Hiseq x technology

Manufactured by Illumina

Sourced in United States

The HiSeq X technology is a next-generation sequencing (NGS) platform developed by Illumina. It is designed to generate high-quality, high-throughput DNA sequencing data. The core function of the HiSeq X technology is to perform massively parallel DNA sequencing, allowing for the rapid and efficient generation of large amounts of genomic data.

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Lab products found in correlation

Repli g single cell kit, by Qiagen (2 mentions) T4 dna ligase, by Thermo Fisher Scientific (2 mentions) Nexus copy number, by BioDiscovery (1 mentions) Csp6i, by New England Biolabs (1 mentions) Minielute pcr purification kit, by Qiagen (1 mentions) Qiaquick pcr purification kit, by Qiagen (1 mentions) Truseq nano dna kit, by Illumina (1 mentions)

17 protocols using hiseq x technology

Whole-Exome and Whole-Genome Sequencing for CHIP

Cited 6 times

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UK Biobank WES of whole blood–derived DNA was performed using Illumina NovaSeq 6000 platform at the Regeneron Sequencing Center (Tarrytown, NY) as described previously (30 (link)). TOPMed WGS to an average depth of 38× was performed using whole blood–derived DNA, PCR-free library construction, and Illumina HiSeq X technology as described elsewhere (29 (link)).
CHIP mutations were called previously in TOPMed (28 (link)) and UK Biobank (26 (link)). CHIP mutations were reevaluated after the error-corrected release of WES in UK Biobank in June 2020. Briefly, CHIP mutations were detected with GATK MuTect2 software (49 (link)) with parameters as previously described (28 (link)). Samples were annotated as having CHIP if Mutect2 identifies one or more of a prespecified list of pathogenic somatic variants (23 (link), 24 (link)). Common germline variants and sequencing artifacts were excluded as before. Each study includes both the presence of (i) any CHIP and (ii) CHIP with VAF > 0.1, as larger CHIP clones above this threshold have previously been more strongly associated with adverse clinical outcomes (24 (link), 26 (link)).

Nakao T., Bick A.G., Taub M.A., Zekavat S.M., Uddin M.M., Niroula A., Carty C.L., Lane J., Honigberg M.C., Weinstock J.S., Pampana A., Gibson C.J., Griffin G.K., Clarke S.L., Bhattacharya R., Assimes T.L., Emery L.S., Stilp A.M., Wong Q., Broome J., Laurie C.A., Khan A.T., Smith A.V., Blackwell T.W., Codd V., Nelson C.P., Yoneda Z.T., Peralta J.M., Bowden D.W., Irvin M.R., Boorgula M., Zhao W., Yanek L.R., Wiggins K.L., Hixson J.E., Gu C.C., Peloso G.M., Roden D.M., Reupena M.S., Hwu C.M., DeMeo D.L., North K.E., Kelly S., Musani S.K., Bis J.C., Lloyd-Jones D.M., Johnsen J.M., Preuss M., Tracy R.P., Peyser P.A., Qiao D., Desai P., Curran J.E., Freedman B.I., Tiwari H.K., Chavan S., Smith J.A., Smith N.L., Kelly T.N., Hidalgo B., Cupples L.A., Weeks D.E., Hawley N.L., Minster R.L., Deka R., Naseri T.T., de las Fuentes L., Raffield L.M., Morrison A.C., Vries P.S., Ballantyne C.M., Kenny E.E., Rich S.S., Whitsel E.A., Cho M.H., Shoemaker M.B., Pace B.S., Blangero J., Palmer N.D., Mitchell B.D., Shuldiner A.R., Barnes K.C., Redline S., Kardia S.L., Abecasis G.R., Becker L.C., Heckbert S.R., He J., Post W., Arnett D.K., Vasan R.S., Darbar D., Weiss S.T., McGarvey S.T., de Andrade M., Chen Y.D., Kaplan R.C., Meyers D.A., Custer B.S., Correa A., Psaty B.M., Fornage M., Manson J.E., Boerwinkle E., Konkle B.A., Loos R.J., Rotter J.I., Silverman E.K., Kooperberg C., Danesh J., Samani N.J., Jaiswal S., Libby P., Ellinor P.T., Pankratz N., Ebert B.L., Reiner A.P., Mathias R.A., Do R, & Natarajan P. (2022). Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential. Science Advances, 8(14), eabl6579.

