Comparative network analysis reveals the dynamics of organic acid diversity during fruit ripening in peach (Prunus persica L. Batsch).


Journal

BMC plant biology
ISSN: 1471-2229
Titre abrégé: BMC Plant Biol
Pays: England
ID NLM: 100967807

Informations de publication

Date de publication:
09 Jan 2023
Historique:
received: 12 07 2022
accepted: 02 01 2023
entrez: 8 1 2023
pubmed: 9 1 2023
medline: 11 1 2023
Statut: epublish

Résumé

Organic acids are important components that determine the fruit flavor of peach (Prunus persica L. Batsch). However, the dynamics of organic acid diversity during fruit ripening and the key genes that modulate the organic acids metabolism remain largely unknown in this kind of fruit tree which yield ranks sixth in the world. In this study, we used 3D transcriptome data containing three dimensions of information, namely time, phenotype and gene expression, from 5 different varieties of peach to construct gene co-expression networks throughout fruit ripening of peach. With the network inferred, the time-ordered network comparative analysis was performed to select high-acid specific gene co-expression network and then clarify the regulatory factors controlling organic acid accumulation. As a result, network modules related to organic acid synthesis and metabolism under high-acid and low-acid comparison conditions were identified for our following research. In addition, we obtained 20 candidate genes as regulatory factors related to organic acid metabolism in peach. The study provides new insights into the dynamics of organic acid accumulation during fruit ripening, complements the results of classical co-expression network analysis and establishes a foundation for key genes discovery from time-series multiple species transcriptome data.

Sections du résumé

BACKGROUND BACKGROUND
Organic acids are important components that determine the fruit flavor of peach (Prunus persica L. Batsch). However, the dynamics of organic acid diversity during fruit ripening and the key genes that modulate the organic acids metabolism remain largely unknown in this kind of fruit tree which yield ranks sixth in the world.
RESULTS RESULTS
In this study, we used 3D transcriptome data containing three dimensions of information, namely time, phenotype and gene expression, from 5 different varieties of peach to construct gene co-expression networks throughout fruit ripening of peach. With the network inferred, the time-ordered network comparative analysis was performed to select high-acid specific gene co-expression network and then clarify the regulatory factors controlling organic acid accumulation. As a result, network modules related to organic acid synthesis and metabolism under high-acid and low-acid comparison conditions were identified for our following research. In addition, we obtained 20 candidate genes as regulatory factors related to organic acid metabolism in peach.
CONCLUSIONS CONCLUSIONS
The study provides new insights into the dynamics of organic acid accumulation during fruit ripening, complements the results of classical co-expression network analysis and establishes a foundation for key genes discovery from time-series multiple species transcriptome data.

Identifiants

pubmed: 36617558
doi: 10.1186/s12870-023-04037-w
pii: 10.1186/s12870-023-04037-w
pmc: PMC9827700
doi:

Substances chimiques

Organic Chemicals 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

16

Subventions

Organisme : National Natural Science Foundation of China
ID : 32070682

Informations de copyright

© 2023. The Author(s).

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Auteurs

Xiaohan Jiang (X)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.

Kangchen Liu (K)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.

Huixiang Peng (H)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.

Jing Fang (J)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.

Aidi Zhang (A)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China.

Yuepeng Han (Y)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China. yphan@wbgcas.cn.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China. yphan@wbgcas.cn.

Xiujun Zhang (X)

Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China. zhangxj@wbgcas.cn.
Center of Economic Botany, Core Botanical Gardens, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China. zhangxj@wbgcas.cn.

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