Evaluating the performance of commercial whole-genome marker sets for capturing common genetic variation

<p>Abstract</p> <p>Background</p> <p>New technologies have enabled genome-wide association studies to be conducted with hundreds of thousands of genotyped SNPs. Several different first-generation genome-wide panels of SNPs have been commercialized. The total amount of common genetic variation is still unknown; however, the coverage of commercial panels can be evaluated against reference population samples genotyped by the International HapMap project. Less information is available about coverage in samples from other populations.</p> <p>Results</p> <p>In this study we compare four commercial panels: the HumanHap 300 and HumanHap 550 Array Sets from the Illumina Infinium series and the Mapping 100 K and Mapping 500 K Array Sets from the Affymetrix GeneChip series. Tagging performance is compared among HapMap CEPH (CEU), Asian (JPT, CHB) and Yoruba (YRI) population samples. It is also evaluated in an Estonian population sample with more than 1000 individuals genotyped in two 500-kbp ENCODE regions of chromosome 2: ENr112 on 2p16.3 and ENr131 on 2p37.1.</p> <p>Conclusion</p> <p>We found that in a non-reference Caucasian population, commercial SNP panels provide levels of coverage similar to those in the HapMap CEPH population sample. We present the proportions of universal and population-specific SNPs in all the commercial platforms studied.</p

An Evaluation of the Performance of Tag SNPs Derived from HapMap in a Caucasian Population

The Haplotype Map (HapMap) project recently generated genotype data for more than 1 million single-nucleotide polymorphisms (SNPs) in four population samples. The main application of the data is in the selection of tag single-nucleotide polymorphisms (tSNPs) to use in association studies. The usefulness of this selection process needs to be verified in populations outside those used for the HapMap project. In addition, it is not known how well the data represent the general population, as only 90–120 chromosomes were used for each population and since the genotyped SNPs were selected so as to have high frequencies. In this study, we analyzed more than 1,000 individuals from Estonia. The population of this northern European country has been influenced by many different waves of migrations from Europe and Russia. We genotyped 1,536 randomly selected SNPs from two 500-kbp ENCODE regions on Chromosome 2. We observed that the tSNPs selected from the CEPH (Centre d'Etude du Polymorphisme Humain) from Utah (CEU) HapMap samples (derived from US residents with northern and western European ancestry) captured most of the variation in the Estonia sample. (Between 90% and 95% of the SNPs with a minor allele frequency of more than 5% have an r (2) of at least 0.8 with one of the CEU tSNPs.) Using the reverse approach, tags selected from the Estonia sample could almost equally well describe the CEU sample. Finally, we observed that the sample size, the allelic frequency, and the SNP density in the dataset used to select the tags each have important effects on the tagging performance. Overall, our study supports the use of HapMap data in other Caucasian populations, but the SNP density and the bias towards high-frequency SNPs have to be taken into account when designing association studies

Haplotype Phasing and Inheritance of Copy Number Variants in Nuclear Families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.Peer reviewe

Kuulmislanguse geneetilised põhjused Eesti lastel ning leitud genotüübi ja fenotüübi omavaheline võrdlus

Eesmärk. Selgitada välja kuulmislanguse (KL) geneetilised põhjused Eesti lastel ja kirjeldada nende fenotüüpi. Metoodika. Uuringus osales 233 KLiga last, kellele tehti APEX-geenikiibi analüüs 201 erineva mutatsiooni suhtes 8 pärilikku KLi põhjustavas geenis (GJB2, GJB3, GJB6, GJA1, SLC26A4, SLC26A5, 12S-rRNA ja tRNA (Ser) geenid). Tulemused. Leidsime 115 patsiendil (49%) GJB2 mutatsiooni vähemalt ühes alleelis, neist 100 lapsel esines vähemalt ühes alleelis mutatsioon c.35delG. 5 patsiendi (2%) KL oli tingitud kaasasündinud tsütomegalovi irusinfektsioonist. Sündroomne KL kinnitati 7 uuritaval. Kogu genoomi genotüpiseerimisplatformi analüüs tehti 28 patsiendile, selle tulemusel leidsime 4 erinevat potentsiaalselt patogeenset deleteerunud kromosoomipiirkonda. Järeldused. Kõige sagedasem lapseea KLi põhjustav mutatsioon on c.35delG, mille osakaal KLiga laste hulgas on 75% GJB2 geeni mutatsioonidest. Uuringu tulemusena selgus või täpsustus KLi etioloogias geneetiline faktor 140 patsiendil (60%). Eesti Arst 2010; 89(12):781−78

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

A Genome-Wide Analysis of Populations from European Russia Reveals a New Pole of Genetic Diversity in Northern Europe

Peer reviewe

Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets

Circulating proteins have important functions in inflammation and a broad range of diseases. To identify genetic influences on inflammation-related proteins, we conducted a genome-wide protein quantitative trait locus (pQTL) study of 91 plasma proteins measured using the Olink Target platform in 14,824 participants. We identified 180 pQTLs (59 cis, 121 trans). Integration of pQTL data with eQTL and disease genome-wide association studies provided insight into pathogenesis, implicating lymphotoxin-alpha in multiple sclerosis. Using Mendelian randomization (MR) to assess causality in disease etiology, we identified both shared and distinct effects of specific proteins across immune-mediated diseases, including directionally discordant effects of CD40 on risk of rheumatoid arthritis versus multiple sclerosis and inflammatory bowel disease. MR implicated CXCL5 in the etiology of ulcerative colitis (UC) and we show elevated gut CXCL5 transcript expression in patients with UC. These results identify targets of existing drugs and provide a powerful resource to facilitate future drug target prioritization. Here the authors identify genetic effectors of the level of inflammation-related plasma proteins and use Mendelian randomization to identify proteins that contribute to immune-mediated disease risk

Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10−8) near FTO (P = 3.72 × 10−23), TMEM18 (P = 3.24 × 10−17), MC4R (P = 4.41 × 10−17), TNNI3K (P = 4.32 × 10−11), SEC16B (P = 6.24 × 10−9), GNPDA2 (P = 1.11 × 10−8) and POMC (P = 4.94 × 10−8) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10−5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different age

Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21-6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10−16), 6p21 (P = 2.3 × 10−14) and 15q25 (P = 2.2 × 10−63). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16INK4A/p14ARF/CDKN2B/p15INK4B/ANRIL; rs1333040, P = 3.0 × 10−7) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10−8). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cance

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss