Genetic dissection of complex traits in yeast: insights from studies of gene expression and other phenotypes in the BYxRM cross.

The genetic basis of many phenotypes of biological and medical interest, including susceptibility to common human diseases, is complex, involving multiple genes that interact with one another and the environment. Despite decades of effort, we possess neither a full grasp of the general rules that govern complex trait genetics nor a detailed understanding of the genetic basis of specific complex traits. We have used a cross between two yeast strains, BY and RM, to systematically investigate the genetic complexity underlying differences in global gene expression and other traits. The number and diversity of traits dissected to the locus, gene, and nucleotide levels in the BYxRM cross make it arguably the most extensively characterized system with regard to causal effects of genetic variation on phenotype. We summarize the insights obtained to date into the genetics of complex traits in yeast, with an emphasis on the BYxRM cross. We then highlight the central outstanding questions about the genetics of complex traits and discuss how to answer them using yeast as a model system.

Genomewide search for type 2 diabetes mellitus susceptibility loci in Finnish families: the Botnia study.

Type 2 diabetes mellitus is a heterogeneous inherited disorder characterized by chronic hyperglycemia resulting from pancreatic beta-cell dysfunction and insulin resistance. Although the pathogenic mechanisms are not fully understood, manifestation of the disease most likely requires interaction between both environmental and genetic factors. In the search for such susceptibility genes, we have performed a genomewide scan in 58 multiplex families (comprising 440 individuals, 229 of whom were affected) from the Botnia region in Finland. Initially, linkage between chromosome 12q24 and impaired insulin secretion had been reported, by Mahtani et al., in a subsample of 26 families. In the present study, we extend the initial genomewide scan to include 32 additional families, update the affectation status, and fine map regions of interest, and we try to replicate the initial stratification analysis. In our analysis of all 58 families, we identified suggestive linkage to one region, chromosome 9p13-q21 (nonparametric linkage [NPL] score 3.9; P<.0002). Regions with nominal P values <.05 include chromosomes 2p11 (NPL score 2.0 [P<.03]), 3p24-p22 (NPL score 2.2 [P<.02]), 4q32-q33 (NPL score 2.5 [P<.01]), 12q24 (NPL score 2.1 [P<.03]), 16p12-11 (NPL score 1.7 [P<.05]), and 17p12-p11 (NPL score 1.9 [P<.03]). When chromosome 12q24 was analyzed in only the 32 additional families, a nominal P value <.04 was observed. Together with data from other published genomewide scans, these findings lend support to the hypothesis that regions on chromosome 9p13-q21 and 12q24 may harbor susceptibility genes for type 2 diabetes.

Sequence variation and linkage disequilibrium in the human T-cell receptor beta (TCRB) locus.

The T-cell receptor (TCR) plays a central role in the immune system, and > 90% of human T cells present a receptor that consists of the alpha TCR subunit (TCRA) and the beta subunit (TCRB). Here we report an analysis of 63 variable genes (BV), spanning 553 kb of TCRB that yielded 279 single-nucleotide polymorphisms (SNPs). Samples were drawn from 10 individuals and represent four populations-African American, Chinese, Mexican, and Northern European. We found nine variants that produce nonfunctional BV segments, removing those genes from the TCRB genomic repertoire. There was significant heterogeneity among population samples in SNP frequency (including the BV-inactivating sites), indicating the need for multiple-population samples for adequate variant discovery. In addition, we observed considerable linkage disequilibrium (LD) (r(2) > 0.1) over distances of approximately 30 kb in TCRB, and, in general, the distribution of r(2) as a function of physical distance was in close agreement with neutral coalescent simulations. LD in TCRB showed considerable spatial variation across the locus, being concentrated in "blocks" of LD; however, coalescent simulations of the locus illustrated that the heterogeneity of LD we observed in TCRB did not differ markedly from that expected from neutral processes. Finally, examination of the extended genotypes for each subject demonstrated homozygous stretches of >100 kb in the locus of several individuals. These results provide the basis for optimization of locuswide SNP typing in TCRB for studies of genotype-phenotype association.

Lower-than-expected linkage disequilibrium between tightly linked markers in humans suggests a role for gene conversion.

Understanding the pattern of linkage disequilibrium (LD) in the human genome is important both for successful implementation of disease-gene mapping approaches and for inferences about human demographic histories. Previous studies have examined LD between loci within single genes or confined genomic regions, which may not be representative of the genome; between loci separated by large distances, where little LD is seen; or in population groups that differ from one study to the next. We measured LD in a large set of locus pairs distributed throughout the genome, with loci within each pair separated by short distances (average 124 bp). Given current models of the history of the human population, nearly all pairs of loci at such short distances would be expected to show complete LD as a consequence of lack of recombination in the short interval. Contrary to this expectation, a significant fraction of pairs showed incomplete LD. A standard model of recombination applied to these data leads to an estimate of effective human population size of 110,000. This estimate is an order of magnitude higher than most estimates based on nucleotide diversity. The most likely explanation of this discrepancy is that gene conversion increases the apparent rate of recombination between nearby loci.

Efficient multipoint linkage analysis through reduction of inheritance space.

Computational constraints currently limit exact multipoint linkage analysis to pedigrees of moderate size. We introduce new algorithms that allow analysis of larger pedigrees by reducing the time and memory requirements of the computation. We use the observed pedigree genotypes to reduce the number of inheritance patterns that need to be considered. The algorithms are implemented in a new version (version 2.1) of the software package GENEHUNTER. Performance gains depend on marker heterozygosity and on the number of pedigree members available for genotyping, but typically are 10-1,000-fold, compared with the performance of the previous release (version 2.0). As a result, families with up to 30 bits of inheritance information have been analyzed, and further increases in family size are feasible. In addition to computation of linkage statistics and haplotype determination, GENEHUNTER can also perform single-locus and multilocus transmission/disequilibrium tests. We describe and implement a set of permutation tests that allow determination of empirical significance levels in the presence of linkage disequilibrium among marker loci.

A joint analysis of asthma affection status and IgE levels in multiple data sets collected for asthma.

We present a joint linkage analysis of eight data sets collected for asthma. Three of the data sets are full genome scans, while the remaining five concentrate on a 40-cM region on chromosome 5. We perform the analysis using one qualitative and one quantitative phenotype: asthma status and IgE level. Considering all data sets simultaneously, we do not find evidence for linkage to asthma affection status beyond the level expected to occur by chance twice per genome scan. In contrast, we observe significant linkage to IgE level on chromosome 6.

An analysis of strategies for discovery of single-nucleotide polymorphisms.

Strategies for the discovery of single-nucleotide polymorphisms (SNPs) can be characterized by the number of individuals in the discovery sample, and by the minimal required number of observations of each allele. We examine the effect of different strategies on two key properties of the resulting SNP collection: (1) the probability that a SNP with a given population allele frequency is detected; and (2) the allele-frequency distribution of the discovered SNPs. We show that strategies that accept all polymorphic sites lead to collections with a high fraction of SNPs with rare minor alleles, particularly in expanded populations. Such SNPs have a low probability of replication in a second sample. We discuss how to tailor a discovery strategy to the desired properties of a SNP collection.