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1.  Stress-induced changes in gene interactions in human cells 
Nucleic Acids Research  2013;42(3):1757-1771.
Cells respond to variable environments by changing gene expression and gene interactions. To study how human cells response to stress, we analyzed the expression of >5000 genes in cultured B cells from nearly 100 normal individuals following endoplasmic reticulum stress and exposure to ionizing radiation. We identified thousands of genes that are induced or repressed. Then, we constructed coexpression networks and inferred interactions among genes. We used coexpression and machine learning analyses to study how genes interact with each other in response to stress. The results showed that for most genes, their interactions with each other are the same at baseline and in response to different stresses; however, a small set of genes acquired new interacting partners to engage in stress-specific responses. These genes with altered interacting partners are associated with diseases in which endoplasmic reticulum stress response or sensitivity to radiation has been implicated. Thus, our findings showed that to understand disease-specific pathways, it is important to identify not only genes that change expression levels but also those that alter interactions with other genes.
doi:10.1093/nar/gkt999
PMCID: PMC3919594  PMID: 24170811
2.  ADAR Regulates RNA Editing, Transcript Stability, and Gene Expression 
Cell reports  2013;5(3):849-860.
SUMMARY
Adenosine deaminases acting on RNA (ADARs) convert adenosine to inosine, which is then recognized as guanosine. To study the role of ADAR proteins in RNA editing and gene regulation, we sequenced and compared the DNA and RNA of human B cells. Then, we followed up the findings experimentally with siRNA knockdown and RNA and protein immunoprecipitations. The results uncovered over 60,000 A-to-G editing sites and several thousand genes whose expression levels are influenced by ADARs. Of these ADAR targets, 90% were identified. Our results also reveal that ADAR regulates transcript stability and gene expression through interaction with HuR (ELAVL1). These findings extend the role of ADAR and show that it cooperates with other RNA-processing proteins to regulate the sequence and expression of transcripts in human cells.
doi:10.1016/j.celrep.2013.10.002
PMCID: PMC3935819  PMID: 24183664
3.  HGV2011: Personalized Genomic Medicine Meets the Incidentalome 
Human mutation  2012;33(3):10.1002/humu.22008.
The 12th International Meeting on Human Genome Variation and Complex Genome Analysis (HGV2011: Berkeley, California, USA, 8th–10th September 2011) was a stimulating workshop where researchers from academia and industry explored the latest progress, challenges, and opportunities in genome variation research. Key themes included progress beyond GWAS, variation in human populations, use of sequence data in medical settings, large-scale sequencing data analysis, and bioinformatics approaches to large datasets.
doi:10.1002/humu.22008
PMCID: PMC3867005  PMID: 22170622
human variation; GWAS; SNP; medical genomics
4.  Widespread RNA and DNA Sequence Differences in the Human Transcriptome 
Science (New York, N.Y.)  2011;333(6038):53-58.
The transmission of information from DNA to RNA is a critical process. We compared RNA sequences from human B cells of 27 individuals to the corresponding DNA sequences from the same individuals and uncovered more than 10,000 exonic sites where the RNA sequences do not match that of the DNA. All 12 possible categories of discordances were observed. These differences were nonrandom as many sites were found in multiple individuals and in different cell types, including primary skin cells and brain tissues. Using mass spectrometry, we detected peptides that are translated from the discordant RNA sequences and thus do not correspond exactly to the DNA sequences. These widespread RNA-DNA differences in the human transcriptome provide a yet unexplored aspect of genome variation.
doi:10.1126/science.1207018
PMCID: PMC3204392  PMID: 21596952
5.  Mapping determinants of human gene expression by regional and genome-wide association 
Nature  2005;437(7063):1365-1369.
To study the genetic basis of natural variation in gene expression, we previously carried out genome-wide linkage analysis and mapped the determinants of ~1,000 expression phenotypes1. In the present study, we carried out association analysis with dense sets of single-nucleotide polymorphism (SNP) markers from the International HapMap Project2. For 374 phenotypes, the association study was performed with markers only from regions with strong linkage evidence; these regions all mapped close to the expressed gene. For a subset of 27 phenotypes, analysis of genome-wide association was performed with >770,000 markers. The association analysis with markers under the linkage peaks confirmed the linkage results and narrowed the candidate regulatory regions for many phenotypes with strong linkage evidence. The genome-wide association analysis yielded highly significant results that point to the same locations as the genome scans for about 50% of the phenotypes. For one candidate determinant, we carried out functional analyses and confirmed the variation in cis-acting regulatory activity. Our findings suggest that association studies with dense SNP maps will identify susceptibility loci or other determinants for some complex traits or diseases.
doi:10.1038/nature04244
PMCID: PMC3005311  PMID: 16251966
6.  Genetic analysis of radiation-induced changes in human gene expression 
Nature  2009;459(7246):587-591.
