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Mrna truseq kit

Manufactured by Illumina
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The Illumina mRNA TruSeq kit is a lab equipment product designed for the preparation and sequencing of mRNA samples. The kit provides a streamlined workflow for isolating, fragmenting, and converting mRNA into a format suitable for sequencing on Illumina platforms.

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Lab products found in correlation

Hiseq 5000 platform, by Illumina (2 mentions) Bioanalyzer, by Agilent Technologies (2 mentions) Hiseq 4000, by Illumina (2 mentions) Hiseq 2000, by Illumina (1 mentions) Rnaeasy kit, by Qiagen (1 mentions) Agilent bioanalyzer, by Agilent Technologies (1 mentions)

Close spelling variants of this product

Illumina stranded TruSeq mRNA kits TruSeq strand mRNA Library Preparation Kit TruSeq standard mRNA library kit TruSeq Standard mRNA library preparation kit TruSeq standard mRNA preparation kit TruSeq mRNA-Seq library preparation kit TruSeq mRNA prep kit TruSeq stranded mRNA (HT) library preparation kit TruSeq mRNA Stranded reagent kit TruSeq mRNA-Seq library kit

7 protocols using mrna truseq kit

1

Transcriptome Profiling of BEAS-2B Cells

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RNA was isolated from variant, wild-type, or vector expressing BEAS-2B cells and quantified. mRNA libraries were generated from the total RNA using the Illumina mRNA TruSeq kit following the manufacturer's directions and sequenced using the Illumina HiSeq 5000 platform. The acquired RNA reads were aligned to hg19 genome assembly using STAR (23 (link)). RNA counts were normalized within sample and log transformed.
Gopal P., Yard B.D., Petty A., Lal J.C., Bera T.K., Hoang T.Q., Buhimschi A.D, & Abazeed M.E. (2022). The Mutational Landscape of Cancer's Vulnerability to Ionizing Radiation. Clinical Cancer Research, 28(24), 5343-5358.
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2

