Andreas Heger

Pfam: the protein families database

Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.

Sequencing depth and coverage: key considerations in genomic analyses

Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP–seq) and chromosome conformation capture (3C)).

Targeting Polycomb to Pericentric Heterochromatin in Embryonic Stem Cells Reveals a Role for H2AK119u1 in PRC2 Recruitment

Summary The mechanisms by which the major Polycomb group (PcG) complexes PRC1 and PRC2 are recruited to target sites in vertebrate cells are not well understood. Building on recent studies that determined a reciprocal relationship between DNA methylation and Polycomb activity, we demonstrate that, in methylation-deficient embryonic stem cells (ESCs), CpG density combined with antagonistic effects of H3K9me3 and H3K36me3 redirects PcG complexes to pericentric heterochromatin and gene-rich domains. Surprisingly, we find that PRC1-linked H2A monoubiquitylation is sufficient to recruit PRC2 to chromatin in vivo, suggesting a mechanism through which recognition of unmethylated CpG determines the localization of both PRC1 and PRC2 at canonical and atypical target sites. We discuss our data in light of emerging evidence suggesting that PcG recruitment is a default state at licensed chromatin sites, mediated by interplay between CpG hypomethylation and counteracting H3 tail modifications.

Long non-coding RNAs and enhancer RNAs regulate the lipopolysaccharide-induced inflammatory response in human monocytes

Early reports indicate that long non-coding RNAs (lncRNAs) are novel regulators of biological responses. However, their role in the human innate immune response, which provides the initial defence against infection, is largely unexplored. To address this issue, here we characterize the long non-coding RNA transcriptome in primary human monocytes using RNA sequencing. We identify 76 enhancer RNAs (eRNAs), 40 canonical lncRNAs, 65 antisense lncRNAs and 35 regions of bidirectional transcription (RBT) that are differentially expressed in response to bacterial lipopolysaccharide (LPS). Crucially, we demonstrate that knockdown of nuclear-localized, NF-κB-regulated, eRNAs (IL1β-eRNA) and RBT (IL1β-RBT46) surrounding the IL1β locus, attenuates LPS-induced messenger RNA transcription and release of the proinflammatory mediators, IL1β and CXCL8. We predict that lncRNAs can be important regulators of the human innate immune response.

Population and single cell genomics reveal the Aire-dependency, relief from Polycomb silencing and distribution of self-antigen expression in thymic epithelia

Promiscuous gene expression (PGE) by thymic epithelial cells (TEC) is essential for generating a diverse T cell antigen receptor repertoire tolerant to self-antigens, and thus for avoiding autoimmunity. Nevertheless, the extent and nature of this unusual expression program within TEC populations and single cells are unknown. Using deep transcriptome sequencing of carefully identified mouse TEC subpopulations, we discovered a program of PGE that is common between medullary (m) and cortical TEC, further elaborated in mTEC, and completed in mature mTEC expressing the autoimmune regulator gene (Aire). TEC populations are capable of expressing up to 19,293 protein-coding genes, the highest number of genes known to be expressed in any cell type. Remarkably, in mouse mTEC, Aire expression alone positively regulates 3980 tissue-restricted genes. Notably, the tissue specificities of these genes include known targets of autoimmunity in human AIRE deficiency. Led by the observation that genes induced by Aire expression are generally characterized by a repressive chromatin state in somatic tissues, we found these genes to be strongly associated with H3K27me3 marks in mTEC. Our findings are consistent with AIRE targeting and inducing the promiscuous expression of genes previously epigenetically silenced by Polycomb group proteins. Comparison of the transcriptomes of 174 single mTEC indicates that genes induced by Aire expression are transcribed stochastically at low cell frequency. Furthermore, when present, Aire expression-dependent transcript levels were 16-fold higher, on average, in individual TEC than in the mTEC population.

Epigenetic conservation at gene regulatory elements revealed by non-methylated DNA profiling in seven vertebrates

Two-thirds of gene promoters in mammals are associated with regions of non-methylated DNA, called CpG islands (CGIs), which counteract the repressive effects of DNA methylation on chromatin. In cold-blooded vertebrates, computational CGI predictions often reside away from gene promoters, suggesting a major divergence in gene promoter architecture across vertebrates. By experimentally identifying non-methylated DNA in the genomes of seven diverse vertebrates, we instead reveal that non-methylated islands (NMIs) of DNA are a central feature of vertebrate gene promoters. Furthermore, NMIs are present at orthologous genes across vast evolutionary distances, revealing a surprising level of conservation in this epigenetic feature. By profiling NMIs in different tissues and developmental stages we uncover a unifying set of features that are central to the function of NMIs in vertebrates. Together these findings demonstrate an ancient logic for NMI usage at gene promoters and reveal an unprecedented level of epigenetic conservation across vertebrate evolution. DOI: http://dx.doi.org/10.7554/eLife.00348.001

Next-generation sequencing of advanced prostate cancer treated with androgen-deprivation therapy.

