Cotton Genomics and Genetics 2025, Vol.16, No.1, 39-47 http://cropscipublisher.com/index.php/cgg 40 important agronomic traits, and how to use genomic methods in cotton breeding. By collating and integrating the contents of different studies, this study hopes to show the current level of research, point out the problems that still exist, and put forward some ideas for how to use comparative genomics to improve cotton traits in the future. 2 Comparative Genomics Platforms and Tools for Cotton 2.1 Genome sequencing of cotton species Today’s high-throughput sequencing technology is very advanced, and high-quality reference genomes of many diploid and tetraploid cotton species can be obtained, which lays the foundation for comparative studies and trait improvement (Manivannan and Amal, 2023). Technologies such as long-read sequencing can better assemble complete gene transcripts and help us understand the complex polyploid genome of cotton more clearly. These technologies can also find genes related to fiber development and stress resistance. There are currently some databases, such as CottonGen and CottonFGD, that integrate these genomic information, annotation data, genetic markers, and trait loci, which can be used by researchers and breeders to search for information, analyze or do breeding (Zhu et al., 2017). 2.2 Synteny and orthology analysis Not all genes are preserved in evolution, but some regions can persist between different cotton varieties. At this time, synteny and orthology analysis are very important. They can help us see which gene regions remain relatively stable and connect the genetic relationships between varieties. Databases like CottonGen provide many practical tools. Not only can you view genetic maps, but you can also directly compare genes to see which are "relatives" to each other (Yu et al., 2013). Of course, this kind of analysis is not just for the sake of looking at the map. The more practical significance is that we can use it to find key genes that may be related to traits, and sometimes even transfer existing trait information. Digging down along these clues can further clarify the evolution of the cotton genome and the genetic loci related to some important agronomic traits (Yu et al., 2015). 2.3 Comparative gene expression and regulation Comparative gene expression studies use a large amount of transcriptome data from different cotton tissues and varieties. With this data, researchers can see which genes are controlling the regulatory network of important cotton traits (Yang et al., 2022b). Now, some databases, such as CottonMD and CottonFGD, have collected a lot of transcriptome, epigenomic and metabolome data (Figure 1). These data can help us analyze how genes are expressed and see which regulatory factors are related to trait changes. With the help of these resources, we can more easily find key genes and regulatory pathways, which is very helpful for trait improvement and functional research (Ashraf et al., 2018). Figure 1 Overview of CottonMD. Construction pipeline of CottonMD through integration of multi-omics data (Adopted from Yang et al., 2022b)
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