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Linkage analysis with genetic markers has been successful in the localization of genes for many monogenic human diseases. In studies of complex diseases, however, tests that rely on linkage disequilibrium (the simultaneous presence of linkage and association) are often more powerful than those that rely on linkage alone. This advantage is illustrated by the transmission/disequilibrium test (TDT). The TDT requires data (marker genotypes) for affected individuals and their parents; for some diseases, however, data from parents may be difficult or impossible to obtain. In this article, we describe a method, called the "sib TDT" (or "S-TDT"), that overcomes this problem by use of marker data from unaffected sibs instead of from parents, thus allowing application of the principle of the TDT to sibships without parental data. In a single collection of families, there might be some that can be analyzed only by the TDT and others that are suitable for analysis by the S-TDT. We show how all the data may be used jointly in one overall TDT-type procedure that tests for linkage in the presence of association. These extensions of the TDT will be valuable for the study of diseases of late onset, such as non-insulin-dependent diabetes, cardiovascular diseases, and other diseases associated with aging.

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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 ...

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Mathematical population genetics is only one of Kingman's many research interests. Nevertheless, his contribution to this field has been crucial, and moved it in several important new directions. Here we outline some aspects of his work which have had a major influence on population genetics theory.

As evidenced by the complete absence of a functionally critical sequence in exon 7, approximately 94% of individuals with clinically typical spinal muscular atrophy (SMA) lack both copies of the SMN1 gene at 5q13. Hence most carriers have only one copy of SMN1. Combining linkage and dosage analyses for SMN1, we observed unaffected individuals who have two copies of SMN1 on one chromosome 5 and zero copies of SMN1 on the other chromosome 5. By dosage analysis alone, such individuals, as well as carriers of non-deletion disease alleles, are indistinguishable from non-carrier individuals. We report that approximately 7% of unaffected individuals without a family history of SMA have three or four copies of SMN1, implying a higher frequency of chromosomes with two copies of SMN1 than previously reported. We present updated calculations for disease and non-disease allele frequencies and we describe how these frequencies can be used for genetic risk assessment in carrier testing for SMA.