Whole exome sequencing analyzed the off-target effect of gene editing through BE3 system.
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE115017 | GEO | 2018/08/06
REPOSITORIES: GEO
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Project description:U87MG is a commonly studied grade IV glioma cell line that has been analyzed in at least 1,700 publications over four decades. In order to comprehensively characterize the genome of this cell line and to serve as a model of broad cancer genome sequencing, we have generated greater than 30x genomic sequence coverage using a novel 50-base mate paired strategy with a 1.4kb mean insert library. A total of 1,014,984,286 mate-end and 120,691,623 single-end two-base encoded reads were generated from five slides. All data were aligned using a custom designed tool called BFAST, allowing optimal color space read alignment and accurate identification of DNA variants. The aligned sequence reads and mate pair information identified 35 interchromosomal translocation events, 1,315 structural variations (>100bp), 191,743 small (<21bp) insertions and deletions (indels), and 2,384,470 single nucleotide variations (SNVs). Among these observations, the known homozygous mutation in PTEN was robustly identified, and genes involved in cell adhesion were overrepresented in the mutated gene list. Data were compared to 219,187 heterozygous single nucleotide polymorphisms assayed by Illumina 1M Duo genotyping array to assess accuracy: 93.83% of all SNPs were reliably detected at filtering thresholds that yield greater than 99.99% sequence accuracy. Protein coding sequences were disrupted predominantly in this cancer cell line due to small indels, large deletions and translocations. In total, 512 genes were homozygously mutated, including 154 by SNVs, 178 by small indels, 145 by large microdeletions and 35 by interchromosomal translocations to reveal a highly mutated cell line genome. Of the small homozygously mutated variants, 8 SNVs and 99 indels were novel events not present in dbSNP. These data demonstrate that routine generation of broad cancer genome sequence is possible outside of genome centers. The sequence analysis of U87MG provides an unparalleled level of mutational resolution compared to any cell line to date. Whole genome sequencing of the U87MG brain cancer cell line using the AB SOLiD3 sequencer and genotyping using the Illumina Human1M-Duov3 DNA Analysis BeadChip
2010-01-24 | E-GEOD-19986 | biostudies-arrayexpress
Project description:U87MG is a commonly studied grade IV glioma cell line that has been analyzed in at least 1,700 publications over four decades. In order to comprehensively characterize the genome of this cell line and to serve as a model of broad cancer genome sequencing, we have generated greater than 30x genomic sequence coverage using a novel 50-base mate paired strategy with a 1.4kb mean insert library. A total of 1,014,984,286 mate-end and 120,691,623 single-end two-base encoded reads were generated from five slides. All data were aligned using a custom designed tool called BFAST, allowing optimal color space read alignment and accurate identification of DNA variants. The aligned sequence reads and mate pair information identified 35 interchromosomal translocation events, 1,315 structural variations (>100bp), 191,743 small (<21bp) insertions and deletions (indels), and 2,384,470 single nucleotide variations (SNVs). Among these observations, the known homozygous mutation in PTEN was robustly identified, and genes involved in cell adhesion were overrepresented in the mutated gene list. Data were compared to 219,187 heterozygous single nucleotide polymorphisms assayed by Illumina 1M Duo genotyping array to assess accuracy: 93.83% of all SNPs were reliably detected at filtering thresholds that yield greater than 99.99% sequence accuracy. Protein coding sequences were disrupted predominantly in this cancer cell line due to small indels, large deletions and translocations. In total, 512 genes were homozygously mutated, including 154 by SNVs, 178 by small indels, 145 by large microdeletions and 35 by interchromosomal translocations to reveal a highly mutated cell line genome. Of the small homozygously mutated variants, 8 SNVs and 99 indels were novel events not present in dbSNP. These data demonstrate that routine generation of broad cancer genome sequence is possible outside of genome centers. The sequence analysis of U87MG provides an unparalleled level of mutational resolution compared to any cell line to date.
