Computational protocol: Systems biology analysis of mitogen activated protein kinase                    inhibitor resistance in malignant melanoma

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Protocol publication

[…] Total RNA from malignant melanoma cells was extracted using a mammalian RNA mini preparation kit (RTN10-1KT, GenElute, Sigma EMD Millipore, Darmstadt, Germany) and then digested with deoxyribonuclease I (AMPD1-1KT, Sigma EMD Millipore, Darmstadt, Germany). Complementary DNA (cDNA) was synthesized using random hexamers (cDNA SuperMix, 95,048–500, Quanta Biosciences, Beverly, MA). The purified DNA library was sequenced using a HighSeq2500 (Illumina, San Diego, CA) at the University of California Irvine Genomics High-Throughput Facility. Purity and integrity of the nucleic acid samples were quantified using a Bioanalyzer (2100 Bioanalyzer, Agilent, Santa Clara, CA). Libraries for next generation mRNA transcriptome sequencing (RNA-Seq) analysis were generated using the TruSeq kit (Truseq RNA Library Prep Kit v2, RS-122-2001, Illumina, San Diego, CA). In brief, the workflow involves purifying the poly-A containing mRNA molecules using oligo-dT attached magnetic beads. Following purification, the mRNA is chemically fragmented into small pieces using divalent cations under elevated temperature. The cleaved RNA fragments are copied into first strand cDNA using reverse transcriptase and random primers. Second strand cDNA synthesis follows, using DNA polymerase I and RNase H. The cDNA fragments are end repaired by adenylation of the 3′ ends and ligated to barcoded adapters. The products are then purified and enriched by nine cycles of PCR to create the final cDNA library subjected to sequencing. The resulting libraries were validated by qPCR and size-quantified by a DNA high sensitivity chip (Bioanalyzer, 5067–4626, Agilent, Santa Clara, CA). Sequencing was performed using 50 base pair read length, single-end reads, and more than 107 reads per sample. Raw sequence reads in the file format for sequences with quality scores (FASTQ) were mapped to human reference Genome Reference Consortium GRCh38 using Bowtie alignment with an extended Burrows-Wheeler indexing for an ultrafast memory efficient alignment within the Tuxedo suite followed by Tophat to account for splice-isoforms [, ]. Read counts were scaled via the median of the geometric means of fragment counts across all libraries. Transcript abundance was quantified using normalized single-end RNA-Seq reads in read counts as well as reads per kilobase million (RPKM). Since single-end reads were acquired in the sequencing protocol, quantification of reads or fragments yielded similar results. Statistical testing for differential expression was based on read counts and performed using EdgeR in the Bioconductor toolbox []. Differentially expressed genes were further analyzed using Ingenuity Pathways Analysis (IPA, Qiagen, Rewood City, CA), classification of transcription factors (TFClass), and gene set enrichment analysis (GSEA, Broad Institute, Cambridge, MA) [, ]. For real-time quantitative polymerase chain reaction (RT-qPCR) validation of RNA-Seq signals of differentially expressed target genes in BRAFi-R melanoma cells, gene expression profiles were analyzed using the ΔΔ threshold cycle (CT) method. Oligonucleotides spanning exon-exon-junctions of transcripts were used for RT-qPCR validation (Additional file : Table 1). Triple replicate samples were subjected to SYBR green (SYBR green master mix, PerfeCTa® SYBR® Green FastMix®, 95072-05k, Quanta Biosciences, Beverly, MA) RT-qPCR analysis in an Eco system (Illumina, San Diego). CT values were normalized using multiple housekeeping genes like actin beta (ACTB, Gene ID: 60), cyclophilin A (PPIA, peptidylprolyl isomerase A, Gene ID: 5478) and RNA polymerase II subunit A (POLR2A, GeneID: 5430). […]

Pipeline specifications

Software tools Bowtie, Tuxedo, TopHat, edgeR, GSEA, GeneID
Databases TFClass GRC
Application RNA-seq analysis
Organisms Homo sapiens
Diseases Melanoma, Neoplasms
Chemicals Carbon