Characterization of single-nucleotide polymorphisms in coding regions of human genes.

A major goal in human genetics is to understand the role of common genetic variants in susceptibility to common diseases. This will require characterizing the nature of gene variation in human populations, assembling an extensive catalogue of single-nucleotide polymorphisms (SNPs) in candidate genes and performing association studies for particular diseases. At present, our knowledge of human gene variation remains rudimentary. Here we describe a systematic survey of SNPs in the coding regions of human genes. We identified SNPs in 106 genes relevant to cardiovascular disease, endocrinology and neuropsychiatry by screening an average of 114 independent alleles using 2 independent screening methods. To ensure high accuracy, all reported SNPs were confirmed by DNA sequencing. We identified 560 SNPs, including 392 coding-region SNPs (cSNPs) divided roughly equally between those causing synonymous and non-synonymous changes. We observed different rates of polymorphism among classes of sites within genes (non-coding, degenerate and non-degenerate) as well as between genes. The cSNPs most likely to influence disease, those that alter the amino acid sequence of the encoded protein, are found at a lower rate and with lower allele frequencies than silent substitutions. This likely reflects selection acting against deleterious alleles during human evolution. The lower allele frequency of missense cSNPs has implications for the compilation of a comprehensive catalogue, as well as for the subsequent application to disease association.     

Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis.

Sequence variation in human genes is largely confined to single-nucleotide polymorphisms (SNPs) and is valuable in tests of association with common diseases and pharmacogenetic traits. We performed a systematic and comprehensive survey of molecular variation to assess the nature, pattern and frequency of SNPs in 75 candidate human genes for blood-pressure homeostasis and hypertension. We assayed 28 Mb (190 kb in 148 alleles) of genomic sequence, comprising the 5' and 3' untranslated regions (UTRs), introns and coding sequence of these genes, for sequence differences in individuals of African and Northern European descent using high-density variant detection arrays (VDAs). We identified 874 candidate human SNPs, of which 22% were confirmed by DNA sequencing to reveal a discordancy rate of 21% for VDA detection. The SNPs detected have an average minor allele frequency of 11%, and 387 are within the coding sequence (cSNPs). Of all cSNPs, 54% lead to a predicted change in the protein sequence, implying a high level of human protein diversity. These protein-altering SNPs are 38% of the total number of such SNPs expected, are more likely to be population-specific and are rarer in the human population, directly demonstrating the effects of natural selection on human genes. Overall, the degree of nucleotide polymorphism across these human genes, and orthologous great ape sequences, is highly variable and is correlated with the effects of functional conservation on gene sequences.     

Exome sequencing identifies ACSF3 as a cause of combined malonic and methylmalonic aciduria

We used exome sequencing to identify the genetic basis of combined malonic and methylmalonic aciduria (CMAMMA). We sequenced the exome of an individual with CMAMMA and followed up with sequencing of eight additional affected individuals (cases). This included one individual who was identified and diagnosed by searching an exome database. We identify mutations in ACSF3, encoding a putative methylmalonyl-CoA and malonyl-CoA synthetase as a cause of CMAMMA. We also examined a canine model of CMAMMA, which showed pathogenic mutations in a predicted ACSF3 ortholog. ACSF3 mutant alleles occur with a minor allele frequency of 0.0058 in ～1,000 control individuals, predicting a CMAMMA population incidence of ～1:30,000. ACSF3 deficiency is the first human disorder identified as caused by mutations in a gene encoding a member of the acyl-CoA synthetase family, a diverse group of evolutionarily conserved proteins, and may emerge as one of the more common human metabolic disorders.     

Single-nucleotide polymorphisms in the public domain: how useful are they?

There is a concerted effort by a number of public and private groups to identify a large set of human single-nucleotide polymorphisms (SNPs). As of March 2001, 2.84 million SNPs have been deposited in the public database, dbSNP, at the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/SNP/). The 2.84 million SNPs can be grouped into 1.65 million non-redundant SNPs. As part of the International SNP Map Working Group, we recently published a high-density SNP map of the human genome consisting of 1.42 million SNPs (ref. 3). In addition, numerous SNPs are maintained in proprietary databases. Our survey of more than 1,200 SNPs indicates that more than 80% of TSC and Washington University candidate SNPs are polymorphic and that approximately 50% of the candidate SNPs from these two sources are common SNPs (with minor allele frequency of > or =20%) in any given population.     

