Human pancreatic islet 3D chromatin architecture provides insights into the genetics of type 2 diabetes

Miguel-Escalada, Irene; Bonàs-Guarch, Sílvia; Cebola, Inês; Joan, P; Mendieta-Esteban, Julen; Dm, Rolando; B-M., Javierre; Atla, Goutham; Farabella, Irene; Cc, Morgan; García-Hurtado, Javier; Beucher, Anthony; Morán, Ignasi; Pasquali, Lorenzo; Ramos, Marco A.; Ev, Appel; Linneberg, Allan; Ap, Gjesing; Dr, Witte; Pedersen, Oluf; Grarup, Niels; Ravassard, Philippe; Torrents, David; Jm, Mercader; Piemonti, Lorenzo; Berney, Thierry; Ej, Koning de; Kerr–Conte, Julie; Pattou, François; Io, Fedko; Prokopenko, Inga; Hansen, Torben; Martí‐Renom, Marc A.; Fraser, Peter; Ferrer, Jorge

doi:10.1101/400291

Cited by 14 publications

(14 citation statements)

References 123 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Rad23a locus was instead characterized by a quite constant and high number of A, AP and APD particles consistently with is stable transcription activity during the entire reprogramming process. Altogether, we observed a consistent 3D co-localization of Active and TSS chromatin particles upon activation of the gene, reminiscent of the recently proposed formation of enhancer hubs or condensates[39][40][41] .TADdyn simulations indicate that TSS caging is a general structural signature of transcription activation. To move from anecdotal observations to more general trends, we compared relative expression levels with the dynamic chromatin conformation changes detected during the simulations of all 11 selected loci (Methods andFig.…”

supporting

confidence: 83%

Dynamic simulations of transcriptional control during cell reprogramming reveal spatial chromatin caging

Stefano

Stadhouders

Farabella

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Chromosome structure is a crucial regulatory factor for a wide range of nuclear processes. Chromosome Conformation Capture (3C)-based experiments combined with computational modelling are pivotal for unveiling 3D chromosome structure. Here, we introduce TADdyn, a new tool that integrates time-course 3C data, restraint-based modelling, and molecular dynamics to simulate the structural rearrangements of genomic loci in a completely data-driven way. We applied TADdyn on in-situ Hi-C time-course experiments studying the reprogramming of murine B cells to pluripotent cells, and characterized the structural rearrangements that take place upon changes in the transcriptional state of 11 genomic loci. TADdyn simulations show that structural cages form around the transcription starting site of active loci to stabilize their dynamics, by initiating (hit) and maintaining (stick) interactions with regulatory regions. Consistent findings with TADdyn for all loci under study suggest that this hit-and-stick mechanism may represent a general mechanism to trigger and stabilize transcription.

show abstract

supporting

confidence: 83%

Dynamic simulations of transcriptional control during cell reprogramming reveal spatial chromatin caging

Stefano

Stadhouders

Farabella

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…A number of approaches have been developed to link regulatory elements to target genes including 3D chromatin architecture assays and correlation of accessible chromatin activity across multiple samples 74,75 . While these approaches have different strengths, a common weakness is reliance on ensemble data and non-cell type-resolved information 27,76 . Recently, a new approach was developed to link regulatory elements based on co-accessibility across single cells 6 , which has the potential to provide cell type-resolved enhancer-promoter relationships.…”

Section: Resultsmentioning

confidence: 99%

“…To calibrate the extent to which co-accessibility reflected physical interactions between regulatory elements, we first performed a distance-matched comparison between co-accessible sites stratified by co-accessibility threshold to chromatin loops identified from Hi-C and promoter capture Hi-C (pcHi-C) assays in primary islets 27,76 . We observed strong enrichment for pairs of sites with co-accessibility scores >.05 in both alpha and beta cells for islet chromatin loops identified from pcHi-C and Hi-C compared to sites that had no evidence for co-accessibility (Figure 5a, Supplementary Figure 11a-c).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Single cell chromatin accessibility reveals pancreatic islet cell type- and state-specific regulatory programs of diabetes risk

