Advances in Fruit Tree Transcriptomics and Gene Expression Analysis
A special issue of Plants (ISSN 2223-7747).
Deadline for manuscript submissions: 31 May 2026 | Viewed by 3
Special Issue Editors
Interests: molecular biology; plant breeding; genetic improvement; transcriptomics; gene expression; genetic diversity; olives; fruit trees; biotic/abiotic stresses
Special Issues, Collections and Topics in MDPI journals
Interests: biotecnology; plant breeding; genetic improvement; transcriptomics; gene expression; genetic diversity; grapes; fruit trees; abiotic stresses
Interests: biotechnology; plant breeding; genetic improvement; transcriptomics; gene expression; genetic diversity; olives; fruit trees; biotic stresses; in vitro culture
Special Issue Information
Dear Colleagues,
The analysis of gene expression in arboreal species plays a key role in elucidating the molecular mechanisms behind plant development, stress response, seasonal adaptation, and trait improvement. Transcriptomic approaches offer deep insights into regulatory networks, providing a valuable source in identifying stress-responsive genes and pathways such as those involved in drought, salinity, cold, and pathogen defense, as well as genes related to fruit development, dormancy regulation, and epigenetic transmission.
This Special Issue aims to provide contributions on gene expression studies across any tree species. We will consider manuscripts employing transcriptomic techniques as well as targeted gene expression analyses focusing on the following topics:
Stress response mechanisms: Differential expression studies elucidating how trees respond to biotic and abiotic stresses, including the identification of transcription factors, signaling components, and epigenetic regulators related to stress resilience.
Genetic improvement and fruit‑trait regulation: Expression profiles related to fruit size, ripening, flavor, hormone regulation, and developmental timing in fruit trees. Studies linking gene expression to agronomically relevant traits and leveraging transcriptomic data for marker development and breeding are also encouraged.
Fundamental pathway elucidation: The investigation of gene networks involved in dormancy, flowering time, wood formation, epigenetic memory, and seasonal growth cycles. Works that integrate transcriptome data to advance understanding of core biological processes across arboreal taxa will be particularly valuable.
Dr. Valentina Fanelli
Dr. Isabella Mascio
Dr. Michele Savoia
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- fruit trees
- transcriptomic
- gene expression
- biotic/abiotic stresses
- genetic improvement
- breeding
- epigenetic
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