Figures for the manuscript "sc2RNA-seq reveals core features of transcription dynamics in single cells"

These are the scripts to generate all figures for the manuscript "sc2RNA-seq reveals core features of transcription dynamics in single cells". Start by using the Makefile!</p

Figures for the manuscript "scSLAM-seq reveals core features of cellular and viral transcription dynamics in single cells"

These are the scripts to generate all figures for the manuscript "scSLAM-seq reveals core features of cellular and viral transcription dynamics in single cells". Start by using the Makefile!</p

HSV-1 Viewer

Since the genome of herpes simplex virus 1 (HSV-1) was first sequenced more than 30 years ago, its predicted 80 genes have been intensively studied. Here, we unravel the complete viral transcriptome and translatome during lytic infection with base-pair resolution by computational integration of multi-omics data. We identified a total of 201 viral transcripts and 284 open reading frames (ORFs) including all known and 46 novel large ORFs. Multiple transcript isoforms expressed from individual gene loci explain translation of the vast majority of novel viral ORFs as well as N-terminal extensions (NTEs) and truncations thereof. We show that key viral regulators and structural proteins possess NTEs, which initiate from non-canonical start codons and govern subcellular protein localization and packaging. We validated a novel non-canonical large spliced ORF in the ICP0 locus and identified a 93 aa ORF overlapping ICP34.5 that is thus also deleted in the FDA-approved oncolytic virus Imlygic. Finally, we extend the current nomenclature to include all novel viral gene products. To make the annotation and all the obtained data readily accessible to the research community, we here provide our HSV-1 genome browser software. Thereby, viral gene expression and all data can be visually examined from whole genome to single-nucleotide resolution.</p

Time-resolved single-cell RNA-seq using scSLAM-seq and GRAND-SLAM

This is the example data for the protocol "Time-resolved single-cell RNA-seq using scSLAM-seq and GRAND-SLAM". The test data comprises sequencing data from 12 different cells. Five of them in mock condition with 4sU, five infected with MCMV with 4sU and 2 uninfected cells without 4sU. For each sample, paired-end sequencing was conducted and therefore two files exist for each sample. The files can be found at data/fastq. The reads should be mapped against the mouse genome and the MCMV genome, which are located in data/genome. The sequence is in fasta-fomat and the features in gtf-format.The scripts conducting quality control, read mapping and GRAND-SLAM analysis can be found in the processing folder. For each computational step in this protocol there is a shell script for running the necessary steps. Executing all scripts will reproduce the analysis of our test data</p

Supplementary Note S1 from Identification of the Cryptic HLA-I Immunopeptidome

Comments on the target decoy approach and extended explanations on Peptide-PRISM</p

Supplementary Figures S1-S9 from Identification of the Cryptic HLA-I Immunopeptidome

Fig. S1. Total peak intensities of cryptic and conventional peptides Fig. S2. Validation of cryptic peptides by mass spectrometry of synthetic peptides Fig. S3. Distribution of peptide categories in all data sets Fig. S4. Predicted binding affinities of peptide categories for all data sets Fig. S5. Extended analysis of PCPS peptides Fig. S6. Extended analysis of peptides with single amino acid substitutions Fig. S7. A reported neoantigen is in fact a cryptic peptide Fig. S8. An intronic peptide Fig. S9. Amino acid bias and HLA-I allele preference of cryptic peptides</p

Supplementary Tables S1-S4 from Identification of the Cryptic HLA-I Immunopeptidome

Table S1. Re-analysis of the GR-LCL data set for PCPS peptides Table S2. Data sets considered in this study Table S3. All identified cryptic peptides Table S4. Number of cryptic peptides per HLA supertype in all samples</p

Extending the Mass Spectrometry-Detectable Landscape of MHC Peptides by Use of Restricted Access Material

Mass spectrometry-based immunopeptidomics enables the comprehensive identification of major histocompatibility complex (MHC) peptides from a cell culture as well as from tissue or tumor samples and is applied for the identification of tumor-specific and viral T-cell epitopes. Although mass spectrometry is generally considered an “unbiased” method for MHC peptide identification, the physicochemical properties of MHC peptides can greatly influence their detectability. Here, we demonstrate that highly hydrophobic peptides are lost during sample preparation when C18 solid-phase extraction (SPE) is used for separating MHC peptides from proteins. To overcome this limitation, we established an optimized protocol involving restricted access material (RAM). Compared to C18-SPE, RAM-SPE improved the overall MHC peptide recovery and extended the landscape of mass spectrometry-detectable MHC peptides toward more hydrophobic peptides

Extending the Mass Spectrometry-Detectable Landscape of MHC Peptides by Use of Restricted Access Material

Mass spectrometry-based immunopeptidomics enables the comprehensive identification of major histocompatibility complex (MHC) peptides from a cell culture as well as from tissue or tumor samples and is applied for the identification of tumor-specific and viral T-cell epitopes. Although mass spectrometry is generally considered an “unbiased” method for MHC peptide identification, the physicochemical properties of MHC peptides can greatly influence their detectability. Here, we demonstrate that highly hydrophobic peptides are lost during sample preparation when C18 solid-phase extraction (SPE) is used for separating MHC peptides from proteins. To overcome this limitation, we established an optimized protocol involving restricted access material (RAM). Compared to C18-SPE, RAM-SPE improved the overall MHC peptide recovery and extended the landscape of mass spectrometry-detectable MHC peptides toward more hydrophobic peptides

Extending the Mass Spectrometry-Detectable Landscape of MHC Peptides by Use of Restricted Access Material

Mass spectrometry-based immunopeptidomics enables the comprehensive identification of major histocompatibility complex (MHC) peptides from a cell culture as well as from tissue or tumor samples and is applied for the identification of tumor-specific and viral T-cell epitopes. Although mass spectrometry is generally considered an “unbiased” method for MHC peptide identification, the physicochemical properties of MHC peptides can greatly influence their detectability. Here, we demonstrate that highly hydrophobic peptides are lost during sample preparation when C18 solid-phase extraction (SPE) is used for separating MHC peptides from proteins. To overcome this limitation, we established an optimized protocol involving restricted access material (RAM). Compared to C18-SPE, RAM-SPE improved the overall MHC peptide recovery and extended the landscape of mass spectrometry-detectable MHC peptides toward more hydrophobic peptides