Goldengate platform

Manufactured by Illumina

Sourced in United States

The GoldenGate platform is a high-throughput genotyping system designed for the analysis of single nucleotide polymorphisms (SNPs) and other genetic variations. The platform combines array-based technology with a robust assay to deliver accurate and efficient genotyping results.

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Lab products found in correlation

Addiction biology snp array, by Illumina (4 mentions) Genomestudio2011 v1, by Illumina (3 mentions) Robotic automatic liquid dispenser, by Tecan (2 mentions) Beadarray reader scanner, by Illumina (2 mentions) Taqman snp genotyping assay, by Thermo Fisher Scientific (1 mentions) Viia 7 real time pcr system, by Thermo Fisher Scientific (1 mentions) Wizard genomic dna purification kit, by Promega (1 mentions) Qiaamp dna blood midi kit, by Qiagen (1 mentions) Dnaeasy kit, by Qiagen (1 mentions) Genomic dna isolation kit, by Qiagen (1 mentions) Goldengate array, by Illumina (1 mentions) 450k array, by Illumina (1 mentions) Taqman assay, by Thermo Fisher Scientific (1 mentions) Genomestudio software, by Illumina (1 mentions) Automated liquid handling system, by Tecan (1 mentions) Beadarray reader, by Illumina (1 mentions) Infinium humanexome beadchip, by Illumina (1 mentions) Genome wide human snp array 6, by Thermo Fisher Scientific (1 mentions)

37 protocols using goldengate platform

Genotyping of American Commercial Hybrids

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Samples of leaf tissue from each hybrid were sent to the DuPont Pioneer^® Company, where DNA extraction and genotyping was performed. The latter was performed using the Illumina GoldenGate^® Platform (Illumina, San Diego, CA, USA), with an array of 768 SNPs [17 (link)]. The SNP panel was developed by Nelson et al. [18 ] to make inferences about the population structure, origins and relationships between American commercial hybrid parents with Plant Variety Protection Act (PVPA) expired.
The NAM parental lines were genotyped using an array of 1,536 SNP markers on the Illumina GoldenGate^® platform, and the data are available at www.panzea.org. Using the NAM genotype data, only the SNPs shared with the Brazilian commercial germplasms were analyzed.
The SNP genotypic data were converted into numeric digits (“1”, “2” and “3”) by means of the Scrime package [19 ] of the R program [20 ] (Vienna, Austria). Quality control of the genomic data was performed using the parameters of call rate (90%) and minor frequency allele (MAF, 5%) using the HapEstXXR package [21 ] of the R program.

de Andrade L.R., Fritsche Neto R., Granato Í.S., Sant’Ana G.C., Morais P.P, & Borém A. (2016). Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents. PLoS ONE, 11(10), e0163739.

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Genotyping TLR1 Variants from Blood

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In the replication set, DNA was extracted from blood using the QIAamp DNA Blood Midi Kit (Qiagen, Hilden, Germany) and TLR1 variants were genotyped using the GoldenGate platform (Illumina, San Diego, CA, USA). In the validation set, DNA was extracted from blood using the Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA) and rs76600635 was genotyped with a TaqMan SNP genotyping assay (Applied Biosystems, Foster City, CA, USA) on a ViiA7 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA).

Wright S.W., Emond M.J., Lovelace-Macon L., Ducken D., Kashima J., Hantrakun V., Chierakul W., Teparrukkul P., Chantratita N., Limmathurotsakul D, & West T.E. (2019). Exonic sequencing identifies TLR1 genetic variation associated with mortality in Thais with melioidosis. Emerging Microbes & Infections, 8(1), 282-290.

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Genotyping of Enamel Matrix Genes

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Genotyping for a custom panel of single nucleotide polymorphisms (SNPs) was performed by the Center for Inherited Disease Research (CIDR) at Johns-Hopkins University using the Illumina GoldenGate platform (San Diego, USA). Whereas the majority of the panel was chosen to follow-up putative associations from a number of GWAS scans, we also included SNPs such as those in and near enamel matrix genes, based on our interest in strong candidate genes. For this study, we interrogated 18 SNPs distributed across four non-amelogenin enamel matrix genes: AMBN, ENAM, TFIP11, and TUFT1 (see Table 1). These genes were chosen because of their known roles in amelogenesis and implication in Mendelian enamel defects. SNPs in these genes were chosen according to several criteria, including their high minor allele frequencies, ability to capture much of the gene-level variation in as few SNPs as possible, low linkage disequilibrium (i.e., correlation) with each other, as well as genotyping constraints such as compatibility with the GoldenGate platform, and mutual compatibility with other genotyped SNPs on the custom panel. Details regarding the design and quality of the genotyping panel are available elsewhere (Stanley et al. 2014 ).

