Richard S. Spielman

Genetic analysis of genome-wide variation in human gene expression

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.

Natural variation in human gene expression assessed in lymphoblastoid cells

The sequencing of the human genome has resulted in greater attention to genetic variation among individuals, and variation at the DNA sequence level is now being extensively studied. At the same time, it has become possible to study variation at the level of gene expression by various methods. At present, it is largely unknown how widespread this variation in transcript levels is over the entire genome and to what extent individual differences in expression level are genetically determined. In the present study, we used lymphoblastoid cells to examine variation in gene expression and identified genes whose transcript levels differed greatly among unrelated individuals. We also found evidence for familial aggregation of expression phenotype by comparing variation among unrelated individuals, among siblings within families and between monozygotic twins. These observations suggest that there is a genetic contribution to polymorphic variation in the level of gene expression.

Mapping determinants of human gene expression by regional and genome-wide association

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 phenotypes. In the present study, we carried out association analysis with dense sets of single-nucleotide polymorphism (SNP) markers from the International HapMap Project. 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.

Common genetic variants account for differences in gene expression among ethnic groups

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.

A second-generation screen of the human genome for susceptibility to insulin-dependent diabetes mellitus

During the past decade, the genetics of type 1 (insulin-dependent) diabetes mellitus (IDDM) has been studied extensively and the disorder has become a paradigm for genetically complex diseases. Previous genome screens and studies focused on candidate genes have provided evidence for genetic linkage between polymorphic DNA markers and 15 putative IDDM susceptibility loci, designated IDDM1-IDDM15 . We have carried out a second-generation screen of the genome for linkage and analysed the data by multipoint linkage methods. An initial panel of 212 affected sibpairs (ASPs) was genotyped for 438 markers spanning all autosomes, and an additional 467 ASPs were used for follow-up genotyping. Other than the well-established linkage with the HLA region at chromosome 6p21.3, there was only one region, located on chromosome 1q and not previously reported, where the log likelihood ratio (lod) was greater than 3. Lods between 1.0 and 1.8 were found in six other regions, three of which have been reported in other studies. Another reported region, on chromosome 6q and loosely linked to HLA, also had an elevated lod. Little or no support was found for most reported IDDM loci (lods were less than 1), despite larger sample sizes in the present study.

Structure, Sequence and Polymorphism in the HLA‐D Region

Molecular analysis of the HLA-D region has uncovered a complex array of related genes encompassing a minimum of 6 alpha and 7 beta chain sequences. A high level of polymorphism is characteristic of the DQ alpha and beta genes, as well as DR beta. The DP genes, both alpha and beta, are also polymorphic, though to a lesser extent. The genes fit into the previously established loci: DP, DQ and DR, except for a newly-discovered sequence, DZ alpha, which is approximately equally related to all of the other alpha chain genes. Analysis of the polymorphism and evolution of the HLA-D region, by examination of the sequences, calls for several independent duplication events in the generation of this family of genes.

Genetics of human gene expression: mapping DNA variants that influence gene expression

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.

Genetic analysis of radiation-induced changes in human gene expression

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 individuals and contribute to individual differences in response to radiation. Here we identify regulators that influence expression levels of radiation-responsive genes. We treated radiation-induced changes in gene expression as quantitative phenotypes, 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 trans-acting 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.

Phenotype and genotype in polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a common disorder in premenopausal women and is characterized by hyperandrogenic chronic anovulation. The cause is unknown. PCOS is associated with significant insulin resistance as well as with defects in insulin secretion. These abnormalities place these women at substantial risk for developing type 2 diabetes mellitus. A defect in insulin-mediated receptor autophosphorylation has been found in a substantial proportion of PCOS women. Both PCOS and the insulin resistance that accompanies it appear to have major genetic components. Family studies of PCOS have supported this, although they suffer from incomplete phenotyping of probands and first-degree relatives. The phenotype in males and nonreproductive age females is uncertain. Despite the shortcomings of the family studies of PCOS, they have consistently indicated familial clustering and suggested that the mode of inheritance is dominant. Our initial studies of 50 families of PCOS probands indicate that 24% of sisters are affected with PCOS. There also appears to be an intermediate phenotype of sisters with regular menstrual cycles who are hyperandrogenic per se (22% of sisters). Additionally, there appears to be a major familial defect, with 50% of first-degree relatives having glucose intolerance (impaired glucose tolerance by oral glucose tolerance test or type 2 diabetes mellitus). These findings suggest that hyperandrogenism in females and glucose intolerance may be genetic traits in PCOS kindreds. Systematic phenotyping will allow assignment of affected status for eventual linkage analysis.

A mixed epigenetic/genetic model for oligogenic inheritance of autism with a limited role for UBE3A.

The genetic contribution to autism is often attributed to the combined effects of many loci (ten or more). This conclusion is based in part on the much lower concordance for dizygotic (DZ) than for monozygotic (MZ) twins, and is consistent with the failure to find strong evidence for linkage in genome‐wide studies. We propose that the twin data are compatible with oligogenic inheritance combined with a major, genetic or epigenetic, de novo component to the etiology. Based on evidence that maternal but not paternal duplications of chromosome 15q cause autism, we attempted to test the hypothesis that autism involves oligogenic inheritance (two or more loci) and that the Angelman gene (UBE3A), which encodes the E6‐AP ubiquitin ligase, is one of the contributing genes. A search for epigenetic abnormalities led to the discovery of a tissue‐specific differentially methylated region (DMR) downstream of the UBE3A coding exons, but the region was not abnormal in autism lymphoblasts or brain samples. Based on evidence for allele sharing in 15q among sib‐pairs, abnormal DNA methylation at the 5′‐CpG island of UBE3A in one of 17 autism brains, and decreased E6‐AP protein in some autism brains, we propose a mixed epigenetic and genetic model for autism with both de novo and inherited contributions. The role of UBE3A may be quantitatively modest, but interacting proteins such as those ubiquitinated by UBE3A may be candidates for a larger role in an oligogenic model. A mixed epigenetic and genetic and mixed de novo and inherited (MEGDI) model could be relevant to other “complex disease traits”.