A computational framework discovers new copy number variants with functional importance.
A computational framework discovers new copy number variants with functional importance.
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DOI：
10.1371/journal.pone.0017539
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发表时间：
2011-03-29
期刊：
影响因子：
3.7
通讯作者：
Demichelis F
中科院分区：
文献类型：
--
作者：
Banerjee S;Oldridge D;Poptsova M;Hussain WM;Chakravarty D;Demichelis F
导致拷贝数变化的结构变异是基因组变异性的重要组成部分。它们解释了两个个体基因组差异的0.7%，其中拷贝数变异(CNV)是最大的组成部分。最近一项基于人群的CNV研究表明，需要更好地表征CNV，特别是小的CNV(<；500bp)。我们提出了一个三步计算框架(Genmline Changes in Copy Num或IgC2N)来发现种系CNV并进行基因分型。首先，我们通过组合多个样本上的信息来检测候选CNV基因座，而不对覆盖标记的数量或变化的大小施加限制。其次，我们对稀有变异的检测进行了微调，并推断出每个基因座的假定拷贝数类别。最后，对于每个变体，我们将连续拷贝数类别之间的相对距离与遗传信息相结合，以一种新的尝试来估计参考模型偏差。这种计算方法被应用于1250个HapMap个体的全基因组数据。新的变异被发现，并在大小、次要等位基因频率、多态类型(获得、损失或两者兼而有之)和形成机制方面进行了表征。使用4200万个标记平台为个体子集生成的数据，我们验证了大多数验证率最高的变体(66.7%)是大小超过1kb的变体。最后，我们查询了129个通过RNA测序确定的个体的转录数据，作为进一步的验证和评估新变体的功能作用。我们研究了变异体调控效应的可能富集性，发现较小的变异体(<；1kb)比较大的变异体更有可能调节基因转录(p值 = 2.04e-08)。我们的结果支持了计算框架的有效性，以检测与疾病易感性研究相关的新变异，并为基因变异在调控网络研究中的重要性提供证据。
Structural variants which cause changes in copy numbers constitute an important component of genomic variability. They account for 0.7% of genomic differences in two individual genomes, of which copy number variants (CNVs) are the largest component. A recent population-based CNV study revealed the need of better characterization of CNVs, especially the small ones (<500 bp).We propose a three step computational framework (Identification of germline Changes in Copy Number or IgC2N) to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias. This computational approach is applied to genome-wide data from 1250 HapMap individuals. Novel variants were discovered and characterized in terms of size, minor allele frequency, type of polymorphism (gains, losses or both), and mechanism of formation. Using data generated for a subset of individuals by a 42 million marker platform, we validated the majority of the variants with the highest validation rate (66.7%) was for variants of size larger than 1 kb. Finally, we queried transcriptomic data from 129 individuals determined by RNA-sequencing as further validation and to assess the functional role of the new variants. We investigated the possible enrichment for variant's regulatory effect and found that smaller variants (<1 Kb) are more likely to regulate gene transcript than larger variants (p-value = 2.04e-08). Our results support the validity of the computational framework to detect novel variants relevant to disease susceptibility studies and provide evidence of the importance of genetic variants in regulatory network studies.
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影响因子：
30.8
作者：
Cahan, Patrick;Li, Yedda;Izumi, Masayo;Graubert, Timothy A.
通讯作者：
Graubert, Timothy A.
影响因子：
3.5
作者：
Kato M;Kawaguchi T;Ishikawa S;Umeda T;Nakamichi R;Shapero MH;Jones KW;Nakamura Y;Aburatani H;Tsunoda T
通讯作者：
Tsunoda T
DOI：
10.1126/science.1183621
发表时间：
2010-04-09
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Kasowski M;Grubert F;Heffelfinger C;Hariharan M;Asabere A;Waszak SM;Habegger L;Rozowsky J;Shi M;Urban AE;Hong MY;Karczewski KJ;Huber W;Weissman SM;Gerstein MB;Korbel JO;Snyder M
通讯作者：
Snyder M
DOI：
10.1073/pnas.0710052104
发表时间：
2007-12-11
影响因子：
11.1
作者：
Beroukhim, Rameen;Getz, Gad;Sellers, William R.
通讯作者：
Sellers, William R.
影响因子：
64.8
作者：
通讯作者：
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