MYH9 is associated with nondiabetic end-stage renal disease in African Americans

As end-stage renal disease (ESRD) has a four times higher incidence in African Americans compared to European Americans, we hypothesized that susceptibility alleles for ESRD have a higher frequency in the West African than the European gene pool. We carried out a genome-wide admixture scan in 1,372 ESRD cases and 806 controls and found a highly significant association between excess African ancestry and nondiabetic ESRD (lod score = 5.70) but not diabetic ESRD (lod = 0.47) on chromosome 22q12. Each copy of the European ancestral allele conferred a relative risk of 0.50 (95% CI = 0.39-0.63) compared to African ancestry. Multiple common SNPs (allele frequencies ranging from 0.2 to 0.6) in the gene encoding nonmuscle myosin heavy chain type II isoform A (MYH9) were associated with two to four times greater risk of nondiabetic ESRD and accounted for a large proportion of the excess risk of ESRD observed in African compared to European Americans.     

Identification of low-frequency variants associated with gout and serum uric acid levels

We tested 16 million SNPs, identified through whole-genome sequencing of 457 Icelanders, for association with gout and serum uric acid levels. Genotypes were imputed into 41,675 chip-genotyped Icelanders and their relatives, for effective sample sizes of 968 individuals with gout and 15,506 individuals for whom serum uric acid measurements were available. We identified a low-frequency missense variant (c.1580C>G) in ALDH16A1 associated with gout (OR = 3.12, P = 1.5 × 10(-16), at-risk allele frequency = 0.019) and serum uric acid levels (effect = 0.36 s.d., P = 4.5 × 10(-21)). We confirmed the association with gout by performing Sanger sequencing on 6,017 Icelanders. The association with gout was stronger in males relative to females. We also found a second variant on chromosome 1 associated with gout (OR = 1.92, P = 0.046, at-risk allele frequency = 0.986) and serum uric acid levels (effect = 0.48 s.d., P = 4.5 × 10(-16)). This variant is close to a common variant previously associated with serum uric acid levels. This work illustrates how whole-genome sequencing data allow the detection of associations between low-frequency variants and complex traits.     

Genome-wide analysis of single-nucleotide polymorphisms in human expressed sequences

Single-nucleotide polymorphisms (SNPs) have been explored as a high-resolution marker set for accelerating the mapping of disease genes. Here we report 48,196 candidate SNPs detected by statistical analysis of human expressed sequence tags (ESTs), associated primarily with coding regions of genes. We used Bayesian inference to weigh evidence for true polymorphism versus sequencing error, misalignment or ambiguity, misclustering or chimaeric EST sequences, assessing data such as raw chromatogram height, sharpness, overlap and spacing, sequencing error rates, context-sensitivity and cDNA library origin. Three separate validations-comparison with 54 genes screened for SNPs independently, verification of HLA-A polymorphisms and restriction fragment length polymorphism (RFLP) testing-verified 70%, 89% and 71% of our predicted SNPs, respectively. Our method detects tenfold more true HLA-A SNPs than previous analyses of the EST data. We found SNPs in a large fraction of known disease genes, including some disease-causing mutations (for example, the HbS sickle-cell mutation). Our comprehensive analysis of human coding region polymorphism provides a public resource for mapping of disease genes (available at http://www.bioinformatics.ucla.edu/snp).     

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.     

Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer

Familial clustering studies indicate that breast cancer risk has a substantial genetic component. To identify new breast cancer risk variants, we genotyped approximately 300,000 SNPs in 1,600 Icelandic individuals with breast cancer and 11,563 controls using the Illumina Hap300 platform. We then tested selected SNPs in five replication sample sets. Overall, we studied 4,554 affected individuals and 17,577 controls. Two SNPs consistently associated with breast cancer: approximately 25% of individuals of European descent are homozygous for allele A of rs13387042 on chromosome 2q35 and have an estimated 1.44-fold greater risk than noncarriers, and for allele T of rs3803662 on 16q12, about 7% are homozygous and have a 1.64-fold greater risk. Risk from both alleles was confined to estrogen receptor-positive tumors. At present, no genes have been identified in the linkage disequilibrium block containing rs13387042. rs3803662 is near the 5' end of TNRC9 , a high mobility group chromatin-associated protein whose expression is implicated in breast cancer metastasis to bone.     

A de novo paradigm for mental retardation

The per-generation mutation rate in humans is high. De novo mutations may compensate for allele loss due to severely reduced fecundity in common neurodevelopmental and psychiatric diseases, explaining a major paradox in evolutionary genetic theory. Here we used a family based exome sequencing approach to test this de novo mutation hypothesis in ten individuals with unexplained mental retardation. We identified and validated unique non-synonymous de novo mutations in nine genes. Six of these, identified in six different individuals, are likely to be pathogenic based on gene function, evolutionary conservation and mutation impact. Our findings provide strong experimental support for a de novo paradigm for mental retardation. Together with de novo copy number variation, de novo point mutations of large effect could explain the majority of all mental retardation cases in the population.     

