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Omni5

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The Omni5 is a high-throughput sequencing platform designed for genomic analysis. It offers a robust and efficient solution for generating large amounts of genetic data. The Omni5 is capable of performing a variety of sequencing applications, including whole-genome, exome, and targeted sequencing. The product's core function is to provide researchers and clinicians with a reliable tool for generating comprehensive genomic data to support their research and diagnostic efforts.

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Lab products found in correlation

Omni2, by Illumina (4 mentions) 610 quad, by Illumina (3 mentions) Genomestudio, by Illumina (2 mentions) Cnv370, by Illumina (1 mentions) Human660w quad beadchip, by Illumina (1 mentions) Omniexpress beadchip, by Illumina (1 mentions) Infinium human omni1 quad, by Illumina (1 mentions) Megaex, by Illumina (1 mentions) Humanomni1 quad chip, by Illumina (1 mentions) Humanhap650y v3, by Illumina (1 mentions) Hiseq 2000, by Illumina (1 mentions)

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Human Omni5 (7 citations) Infinium Omni5-4 Kit (3 citations) Omni5 array (2 citations) Omni5 Beadchip array (2 citations)

11 protocols using omni5

1

Genotyping and Haplotype Analysis of TAS2R38 in CF

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All patients underwent genotyping when they enrolled in the Twin-Sibling Study, which was performed in two phases as a part of the International CF Modifier Consortium23 (link). Genotyping was carried out on the Illumina Quad 610 platform for Phase 1 and on the Illumina 660W and Omni5 platforms for Phase 2. MaCH/Minimac software was used for calculating genotypes based on the genotyped data. For calculation, the reference used was Phase I, Version 3 haplotype data from the 1000 Genomes project24 (link), including all reference samples from the 1000 Genomes project.
At the TAS2R38 locus, we identified rs713598, rs1726866, and rs10246939 in codons 49, 262, and 296, respectively. rs713598 was imputed and rs7126866 and rs10246939 were genotyped on all platforms. The imputation quality for rs713598 in Illumina Quad 610, Illumina 660W, and Omni5 platforms were 0.93, 0.90, and 0.93, respectively, demonstrating that the imputation was of high quality. Next, the genotyping was scored based on the negative strand and coded, such that patients with (CC) (CC) (GG) nucleotide pairs at the respective SNP locations were designated homozygous for the functional haplotype (PAV/PAV). Patients with (C-) (C-) (G-) were designated heterozygous for the functional haplotype (PAV/*), and those without this coding were designated homozygous for the non-functional allele.
Dalesio N.M., Aksit M.A., Ahn K., Raraigh K.S., Collaco J.M., McGrath-Morrow S., Zeitlin P.L., An S.S, & Cutting G.R. (2020). Cystic Fibrosis Transmembrane Conductance Regulator function, not TAS2R38 Gene Haplotypes, Predict Sinus Surgery in Children and Young Adults with Cystic Fibrosis. International forum of allergy & rhinology, 10(6), 748-754.
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2

Replicating rs1078761 association with CF lung disease

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To assess replication of the association of rs1078761 with CF lung disease severity, data from a published GWAS for lung disease severity in CF were interrogated [24 (link)]. Briefly, genotyping was performed using the Illumina 660W, Omni5, CNV370 or 610 platforms. Imputation was performed using MaCH/Minimac software and the 1000 Genomes Phase I, Version 3 reference population. Lung disease severity was quantified using the previously described KNoRMA phenotype which represents multiple measurements of CF-specific forced expiratory volume at one second (FEV1) percentiles adjusted for age, sex and mortality [25 (link)].
Saferali A., Tang A.C., Strug L.J., Quon B.S., Zlosnik J., Sandford A.J, & Turvey S.E. (2020). Immunomodulatory function of the cystic fibrosis modifier gene BPIFA1. PLoS ONE, 15(1), e0227067.
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3

