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Irritable bowel syndrome (IBS) results from disordered brain–gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (rg > 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain–gut interactions underlying IBS.

Chromosome conformation capture (3C) provides an adaptable tool for studying diverse biological questions. Current 3C methods generally provide either low-resolution interaction profiles across the entire genome, or high-resolution interaction profiles at limited numbers of loci. Due to technical limitations, generation of reproducible high-resolution interaction profiles has not been achieved at genome-wide scale. Here, to overcome this barrier, we systematically test each step of 3C and report two improvements over current methods. We show that up to 30% of reporter events generated using the popular in situ 3C method arise from ligations between two individual nuclei, but this noise can be almost entirely eliminated by isolating intact nuclei after ligation. Using Nuclear-Titrated Capture-C, we generate reproducible high-resolution genome-wide 3C interaction profiles by targeting 8055 gene promoters in erythroid cells. By pairing high-resolution 3C interaction calls with nascent gene expression we interrogate the role of promoter hubs and super-enhancers in gene regulation.

Summary Gut dysmotility is associated with constipation, diarrhea, and functional gastrointestinal disorders like irritable bowel syndrome (IBS), although its molecular underpinnings are poorly characterized. We studied stool frequency (defined by the number of bowel movements per day, based on questionnaire data) as a proxy for gut motility in a GWAS meta-analysis including 167,875 individuals from UK Biobank and four smaller population-based cohorts. We identify 14 loci associated with stool frequency (p ≤ 5.0 × 10 −8 ). Gene set and pathway analyses detected enrichment for genes involved in neurotransmitter/neuropeptide signaling and preferentially expressed in enteric motor neurons controlling peristalsis. PheWAS identified pleiotropic associations with dysmotility syndromes and the response to their pharmacological treatment. The genetic architecture of stool frequency correlates with that of IBS, and UK Biobank participants from the top 1% of stool frequency polygenic score distribution were associated with 5× higher risk of IBS with diarrhea. These findings pave the way for the identification of actionable pathological mechanisms in IBS and the dysmotility syndromes.

Competing interests P.F.P. is currently an employee of Inivata Limited. J.C. is currently an employee of AstraZeneca and may or may not own stock options. M.S. is a cofounder of Enhanc3D Genomics Ltd. The rest of the authors declare no competing interests.

33Japan 34 35 ABSTRACT 37 Genome-wide association studies (GWAS) have identified over 150,000 links between 38 common genetic variants and human traits or complex diseases. Over 80% of these 39 associations map to polymorphisms in non-coding DNA. Therefore, the challenge is 40 to identify disease-causing variants, the genes they affect, and the cells in which 41 these effects occur. We have developed a platform using ATAC-seq, DNaseI 42 footprints, NG Capture-C and machine learning to address this challenge. Applying 43 this approach to red blood cell traits identifies a significant proportion of known 44 causative variants and their effector genes, which we show can be validated by direct 45 in vivo modelling.Identification of the variation of the genome that determines the risk of common chronic and 48 infectious diseases informs on their primary causes, which leads to preventative or 49 therapeutic approaches and insights. Whilst genome-wide association studies (GWASs) 50 have identified thousands of chromosome regions 1 , the identification of the causal genes, 51 variants and cell types remains a major bottleneck. This is due to three major features of the 52 genome and its complex association with disease susceptibility. Trait-associated variants 53 are often tightly associated, through linkage disequilibrium (LD), with tens or hundreds of 54 other variants, mostly single-nucleotide polymorphisms (SNPs), any one or more of which 55 could be causal; the majority (>85%) the variants identified in GWAS lie within the non-56 coding genome 2 . Although non-coding regions are increasingly well annotated, many 57 variants do not correspond to known regulatory elements, and even when they do, it is rarely 58 known which genes these elements control, and in which cell types. New technical 59 approaches to link variants to the genes they control are rapidly improving but are often 60 limited by their sensitivity and resolution [3][4][5][6] ; and because so few causal variants have been 61 unequivocally linked to the genes they affect, the mechanisms by which non-coding variants 62 alter gene expression remain unknown in all but a few cases; and, third, the complexity of 63 gene regulation and cell/cell interactions means that knowing when in development, in which 64 cell type, in which activation state, and within which pathway(s) a causal variant exerts its 65 effect is usually impossible to predict. Although significant progress is being made, currently, 66 none of these problems has been adequately solved. 68Here, we have developed an integrated platform of experimental and computational 69 methods to prioritise likely causal variants, link them to the genes they regulate, and 70 determine the mechanism by which they alter gene function. To illustrate the approach we 71 have initially focussed on a single haematopoietic lineage: the development of mature red 72 blood cells (RBC), for which all stages of lineage specification and differentiation from a 73 haematopoietic stem cell to a RBC are known, and can be r...

