Bora Uyar

ELM—the database of eukaryotic linear motifs

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.

The eukaryotic linear motif resource ELM: 10 years and counting

The eukaryotic linear motif (ELM http://elm.eu.org) resource is a hub for collecting, classifying and curating information about short linear motifs (SLiMs). For >10 years, this resource has provided the scientific community with a freely accessible guide to the biology and function of linear motifs. The current version of ELM contains ∼200 different motif classes with over 2400 experimentally validated instances manually curated from >2000 scientific publications. Furthermore, detailed information about motif-mediated interactions has been annotated and made available in standard exchange formats. Where appropriate, links are provided to resources such as switches.elm.eu.org and KEGG pathways.

ELM 2016—data update and new functionality of the eukaryotic linear motif resource

The Eukaryotic Linear Motif (ELM) resource (http://elm.eu.org) is a manually curated database of short linear motifs (SLiMs). In this update, we present the latest additions to this resource, along with more improvements to the web interface. ELM 2016 contains more than 240 different motif classes with over 2700 experimentally validated instances, manually curated from more than 2400 scientific publications. In addition, more data have been made available as individually searchable pages and are downloadable in various formats.

Short Linear Motifs: Ubiquitous and Functionally Diverse Protein Interaction Modules Directing Cell Regulation

Interaction Modules Directing Cell Regulation Kim Van Roey,† Bora Uyar,† Robert J. Weatheritt,‡ Holger Dinkel,† Markus Seiler,† Aidan Budd,† Toby J. Gibson,† and Norman E. Davey*,†,§ †Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany ‡MRC Laboratory of Molecular Biology (LMB), Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, United Kingdom Department of Physiology, University of California, San Francisco, San Francisco, California 94143, United States

genBlastG: using BLAST searches to build homologous gene models

MOTIVATION BLAST users frequently expect to obtain homologous genes with certain similarity to their query genes. But what they get from BLAST searches are often collections of local alignments called high-scoring segment pairs (HSPs). On the other hand, most homology-based gene finders have been built using computation-intensive algorithms, without taking full advantage of BLAST searches that have been perfected over the last decades. RESULTS Here we report an efficient algorithm, genBlastG that directly uses the HSPs reported by BLAST to define high-quality gene models. AVAILABILITY http://genome.sfu.ca/genblast/download.html

How pathogens use linear motifs to perturb host cell networks.

Molecular mimicry is one of the powerful stratagems that pathogens employ to colonise their hosts and take advantage of host cell functions to guarantee their replication and dissemination. In particular, several viruses have evolved the ability to interact with host cell components through protein short linear motifs (SLiMs) that mimic host SLiMs, thus facilitating their internalisation and the manipulation of a wide range of cellular networks. Here we present convincing evidence from the literature that motif mimicry also represents an effective, widespread hijacking strategy in prokaryotic and eukaryotic parasites. Further insights into host motif mimicry would be of great help in the elucidation of the molecular mechanisms behind host cell invasion and the development of anti-infective therapeutic strategies.

RNA-seq analysis of the C. briggsae transcriptome

Curation of a high-quality gene set is the critical first step in genome research, enabling subsequent analyses such as ortholog assignment, cis-regulatory element finding, and synteny detection. In this project, we have reannotated the genome of Caenorhabditis briggsae, the best studied sister species of the model organism Caenorhabditis elegans. First, we applied a homology-based gene predictor genBlastG to annotate the C. briggsae genome. We then validated and further improved the C. briggsae gene annotation through RNA-seq analysis of the C. briggsae transcriptome, which resulted in the first validated C. briggsae gene set (23,159 genes), among which 7347 genes (33.9% of all genes with introns) have all of their introns confirmed. Most genes (14,812, or 68.3%) have at least one intron validated, compared with only 3.9% in the most recent WormBase release (WS228). Of all introns in the revised gene set (103,083), 61,503 (60.1%) have been confirmed. Additionally, we have identified numerous trans-splicing leaders (SL1 and SL2 variants) in C. briggsae, leading to the first genome-wide annotation of operons in C. briggsae (1105 operons). The majority of the annotated operons (564, or 51.0%) are perfectly conserved in C. elegans, with an additional 345 operons (or 31.2%) somewhat divergent. Additionally, RNA-seq analysis revealed over 10 thousand small-size assembly errors in the current C. briggsae reference genome that can be readily corrected. The revised C. briggsae genome annotation represents a solid platform for comparative genomics analysis and evolutionary studies of Caenorhabditis species.

