Lydia Steiner

The p53-p21-DREAM-CDE/CHR pathway regulates G2/M cell cycle genes

The tumor suppressor p53 functions predominantly as a transcription factor by activating and downregulating gene expression, leading to cell cycle arrest or apoptosis. p53 was shown to indirectly repress transcription of the CCNB2, KIF23 and PLK4 cell cycle genes through the recently discovered p53-p21-DREAM-CDE/CHR pathway. However, it remained unclear whether this pathway is commonly used. Here, we identify genes regulated by p53 through this pathway in a genome-wide computational approach. The bioinformatic analysis is based on genome-wide DREAM complex binding data, p53-depedent mRNA expression data and a genome-wide definition of phylogenetically conserved CHR promoter elements. We find 210 target genes that are expected to be regulated by the p53-p21-DREAM-CDE/CHR pathway. The target gene list was verified by detailed analysis of p53-dependent repression of the cell cycle genes B-MYB (MYBL2), BUB1, CCNA2, CCNB1, CHEK2, MELK, POLD1, RAD18 and RAD54L. Most of the 210 target genes are essential regulators of G2 phase and mitosis. Thus, downregulation of these genes through the p53-p21-DREAM-CDE/CHR pathway appears to be a principal mechanism for G2/M cell cycle arrest by p53.

A Pipeline for Computational Historical Linguistics

There are many parallels between historical linguistics and molecular phylogenetics. In this paper we describe an algorithmic pipeline that mimics, as closely as possible, the traditional workflow of language reconstruction known as the comparative method. The pipeline consists of suitably modified algorithms based on recent research in bioinformatics, which are adapted to the specifics of linguistic data. This approach can alleviate much of the laborious research needed to establish proof of historical relationships between languages. Equally important to our proposal is that each step in the workflow of the comparative method is implemented independently, so language specialists have the possibility to scrutinize intermediate results. We have used our pipeline to investigate two groups of languages, the Tsezic languages of the Caucasus and the Mataco-Guaicuruan languages of South America, based on the lexical data from the Intercontinental Dictionary Series (IDS). The results of these tests show that the current approach is a viable and useful extension to historical linguistic research.

The transcription factor p53: not a repressor, solely an activator.

The predominant function of the tumor suppressor p53 is transcriptional regulation. It is generally accepted that p53-dependent transcriptional activation occurs by binding to a specific recognition site in promoters of target genes. Additionally, several models for p53-dependent transcriptional repression have been postulated. Here, we evaluate these models based on a computational meta-analysis of genome-wide data. Surprisingly, several major models of p53-dependent gene regulation are implausible. Meta-analysis of large-scale data is unable to confirm reports on directly repressed p53 target genes and falsifies models of direct repression. This notion is supported by experimental re-analysis of representative genes reported as directly repressed by p53. Therefore, p53 is not a direct repressor of transcription, but solely activates its target genes. Moreover, models based on interference of p53 with activating transcription factors as well as models based on the function of ncRNAs are also not supported by the meta-analysis. As an alternative to models of direct repression, the meta-analysis leads to the conclusion that p53 represses transcription indirectly by activation of the p53-p21-DREAM/RB pathway.

Transcriptional regulation by histone modifications: towards a theory of chromatin re-organization during stem cell differentiation

Chromatin-related mechanisms, as e.g. histone modifications, are known to be involved in regulatory switches within the transcriptome. Only recently, mathematical models of these mechanisms have been established. So far they have not been applied to genome-wide data. We here introduce a mathematical model of transcriptional regulation by histone modifications and apply it to data of trimethylation of histone 3 at lysine 4 (H3K4me3) and 27 (H3K27me3) in mouse pluripotent and lineage-committed cells. The model describes binding of protein complexes to chromatin which are capable of reading and writing histone marks. Molecular interactions of the complexes with DNA and modified histones create a regulatory switch of transcriptional activity. The regulatory states of the switch depend on the activity of histone (de-) methylases, the strength of complex-DNA-binding and the number of nucleosomes capable of cooperatively contributing to complex-binding. Our model explains experimentally measured length distributions of modified chromatin regions. It suggests (i) that high CpG-density facilitates recruitment of the modifying complexes in embryonic stem cells and (ii) that re-organization of extended chromatin regions during lineage specification into neuronal progenitor cells requires targeted de-modification. Our approach represents a basic step towards multi-scale models of transcriptional control during development and lineage specification.

