Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells
Spermatogonial stem cells (SSCs) are exquisitely regulated to reach a balance between proliferation and differentiation in the niche of seminiferous epithelium. Several extrinsic factors such as GDNF are reported to switch the transition, activating various intrinsic signaling pathways. Transcriptom...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Stem Cells International |
| Online Access: | http://dx.doi.org/10.1155/2018/5842714 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832553409795850240 |
|---|---|
| author | Min Wang Wene Zhao Fuqiang Wang Xiufeng Ling Daozhen Chen Tao Zhou Ying Wang |
| author_facet | Min Wang Wene Zhao Fuqiang Wang Xiufeng Ling Daozhen Chen Tao Zhou Ying Wang |
| author_sort | Min Wang |
| collection | DOAJ |
| description | Spermatogonial stem cells (SSCs) are exquisitely regulated to reach a balance between proliferation and differentiation in the niche of seminiferous epithelium. Several extrinsic factors such as GDNF are reported to switch the transition, activating various intrinsic signaling pathways. Transcriptomics analysis could provide a comprehensive landscape of gene expression and regulation. Here, we reanalyzed a previously published transcriptome of two cell types (standing for self-renewing and differentiating SSCs correspondingly). First, we proposed a new parameter, the expression index, to sort the genes considering both absolute and relative expression levels. Using a dynamic statistical model, we identified a list of 1119 candidate genes for SSC self-renewal with the best enrichment of canonical markers. Finally, based on interaction relations, we further optimized the list and constructed a refined network containing integrated information of interactions, expression alternations, biological functions, and disease associations. Further annotation of the 521 refined genes involved in the network revealed an enrichment of well-studied signaling pathways. We believe that the refined network could help us better understand the regulation of SSCs’ fates, as well as find novel regulators or targets for SSC self-renewal or preservation of male fertility. |
| format | Article |
| id | doaj-art-8bdef27d7b4548b2a000d5f74e627ac9 |
| institution | Kabale University |
| issn | 1687-966X 1687-9678 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Stem Cells International |
| spelling | doaj-art-8bdef27d7b4548b2a000d5f74e627ac92025-02-03T05:53:59ZengWileyStem Cells International1687-966X1687-96782018-01-01201810.1155/2018/58427145842714Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem CellsMin Wang0Wene Zhao1Fuqiang Wang2Xiufeng Ling3Daozhen Chen4Tao Zhou5Ying Wang6Centre for Reproductive Medicine, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, ChinaAnalytical and Testing Center, Nanjing Medical University, Nanjing 210004, ChinaAnalytical and Testing Center, Nanjing Medical University, Nanjing 210004, ChinaDepartment of Reproduction, The Affiliated Obstetrics and Gynaecology Hospital of Nanjing Medical University and Nanjing Maternity and Child Health Care Hospital, Nanjing 210004, ChinaCentral Laboratory, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, ChinaCentral Laboratory, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, ChinaDepartment of Reproduction, The Affiliated Obstetrics and Gynaecology Hospital of Nanjing Medical University and Nanjing Maternity and Child Health Care Hospital, Nanjing 210004, ChinaSpermatogonial stem cells (SSCs) are exquisitely regulated to reach a balance between proliferation and differentiation in the niche of seminiferous epithelium. Several extrinsic factors such as GDNF are reported to switch the transition, activating various intrinsic signaling pathways. Transcriptomics analysis could provide a comprehensive landscape of gene expression and regulation. Here, we reanalyzed a previously published transcriptome of two cell types (standing for self-renewing and differentiating SSCs correspondingly). First, we proposed a new parameter, the expression index, to sort the genes considering both absolute and relative expression levels. Using a dynamic statistical model, we identified a list of 1119 candidate genes for SSC self-renewal with the best enrichment of canonical markers. Finally, based on interaction relations, we further optimized the list and constructed a refined network containing integrated information of interactions, expression alternations, biological functions, and disease associations. Further annotation of the 521 refined genes involved in the network revealed an enrichment of well-studied signaling pathways. We believe that the refined network could help us better understand the regulation of SSCs’ fates, as well as find novel regulators or targets for SSC self-renewal or preservation of male fertility.http://dx.doi.org/10.1155/2018/5842714 |
| spellingShingle | Min Wang Wene Zhao Fuqiang Wang Xiufeng Ling Daozhen Chen Tao Zhou Ying Wang Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells Stem Cells International |
| title | Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells |
| title_full | Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells |
| title_fullStr | Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells |
| title_full_unstemmed | Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells |
| title_short | Bioinformatics Analysis of Transcriptomic Data Reveals Refined Functional Networks for the Self-Renewal of Mouse Spermatogonial Stem Cells |
| title_sort | bioinformatics analysis of transcriptomic data reveals refined functional networks for the self renewal of mouse spermatogonial stem cells |
| url | http://dx.doi.org/10.1155/2018/5842714 |
| work_keys_str_mv | AT minwang bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT wenezhao bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT fuqiangwang bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT xiufengling bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT daozhenchen bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT taozhou bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells AT yingwang bioinformaticsanalysisoftranscriptomicdatarevealsrefinedfunctionalnetworksfortheselfrenewalofmousespermatogonialstemcells |