Sequencers

Manufactured by Illumina

Sourced in United States

Illumina sequencers are high-performance instruments designed for DNA and RNA sequencing. They utilize advanced technology to generate large volumes of sequencing data with high accuracy. The core function of Illumina sequencers is to determine the nucleotide sequence of genetic material.

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Lab products found in correlation

2100 bioanalyzer, by Illumina (4 mentions) E gel, by Thermo Fisher Scientific (4 mentions) Agilent sureselect human all exon 50 mb kit, by Agilent Technologies (2 mentions) Chromium single cell 3 reagent kit, by 10x Genomics (2 mentions) Chromium single cell 5 reagent kit, by 10x Genomics (2 mentions) Cell ranger single cell software suite, by 10x Genomics (2 mentions) Nextflex chip seq, by PSC Biotech (2 mentions) Qpcr with kapa library quantification kit, by Roche (2 mentions) Chromium next gem single cell immune profiling 5 v1, by 10x Genomics (2 mentions) Chromium next gem single cell 5 library gel bead kit v1.1 or v2, by 10x Genomics (2 mentions) Chromium single cell 3 library gel bead kit v2, by 10x Genomics (2 mentions) Allprep dna rna micro kit, by Qiagen (1 mentions) Ovation solo rna seq system, by Tecan (1 mentions) Bioruptor, by Diagenode (1 mentions) Ampure xp bead, by Beckman Coulter (1 mentions) Rneasy kit, by Qiagen (1 mentions) Qiaamp dna mini kit, by Qiagen (1 mentions) Miseq sequencing, by Illumina (1 mentions) Cytoscape v, by Cytoscape (1 mentions) Chromium single cell 3 library and gel bead kit v2, by 10x Genomics (1 mentions)

Spelling variants of this product

HiSeq XTen sequencers (28 citations) HiSeq 1500 sequencer (27 citations) HiSeq 2500 DNA sequencer (22 citations) Access Array Barcode Library for Illumina Sequencers (5 citations) HiSeq 2000 or 2500 sequencers (4 citations) HiSeq 2000 and 2500 sequencers (3 citations) NovaSeq 6000 S4 sequencers (2 citations) NEBNext Multiplex Small RNA Library Prep Set for Illumina sequencers (2 citations) NextSeq 500 High Output sequencer (2 citations) HiSeq 4000 sequencer platform (2 citations)

55 protocols using sequencers

RNA-seq Library Preparation and Analysis

Cited 1 time

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Total RNA was isolated from purified cells using an AllPrep DNA/RNA Micro Kit (Qiagen, Hilden, Germany). RNA-seq libraries were prepared from 5 ng RNA per sample using the Ovation SoLo RNA-seq System (NuGEN, Redwood City, CA, USA). cDNA fragments of ∼350 bp were obtained by sonication (Bioruptor, Diagenode, Liège, Belgium), fluorescence-controlled PCR amplification, and size selection using AMPure XP Beads (Beckmann Coulter, Brea, CA, USA). Quality and mean fragment size of library samples were assessed using a Bioanalyzer (2100 Bioanalyzer, Agilent Technologies, Santa Clara, CA, USA), and libraries were sequenced on Illumina sequencers in paired-end mode.
Sequencing data were analysed using the Galaxy platform.²¹ (link) RNA-seq reads were trimmed and mapped to the Mus musculus genome (NCBI37/mm9) using STAR.²² (link) After duplicate removal, transcript abundance was estimated as fragments per kilobase of transcript per million fragments, mapped using Cufflinks.²³ (link)

Simon-Chica A., Fernández M.C., Wülfers E.M., Lother A., Hilgendorf I., Seemann G., Ravens U., Kohl P, & Schneider-Warme F. (2021). Novel insights into the electrophysiology of murine cardiac macrophages: relevance of voltage-gated potassium channels. Cardiovascular Research, 118(3), 798-813.

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Poly-A RNA-seq Library Preparation and Differential Expression Analysis

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Total RNA was isolated from cells or tissue extracts using RNeasy Kit (Qiagen) and 1.5 μg of total RNA was used to prepared Poly-A RNA-seq libraries following Illumina protocols. Samples were sequenced using Illumina Sequencers at the QB3 Vincent J Coates Genomics Sequencing Laboratory, UC Berkeley. Sequenced reads were mapped against RefSeq genes using TopHat (Trapnell et al., 2009 (link)) and differentially expressed genes were determined using Cuffdiff (Trapnell et al., 2010 (link)). Genes expressed more than 1 FPKM and with >twofold difference and p-value < 0.05 as calculated by Cuffdiff were considered as differentially expressed for scatter plots representations and for GO term analysis using DAVID Bioinformatic resources (Huang et al., 2009 (link)).