Robust Genome-Wide Association Studies

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Samples were genotyped using the Affymetrix 6.0 and Illumina (610 Quad, Human660W-quad Beadchip, Omni5, OmniExpress Beadchip, Oncoarray) platforms. Each of the GWAS was subjected to rigorous standardised quality control independently prior to imputation, which was performed via the Michigan imputation server (https://imputationserver.sph.umich.edu/) based on the Haplotype Reference Consortium (HRC)29 (link). After imputation, each site was filtered to include only imputed variants with information score>0.6 and further quality controls checks were implemented (genotype rate >95%, minor allele frequencies >0.01, and Hardy-Weinberg equilibrium (HWE) >x10−5 in controls). Finally, the data were pooled and final quality control was performed on the pooled GWAS set including checks for missingness, duplicates, sex mismatch, abnormal heterozygosity, cryptic relatedness, population outliers (principal components analyses: Eigenstrat), and genomic inflation (λ > 1.00). Additional information on the MM GWAS studies contributing in the InterLymph consortium are showed in supplementary table 1.
Macauda A., Piredda C., Clay-Gilmour A.I., Sainz J., Buda G., Markiewicz M., Barington T., Ziv E., Hildebrandt M.A., Belachew A.A., Varkonyi J., Prejzner W., Druzd-Sitek A., Spinelli J., Andersen N.F., Hofmann J.N., Dudziński M., Martinez-Lopez J., Iskierka-Jazdzewska E., Milne R.L., Mazur G., Giles G.G., Ebbesen L.H., Rymko M., Jamroziak K., Subocz E., Reis R.M., Garcia-Sanz R., Suska A., Haastrup E.K., Zawirska D., Grzasko N., Vangsted A.J., Dumontet C., Kruszewski M., Dutka M., Camp N.J., Waller R.G., Tomczak W., Pelosini M., Raźny M., Marques H., Abildgaard N., Wątek M., Jurczyszyn A., Brown E.E., Berndt S., Butrym A., Vachon C.M., Norman A.D., Slager S.L., Gemignani F., Canzian F, & Campa D. (2021). Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients. International journal of cancer, 149(2), 327-336.
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4

Genotyping and QC of Saliva DNA

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Genotyping for DNA from saliva was performed using two assays: Illumina Infinium Human Omni1-Quad assay and Infinium Omni5 assay. Both datasets were quality controlled separately (due to different arrays) using PLINK software (http://zzz.bwh.harvard.edu/plink/) as introduced in [14 ], mainly including removal of subjects (missing rate > 10 %) and SNPs (genotyping rate < 90 %, Hardy-Weinberg equilibrium < 10−6 or minor allele frequency (MAF) < 0.01). Missing value imputation was performed using the 1000 Genomes reference panel phase 1, version 3 and the software IMPUTE2 [33 (link)]. Loci with a high imputation quality score (> 0.9) from the two datasets were merged, resulting in 10,513,590 loci. After further quality control (missing rate > 1 %, MAF < 0.05), 3,622,550 loci were left for analysis. We adjusted for the population structure by using the first three principal components (PCs) of the genotype matrix.
Lin D., Chen J., Perrone-Bizzozero N., Bustillo J.R., Du Y., Calhoun V.D, & Liu J. (2018). Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia. Genome Medicine, 10, 13.
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5

Genotyping and Quality Control for CGMS Data

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CGMS data are genotyped on four different Illumina platform: 610Quad, 660W, Omni2.5, and Omni5. Genotype calling was performed using GenomeStudio V2011.1. Quality control steps were performed separately for each platform and described in detail in Gong et al.10 (link) Briefly, PLINK34 (link) was used for most quality control steps, while KING35 (link) identified any cryptic familial relationships among all individuals and PC-AiR36 (link) calculated PCs. Parents in six parent-offspring pairs, 19 samples clustered with Hapmap337 (link) African and East Asian ethnicity, and 10 samples with sex mismatch were excluded. Significant PCs were selected to be included in the association based on the Tracy-Widom test result using the function twtable in POPGEN of Eigensoft.38 (link) For colocalization of meconium ileus association with GTEx eQTLs, GWAS summary statistics10 (link) were reformatted as BED file and lifted to GRCh38 by LiftOver39 for colocalization analysis against GTEx v8 in LocusFocus.40
Mastromatteo S., Chen A., Gong J., Lin F., Thiruvahindrapuram B., Sung W.W., Whitney J., Wang Z., Patel R.V., Keenan K., Halevy A., Panjwani N., Avolio J., Wang C., Côté-Maurais G., Bégin S., Adam D., Brochiero E., Bjornson C., Chilvers M., Price A., Parkins M., van Wylick R., Mateos-Corral D., Hughes D., Smith M.J., Morrison N., Tullis E., Stephenson A.L., Wilcox P., Quon B.S., Leung W.M., Solomon M., Sun L., Ratjen F, & Strug L.J. (2022). High-quality read-based phasing of cystic fibrosis cohort informs genetic understanding of disease modification. Human Genetics and Genomics Advances, 4(1), 100156.
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6

Illumina OMNI Array Genotyping

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Genotyping was performed on the Illumina OMNI-5 and OMNI-2.5 genotyping arrays (Illumina) using Infinium2 chemistry. Genotypes were called using the Gentrain2 algorithm within Illumina Genome Studio.
Kottyan L.C., Davis B.P., Sherrill J.D., Liu K., Rochman M., Kaufman K., Weirauch M.T., Vaughn S., Lazaro S., Rupert A.M., Kohram M., Stucke E.M., Kemme K.A., Magnusen A., He H., Dexheimer P., Chehade M., Wood R.A., Pesek R.D., Vickery B.P., Fleischer D.M., Lindbad R., Sampson H.A., Mukkada V., Putnam P.E., Abonia J.P., Martin L.J., Harley J.B, & Rothenberg M.E. (2014). Genome-wide association analysis of eosinophilic esophagitis provides insight into the tissue specificity of this allergic disease. Nature genetics, 46(8), 895-900.
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7