Humans are exposed to radiation through the environment and in medical settings. To deal with radiation-induced damage, cells mount complex responses that rely on changes in gene expression. These gene expression responses differ greatly between individuals1 and contribute to individual differences in response to radiation2. Here we identify regulators that influence expression levels of radiation-responsive genes. We treated radiation-induced changes in gene expression as quantitative phenotypes3,4, and conducted genetic linkage and association studies to map their regulators. For more than 1,200 of these phenotypes there was significant evidence of linkage to specific chromosomal regions. Nearly all of the regulators act in trans to influence the expression of their target genes; there are very few cis-acting regulators. Some of the transacting regulators are transcription factors, but others are genes that were not known to have a regulatory function in radiation response. These results have implications for our basic and clinical understanding of how human cells respond to radiation.
doi:10.1038/nature07940
PMCID: PMC3005325  PMID: 19349959
7.  In silico method for inferring genotypes in pedigrees 
Nature genetics  2006;38(9):1002-1004.
Our genotype inference method combines sparse marker data from a linkage scan and high-resolution SNP genotypes for several individuals to infer genotypes for related individuals. We illustrate the method’s utility by inferring over 53 million SNP genotypes for 78 children in the Centre d’Etude du Polymorphisme Humain families. The method can be used to obtain high-density genotypes in different family structures, including nuclear families commonly used in complex disease gene mapping studies.
doi:10.1038/ng1863
PMCID: PMC3005330  PMID: 16921375
8.  Common genetic variants account for differences in gene expression among ethnic groups 
Nature genetics  2007;39(2):226-231.
Variation in DNA sequence contributes to individual differences in quantitative traits, but in humans the specific sequence variants are known for very few traits. We characterized variation in gene expression in cells from individuals belonging to three major population groups. This quantitative phenotype differs significantly between European-derived and Asian-derived populations for 1,097 of 4,197 genes tested. For the phenotypes with the strongest evidence of cis determinants, most of the variation is due to allele frequency differences at cis-linked regulators. The results show that specific genetic variation among populations contributes appreciably to differences in gene expression phenotypes. Populations differ in prevalence of many complex genetic diseases, such as diabetes and cardiovascular disease. As some of these are probably influenced by the level of gene expression, our results suggest that allele frequency differences at regulatory polymorphisms also account for some population differences in prevalence of complex diseases.
doi:10.1038/ng1955
PMCID: PMC3005333  PMID: 17206142
9.  Genetics of human gene expression: mapping DNA variants that influence gene expression 
Nature reviews. Genetics  2009;10(9):595-604.
There is extensive natural variation in human gene expression. As quantitative phenotypes, expression levels of genes are heritable. Genetic linkage and association mapping have identified cis- and trans-acting DNA variants that influence expression levels of human genes. New insights into human gene regulation are emerging from genetic analyses of gene expression in cells at rest and following exposure to stimuli. The integration of these genetic mapping results with data from co-expression networks is leading to a better understanding of how expression levels of individual genes are regulated and how genes interact with each other. These findings are important for basic understanding of gene regulation and of diseases that result from disruption of normal gene regulation.
doi:10.1038/nrg2630
PMCID: PMC2989458  PMID: 19636342
10.  Genetic analysis of genome-wide variation in human gene expression 
Nature  2004;430(7001):743-747.
Natural variation in gene expression is extensive in humans and other organisms, and variation in the baseline expression level of many genes has a heritable component. To localize the genetic determinants of these quantitative traits (expression phenotypes) in humans, we used microarrays to measure gene expression levels and performed genome-wide linkage analysis for expression levels of 3,554 genes in 14 large families. For approximately 1,000 expression phenotypes, there was significant evidence of linkage to specific chromosomal regions. Both cis- and trans-acting loci regulate variation in the expression levels of genes, although most act in trans. Many gene expression phenotypes are influenced by several genetic determinants. Furthermore, we found hotspots of transcriptional regulation where significant evidence of linkage for several expression phenotypes (up to 31) coincides, and expression levels of many genes that share the same regulatory region are significantly correlated. The combination of microarray techniques for phenotyping and linkage analysis for quantitative traits allows the genetic mapping of determinants that contribute to variation in human gene expression.
doi:10.1038/nature02797
PMCID: PMC2966974  PMID: 15269782
11.  Polymorphic Cis- and Trans-Regulation of Human Gene Expression 
PLoS Biology  2010;8(9):e1000480.
Using genetic and molecular analyses, we identified over 1,000 polymorphic regulators that regulate expression levels of human genes.
