Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain.
Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain.
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DOI：
10.1093/hmg/ddw369
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发表时间：
2017-01-01
影响因子：
3.5
通讯作者：
Ponting CP
中科院分区：
文献类型：
--
作者：
Handel AE;Gallone G;Zameel Cader M;Ponting CP
密集的基因分型方法揭示了基因表达和疾病易感性的遗传结构。然而，将因果关系分配给与转录组或表型性状相关的遗传变异是一个更大的挑战。ENCODE、表观基因组路线图等对表观基因组资源的开发导致了寻求推断这些全基因组关联信号背后可能的功能变异的策略。例如，通过dna -seq和FAIRE-seq等技术检测，已知这些变异往往位于开放染色质区域内。我们的目的是评估人脑中与表型或转录组性状相关的变异位于转录因子结合位点内的比例。使用生物信息学工具Wellington和HINT从现有的来自中枢神经系统组织的dna -seq数据中推断转录因子足迹，具有高空间分辨率。然后利用该数据集评估转录因子结合改变对表达数量性状位点（eQTL）和全基因组关联研究（GWAS）信号的可能贡献。令人惊讶的是，我们发现大多数与GWAS或eQTL表型相关的单倍型位于dna -seq足迹之外。这可能意味着dna -seq足迹是一种太不敏感的方法，无法识别大部分真正的转录因子结合位点。重要的是，这表明，由于无法在单倍型中识别致病变异，为基因组工程研究确定因果关系的变异优先级将继续受到挫折。
Dense genotyping approaches have revealed much about the genetic architecture both of gene expression and disease susceptibility. However, assigning causality to genetic variants associated with a transcriptomic or phenotypic trait presents a far greater challenge. The development of epigenomic resources by ENCODE, the Epigenomic Roadmap and others has led to strategies that seek to infer the likely functional variants underlying these genome-wide association signals. It is known, for example, that such variants tend to be located within areas of open chromatin, as detected by techniques such as DNase-seq and FAIRE-seq. We aimed to assess what proportion of variants associated with phenotypic or transcriptomic traits in the human brain are located within transcription factor binding sites. The bioinformatic tools, Wellington and HINT, were used to infer transcription factor footprints from existing DNase-seq data derived from central nervous system tissues with high spatial resolution. This dataset was then employed to assess the likely contribution of altered transcription factor binding to both expression quantitative trait loci (eQTL) and genome-wide association study (GWAS) signals. Surprisingly, we show that most haplotypes associated with GWAS or eQTL phenotypes are located outside of DNase-seq footprints. This could imply that DNase-seq footprinting is too insensitive an approach to identify a large proportion of true transcription factor binding sites. Importantly, this suggests that prioritising variants for genome engineering studies to establish causality will continue to be frustrated by an inability of footprinting to identify the causative variant within a haplotype.