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Gaiix sequencing

Manufactured by Illumina

The GAIIx sequencing system is a laboratory equipment product developed by Illumina. It is designed to perform high-throughput DNA sequencing. The core function of the GAIIx is to generate DNA sequence data from biological samples.

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2 protocols using gaiix sequencing

1

Transcriptome Reconstruction of K562 Cells

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Transcriptome reconstruction of PH and ENCODE datasets of K562 cells by RNA-Seq was performed respectively using rigorous read set through a sliding window filtering the average quality values within the window less than 20 and the length of reads less than 35 bp by Trimmomatic [53 ]. After quality control, we obtained 90.7 million 2*100-base paired-end reads generated by Illumina Hiseq2000 sequencing on polyadenylated selected (Poly-A+) RNAs. On the other hand, ENCODE RNA-Seq dataset was incorporated 112.3 million 2*76-base paired-end reads generated by Illumina GAIIx sequencing on Poly-A+ RNAs from NCBI Gene Expression Omnibus (GEO) database with accession number GSM765405.
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2

Somatic Mutation Identification by NGS

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EXAMPLE 5

Somatic Mutation Identification by Illumina GAIIx Sequencing and Sanger Sequencing

All captured DNA libraries were sequenced with Illumina GAIIx Genome Analyzer, yielding 75 base pairs from the final library fragments. All sequencing reads were analyzed and aligned to human genome hg18 with the Eland algorithm of CASAVA 1.6 software (Illumina). A mismatched base was identified as a mutation only when (i) it was identified by more than four distinct tags; (ii) the number of distinct tags containing a particular mismatched base was at least 20% of the total distinct tags; and (iii) it was not present in >0.5% of the tags in the matched normal sample.

All somatic mutations identified by the first round of exome sequencing were subjected to conventional Sanger sequencing. PCR amplification and sequencing were performed following protocols described previously (3) using the primers listed in Table S4. SNP search databases included ncbi.nlm.nih.gov/projects/SNP/ and /browser.1000genomes.org/index.html.

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