Large-scale profiling and identification of potential regulatory mechanisms for allelic gene expression in colorectal cancer cells

Allelic variation in gene expression is common in humans and this variation is associated with phenotypic variation. In this study, we employed high-density single nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs to identify genes with allelic gene expression in cells from colorectal cancer cell lines. We found 2 monoallelically expressed genes (ERAP2 and MYLK4), 32 genes with an allelic imbalance in their expression, and 13 genes showing allele substitution by RNA editing. Among a total of 34 allelically expressed genes in colorectal cancer cells, 15 genes (44.1%) were associated with cis-acting eQTL, indicating that large portions of allelically expressed genes are regulated by cis-acting mechanisms of gene expression. In addition, potential regulatory variants present in the proximal promoter regions of genes showing either monoallelic expression or allelic imbalance were not tightly linked with coding SNPs, which were detected with allelic gene expression. These results suggest that multiple rare variants could be involved in the cis-acting regulatory mechanism of allelic gene expression. In the comparison with allelic gene expression data from Centre d'Etude du Polymorphisme Humain (CEPH) family B cells, 12 genes showed B-cell specific allelic imbalance and 1 noncoding SNP showed colorectal cancer cell-specific allelic imbalance. In addition, different patterns of allele substitution were observed between B cells and colorectal cancer cells. Overall, our study not only indicates that allelic gene expression is common in colorectal cancer cells, but our study also provides a better understanding of allele-specific gene expression in colorectal cancer 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.     

Allelic variation in gene expression identified through computational analysis of the dbEST database

Differential expression between the two alleles of an individual and between people with different genotypes has been commonly observed. Quantitative differences in gene expression between people may provide the genetic basis for the phenotypic difference between individuals and may be the primary cause of complex diseases. In this paper, we developed a computational method to identify genes that displayed allelic variation in gene expression in human EST libraries. To model allele-specific gene expression, we first identified EST libraries in which both A and B alleles were expressed and then identified allelic variation in gene expression based on the EST counts for each allele using a binomial test. Among 1107 SNPs that had a sufficient number of ESTs for the analysis, 524 (47%) displayed allelic variation in at least one cDNA library. We verified experimentally the allelic variation in gene expression for 6 of these SNPs. The frequency of allelic variation observed in EST libraries was similar to the previous studies using the SNP chip and primer extension method. We found that genes that displayed allelic variation were distributed throughout the human genome and were enriched in certain chromosome regions. The SNPs and genes identified in this study will provide a rich source for evaluating the effects of those SNPs and associated haplotypes in human health and diseases.     

Genomic imprinting absent in Drosophila melanogaster adult females

Genomic imprinting occurs when expression of an allele differs based on the sex of the parent that transmitted the allele. In D. melanogaster, imprinting can occur, but its impact on allelic expression genome-wide is unclear. Here, we search for imprinted genes in D. melanogaster using RNA-seq to compare allele-specific expression between pools of 7- to 10-day-old adult female progeny from reciprocal crosses. We identified 119 genes with allelic expression consistent with imprinting, and these genes showed significant clustering within the genome. Surprisingly, additional analysis of several of these genes showed that either genomic heterogeneity or high levels of intrinsic noise caused imprinting-like allelic expression. Consequently, our data provide no convincing evidence of imprinting for D. melanogaster genes in their native genomic context. Elucidating sources of false-positive signals for imprinting in allele-specific RNA-seq data, as done here, is critical given the growing popularity of this method for identifying imprinted genes.     

Genome-wide identification of allele-specific effects on gene expression for single and multiple individuals

The analysis of allele-specific gene expression (ASE) is essential for the mapping of genetic variants that affect gene regulation, and for the identification of alleles that modify disease risk. Although RNA sequencing offers the opportunity to measure expression at allele levels, the availability of powerful statistical methods for mapping ASE in single or multiple individuals is limited. We developed a maximum likelihood model to characterize ASE in the human genome. Approximately 17% of genes displayed an allele-specific effect on gene expression in a single individual. Simulations using our model gave a better performance and improved robustness when compared with the binomial test, with different coverage levels, allelic expression fractions and random noise. In addition, our method can identify ASE in multiple individuals, with enhanced performance. This is helpful in understanding the mechanism of genetic regulation leading to expression changes, alternative splicing variants and even disease susceptibility.     

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.     

