Christopher Schröder and Sven Rahmann
Algorithms for Molecular Biology
Christopher Schröder and Sven Rahmann
Algorithms for Molecular Biology
Christopher Schröder*, Elsa Leitão*, Stefan Wallner, Gerd Schmitz, Ludger Klein-Hitpass, Anupam Sinha, Karl-Heinz Jöckel, Stefanie Heilmann-Heimbach, Per Hoffmann, Markus M. Nöthen, Michael Steffens, Peter Ebert, Sven Rahmann and Bernhard Horsthemke
* Contributed equally
Epigenetics & Chromatin 2017
There is increasing evidence for inter-individual methylation differences at CpG dinucleotides in the human genome, but the regional extent and function of these differences have not yet been studied in detail. For identifying regions of common methylation differences, we used whole genome bisulfite sequencing data of monocytes from five donors and a novel bioinformatic strategy.
We identified 157 differentially methylated regions (DMRs) with four or more CpGs, almost none of which has been described before. The DMRs fall into different chromatin states, where methylation is inversely correlated with active, but not repressive histone marks. However, methylation is not correlated with the expression of associated genes. High-resolution single nucleotide polymorphism (SNP) genotyping of the five donors revealed evidence for a role of cis-acting genetic variation in establishing methylation patterns. To validate this finding in a larger cohort, we performed genome-wide association studies (GWAS) using SNP genotypes and 450k array methylation data from blood samples of 1128 individuals. Only 30/157 (19%) DMRs include at least one 450k CpG, which shows that these arrays miss a large proportion of DNA methylation variation. In most cases, the GWAS peak overlapped the CpG position, and these regions are enriched for CREB group, NF-1, Sp100 and CTCF binding motifs. In two cases, there was tentative evidence for a trans-effect by KRAB zinc finger proteins.
Allele-specific DNA methylation occurs in discrete chromosomal regions and is driven by genetic variation in cis and trans, but in general has little effect on gene expression
Christopher Schröder, Daniela Beißer and Sven Rahmann from the Genome Informatics group contributed to novel insights about epigenetic changes during cell differentiation. The article will appear soon in the renowned “Epigenetics & Chromatin” journal (IF 4.873) by BioMedCentral.
Epigenetic dynamics of monocyte to macrophage differentiation
by Stefan Wallner, Christopher Schröder, Elsa Leitão, Tea Berulava, Claudia
Haak, Daniela Beißer, Sven Rahmann, Andreas S Richter, Thomas Manke,
Ulrike Böhnisch, Laura Arrigoni, Sebastian Fröhler, Filippos Klironomos,
Wei Chen, Nikolaus Rajewsky, Fabian Müller, Peter Ebert, Thomas
Lengauer, Matthias Barann, Philip Rosenstiel, Gilles Gasparoni, Karl
Nordström, Jörn Walter, Benedikt Brors, Gideon Zipprich, Bärbel Felder,
Ludger Klein-Hitpass, Corinna Attenberger, Gerd Schmitz, Bernhard Horsthemke
Monocyte to macrophage differentiation involves major biochemical and
structural changes. In order to elucidate the role of gene regulatory
changes during this process, we used high-throughput sequencing to
analyze the complete transcriptome and epigenome of human monocytes that
were differentiated in vitro by addition of colony stimulating factor 1
(CSF1) in serum-free medium. Numerous mRNAs and miRNAs were
significantly up- or downregulated. More than 100 discrete DNA regions,
most often far away from transcription start sites, were rapidly
demethylated by the ten-eleven translocation (TET) enzymes, became
nucleosome-free and gained histone marks indicative of active enhancers.
These regions were unique for macrophages and associated with genes
involved in the regulation of the actin cytoskeleton, phagocytosis and
innate immune response. In summary, we have discovered a phagocytic gene
network that is repressed by DNA methylation in monocytes and rapidly
de-repressed after the onset of macrophage differentiation.
An article by Christopher Schröder and Sven Rahmann about estimating parameters of beta mixture models, which has applications in determining the methylation state of genomic regions, has been accepted at WABI 2016 and will be presented at the conference in Aarhus (Danmark), August 22-24, 2016. The paper will be available in the WABI 2016 proceedings (LNBI series, Springer Verlag) in August 2016.
A hybrid parameter estimation algorithm for beta mixtures and applications to methylation state classification
by Christopher Schröder and Sven Rahmann
Mixtures of beta distributions have previously been shown to be a flexible tool for modeling data with values on the unit interval, such as methylation levels. However, maximum likelihood parameter estimation with beta distributions suffers from problems because of singularities in the log-likelihood function if some observations take the values 0 or 1. While ad-hoc corrections have been proposed to mitigate this problem, we propose a different approach to parameter estimation for beta mixtures where such problems do not arise in the first place. Our algorithm has significant computational advantages over the maximum-likelihood-based EM algorithm. As an application, we demonstrate that methylation state classification is more accurate when using adaptive thresholds from beta mixtures than non-adaptive thresholds on observed methylation levels.
Bianca Stöcker; Johannes Köster; Sven Rahmann
SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.
Third generation sequencing methods provide longer reads than second generation methods and have distinct error characteristics.
In a SMRT library the sequenced DNA fragments are circular with adapter sequences between forward and backward strand, and a fragment may be sequenced multiple times in a single run. For a single pass through the sequence (subread), the error rate is high, but it is possible to calculate a consensus after multiple passes (circular consensus sequence read, CCS). Thus the error rate of CCSs decreases with the number of passes.
We analyzed public data from Pacific Biosciences (PacBio) SMRT sequencing, developed an error model and implemented it in a new read simulator called SimLoRD. Reads are simulated from both strands of a provided or randomly generated reference sequence. It offers options to choose the read length distribution and to model error probabilities depending on the number of passes through the sequencer. The new error model makes SimLoRD the most realistic SMRT read simulator available.
Toll‐like receptor (TLR) 13 and TLR2 are the major sensors of Gram‐positive bacteria in mice. TLR13 recognizes Sa19, a specific 23S ribosomal (r) RNA‐derived fragment and bacterial modification of Sa19 ablates binding to TLR13, and to antibiotics such as erythromycin. Similarly, RNase A‐treated Staphylococcus aureus activate human peripheral blood mononuclear cells (PBMCs) only via TLR2, implying single‐stranded (ss) RNA as major stimulant. Continue reading
Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. Continue reading
Evolutionary Origin and Methylation Status of Human Intronic CpG Islands that Are Not Present in Mouse
Rademacher, K., Schröder, C., Kanber, D., Klein-Hitpass, L., Wallner, S., Zeschnigk, M., Horsthemke, B.
Genome Biol Evol 6, 1579–1588 (2014), doi:10.1093/gbe/evu125
Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrocopy derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrocopy and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences.