Cotton Genomics and Genetics 2025, Vol.16, No.3, 107-116 http://cropscipublisher.com/index.php/cgg 112 tools are accurate enough. What is more troublesome is that the differentiation process of fiber cells is complex in itself. Sometimes the same cell group expresses completely different genes at different developmental stages. With existing technology, it is difficult to capture these changes and their precise location in the tissue at the same time. In other words, we know there is a change, but we don’t know where it occurs; or we can see what is expressed, but we don’t know which type of cell is responsible. This vague state directly affects our understanding of how cell types are specifically regulated (Fang et al., 2018). Figure 2 Statistics of transcription factor expression in different tissues of cotton. (a) Quantity and classification of transcription factor families. A total of 1 467 different transcription factors were annotated in 46 transcription factor families. The numbers represent the percentages of transcription factor genes. (b-e) Detailed illustration of the expression of transcription factors related to fiber elongation and development. The x-axis indicates the distribution of transcription factors in seven different tissues of cotton. The y-axis represents the FPKM value of each transcription factor in different tissues (Adopted from Yang et al., 2021) 7.2 Need for high-quality, cell-type-specific epigenomic maps Many times, we don't actually lack data. The problem is that most existing epigenomic maps come from "mixed samples", that is, the average level measured by mixing many types of cells together. For fibroblasts, this information is not accurate enough. Their respective chromatin states and their own unique regulatory patterns are all obscured. What is really lacking now is a "single perspective" map for different types of fibroblasts at different
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