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Discovery of putative capsaicin biosynthetic genes by RNA-Seq and digital gene expression analysis of pepper
The Indian pepper ‘Guijiangwang’ (Capsicum frutescens L.), one of the world’s hottest chili peppers, is rich in capsaicinoids. The accumulation of the alkaloid capsaicin and its analogs in the epidermal cells of the placenta contribute to the pungency of Capsicum fruits. To identify putative genes i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069471/ https://www.ncbi.nlm.nih.gov/pubmed/27756914 http://dx.doi.org/10.1038/srep34121 |
Sumario: | The Indian pepper ‘Guijiangwang’ (Capsicum frutescens L.), one of the world’s hottest chili peppers, is rich in capsaicinoids. The accumulation of the alkaloid capsaicin and its analogs in the epidermal cells of the placenta contribute to the pungency of Capsicum fruits. To identify putative genes involved in capsaicin biosynthesis, RNA-Seq was used to analyze the pepper’s expression profiles over five developmental stages. Five cDNA libraries were constructed from the total RNA of placental tissue and sequenced using an Illumina HiSeq 2000. More than 19 million clean reads were obtained from each library, and greater than 50% of the reads were assignable to reference genes. Digital gene expression (DGE) profile analysis using Solexa sequencing was performed at five fruit developmental stages and resulted in the identification of 135 genes of known function; their expression patterns were compared to the capsaicin accumulation pattern. Ten genes of known function were identified as most likely to be involved in regulating capsaicin synthesis. Additionally, 20 new candidate genes were identified related to capsaicin synthesis. We use a combination of RNA-Seq and DGE analyses to contribute to the understanding of the biosynthetic regulatory mechanism(s) of secondary metabolites in a nonmodel plant and to identify candidate enzyme-encoding genes. |
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