Cotton Genomics and Genetics 2025, Vol.16, No.5, 232-240 http://cropscipublisher.com/index.php/cgg 236 are designed to identify the connection points of reverse splicing, as this type of splicing method is unique to circRNA. However, the performance of different tools varies and is not completely uniform. Some studies have compared CIRI, find_circ, CIRCexplorer, etc., and found that their results were quite consistent when identifying highly expressed circrnas. However, when encountering low abundance or special types, there would be differences, and even false positive results specific to the tools themselves would occur (Hansen, 2018). Therefore, many studies will adopt a compromise approach-integrating the results of several tools to enhance the overall reliability. In multiple developmental stages and varieties of cotton, this type of method has detected hundreds and thousands of circular RNAs. 5.2 Databases and repositories of plant circRNAs, including cotton-specific resources At present, for the study of circular RNA in plants, the database is passable, but it is still far from being "perfect". In fact, many databases are borrowed from animals. There are not many that are specifically designed for plants, let alone for cotton. However, some resource libraries do already cover the circular RNA data of cotton, as well as that of other crops. This type of resource not only integrates RNA sequencing data, but also incorporates the predicted circular RNA sequences and annotation information, which is helpful for subsequent functional studies and cross-species comparisons (Gao and Zhao, 2018). Although their coverage is still limited at present, they at least provide researchers with a starting point to enter. 5.3 Challenges in accurately annotating and quantifying circRNAs in complex genomes It is indeed quite difficult to accurately annotate and quantify circrnas in plants with complex genomes like cotton. The problem is not one or two, but the accumulation of multiple factors. For instance, cotton is polyploid, with high sequence similarity in many regions of the genome and a large number of repetitive elements, which makes the localization of reverse splicing sites tricky (Zhao et al., 2017). Furthermore, algorithms are not omnipotent. Different tools often have poor recognition ability for low-expression and atypical splicing circrnas and may even report errors (Dong et al., 2023). What is even more troublesome is that some genomes themselves are not fully annotated, especially the circRNA reference set for plants, where the available information is relatively limited, making it extremely difficult to predict from scratch and compare across samples. Moreover, circular RNAs and linear transcripts often overlap, and with their different expressions in various tissues and under different conditions, it becomes difficult to conduct accurate quantitative analysis. Nowadays, many studies are attempting to adopt combined strategies, such as improving annotations, developing reference resources specifically for cotton, or integrating the recognition results of multiple tools, to enhance the quality of analysis. These works are precisely the key directions of current research. 6 Case Study 6.1 Identification of key circRNAs acting as miR156/miR828 sponges in fiber cells When studying the regulatory network of cotton fiber development, in the past, almost all attention was focused on miRNA. However, with the continuous advancement of high-throughput sequencing technology and bioinformatics tools, researchers have begun to turn their attention to those "overlooked roles"-such as circrnas. In fact, studies have found that in cotton fibroblasts, there are some circrnas that may have binding sites for miR156 or miR828. These two mirnas are highly expressed during the initiation and elongation stages of fibers, and are closely related to several key developmental transcription factors (such as SPL and MYB families) (Wang et al., 2017). Although there is currently a lack of direct experimental evidence to fully prove that certain circrnas can indeed "attach" to miR156/miR828, from the perspective of sequence prediction and expression patterns, this possibility is not groundless. Especially in specific fibrous tissues, the existence of multiple circrnas with potential binding sites for these mirnas is already quite revealing in itself. 6.2 Impact on downstream target gene expression When it comes to the regulation of circRNA, it is impossible to avoid its influence on downstream target genes. Especially the two transcription factors, SPL and MYB, they directly determine how fibroblasts differentiate, elongate, and even the efficiency of secondary wall synthesis. Mirnas like miR156/157 usually "target" the SPL gene and inhibit its expression. However, once such mirnas are adsorbed by circrnas, the expression of SPL will
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