Illumina RNA-seq Library Generation and Analysis

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One µg of total RNA was converted to mRNA libraries using the Illumina mRNA TruSeq kit (RS-122-2001 or RS-122-2002) following the manufacturer’s directions. Libraries were sequenced 48×7×48 bp on the Illumina HiSeq 2000 as previously described (Cancer Genome Atlas Research Network, 2012 (link)). FASTQ files were generated by CASAVA. RNA reads were aligned to the hg19 genome assembly using MapSplice 0.7.5 (Wang et al., 2010 (link)). Gene expression was quantified for the transcript models corresponding to the TCGA GAF2.1 (https://gdc-api.nci.nih.gov/v0/data/a0bb9765-3f03-485b-839d-7dce4a9bcfeb) using RSEM (Li and Dewey, 2011 (link)), and gene expression was normalized within-sample to a fixed upper quartile.
Fusion gene alignments were determined using MapSplice (Wang et al., 2010 (link)). For further details on this procedure, refer to Description file at the Data Coordinating Center data portal under the V2_MapSpliceRSEM workflow (https://gdcapi.nci.nih.gov/legacy/data/e34a93ee-d3c4-44c7-8bfa-0c19c6df0866). Putative TRIO fusions were selected from discordant paired end reads in which the non-TRIO end mapped to an identified gene. BAM files and expression data can be found at the Genomic Data Commons (https://gdc-portal.nci.nih.gov/legacy-archive/).
Abeshouse A., Adebamowo C., Adebamowo S.N., Akbani R., Akeredolu T., Ally A., Anderson M.L., Anur P., Appelbaum E.L., Armenia J., Auman J.T., Bailey M.H., Baker L., Balasundaram M., Balu S., Barthel F.P., Bartlett J., Baylin S.B., Behera M., Belyaev D., Bennett J., Benz C., Beroukhim R., Birrer M., Bocklage T., Bodenheimer T., Boice L., Bootwalla M.S., Bowen J., Bowlby R., Boyd J., Brohl A.S., Brooks D., Byers L., Carlsen R., Castro P., Chen H.W., Cherniack A.D., Chibon F., Chin L., Cho J., Chuah E., Chudamani S., Cibulskis C., Cooper L.A., Cope L., Cordes M.G., Crain D., Curley E., Danilova L., Dao F., Davis I.J., Davis L.E., Defreitas T., Delman K., Demchok J.A., Demetri G.D., Demicco E.G., Dhalla N., Diao L., Ding L., DiSaia P., Dottino P., Doyle L.A., Drill E., Dubina M., Eschbacher J., Fedosenko K., Felau I., Ferguson M.L., Frazer S., Fronick C.C., Fulidou V., Fulton L.A., Fulton R.S., Gabriel S.B., Gao J., Gao Q., Gardner J., Gastier-Foster J.M., Gay C.M., Gehlenborg N., Gerken M., Getz G., Godwin A.K., Godwin E.M., Gordienko E., Grilley-Olson J.E., Gutman D.A., Gutmann D.H., Hayes D.N., Hegde A.M., Heiman D.I., Heins Z., Helsel C., Hepperla A.J., Higgins K., Hoadley K.A., Hobensack S., Holt R.A., Hoon D.B., Hornick J.L., Hoyle A.P., Hu X., Huang M., Hutter C.M., Iacocca M., Ingram D.R., Ittmann M., Iype L., Jefferys S.R., Jones K.B., Jones C.D., Jones S.J., Kalir T., Karlan B.Y., Karseladze A., Kasaian K., Kim J., Kundra R., Kuo H., Ladanyi M., Lai P.H., Laird P.W., Larsson E., Lawrence M.S., Lazar A.J., Lee S., Lee D., Lehmann K.V., Leraas K.M., Lester J., Levine D.A., Li I., Lichtenberg T.M., Lin P., Liu J., Liu W., Liu E.M., Lolla L., Lu Y., Ma Y., Madan R., Maglinte D.T., Magliocco A., Maki R.G., Mallery D., Manikhas G., Mardis E.R., Mariamidze A., Marra M.A., Martignetti J.A., Martinez C., Mayo M., McLellan M.D., Meier S., Meng S., Meyerson M., Mieczkowski P.A., Miller C.A., Mills G.B., Moore R.A., Morris S., Mose L.E., Mozgovoy E., Mungall A.J., Mungall K., Nalisnik M., Naresh R., Newton Y., Noble M.S., Novak J.E., Ochoa A., Olvera N., Owonikoko T.K., Paklina O., Parfitt J., Parker J.S., Pastore A., Paulauskis J., Penny R., Pereira E., Perou C.M., Perou A.H., Pihl T., Pollock R.E., Potapova O., Radenbaugh A.J., Ramalingam S.S., Ramirez N.C., Rathmell W.K., Raut C.P., Riedel R.F., Reilly C., Reynolds S.M., Roach J., Robertson A.G., Roszik J., Rubin B.P., Sadeghi S., Saksena G., Salner A., Sanchez-Vega F., Sander C., Schein J.E., Schmidt H.K., Schultz N., Schumacher S.E., Sekhon H., Senbabaoglu Y., Setdikova G., Shelton C., Shelton T., Shen R., Shi Y., Shih J., Shmulevich I., Sica G.L., Simons J.V., Singer S., Sipahimalani P., Skelly T., Socci N., Sofia H.J., Soloway M.G., Spellman P., Sun Q., Swanson P., Tam A., Tan D., Tarnuzzer R., Thiessen N., Thompson E., Thorne L.B., Tong P., Torres K.E., van de Rijn M., Van Den Berg D.J., Van Tine B.A., Veluvolu U., Verhaak R., Voet D., Voronina O., Wan Y., Wang Z., Wang J., Weinstein J.N., Weisenberger D.J., Wilkerson M.D., Wilson R.K., Wise L., Wong T., Wong W., Wrangle J., Wu Y., Wyczalkowski M., Yang L., Yau C., Yellapantula V., Zenklusen J.C., Zhang J.(., Zhang H., Zhang H, & Zmuda E. (2017). COMPREHENSIVE AND INTEGRATED GENOMIC CHARACTERIZATION OF ADULT SOFT TISSUE SARCOMAS. Cell, 171(4), 950-965.e28.
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3

