Veracode goldengate assay

Manufactured by Illumina

Sourced in United States

The VeraCode GoldenGate assay is a high-throughput genotyping technology developed by Illumina. It enables the simultaneous analysis of multiple genetic markers across large sample sizes. The assay utilizes bead-based technology and advanced imaging to deliver accurate and reliable genotyping results.

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Lab products found in correlation

Beadxpress reader, by Illumina (3 mentions) Qiaamp dna extraction kit, by Qiagen (1 mentions) Beadxpress platform, by Illumina (1 mentions) Flexigene, by Qiagen (1 mentions) Genomestudio v2011, by Illumina (1 mentions) Quickgene 810 nucleic acid isolation system, by Fujifilm (1 mentions) Quickgene dna whole blood kit, by Fujifilm (1 mentions)

7 protocols using veracode goldengate assay

Genetic Markers for Cardiometabolic Traits

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We selected 96 previously identified GWAS/literature reported risk SNPs for cardio-metabolic traits (Kathiresan et al., 2008 (link); Kooner et al., 2011 (link); Willer et al., 2008 (link))(http://www.genome.gov/gwastudies) as described in detail in our ongoing unpublished work (Farook et al.) for this study. Genomic DNA was extracted from blood samples collected from the MA children who participated in the SAFARI study, using Qiagens’s QIAmp DNA 96 BLOOD KIT or QIAmp DNA BLOOD MINIKIT according to the manufacturer’s protocol. Genotyping of the 96 SNPs was done using the Illumina’s Goldengate Veracode Assay per the manufacturer’s protocol (Illumina, San Diego, CA; www.illumina.org).

Arya R., Farook V.S., Fowler S.P., Puppala S., Chittoor G., Resendez R.G., Mummidi S., Vanamala J., Almasy L., Curran J.E., Comuzzie A.G., Lehman D.M., Jenkinson C.P., Lynch J.L., DeFronzo R.A., Blangero J., Hale D.E., Duggirala R, & Diego V.P. (2018). Genetic and Environmental (Physical Fitness and Sedentary Activity) Interaction Effects on Cardiometabolic Risk Factors in Mexican American Children and Adolescents. Genetic epidemiology, 42(4), 378-393.

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Genetic Profiling of Sporadic BAVM

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SNPs selected for replication were genotyped at the UCSF GCF using
the Illumina Golden Gate Veracode assay and the Assay Design Tool (ADT)
(https://my.illumina.com/custom/UploadVeraCodePrelim). SNPs
with designability scores <0.6 were replaced with the next most
significantly associated SNP in the same LD block if one with a higher
designability score (≥0.6) was available.
A total of 61 SNPs were selected for genotyping in the replication
cohort using the following criteria: (1) 22 SNPs with
P<10⁻⁰⁵ in meta-analysis of discovery
cohorts; (2) 30 SNPs with P<10⁻⁰⁴ in
meta-analysis and in 752 genes from eight candidate pathways related to BAVM
biology (transforming growth factor (TGF)-beta signaling, notch, vascular
endothelial growth factor (VEGF), inflammation, mitogen-activated protein
kinase (MAPK), vascular endothelial growth, vascular development, hedgehog);
(3) 3 SNPs with P<10⁻⁰⁵ in Phase 1 but not
passing imputation QC in Phase 2; and (d) 6 candidate SNPs reportedly
associated with sporadic BAVM (rs522616, rs2071219, rs1333040, rs10486391,
rs1800587, rs1143627).[10 (link)–15 (link)] Of these,
57 SNPs were successfully genotyped in the replication cohort (call rate
>96.9%). Samples with >10% missing genotypes
were excluded, resulting in 608 cases and 744 controls.

Weinsheimer S., Bendjilali N., Nelson J., Guo D.E., Zaroff J.G., Sidney S., McCulloch C.E., Salman R.A., Berg J.N., Koeleman B.P., Simon M., Boström A., Fontanella M., Sturiale C.L., Pola R., Puca A., Lawton M.T., Young W.L., Pawlikowska L., Klijn C.J, & Kim H. (2016). Genome-wide association study of sporadic brain arteriovenous malformations. Journal of neurology, neurosurgery, and psychiatry, 87(9), 916-923.

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Genome-Wide Association Study of Prostate Cancer

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About 80 SNPs reached genome-wide significance in association with the risk of PCa in GWAS published (15 (link)-28 (link)) (http://www.genome.gov/gwastudies/). These SNPs were selected for the design of a GoldenGate VeraCode assay (Illumina). After score-based selection, 72 SNPs were retained for genotyping. All DNA samples were extracted from peripheral whole blood by using QIAamp DNA extraction kit (QIAGEN). Genotyping assay was then run on the Illumina BeadXpress Reader. Genotyping data were analyzed and exported using BeadStudio software. The genotyping call rate for the SNPs in this study was 99.86%.

He Y., Gu J., Strom S., Logothetis C.J., Kim J, & Wu X. (2014). The Prostate Cancer Susceptibility Variant rs2735839 Near KLK3 Gene Is Associated with Aggressive Prostate Cancer and Can Stratify Gleason Score 7 Patients. Clinical cancer research : an official journal of the American Association for Cancer Research, 20(19), 5133-5139.

