Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives

Genomic imprinting is an epigenetic occurrence that results in the expression of alleles specific to the parent of origin, plays pivotal roles in plant development, stress adaptation, and agronomic trait regulation. While imprinting has been intensively investigated in model plants (e.g. Arabidopsis, maize, and rice), its dynamic regulatory mechanisms and evolutionary implications remain enigmatic. Recent advances in bioinformatics-including single-cell omics, machine learning, and deep learning-have revolutionized the identification, functional annotation, and network modeling of imprinted genes. This review not only provides a detailed summary of the identification, functions and regulatory mechanisms of plant imprinted genes, but also systematically summarizes methodologies for studying plant genomic imprinting, highlights challenges in multi-omics data integration, and envisions artificial intelligence-driven strategies for epigenetic breeding.

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Publication Details

Journal
Briefings in Functional Genomics
Published
2025-12-12
DOI
https://doi.org/10.1093/bfgp/elaf025
Primary Topic
Plant Molecular Biology Research
Type
article
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article

Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives

Xiaotong Jing, Quan Zou, Xi Su, Mengting Niu
Briefings in Functional Genomics
Plant Molecular Biology Research
article

Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives

Xiaotong Jing, Quan Zou, Xi Su, Mengting Niu
article en

Abstract

Genomic imprinting is an epigenetic occurrence that results in the expression of alleles specific to the parent of origin, plays pivotal roles in plant development, stress adaptation, and agronomic trait regulation. While imprinting has been intensively investigated in model plants (e.g. Arabidopsis, maize, and rice), its dynamic regulatory mechanisms and evolutionary implications remain enigmatic. Recent advances in bioinformatics-including single-cell omics, machine learning, and deep learning-have revolutionized the identification, functional annotation, and network modeling of imprinted genes. This review not only provides a detailed summary of the identification, functions and regulatory mechanisms of plant imprinted genes, but also systematically summarizes methodologies for studying plant genomic imprinting, highlights challenges in multi-omics data integration, and envisions artificial intelligence-driven strategies for epigenetic breeding.

Briefings in Functional GenomicsVol. 25
University of Electronic Science and Technology of China (CN), Shenzhen Polytechnic University (CN), Foshan Maternity and Child Health Care Hospital (CN), Quzhou University (CN)
Zero hunger
Openalex Percentile: Top 22%
Plant Molecular Biology Research
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