BACKGROUNDnAndrogen-deprivation therapy (ADT) is standard treatment for locally advanced or metastatic prostate cancer (PCa). Many patients develop castration resistance (castration-resistant PCa [CRPC]) after approximately 2-3 yr, with a poor prognosis. The molecular mechanisms underlying CRPC progression are unclear.nnnOBJECTIVEnTo undertake quantitative tumour transcriptome profiling prior to and following ADT to identify functionally important androgen-regulated pathways or genes that may be reactivated in CRPC.nnnDESIGN, SETTING, AND PARTICIPANTSnRNA sequencing (RNA-seq) was performed on tumour-rich, targeted prostatic biopsies from seven patients with locally advanced or metastatic PCa before and approximately 22 wk after ADT initiation. Differentially regulated genes were identified in treatment pairs and further investigated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on cell lines and immunohistochemistry on a separate CRPC patient cohort. Functional assays were used to determine the effect of pathway modulation on cell phenotypes.nnnOUTCOME MEASUREMENTS AND STATISTICAL ANALYSISnWe searched for gene expression changes affecting key cell signalling pathways that may be targeted as proof of principle in a CRPC in vitro cell line model.nnnRESULTS AND LIMITATIONSnWe identified ADT-regulated signalling pathways, including the Wnt/β-catenin signalling pathway, and observed overexpression of β-catenin in a subset of CRPC by immunohistochemistry. We validated 6 of 12 (50%) pathway members by qRT-PCR on LNCaP/LNCaP-AI cell RNAs, of which 4 (67%) demonstrated expression changes consistent with RNA-seq data. We show that the tankyrase inhibitor XAV939 (which promotes β-catenin degradation) reduced androgen-independent LNCaP-AI cell line growth compared with androgen-responsive LNCaP cells via an accumulation of cell proportions in the G0/G1 phase and reduction in the S and G2/M phases. Our biopsy protocol did not account for tumour heterogeneity, and pathway inhibition was limited to pharmacologic approaches.nnnCONCLUSIONSnRNA-seq of paired PCa samples revealed ADT-regulated signalling pathways. Proof-of-principle inhibition of the Wnt/β-catenin signalling pathway specifically delays androgen-independent PCa cell cycle progression and proliferation and warrants further investigation as a potential target for therapy for CRPC.

GAT: a simulation framework for testing the association of genomic intervals.

Motivation: A common question in genomic analysis is whether two sets of genomic intervals overlap significantly. This question arises, for example, when interpreting ChIP-Seq or RNA-Seq data in functional terms. Because genome organization is complex, answering this question is non-trivial. Summary: We present Genomic Association Test (GAT), a tool for estimating the significance of overlap between multiple sets of genomic intervals. GAT implements a null model that the two sets of intervals are placed independently of one another, but allows each set’s density to depend on external variables, for example, isochore structure or chromosome identity. GAT estimates statistical significance based on simulation and controls for multiple tests using the false discovery rate. Availability: GAT’s source code, documentation and tutorials are available at http://code.google.com/p/genomic-association-tester. Contact: andreas.heger@dpag.ox.ac.uk

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package.

IRF5:RelA Interaction Targets Inflammatory Genes in Macrophages

Summary Interferon Regulatory Factor 5 (IRF5) plays a major role in setting up an inflammatory macrophage phenotype, but the molecular basis of its transcriptional activity is not fully understood. In this study, we conduct a comprehensive genome-wide analysis of IRF5 recruitment in macrophages stimulated with bacterial lipopolysaccharide and discover that IRF5 binds to regulatory elements of highly transcribed genes. Analysis of protein:DNA microarrays demonstrates that IRF5 recognizes the canonical IRF-binding (interferon-stimulated response element [ISRE]) motif in vitro. However, IRF5 binding in vivo appears to rely on its interactions with other proteins. IRF5 binds to a noncanonical composite PU.1:ISRE motif, and its recruitment is aided by RelA. Global gene expression analysis in macrophages deficient in IRF5 and RelA highlights the direct role of the RelA:IRF5 cistrome in regulation of a subset of key inflammatory genes. We map the RelA:IRF5 interaction domain and suggest that interfering with it would offer selective targeting of macrophage inflammatory activities.