon and melon genomes
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- 作者：Yasemin Celik Altunoglu…
- 关键词：LEA gene family ; Citrullus lanatus ; Cucumis melo ; Genome ; wide analysis ; Drought stress
- 刊名：Physiology and Molecular Biology of Plants
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：23
- 期：1
- 页码：5-21
- 全文大小：
- 刊物主题：Plant Sciences; Plant Physiology; Biological and Medical Physics, Biophysics; Cell Biology;
- 出版者：Springer India
- ISSN：0974-0430
- 卷排序：23
文摘
Late embryogenesis abundant (LEA) proteins are large and diverse group of polypeptides which were first identified during seed dehydration and then in vegetative plant tissues during different stress responses. Now, gene family members of LEA proteins have been detected in various organisms. However, there is no report for this protein family in watermelon and melon until this study. A total of 73 LEA genes from watermelon (ClLEA) and 61 LEA genes from melon (CmLEA) were identified in this comprehensive study. They were classified into four and three distinct clusters in watermelon and melon, respectively. There was a correlation between gene structure and motif composition among each LEA groups. Segmental duplication played an important role for LEA gene expansion in watermelon. Maximum gene ontology of LEA genes was observed with poplar LEA genes. For evaluation of tissue specific expression patterns of ClLEA and CmLEA genes, publicly available RNA-seq data were analyzed. The expression analysis of selected LEA genes in root and leaf tissues of drought-stressed watermelon and melon were examined using qRT-PCR. Among them, ClLEA-12-17-46 genes were quickly induced after drought application. Therefore, they might be considered as early response genes for water limitation conditions in watermelon. In addition, CmLEA-42-43 genes were found to be up-regulated in both tissues of melon under drought stress. Our results can open up new frontiers about understanding of functions of these important family members under normal developmental stages and stress conditions by bioinformatics and transcriptomic approaches.