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Plant Biology and Biotechnology: Focus on Genomics, Bioinformatics and AI

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 402

Special Issue Editors


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Guest Editor
The Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119048 Moscow, Russia
Interests: computer genomics; bioinformatics; digital medicine (e-Health); gene expression regulation; ChIP-seq
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Special Issue Information

Dear Colleagues,

In the study of the molecular mechanisms of plant development and growth, response to environment is important for agrobiotechnology applications. The fast development of machine learning methods and AI (artificial intelligence) applications has revolutionized the methods of computer modeling in plant biotechnology. Sequencing and systems biology approaches offer a comprehensive view of plant growth from the molecular to cellular, organ, and population levels. Sequencing and microscopy technologies make it possible to model protein–protein and gene regulatory interactions in plant cells, providing a basis for better crop production and sustainability. Plant–pathogen interaction studies complement network modeling problems in plant bioinformatics. Note the recent conference Plantgen, 2025 in Novosibirsk, Russia (https://conf.icgbio.ru/plantgen2025/en/), on computer modeling in plants. Based on this rapidly expanding research area, we are pleased to announce this Special Issue on molecular informatics for plant biotechnology, continuing IJMS’s Special Issues on bioinformatics based on sequencing data analysis, entitled “Plant Biology and Biotechnology: Focus on Genomics, Bioinformatics and AI”  (https://www.mdpi.com/journal/ijms/special_issues/PlantBi_Biology).

For this Special Issue, we aim to collate works focused on the following topics:

  1. computer model of gene expression regulation in plants;
  2. plant genomics and bioinformatics using AI methods;
  3. miRNA and molecular mechanisms of gene regulation in plants;
  4. digital phenotyping using machine learning tools;
  5. the sequencing of novel model organisms for biotechnology.

Prof. Dr. Yuriy L. Orlov
Prof. Dr. Ming Chen
Guest Editors

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Keywords

  • gene expression regulation in plants
  • ncRNA and gene editing in plants
  • AI applications in plant bioinformatics
  • molecular mechanisms of stress resistance in plants
  • ncRNA and gene editing in plants
  • plant–pathogen interactions
  • systems biology and ecological networks for agrobiology
  • next-generation sequencing in plants
  • modeling of plant cell growth
  • gene networks and pathway modeling in plants
  • computer phenotyping of plants

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Published Papers (1 paper)

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Review

22 pages, 1889 KiB  
Review
DNA-Barcoding for Cultivar Identification and Intraspecific Diversity Analysis of Agricultural Crops
by Lidiia S. Samarina, Natalia G. Koninskaya, Ruset M. Shkhalakhova, Taisiya A. Simonyan and Daria O. Kuzmina
Int. J. Mol. Sci. 2025, 26(14), 6808; https://doi.org/10.3390/ijms26146808 - 16 Jul 2025
Viewed by 286
Abstract
DNA barcoding of intraspecific diversity of agricultural crops is important to develop the genetic passports of valuable genotypes and cultivars. The advantage of DNA-barcoding as compared to traditional genotyping of cultivars is that the procedure can be unified and applied for the broad [...] Read more.
DNA barcoding of intraspecific diversity of agricultural crops is important to develop the genetic passports of valuable genotypes and cultivars. The advantage of DNA-barcoding as compared to traditional genotyping of cultivars is that the procedure can be unified and applied for the broad range of accessions. This not only makes it cost efficient, but also allows to develop open access genetic databases to accumulate information of the world’s germplasm collections of different crops. In this regard, the aim of the review was to analyze the latest research in this field, including the selection of loci, universal primers, strategies of amplicons analysis, bioinformatic tools, and the development of databases. We reviewed the advantages and disadvantages of each strategy with the focus of cultivars identification. The data indicates that following chloroplast loci are the most prominent for the intraspecific diversity analysis: (trnE-UUC/trnT-GUU, rpl23/rpl2.l, psbA-trnH, trnL-trnF, trnK, rpoC1, ycf1-a, rpl32-trnL, trnH-psbA and matK). We suggest that the combination of three or four of these loci can be a sufficient DNA barcode for cultivar-level identification. This combination has to be selected for each crop. Advantages and disadvantages of different approaches of amplicons analysis are discussed. The bioinformatic tools and databases for the plant barcoding are reviewed. This review will be useful for selecting appropriate strategies for barcoding of intraspecific diversity of agricultural crops to develop genetic passports of valuable cultivars in germplasm collections worldwide. Full article
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