Literature DB >> 33621950

Infertility network and hub genes for nonobstructive azoospermia utilizing integrative analysis.

Baoquan Han1, Zihui Yan2, Shuai Yu1, Wei Ge2, Yaqi Li3, Yan Wang1, Bo Yang4, Wei Shen1,2, Hui Jiang5, Zhongyi Sun1.   

Abstract

Non-obstructive azoospermia (NOA) is the most severe form of male infertility owing to the absence of sperm during ejaculation as a result of failed spermatogenesis. The molecular mechanisms of NOA have not been well studied. Here, we revealed the dysregulated differentially expressed genes in NOA and related signaling pathways or biological processes. Cluster features of biological processes include spermatogenesis, fertilization, cilium movement, penetration of zona pellucida, sperm chromatin condensation, and being significantly enriched metabolic pathways in proximal tubule bicarbonate reclamation, aldosterone synthesis and secretion, glycolysis and glycogenesis pathways in NOA using Gene Ontology analysis and pathway enrichment analysis. The NOA gene co-expression network was constructed by weighted gene co-expression network analysis to identify the hub genes (CHD5 and SPTBN2). In addition, we used another Gene Expression Omnibus dataset (GSE45887) to validate these hub genes. Furthermore, we used the Seurat package to classify testicular tissue cells from NOA patients and to characterize the differential expression of hub genes in different cell types from different adult males based on the scRNA-seq dataset (GSE106487). These results provide new insights into the pathogenesis of NOA. Of particular note, CHD5 and SPTBN2 may be potential biomarkers for the diagnosis and treatment of NOA.

Entities:  

Keywords:  biomarkers; integrative analysis; male infertility; nonobstructive azoospermia; scRNA-seq

Mesh:

Substances:

Year:  2021        PMID: 33621950      PMCID: PMC7993690          DOI: 10.18632/aging.202559

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


  31 in total

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Journal:  Stat Appl Genet Mol Biol       Date:  2005-08-12

Review 2.  Genetics of male infertility.

Authors:  Csilla Krausz; Antoni Riera-Escamilla
Journal:  Nat Rev Urol       Date:  2018-06       Impact factor: 14.432

3.  Potential biomarkers of nonobstructive azoospermia identified in microarray gene expression analysis.

Authors:  Agnieszka Malcher; Natalia Rozwadowska; Tomasz Stokowy; Tomasz Kolanowski; Piotr Jedrzejczak; Wojmir Zietkowiak; Maciej Kurpisz
Journal:  Fertil Steril       Date:  2013-09-04       Impact factor: 7.329

4.  Identification and functional analysis of spermatogenesis-associated gene modules in azoospermia by weighted gene coexpression network analysis.

Authors:  Wenzhong Zheng; Zihao Zou; Shouren Lin; Xiang Chen; Feixiang Wang; Xianxin Li; Jican Dai
Journal:  J Cell Biochem       Date:  2018-09-30       Impact factor: 4.429

5.  Whole-exome sequencing of a large Chinese azoospermia and severe oligospermia cohort identifies novel infertility causative variants and genes.

Authors:  Shitao Chen; Guishuan Wang; Xiaoguo Zheng; Shunna Ge; Yubing Dai; Ping Ping; Xiangfeng Chen; Guihua Liu; Jing Zhang; Yang Yang; Xinzong Zhang; An Zhong; Yongtong Zhu; Qingjun Chu; Yonghan Huang; Yong Zhang; Changli Shen; Yiming Yuan; Qilong Yuan; Xiuying Pei; C Yan Cheng; Fei Sun
Journal:  Hum Mol Genet       Date:  2020-08-11       Impact factor: 6.150

6.  The gene expression analysis of paracrine/autocrine factors in patients with spermatogenetic failure compared with normal spermatogenesis.

Authors:  Agnieszka Malcher; Natalia Rozwadowska; Tomasz Stokowy; Piotr Jedrzejczak; Wojmir Zietkowiak; Maciej Kurpisz
Journal:  Am J Reprod Immunol       Date:  2013-07-19       Impact factor: 3.886

Review 7.  Understanding new genetics of male infertility.

Authors:  Maria Rosa Maduro; Dolores J Lamb
Journal:  J Urol       Date:  2002-11       Impact factor: 7.450

8.  Single cardiomyocyte nuclear transcriptomes reveal a lincRNA-regulated de-differentiation and cell cycle stress-response in vivo.

Authors:  Kelvin See; Wilson L W Tan; Eng How Lim; Zenia Tiang; Li Ting Lee; Peter Y Q Li; Tuan D A Luu; Matthew Ackers-Johnson; Roger S Foo
Journal:  Nat Commun       Date:  2017-08-09       Impact factor: 14.919

9.  Single-cell Transcriptome Profiling reveals Dermal and Epithelial cell fate decisions during Embryonic Hair Follicle Development.

Authors:  Wei Ge; Shao-Jing Tan; Shan-He Wang; Lan Li; Xiao-Feng Sun; Wei Shen; Xin Wang
Journal:  Theranostics       Date:  2020-06-12       Impact factor: 11.556

10.  Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Authors:  Yingyao Zhou; Bin Zhou; Lars Pache; Max Chang; Alireza Hadj Khodabakhshi; Olga Tanaseichuk; Christopher Benner; Sumit K Chanda
Journal:  Nat Commun       Date:  2019-04-03       Impact factor: 14.919

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  2 in total

1.  Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Non-Obstructive Azoospermia Testis.

Authors:  Xiao-Juan Tang; Qiao-Hong Xiao; Xue-Lin Wang; Yan He; Ya-Nan Tian; Bin-Tong Xia; Yang Guo; Jiao-Long Huang; Peng Duan; Yan Tan
Journal:  Front Genet       Date:  2022-05-20       Impact factor: 4.772

2.  Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue.

Authors:  Ranran Zhou; Xianyuan Lv; Tianle Chen; Qi Chen; Hu Tian; Cheng Yang; Wenbin Guo; Cundong Liu
Journal:  Aging (Albany NY)       Date:  2021-11-04       Impact factor: 5.682

  2 in total

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