GuhaThakurta Debraj, Xie Tao, Anand Manish, Edwards Stephen W, Li Guoya, Wang Susanna S, Schadt Eric E
Genetics, Rosetta Inpharmatics LLC, Merck & Co., Inc. 401 Terry Avenue North, Seattle, WA 98109, USA.
BMC Genomics. 2006 Sep 15;7:235. doi: 10.1186/1471-2164-7-235.
Changes in gene expression are known to be responsible for phenotypic variation and susceptibility to diseases. Identification and annotation of the genomic sequence variants that cause gene expression changes is therefore likely to lead to a better understanding of the cause of disease at the molecular level. In this study we investigate the pattern of single nucleotide polymorphisms (SNPs) in genes for which the mRNA levels show cis-genetic linkage (gene expression quantitative trait loci mapping in cis, or cis-eQTLs) in segregating mouse populations. Such genes are expected to have polymorphisms near their physical location (cis-variations) that affect their mRNA levels by altering one or more of the cis-regulatory elements. This led us to characterize the SNPs in promoter (5 Kb upstream) and non-coding gene regions (introns and 5 Kb downstream) (cis-SNPs) and the effects they may have on putative transcription factor binding sites.
We demonstrate that the cis-eQTL genes (CEGs) have a significantly higher frequency of cis-SNPs compared to non-CEGs (when both sets are taken from the non-IBD regions, i.e. regions not identical by descent). Most CEGs having cis-SNPs do not contain these SNPs in the phylogenetically conserved regions. In those CEGs that contain cis-SNPs in the phylogenetically conserved regions, enrichment of cis-SNPs occurs both within and outside of the conserved sequences. A higher fraction of CEGs are also seen to harbor cis-SNP that affect predicted transcription factor binding sites, a likely consequence of the higher cis-SNPs density in these genes.
This present study provides the first genome-wide investigation of the putative cis-regulatory variations in a large set of genes whose levels of expression give rise to cis-linkage in segregating mammalian populations. Our results provide insights into the challenges that exist in identifying polymorphisms regulating gene expression using bioinformatic sequence analysis approaches. The data provided herein should benefit future investigations in this area.
已知基因表达的变化是表型变异和疾病易感性的原因。因此，识别和注释导致基因表达变化的基因组序列变异可能有助于在分子水平上更好地理解疾病的病因。在本研究中，我们调查了在分离的小鼠群体中，mRNA水平显示顺式遗传连锁（顺式基因表达数量性状位点定位，或顺式eQTL）的基因中的单核苷酸多态性（SNP）模式。预计此类基因在其物理位置附近具有多态性（顺式变异），通过改变一个或多个顺式调控元件来影响其mRNA水平。这促使我们对启动子（上游5kb）和非编码基因区域（内含子和下游5kb）中的SNP（顺式SNP）及其对假定转录因子结合位点可能产生的影响进行表征。
我们证明，与非顺式eQTL基因（当两组均取自非IBD区域，即非同源区域时）相比，顺式eQTL基因（CEG）的顺式SNP频率显著更高。大多数具有顺式SNP的CEG在系统发育保守区域中不包含这些SNP。在那些在系统发育保守区域中包含顺式SNP的CEG中，顺式SNP在保守序列内外均有富集。还发现较高比例的CEG含有影响预测转录因子结合位点的顺式SNP，这可能是这些基因中顺式SNP密度较高的结果。
本研究首次在大量基因中进行了全基因组范围内的假定顺式调控变异研究，这些基因的表达水平在分离的哺乳动物群体中产生顺式连锁。我们的结果为使用生物信息序列分析方法识别调控基因表达的多态性所面临的挑战提供了见解。本文提供的数据应有助于该领域未来的研究。
