Transcriptome profiling identifies tissue-specific genes regulating sugar metabolism in Actinidia valvata Dunn

Yuexia Wang; Shiming Han; Muhammad Shahr Yar Ali; Shuai Zheng; Jihong Dong; Muhammad Sajjad; Yumei Fang

doi:doi.org/10.35495/ajab.2025.035

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Transcriptome profiling identifies tissue-specific genes regulating sugar metabolism in Actinidia valvata Dunn

Author(s)

Yuexia Wang School of Public Administration, China University of Mining and Technology, Xuzhou, Jiangsu, China; School of Biological Sciences and Technology, Liupanshui Normal University, Liupanshui, P.R. China

Shiming Han School of Public Administration, China University of Mining and Technology, Xuzhou, Jiangsu, China; School of Biological Sciences and Technology, Liupanshui Normal University, Liupanshui, P.R. China

Muhammad Shahr Yar Ali Department of Biosciences, COMSATS University Islamabad,Islamabad 45550,Pakistan

Shuai Zheng School of Biological Sciences and Technology, Liupanshui Normal University,Liupanshui,P.R. China

Jihong Dong School of Public Administration, China University of Mining and Technology,Xuzhou, Jiangsu,China

Muhammad Sajjad Department of Biosciences, COMSATS University Islamabad,Islamabad 45550,Pakistan

Yumei Fang School of Biological Sciences and Technology, Liupanshui Normal University,Liupanshui,P.R. China

Abstract

Actinidia valvata Dunn is a fruit tree that originated in China and is well recognized for its nutrient, health, and medicinal value. With the aim of identifying the nutrients involved, this study conducted a comprehensive transcriptome analysis of the stem, leaf, and fruit of A. valvata using the Illumina HiSeq platform. RNA-Seq analysis produced 39.03 GB of clean data and further identified a total of 50,928 unigenes with an average length of 1,236.40 bp. Functional annotation of these unigenes was carried out by comparing them with several databases. This resulted in the incorporation of annotated information regarding 32,202 unigenes, which constituted 63.23% of the total. Moreover, 11,809 unigenes participated in 129 unique metabolic pathways. Comparative analysis of gene expression across various tissues led to the identification of differentially expressed genes (DEGs). Among these, 26 DEGs were closely associated with sugar metabolism pathways. Moreover, correlation analysis between total sugar content and expression of the DEGs implied in sugar metabolism proved that the identified key genes SUS, INV, SPS, HK, malZ, and GPI have strong functions in sugar metabolism in A. valvata. Our findings reveal that sucrose synthase (SUS) and invertase (INV) are critical drivers of sugar accumulation in fruits, providing targets for breeding sweeter kiwifruit varieties.

Publication Details

Page(s) 1-15

DOI doi.org/10.35495/ajab.2025.035

Published Journal: Asian Journal of Agriculture and Biology, Volume: 3, Issue: 0, Year: 2025

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Keywords

SUS, DEGS, A, INV, Sugar metabolism, Kiwi berry, Total phenolic, SPS, valvata

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