Expression levels of human genes vary extensively among individuals. This variation facilitates analyses of expression levels as quantitative phenotypes in genetic studies where the entire genome can be scanned for regulators without prior knowledge of the regulatory mechanisms, thus enabling the identification of unknown regulatory relationships. Here, we carried out such genetic analyses with a large sample size and identified cis- and trans-acting polymorphic regulators for about 1,000 human genes. We validated the cis-acting regulators by demonstrating differential allelic expression with sequencing of transcriptomes (RNA-Seq) and the trans-regulators by gene knockdown, metabolic assays, and chromosome conformation capture analysis. The majority of the regulators act in trans to the target (regulated) genes. Most of these trans-regulators were not known to play a role in gene expression regulation. The identification of these regulators enabled the characterization of polymorphic regulation of human gene expression at a resolution that was unattainable in the past.
Author Summary
Cellular characteristics and functions are determined largely by gene expression and expression levels differ among individuals, however it is not clear how these levels are regulated. While many cis-acting DNA sequence variants in promoters and enhancers that influence gene expression have been identified, only a few polymorphic trans-regulators of human genes are known. Here, we used human B-cells from individuals belonging to large families and identified polymorphic trans-regulators for about 1,000 human genes. We validated these results by gene knockdown, metabolic perturbation studies and chromosome conformation capture assays. Although these regulatory relationships were identified in cultured B-cells, we show that some of the relationships were also found in primary fibroblasts. The large number of regulators allowed us to better understand gene expression regulation, to uncover new gene functions, and to identify their roles in disease processes. This study shows that genetic variation is a powerful tool not only for gene mapping but also to study gene interaction and regulation.
doi:10.1371/journal.pbio.1000480
PMCID: PMC2939022  PMID: 20856902
12.  Identification of polymorphic antioxidant response elements (AREs) in the human genome 
Human molecular genetics  2007;16(10):1188-1200.
Single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBSs) may affect the binding of transcription factors, lead to differences in gene expression and phenotypes, and therefore affect susceptibility to environmental exposure. We developed an integrated computational system for discovering functional SNPs in TFBSs in the human genome and predicting their impact on the expression of target genes. In this system we: (1) construct a position weight matrix (PWM) from a collection of experimentally discovered TFBSs; (2) predict TFBSs in SNP sequences using the PWM and map SNPs to the upstream regions of genes; (3) examine the evolutionary conservation of putative TFBSs by phylogenetic footprinting; (4) prioritize candidate SNPs based on microarray expression profiles from tissues in which the transcription factor of interest is either deleted or over-expressed; and (5) finally, analyze association of SNP genotypes with gene expression phenotypes. The application of our system has been tested to identify functional polymorphisms in the antioxidant response element (ARE), a cis-acting enhancer sequence found in the promoter region of many genes that encode antioxidant and Phase II detoxification enzymes/proteins. In response to oxidative stress, the transcription factor NRF2 (nuclear factor erythroid-derived 2-like 2) binds to AREs, mediating transcriptional activation of its responsive genes and modulating in vivo defense mechanisms against oxidative damage. Using our novel computational tools, we have identified a set of polymorphic AREs with functional evidence, showing the utility of our system to direct further experimental validation of genomic sequence variations that could be useful for identifying high-risk individuals.
doi:10.1093/hmg/ddm066
PMCID: PMC2805149  PMID: 17409198
13.  Genetic Analysis of Variation in Human Meiotic Recombination 
PLoS Genetics  2009;5(9):e1000648.
The number of recombination events per meiosis varies extensively among individuals. This recombination phenotype differs between female and male, and also among individuals of each gender. In this study, we used high-density SNP genotypes of over 2,300 individuals and their offspring in two datasets to characterize recombination landscape and to map the genetic variants that contribute to variation in recombination phenotypes. We found six genetic loci that are associated with recombination phenotypes. Two of these (RNF212 and an inversion on chromosome 17q21.31) were previously reported in the Icelandic population, and this is the first replication in any other population. Of the four newly identified loci (KIAA1462, PDZK1, UGCG, NUB1), results from expression studies provide support for their roles in meiosis. Each of the variants that we identified explains only a small fraction of the individual variation in recombination. Notably, we found different sequence variants associated with female and male recombination phenotypes, suggesting that they are regulated by different genes. Characterization of genetic variants that influence natural variation in meiotic recombination will lead to a better understanding of normal meiotic events as well as of non-disjunction, the primary cause of pregnancy loss.