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Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
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2014-08-12 | GSE60168 | GEO
Project description:Deep high-throughput transcriptome sequencing (RNA-seq) performed on 3 pairs of matched tumor and adjacent non-tumorours (NT) tissues from HCC patients of Chinese origin generated 183.6-million reads that could be aligned. We discovered a number of differentially expressed genes and multiple types of somatic single nucleotide variations (SNVs) in expressed genes. After the removal of the error alignments, high-quality reads were mapped to the human reference sequence (GRCh37/hg19) using three different softwares TopHat, Burrows-Wheeler Aligner (BWA) and CLC Genomics Workbench (CLC). The high-quality variants were identified using VarScan with the following parameters: minimum coverage depth of 10, variation frequency of more than 30% and base quality of more than 15. A total of 568, 545 and 494 potential somatic single nucleotide variants (SNVs), including 94, 89 and 101 coding somatic SNVs (cSNVs), were identified in 3 tumor samples HCC448T, HCC473T and HCC510T, respectively. Validation analysis was carried out for 10 of the intersected cSNVs (all are non-synonymous substitutions) within selected genes of interests with the majority confirmed. Examination of 3 paired human hepatocellular carcinoma and matched non-tumor tissues
2013-04-02 | E-GEOD-33294 | biostudies-arrayexpress
Project description:The genetic landscape and molecular features of collecting duct carcinoma (CDC) of the kidney remain largely unknown. Herein, we performed whole exome sequencing (WES) and transcriptome sequencing (RNASeq) on 7 CDC samples (CDC1 -7). Among the 7 samples, 4 samples with matched non-tumor tissue were used for copy number analysis by SNP array data. No recurrent somatic SNVs were observed except for MLL, which was found to be mutated (p.V297I and p.F407C) in 2 samples. We identified somatic SNVs in 14 other cancer census genes including: ATM, CREBBP, PRDM1, CBFB, FBXW7, IKZF1, KDR, KRAS, NACA, NF2, NUP98, SS18, TP53, and ZNF521. SNP array data identified a CDKN2A homozygous deletion in 3 samples and SNV analysis showed a non-sense mutation of the CDKN2A gene with unknown somatic status. To estimate the recurrent rate of CDKN2A abnormalities, we performed FISH screening of additional samples and confirmed the frequent loss (62.5%) of CDKN2A expression. Since cisplatin based therapy is the common treatment option for CDC, we investigated the expression of solute carrier (SLC) family transporters and found 45% alteration. In addition, SLC7A11 (cystine transporter, xCT), a cisplatin resistance associated gene, was found to be overexpressed in 4 out of 5 (80%) cases of CDC tumors tested, as compared to matched non-tumor tissue. In summary, our study provides a comprehensive genomic analysis of CDC and identifies potential pathways suitable for targeted therapies.
2016-10-25 | GSE89122 | GEO
Project description:Deep high-throughput transcriptome sequencing (RNA-seq) performed on 3 pairs of matched tumor and adjacent non-tumorours (NT) tissues from HCC patients of Chinese origin generated 183.6-million reads that could be aligned. We discovered a number of differentially expressed genes and multiple types of somatic single nucleotide variations (SNVs) in expressed genes. After the removal of the error alignments, high-quality reads were mapped to the human reference sequence (GRCh37/hg19) using three different softwares TopHat, Burrows-Wheeler Aligner (BWA) and CLC Genomics Workbench (CLC). The high-quality variants were identified using VarScan with the following parameters: minimum coverage depth of 10, variation frequency of more than 30% and base quality of more than 15. A total of 568, 545 and 494 potential somatic single nucleotide variants (SNVs), including 94, 89 and 101 coding somatic SNVs (cSNVs), were identified in 3 tumor samples HCC448T, HCC473T and HCC510T, respectively. Validation analysis was carried out for 10 of the intersected cSNVs (all are non-synonymous substitutions) within selected genes of interests with the majority confirmed.
2013-04-02 | GSE33294 | GEO