Advances and challenges in plant molecular marker technologies and their applications in the artificial intelligence empowered era

Plant molecular marker technologies have reshaped crop genetics and breeding by making it possible to analyse genome-wide variation with a precision that phenotype-based selection, even in experienced programmes, cannot reach in routine practice. This review summarises recent progress in marker platforms from classical RFLP and SSR systems to high-throughput SNP genotyping, with emphasis on KASP, multiple nucleotide polymorphism and multi-gene panel technologies, and on sequencing-based methods such as GBS, GBTS and Hyper-seq that often serve as an upstream discovery layer for targeted assays and databases. These platforms are increasingly integrated into practical workflows for marker-assisted and genomic selection, DNA fingerprinting, germplasm characterisation and plant variety protection, and multi-locus markers have become a central tool for high-resolution DUS testing and EDV determination that adds an independent layer of evidence to morphology-based assessments. Key challenges now include cross-platform standardisation, design of marker panels that balance cost with information content, interoperability of databases across institutions and countries, and the definition of molecular distance thresholds that are acceptable both biologically and in legal and regulatory settings. The review also considers the rapid integration of molecular marker data with artificial intelligence, including AI-driven marker discovery and panel optimisation, genomic prediction in multi-environment trials and the concept of an intelligent seed-industry operating system that links genotypic, phenotypic and environmental information in a coherent data framework. These developments collectively point to a shift from isolated marker assays towards platform-level, AI-supported infrastructures that can accelerate variety innovation and contribute to the modernisation and quality improvement of the seed industry.

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Publication Details

Journal
Frontiers in Plant Science
Published
2026-01-15
DOI
https://doi.org/10.3389/fpls.2025.1757949
Citations
2
Primary Topic
Plant Genetic and Mutation Studies
Type
article
Field-Weighted Citation Impact
62.68

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article

Advances and challenges in plant molecular marker technologies and their applications in the artificial intelligence empowered era

Weilin Pu, W. Yu, Zhenchen Zhang, Xiaoxu Li et al.
2 citations
Frontiers in Plant Science
Plant Genetic and Mutation Studies
62.68
article

Advances and challenges in plant molecular marker technologies and their applications in the artificial intelligence empowered era

Weilin Pu, W. Yu, Zhenchen Zhang, Xiaoxu Li, He Xie, Xuebo Wang, Yangyang Li, Pingjun Huang, Xiaonian Yang, Weicai Zhao, Jiashuo Yang, Xinyao Zhang, Zhengrong Hu
article en
2 citations

Abstract

Plant molecular marker technologies have reshaped crop genetics and breeding by making it possible to analyse genome-wide variation with a precision that phenotype-based selection, even in experienced programmes, cannot reach in routine practice. This review summarises recent progress in marker platforms from classical RFLP and SSR systems to high-throughput SNP genotyping, with emphasis on KASP, multiple nucleotide polymorphism and multi-gene panel technologies, and on sequencing-based methods such as GBS, GBTS and Hyper-seq that often serve as an upstream discovery layer for targeted assays and databases. These platforms are increasingly integrated into practical workflows for marker-assisted and genomic selection, DNA fingerprinting, germplasm characterisation and plant variety protection, and multi-locus markers have become a central tool for high-resolution DUS testing and EDV determination that adds an independent layer of evidence to morphology-based assessments. Key challenges now include cross-platform standardisation, design of marker panels that balance cost with information content, interoperability of databases across institutions and countries, and the definition of molecular distance thresholds that are acceptable both biologically and in legal and regulatory settings. The review also considers the rapid integration of molecular marker data with artificial intelligence, including AI-driven marker discovery and panel optimisation, genomic prediction in multi-environment trials and the concept of an intelligent seed-industry operating system that links genotypic, phenotypic and environmental information in a coherent data framework. These developments collectively point to a shift from isolated marker assays towards platform-level, AI-supported infrastructures that can accelerate variety innovation and contribute to the modernisation and quality improvement of the seed industry.

Frontiers in Plant ScienceVol. 16
China Tobacco (CN), Tobacco Research Institute (CN), Guangdong Academy of Agricultural Sciences (CN), Fujian Tobacco Industry Limited Liability Company (China) (CN), Yunnan Academy of Agricultural Sciences (CN), Chinese Academy of Agricultural Sciences (CN), Beijing Academy of Science and Technology (CN)
China National Tobacco Corporation
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Plant Genetic and Mutation Studies
62.68
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