Browsing by Author "Chen, Yulin"

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    A decision analysis model for KEGG pathway analysis
    (Springer Nature, 2016-10-06) Du, Junli; Li, Manlin; Yuan, Zhifa; Guo, Mancai; Song, Jiuzhou; Xie, Xiaozhen; Chen, Yulin
    The knowledge base-driven pathway analysis is becoming the first choice for many investigators, in that it not only can reduce the complexity of functional analysis by grouping thousands of genes into just several hundred pathways, but also can increase the explanatory power for the experiment by identifying active pathways in different conditions. However, current approaches are designed to analyze a biological system assuming that each pathway is independent of the other pathways. A decision analysis model is developed in this article that accounts for dependence among pathways in time-course experiments and multiple treatments experiments. This model introduces a decision coefficient—a designed index, to identify the most relevant pathways in a given experiment by taking into account not only the direct determination factor of each Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway itself, but also the indirect determination factors from its related pathways. Meanwhile, the direct and indirect determination factors of each pathway are employed to demonstrate the regulation mechanisms among KEGG pathways, and the sign of decision coefficient can be used to preliminarily estimate the impact direction of each KEGG pathway. The simulation study of decision analysis demonstrated the application of decision analysis model for KEGG pathway analysis. A microarray dataset from bovine mammary tissue over entire lactation cycle was used to further illustrate our strategy. The results showed that the decision analysis model can provide the promising and more biologically meaningful results. Therefore, the decision analysis model is an initial attempt of optimizing pathway analysis methodology.
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    Whole-genome bisulfite sequencing of goat skins identifies signatures associated with hair cycling
    (Springer Nature, 2018-08-28) Li, Chao; Li, Yan; Zhou, Guangxian; Gao, Ye; Ma, Sen; Chen, Yulin; Song, Jiuzhou; Wang, Xiaolong
    Hair follicles (HFs), upon development, undergo repetitive cycles of growth (anagen), regression (catagen), and rest (telogen). The transition between the stages is determined by multiple molecular signals, including DNA methylation, which plays important roles in mammalian cellular identity and is essential for the development of HFs. Secondary hair follicles (SHFs) in cashmere goat exhibit classic cyclic hair development, and little has been done on a genome-wide scale to examine potentially methylated genes involved in the hair cyclic transition. Genome-wide DNA methylation profiles between skin tissues sampled during the anagen and telogen stages in cashmere goats were investigated using whole-genome bisulfite sequencing (WGBS). The methylation status was observed to be higher in the skin samples with HFs in the telogen than those in the anagen stage. A total of 1311 differentially methylated regions (DMRs) were identified between the two groups, which contained 493 fully annotated DMR-related genes (DMGs) (269 Hyper- DMGs and 224 Hypo-DMGs). Furthermore, a significant over-representation of the functional categories for DMGs related to immune response and intercellular crosstalk during hair cycling was observed. By integrating DNA methylation and mRNA expression data, we revealed that four genes (FMN1, PCOLCE, SPTLC3, and COL5A1) are crucial factors for elucidating epigenetic mechanisms contributing to the telogen-to-anagen transition. Our study provided systematic methylome maps pertaining to the hair cycling stages (anagen vs telogen) at a single-base resolution, and revealed stage-specific methylation loci during cashmere growth or quiescence. Furthermore, we identified epigenetically regulated genes that are potentially involved in HF development and growth in cashmere goats, and likely in other mammal species.