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Genetic Analyses of Coagulation Factors

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For details on the genetic analyses, please refer to Cronjé, Nienaber-Rousseau (39 (link)). In short, genomic DNA was isolated from buffy coat using the FlexiGene™ kits (QIAGEN Inc., Valencia, CA, USA). SNPs selected from the literature [FGB-rs7439150, rs1800789 (1420G/A), rs1800791 (−854G/A), rs1800790 (−455G/A), rs1800788 (249C/T), rs1800787 (−148C/T), rs4220, rs4463047, FGA-rs6050, rs2070011 (2224G/A), and FGG rs2066865 and rs1049636 (9340T/C) as well as FXIII His95Arg A/G (rs6003) and Val34Leu, C/A (rs5985)], and two novel FGB SNPs in the promoter region (rs2227385 and rs2227388) identified via sequencing a subpopulation were genotyped. The Thermo Fischer Scientific® Taqman based assay, Illumina® VeraCode GoldenGate assay technology using a BeadXpress® platform and competitive allele-specific polymerase chain reactions (KASP) were used for genotyping.

Rautenbach P.H., Nienaber-Rousseau C., de Lange-Loots Z., Kruger I.M, & Pieters M. (2022). Associations Between 25-Hydroxyvitamin D and Total and γ' Fibrinogen and Plasma Clot Properties and Gene Interactions in a Group of Healthy Black South African Women. Frontiers in Cardiovascular Medicine, 9, 868542.

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Genotyping Domestic and Przewalski Horses

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A VeraCode GoldenGate assay (Illumina) was designed targeting 384 SNPs that were called in the resequencing samples. A total of 200 domestic horses, one Przewalski’s horse and five other equids were genotyped using the standard protocol. The GoldenGate assays were read using a BeadXpress Reader (Illumina), and data were analyzed on GenomeStudio v2011.1 software (Illumina). SNPs located outside the non-dun2 deletion with a call rate of less than 80% (17 SNPs) or invariable in typed individuals (one SNP) were excluded from the analysis. The three SNPs within the deleted region had a call rate of 67–68%, consistent with one-third of the samples being homozygous for the non-dun2 deletion. All samples used had call rates of no less than 97% (domestic horses) or 90% (other equids).

Imsland F., McGowan K., Rubin C.J., Henegar C., Sundström E., Berglund J., Schwochow D., Gustafson U., Imsland P., Lindblad-Toh K., Lindgren G., Mikko S., Millon L., Wade C., Schubert M., Orlando L., Penedo M.C., Barsh G.S, & Andersson L. (2015). Regulatory mutations in TBX3 disrupt asymmetric hair pigmentation that underlies Dun camouflage color in horses. Nature genetics, 48(2), 152-158.

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Ancestry Informative Marker Genotyping in BioVU

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All 7,252 BioVU samples were genotyped using the Illumina VeraCode GoldenGate assay in the Center for Human Genetics Research (CHGR) DNA Resources Core at Vanderbilt University for 308 ancestry informative markers (AIMs) and scanned on the Illumina BeadXpress reader. AIMs genotypes were merged with existing data for 805 individuals from the International HapMap Project (Phase 3, Revision3, Build 36), including 165 CEU, 203 YRI, 137 CHB, 113 JPT, 101 GIH samples, and 86 MXL, as reference populations to assist in determining genetic ancestry (Table S1). The genetic data underwent quality control measures, including removal of 39 non-autosomal SNPs, 38 SNPs not also in the HapMap dataset, and 11 SNPs that were co-linear with principal component (PC) three and caused atypical clustering, leaving 220 SNPs for analysis (SNP list available upon request). Within the final merged dataset of 220 SNPs for 8,057 individuals, all SNPs had a minor allele frequency (MAF) greater than five percent. Of the BioVU samples in our dataset, 52% (4,192) were female.

Hall J.B., Dumitrescu L., Dilks H.H., Crawford D.C, & Bush W.S. (2014). Accuracy of Administratively-Assigned Ancestry for Diverse Populations in an Electronic Medical Record-Linked Biobank. PLoS ONE, 9(6), e99161.

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Genotyping of PON1 Gene Polymorphisms

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The candidate SNPs (single nucleotide polymorphisms) were selected from 3 public databases: the International HapMap Project database (http://hapmap.ncbi.nlm.nih.gov/), the Functional Element SNPs database (http://sysbio.kribb.re.kr:8080/fesd/index.jsp) [23 (link)], and the SNPinfo Web Server (http://snpinfo.niehs.nih.gov/). The selection criteria were as follows: (i) haplotype-tagging SNPs with an R-square cutoff of 0.9 and minimum minor allele frequency in CHB and JPT population of 0.05; (ii) SNPs located in functional regions, such as the promoter, start codon, splice site, coding exon, and stop codon; and (iii) non-synonymous SNPs. Finally, we selected seven SNPs (rs662, rs13306698, rs854572, rs854573, rs854552, rs854565, and rs854568) in the PON1 gene for genotyping.
Genomic DNA was isolated from peripheral blood using the QuickGene-810 Nucleic Acid Isolation System (Fujifilm, Tokyo, Japan) and the QuickGene DNA Whole Blood Kit in accordance with the manufacturer’s protocol; the DNA samples were stored at-70°C until analysis. SNP genotyping was performed using the VeraCode GoldenGate assay (Illumina, San Diego, CA, USA). All SNPs were in Hardy-Weinberg equilibrium in cases and controls, and the call rate for the seven SNPs was 100%. S1 Table presents detailed information on the seven SNPs and allele frequencies.

Eom S.Y., Yim D.H., Lee C.H., Choe K.H., An J.Y., Lee K.Y., Kim Y.D, & Kim H. (2015). Interactions between Paraoxonase 1 Genetic Polymorphisms and Smoking and Their Effects on Oxidative Stress and Lung Cancer Risk in a Korean Population. PLoS ONE, 10(3), e0119100.

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