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Cockayne syndrome (CS) and UV-sensitivity syndrome (UVSS) are rare genetic disorders caused by mutation of the DNA repair and chromatin remodelling proteins CSA or CSB, but only CS patients display a progeroid and neurodegenerative phenotype. As epigenetic modifications constitute a well-established hallmark of ageing, we characterized genome-wide DNA methylation (DNAm) of fibroblasts from CS versus UVSS patients and healthy donors. The analysis of differentially methylated positions and regions revealed a CS-specific epigenetic signature, enriched in developmental transcription factors, transmembrane transporters, and cell adhesion factors. The CS-specific signature compared to DNAm changes in other progeroid diseases and regular ageing, identifyied commonalities and differences in epigenetic remodelling. CS shares DNAm changes with normal ageing more than other progeroid diseases do, and according to the methylation clock CS samples show up to 13-fold accelerated ageing. Thus, CS is characterized by a specific epigenomic signature that partially overlaps with and exacerbates DNAm changes occurring in physiological aging. Our results unveil new genes and pathways that are potentially relevant for the progeroid/degenerative CS phenotype.

We present ChIPflow, a Snakemake-based pipeline for epigenomic data from the raw fastq files to the differential analysis. It can be applied to any chromatin factor, e.g. histone modification or transcription factor, which can be profiled with ChIP-seq. ChIPflow streamlines critical steps like the quality assessment of the immunoprecipitation using cross-correlation and the replicate comparison for both narrow and broad peaks. For the differential analysis ChIPflow provides linear and nonlinear methods for normalisation between samples as well as conservative and stringent models for estimating the variance and testing the significance of the observed binding/marking differences.ChIPflow can process in parallel multiple chromatin factors with different experimental designs, number of biological replicates and/or conditions. It also facilitates the specific parametrisation of each dataset allowing both narrow or broad peak calling, as well as comparisons between the conditions using multiple statistical settings. Finally, complete reports are produced at the end of the bioinformatic and the statistical part of the analysis, which facilitate the data quality control and the interpretation of the results.We explored the discriminative power of the statistical settings for the differential analysis, using a published dataset of three histone marks (H3K4me3, H3K27ac and H3K4me1) and two transcription factors (Oct4 and Klf4) profiled with ChIP-seq in two biological conditions (shControl and shUbc9). We show that distinct results are obtained depending on the sources of ChIP-seq variability and the dynamics of the chromatin factor under study. We propose that ChIPflow can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes and the associated genes sets.

Virulence of the neonatal pathogen Group B Streptococcus depends on the master regulator CovR. Inactivation of CovR leads to large-scale transcriptome remodeling and impairs almost every step of the interaction between the pathogen and the host. However, comparative analyses suggested a plasticity of the CovR signalling pathway in clinical isolates, probably due to the host selective pressure and leading to phenotypic heterogeneity in the bacterial population. Here, we characterize the CovR regulatory network in a strain representative of the hypervirulent lineage responsible of the majority of late-onset meningitidis. Genome-wide binding and transcriptome analysis demonstrated that CovR acts as a direct and global repressor of virulence genes, either as a primary regulator or with specialized co-regulators. Remarkably, CovR directly regulates genes of the pan-genome, including the two specific hypervirulent adhesins and horizontally acquired genes, as well as core-genes showing mutational biases in the population. Parallel analysis of the CovR network in a second isolate links strain-specificities to micro-evolutions in CovR-regulated promoters and to broad difference due to variability in CovR activation by phosphorylation. Our results highlight the direct, coordinated, and strain-specific regulation of virulence genes by CovR. This intra-species evolution of the signalling network reshapes bacterial-host interactions, increasing the potential for adaptation and the emergence of clone associated with specific diseases.

