Bioscience Evidence 2025, Vol.15, No.5, 219-227 http://bioscipublisher.com/index.php/be 219 Review Article Open Access Bioinformatics Tools for Cotton Genomics: A Review Zhen Li Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China Corresponding email: zhen.li@hibio.org Bioscience Evidence, 2025, Vol.15, No.5 doi: 10.5376/be.2025.15.0022 Received: 24 Jul., 2025 Accepted: 29 Aug., 2025 Published: 15 Sep., 2025 Copyright © 2025 Li, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li Z., 2025, Bioinformatics tools for cotton genomics: a review, Bioscience Evidence, 15(5): 219-227 (doi: 10.5376/be.2025.15.0022) Abstract The development of cotton genomics is closely related to new technologies. High-throughput sequencing enables us to obtain more data, and there are also an increasing number of bioinformatics tools. Some commonly used platforms nowadays include CottonFGD, CottonMD, CottonGen and CottonGVD. These databases collect information at different levels such as the genome, transcriptome, epigenome, metabolome and phenotype. Researchers can use them for gene function annotation, variation detection, trait analysis and molecular breeding. These tools have significantly enhanced research efficiency, helped us better understand complex traits, and promoted precise breeding. In the future, long-read sequencing, pan-genomics, multi-omics integration, and artificial intelligence will all bring new impetus to research. The aim of this study is to summarize the application of these tools and explore their role in precise cotton breeding. Keywords Cotton genomics; Bioinformatics tools; Multi-omics database; Precision breeding; Mining of functional genes 1 Introduction Cotton (Gossypium spp.) is one of the most important natural fiber crops in the world and also an important source of oil. It not only supports the textile industry, but also provides food and feed by-products (Yu et al., 2013; Yang et al., 2020). With the continuous increase in population and the pressure of climate change, the demand for high-yield, high-quality and stress-resistant cotton is growing. The development of genomics has provided new methods and tools for genetic improvement and trait research of cotton (Yu et al., 2013; Naoumkina and Kim, 2023). Through in-depth studies of whole-genome, transcriptomic and epigenomic data, scientists can identify genes related to important traits more quickly, promoting molecular breeding and precise selection (Yang et al., 2022; Khalilisamani et al., 2024). However, the cotton genome is large and complex, and the amount of data is also very large. The traditional analytical methods are no longer sufficient. Bioinformatics tools have thus become key assistants in research. Nowadays, there are many databases and platforms, such as CottonGen, CottonFGD, CottonMD and CottonGVD. These platforms integrate multiple types of data such as genomics, transcriptomics, variations, epigenetics and metabolomics, and are also equipped with functions such as BLAST, gene annotation, QTL mapping, GWAS and co-expression networks (Yu et al., 2013; 2015; Zhu et al., 2017; Yang et al., 2020; Peng et al., 2021; Yang et al., 2022). These tools can conduct single-gene research, multi-omics and cross-species batch analysis, and visualize the results to assist in cotton functional genomics and molecular breeding research. This article mainly sorts out the commonly used bioinformatics tools and applications in the current field of cotton genomics, with a focus on the integration and analysis of genomic, transcriptomic, epigenomic and variant data. We will also discuss the role of these tools in trait research, stress resistance exploration and molecular breeding, as well as the challenges faced in the research, and look forward to future development directions. It is hoped that this can provide references for researchers and promote the genetic improvement and industrial upgrading of cotton. 2 Cotton Genomics Landscape 2.1 Overview of cotton genome structure and evolution (diploid vs. allotetraploid) The genus Gossypium has approximately 50 species. They were divided into eight diploid groups (A-G, K) and one allotetraploid group (AD) (Chen et al., 2017). The genomic structure of diploid cotton (such as G. arboreum
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