Table_3_Integrated Analysis of Methylome and Transcriptome Changes Reveals the Underlying Regulatory Signatures Driving Curly Wool Transformation in Chinese Zhongwei Goats.xlsx
The Zhongwei goat is kept primarily for its beautiful white, curly pelt that appears when the kid is approximately 1 month old; however, this representative phenotype often changes to a less curly phenotype during postnatal development in a process that may be mediated by multiple molecular signals. DNA methylation plays important roles in mammalian cellular processes and is essential for the initiation of hair follicle (HF) development. Here, we sought to investigate the effects of genome-wide DNA methylation by combining expression profiles of the underlying curly fleece dynamics. Genome-wide DNA methylation maps and transcriptomes of skin tissues collected from 45- to 108-day-old goats were used for whole-genome bisulfite sequencing (WGBS) and RNA sequencing, respectively. Between the two developmental stages, 1,250 of 3,379 differentially methylated regions (DMRs) were annotated in differentially methylated genes (DMGs), and these regions were mainly related to intercellular communication and the cytoskeleton. Integrated analysis of the methylome and transcriptome data led to the identification of 14 overlapping genes that encode crucial factors for wool fiber development through epigenetic mechanisms. Furthermore, a functional study using human hair inner root sheath cells (HHIRSCs) revealed that, one of the overlapping genes, platelet-derived growth factor C (PDGFC) had a significant effect on the messenger RNA expression of several key HF-related genes that promote cell migration and proliferation. Our study presents an unprecedented analysis that was used to explore the enigma of fleece morphological changes by combining methylome maps and transcriptional expression, and these data revealed stage-specific epigenetic changes that potentially affect fiber development. Furthermore, our functional study highlights a possible role for the overlapping gene PDGFC in HF cell growth, which may be a predictable biomarker for fur goat selection.
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References
- https://doi.org//10.1038/ncomms10815
- https://doi.org//10.1186/gb-2012-13-10-r87
- https://doi.org//10.1038/gt.2011.208
- https://doi.org//10.1046/j.1365-2133.2004.05775.x
- https://doi.org//10.1016/j.ajhg.2016.10.004
- https://doi.org//10.1016/j.molcel.2012.06.019
- https://doi.org//10.1038/jid.2013.126
- https://doi.org//10.1093/nar/gks1147
- https://doi.org//10.1016/j.cell.2010.03.013
- https://doi.org//10.1093/molbev/msx114
- https://doi.org//10.1038/nbt2478
- https://doi.org//10.1007/978-1-62703-706-8_17
- https://doi.org//10.4238/2015.December.22.15
- https://doi.org//10.1242/jcs.018689
- https://doi.org//10.1111/cup.13050
- https://doi.org//10.1038/nbt3172
- https://doi.org//10.1371/journal.pone.0151118
- https://doi.org//10.1038/jid.2014.292
- https://doi.org//10.1101/gr.143503.112
- https://doi.org//10.1371/journal.pbio.2002117
- https://doi.org//10.1038/jid.2011.364
- https://doi.org//10.1038/nature13544
- https://doi.org//10.1007/978-981-10-8195-8_10
- https://doi.org//10.1017/S1751731109003966
- https://doi.org//10.1016/j.ebiom.2015.02.015
- https://doi.org//10.1016/j.taap.2014.08.019
- https://doi.org//10.1371/journal.pone.0071763
- https://doi.org//10.1038/nmeth3317
- https://doi.org//10.1073/pnas.0703004104
- https://doi.org//10.1093/bioinformatics/btr167
- https://doi.org//10.1046/j.1523-1747.2003.12087.x
- https://doi.org//10.1186/1471-2105-9-559
- https://doi.org//10.1016/j.jid.2016.04.014
- https://doi.org//10.1093/bioinformatics/btp352
- https://doi.org//10.1186/s12864-018-5002-5
- https://doi.org//10.1126/science.aah6102
- https://doi.org//10.1186/s12711-017-0359-5
- https://doi.org//10.1267/ahc.06004
- https://doi.org//10.3389/fphys.2018.00446
- https://doi.org//10.1007/s100380170018
- https://doi.org//10.1111/1523-1747.ep12362866
- https://doi.org//10.1016/j.stem.2011.11.005
- https://doi.org//10.1038/s41467-018-07459-5
- https://doi.org//10.1074/jbc.M110.120659
- https://doi.org//10.1111/exd.12488
- https://doi.org//10.1093/nar/gkw199
- https://doi.org//10.1038/nm3490
- https://doi.org//10.1038/ncb0901-823
- https://doi.org//10.1038/nature08683
- https://doi.org//10.1016/j.devcel.2015.06.023
- https://doi.org//10.1073/pnas.1419161111
- https://doi.org//10.1038/jid.2010.309
- https://doi.org//10.1093/nar/gkw937
- https://doi.org//10.1016/j.jid.2017.06.015
- https://doi.org//10.1091/mbc.E18-08-0488
- https://doi.org//10.1186/s13104-018-3335-4
- https://doi.org//10.1186/s12864-017-4145-0
- https://doi.org//10.1111/exd.13347
- https://doi.org//10.1093/nar/gkl167
- https://doi.org//10.1038/s41598-017-13986-w
- https://doi.org//10.1172/JCI82887
- https://doi.org//10.1093/emboj/cdg560
- https://doi.org//10.1111/j.1600-0625.2011.01274.x
- https://doi.org//10.1111/j.1365-2133.2011.10646.x
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Categories
- Gene and Molecular Therapy
- Biomarkers
- Genetics
- Genetically Modified Animals
- Developmental Genetics (incl. Sex Determination)
- Epigenetics (incl. Genome Methylation and Epigenomics)
- Gene Expression (incl. Microarray and other genome-wide approaches)
- Livestock Cloning
- Genome Structure and Regulation
- Genetic Engineering
- Genomics
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