19DNA folding within nuclei is a highly ordered process, with implications for gene 20 regulation and development. An array of chromosome conformation capture (3C) 21 methods have been developed to investigate how DNA is packaged within nuclei and to 22 interrogate specific interactions. While these methods use different approaches to 23 examine target loci (many-versus-all) or the entire genome (all-versus-all), they all rely on 24 the core principle of endonuclease digestion and proximity-based ligation to re-arrange 25 genomic order to reflect the three-dimensional nuclear conformation. This sequence 26 reorganization creates novel chimeric DNA fragments which require specialist 27 bioinformatic tools to analyze and visualize. Despite this need for specialist bioinformatic 28 skills, the core biological importance of genome folding has seen widespread 29 methodological uptake. To service the needs of experimentalists using the many-versus-30 all Capture-C family of methods we have developed CaptureCompendium; a toolkit of 31 software to simplify the design, analysis and presentation of 3C experiments. 32 203 This work was carried out as part of the WIGWAM Consortium (Wellcome Investigation of 204 Genome Wide Association Mechanisms) funded by a Wellcome Trust Strategic Award 205 (106130/Z/14/Z) and Medical Research Council (MRC) Core Funding (MC_UU_12009). We 206 wish to thank all the testers and users of the tools, particularly Duantida Songdej and Nigel 207 Roberts, for dedicated and detailed error reporting and alpha testing, and Jason Torres and 208 Gabriele Mingiolini for portability testing. We acknowledge the CCB computational cluster and 209 the AVI research group for providing the computational resources and system administration 210 for the software development and production runs. Wellcome Trust Doctoral Programmes

BackgroundHi-C and capture Hi-C (CHi-C) are used to map physical contacts between chromatin regions in cell nuclei using high-throughput sequencing. Analysis typically proceeds considering the evidence for contacts between each possible pair of fragments independent from other pairs. This can produce long runs of fragments which appear to all make contact with the same baited fragment of interest.ResultsWe hypothesised that these long runs could result from a smaller subset of direct contacts and propose a new method, based on a Bayesian sparse variable selection approach, which attempts to fine map these direct contacts. Our model is conceptually novel, exploiting the spatial pattern of counts in CHi-C data. Although we use only the CHi-C count data in fitting the model, we show that the fragments prioritised display biological properties that would be expected of true contacts: for bait fragments corresponding to gene promoters, we identify contact fragments with active chromatin and contacts that correspond to edges found in previously defined enhancer-target networks; conversely, for intergenic bait fragments, we identify contact fragments corresponding to promoters for genes expressed in that cell type. We show that long runs of apparently co-contacting fragments can typically be explained using a subset of direct contacts consisting of <10% of the number in the full run, suggesting that greater resolution can be extracted from existing datasets.ConclusionsOur results appear largely complementary to those from a per-fragment analytical approach, suggesting that they provide an additional level of interpretation that may be used to increase resolution for mapping direct contacts in CHi-C experiments.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5314-5) contains supplementary material, which is available to authorized users.