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Whole Genome Sequencing and CNV Analysis

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Genomic DNA extracted from blood was used to perform WGS for Patient 1 via the commercial provider Macrogen (South Korea) using Illumina HiSeqX technology. Sequencing was performed to an average sequence depth of 28.5×. The resulting sequence files were aligned to hg38 using Isaac Aligner [20 (link)]. Subsequently, WGS data were analyzed for CNVs using the software Nexus Copy Number (BioDiscovery, El Segundo, CA, USA).

Lu X., Wang R., Li M., Zhang B., Rao H., Huang X., Chen X, & Wu Y. (2024). Identification of two novel large deletions in FBN1 gene by next-generation sequencing and multiplex ligation-dependent probe amplification. BMC Medical Genomics, 17, 47.

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Benchmark Genome Sequencing Data

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Each of the three sequencing centers used the Illumina HiSeq X technology to generate short-read genome sequence data of at least 30X coverage, using DNA from three GIAB reference cell lines (see below). These resulting 27 datasets were then processed through the bioinformatic pipelines in use at each center to create 81 datasets defined by four variables: unique cell line, replicate, sequencing center, and analysis pipeline. Figure 1 provides an overview of the combinatorial study design, which leveraged the benchmark data provided by the GIAB consortium (Zook et al., 2016 (link)). The genome sequence data are submitted to the NCBI SRA database under accession SRP278908.

Corbett R.D., Eveleigh R., Whitney J., Barai N., Bourgey M., Chuah E., Johnson J., Moore R.A., Moradin N., Mungall K.L., Pereira S., Reuter M.S., Thiruvahindrapuram B., Wintle R.F., Ragoussis J., Strug L.J., Herbrick J.A., Aziz N., Jones S.J., Lathrop M., Scherer S.W., Staffa A, & Mungall A.J. (2020). A Distributed Whole Genome Sequencing Benchmark Study. Frontiers in Genetics, 11, 612515.

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Whole-Genome Sequencing of TOPMed Cohorts

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We used the sequencing data available through the NHLBI's Trans‐Omics for Precision Medicine (TOPMed) program (https://nhlbiwgs.org). WGS was performed to an average depth of 38X using DNA isolated from blood, PCR‐free library construction, and Illumina HiSeq X technology. Details for variant calling and quality control are described in detail in Taliun et al. (2021 (link)). In brief, variant discovery and genotype calling was performed jointly across all the available TOPMed studies using the GotCloud 6 pipeline, resulting in a single, multistudy, genotype call set. Sample‐level quality control was performed to check for pedigree errors, discrepancies between self‐reported and genetic sex, and concordance with prior genotyping array data. Among the GeneSTAR samples in TOPMed Freeze 6, 806 EAs in 196 families and 661 AAs in 190 families had complete phenotype data.

Ngwa J.S., Yanek L.R., Kammers K., Kanchan K., Taub M.A., Scharpf R.B., Faraday N., Becker L.C., Mathias R.A, & Ruczinski I. (2022). Secondary analyses for genome‐wide association studies using expression quantitative trait loci. Genetic Epidemiology, 46(3-4), 170-181.

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Genome-wide Chromatin Interaction Mapping

Cited 2 times

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ATAC-seq data was collected from phase 3 ENCODE project [35 (link)]. For 4C-seq, gastric mucosa cells from bariatric surgeries were scraped and enzymatically dissociated. 4C-seq libraries were generated, as previously described [36 (link), 37 (link)], digested with DnpII (New England Biolabs) and Csp6I (New England Biolabs) and re-circularized with T4 DNA Ligase (Thermo Fisher Scientific). 4C-seq libraries were PCR-amplified (supplementary Table 2) and sequenced on Illumina HiSeqX technology.
CDH1 interactions on a genome scale were mapped, based on Pipe4C [37 (link)] and PeakC [38 (link)] with window size 2, alpha fdr 0.1 and minimal distance 500.

