Bioinformatics analysis and verification of hub genes in 46,XY, disorders of sexual development.

IF 1.8 4区生物学 Q3 DEVELOPMENTAL BIOLOGY

Reproduction, fertility, and development Pub Date : 2023-03-01 DOI:10.1071/RD22134

Zilong Cao, Liqiang Liu, Zhaoyun Bu, Zhe Yang, Yangqun Li, Rui Li

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引用次数: 0

Abstract

Context: 46,XY, disorders of sexual development (46,XY, DSD) is a congenital genetic disease whose pathogenesis is complex and clinical manifestations are diverse. The existing molecular research has often focused on single-centre sequencing data, instead of prediction based on big data.

Aims: This work aimed to fully understand the pathogenesis of 46,XY, DSD, and summarise the key pathogenic genes.

Methods: Firstly, the potential pathogenic genes were identified from public data. Secondly, bioinformatics was used to predict pathogenic genes, including hub gene analysis, protein-protein interaction (PPI) and function enrichment analysis. Lastly, the genomic DNA from two unrelated families were recruited, next-generation sequencing and Sanger sequencing were performed to verify the hub genes.

Key results: A total of 161 potential pathogenic genes were selected from MGI and PubMed gene sets. The PPI network was built which included 144 nodes and 194 edges. MCODE 4 was selected from PPI which scored the most significant P -value. The top 15 hub genes were ranked and identified by Cytoscape. Furthermore, three variants were found on SRD5A2 gene by genome sequencing, which belonged to the prediction hub genes.

Conclusions: Our results indicate that occurrence of 46,XY, DSD is attributed to a variety of genes. Bioinformatics analysis can help us predict the hub genes and find the most core network MCODE model.

Implications: Bioinformatic predictions may provide a novel perspective on better understanding the pathogenesis of 46,XY, DSD.

查看原文本刊更多论文

46,XY，性发育障碍枢纽基因的生物信息学分析与验证。

背景:46,XY，性发育障碍(46,XY, DSD)是一种先天性遗传病，其发病机制复杂，临床表现多样。现有的分子研究往往集中在单中心测序数据上，而不是基于大数据的预测。目的:全面了解46、XY、DSD的发病机制，总结关键致病基因。方法:首先从公开资料中鉴定潜在致病基因。其次，利用生物信息学方法对致病基因进行预测，包括枢纽基因分析、蛋白-蛋白相互作用(PPI)分析和功能富集分析。最后，从两个无亲缘关系的家族中提取基因组DNA，进行下一代测序和Sanger测序，验证中心基因。关键结果:从MGI和PubMed基因集中共筛选出161个潜在致病基因。构建了包含144个节点和194条边的PPI网络。从PPI中选取P值最显著的MCODE 4。通过Cytoscape对前15个枢纽基因进行排序和鉴定。此外，通过基因组测序发现SRD5A2基因有3个变异，属于预测枢纽基因。结论:我们的研究结果表明，46,XY, DSD的发生可归因于多种基因。生物信息学分析可以帮助我们预测中心基因，找到最核心的网络MCODE模型。意义:生物信息学预测可能为更好地理解46,XY, DSD的发病机制提供一个新的视角。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Reproduction, fertility, and development 生物-动物学

CiteScore

2.10

自引率

10.50%

发文量

317

审稿时长

2 months

期刊介绍： Reproduction, Fertility and Development is an international journal for the publication of original and significant contributions on vertebrate reproductive and developmental biology. Subject areas include, but are not limited to: physiology, biochemistry, cell and molecular biology, endocrinology, genetics and epigenetics, behaviour, immunology and the development of reproductive technologies in humans, livestock and wildlife, and in pest management. Reproduction, Fertility and Development is a valuable resource for research scientists working in industry or academia on reproductive and developmental biology, clinicians and veterinarians interested in the basic science underlying their disciplines, and students. Reproduction, Fertility and Development is the official journal of the International Embryo Technology Society and the Society for Reproductive Biology. Reproduction, Fertility and Development is published with the endorsement of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the Australian Academy of Science.