SNP-based large-scale identification of allele-specific gene expression in human B cells

Polymorphism and variations in gene expression provide the genetic basis for human variation. Allelic variation of gene expression, in particular, may play a crucial role in phenotypic variation and disease susceptibility. To identify genes with allelic expression in human cells, we genotyped genomic DNA and cDNA isolated from 31 immortalized B cell lines from three Centre d'Etude du Polymorphisme Humain (CEPH) families using high-density single-nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs. We identified seven SNPs in five genes with monoallelic expression, 146 SNPs in 125 genes with allelic imbalance in expression with preferentially higher expression of one allele in a heterozygous individual. The monoallelically expressed genes (ERAP2, MDGA1, LOC644422, SDCCAG3P1 and CLTCL1) were regulated by cis-acting, non-imprinted differential allelic control. In addition, all monoallelic gene expression patterns and allelic imbalances in gene expression in B cells were transmitted from parents to offspring in the pedigree, indicating genetic transmission of allelic gene expression. Furthermore, frequent allele substitution, probably due to RNA editing, was also observed in 21 genes in 23 SNPs as well as in 48 SNPs located in regions containing no known genes. In this study, we demonstrated that allelic gene expression is frequently observed in human B cells, and SNP chips are very useful tools for detecting allelic gene expression. Overall, our data provide a valuable framework for better understanding allelic gene expression in human B cells.     

Genome-wide detection of allelic gene expression in hepatocellular carcinoma cells using a human exome SNP chip

Allelic variations in gene expression influence many biological responses and cause phenotypic variations in humans. In this study, Illumina Human Exome BeadChips containing more than 240,000 single nucleotide polymorphisms (SNPs) were used to identify changes in allelic gene expression in hepatocellular carcinoma cells following lipopolysaccharide (LPS) stimulation. We found 17 monoallelically expressed genes, 58 allelic imbalanced genes, and 7 genes showing allele substitution. In addition, we also detected 33 differentially expressed genes following LPS treatment in vitro using these human exome SNP chips. However, alterations in allelic gene expression following LPS treatment were detected in only three genes (MLXIPL, TNC, and MX2), which were observed in one cell line sample only, indicating that changes in allelic gene expression following LPS stimulation of liver cells are rare events. Among a total of 75 genes showing allelic expression in hepatocellular carcinoma cells, either monoallelic or imbalanced, 43 genes (57.33%) had expression quantitative trait loci (eQTL) data, indicating that high-density exome SNP chips are useful and reliable for studying allelic gene expression. Furthermore, most genes showing allelic expression were regulated by cis-acting mechanisms and were also significantly associated with several human diseases. Overall, our study provides a better understanding of allele-specific gene expression in hepatocellular carcinoma cells with and without LPS stimulation and potential clues for the cause of human disease due to alterations in allelic gene expression.     

The impact of cis-acting polymorphisms on the human phenotype

Cis-acting polymorphisms that affect gene expression are now known to be frequent, although the extent and mechanisms by which such variation affects the human phenotype are, as yet, only poorly understood. Key signatures of cis-acting variation are differences in gene expression that are tightly associated with regulatory SNPs or expression Quantitative Trait Loci (eQTL) and an imbalance of allelic expression (AEI) in heterozygous samples. Such cis-acting sequence differences appear often to have been under selection within and between populations and are also thought to be important in speciation. Here we describe the example of lactase persistence. In medical research, variants that affect regulation in cis have been implicated in both monogenic and polygenic disorders, and in the metabolism of drugs. In this review we suggest that by further understanding common regulatory variations and how they interact with other genetic and environmental variables it will be possible to gain insight into important mechanisms behind complex disease, with the potential to lead to new methods of diagnosis and treatments.     

Genetic Variants Contribute to Gene Expression Variability in Humans

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed.     

cis-Expression QTL analysis of established colorectal cancer risk variants in colon tumors and adjacent normal tissue

Genome-wide association studies (GWAS) have identified 19 risk variants associated with colorectal cancer. As most of these risk variants reside outside the coding regions of genes, we conducted cis-expression quantitative trait loci (cis-eQTL) analyses to investigate possible regulatory functions on the expression of neighboring genes. Forty microsatellite stable and CpG island methylator phenotype-negative colorectal tumors and paired adjacent normal colon tissues were used for genome-wide SNP and gene expression profiling. We found that three risk variants (rs10795668, rs4444235 and rs9929218, using near perfect proxies rs706771, rs11623717 and rs2059252, respectively) were significantly associated (FDR q-value ≤0.05) with expression levels of nearby genes (<2 Mb up- or down-stream). We observed an association between the low colorectal cancer risk allele (A) for rs10795668 at 10p14 and increased expression of ATP5C1 (q = 0.024) and between the colorectal cancer high risk allele (C) for rs4444235 at 14q22.2 and increased expression of DLGAP5 (q = 0.041), both in tumor samples. The colorectal cancer low risk allele (A) for rs9929218 at 16q22.1 was associated with a significant decrease in expression of both NOL3 (q = 0.017) and DDX28 (q = 0.046) in the adjacent normal colon tissue samples. Of the four genes, DLGAP5 and NOL3 have been previously reported to play a role in colon carcinogenesis and ATP5C1 and DDX28 are mitochondrial proteins involved in cellular metabolism and division, respectively. The combination of GWAS findings, prior functional studies, and the cis-eQTL analyses described here suggest putative functional activities for three of the colorectal cancer GWAS identified risk loci as regulating the expression of neighboring genes.     

Differential allelic expression of c.1568C > A at UGT2B15 is due to variation in a novel cis-regulatory element in the 3'UTR

Differential allelic expression (DAE) is a powerful tool to identify cis-regulatory elements for gene expression. The UDP-glucuronosyltransferase 2 family, polypeptide B15 (UGT2B15), is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In the present study, we measured the relative expression of two alleles at SNP c.1568C>A (rs4148269) in this gene, which causes an amino acid substitution (T523K). An excess of the C over the A allele was consistently observed in both liver (P = 0.0021) and breast (P = 0.012) samples, suggesting that SNP(s) in strong linkage disequilibrium (LD) with c.1568C>A can regulate UGT2B15 expression in both tissues. By resequencing, one such SNP, c.1761T>C (rs3100) in 3′ untranslated region (UTR), was identified. Reporter gene assays showed that the 1761T allele results in a significantly higher gene expression level than the 1761C allele in HepG2, MCF-7, LNCaP, and Caco-2 cell lines (all P < 0.001), thus indicating that this variation can regulate UGT2B15 gene expression in liver, breast, colon, and prostate tissues. Considering its location, we postulated that this SNP is within an unknown microRNA binding site and can influence microRNA targeting. Considering the importance of UGT2B15 in metabolism, we proposed that this SNP might contribute to multiple cancer risk and variability in drug response.