SNP and haplotype mapping for genetic analysis in the rat

The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.     

A genome-wide scalable SNP genotyping assay using microarray technology

Oligonucleotide probe arrays have enabled massively parallel analysis of gene expression levels from a single cDNA sample. Application of microarray technology to analyzing genomic DNA has been stymied by the sequence complexity of the entire human genome. A robust, single base-resolution direct genomic assay would extend the reach of microarray technology. We developed an array-based whole-genome genotyping assay that does not require PCR and enables effectively unlimited multiplexing. The assay achieves a high signal-to-noise ratio by combining specific hybridization of picomolar concentrations of whole genome-amplified DNA to arrayed probes with allele-specific primer extension and signal amplification. As proof of principle, we genotyped several hundred previously characterized SNPs. The conversion rate, call rate and accuracy were comparable to those of high-performance PCR-based genotyping assays.     

Systematic assessment of copy number variant detection via genome-wide SNP genotyping

SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.     

Human Genome Variation 2006: emerging views on structural variation and large-scale SNP analysis

The eighth annual Human Genome Variation Meeting was held in September 2006 in the Hong Kong Special Administrative Region, China. The meeting highlighted recent advances in characterization of genetic variation, including genome-wide association studies and structural variation.     

An evaluation of HapMap sample size and tagging SNP performance in large-scale empirical and simulated data sets

A substantial investment has been made in the generation of large public resources designed to enable the identification of tag SNP sets, but data establishing the adequacy of the sample sizes used are limited. Using large-scale empirical and simulated data sets, we found that the sample sizes used in the HapMap project are sufficient to capture common variation, but that performance declines substantially for variants with minor allele frequencies of <5%.     

Bayesian method to predict individual SNP genotypes from gene expression data

RNA profiling can be used to capture the expression patterns of many genes that are associated with expression quantitative trait loci (eQTLs). Employing published putative cis eQTLs, we developed a Bayesian approach to predict SNP genotypes that is based only on RNA expression data. We show that predicted genotypes can accurately and uniquely identify individuals in large populations. When inferring genotypes from an expression data set using eQTLs of the same tissue type (but from an independent cohort), we were able to resolve 99% of the identities of individuals in the cohort at P(adjusted) ≤ 1 × 10(-5). When eQTLs derived from one tissue were used to predict genotypes using expression data from a different tissue, the identities of 90% of the study subjects could be resolved at P(adjusted) ≤ 1 × 10(-5). We discuss the implications of deriving genotypic information from RNA data deposited in the public domain.     

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.     

A SNP in the ABCC11 gene is the determinant of human earwax type

Human earwax consists of wet and dry types. Dry earwax is frequent in East Asians, whereas wet earwax is common in other populations. Here we show that a SNP, 538G --> A (rs17822931), in the ABCC11 gene is responsible for determination of earwax type. The AA genotype corresponds to dry earwax, and GA and GG to wet type. A 27-bp deletion in ABCC11 exon 29 was also found in a few individuals of Asian ancestry. A functional assay demonstrated that cells with allele A show a lower excretory activity for cGMP than those with allele G. The allele A frequency shows a north-south and east-west downward geographical gradient; worldwide, it is highest in Chinese and Koreans, and a common dry-type haplotype is retained among various ethnic populations. These suggest that the allele A arose in northeast Asia and thereafter spread through the world. The 538G --> A SNP is the first example of DNA polymorphism determining a visible genetic trait.     

A nonsynonymous SNP in PRKCH (protein kinase C eta) increases the risk of cerebral infarction

Cerebral infarction is the most common type of stroke and often causes long-term disability. To investigate the genetic contribution to cerebral infarction, we conducted a case-control study using 52,608 gene-based tag SNPs selected from the JSNP database. Here we report that a nonsynonymous SNP in a member of protein kinase C (PKC) family, PRKCH, was significantly associated with lacunar infarction in two independent Japanese samples (P = 5.1 x 10(-7), crude odds ratio of 1.40). This SNP is likely to affect PKC activity. Furthermore, a 14-year follow-up cohort study in Hisayama (Fukuoka, Japan) supported involvement of this SNP in the development of cerebral infarction (P = 0.03, age- and sex-adjusted hazard ratio of 2.83). We also found that PKCeta was expressed mainly in vascular endothelial cells and foamy macrophages in human atherosclerotic lesions, and its expression increased as the lesion type progressed. Our results support a role for PRKCH in the pathogenesis of cerebral infarction.     

Biological and biomedical implications of the co-evolution of pathogens and their hosts

Co-evolution between host and pathogen is, in principle, a powerful determinant of the biology and genetics of infection and disease. Yet co-evolution has proven difficult to demonstrate rigorously in practice, and co-evolutionary thinking is only just beginning to inform medical or veterinary research in any meaningful way, even though it can have a major influence on how genetic variation in biomedically important traits is interpreted. Improving our understanding of the biomedical significance of co-evolution will require changing the way in which we look for it, complementing the phenomenological approach traditionally favored by evolutionary biologists with the exploitation of the extensive data becoming available on the molecular biology and molecular genetics of host-pathogen interactions.     

Global diversity and evidence for coevolution of KIR and HLA

The killer immunoglobulin-like receptor (KIR) gene cluster shows extensive genetic diversity, as do the HLA class I loci, which encode ligands for KIR molecules. We genotyped 1,642 individuals from 30 geographically distinct populations to examine population-level evidence for coevolution of these two functionally related but unlinked gene clusters. We observed strong negative correlations between the presence of activating KIR genes and their corresponding HLA ligand groups across populations, especially KIR3DS1 and its putative HLA-B Bw4-80I ligands (r = -0.66, P = 0.038). In contrast, we observed weak positive relationships between the various inhibitory KIR genes and their ligands. We observed a negative correlation between distance from East Africa and frequency of activating KIR genes and their corresponding ligands, suggesting a balance between selection on HLA and KIR loci. Most KIR-HLA genetic association studies indicate a primary influence of activating KIR-HLA genotypes in disease risk; concomitantly, activating receptor-ligand pairs in this study show the strongest signature of coevolution of these two complex genetic systems as compared with inhibitory receptor-ligand pairs.     

Integrated detection and population-genetic analysis of SNPs and copy number variation

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.     

Variants of ENPP1 are associated with childhood and adult obesity and increase the risk of glucose intolerance and type 2 diabetes

We identified a locus on chromosome 6q16.3-q24.2 (ref. 1) associated with childhood obesity that includes 2.4 Mb common to eight genome scans for type 2 diabetes (T2D) or obesity. Analysis of the gene ENPP1 (also called PC-1), a candidate for insulin resistance, in 6,147 subjects showed association between a three-allele risk haplotype (K121Q, IVS20delT-11 and A-->G+1044TGA; QdelTG) and childhood obesity (odds ratio (OR) = 1.69, P = 0.0006), morbid or moderate obesity in adults (OR = 1.50, P = 0.006 or OR = 1.37, P = 0.02, respectively) and T2D (OR = 1.56, P = 0.00002). The Genotype IBD Sharing Test suggested that this obesity-associated ENPP1 risk haplotype contributes to the observed chromosome 6q linkage with childhood obesity. The haplotype confers a higher risk of glucose intolerance and T2D to obese children and their parents and associates with increased serum levels of soluble ENPP1 protein in children. Expression of a long ENPP1 mRNA isoform, which includes the obesity-associated A-->G+1044TGA SNP, was specific for pancreatic islet beta cells, adipocytes and liver. These findings suggest that several variants of ENPP1 have a primary role in mediating insulin resistance and in the development of both obesity and T2D, suggesting that an underlying molecular mechanism is common to both conditions.