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Tophat

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TopHat is a software tool designed to align RNA-seq reads to a reference genome. It is a core component of the Tuxedo suite of tools for the analysis of RNA-seq data. TopHat's primary function is to identify splice junctions between exons, thereby enabling the discovery of novel splice sites and transcripts.

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Lab products found in correlation

Trizol, by Thermo Fisher Scientific (2 mentions) Nextseq 500, by Illumina (1 mentions) Nucleospin rna kit, by Macherey-Nagel (1 mentions) Nextseq 500 device, by Illumina (1 mentions) Nebnext ultra rna library kit, by Illumina (1 mentions) Nebnext rrna depletion kit, by New England Biolabs (1 mentions) Ipa software, by Qiagen (1 mentions) Igenome, by Illumina (1 mentions) Hiseq 1500, by Illumina (1 mentions) Nebnext ultra rna library prep kit, by New England Biolabs (1 mentions)

6 protocols using tophat

1

Yeast RNA Sequencing and Differential Expression

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Three independent yeast colonies were grown in 50 ml YPD media ± doxycycline as per the conditions detailed above. Total RNA was extracted from the cultures using a Nucleospin RNA kit (Macherey-Nagel) and RNA sequencing was carried out by the Centre for Genome Enabled Biology and Medicine at the University of Aberdeen using Illumina NextSeq 500. The RNA-sequencing data discussed in this publication have been deposited in NCBI’s Gene Expression Omnibus (37 (link)) and are accessible through GEO Series accession number GSE126435 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE126435). Library preparation, base-calling and quality control methods are described fully in the GEO database entry. Following quality control, the reads were mapped to the sequenced S. cerevisiae genome using TopHat for Illumina (38 (link)). Differential expression between test and control samples was assessed using CuffDiff (39 (link)).
McFarland M.R., Keller C.D., Childers B.M., Adeniyi S.A., Corrigall H., Raguin A., Romano M.C, & Stansfield I. (2020). The molecular aetiology of tRNA synthetase depletion: induction of a GCN4 amino acid starvation response despite homeostatic maintenance of charged tRNA levels. Nucleic Acids Research, 48(6), 3071-3088.
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2

Mapping Filtered Mouse Reads to Genome

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Filtered reads were mapped to the reference genome of M. musculus using the aligner TopHat (Trapnell et al., 2009 (link)) (Illumina).
Lee D.J., Kim H.Y., Lee S.J, & Jung H.S. (2021). Spatiotemporal Changes in Transcriptome of Odontogenic and Non-odontogenic Regions in the Dental Arch of Mus musculus. Frontiers in Cell and Developmental Biology, 9, 723326.
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3

RNA-seq Analysis of Mouse Cardiac Cell Populations

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RNA was extracted from excised LV or isolated myocyte and nonmyocyte cell populations using TRIzol (Invitrogen). To minimize biologic variation, RNA was pooled from n = 3 mice for whole LV tissue samples and n = 6 mice from isolated cell populations. cDNA libraries were constructed, and 5′ RNA-seq was performed as previously described (10 (link)). Libraries were sequenced on the Illumina platform and then aligned to the mouse reference sequence mm9 using Tophat (version 1.4.0). Of note, myosin heavy chain family genes (Myh1-Myh15) were selectively realigned using the STAR aligner because of frequent misalignment with Tophat secondary to the high degree of homology among these genes. The total number of reads of each transcript was normalized to 1 million, with P values of gene fold-changes determined as previously described (10 (link)).
Burke M.A., Chang S., Wakimoto H., Gorham J.M., Conner D.A., Christodoulou D.C., Parfenov M.G., DePalma S.R., Eminaga S., Konno T., Seidman J.G, & Seidman C.E. (2016). Molecular profiling of dilated cardiomyopathy that progresses to heart failure. JCI Insight, 1(6), e86898.
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4

RNA-seq analysis of tumor-infiltrating CD8+ T cells

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Tumor-infiltrating CD8 T cells from CT26-tumor bearing mice treated with Glucose 5% (control) or Folfox when tumors reached 50–70 mm2 were sorted by flow cytometry 8 days following treatment. CD8 TILs cells coming from 2 independent experiments with 8–10 pooled tumors for each experiment were used. Splenic CD8 T cells from 2 naïve mice were used as reference. Total mRNA was isolated using Trizol (Gibco Life Technologies) according to the manufacturer's instructions. rRNA from total RNA extracted were removed with NEBNextrRNA depletion kit (New England BioLabs). 100 ng of RNA depleted of rRNA was used for the library preparation with a NEBNext Ultra RNA library kit for Illumina according to the manufacturer's instructions (New England BioLabs). RNA sequencing was performed on a NextSeq 500 device (Illumina). The libraries were sequenced with paired-end 75–base pair ‘reads’. FASTQ files were mapped with the BWA software package (mm10 National Center for Biotechnology Information assembly of the Mus musculus genome) for Illumina. Analysis was performed with the splice junction mapper TopHat for Illumina. The files generated were processed with Cufflinks software to obtain annotated expressed genes in each studied subtype. Heatmaps of selected genes were generated using R software (http://www.R-project.org).
Dosset M., Vargas T.R., Lagrange A., Boidot R., Végran F., Roussey A., Chalmin F., Dondaine L., Paul C., Lauret Marie-Joseph E., Martin F., Ryffel B., Borg C., Adotévi O., Ghiringhelli F, & Apetoh L. (2018). PD-1/PD-L1 pathway: an adaptive immune resistance mechanism to immunogenic chemotherapy in colorectal cancer. Oncoimmunology, 7(6), e1433981.
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5

Differential Gene Expression Analysis of Tumor Samples and Cell Lines

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Sequence data quality check was performed using FastQC. The RNA-Seq data were mapped to the hg19 reference genome by TopHat for Illumina using default options. Assembly of transcripts and estimation of their abundance (fragments per kilobase of exon per million fragments mapped (FPKM)) were carried out using Cufflinks software. Differential gene expression analyses between groups were performed using HTSeq software for tumor samples66 (link) and DESeq2 software for cell line samples67 (link). Heatmap.2 in the ‘gplots’ package of the R program was used for the construction of heat maps. Genes that were up- or downregulated in both C13* and SKOV3 cells with a P value of less than 0.05 were analyzed using IPA software (Qiagen, Redwood City, CA, USA; http://www.ingenuity.com) in order to assign the genes to different functional networks. Fisher’s exact test was utilized to calculate P values with IPA. IPA generated a z-score for each predefined canonical pathway, where a z-score of at least 2 was associated with a confidence level of at least 99% that results were not chance. Positive and negative z-scores represented the activated and suppressed states, respectively.
Liu D., Zhang X.X., Li M.C., Cao C.H., Wan D.Y., Xi B.X., Tan J.H., Wang J., Yang Z.Y., Feng X.X., Ye F., Chen G., Wu P., Xi L., Wang H., Zhou J.F., Feng Z.H., Ma D, & Gao Q.L. (2018). C/EBPβ enhances platinum resistance of ovarian cancer cells by reprogramming H3K79 methylation. Nature Communications, 9, 1739.
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6

Transcriptome Analysis of Fibroblast Development

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mRNA was extracted from fibroblasts at PD 10 and the cDNA library was synthesized using the NEBNext Ultra RNA Library Prep Kit (E7370S, New England BioLabs, Beverly, MA, U.S.A). Sequencing was carried out (technically n=2 in each sample) by HiSeq1500 (Illumina, San Diego, CA, U.S.A) with 60bp single-reads. The reference genome mapping (UCSC/hg19) was performed using TopHat (version 2.0.13; with default parameters) with annotation data from iGenomes (Illumina). Cuffdiff (Cufflinks version 2.2.1; with default parameters) was used to quantify the gene expression levels. FPKM data were analyzed by iDEP (http://bioinformatics.sdstate.edu/idep/) as described by the authors [49 (link)].
Kato H., Maezawa Y., Takayama N., Ouchi Y., Kaneko H., Kinoshita D., Takada-Watanabe A., Oshima M., Koshizaka M., Ogata H., Kubota Y., Mitsukawa N., Eto K., Iwama A, & Yokote K. (2021). Fibroblasts from different body parts exhibit distinct phenotypes in adult progeria Werner syndrome. Aging (Albany NY), 13(4), 4946-4961.
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