Degrons in cancer

Understanding protein degradation signals and systems reveals targets for cancer therapy. Gloss There are many cellular proteins that need to be eliminated quickly in response to changing conditions in or around the cells. Most of these proteins carry a short functional element in their sequence, called a degron. Degrons are typically composed of 6 to 10 amino acids and are generally located within flexible regions of proteins so that the degrons can easily interact with other proteins. E3 ubiquitin ligases bind to specific degrons, enabling the attachment of multiple copies of ubiquitin to target proteins. The ubiquitin chains are a molecular signal that directs the proteins to the proteasome, where the tagged proteins are chopped up into pieces and recycled. The correct removal of proteins is important for many biological processes, such as regulating transcription and controlling the major steps during cell division. Regulated protein degradation also turns off the activity of some proteins that are activated by transient external signals. The encounter between the E3 ligase and the degron determines whether a protein lives or dies. There are ~600 different E3 ligases that are encoded in the human genome. Each of these E3 ligases targets a different set of proteins and operates under a different condition. This ubiquitin-mediated protein degradation process is regulated at multiple levels. Defects in this system can cause systemic diseases, including cancer. This Review with 8 figures, 1 table, and 360 references describes how mutations that affect ubiquitin-mediated protein degradation system contribute to cancer. Degrons are the elements that are used by E3 ubiquitin ligases to target proteins for degradation. Most degrons are short linear motifs embedded within the sequences of modular proteins. As regulatory sites for protein abundance, they are important for many different cellular processes, such as progression through the cell cycle and monitoring cellular hypoxia. Degrons enable the elimination of proteins that are no longer required, preventing their possible dysfunction. Although the human genome encodes ~600 E3 ubiquitin ligases, only a fraction of these enzymes have well-defined target degrons. Thus, for most cellular proteins, the destruction mechanisms are poorly understood. This is important for many diseases, especially for cancer, a disease that involves the enhanced expression of oncogenes and the persistence of encoded oncoproteins coupled with reduced abundance of tumor suppressors. Loss-of-function mutations occur in the degrons of several oncoproteins, such as the transcription factors MYC and NRF2, and in various mitogenic receptors, such as NOTCH1 and several receptor tyrosine kinases. Mutations eliminating the function of the β-catenin degron are found in many cancers and are considered one of the most abundant mutations driving carcinogenesis. In this Review, we describe the current knowledge of degrons in cancer and suggest that increased research on the “dark degrome” (unknown degron-E3 relationships) would enhance progress in cancer research.

Fine tuning of RFX/DAF-19-regulated target gene expression through binding to multiple sites in Caenorhabditis elegans

In humans, mutations of a growing list of regulatory factor X (RFX) target genes have been associated with devastating genetics disease conditions including ciliopathies. However, mechanisms underlying RFX transcription factors (TFs)-mediated gene expression regulation, especially differential gene expression regulation, are largely unknown. In this study, we explore the functional significance of the co-existence of multiple X-box motifs in regulating differential gene expression in Caenorhabditis elegans. We hypothesize that the effect of multiple X-box motifs is not a simple summation of binding effect to individual X-box motifs located within a same gene. To test this hypothesis, we identified eight C. elegans genes that contain two or more X-box motifs using comparative genomics. We examined one of these genes, F25B4.2, which contains two 15-bp X-box motifs. F25B4.2 expression in ciliated neurons is driven by the proximal motif and its expression is repressed by the distal motif. Our data suggest that two X-box motifs cooperate together to regulate the expression of F25B4.2 in location and intensity. We propose that multiple X-box motifs might be required to tune specific expression level. Our identification of genes with multiple X-box motifs will also improve our understanding of RFX/DAF-19-mediated regulation in C. elegans and in other organisms including humans.

RCAS: an RNA centric annotation system for transcriptome-wide regions of interest

Abstract In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de.