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Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis
BACKGROUND: Carotenoids are a class of terpenoid pigments that contribute to the color and nutritional value of many fruits. Their biosynthetic pathways have been well established in a number of plant species; however, many details of the regulatory mechanism controlling carotenoid metabolism remain...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865023/ https://www.ncbi.nlm.nih.gov/pubmed/31747897 http://dx.doi.org/10.1186/s12864-019-6261-5 |
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author | Zhang, Lina Zhang, Qiuyun Li, Wenhui Zhang, Shikui Xi, Wanpeng |
author_facet | Zhang, Lina Zhang, Qiuyun Li, Wenhui Zhang, Shikui Xi, Wanpeng |
author_sort | Zhang, Lina |
collection | PubMed |
description | BACKGROUND: Carotenoids are a class of terpenoid pigments that contribute to the color and nutritional value of many fruits. Their biosynthetic pathways have been well established in a number of plant species; however, many details of the regulatory mechanism controlling carotenoid metabolism remain to be elucidated. Apricot is one of the most carotenoid-rich fruits, making it a valuable system for investigating carotenoid metabolism. The purpose of this study was to identify key genes and regulators associated with carotenoid metabolism in apricot fruit based on transcriptome sequencing. RESULTS: During fruit ripening in the apricot cultivar ‘Luntaixiaobaixing’ (LT), the total carotenoid content of the fruit decreased significantly, as did the levels of the carotenoids β-carotene, lutein and violaxanthin (p < 0.01). RNA sequencing (RNA-Seq) analysis of the fruit resulted in the identification of 44,754 unigenes and 6916 differentially expressed genes (DEGs) during ripening. Among these genes, 33,498 unigenes were annotated using public protein databases. Weighted gene coexpression network analysis (WGCNA) showed that two of the 13 identified modules (‘blue’ and ‘turquoise’) were highly correlated with carotenoid metabolism, and 33 structural genes from the carotenoid biosynthetic pathway were identified. Network visualization revealed 35 intramodular hub genes that putatively control carotenoid metabolism. The expression levels of these candidate genes were determined by quantitative real-time PCR analysis, which showed ripening-associated carotenoid accumulation. This analysis revealed that a range of genes (NCED1, CCD1/4, PIF3/4, HY5, ERF003/5/12, RAP2–12, AP2, AP2-like, BZR1, MADS14, NAC2/25, MYB1R1/44, GLK1/2 and WRKY6/31/69) potentially affect apricot carotenoid metabolism during ripening. Based on deciphering the molecular mechanism involved in ripening, a network model of carotenoid metabolism in apricot fruit was proposed. CONCLUSIONS: Overall, our work provides new insights into the carotenoid metabolism of apricot and other species, which will facilitate future apricot functional studies and quality breeding through molecular design. |
format | Online Article Text |
id | pubmed-6865023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68650232019-12-12 Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis Zhang, Lina Zhang, Qiuyun Li, Wenhui Zhang, Shikui Xi, Wanpeng BMC Genomics Research Article BACKGROUND: Carotenoids are a class of terpenoid pigments that contribute to the color and nutritional value of many fruits. Their biosynthetic pathways have been well established in a number of plant species; however, many details of the regulatory mechanism controlling carotenoid metabolism remain to be elucidated. Apricot is one of the most carotenoid-rich fruits, making it a valuable system for investigating carotenoid metabolism. The purpose of this study was to identify key genes and regulators associated with carotenoid metabolism in apricot fruit based on transcriptome sequencing. RESULTS: During fruit ripening in the apricot cultivar ‘Luntaixiaobaixing’ (LT), the total carotenoid content of the fruit decreased significantly, as did the levels of the carotenoids β-carotene, lutein and violaxanthin (p < 0.01). RNA sequencing (RNA-Seq) analysis of the fruit resulted in the identification of 44,754 unigenes and 6916 differentially expressed genes (DEGs) during ripening. Among these genes, 33,498 unigenes were annotated using public protein databases. Weighted gene coexpression network analysis (WGCNA) showed that two of the 13 identified modules (‘blue’ and ‘turquoise’) were highly correlated with carotenoid metabolism, and 33 structural genes from the carotenoid biosynthetic pathway were identified. Network visualization revealed 35 intramodular hub genes that putatively control carotenoid metabolism. The expression levels of these candidate genes were determined by quantitative real-time PCR analysis, which showed ripening-associated carotenoid accumulation. This analysis revealed that a range of genes (NCED1, CCD1/4, PIF3/4, HY5, ERF003/5/12, RAP2–12, AP2, AP2-like, BZR1, MADS14, NAC2/25, MYB1R1/44, GLK1/2 and WRKY6/31/69) potentially affect apricot carotenoid metabolism during ripening. Based on deciphering the molecular mechanism involved in ripening, a network model of carotenoid metabolism in apricot fruit was proposed. CONCLUSIONS: Overall, our work provides new insights into the carotenoid metabolism of apricot and other species, which will facilitate future apricot functional studies and quality breeding through molecular design. BioMed Central 2019-11-20 /pmc/articles/PMC6865023/ /pubmed/31747897 http://dx.doi.org/10.1186/s12864-019-6261-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Zhang, Lina Zhang, Qiuyun Li, Wenhui Zhang, Shikui Xi, Wanpeng Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title | Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title_full | Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title_fullStr | Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title_full_unstemmed | Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title_short | Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis |
title_sort | identification of key genes and regulators associated with carotenoid metabolism in apricot (prunus armeniaca) fruit using weighted gene coexpression network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865023/ https://www.ncbi.nlm.nih.gov/pubmed/31747897 http://dx.doi.org/10.1186/s12864-019-6261-5 |
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