Author Summary
Meiotic recombination is essential for the formation of human gametes and is a key process that generates genetic diversity. Given its importance, we would expect the number and location of exchanges to be tightly regulated. However, studies show significant gender and inter-individual variation in genome-wide recombination rates. The genetic basis for this variation is poorly understood. In this study, we used genotypes from high-density single nucleotide polymorphism (SNP) markers of 2,315 individuals and their children from two Caucasian samples in a genome-wide association study to identify genetic variants that influence the number of meiotic recombination events per gamete. We found three loci that influence female recombination and three different loci that influence male recombination. Our results suggest that gender differences in recombination result from differences in the genetic regulation of female and male meiosis. Also, each identified locus only explains a small proportion of variance; together, each set of loci explains about 10% of the variation in the gender-specific recombination phenotype. This suggests a mechanism for variability in recombination that is essential for genetic diversity while maintaining the number of recombinations within a range to ensure proper chromosome segregation.
doi:10.1371/journal.pgen.1000648
PMCID: PMC2730532  PMID: 19763160
14.  Effects of cis and trans Genetic Ancestry on Gene Expression in African Americans 
PLoS Genetics  2008;4(12):e1000294.
Variation in gene expression is a fundamental aspect of human phenotypic variation. Several recent studies have analyzed gene expression levels in populations of different continental ancestry and reported population differences at a large number of genes. However, these differences could largely be due to non-genetic (e.g., environmental) effects. Here, we analyze gene expression levels in African American cell lines, which differ from previously analyzed cell lines in that individuals from this population inherit variable proportions of two continental ancestries. We first relate gene expression levels in individual African Americans to their genome-wide proportion of European ancestry. The results provide strong evidence of a genetic contribution to expression differences between European and African populations, validating previous findings. Second, we infer local ancestry (0, 1, or 2 European chromosomes) at each location in the genome and investigate the effects of ancestry proximal to the expressed gene (cis) versus ancestry elsewhere in the genome (trans). Both effects are highly significant, and we estimate that 12±3% of all heritable variation in human gene expression is due to cis variants.
Author Summary
Variation in gene expression is a fundamental aspect of human phenotypic variation, and understanding how this variation is apportioned among human populations is an important aim. Previous studies have compared gene expression levels between distinct populations, but it is unclear whether the differences that were observed have a genetic or nongenetic basis. Admixed populations, such as African Americans, offer a solution to this problem because individuals vary in their proportion of European ancestry while the analysis of a single population minimizes nongenetic factors. Here, we show that differences in gene expression among African Americans of different ancestry proportions validate gene expression differences between European and African populations. Furthermore, by drawing a distinction between an African American individual's ancestry at the location of a gene whose expression is being analyzed (cis) versus at distal locations (trans), we can use ancestry effects to quantify the relative contributions of cis and trans regulation to human gene expression. We estimate that 12±3% of all heritable variation in human gene expression is due to cis variants.
doi:10.1371/journal.pgen.1000294
PMCID: PMC2586034  PMID: 19057673
15.  Genetic heterogeneity and trans regulators of gene expression 
BMC Proceedings  2007;1(Suppl 1):S80.
Heterogeneity poses a challenge to linkage mapping. Here, we apply a latent class extension of Haseman-Elston regression to expression phenotypes with significant evidence of linkage to trans regulators in 14 large pedigrees. We test for linkage, accounting for heterogeneity, and classify individual families as "linked" and "unlinked" on the basis of their contribution to the overall evidence of linkage.
PMCID: PMC2367595  PMID: 18466583
16.  Data for Genetic Analysis Workshop (GAW) 15, Problem 1: genetics of gene expression variation in humans 
BMC Proceedings  2007;1(Suppl 1):S2.
Here we describe the data provided for Problem 1 of Genetic Analysis Workshop 15. The data provided for Problem 1 were unusual in two ways. First, the phenotype was the level of gene expression for each gene, not a conventional phenotype like height or disease, and second, there were more than 3500 such phenotypes. Natural variation in gene expression was a new idea in 2004 when these data were collected and published. Because the phenotypes were measured in members of 14 Centre d'Etude du Polymorphisme Humain (CEPH) families, there was an opportunity for linkage mapping on a very large scale. For this purpose, 2882 single-nucleotide polymorphism genotypes were also provided for each family member.
PMCID: PMC2367458  PMID: 18466516
17.  GenMapDB: a database of mapped human BAC clones 
Nucleic Acids Research  2001;29(1):144-147.
GenMapDB (http://genomics.med.upenn.edu/genmapdb) is a repository of human bacterial artificial chromosome (BAC) clones mapped by our laboratory to sequence-tagged site markers. Currently, GenMapDB contains over 3000 mapped clones that span 19 chromosomes, chromosomes 2, 4, 5, 9–22, X and Y. This database provides positional information about human BAC clones from the RPCI-11 human male BAC library. It also contains restriction fragment analysis data and end sequences of the clones. GenMapDB is freely available to the public. The main purpose of GenMapDB is to organize the mapping data and to allow the research community to search for mapped BAC clones that can be used in gene mapping studies and chromosomal mutation analysis projects.
PMCID: PMC29809  PMID: 11125073

Results 1-17 (17)