Objective The risk loci for juvenile idiopathic arthritis (JIA) consist of extended haplotypes that include functional elements in addition to canonical coding genes. As with most autoimmune diseases, the risk haplotypes for JIA are highly enriched for H3K4me1/H3K27ac histone marks, epigenetic signatures that typically identify poised or active enhancers. In this study, we test the hypothesis that genetic risk for JIA is exerted through altered enhancer-mediated gene regulation. Methods We mined publically available HiC and other chromatin conformation data to determine whether H3K27ac-marked regions in 25 JIA risk loci showed physical evidence of contact with gene promoters. We also used in vitro reporter assays to establish as proof-of-concept the idea that genetic variants in linkage disequilibrium with GWAS-identified tag SNPs alter enhancer function. Results All 25 loci examined showed multiple contact sites in the 4 different cell lines that we queried. These regions were characterized by HiC-defined loop structures that included 237 immune-related genes. Using in vitro assays, we found that a 657 bp, H3K4me1/H3K27-marked region within the first intron of IL2RA shows enhancer activity in reporter assays, and this activity is attenuated by SNPs on the IL2RA haplotype that we identified using whole genome sequencing of children with JIA. Similarly, we identified a 1,669 bp sequence in an intergenic region of the IL6R locus where SNPs identified in children with JIA increase enhancer function in reporter assays. Conclusions These studies provide evidence that altered enhancer function contributes to genetic risk in JIA. Further studies to identify the specific target genes of genetically altered enhancers are warranted.

Working with a combination of ProMOL (a plugin for PyMOL that searches a library of enzymatic motifs for local structural homologs), BLAST and Pfam (servers that identify global sequence homologs), and Dali (a server that identifies global structural homologs), we have begun the process of assigning functional annotations to the approximately 3,500 structures in the Protein Data Bank that are currently classified as having “unknown function”. Using a limited template library of 388 motifs, over 500 promising in silico matches have been identified by ProMOL, among which 65 exceptionally good matches have been identified. The characteristics of the exceptionally good matches are discussed.

BackgroundThe accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues.ResultsProMOL is a plugin for the PyMOL molecular graphics environment that can be used to create active site motifs for enzymes. A library of 181 active site motifs has been created with ProMOL, based on definitions published in the Catalytic Site Atlas (CSA). Searches with ProMOL produce better than 50% useful Enzyme Commission (EC) class suggestions for level 1 searches in EC classes 1, 4 and 5, and produce some useful results for other classes. 261 additional motifs automatically translated from Jonathan Barker’s JESS motif set [Bioinformatics 19:1644–1649, 2003] and a set of NMR motifs is under development. Alignments are evaluated by visual superposition, Levenshtein distance and root-mean-square deviation (RMSD) and are reasonably consistent with related search methods.ConclusionThe ProMOL plugin for PyMOL provides ready access to template-based local alignments. Recent improvements to ProMOL, including the expanded motif library, RMSD calculations and output selection formatting, have greatly increased the program’s usability and speed, and have improved the way that the results are presented.

The presence of abnormal gene expression signatures is a well-described feature of the oligoarticular and polyarticular forms of juvenile idiopathic arthritis. In this review, we discuss how new insights into genetic risk for JIA and the three dimensional architecture of the genome may be used to develop a better understanding of the mechanisms driving these gene expression patterns.

BackgroundOur group has shown that, like most complex traits, the risk loci for juvenile idiopathic arthritis (JIA) identified on genome-wide association studies (GWAS) and genetic fine mapping studies are highly enriched for enhancers. Enhancers are regulatory elements that fine-tune gene expression to specific physiologic circumstances. Enhancers do not always regulate the nearest gene, and may regulate more than one gene. Enhancers typically regulate genes within the same chromatin loop, or topologically associated domain (TAD).ObjectivesTo gain a better understanding of the genetics of JIA by examining the broader chromatin architecture that encompasses the known risk haplotypes.MethodsWe used publically available chromatin conformation HiC data and the online JuiceBox software suite to query known JIA risk haplotypes for evidence of physical interactions between putative enhancers within the haplotypes and immunologically relevant genes. We specifically queried 20 haplotypes in which H3K4me1/H3K27ac marks were prominent within both lymphoid and myeloid cells. We queried data from GM12787 (B cell), K562 (lymphoblast), and THP-1 (monocyte/macrophage) cells, as well as human cord blood T cells. To identify TADs associated with specific enhancers, we used a 5KB resolution (which allowed us to visualize chromatin loops as peaks), setting the cursor at the center of each putative enhancer. We also identified the genes within the identified chromatin loop domains and used gene ontology (GO) analyses to identify functional associations among genes within the TADs incorporating the JIA risk loci.ResultsWe identified at least one chromatin loop structure in all 20 of the JIA risk haplotypes for each of the 4 cell lines we queried. These loops were not cell type specific. That is, almost identical loops structures could be seen in each of the cell lines at each of the loci, suggesting that these enhancers regulate a broad range of common leukocyte functions. The TADs incorporating the JIA haplotypes invariably included genes of immunologic interest. For example, the TAD incorporating the IL2RA haplotype including IL15R (the alpha chain of the IL15 receptor) and PKCQ, a protein kinase C-family enzyme important in both T and B cell activation. The most complex locus was C5orf56 which encompassed 23 genes (including IL3, IL4, and IL13) and 3 miRNA within 4 loops and sub-loops. Genes within the TADs were highly enriched for multiple GO terms for processes involved in leukocyte activation (e.g., MAP kinase signaling cascade), JAK-STAT responses, chemotaxis, and cytokine-mediated signaling pathways.ConclusionThese 20 JIA-associated risk loci are situated within complex chromatin regions that show similar features in both lymphoid and myeloid cells. HiC data demonstrate direct physical contacts between putative enhancers within the risk loci and multiple genes of immunologic interest. We hypothesize that at least some of the genes within the haplotype-associated TADs are the long sought “target genes” of JIA-associated genetic...