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Human670 quadcustom beadchip

Manufactured by Illumina
Sourced in United Kingdom, United States

The Human670-QuadCustom Illumina BeadChip is a high-throughput genotyping array designed to analyze genetic variations across the human genome. It provides comprehensive coverage of common and rare genetic variants, enabling researchers to investigate genetic associations with various traits and diseases.

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6 protocols using human670 quadcustom beadchip

1

Genotype Imputation and Quality Control

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Genotyping was performed with the Human670‐QuadCustom Illumina BeadChip (Illumina, Inc., San Diego, CA, USA) (batch1) at the Wellcome Trust Sanger Institute, and with the Illumina Human Core Exome BeadChip (Illumina) (batch2) at the Wellcome Trust Sanger Institute and at the Broad Institute of MIT and Harvard (batch3). Genotype quality control thresholds have been previously described (He et al. 2016) and listed in Supporting Information Table S1. Pre‐phasing of the data was done with SHAPEIT2 (Delaneau et al. 2013). The pre‐phased genotype data were imputed with IMPUTE version 2.3.1 (Howie et al. 2009) using a combined reference panel consisting of 1000 Genomes Phase I (haplotype released in September 2013) and 1941 Finnish low‐pass whole genome sequences from the SISu project. The two panels consist of 37 878 799 and 13 625 209 variants, respectively. Following post‐imputation, exclusion criteria were applied for SNPs: effect allele frequency <0.01 and >0.99, SNP call rate < 0.95, HWE P < 1.0 × 10−6, and imputation info <0.8. For batches 1, 2 and 3, the number of variants that passed the quality control procedure was 521 529, 342 853 and 322 926, respectively. Quality controls and imputation for the GWAS data were done centrally at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
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2

High-throughput Genotyping of Genetic Variants

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For the London cohorts, DNA from participants was extracted from whole blood using the salting-out method (Miller et al., 1988 (link)) and normalized to 5 ng/µL. 10 ng DNA was used as template for 2 µL TaqMan assays (Applied Biosystems, Foster City, CA, USA) performed on the ABI 7900HT platform in 384-well format and analysed with Autocaller software. Pre-developed assays were used to type all SNPs. See Supplementary file 1 Table 4 for primer and reporter sequences. Typing for two SNP (rs6127118 and rs11574010) failed. For the Finnish cohort, DNA was extracted from whole blood and genotyping was performed at the Wellcome Trust Sanger Institute (Hinxton, UK) on the Human670-QuadCustom Illumina BeadChip (Illumina, Inc, San Diego, CA, USA), as previously described (Loukola et al., 2014 (link); Loukola et al., 2008 (link); Broms et al., 2012 (link)). Genotyping and imputation for the Finnish cohort at the Wellcome Trust Sanger Centre have been described previously (Loukola et al., 2015 (link)).
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3

Genotyping and Quality Control of NAG-FIN Sample

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Genotyping for the NAG-FIN sample was performed with the Human670-QuadCustom Illumina BeadChip (Illumina, San Diego, CA, USA) (N=1097) at the Wellcome Trust Sanger Institute, UK, and with the Illumina Human Core Exome BeadChip (N=901) at the Wellcome Trust Sanger Institute, and at the Broad Institute of MIT and Harvard, USA. Quality controls (QC) for the genotype data have been previously described21 (link) and are also presented in Supplementary Table 1. Pre-phasing of the data was done with SHAPEIT222 (link) and imputation with IMPUTE223 (link) using the 1000 Genomes Phase I integrated haplotypes reference panel.24 (link) For analyses of the 10 NSP genes (NRG1, NRG3, ERBB4, BACE1, PSEN1, PSEN2, APH1A, APH1B, PSENEN and NCSTN), we extracted SNPs within the gene regions (according to the longest isoform reported at the UCSC Genome browser) with 50 kb flanking regions. Gene boundaries (according to GRCh37/hg19) are listed in Supplementary Table 1, along with the number of SNPs included for each gene. Only variants with minor allele frequency (MAF) <0.01 located in coding regions, splice sites, promoters or untranslated regions (UTRs) were included in the rare variant analysis. Altogether, 15 036 SNPs were analyzed in our discovery phase.
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4