Shaffer J.R., Carlson J.C., Stanley B.O., Feingold E., Cooper M., Vanyukov M.M., Maher B.S., Slayton R.L., Willing M.C., Reis S.E., McNeil D.W., Crout R.J., Weyant R.J., Levy S.M., Vieira A.R, & Marazita M.L. (2014). Effects of enamel matrix genes on dental caries are moderated by fluoride exposures. Human genetics, 134(2), 159-167.

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Wheat Genotyping and SNP Marker Analysis

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Wheat accessions included in this study were genotyped through the Triticeae Coordinated Agriculture Project (TCAP) using Illumina GoldenGate platform (Illumina Inc., San Diego, CA) at the USDA-ARS genotyping laboratory in Fargo, ND, USA [27 ]. Marker data were coded as x = {-1, 0, 1}, where -1 represents homozygous for the minor allele, 0 represents heterogeneous, and 1 represents homozygous for the major allele. The single nucleotide polymorphism (SNP) markers were filtered by removing SNPs with missing values > 10% and minor allele frequency [MAF] < 5%. The filtration step resulted in 3216 high-quality SNPs, missing values were imputed using random forest regression [28 ], which was applied using the MissForest R/package [29 (link)]. Filtered SNP markers were plotted in Manhattan plots using “wnsp 2013 consensus map”; available on: https://triticeaetoolbox.org/wheat/ [30 (link)].

Elbasyoni I.S., El-Orabey W.M., Morsy S., Baenziger P.S., Al Ajlouni Z, & Dowikat I. (2019). Evaluation of a global spring wheat panel for stripe rust: Resistance loci validation and novel resources identification. PLoS ONE, 14(11), e0222755.

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Illumina GoldenGate Genotyping Protocol

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Genotyping was conducted using the protocol designed by Illumina for the GoldenGate platform (Illumina, Inc., San Diego, CA, USA) using a Tecan robotic automatic liquid dispenser (Tecan, Trading AG, Männedorf Switzerland), which operates under the Illumina protocol. The microarrays were read on the BeadArray Reader scanner (Illumina, Inc., San Diego, CA, USA). Genotype acquisition and generation of documentation (ped and .map files) were conducted using the GenomeStudio2011 v1.0 software (Illumina, Inc., San Diego, CA, USA). Subjects who did not comply with the call rate criteria (>95%) were excluded.

Pavón-Romero G.F., Pérez-Rubio G., Ramírez-Jiménez F., Ambrocio-Ortiz E., Merino-Camacho C.R., Falfán-Valencia R, & Teran L.M. (2020). IL10 rs1800872 Is Associated with Non-Steroidal Anti-Inflammatory Drugs Exacerbated Respiratory Disease in Mexican-Mestizo Patients. Biomolecules, 10(1), 104.

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Genotyping FTO Variants in Obesity

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384 SNPs were genotyped on an Illumina Golden gate platform (Illumina, San Diego, CA). The SNPs included 110 markers used to estimate individual (continental) ancestry. The FTO gene was chosen based on the association between FTO and obesity [7 (link)-9 (link)]. Sixty-eight FTO SNPs were chosen in two ways; as representatives for regions of high linkage disequilibrium (tag SNPs) using the software program TAGGER [28 (link)] and SNPs that were especially interesting due to previous associations or functional effects on gene transcription or performance [7 (link)-9 (link)]. All subsequent genetic analyses were performed using PLINK [29 (link)].

Scheid J.L., Carr K.A., Lin H., Fletcher K.D., Sucheston L., Singh P.K., Salis R., Erbe R., Faith M.S., Allison D.B, & Epstein L.H. (2014). FTO Polymorphisms Moderate the Association of Food Reinforcement with Energy Intake. Physiology & behavior, 132, 51-56.