Chiou

Zeng

Zhang

et al. 2019

Preprint

View full text Add to dashboard Cite

43Genetic risk variants for complex, multifactorial diseases are enriched in cis-regulatory elements. 44Single cell epigenomic technologies create new opportunities to dissect cell type-specific 45 mechanisms of risk variants, yet this approach has not been widely applied to disease-relevant 46 tissues. Given the central role of pancreatic islets in type 2 diabetes (T2D) pathophysiology, we 47 generated accessible chromatin profiles from 14.2k islet cells and identified 13 cell clusters 48 including multiple alpha, beta and delta cell clusters which represented hormone-producing and 49 signal-responsive cell states. We cataloged 244,236 islet cell type accessible chromatin sites and 50 identified transcription factors (TFs) underlying both lineage-and state-specific regulation. We 51 measured the enrichment of T2D and glycemic trait GWAS for the accessible chromatin profiles 52 of single cells, which revealed heterogeneity in the effects of beta cell states and TFs on fasting 53 glucose and T2D risk. We further used machine learning to predict the cell type-specific regulatory 54 function of genetic variants, and single cell co-accessibility to link distal sites to putative cell type-55 specific target genes. We localized 239 fine-mapped T2D risk signals to islet accessible 56 chromatin, and further prioritized variants at these signals with predicted regulatory function and 57 co-accessibility with target genes. At the KCNQ1 locus, the causal T2D variant rs231361 had 58 predicted effects on an enhancer with beta cell-specific, long-range co-accessibility to the insulin 59 promoter, and deletion of this enhancer reduced insulin gene and protein expression in human 60 embryonic stem cell-derived beta cells. Our findings provide a cell type-and state-resolved map 61 of gene regulation in human islets, illuminate likely mechanisms of T2D risk at hundreds of loci, 62 and demonstrate the power of single cell epigenomics for interpreting complex disease genetics. 63 64 65 66 67 68 69 70 71 72 73 Gene regulatory programs are largely orchestrated by cis-regulatory elements that direct the 74 expression of genes in response to specific developmental and environmental cues. Genetic 75 variants associated with disease by genome-wide association studies (GWAS) are highly 76 enriched within putative cis-regulatory elements 1 , highlighting the importance of regulatory 77 sequence in mediating disease risk. The activity of regulatory elements is often restricted to 78 specific cell types and/or cell states, limiting the ability of ATAC-seq and other "ensemble" (or 79 "bulk") epigenomic technologies to map regulatory elements in individual cell types within disease-80 relevant tissues. To overcome this limitation, new approaches to obtain ATAC-seq profiles from 81 single nuclei (snATAC-seq) allow for the disaggregation of open chromatin from heterogenous 82 samples into component cell types and subtypes 2-5 . These developments create opportunities to 83dissect the molecular mechanisms that underlie genetic risk of disease. How...

show abstract

“…Non-coding sequences harbour a large regulatory potential, containing sequence elements that drive tissue-specific expression, such as transcriptional enhancers, whose sequence variation associates with several common and rare human diseases [1][2][3] . Despite the importance of these sequences to maintain appropriate gene regulatory programmes, the lexicon of cis-regulatory elements is still not fully understood and thus large defined deletions are often better suited to study their function than short indels [4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

One-step dual CRISPR/Cas9 guide RNA cloning protocol

Beucher

Cebola

2019

Preprint

Self Cite

View full text Add to dashboard Cite

Existing protocols for dual guide RNA cloning rely on synthesised DNA oligonucleotides of >100 bp that contain both guide RNA sequences, and are therefore not reusable in alternative experimental designs. Here, we describe a single-step protocol to rapidly and inexpensively generate vectors expressing two guide RNAs (gRNAs) simultaneously, which allows re-usage of gRNAs oligonucleotides from one experimental design to another. This protocol is applicable to cloning gRNAs into virtually any CRISPR/Cas9 backbone that allows cloning by Golden Gate, by adapting the primer design. Here, we provide details for cloning gRNAs into vectors with BbsI and BsmBI sites, two of the most frequently found enzymes in CRISPR/Cas9 gRNA expression cassettes.This protocol has been successfully applied to delete pancreatic islet enhancers that harbour type 2 diabetes variants and to validate enhancer-promoter interactions (Miguel-Escalada et al., Nature Genetics 2019).In the future, we foresee that this simple protocol may also be applied to target coding sequences, as well as to target other important kinds of noncoding regulatory elements, including lncRNAs, miRNAs, and chromatin structural anchor points.

show abstract

Human pancreatic islet 3D chromatin architecture provides insights into the genetics of type 2 diabetes

Cited by 14 publications

References 123 publications

Dynamic simulations of transcriptional control during cell reprogramming reveal spatial chromatin caging

Dynamic simulations of transcriptional control during cell reprogramming reveal spatial chromatin caging

Single cell chromatin accessibility reveals pancreatic islet cell type- and state-specific regulatory programs of diabetes risk

One-step dual CRISPR/Cas9 guide RNA cloning protocol

Contact Info

Product

Resources

About