Evidence for diversity in transcriptional profiles of single hematopoietic stem cells

Hematopoietic stem cells replenish all the cells of the blood throughout the lifetime of an animal. Although thousands of stem cells reside in the bone marrow, only a few contribute to blood production at any given time. Nothing is known about the differences between individual stem cells that dictate their particular state of activation readiness. To examine such differences between individual stem cells, we determined the global gene expression profile of 12 single stem cells using microarrays. We showed that at least half of the genetic expression variability between 12 single cells profiled was due to biological variation in 44% of the genes analyzed. We also identified specific genes with high biological variance that are candidates for influencing the state of readiness of individual hematopoietic stem cells, and confirmed the variability of a subset of these genes using single-cell real-time PCR. Because apparent variation of some genes is likely due to technical factors, we estimated the degree of biological versus technical variation for each gene using identical RNA samples containing an RNA amount equivalent to that of single cells. This enabled us to identify a large cohort of genes with low technical variability whose expression can be reliably measured on the arrays at the single-cell level. These data have established that gene expression of individual stem cells varies widely, despite extremely high phenotypic homogeneity. Some of this variation is in key regulators of stem cell activity, which could account for the differential responses of particular stem cells to exogenous stimuli. The capacity to accurately interrogate individual cells for global gene expression will facilitate a systems approach to biological processes at a single-cell level.     

Proteomic shifts in embryonic stem cells with gene dose modifications suggest the presence of balancer proteins in protein regulatory networks

Large numbers of protein expression changes are usually observed in mouse models for neurodegenerative diseases, even when only a single gene was mutated in each case. To study the effect of gene dose alterations on the cellular proteome, we carried out a proteomic investigation on murine embryonic stem cells that either overexpressed individual genes or displayed aneuploidy over a genomic region encompassing 14 genes. The number of variant proteins detected per cell line ranged between 70 and 110, and did not correlate with the number of modified genes. In cell lines with single gene mutations, up and down-regulated proteins were always in balance in comparison to parental cell lines regarding number as well as concentration of differentially expressed proteins. In contrast, dose alteration of 14 genes resulted in an unequal number of up and down-regulated proteins, though the balance was kept at the level of protein concentration. We propose that the observed protein changes might partially be explained by a proteomic network response. Hence, we hypothesize the existence of a class of "balancer" proteins within the proteomic network, defined as proteins that buffer or cushion a system, and thus oppose multiple system disturbances. Through database queries and resilience analysis of the protein interaction network, we found that potential balancer proteins are of high cellular abundance, possess a low number of direct interaction partners, and show great allelic variation. Moreover, balancer proteins contribute more heavily to the network entropy, and thus are of high importance in terms of system resilience. We propose that the "elasticity" of the proteomic regulatory network mediated by balancer proteins may compensate for changes that occur under diseased conditions.     

Discrimination among the transcripts of the allelic human beta-globin genes beta A, beta S and beta C using oligodeoxynucleotide hybridization probes

Three nonadecadeoxynucleotides complementary to the sense strand of the normal human beta-globin gene, beta A, and to the two allelic genes beta S and beta C were synthesized. The beta S and beta C globin genes both differ from the beta A gene by a single nucleotide substitution in the sequence coding for codon 6. The oligodeoxynucleotides are complementary to the genes in the region of the mutations and are therefore allele-specific. When radiolabeled and used as hybridization probes, the oligodeoxynucleotides are found to hybridize specifically to the mRNA transcribed from each allele.     

Differential replication timing of X-linked genes measured by a novel method using single-nucleotide primer extension.

The ratio of two differentially replicating alleles is not constant during S phase. Using this fact, we have developed a method for determining allele-specific replication timing for alleles differing by at least a single base pair. Unsynchronized cells in tissue culture are first sorted into fractions based on DNA content as a measure of position in S phase. DNA is purified from each fraction and used for PCR with primers that bracket the allelic difference, amplifying both alleles. The ratio of alleles in the amplified product is then determined by a single nucleotide primer extension (SNuPE) assay, modified as described [Singer-Sam,J. and Riggs,A.D. (1993) Methods Enzymol., 225, 344-351]. We report here use of this SNuPE-based method to analyze replication timing of two X-linked genes, Pgk-1 and Xist, as well as the autosomal gene Gabra-6. We have found that the two alleles of the Gabra-6 gene replicate synchronously, as expected; similarly, the active allele of the Pgk-1 gene on the active X chromosome (Xa) replicates early relative to the silent allele on the inactive X chromosome (Xi). In contrast, the expressed allele of the Xist gene, which is on the Xi, replicates late relative to the silent allele on the Xa.