Herrera F.J., Yamaguchi T., Roelink H, & Tjian R. (2014). Core promoter factor TAF9B regulates neuronal gene expression. eLife, 3, e02559.

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RNA Sequencing Protocol for Differential Gene Expression

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RNA samples were extracted using the Qiagen RNeasy following manufacturer’s instructions. RNA was sent out to a commercial company, Novogene, for library preparation and high-throughput sequencing using Illumina sequencers to generated paired-end results. Raw counts of gene transcripts were obtained using an alignment-independent tool, Salmon (https://combine-lab.github.io/salmon/), using standard settings. The raw count matrix was subsequently imported into R-studio (R version 3.5) and used as input file for DESeq2 analysis (https://bioconductor.org/packages/release/bioc/html/DESeq2.html) with default settings from online software instruction for normalization and differential gene expression analysis. Salmon was used to normalize and quantitate gene expression in transcripts-per-million (tpm) through quasi-alignment. Differentially expressed genes were used as input for principal component analysis (PCA), gene set enrichment analysis (GSEA) (https://www.gsea-msigdb.org/gsea/index.jsp) and motif analysis using HOMER (http://homer.ucsd.edu/homer/ngs/index.html). Detailed Scripts and parameters used for each steps of analysis could be provided by reasonable request to the authors.

Pitarresi J.R., Norgard R.J., Chiarella A.M., Suzuki K., Bakir B., Sahu V., Li J., Zhao J., Marchand B., Wengyn M.D., Hsieh A., Kim I.K., Zhang A., Sellin K., Lee V., Takano S., Miyahara Y., Ohtsuka M., Maitra A., Notta F., Kremer R., Stanger B.Z, & Rustgi A.K. (2021). PTHrP drives pancreatic cancer growth and metastasis and reveals a new therapeutic vulnerability. Cancer discovery, 11(7), 1774-1791.

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Single-cell RNA-seq Library Preparation

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Single-cell libraries were prepared as previously described (Jaitin et al., 2014 (link)). Briefly, mRNA from cells sorted into massively parallel single cell RNA-Seq (MARS-Seq) capture plates was barcoded and converted into cDNA and pooled using an automated pipeline. The pooled sample was then linearly amplified by T7 in-vitro transcription. The resulting RNA was fragmented and converted into a sequencing ready library by tagging the samples with pool barcodes and Illumina adaptor sequences during ligation, followed by reverse transcription and PCR. Each pool of cells was tested for library quality and concentration was assessed as described earlier (Jaitin et al., 2014 (link)). All RNA-seq libraries (pooled at equimolar concentration) were sequenced using Illumina sequencers at an average sequencing depth of ~40,000 reads per cell for RNA-seq. RNA-seq reads were aligned using hisat 0.1.5 and assigned to exons defined by a reference set obtained from the UCSC genome browser. We used statistics on empty-well spurious unique molecular identifier (UMI) detection to ensure that the batches we used for analysis show a low level of cross-single-cell contamination.

Lavin Y., Kobayashi S., Leader A., David Amir E.A., Elefant N., Bigenwald C., Remark R., Sweeney R., Becker C.D., Levine J.H., Meinhof K., Chow A., Kim-Shulze S., Wolf A., Medaglia C., Li H., Rytlewski J.A., Emerson R.O., Solovyov A., Greenbaum B.D., Sanders C., Vignali M., Beasley M.B., Flores R., Gnjatic S., Pe’er D., Rahman A., Amit I, & Merad M. (2017). Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses. Cell, 169(4), 750-765.e17.

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HTS Aptamer Data Bioinformatics Preparation

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The characteristics of the HTS aptamer data (e.g. FASTQ) should be understood prior to bioinformatics analysis. To date, Illumina sequencers are the most common HTS platform for acquired HTS aptamer data. Three criteria should be noted from DNA amplicon molecule (Figure 1) used to attain HTS aptamer data:

Thiel W.H, & Giangrande P.H. (2015). Analyzing HT-SELEX data with the Galaxy Project tools - a web based bioinformatics platform for biomedical research. Methods (San Diego, Calif.), 97, 3-10.

