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.The expression levels of genes determine the distinctive characteristics of cells. Recent studies have shown that gene expression levels in humans differ not only among cell types within an individual but also among individuals 1,2 . This observation led to analysis of gene expression as a phenotype and to the identification of polymorphic genetic variants that influence individual differences in expression level [3][4][5][6][7][8] . However, these studies of the genetics of human gene expression have been restricted to individuals from one Europeanderived sample, the families collected by the Centre d'Etude du Polymorphisme Humain Correspondence should be addressed to V.G.C. (vcheung@mail.med.upenn.edu) or R.S.S. (spielman@pobox.upenn.edu). Accession codes. Gene Expression Omnibus (GEO): GSE5859.URLs. Human Variation Panel: http://ccr.coriell.org/nigms/cells/humdiv.html. MultiExperiment Viewer: http://www.tm4.org. Information on HapMap SNP markers can be found at http://www.hapmap.org.Note: Supplementary information is available on the Nature Genetics website. COMPETING INTERESTS STATEMENTThe authors declare that they have no competing financial interests. Much of the recognized genetic variation among populations is in DNA polymorphisms with no known functional significance. On the other hand, some allele frequency differences between populations have highly significant phenotypic consequences. Among the bestestablished are the differences in allele frequencies for mendelian genetic diseases. The marked population differences in prevalence of these qualitative phenotypes (such as cystic fibrosis 9 and Tay-Sachs disease 10 ) are entirely due to differences in frequencies of the mutant alleles. However, genetic differences among populations in quantitative phenotypes are potentially just as important functionally.Here we extend the comparative genetic analysis of population differences from qualitative phenotypes to a particular quantitative phenotype, the expression ...

Despite being scarce in the human genome, active L1 retrotransposons continue to play a significant role in its evolution. Because of their recent expansion, many L1s are not fixed in humans, and, when present, their mobilization potential can vary among individuals. Previously, we showed that the great majority of retrotransposition events in humans are caused by highly active, or hot, L1s. Here, in four populations of diverse geographic origins (160 haploid genomes), we investigated the degree of sequence polymorphism of three hot L1s and the extent of individual variation in mobilization capability of their allelic variants. For each locus, we found one previously uncharacterized allele in every three to five genomes, including some with nonsense and insertion͞deletion mutations. Single or multiple nucleotide substitutions drastically affected the retrotransposition efficiency of some alleles. Onethird of elements were no longer hot, and these so-called cool alleles substantially increased the range of individual susceptibility to retrotransposition events. Adding the activity of the three elements in each individual resulted in a surprising degree of variation in mobilization capability, ranging from 0% to 390% of a reference L1. These data suggest that individual variation in retrotransposition potential makes an important contribution to human genetic diversity.human variation ͉ population genetics ͉ retrotransposon

Complex diseases such as cardiovascular disease are likely due to the effects of high-order interactions among multiple genes and demographic factors. Therefore, in order to understand their underlying biological mechanisms, we need to consider simultaneously the effects of genotypes across multiple loci. Statistical methods such as multifactor dimensionality reduction (MDR), the combinatorial partitioning method (CPM), recursive partitioning (RP), and patterning and recursive partitioning (PRP) are designed to uncover complex relationships without relying on a specific model for the interaction, and are therefore well-suited to this data setting. However, the theoretical overlap among these methods and their relative merits have not been well characterized. In this paper we demonstrate mathematically that MDR is a special case of RP in which (1) patterns are used as predictors (PRP), (2) tree growth is restricted to a single split, and (3) misclassification error is used as the measure of impurity. Both approaches are applied to a case-control study assessing the effect of eleven single nucleotide polymorphisms on coronary artery calcification in people at risk for cardiovascular disease.

The spring asthma peak is closely associated with increased tree pollen counts, and the asthma increase at this time is likely due to allergic reactions to pollen. No significant associations could be established with the fall peak. The winter peak correlates with elevated SO(2) and NO(x) levels.

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.