MF network analysis. (A) PpPG21 and PpPG22 GCNs and the MF network. Biological processes of interest are highlighted in the MF network. TF: transcription factor, CYP450: cytochrome P450. (B) Gene set enrichment analysis of the MF network..
Newswise — Peach genetics faces challenges such as long intergeneration times and limited genetic transformation systems, making gene identification and validation complex. Traditional approaches often fall short in predicting gene functions due to these limitations. Gene coexpression networks (GCNs), which map the relationships between gene expressions, offer a promising solution. By leveraging the 'guilty-by-association' principle, GCNs can predict gene functions based on shared expression patterns. Due to these challenges, there is a pressing need for innovative tools like GCNs to enhance our understanding of peach genetics.
Researchers from the Institut de Recerca i Tecnologia Agroalimentàries (IRTA) and Centre de Recerca en Agrigenòmica (CRAG) have made a significant stride in agricultural genomics. Published study (DOI: 10.1093/hr/uhad294) in the prestigious journal Horticulture Research on January 2, 2024, the study introduces a new tool that leverages GCNs to predict gene functions in peaches, potentially revolutionizing fruit breeding.
The study created four GCNs from 604 Illumina RNA-Seq libraries and evaluated their performance using a machine-learning algorithm based on the 'guilty-by-association' principle. Among the networks, COO300 showed the best performance, encompassing 21,956 genes. To validate COO300, researchers conducted two case studies. In the first case study, genes PpPG21 and PpPG22, involved in peach fruit softening, were analyzed. The coexpressed genes formed the melting flesh (MF) network, which was enriched with terms related to cell wall organization and phytohormone signaling. The MF network included genes associated with cell wall disassembly and ripening-related phytohormones, demonstrating COO300's ability to predict gene functions accurately. In the second case study, the transcription factor PpMYB10.1, which regulates anthocyanin accumulation, was examined. The fruit color (FC) network identified genes involved in anthocyanin metabolism and regulation. By comparing the FC network with grapevine orthologs, researchers identified conserved regulatory networks, further validating COO300's predictive capabilities.
Dr. Iban Eduardo, a leading researcher at CRAG, stated, "The development of the COO300 network represents a significant breakthrough in peach genetics. By accurately predicting gene functions, this tool not only enhances our understanding of peach biology but also paves the way for more targeted and efficient breeding strategies."
The study's impact is profound, offering breeders a powerful tool to enhance peach varieties. By decoding gene functions, the PeachGCN v1.0 and its scripts, accessible to all, will drive advancements in flavor, longevity, and nutrition of peaches. This genomic insight is a harbinger of change, signaling a shift towards data-driven breeding in agriculture.
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References
DOI
Original Source URL
https://doi.org/10.1093/hr/uhad294
Funding information
We acknowledge financial support through the Severo Ochoa Programme for Centers of Excellence in R&D (SEV-2015-0533 and CEX2019-000902-S). Also, this work was funded by the Spanish Ministry of Science and Innovation through the Estate Agency of Research: Project PID2020-118612RR-I00 (Better Almonds) and PID2019-110599RR-I00. Authors F.P. C., I. E., I. B. are grateful to CERCA Program from Generalitat of Catalonia for its support. F. P. C. wishes to acknowledge the receipt of a FPI doctoral fellowship from the Spanish Ministry of Science and Innovation. This work was also supported by grants PID2021-128865NB-I00 and RYC-2017-23645 awarded to J.T.M. and the PRE2019-088044 fellowship awarded to L.O. from the Ministerio de Ciencia, Innovación y Universidades (MCIU, Spain), Agencia Estatal de Investigación (AEI, Spain), and Fondo Europeo de Desarrollo Regional (FEDER, European Union).
About Horticulture Research
Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2022. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.
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