Project description:DNA methylation at a gene promoter region has the potential to regulate gene transcription. Their patterns are often complex with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). The methylation state at adjacent CpG sites is therefore lost when data is summarised this way. Methylation patterns can only be characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. We have developed an analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. We have performed multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Using Methpat, we demonstrate clonal diversity of epialleles analysed at specific gene promoter regions. We also describe the existence of DNA methylation within the mitochondrial genome. Multiplex bisulfite PCR and Next Generation sequencing of 35 samples
Project description:DNA methylation at a gene promoter region has the potential to regulate gene transcription. Their patterns are often complex with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). The methylation state at adjacent CpG sites is therefore lost when data is summarised this way. Methylation patterns can only be characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. We have developed an analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. We have performed multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Using Methpat, we demonstrate clonal diversity of epialleles analysed at specific gene promoter regions. We also describe the existence of DNA methylation within the mitochondrial genome.
Project description:In this study, using a murine model of Ph+ acute lymphoblastic leukemia (Ph+ ALL), a combined pharmacological profile and drug selection experimental approach identified distinct stages of tumor clonal evolution with vulnerabilities to sets of small molecules. Through genotypic, phenotypic, signaling, and binding measurements, we identified the mutation V299L in the ABL1 kinase domain as mediator for an on-target ABL1 inhibition and hence the sensitization phenotype. To further rule out any off-target effects, we performed RNA-seq analysis of select derived cell lines. Variant calls suggest that although there were other mutations, the only mutation shared among cell lines with the sensitization phenotype and that went from 0% to 100% variant allele frequency was c.895G>C, leading to BCR-ABL1 V299L. In addition, transcriptional profile does not suggest functional changes in BCR-ABL1 V299L and WT cell lines. RNA-seq of parental murine Ph+ acute lymphoblastic leukemia (Ph+ ALL) cell line and derived cell lines (via dose escalating concentrations of dasatinib or DMSO vehicle control).