Transcriptomic Analysis of Mouse Liver

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Three liver RNA samples from each treatment group were selected. RNA was cleaned using an RNAeasy kit (Qiagen). Concentrated RNA was submitted to the DNA Sequencing Group at the Roy J. Carver Biotechnology Center at UIUC. cDNA libraries were prepared with the mRNA TruSeq Kit (Illumina Inc.). Double stranded cDNA was generated from fragmented RNA and adapters were ligated to the ends. Casava 1.8.2. was used to base call and demultiplex samples. FASTQ files were trimmed using FASTQ Trimmer (version 1.0.0). TopHat (version 0.5) was used to map single-end RNA-seq reads to Mus musculus reference genome. Gene expression values quantified from BAM files were calculated using StrandNGS (version 3.1) Quantification tool. Partial reads were considered and the option of detecting novel genes and exons was selected. Default parameters for finding novel exons and genes were specified. DESeq normalization algorithm using default values was chosen. Differentially expressed genes were then determined by fold-change and p-value with Benjamini and Hochberg multiple test correction for each gene for each treatment relative to the vehicle control. We considered genes with fold-change >2 and FDR (or q) < 0.05 as significantly and differentially expressed. PCA analysis was performed using StrandNGS.
Chen K.L., Zhao Y.C., Hieronymi K., Smith B.P, & Madak-Erdogan Z. (2017). Bazedoxifene and conjugated estrogen combination maintains metabolic homeostasis and benefits liver health. PLoS ONE, 12(12), e0189911.
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4

RNA-Seq Analysis of Transcriptome

Cited 1 time
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Total RNA was isolated from duplicate wells of indicated conditions. RNA integrity and concentration were assessed using a BioAnalyzer (Agilent). RNA sequencing libraries were generated using Illumina mRNA TruSeq kit with dual index barcoding. Multiplexed libraries were sequenced at the Cold Spring Harbor Labs core sequencing facility. Approximately 8 million paired-end 76 bp reads were sequenced per replicate on a HiSeq 2500 instrument on RAPID mode. After removing adaptor sequences with Trimmomatic47 (link), RNA-Seq reads were aligned to GRCm38 – mm10 with STAR48 (link). Genome wide transcript counting was performed by HTSeq or featureCounts to generate FPKM matrix49 (link),50 (link). Differential expression analysis was performed with DESeq2 package in R51 (link). Genes with a real adjusted p value were used for downstream analyses.
Morris JP I.V., Yashinskie J.J., Koche R., Chandwani R., Tian S., Chen C.C., Baslan T., Marinkovic Z.S., Sánchez-Rivera F.J., Leach S.D., Carmona-Fontaine C., Thompson C.B., Finley L.W, & Lowe S.W. (2019). Alpha-ketoglutarate links p53 to cell fate during tumor suppression. Nature, 573(7775), 595-599.
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5

BEAS-2B Cell RNA Sequencing

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RNA was isolated from variant, wild type, or vector expressing BEAS-2B cells and quantified. mRNA libraries were generated from the total RNA using the Illumina mRNA TruSeq kit following the manufacturer’s directions and sequenced using the Illumina HiSeq 5000 platform. The acquired RNA reads were aligned to hg19 genome assembly using STAR23 (link). RNA counts were normalized within sample and log transformed.
Gopal P., Yard B.D., Petty A., Lal J.C., Bera T.K., Hoang T.Q., Buhimschi A.D, & Abazeed M.E. (2022). The Mutational Landscape of Cancer's Vulnerability to Ionizing Radiation. Clinical Cancer Research, 28(24), 5343-5358.
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6

RNA Quality and Quantity Assessment

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RNA quality and quantity were assessed using an Agilent Bio-analyzer. RNA-Seq libraries were prepared using Illumina mRNA TruSeq kits as protocolled by Illumina. Library quality and quantity were checked using an Agilent Bio-analyzer and the pool of libraries was sequenced using an Illumina HiSeq4000 and Illumina reagents.
Jambusaria A., Hong Z., Zhang L., Srivastava S., Jana A., Toth P.T., Dai Y., Malik A.B, & Rehman J. (2020). Endothelial heterogeneity across distinct vascular beds during homeostasis and inflammation. eLife, 9, e51413.
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7

RNA-Seq Library Preparation and Sequencing

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Agilent Bio-analyzer was used to check RNA quality and quantity. All samples showed RNA integrity number >8. RNA-seq libraries were prepared using Illumina mRNA TruSeq kits according to the protocol by Illumina. Library quality and quantity were checked, and the pool of libraries was sequenced using an Illumina HiSeq4000 and Illumina reagents. The data are available via Gene Expression Omnibus (GEO) accession no. GSE231219 and its linked datasets.
Chakraborty S., Singh A., Wang L., Wang X., Sanborn M.A., Ye Z., Maienschein-Cline M., Mukhopadhyay A., Ganesh B.B., Malik A.B, & Rehman J. (2023). Trained immunity of alveolar macrophages enhances injury resolution via KLF4-MERTK-mediated efferocytosis. The Journal of Experimental Medicine, 220(11), e20221388.
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