cis sequence effects on gene expression. Homo sapiens

Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation provides insight into biological mechanisms that underlie gene regulation and function. We investigated the role of sequence variation in cis on gene expression (cis sequence effects) in a group of genes frequently studied in cancer research. We assessed the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects, and compared our results to the literature. Keywords: genetical genomics Overall design: Thirty lymphoblastoid cell lines drawn from the SNP500Cancer resource were cultured in triplicate. The intersection of gene expression profiling data at N=697 candidate genes and genomic sequencing data at N=552 candidate genes from these cell lines yielded data at thirty candidate genes with strong and variable gene expression suitable for the investigation of cis sequence effects. We used regression on SNP genotype in an additive model, the single-point additive model of Mander, and the haplotype phylogeny scanning approach of Templeton to evaluate associations between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed and rank-invariant normalized mean gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p<0.05) association with gene expression using one or more methods. Data were available for fourteen candidate genes common to the literature and our analysis, five of which exhibited significant cis effects in this study. Using the literature results as a “gold standard”, and after excluding two genes that exhibited discordant literature results, our study concordantly identified 4 of 5 genes, and 6 of 7 genes as exhibiting and not exhibiting significant cis sequence effects, respectively.

个体内与个体间的序列变异及转录变异通常被独立研究。对序列变异与基因表达变异进行联合分析，可为解析基因调控与功能背后的生物学机制提供关键洞见。

我们针对癌症研究中高频探究的一组基因，分析了顺式序列效应（cis sequence effects）对基因表达的影响。本研究评估了存在顺式序列效应的基因占比，以及顺式序列变异可解释的基因表达变异比例，并将研究结果与现有文献进行对比。

关键词：遗传基因组学（genetical genomics）

整体实验设计：从SNP500Cancer资源中获取的30株淋巴母细胞系，进行三次重复培养。对这些细胞系的697个候选基因的基因表达谱数据，与552个候选基因的基因组测序数据取交集后，最终得到30个候选基因的有效数据集——这些基因的基因表达水平显著且存在变异，适用于顺式序列效应的研究。

我们采用加性模型下的SNP基因型回归分析、曼德（Mander）提出的单点加性模型，以及坦普尔顿（Templeton）的单倍型系统发育扫描方法，分别评估单个SNP、基因内所有SNP以及双型（diplotypes）与经对数转换且秩不变归一化后的平均基因表达量之间的关联。

通过一种或多种分析方法，8个候选基因所在的SNP及双型与基因表达存在统计学显著关联（p<0.05）。

本研究与现有文献共有的候选基因共14个，其中本研究发现5个存在显著顺式效应。以文献结果作为“金标准”，并排除2个文献结果不一致的基因后，本研究准确识别出5个存在显著顺式效应基因中的4个，以及7个无显著顺式效应基因中的6个。