São José C., Garcia-Pelaez J., Ferreira M., Arrieta O., André A., Martins N., Solís S., Martínez-Benítez B., Ordóñez-Sánchez M.L., Rodríguez-Torres M., Sommer A.K., te Paske I.B., Caldas C., Tischkowitz M., Tusié M.T., Hoogerbrugge N., Demidov G., de Voer R.M., Laurie S, & Oliveira C. (2023). Combined loss of CDH1 and downstream regulatory sequences drive early-onset diffuse gastric cancer and increase penetrance of hereditary diffuse gastric cancer. Gastric Cancer, 26(5), 653-666.

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Whole Genome Sequencing of TOPMed Cohort

Cited 1 time

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We used the sequencing data available through the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program (https://nhlbiwgs.org). WGS was performed to an average depth of 38X using DNA isolated from blood, PCR-free library construction, and Illumina HiSeq X technology. Details for variant calling and quality control are described in detail in Taliun et al. [29 (link)]. In brief, variant discovery and genotype calling was performed jointly across all the available TOPMed studies using the GotCloud 6 pipeline, resulting in a single, multi-study, genotype call set. Sample-level quality control was performed to check for pedigree errors, discrepancies between self-reported and genetic sex, and concordance with prior genotyping array data. Among the GeneSTAR samples in TOPMed Freeze 6, 806 EAs in 196 families and 661 AAs in 190 families had complete phenotype data.

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Whole Genome Sequencing for COPD Study

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Whole genome sequencing data was generated through the NHLBI TOPMed consortium to a mean depth of 30X using DNA from blood, PCR-free library construction and Illumina HiSeq X technology(28 (link)). For COPDGene, Freeze 5b WGS data was used which includes 8,598 subjects including 5,773 non-Hispanic white (NHW) and 2825 African American (AA). For replication in ECLIPSE, Freeze 8 WGS data was used which included 2345 subjects, and a subset of 2212 were included in this analysis. Reads were mapped to human genome assembly version GRCh38 and computational phasing was performed using Eagle 2.4 (Dec 13, 2017).

Saferali A., Qiao D., Kim W., Raraigh K., Levy H., Diaz A.A., Cutting G.R., Cho M.H, & Hersh C.P. (2022). CFTR variants are associated with chronic bronchitis in smokers. The European respiratory journal, 60(2), 2101994.

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ATAC-seq Profiling of Normal Stomach

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ATAC-seq data from normal stomach tissue were collected from phase 3 ENCODE project [31 (link)]. ATAC-seq libraries were generated from MKN74 cell line and CDH1 deletion clone, as described previously [32 (link)]. A total of 5 × 10⁴ cells were lysed and chromatin was tagmented using Tn5 transposase and purified with MiniElute PCR purification kit (Qiagen), following the manufacturer’s protocol. The appropriate number of PCR cycles was determined using SYBR Green qPCR. Transposed DNA fragments were amplified by PCR and purified using QIAquick PCR purification kit (Qiagen), following the manufacturer’s protocol. Quality control of ATAC-seq libraries was accessed by tapestation, and samples were sequenced in Illumina HiSeqX technology according to standard protocols. ATAC-seq peaks were mapped resourcing to an ENCODE-DCC ATAC-seq bioinformatics pipeline with default parameters for adaptors trimming (cutadapt: -e 0.1 -m 5), alignment (bowtie), quality filtering for mapq < 30, removal of duplicates and mitochondrial reads (piccard), peak calling (macs2), and replicate statistical analysis (idr, p-value < 0.05).

São José C., Pereira C., Ferreira M., André A., Osório H., Gullo I., Carneiro F, & Oliveira C. (2023). 3D Chromatin Architecture Re-Wiring at the CDH3/CDH1 Loci Contributes to E-Cadherin to P-Cadherin Expression Switch in Gastric Cancer. Biology, 12(6), 803.