Modeling the dynamic epigenome: from histone modifications towards self-organizing chromatin

Epigenetic mechanisms play an important role in regulating and stabilizing functional states of living cells. However, in spite of an increasing amount of experimental data, models of transcriptional regulation by epigenetic processes, in particular by histone modifications, are rather rare. In this article, we focus on epigenetic modes of transcriptional regulation based on histone modifications and their potential dynamical interplay with DNA methylation and higher-order chromatin structure. The main purpose of this article is to review recent formal modeling approaches to the dynamics and propagation of histone modifications and to relate them to available experimental data. We evaluate their assumptions with respect to recruitment of relevant modifiers, establishment and processing of modifications, and compare the emerging stability properties and memory effects. Theoretical predictions that await experimental validation are highlighted and potential extensions of these models towards multiscale models of self-organizing chromatin are discussed.

A Global Genome Segmentation Method for Exploration of Epigenetic Patterns

Current genome-wide ChIP-seq experiments on different epigenetic marks aim at unraveling the interplay between their regulation mechanisms. Published evaluation tools, however, allow testing for predefined hypotheses only. Here, we present a novel method for annotation-independent exploration of epigenetic data and their inter-correlation with other genome-wide features. Our method is based on a combinatorial genome segmentation solely using information on combinations of epigenetic marks. It does not require prior knowledge about the data (e.g. gene positions), but allows integrating the data in a straightforward manner. Thereby, it combines compression, clustering and visualization of the data in a single tool. Our method provides intuitive maps of epigenetic patterns across multiple levels of organization, e.g. of the co-occurrence of different epigenetic marks in different cell types. Thus, it facilitates the formulation of new hypotheses on the principles of epigenetic regulation. We apply our method to histone modification data on trimethylation of histone H3 at lysine 4, 9 and 27 in multi-potent and lineage-primed mouse cells, analyzing their combinatorial modification pattern as well as differentiation-related changes of single modifications. We demonstrate that our method is capable of reproducing recent findings of gene centered approaches, e.g. correlations between CpG-density and the analyzed histone modifications. Moreover, combining the clustered epigenetic data with information on the expression status of associated genes we classify differences in epigenetic status of e.g. house-keeping genes versus differentiation-related genes. Visualizing the distribution of modification states on the chromosomes, we discover strong patterns for chromosome X. For example, exclusively H3K9me3 marked segments are enriched, while poised and active states are rare. Hence, our method also provides new insights into chromosome-specific epigenetic patterns, opening up new questions how “epigenetic computation” is distributed over the genome in space and time.

The ancestor of modern Holozoa acquired the CCA-adding enzyme from Alphaproteobacteria by horizontal gene transfer

Transfer RNAs (tRNAs) require the absolutely conserved sequence motif CCA at their 3′-ends, representing the site of aminoacylation. In the majority of organisms, this trinucleotide sequence is not encoded in the genome and thus has to be added post-transcriptionally by the CCA-adding enzyme, a specialized nucleotidyltransferase. In eukaryotic genomes this ubiquitous and highly conserved enzyme family is usually represented by a single gene copy. Analysis of published sequence data allows us to pin down the unusual evolution of eukaryotic CCA-adding enzymes. We show that the CCA-adding enzymes of animals originated from a horizontal gene transfer event in the stem lineage of Holozoa, i.e. Metazoa (animals) and their unicellular relatives, the Choanozoa. The tRNA nucleotidyltransferase, acquired from an α-proteobacterium, replaced the ancestral enzyme in Metazoa. However, in Choanoflagellata, the group of Choanozoa that is closest to Metazoa, both the ancestral and the horizontally transferred CCA-adding enzymes have survived. Furthermore, our data refute a mitochondrial origin of the animal tRNA nucleotidyltransferases.