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全面分析与男性不育相关的染色体断裂点和候选基因:细胞遗传学研究和表达分析的启示。

Comprehensive analysis of chromosomal breakpoints and candidate genes associated with male infertility: insights from cytogenetic studies and expression analyses.

机构信息

Department of Cell and Molecular Biology, Faculty of Biology, College of Science, University of Tehran, Tehran, Iran.

Laboratory of Biochemistry and Molecular Biology of Germ Cells, Institute of Animal Physiology and Genetics of the Czech Academy of Sciences, Rumburska 89, 277 21, Libechov, Czech Republic.

出版信息

Mamm Genome. 2024 Dec;35(4):764-783. doi: 10.1007/s00335-024-10074-z. Epub 2024 Oct 2.

Abstract

The study aimed to investigate prevalent chromosomal breakpoints identified in balanced structural chromosomal anomalies and to pinpoint potential candidate genes linked with male infertility. This was acchieved through a comprehensive approach combining RNA-seq and microarray data analysis, enabling precise identification of candidate genes. The Cytogenetics data from 2,500 infertile males referred to Royan Research Institute between 2009 and 2022 were analyzed, with 391 cases meeting the inclusion criteria of balanced chromosomal rearrangement. Of these, 193 cases exhibited normal variations and were excluded from the analysis. By examining the breakpoints, potential candidate genes were suggested. Among the remaining 198 cases, reciprocal translocations were the most frequent anomaly (129 cases), followed by Robertsonian translocations (43 cases), inversions (34 cases), and insertions (3 cases).Some patients had more than one chromosomal abnormality. Chromosomal anomalies were most frequently observed in chromosomes 13 (21.1%), 14 (20.1%), and 1 (16.3%) with 13q12, 14q12, and 1p36.3 being the most prevalent breakpoints, respectively. Chromosome 1 contributed the most to reciprocal translocations (20.2%) and inversions (17.6%), while chromosome 14 was the most involved in the Robertsonian translocations (82.2%). The findings suggested that breakpoints at 1p36.3 and 14q12 might be associated with pregestational infertility, whereas breakpoints at 13q12 could be linked to both gestational and pregestational infertility. Several candidate genes located on common breakpoints were proposed as potentially involved in male infertility. Bioinformatics analyses utilizing three databases were conducted to examine the expression patterns of 78 candidate genes implicated in various causes of infertility.‏ In azoospermic individuals, significant differential expression was observed in 19 genes: 15 were downregulated (TSSK2, SPINK2, TSSK4, CDY1, CFAP70, BPY2, BTG4, FKBP6, PPP2R1B, SPECC1L, CENPJ, ‏SKA3, FGF9, NODAL, CLOCK), while four genes were upregulated ‏(‏HSPB1, MIF, PRF1, ENTPD6). In the case of Asthenozoospermia, seven genes showed significant upregulation (PRF1, DDX21, KIT, SRD5A3, MTCH1, DDX50, NODAL). Though RNA-seq data for Teratozoospermia were unavailable, microarray data revealed differential expression insix genes: three downregulated (BUB1, KLK4, PIWIL2) and three upregulated (AURKC, NPM2, RANBP2). These findings enhance our understanding of the molecular basis of male infertility and could provide valuable insights for future diagnostic and therapeutic strategies.

摘要

本研究旨在探讨平衡结构染色体异常中发现的常见染色体断裂点,并确定与男性不育相关的潜在候选基因。这是通过结合 RNA-seq 和微阵列数据分析的综合方法实现的,能够精确识别候选基因。对 2009 年至 2022 年间罗扬研究所的 2500 名不育男性的细胞遗传学数据进行了分析,其中 391 例符合平衡染色体重排的纳入标准。其中,193 例表现出正常变异,被排除在分析之外。通过检查断裂点,提出了潜在的候选基因。在其余 198 例中,相互易位是最常见的异常(129 例),其次是罗伯逊易位(43 例)、倒位(34 例)和插入(3 例)。一些患者有不止一种染色体异常。染色体异常最常发生在 13 号染色体(21.1%)、14 号染色体(20.1%)和 1 号染色体(16.3%),分别是 13q12、14q12 和 1p36.3 是最常见的断裂点。1 号染色体对相互易位(20.2%)和倒位(17.6%)的贡献最大,而 14 号染色体是罗伯逊易位(82.2%)最常涉及的染色体。研究结果表明,1p36.3 和 14q12 处的断裂点可能与孕前不育有关,而 13q12 处的断裂点可能与孕前和孕期不育有关。提出了位于常见断裂点的几个候选基因,这些基因可能与男性不育有关。利用三个数据库进行了生物信息学分析,以检查与各种不育原因相关的 78 个候选基因的表达模式。在无精子症个体中,观察到 19 个基因的显著差异表达:15 个基因下调(TSSK2、SPINK2、TSSK4、CDY1、CFAP70、BPY2、BTG4、FKBP6、PPP2R1B、SPECC1L、CENPJ、SKA3、FGF9、NODAL、CLOCK),而 4 个基因上调(HSPB1、MIF、PRF1、ENTPD6)。在弱精子症中,有 7 个基因显示出显著的上调(PRF1、DDX21、KIT、SRD5A3、MTCH1、DDX50、NODAL)。虽然没有关于畸形精子症的 RNA-seq 数据,但微阵列数据显示 6 个基因的差异表达:3 个下调(BUB1、KLK4、PIWIL2)和 3 个上调(AURKC、NPM2、RANBP2)。这些发现加深了我们对男性不育分子基础的理解,并为未来的诊断和治疗策略提供了有价值的见解。

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