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Sample GSM1548440

Query DataSets for GSM1548440

Status

Public on Jan 22, 2015

Title

ICC10 (Exome-seq)

Sample type

SRA

Source name

iCCA patient, liver

Organism

Homo sapiens

Characteristics

material type: fresh-frozen
tissue: liver
cell type: intrahepatic cholangiocarcinoma

Treatment protocol

not applicable

Growth protocol

not applicable

Extracted molecule

genomic DNA

Extraction protocol

Total RNA was extracted from homogenized cholangiocarcinoma samples and their normal conterparts usingTRizol Regent (Invitrogen). Quantity of RNA was measured using Quant-iT Ribogreen RNA assay kit and quality was assessed using a Bioanalyzer. One µg of RNA was used for subsequent RNA-seq library generation. DNA was isolated using the ChargeSwitch® gDNA Mini Tissue Ki/t (Invitrogen) after tissue disruption with a homogenizer. DNA quantity was assessed through Quant-It PicoGreen dsDNA Assay kit (Invitrogen) and its integrity confirmed by agarose gel.
For RNA-seq, the sequencing library was prepared with the standard TruSeq RNA Sample Prep Kit v2 protocol (Illumina, CA, USA). Briefly, total RNA was poly-A-selected and then fragmented. The cDNA was synthesized using random hexamers, end-repaired and ligated with appropriate adaptors for sequencing. The library then underwent size selection and purification using AMPure XP beads (Beckman Coulter, CA, USA). The appropriate Illumina recommended 6 bp barcode bases are introduced at one end of the adaptors during PCR amplification step. The size and concentration of the RNAseq libraries was measured by Bioanalyzer and Qubit fluorometry (Life Technologies, NY, USA) before loading onto the sequencer. The mRNA libraries were sequenced on the Illumina HiSeq 2500 System with 100 nucleotide single-end reads, according to the standard manufacturer's protocol (Illumina, CA, USA). For exome-seq, total genomic DNA library is generated following the manufacturer protocol (NEBNext DNA Library Prep Master Mix Set for Illumina, New England Biolabs, Ipswich, MA). For whole exome sequencing (WES), the library then undergoes solution-based hybridization to an oligonucleotide pool designed to enrich for the whole exome regions of interests. The library is captured by following the manufacturer protocol (SeqCap EZ Human Exome Library v3.0 User Guide. Roche NimbleGen. Madison, WI).

Library strategy

OTHER

Library source

genomic

Library selection

other

Instrument model

Illumina HiSeq 2500

Description

tumoral tissue of ICC9
library strategy: Exome-seq

Data processing

For RNA-seq, between 20 and 25 million 100 base pair (bp) reads were generated for each of 7 matched-normal samples. Actual alignment of the raw cDNA reads was carried out by tophat-fusion and de novo assembly of transcript level reads was carried out by Cufflinks. Briefly, tophat-fusion breaks up individual reads into 25 bp segments, which are mapped independently to the reference build hg19 via bowtie. Following Edgren et al, we used the following filtration scheme to identify fusion events: 1) BLAST sequence around putative breakpoint to hg19 build to identify and remove paralogous sequences; 2) Filter fusions based on the number of reads that support the putative fusion breakpoints, setting the minimum number of such spanning reads conservatively; 3) compute scores of distributions of coverage of reads around the putative breakpoints, rejecting non uniformly covered reads; 4) fusions between adjacent genes were rejected as read-through transcript events, with a minimum distance of 100 kb; 5) finally, we considered a read to support a fusion if it mapped to both sides of breakpoint by at least a minimum fusion anchor length of 25bp, or generally about a quarter of a read length.
For exome-seq, the experiments achieved high quality in the metrics of high read quality, high mapping rate, low duplication rate and adequate coverage of the target regions. PCR and optical duplicates, low-quality (Q<20) and non-uniquely mapped reads were successfully removed. Remaining reads were aligned to the human genome reference 19th version using BWA. Afterwards, somatic single nucleotide variants (SNV) and small indels were identified through VarScan2. We calculated p-value using Fisher’s Exact Test for all putative mutation sites based on the distribution of read support for different alleles in tumor and matched normal samples. The VarScan2 software was employed in above analyses because of their desirable feature in detecting mutations in low purity or heterogeneous cancer samples. Purity information was factored in Mutant allele frequency estimations.
Genome_build: human genome 19
Supplementary_files_format_and_content:

Submission date

Nov 18, 2014

Last update date

May 15, 2019

Contact name

Daniela Sia

Organization name

Icahn school of Medicine at Mount Sinai

Department

Liver Diseases

Street address

1425 Madison Avenue