A Practical Guide for Structural Variation Detection in the Human Genome.
A Practical Guide for Structural Variation Detection in the Human Genome.
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DOI：
10.1002/cphg.103
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发表时间：
2020-09
影响因子：
--
通讯作者：
Yang L
中科院分区：
文献类型：
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作者：
Yang L
分析健康和患病个体的遗传变异-包括单核苷酸变异、小插入和缺失、拷贝数变异和结构变异（SV）-是遗传和生物医学研究的关键组成部分。SV是基因组中的大规模变化，涉及DNA片段的断裂和重新连接。它们可能影响数千至数百万个核苷酸，并可能导致基因和调控元件的丢失、获得和重组。已知SV影响基因表达并可能导致表型改变和疾病。因此，从人类基因组中识别SV特别重要。在这篇综述中，我描述了现有的高通量检测方法的优点和缺点，用于发现SV，这是最具挑战性的遗传变异检测。一个实用的指南，建议发现不同类型的SV，包括常见的种系变异，罕见的变异，体细胞变异和复杂的变异最合适的策略。我还讨论了设计实验时需要考虑的因素，如成本和性能，不同的策略。最后，我提出了几种方法来识别潜在的SV工件所造成的样品，实验程序和计算分析。
Profiling genetic variants—including single nucleotide variants, small insertions and deletions, copy number variations and structural variations (SVs)—from both healthy and diseased individuals is a key component of genetic and biomedical research. SVs are large-scale changes in the genome and involve breakage and rejoining of DNA fragments. They may affect thousands to millions of nucleotides, and can lead to loss, gain and reshuffling of genes as well as regulatory elements. SVs are known to impact gene expression and potentially resulting in altered phenotypes and diseases. Therefore, identifying SVs from human genomes is particularly important. In this review, I describe advantages and disadvantages of the available high throughput assays for the discovery of SVs, which are the most challenging genetic alterations to detect. A practical guide is offered to suggest the most suitable strategies of discovering different types of SVs including common germline variants, rare variants, somatic variants and complex variants. I also discuss factors to be considered, such as cost and performance, for different strategies when designing experiments. Lastly, I present several approaches to identify potential SV artifacts caused by samples, experimental procedures and computational analysis.