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author:("saffan, David")
4.  Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI) of candidate neuropsychiatric disorder genes in human brain 
BMC Genomics  2011;12:518.
Background
Common genetic variants that regulate gene expression are widely suspected to contribute to the etiology and phenotypic variability of complex diseases. Although high-throughput, microarray-based assays have been developed to measure differences in mRNA expression among independent samples, these assays often lack the sensitivity to detect rare mRNAs and the reproducibility to quantify small changes in mRNA expression. By contrast, PCR-based allelic expression imbalance (AEI) assays, which use a "marker" single nucleotide polymorphism (mSNP) in the mRNA to distinguish expression from pairs of genetic alleles in individual samples, have high sensitivity and accuracy, allowing differences in mRNA expression greater than 1.2-fold to be quantified with high reproducibility. In this paper, we describe the use of an efficient PCR/next-generation DNA sequencing-based assay to analyze allele-specific differences in mRNA expression for candidate neuropsychiatric disorder genes in human brain.
Results
Using our assay, we successfully analyzed AEI for 70 candidate neuropsychiatric disorder genes in 52 independent human brain samples. Among these genes, 62/70 (89%) showed AEI ratios greater than 1 ± 0.2 in at least one sample and 8/70 (11%) showed no AEI. Arranging log2AEI ratios in increasing order from negative-to-positive values revealed highly reproducible distributions of log2AEI ratios that are distinct for each gene/marker SNP combination. Mathematical modeling suggests that these log2AEI distributions can provide important clues concerning the number, location and contributions of cis-acting regulatory variants to mRNA expression.
Conclusions
We have developed a highly sensitive and reproducible method for quantifying AEI of mRNA expressed in human brain. Importantly, this assay allowed quantification of differential mRNA expression for many candidate disease genes entirely missed in previously published microarray-based studies of mRNA expression in human brain. Given the ability of next-generation sequencing technology to generate large numbers of independent sequencing reads, our method should be suitable for analyzing from 100- to 200-candidate genes in 100 samples in a single experiment. We believe that this is the appropriate scale for investigating variation in mRNA expression for defined sets candidate disorder genes, allowing, for example, comprehensive coverage of genes that function within biological pathways implicated in specific disorders. The combination of AEI measurements and mathematical modeling described in this study can assist in identifying SNPs that correlate with mRNA expression. Alleles of these SNPs (individually or as sets) that accurately predict high- or low-mRNA expression should be useful as markers in genetic association studies aimed at linking candidate genes to specific neuropsychiatric disorders.
doi:10.1186/1471-2164-12-518
PMCID: PMC3228908  PMID: 22013986
5.  Evidence for population variation in TSC1 and TSC2 gene expression 
BMC Medical Genetics  2011;12:29.
Background
Tuberous sclerosis complex (TSC) is an autosomal dominant neurogenetic disorder caused by mutations in one of two genes, TSC1 or TSC2, which encode the proteins hamartin and tuberin, respectively [1-3]. Common features of TSC include intractable epilepsy, mental retardation, and autistic features. TSC is associated with specific brain lesions, including cortical tubers, subependymal nodules and subependymal giant cell astrocytomas. In addition, this disease frequently produces characteristic tumors, termed hamartomas, in the kidneys, heart, skin, retina, and lungs. Disease severity in TSC can be quite variable and is not determined by the primary mutation alone. In fact, there is often considerable variability in phenotype within single families, where all affected individuals carry the same mutation. Factors suspected to influence phenotype in TSC include the specific primary mutation, random occurrence of second-hit somatic mutations, mosaicism, "modifying genes", and environmental factors. In addition to these factors, we hypothesize that differences in mRNA expression from the non-mutated TSC allele, or possibly from the mutated allele, play a part in modifying disease severity. Common genetic variants that regulate mRNA expression have previously been shown to play important roles in human phenotypic variability, including disease susceptibility. A prediction based on this idea is that common regulatory variants that influence disease severity in TSC should be detectable in non-affected individuals.
Methods
A PCR/primer extension assay was used to measure allele specific expression of TSC1 and TSC2 mRNAs in leukocytes isolated from normal volunteers. This assay can be used to measure "allelic expression imbalance" (AEI) in individuals by making use of heterozygous "marker" single nucleotide polymorphisms (SNPs) located within their mRNA.
Results
In this study we show for the first time that TSC1 and TSC2 genes exhibit allele-specific differences in mRNA expression in blood leukocytes isolated from normal individuals.
Conclusions
These results support the possibility that allele-specific variation in TSC mRNA expression contributes to the variable severity of symptoms in TSC patients.
doi:10.1186/1471-2350-12-29
PMCID: PMC3051885  PMID: 21345208
6.  Polymorphisms affecting gene transcription and mRNA processing in pharmacogenetic candidate genes: detection through allelic expression imbalance in human target tissues 
Pharmacogenetics and genomics  2008;18(9):781-791.
Genetic variation in mRNA expression plays a critical role in human phenotypic diversity, but it has proven difficult to detect regulatory polymorphisms - mostly single nucleotide polymorphisms (rSNPs). Additionally, variants in the transcribed region, termed here ‘structural RNA SNPs’ (srSNPs), can affect mRNA processing and turnover. Both rSNPs and srSNPs cause allelic mRNA expression imbalance (AEI) in heterozygous individuals. We have applied a rapid and accurate AEI methodology for testing 42 genes implicated in human diseases and drug response, specifically cardiovascular and CNS diseases, and affecting drug metabolism and transport. Each gene was analyzed in physiologically relevant human autopsy tissues, including brain, heart, liver, intestines, and lymphocytes. Substantial AEI was observed in ∼55% of the surveyed genes. Focusing on cardiovascular candidate genes in human hearts, AEI analysis revealed frequent cis-acting regulatory factors in SOD2 and ACE mRNA expression, having potential clinical significance. SNP scanning to locate regulatory polymorphisms in a number of genes failed to support several previously proposed promoter SNPs discovered with use of reporter gene assays in heterologous tissues, while srSNPs appear more frequent than expected. Computational analysis of mRNA folding indicates that ∼90% of srSNPs affects mRNA folding, and hence potentially function. Our results indicate that both rSNPs and srSNPs represent a still largely untapped reservoir of variants that contribute to human phenotypic diversity.
doi:10.1097/FPC.0b013e3283050107
PMCID: PMC2779843  PMID: 18698231

Results 1-6 (6)