Illumina Genotyping of EoE-CSC and Controls

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The EoE-CSC was ordered from Illumina and genotyped using Golden Gate Genotyping chemistry. Genotyping for the previous GWAS and external controls was performed as previously described 18 (link) on the Illumina OMNI-5 and OMNI-2.5 genotyping arrays (Illumina) using Infinium2 chemistry. Genotypes were called using the Gentrain2 algorithm within Illumina Genome Studio.
Kottyan L.C., Trimarchi M.P., Lu X., Caldwell J.M., Maddox A., Parameswaran S., Lape M., D’Mello R.J., Bonfield M., Ballaban A., Mukkada V., Putnam P.E., Abonia P., Baruch N.B., Eapen A.A., Wen T., Weirauch M.T, & Rothenberg M.E. (2020). Replication and Meta-Analyses Nominate Numerous Eosinophilic Esophagitis Risk Genes. The Journal of allergy and clinical immunology, 147(1), 255-266.
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8

Genome-wide Genotyping for Mtb Exposure

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Genome-wide genotyping for the Mtb exposure outcome cohort is reported in a GWA study (McHenry et al., 2021 ). Briefly, active cases from the original 2-year study (Stein et al., 2018 (link)) and those with latent Mtb infection and Resisters in the long-term follow up study (Stein et al., 2019 (link)) were typed from a combination of the Illumina MEGAEX and Illumina Omni5 chips. Genome-wide genotyping for our sarcoidosis outcome data is reported in another GWA study (Adrianto et al., 2012 (link)). Genotyping for sarcoidosis cases and healthy controls was performed using the Illumina HumanOmni1-Quad chip (Adrianto et al., 2012 (link)).
Dawkins B.A., Garman L., Cejda N., Pezant N., Rasmussen A., Rybicki B.A., Levin A.M., Benchek P., Seshadri C., Mayanja-Kizza H., Iannuzzi M.C., Stein C.M, & Montgomery C.G. (2022). Novel HLA Associations with Outcomes of Mycobacterium tuberculosis Exposure and Sarcoidosis in Individuals of African Ancestry Using Nearest-neighbor Feature Selection. Genetic epidemiology, 46(7), 463-474.
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9

Illumina OMNI Array Genotyping

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Genotyping was performed on the Illumina OMNI-5 and OMNI-2.5 genotyping arrays (Illumina) using Infinium2 chemistry. Genotypes were called using the Gentrain2 algorithm within Illumina Genome Studio.
Kottyan L.C., Davis B.P., Sherrill J.D., Liu K., Rochman M., Kaufman K., Weirauch M.T., Vaughn S., Lazaro S., Rupert A.M., Kohram M., Stucke E.M., Kemme K.A., Magnusen A., He H., Dexheimer P., Chehade M., Wood R.A., Pesek R.D., Vickery B.P., Fleischer D.M., Lindbad R., Sampson H.A., Mukkada V., Putnam P.E., Abonia J.P., Martin L.J., Harley J.B, & Rothenberg M.E. (2014). Genome-wide association analysis of eosinophilic esophagitis provides insight into the tissue specificity of this allergic disease. Nature genetics, 46(8), 895-900.
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10

Genotyping and Transcriptomic Analysis of DLPFC

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The pre-imputed and quality controlled genotype data and the non-quality controlled human dorsolateral prefrontal cortex expression data of the BSC [Jaffe and others 2018] were provided to us by Dr. Andrew Jaffee. Genotyping of postmortem tissue in this cohort was performed using the Illumina HumanHap650Y_V3, Human 1M-Duo_V3, and Omni5 chips, followed by imputation on the 1,000 Genomes Phase 3 reference set. As with CMC, we removed SNPs with genotyping rate < 0.90, minor allele frequency < 0.05, Hardy-Weinberg P value < 1*10 -6 . The Poly(A)+ RNA sequencing was performed by the BSC investigators using Illumina HiSeq 2000 with two hundred bp paired-end sequencing. Reads were mapped to the human genome hg19 using TopHat 2.0.4.
Peng X., Bader J.S., & Avramopoulos D. (2020). Schizophrenia Risk Alleles Often Affect the Expression of Many Genes and Each Gene May Have a Different Effect on The Risk; A Mediation Analysis.
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