Screening a large reference sample to identify very low frequency sequence variants: comparisons between two genes

Most human sequence variation is in the form of single-nucleotide polymorphisms (SNPs). It has been proposed that coding-region SNPs (cSNPs) be used for direct association studies to determine the genetic basis of complex traits. The success of such studies depends on the frequency of disease-associated alleles, and their distribution in different ethnic populations. If disease-associated alleles are frequent in most populations, then direct genotyping of candidate variants could show robust associations in manageable study samples. This approach is less feasible if the genetic risk from a given candidate gene is due to many infrequent alleles. Previous studies of several genes demonstrated that most variants are relatively infrequent (<0.05). These surveys genotyped small samples (n<75) and thus had limited ability to identify rare alleles. Here we evaluate the prevalence and distribution of such rare alleles by genotyping an ethnically diverse reference sample that is more than six times larger than those used in previous studies (n=450). We screened for variants in the complete coding sequence and intron-exon junctions of two candidate genes for neuropsychiatric phenotypes: SLC6A4, encoding the serotonin transporter; and SLC18A2, encoding the vesicular monoamine transporter. Both genes have unique roles in neuronal transmission, and variants in either gene might be associated with neurobehavioral phenotypes.     

Genome-wide association studies of 14 agronomic traits in rice landraces

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ～ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ～ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.     

A model-based approach for analysis of spatial structure in genetic data

Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.     

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.     

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%.     

Dichotomy of single-nucleotide polymorphism haplotypes in olfactory receptor genes and pseudogenes

Substantial efforts are focused on identifying single-nucleotide polymorphisms (SNPs) throughout the human genome, particularly in coding regions (cSNPs), for both linkage disequilibrium and association studies. Less attention, however, has been directed to the clarification of evolutionary processes that are responsible for the variability in nucleotide diversity among different regions of the genome. We report here the population sequence diversity of genomic segments within a 450-kb cluster of olfactory receptor (OR) genes on human chromosome 17. We found a dichotomy in the pattern of nucleotide diversity between OR pseudogenes and introns on the one hand and the closely interspersed intact genes on the other. We suggest that weak positive selection is responsible for the observed patterns of genetic variation. This is inferred from a lower ratio of polymorphism to divergence in genes compared with pseudogenes or introns, high non-synonymous substitution rates in OR genes, and a small but significant overall reduction in variability in the entire OR gene cluster compared with other genomic regions. The dichotomy among functionally different segments within a short genomic distance requires high recombination rates within this OR cluster. Our work demonstrates the impact of weak positive selection on human nucleotide diversity, and has implications for the evolution of the olfactory repertoire.     

Many sequence variants affecting diversity of adult human height

Adult human height is one of the classical complex human traits. We searched for sequence variants that affect height by scanning the genomes of 25,174 Icelanders, 2,876 Dutch, 1,770 European Americans and 1,148 African Americans. We then combined these results with previously published results from the Diabetes Genetics Initiative on 3,024 Scandinavians and tested a selected subset of SNPs in 5,517 Danes. We identified 27 regions of the genome with one or more sequence variants showing significant association with height. The estimated effects per allele of these variants ranged between 0.3 and 0.6 cm and, taken together, they explain around 3.7% of the population variation in height. The genes neighboring the identified loci cluster in biological processes related to skeletal development and mitosis. Association to three previously reported loci are replicated in our analyses, and the strongest association was with SNPs in the ZBTB38 gene.     

The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes

Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.     

Mutations in BRIP1 confer high risk of ovarian cancer

Ovarian cancer causes more deaths than any other gynecologic malignancy in developed countries. Sixteen million sequence variants, identified through whole-genome sequencing of 457 Icelanders, were imputed to 41,675 Icelanders genotyped using SNP chips, as well as to their relatives. Sequence variants were tested for association with ovarian cancer (N of affected individuals = 656). We discovered a rare (0.41% allelic frequency) frameshift mutation, c.2040_2041insTT, in the BRIP1 (FANCJ) gene that confers an increase in ovarian cancer risk (odds ratio (OR) = 8.13, P = 2.8 × 10(-14)). The mutation was also associated with increased risk of cancer in general and reduced lifespan by 3.6 years. In a Spanish population, another frameshift mutation in BRIP1, c.1702_1703del, was seen in 2 out of 144 subjects with ovarian cancer and 1 out of 1,780 control subjects (P = 0.016). This allele was also associated with breast cancer (seen in 6/927 cases; P = 0.0079). Ovarian tumors from heterozygous carriers of the Icelandic mutation show loss of the wild-type allele, indicating that BRIP1 behaves like a classical tumor suppressor gene in ovarian cancer.