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Illumina Paired-end Sequencing Workflow

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Single-end read describes HTS data attained from one end of the amplicon DNA molecule (Read 1). Single-end reads may start analysis with barcode splitting (Step 2.2). Single-end reads with 100 nucleotide read lengths will be sufficient for most aptamer libraries. Paired-end read refers to sequence attained from both ends of the same amplicon DNA molecule (Read 1 and Read 2). A paired-end read will include the single-end read data (Read 1) along with reads from the opposing end of the amplicon DNA molecule (Read 2). Paired-end reads may be used to extend the total sequence space to read lengths greater than attainable by Illumina sequencers or as additional error proofing. Currently the Galaxy webserver does not have tools to merge or error proof paired end reads with overlapping regions of sequence information.

Thiel W.H, & Giangrande P.H. (2015). Analyzing HT-SELEX data with the Galaxy Project tools - a web based bioinformatics platform for biomedical research. Methods (San Diego, Calif.), 97, 3-10.

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Genetic Characterization of Motor Neuron Diseases

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Samples validated using digital PCR were procured from the Motor Neuron Diseases Research Laboratory (Nemours Alfred I. duPont Hospital for Children) collection and were generated from cell lines as described previously.^{12 (link),30 (link)} Historical patient samples with known SMA or carrier status measured by MLPA were obtained from Cambridge University. GS was performed on 73 samples with digital PCR results, 45 samples with MLPA results, and 12,747 population samples from the 1000 Genomes Project^{29 (link)} (1109 of which have MLPA calls), the National Institute for Health Research (NIHR) BioResource Rare Diseases project and the Next Generation Children (NGC) project.^{31 (link)} The sequencing and processing of this data was done using a variety of sample preparation methods, Illumina sequencers, and read aligners. A full description of this data can be found in the Supplementary Methods.

Chen X., Sanchis-Juan A., French C.E., Connell A.J., Delon I., Kingsbury Z., Chawla A., Halpern A.L., Taft R.J., Bentley D.R., Butchbach M.E., Raymond F.L, & Eberle M.A. (2020). Spinal muscular atrophy diagnosis and carrier screening from genome sequencing data. Genetics in Medicine, 22(5), 945-953.

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Blood RNA Sequencing Protocol

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Peripheral venous or arterial blood samples were collected using customized blood RNA tubes (PAXgene; PreAnalytiX),^{14 (link)} frozen, and then later extracted. The RNA from samples underwent next-generation sequencing using sequencers (Illumina). Details of the sequencing method, quality control, and analysis are provided in the eMethods, eTable 1, and eFigures 1-3 in Supplement 1.

Montaldo P., Burgod C., Herberg J.A., Kaforou M., Cunnington A.J., Mejias A., Cirillo G., Miraglia Del Giudice E., Capristo C., Bandiya P., Kamalaratnam C.N., Chandramohan R., Manerkar S., Rodrigo R., Sumanasena S., Krishnan V., Pant S., Shankaran S, & Thayyil S. (2024). Whole-Blood Gene Expression Profile After Hypoxic-Ischemic Encephalopathy. JAMA Network Open, 7(2), e2354433.

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Genomic DNA extraction and sequencing of Bordetella pertussis

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Heat-killed cells were resuspended in 1 ml PBS and OD₆₀₀ was measured. Volumes of suspension equating 1 ml at an OD₆₀₀ of 2.0 (~4×10⁹B. pertussis cells) were pelleted in a microcentrifuge for 2 min at 12 000 g. gDNA was extracted from each pellet using the QIAamp DNA mini kit (Qiagen) according to the manufacturer’s instructions, including a single-step elution into 200 µl of elution buffer (buffer AE).
gDNA from 34 isolates was sent for Illumina MiSeq sequencing at the Milner Centre, University of Bath. gDNA from the remaining 32 isolates was sent to Novogene for Illumina NovaSeq sequencing. gDNA from three isolates was lost during shipping, hence 63 isolates were sequenced with Illumina sequencers.

Ring N., Davies H., Morgan J., Sundaresan M., Tiong A., Preston A, & Bagby S. (2022). Comparative genomics of Bordetella pertussis isolates from New Zealand, a country with an uncommonly high incidence of whooping cough. Microbial Genomics, 8(1), 000756.

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10x Genomics Chromium v3 Nuclei Capture

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Nuclei were captured and barcoded using 10x Genomics Chromium v3 according to the manufacturer’s protocol. Samples were processed and libraries were prepared by The Rockefeller Genomics Core. Sequencing was performed by Genewiz using Illumina sequencers.

Ilanges A., Shiao R., Shaked J., Luo J.D., Yu X, & Friedman J.M. (2022). Brainstem ADCYAP1+ neurons control multiple aspects of sickness behaviour. Nature, 609(7928), 761-771.

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