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Genotyping of GABRA2 SNP rs279858

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DNA was genotyped using the Illumina Addiction biology SNP array using the Illumina GoldenGate platform (Hodgkinson et al., 2008 (link)). GABRA2 SNP rs279858 (exon 5, K132K) was examined given prior work demonstrating associations between the minor allele and problem behavior and maladaptive personality (Trucco et al., 2014 (link); Villafuerte et al., 2013 (link)). All MLS participants (n=1139) were also genotyped for 150 ancestry informative markers (Hodgkinson et al., 2008 (link)), and ethnic factor scores were calculated using principal component analysis in SAS 9.3 as in prior work (Glaser et al., 2014 (link)). The four scores explaining the highest variance (~96%) were examined to control for population stratification.

Trucco E.M., Cope L.M., Burmeister M., Zucker R.A, & Heitzeg M.M. (2018). Pathways to Youth Behavior: The Role of Genetic, Neural, and Behavioral Markers. Journal of research on adolescence : the official journal of the Society for Research on Adolescence, 28(1), 26-39.

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Genetic Risk Score Calculation Protocol

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Genetic information was obtained through a previous initiative. DNA was extracted from venous blood samples using the Qiagen (Germantown, MD) DNAeasy kit, which were then sent to BGI-Shenzhen for processing. Genotype information was obtained using a Goldengate platform (Illumina).
GRS were calculated using the same method as presented by Ananthakrishnan et al. Risk alleles as well as their log odds ratios of association with disease were identified from Jostins et al. Each allele was then assigned a weight, with wild type as 0, heterozygous as 1 and homozygous as 2. The overall GRS was the summation of the weighted contribution of each risk allele calculated as Σ [log(odds ratio) × allele weight (0,1,2)]. Missing data on allele genotype were counted as wild type. Unlike Ananthakrishnan et al., we elected to keep GRS as a continuous variable for our analyses rather than arbitrarily dividing it into quartiles. Our Immunochip covers 151 of the 163 risk alleles described by Jostins et al. (14 (link)). The list of genes and their odds ratios is included in Supplementary Appendix 1a.

Pang J.X., Kheirkhahrahimabadi H., Bindra S., Bindra G., Panaccione R., Eksteen B., Kaplan G.G., Nasser Y., Beck P.L, & Jijon H.B. (2020). Differential Effect of Genetic Burden on Disease Phenotypes in Crohn’s Disease and Ulcerative Colitis in a Canadian Cohort. Journal of the Canadian Association of Gastroenterology, 4(2), 65-72.

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Genotyping Mouse Strains via SNP Analysis

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Genomic DNA was prepared from tail biopsies using a Qiagen Genomic DNA isolation kit following manufacturer's recommendations. SNP analysis was performed using Illumina's Golden Gate platform. There are 22 SNPs that are polymorphic between C57BL/6NTac and C57BL/6J and one specific SNP showing the introduced point mutation in the Tyrosinase gene. (Fig. S1)

Zevnik B., Uyttersprot N.C., Perez A.V., Bothe G.W., Kern H, & Kauselmann G. (2014). C57BL/6N Albino/Agouti Mutant Mice as Embryo Donors for Efficient Germline Transmission of C57BL/6 ES Cells. PLoS ONE, 9(3), e90570.

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Genotyping Malaria Parasite Isolates

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We also examined each parasite isolate genome for their genotypes at the 96 SNPs in a genome-wide panel using the Illumina GoldenGate platform as described (Nkhoma et al., 2013 (link)). These SNPs were gleaned from PlasmoDB version 6.2 (www.plasmodb.org) and were chosen if they were highly polymorphic for parasites from the Thai-Burma border, assayable, not in genes encoding surface proteins (e.g., var, rifin, surfin, stevor), transporters or telomeric genes that may be under strong selection, were distributed across all 14 chromosomes and were found to have MAFs between 0.10 and 0.50. No formal linkage or neutrality analysis was reported in regard to the generation of the SNP barcode. The 96-SNP panel was used to analyse genetic diversity and population structure of asymptomatic and clinical isolates from pregnant women and children younger than 5 years old at the Thai-Burma border (N = 1,731) from 2001 to 2010 (Nkhoma et al., 2013 (link)).

Argyropoulos D.C., Tan M.H., Adobor C., Mensah B., Labbé F., Tiedje K.E., Koram K.A., Ghansah A, & Day K.P. (2023). Performance of SNP barcodes to determine genetic diversity and population structure of Plasmodium falciparum in Africa. Frontiers in Genetics, 14, 1071896.

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