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Microarray meta‐analysis identifies candidate genes for human spermatogenic arrest
Author(s) -
Kui Fang,
Ye Hui,
Chen XiLing,
Zhang Jun
Publication year - 2019
Publication title -
andrologia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.633
H-Index - 59
eISSN - 1439-0272
pISSN - 0303-4569
DOI - 10.1111/and.13301
Subject(s) - microarray analysis techniques , biology , male infertility , phenotype , microarray , gene , candidate gene , genetics , andrology , spermatogenesis , gene expression profiling , gene expression , meiosis , bioinformatics , infertility , medicine , endocrinology , pregnancy
Male infertility affects approximately half of couples who have difficulty becoming pregnant, and its prevalence is continuously rising. Many studies have been performed using animal testes to reveal the mechanisms of male infertility, but few studies have investigated human testes due to various limitations. The aim of this study was to investigate the gene expression profile of impaired human testes through a meta‐analysis of microarray data sets, which was accomplished by using 178 human testis samples and 7 microarray data sets. Impaired testes were categorised into four pathological phenotypes or the normal phenotype based on their Johnsen score. Then, a meta‐analysis was performed to screen out the differentially expressed genes (DEGs) in each phenotype. The DEGs were used in a subsequent bioinformatics analysis. Our results identified several novel hub genes and pathways and suggested that G1 mitotic cell cycle arrest was a remarkable feature in pre‐meiotic arrest. Furthermore, fifteen p53‐interacting proteins, such as ABL1 and HDAC2, whose roles in spermatogenesis have not been well characterised, were selected from the DEGs through a strict screening procedure.