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Whole Genome Sequencing Protocol

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The extraction of genomic DNA was performed as above and the sequencing library was prepared with the Illumina TruSeq Nano DNA Kit, as per the manufacturer’s instructions with a library size of 350 bp. WGS was performed by Illumina HiSeq X technology at Macrogen (Seoul, South Korea) with a read length of 151 bp. The pair-ended reads passed the quality control check, followed by adapter trimming and quality filtering using Trimmomatic (v0.36) [36 (link)].

Gahamanyi N., Song D.G., Yoon K.Y., Mboera L.E., Matee M.I., Mutangana D., Komba E.V., Pan C.H, & Amachawadi R.G. (2021). Genomic Characterization of Fluoroquinolone-Resistant Thermophilic Campylobacter Strains Isolated from Layer Chicken Feces in Gangneung, South Korea by Whole-Genome Sequencing. Genes, 12(8), 1131.

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WGS Variant Calling and Quality Control

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WGS was performed to an average depth of 38X using DNA isolated from blood, PCR-free library construction, and Illumina HiSeq X technology. Details for variant calling and quality control are described in Taliun et al. ^{47 (link)}. Briefly, variant discovery and genotype calling was performed jointly, across all the available TOPMed Freeze 8 studies, using the GotCloud ^{48 (link)} pipeline resulting in a single multi-study genotype call set.

Taub M.A., Conomos M.P., Keener R., Iyer K.R., Weinstock J.S., Yanek L.R., Lane J., Miller-Fleming T.W., Brody J.A., Raffield L.M., McHugh C.P., Jain D., Gogarten S.M., Laurie C.A., Keramati A., Arvanitis M., Smith A.V., Heavner B., Barwick L., Becker L.C., Bis J.C., Blangero J., Bleecker E.R., Burchard E.G., Celedón J.C., Chang Y.P., Custer B., Darbar D., de las Fuentes L., DeMeo D.L., Freedman B.I., Garrett M.E., Gladwin M.T., Heckbert S.R., Hidalgo B.A., Irvin M.R., Islam T., Johnson W.C., Kaab S., Launer L., Lee J., Liu S., Moscati A., North K.E., Peyser P.A., Rafaels N., Seidman C., Weeks D.E., Wen F., Wheeler M.M., Williams L.K., Yang I.V., Zhao W., Aslibekyan S., Auer P.L., Bowden D.W., Cade B.E., Chen Z., Cho M.H., Cupples L.A., Curran J.E., Daya M., Deka R., Eng C., Fingerlin T.E., Guo X., Hou L., Hwang S.J., Johnsen J.M., Kenny E.E., Levin A.M., Liu C., Minster R.L., Naseri T., Nouraie M., Reupena M.S., Sabino E.C., Smith J.A., Smith N.L., Lasky-Su J., Taylor JG V.I., Telen M.J., Tiwari H.K., Tracy R.P., White M.J., Zhang Y., Wiggins K.L., Weiss S.T., Vasan R.S., Taylor K.D., Sinner M.F., Silverman E.K., Shoemaker M.B., Sheu W.H., Sciurba F., Schwartz D.A., Rotter J.I., Roden D., Redline S., Raby B.A., Psaty B.M., Peralta J.M., Palmer N.D., Nekhai S., Montgomery C.G., Mitchell B.D., Meyers D.A., McGarvey S.T., Mak A.C., Loos R.J., Kumar R., Kooperberg C., Konkle B.A., Kelly S., Kardia S.L., Kaplan R., He J., Gui H., Gilliland F.D., Gelb B.D., Fornage M., Ellinor P.T., de Andrade M., Correa A., Chen Y.D., Boerwinkle E., Barnes K.C., Ashley-Koch A.E., Arnett D.K., Albert C., Laurie C.C., Abecasis G., Nickerson D.A., Wilson J.G., Rich S.S., Levy D., Ruczinski I., Aviv A., Blackwell T.W., Thornton T., O’Connell J., Cox N.J., Perry J.A., Armanios M., Battle A., Pankratz N., Reiner A.P, & Mathias R.A. (2022). Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed. Cell Genomics, 2(1), 100084.

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