Computational protocol: Characterization and metabolic synthetic lethal testing in a new model of SDH-loss familial pheochromocytoma and paraganglioma

Similar protocols

Protocol publication

[…] Cell pellets for Sdhc fl/fl and Sdhc fl/+ iMEF lines collected over the time series experiment were subjected to RNA extraction using the Qiagen RNeasy kit. Purified RNA was the submitted to the Mayo Clinic Medical Genome Facility for indexing and preparation of deep sequencing libraries using the Illumina TruSeq mRNA v2 kit, followed by deep sequencing on a HiSeq 4000 instrument, multiplexing 8 samples per lane and performing 100 sequencing cycles. Following sequencing, reads belonging to individual experiments were deconvoluted on the basis of unique sequence barcodes. Deconvoluted sequence read data for individual experiments are available from the NCBI sequence read archive (SRA) under identifier SRP117182.Paired end sequence reads were then aligned to the mm9 mouse reference genome using the Bowtie fast read aligner [] and the Mayo Clinic Research Computing Facility Beowulf-style Linux cluster. SAM files were then converted to BAM file format using SAMtools [], and FPKM quantitation of individual transcript abundance was performed using R package systemPipeR [], available through the Bioconductor project. The resulting processed gene expression datasets are available via NCBI Gene Expression Omnibus (GEO) under entry GSE103662. [...] Cell pellets for Sdhc fl/fl and Sdhc fl/wt iMEF lines collected over the time series experiment were subjected to DNA extraction using the Qiagen Blood and Tissue kit. Purified genomic DNA was then submitted to the Mayo Clinic Medical Genome Facility for subsequent bisulfite conversion, indexing and preparation of paired-end deep sequencing libraries, followed by deep sequencing on a HiSeq 4000 instrument, multiplexing 8 samples per lane and performing 100 sequencing cycles. Following sequencing, reads belonging to individual experiments were deconvoluted on the basis of unique sequence barcodes. Deconvoluted sequence read data for individual experiments are available from the NCBI sequence read archive (SRA) under identifier SRP117088.Sequence reads were then aligned to the mm10 mouse reference genome using the Bismark bisulfite read mapper [] and the Mayo Clinic Research Computing Facility Beowulf-style Linux cluster. Methylation calling was performed using the Bismark methylation extractor utility, and CpG context-specific methylation status of individual sites was extracted using the Bismark bismark2bedGraph utility.Bismark .COV files were then used in downstream filtering and analysis performed in R using the package RnBeads []. In brief, the data was filtered to remove sex chromosomes, CpG sites with exceptionally high coverage, CpG sites with no methylation information, and CpG sites having exceptionally low standard deviation in beta value across samples. Differential methylation analysis at the CpG site level was performed in RnBeads, grouping all Sdhc fl/wt samples into the control group, and including Sdhc fl/fl samples, except for the day 0 sample, in the experimental group. Beta values for individual CpG sites, as well as averaged beta values for CpG sites mapping to annotated GpG islands and promoters (1.5 kb upstream and 500 bp downstream of annotated TSS) were exported for downstream exploratory analysis. The resulting processed DNA methylation datasets are available via NCBI Gene Expression Omnibus (GEO) under entry GSE103609.Average differences in site-specific, CpG island-specific, and promoter-specific methylation beta values were calculated by subtracting the methylation values of the Sdhc fl/wt iMEF line (control) from the Sdhc fl/fl iMEF line (experimental). [...] Processed Bismark .COV files describing DNA methylation change in SDHB-loss immortalized mouse chromaffin cells (imCCs) were downloaded from NCBI GEO entry GSE43298. This dataset has been described previously []. Data were handled in RnBeads using the same methods as used to process iMEF RRBS data to produce methylation beta value quantitations. Average differences in promoter-specific methylation beta values were calculated by subtracting the mean methylation values of the SDHB-wt imCC line (control) from the SDHB-loss imCC line (experimental).Datasets measuring DNA methylation in biopsied human PPGL tumors via Illumina HumanMethylation450 BeadChip were obtained from ArrayExpress under entry E-GEOD-43298. This dataset has also been described previously []. Average beta values for SDHx tumors and all other tumors were calculated in R. Average differences in promoter-specific methylation beta values were calculated by subtracting the mean methylation values the CpG island nearest to a given TSS of the non-SDHx PPGL tumors (control) from the SDHx PPGL tumors (experimental).Correlative analysis of methylation differences observed in SDHC-loss iMEFs, SDHB-loss imCCs, and SDHx-attributable PPGL tumors was performed in R. Analysis of functional term enrichment in subset of genes observed to have promoter hypermethylation (beta difference > 0.05) across all three contexts was performed using the DAVID functional annotation database []. [...] Raw MS/MS spectra data was processed by MaxQuant (v 1.4.1.2) for protein quantification against the Uniprot mouse database (downloaded on 2013/09/27 with a total of 43310 sequences). The fixed cysteine carbamidomethylation modification and the variable modifications of methionine oxidation and protein N-terminal acetylation were specified. The proteolytic enzyme, trypsin, was selected, permitting a two missing cleavages. Multiplicity was set to two. R6 and K6 were specified as heavy amino acid labels with a maximum of three labeled amino acids per peptide. Default values were included for the rest of the search parameters. The precursor ion and fragment ion mass tolerance was set at 4.5 ppm and 0.5 Da respectively. The database search was filtered to achieve a 1% False Discovery Rate (FDR) at peptide, protein and modified site level. The minimum Andromeda score for modified peptides was set at 40. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [] partner repository with the dataset identifier PXD007874. […]

Pipeline specifications

Software tools Bismark, RnBeads, DAVID
Application BS-seq analysis