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Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis

Angelica sinensis (Oliv.) Diels is a widely used medicinal plant mainly originated in Gansu, China. Angelica sinensis is greatly demanded in the clinical practice of Chinese medicine due to its broad pharmacological activities of hematopoietic and anti-inflammatory properties. But, the percentage of...

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Autores principales: Yu, Guang, Zhou, Yuan, Yu, Juanjuan, Hu, Xueqin, Tang, Ye, Yan, Hui, Duan, Jinao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624268/
https://www.ncbi.nlm.nih.gov/pubmed/31296928
http://dx.doi.org/10.1038/s41598-019-46414-2
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author Yu, Guang
Zhou, Yuan
Yu, Juanjuan
Hu, Xueqin
Tang, Ye
Yan, Hui
Duan, Jinao
author_facet Yu, Guang
Zhou, Yuan
Yu, Juanjuan
Hu, Xueqin
Tang, Ye
Yan, Hui
Duan, Jinao
author_sort Yu, Guang
collection PubMed
description Angelica sinensis (Oliv.) Diels is a widely used medicinal plant mainly originated in Gansu, China. Angelica sinensis is greatly demanded in the clinical practice of Chinese medicine due to its broad pharmacological activities of hematopoietic and anti-inflammatory properties. But, the percentage of early flowering in Angelica sinensis arrives to 20%~30%, which severely affects its quality and quantity. Here, transcriptome profiling and digital gene expression analysis were applied to study the mechanism of early flowering in Angelica sinensis. A total of 49,183,534 clean reads were obtained and assembled into 68,262 unigenes, and 49,477 unigenes (72.5%) could be annotated to a minimum of one database in the Nr, Nt, Swiss-Pro, GO, COG and KEGG. Taking the above transcriptome data as a reference, digital gene expression result showed that 5,094 genes expression level were significant changed during early flowering. These annotated genes offered much information promoting that the biosynthesis of secondary metabolites pathway, the hormone signal transduction pathway, and the transcription regulation system may be closely related to the early flowering phenomenon of Angelica sinensis. Further expression patterns of key genes contribute to early flowering were analyzed using quantitative real-time PCR. The transcriptome result offered important gene expression information about early flowering in Angelica sinensis.
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spelling pubmed-66242682019-07-19 Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis Yu, Guang Zhou, Yuan Yu, Juanjuan Hu, Xueqin Tang, Ye Yan, Hui Duan, Jinao Sci Rep Article Angelica sinensis (Oliv.) Diels is a widely used medicinal plant mainly originated in Gansu, China. Angelica sinensis is greatly demanded in the clinical practice of Chinese medicine due to its broad pharmacological activities of hematopoietic and anti-inflammatory properties. But, the percentage of early flowering in Angelica sinensis arrives to 20%~30%, which severely affects its quality and quantity. Here, transcriptome profiling and digital gene expression analysis were applied to study the mechanism of early flowering in Angelica sinensis. A total of 49,183,534 clean reads were obtained and assembled into 68,262 unigenes, and 49,477 unigenes (72.5%) could be annotated to a minimum of one database in the Nr, Nt, Swiss-Pro, GO, COG and KEGG. Taking the above transcriptome data as a reference, digital gene expression result showed that 5,094 genes expression level were significant changed during early flowering. These annotated genes offered much information promoting that the biosynthesis of secondary metabolites pathway, the hormone signal transduction pathway, and the transcription regulation system may be closely related to the early flowering phenomenon of Angelica sinensis. Further expression patterns of key genes contribute to early flowering were analyzed using quantitative real-time PCR. The transcriptome result offered important gene expression information about early flowering in Angelica sinensis. Nature Publishing Group UK 2019-07-11 /pmc/articles/PMC6624268/ /pubmed/31296928 http://dx.doi.org/10.1038/s41598-019-46414-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yu, Guang
Zhou, Yuan
Yu, Juanjuan
Hu, Xueqin
Tang, Ye
Yan, Hui
Duan, Jinao
Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title_full Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title_fullStr Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title_full_unstemmed Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title_short Transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in Angelica sinensis
title_sort transcriptome and digital gene expression analysis unravels the novel mechanism of early flowering in angelica sinensis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624268/
https://www.ncbi.nlm.nih.gov/pubmed/31296928
http://dx.doi.org/10.1038/s41598-019-46414-2
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