Table_1_m6A Methylation Analysis of Differentially Expressed Genes in Skin Tissues of Coarse and Fine Type Liaoning Cashmere Goats.docx
N6-methyladenosine (m6A) is the most common internal modification in mRNAs of all higher eukaryotes. Here we perform two high-throughput sequencing methods, m6A-modified RNA immunoprecipitation sequence (MeRIP-seq) and RNA sequence (RNA-seq) to identify key genes with m6A modification in cashmere fiber growth. A total of 9,085 m6A sites were differentially RNA m6A methylated as reported from by MeRIP-seq, including 7,170 upregulated and 1,915 downregulated. In addition, by comparing m6A-modified genes between the fine-type Liaoning cashmere goat (FT-LCG) and coarse-type Liaoning Cashmere Goat (CT-LCG) skin samples, we obtain 1,170 differentially expressed genes. In order to identify the differently methylated genes related to cashmere fiber growth, 19 genes were selected to validate by performing qRT-PCR in FT-LCG and CT-LCG. In addition, GO enrichment analysis shows that differently methylated genes are mainly involved in keratin filament and intermediate filament. These findings provide a theoretical basis for future research on the function of m6A modification during the growth of cashmere fiber.
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References
- https://doi.org//10.1016/j.celrep.2015.09.015
- https://doi.org//10.1016/s1534-5807(02)00167-3
- https://doi.org//10.1080/10495398.2012.750245
- https://doi.org//10.1007/s10709-016-9914-1
- https://doi.org//10.1007/s10709-017-9950-5
- https://doi.org//10.1080/10495398.2017.1356731
- https://doi.org//10.1093/nar/gkp335
- https://doi.org//10.1016/0022-2836(77)90047-x
- https://doi.org//10.1038/cr.2014.162
- https://doi.org//10.1360/yc-006-1078
- https://doi.org//10.1093/nar/gkx1030
- https://doi.org//10.1073/pnas.71.10.3971
- https://doi.org//10.1038/nature11112
- https://doi.org//10.1093/nar/2.10.1653
- https://doi.org//10.4238/2015.December.22.15
- https://doi.org//10.1038/253374a0
- https://doi.org//10.1038/nature20577
- https://doi.org//10.1016/j.molcel.2010.05.004
- https://doi.org//10.1038/nature14101
- https://doi.org//10.1038/nature05766
- https://doi.org//10.1016/j.molcel.2017.08.003
- https://doi.org//10.1007/s11033-010-9968-6
- https://doi.org//10.1038/nmeth.3317
- https://doi.org//10.1016/j.jid.2018.09.019
- https://doi.org//10.1177/1087057115623264
- https://doi.org//10.1186/1471-2407-11-137
- https://doi.org//10.1038/cr.2017.117
- https://doi.org//10.3390/ijms16059152
- https://doi.org//10.1371/journal.pone.0147124
- https://doi.org//10.14806/ej.17.1.200
- https://doi.org//10.1016/j.ymeth.2014.06.008
- https://doi.org//10.1146/annurev-cellbio-100616-060758
- https://doi.org//10.1038/nbt.3122
- https://doi.org//10.1371/journal.pgen.1000748
- https://doi.org//10.1016/j.jprot.2012.03.027
- https://doi.org//10.1093/bioinformatics/btp616
- https://doi.org//10.1046/j.0022-202X.2003.22128.x
- https://doi.org//10.1046/j.1523-1747.1999.00775.x
- https://doi.org//10.1111/j.1600-0625.2010.01217.x
- https://doi.org//10.1152/physrev.2001.81.1.449
- https://doi.org//10.2217/epi-2019-0002
- https://doi.org//10.1016/j.neuron.2017.12.036
- https://doi.org//10.1371/journal.pone.0167322
- https://doi.org//10.3724/SP.J.1005.2012.00719
- https://doi.org//10.1038/s41422-018-0040-8
- https://doi.org//10.1111/j.1600-0625
- https://doi.org//10.1093/bioinformatics/btv145
- https://doi.org//10.1093/gigascience/giy105
- https://doi.org//10.1007/s11033-008-9325-1
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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