Motivation: KEN-box-mediated target selection is one of the mechanisms used in the proteasomal destruction of mitotic cell cycle proteins via the APC/C complex. While annotating the Eukaryotic Linear Motif resource (ELM, http://elm.eu.org/), we found that KEN motifs were significantly enriched in human protein entries with cell cycle keywords in the UniProt/Swiss-Prot database—implying that KEN-boxes might be more common than reported. Results: Matches to short linear motifs in protein database searches are not, per se, significant. KEN-box enrichment with cell cycle Gene Ontology terms suggests that collectively these motifs are functional but does not prove that any given instance is so. Candidates were surveyed for native disorder prediction using GlobPlot and IUPred and for motif conservation in homologues. Among >25 strong new candidates, the most notable are human HIPK2, CHFR, CDC27, Dab2, Upf2, kinesin Eg5, DNA Topoisomerase 1 and yeast Cdc5 and Swi5. A similar number of weaker candidates were present. These proteins have yet to be tested for APC/C targeted destruction, providing potential new avenues of research. Contact: toby.gibson@embl.de Supplementary information: Tables of KEN-box candidates and keyword/conservation significance assessments are available as supplementary data at Bioinformatics online.

Despite evolutionary conserved mechanisms to silence transposable element activity, there are drastic differences in the abundance of transposable elements even among closely related plant species. We conducted a de novo assembly for the 375 Mb genome of the perennial model plant, Arabis alpina. Analysing this genome revealed long-lasting and recent transposable element activity predominately driven by Gypsy long terminal repeat retrotransposons, which extended the low-recombining pericentromeres and transformed large formerly euchromatic regions into repeat-rich pericentromeric regions. This reduced capacity for long terminal repeat retrotransposon silencing and removal in A. alpina co-occurs with unexpectedly low levels of DNA methylation. Most remarkably, the striking reduction of symmetrical CG and CHG methylation suggests weakened DNA methylation maintenance in A. alpina compared with Arabidopsis thaliana. Phylogenetic analyses indicate a highly dynamic evolution of some components of methylation maintenance machinery that might be related to the unique methylation in A. alpina. Fil: Willing, Eva Maria. Max Planck Institute for Plant Breeding Research; Alemania Fil: Rawat, Vimal. Central European Institute of Technology; República Checa Fil: Mandáková, Terezie. Central European Institute of Technology; República Checa Fil: Maumus, Florian. INRA. Research Unit in Genomics; Francia Fil: James, Geo Velikkakam. Max Planck Institute for Plant Breeding Research; Alemania Fil: Nordström, Karl J. V.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Becker, Claude. Max Planck Institute for Developmental Biology; Alemania Fil: Warthmann, Norman. Max Planck Institute for Developmental Biology; Alemania. The Australian National University; Australia Fil: Chica, Claudia. Centre National de la Recherche Scientifique; Francia Fil: Szarzynska, Bogna. Centre National de la Recherche Scientifique; Francia Fil: Zytnicki, Matthias. Max Planck Institute for Developmental Biology; Alemania Fil: Albani, Maria C.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Kiefer, Christiane. Max Planck Institute for Plant Breeding Research; Alemania Fil: Bergonzi, Sara. Max Planck Institute for Plant Breeding Research; Alemania Fil: Castaings, Loren. Max Planck Institute for Plant Breeding Research; Alemania Fil: Mateos, Julieta Lisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute for Plant Breeding Research; Alemania Fil: Berns, Markus C.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Bujdoso, Nora. Max Planck Institute for Plant Breeding Research; Alemania Fil: Piofczyk, Thomas. Max Planck Institute for Plant Breeding Research; Alemania Fil: Roudier, François. Centre National de la Recherche Scientifique; Francia Fil: Carbonero, Pilar. Universidad Politécnica de Madrid; España Fil: Paz Ares, Javier. Consejo Superior de Investigaciones Cientificas; España Fil: Davis, Seth J.. Max Planck Institute for Plant Breeding Research; Alemania Fil: Pecinka, Ales. Max Planck Institute for Plant Breeding Research; Alemania Fil: Quesneville, Hadi. INRA. Research Unit in Genomics; Francia Fil: Colot, Vincent. Centre National de la Recherche Scientifique; Francia Fil: Lysak, Martin A.. Central European Institute of Technology; República Checa Fil: Weigel, Detlef. Max Planck Institute for Developmental Biology; Alemania Fil: Coupland, George. Max Planck Institute for Plant Breeding Research; Alemania Fil: Schneeberger, Korbinian. Max Planck Institute for Plant Breeding Research; Alemania

Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances. Author has checked copyright DG 09/11/12 Names (!) JG 2012-11-26

Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict de novo in protein sequences due to the difficulty of obtaining robust statistical assessments. The ELM resource at http://elm.eu.org/ provides an expanding knowledge base, currently covering 146 known motifs, with annotation that includes >1300 experimentally reported instances. ELM is also an exploratory tool for suggesting new candidates of known linear motifs in proteins of interest. Information about protein domains, protein structure and native disorder, cellular and taxonomic contexts is used to reduce or deprecate false positive matches. Results are graphically displayed in a ‘Bar Code’ format, which also displays known instances from homologous proteins through a novel ‘Instance Mapper’ protocol based on PHI-BLAST. ELM server output provides links to the ELM annotation as well as to a number of remote resources. Using the links, researchers can explore the motifs, proteins, complex structures and associated literature to evaluate whether candidate motifs might be worth experimental investigation. publishedVersion

It is now clear that a detailed picture of cell regulation requires a comprehensive understanding of the abundant short protein motifs through which signaling is channeled. The current body of knowledge has slowly accumulated through piecemeal experimental investigation of individual motifs in signaling. Computational methods contributed little to this process. A new generation of bioinformatics tools will aid the future investigation of motifs in regulatory proteins, and the disordered polypeptide regions in which they frequently reside. Allied to high throughput methods such as phosphoproteomics, signaling networks are becoming amenable to experimental deconstruction. In this review, we summarise the current state of linear motif biology, which uses low affinity interactions to create cooperative, combinatorial and highly dynamic regulatory protein complexes. The discrete deterministic properties implicit to these assemblies suggest that models for cell regulatory networks in systems biology should neither be overly dependent on stochastic nor on smooth deterministic approximations.

Background Linear motifs (LMs) are abundant short regulatory sites used for modulating the functions of many eukaryotic proteins. They play important roles in post-translational modification, cell compartment targeting, docking sites for regulatory complex assembly and protein processing and cleavage. Methods for LM detection are now being developed that are strongly dependent on scores for motif conservation in homologous proteins. However, most LMs are found in natively disordered polypeptide segments that evolve rapidly, unhindered by structural constraints on the sequence. These regions of modular proteins are difficult to align using classical multiple sequence alignment programs that are specifically optimised to align the globular domains. As a consequence, poor motif alignment quality is hindering efforts to detect new LMs. Results We have developed a new benchmark, as part of the BAliBASE suite, designed to assess the ability of standard multiple alignment methods to detect and align LMs. The reference alignments are organised into different test sets representing real alignment problems and contain examples of experimentally verified functional motifs, extracted from the Eukaryotic Linear Motif (ELM) database. The benchmark has been used to evaluate and compare a number of multiple alignment programs. With distantly related proteins, the worst alignment program correctly aligns 48% of LMs compared to 73% for the best program. However, the performance of all the programs is adversely affected by the introduction of other sequences containing false positive motifs. The ranking of the alignment programs based on LM alignment quality is similar to that observed when considering full-length protein alignments, however little correlation was observed between LM and overall alignment quality for individual alignment test cases. Conclusion We have shown that none of the programs currently available is capable of reliably aligning LMs in distantly related sequences and we have highlighted a number of specific problems. The results of the tests suggest possible ways to improve program accuracy for difficult, divergent sequences.

Background The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. Results We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree) and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. Conclusion The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable.

SUMMARYSenescent cells play important physiological- and pathophysiological roles in tumor suppression, tissue regeneration, and aging. While select genetic and epigenetic elements crucial for senescence induction were identified, the dynamics, underlying epigenetic mechanisms, and regulatory networks defining senescence competence, induction and maintenance remain poorly understood, precluding a deliberate therapeutic manipulation of these dynamic processes. Here, we show, using dynamic analyses of transcriptome and epigenome profiles, that the epigenetic state of enhancers predetermines their sequential activation during senescence. We demonstrate that activator protein 1 (AP-1) ‘imprints’ the senescence enhancer landscape effectively regulating transcriptional activities pertinent to the timely execution of the senescence program. We define and validate a hierarchical transcription factor (TF) network model and demonstrate its effectiveness for the design of senescence reprogramming experiments. Together, our findings define the dynamic nature and organizational principles of gene-regulatory elements driving the senescence program and reveal promising inroads for therapeutic manipulation of senescent cells.