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用于发现和鉴定小鼠及人类骨质疏松症相关基因的先进遗传方法

Advanced Genetic Approaches in Discovery and Characterization of Genes Involved With Osteoporosis in Mouse and Human.

作者信息

Yuan Jinbo, Tickner Jennifer, Mullin Benjamin H, Zhao Jinmin, Zeng Zhiyu, Morahan Grant, Xu Jiake

机构信息

School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia.

Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia.

出版信息

Front Genet. 2019 Apr 2;10:288. doi: 10.3389/fgene.2019.00288. eCollection 2019.

Abstract

Osteoporosis is a complex condition with contributions from, and interactions between, multiple genetic loci and environmental factors. This review summarizes key advances in the application of genetic approaches for the identification of osteoporosis susceptibility genes. Genome-wide linkage analysis (GWLA) is the classical approach for identification of genes that cause monogenic diseases; however, it has shown limited success for complex diseases like osteoporosis. In contrast, genome-wide association studies (GWAS) have successfully identified over 200 osteoporosis susceptibility loci with genome-wide significance, and have provided most of the candidate genes identified to date. Phenome-wide association studies (PheWAS) apply a phenotype-to-genotype approach which can be used to complement GWAS. PheWAS is capable of characterizing the association between osteoporosis and uncommon and rare genetic variants. Another alternative approach, whole genome sequencing (WGS), will enable the discovery of uncommon and rare genetic variants in osteoporosis. Meta-analysis with increasing statistical power can offer greater confidence in gene searching through the analysis of combined results across genetic studies. Recently, new approaches to gene discovery include animal phenotype based models such as the Collaborative Cross and ENU mutagenesis. Site-directed mutagenesis and genome editing tools such as CRISPR/Cas9, TALENs and ZNFs have been used in functional analysis of candidate genes and . These resources are revolutionizing the identification of osteoporosis susceptibility genes through the use of genetically defined inbred mouse libraries, which are screened for bone phenotypes that are then correlated with known genetic variation. Identification of osteoporosis-related susceptibility genes by genetic approaches enables further characterization of gene function in animal models, with the ultimate aim being the identification of novel therapeutic targets for osteoporosis.

摘要

骨质疏松症是一种复杂的病症,由多个基因位点和环境因素共同作用并相互影响所致。本综述总结了应用基因方法鉴定骨质疏松症易感基因方面的关键进展。全基因组连锁分析(GWLA)是鉴定导致单基因疾病基因的经典方法;然而,它在骨质疏松症等复杂疾病的研究中成效有限。相比之下,全基因组关联研究(GWAS)已成功鉴定出200多个具有全基因组显著性的骨质疏松症易感位点,并提供了迄今为止鉴定出的大多数候选基因。全表型组关联研究(PheWAS)采用从表型到基因型的方法,可用于补充GWAS。PheWAS能够描述骨质疏松症与不常见和罕见基因变异之间的关联。另一种替代方法,即全基因组测序(WGS),将有助于发现骨质疏松症中不常见和罕见的基因变异。通过对多个基因研究的综合结果进行分析,具有更强统计效力的荟萃分析能够在基因搜索中提供更高的可信度。最近,新的基因发现方法包括基于动物表型的模型,如协作杂交和ENU诱变。定点诱变和基因组编辑工具,如CRISPR/Cas9、TALENs和ZNFs,已用于候选基因的功能分析。这些资源正在通过使用基因定义的近交小鼠文库来筛选与已知基因变异相关的骨表型,从而彻底改变骨质疏松症易感基因的鉴定。通过基因方法鉴定骨质疏松症相关的易感基因能够进一步在动物模型中表征基因功能,最终目标是确定骨质疏松症的新型治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba09/6455049/d9224b852e8c/fgene-10-00288-g001.jpg

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