Zhihong Wu1, Erhan Hai1, Zhengyang Di1, Rong Ma1, Fangzheng Shang1, Yu Wang2, Min Wang1, Lili Liang1, Youjun Rong1, Jianfeng Pan1, Wenbin Wu3, Rui Su1, Zhiying Wang1, Ruijun Wang1, Yanjun Zhang1,4, Jinquan Li1,5,6,4. 1. College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, China. 2. College of Veterinary Medicine, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, China. 3. Zhenlai Hehe Animal Husbandry Development Co., Ltd, Baicheng, China. 4. Engineering Research Center for Goat Genetics and Breeding, Hohhot, Inner Mongolia Autonomous Region, China. 5. Key Laboratory of Animal Genetics, Breeding and Reproduction, Hohhot, Inner Mongolia Autonomous Region, China. 6. Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China.
Abstract
OBJECTIVE: Mature hair follicles represent an important stage of hair follicle development, which determines the stability of hair follicle structure and its ability to enter the hair cycle. Here, we used weighted gene co-expression network analysis (WGCNA) to identify hub genes of mature skin and hair follicles in Inner Mongolian cashmere goats. METHODS: We used transcriptome sequencing data for the skin of Inner Mongolian cashmere goats from fetal days 45-135 days, and divided the co expressed genes into different modules by WGCNA. Characteristic values were used to screen out modules that were highly expressed in mature skin follicles. Module hub genes were then selected based on the correlation coefficients between the gene and module eigenvalue, gene connectivity, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The results were confirmed by quantitative polymerase chain reaction (qPCR). RESULTS: Ten modules were successfully defined, of which one, with a total of 3166 genes, was selected as a specific module through sample and gene expression pattern analyses. A total of 584 candidate hub genes in the module were screened by the correlation coefficients between the genes and module eigenvalue and gene connectivity. Finally, GO/KEGG functional enrichment analyses detected WNT10A as a key gene in the development and maturation of skin hair follicles in fetal Inner Mongolian cashmere goats. qPCR showed that the expression trends of 13 genes from seven fetal skin samples were consistent with the sequencing results, indicating that the sequencing results were reliable.n.
OBJECTIVE: Mature hair follicles represent an important stage of hair follicle development, which determines the stability of hair follicle structure and its ability to enter the hair cycle. Here, we used weighted gene co-expression network analysis (WGCNA) to identify hub genes of mature skin and hair follicles in Inner Mongolian cashmere goats. METHODS: We used transcriptome sequencing data for the skin of Inner Mongolian cashmere goats from fetal days 45-135 days, and divided the co expressed genes into different modules by WGCNA. Characteristic values were used to screen out modules that were highly expressed in mature skin follicles. Module hub genes were then selected based on the correlation coefficients between the gene and module eigenvalue, gene connectivity, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The results were confirmed by quantitative polymerase chain reaction (qPCR). RESULTS: Ten modules were successfully defined, of which one, with a total of 3166 genes, was selected as a specific module through sample and gene expression pattern analyses. A total of 584 candidate hub genes in the module were screened by the correlation coefficients between the genes and module eigenvalue and gene connectivity. Finally, GO/KEGG functional enrichment analyses detected WNT10A as a key gene in the development and maturation of skin hair follicles in fetal Inner Mongolian cashmere goats. qPCR showed that the expression trends of 13 genes from seven fetal skin samples were consistent with the sequencing results, indicating that the sequencing results were reliable.n.
Authors: Jiyoon Lee; Robert Bӧscke; Pei-Ciao Tang; Byron H Hartman; Stefan Heller; Karl R Koehler Journal: Cell Rep Date: 2018-01-02 Impact factor: 9.423
Authors: Jörg Klufa; Thomas Bauer; Buck Hanson; Craig Herbold; Philipp Starkl; Beate Lichtenberger; Dagmar Srutkova; Daniel Schulz; Igor Vujic; Thomas Mohr; Klemens Rappersberger; Bernd Bodenmiller; Hana Kozakova; Sylvia Knapp; Alexander Loy; Maria Sibilia Journal: Sci Transl Med Date: 2019-12-11 Impact factor: 19.319
Authors: Arthur Sant'Anna Feltrin; Ana Carolina Tahira; Sérgio Nery Simões; Helena Brentani; David Corrêa Martins Journal: PLoS One Date: 2019-01-15 Impact factor: 3.240