The fine-scale architecture of structural variants in 17 mouse genomes.
The fine-scale architecture of structural variants in 17 mouse genomes.
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DOI：
10.1186/gb-2012-13-3-r18
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发表时间：
2012
期刊：
影响因子：
12.3
通讯作者：
Flint J
中科院分区：
文献类型：
--
作者：
Yalcin B;Wong K;Bhomra A;Goodson M;Keane TM;Adams DJ;Flint J
哺乳动物基因组中结构变体（SV）的准确目录对于阐明驱动SV形成并评估其功能影响的潜在机制是必要的。 SV检测的下一代测序方法是基于数组的方法的预先提前，但几乎仅限于四种基本类型：删除，插入，倒置和复制号。
通过对100 MBP的基因组的目视检查，对17个近交小鼠菌株的下一代序列数据进行了排列，我们识别并解释了21种配对末端映射模式，我们通过PCR验证了这一模式。这些配对的映射模式比以前认识到的SV揭示了更大的多样性和复杂性。此外，在261 SV位点对4,176个断点的基于Sanger的序列分析显示，在分析的结构变体的大约四分之一时，还显示了额外的复杂性。我们在SV断点上发现微缺失和微插入范围为1至107 bp，而SNP延伸了断点微体积，并且可能催化SV形成。
使用实验分析来训练计算SV调用的一种集成方法对于准确解决SV架构至关重要。我们发现SV形成的复杂性很大。小鼠中约四分之一的SV由删除，插入，反转和拷贝数增益的复杂混合物组成。可以对计算方法进行调整以识别大多数配对的映射模式。
Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.
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通讯作者：
Garraway, Levi A.