Genotyping Dopamine Receptor Genes in Cohorts

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DNA was extracted from blood samples by standard methods. Altogether 303 individuals were genotyped for 76 SNPs in all known dopamine receptor genes (DRD1-5) using Sequenom’s homogeneous hME and iPLEX Gold technology (Sequenom, San Diego, CA, USA), as previously described [4] (link). For 1125 individuals, genotypes were derived from GWA data. Of the 76 SNPs genotyped with Sequenom, 70 were available in the GWA data (21 DRD1 SNPs, 30 DRD2/ANKK1 SNPs, 15 DRD3 SNPs, two DRD4 SNPs, and two DRD5 SNPs). All analyses in this paper are based on these 70 SNPs. Genotyping was performed at the Welcome Trust Sanger Institute (Hinxton, UK) on the Human670-QuadCustom Illumina BeadChip (Illumina, Inc., San Diego, CA, USA), as previously described [4] (link). Altogether 29 markers were genotyped, 41 being imputed using IMPUTE v2.1.0 [24] (link) using HapMap rel#24 CEU - NCBI Build 36 (dbSNP b126) as reference panel. The reference panel used in the imputation was HapMap rel#24 CEU - NCBI Build 36 (dbSNP b126). The posterior probability threshold for "best-guess" imputed genotype was 0.9: genotypes below the threshold were set to missing. Marker quality controls are presented in Table S2 in File S1.
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5

Genotyping and Imputation Protocol

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Genotyping was performed at the Wellcome Trust Sanger Institute using the Human670‐QuadCustom Illumina BeadChip (N = 1104) and the Illumina Human Core Exome BeadChip (N = 858). Pre‐imputation exclusion criteria for the data generated with the Human670‐QuadCustom Illumina BeadChip were minor allele frequency (MAF) < 0.01, sample and SNP call rate <0.95 (<0.99 for SNPs with MAF < 0.05); and the criteria for the data generated with the Illumina Human Core Exome BeadChip were minor allele count <2, sample call rate <0.98, SNP call rate <0.95 (<0.99 for SNPs with MAF < 0.05). Both genotype datasets were filtered according to the Hardy–Weinberg equilibrium (HWE) test P < 1e‐06. Further, sample heterozygosity test, gender, and Multidimensional Scaling (MDS) outlier checks were done for both. Pre‐phasing of the data was done with SHAPEIT2 (Delaneau et al. 2013) and imputation with IMPUTE2 (Howie et al. 2009) using the 1000 Genomes Phase I integrated haplotypes (produced using SHAPEIT2) reference panel (1000 Genomes Project Consortium, 2012). Quality controls and imputation for the GWAS data were done centrally at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
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6

Genome-wide Genotyping and Imputation

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Genome-wide data were collected using blood samples obtained at the age 22 assessment. Genotyping was performed at the Welcome Trust Sanger Institute (Hinxton, UK) on the Human670-QuadCustom Illumina BeadChip (Illumina, Inc., San Diego, CA, USA), as previously described in Broms et al. (2012) (link). The data were checked for MAF >1%, genotyping success rate per SNP and per individual (> 95%; >99% for SNPs with MAF<5%), Hardy-Weinberg Equilibrium (HWE p > 1 × 10−6), sex, and heterozygosity. In addition, to check whether any individuals were unexpectedly related to each other, a multidimensional scaling plot (using a pairwise-IBS matrix) with only one member of each known family was created. After the pedigree was checked for accuracy, the basic filters (MAF, genotyping success, HWE) were reapplied to the data. The GABRA2 SNP rs279871 was not initially genotyped on this array, and was imputed using ShapeIT (Delaneau, Marchini, & Zagury, 2012 (link)) in pre-phasing and IMPUTE2 (Howie, Donnelly, & Marchini, 2009 (link)) for genotype imputation. The posterior probability threshold for “best-guess” imputed genotype was 0.9. Genotypic information for this SNP was available for 100% of the sample2. Imputation was done on the plus strand, and the MAF for the C allele (which corresponds to the G allele in CDP, due to strand differences in genotyping and imputation) was 0.41.
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