. 2019 Jan 15;26(3):788-801.e6.

doi: 10.1016/j.celrep.2018.12.083.

Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

Nathan Lawlor¹, Eladio J Márquez¹, Peter Orchard², Narisu Narisu³, Muhammad Saad Shamim⁴, Asa Thibodeau¹, Arushi Varshney⁵, Romy Kursawe¹, Michael R Erdos³, Matt Kanke⁶, Huiya Gu⁷, Evgenia Pak³, Amalia Dutra³, Sheikh Russell⁸, Xingwang Li¹, Emaly Piecuch⁹, Oscar Luo¹, Peter S Chines³, Christian Fuchbserger¹⁰; NIH Intramural Sequencing Center; Praveen Sethupathy⁶, Aviva Presser Aiden¹¹, Yijun Ruan¹, Erez Lieberman Aiden¹², Francis S Collins³, Duygu Ucar¹³, Stephen C J Parker¹⁴, Michael L Stitzel¹⁵

Affiliations

"VSports app下载" Affiliations

¹ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
² Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
³ National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
⁴ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA.
⁵ Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
⁶ Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA.
⁷ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
⁸ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA.
⁹ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA.
¹⁰ Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
¹¹ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA.
¹² Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
¹³ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA.
¹⁴ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
¹⁵ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA. Electronic address: michael.stitzel@qiuluzeuv.cn.

PMID: 30650367
PMCID: PMC6389269
DOI: "V体育平台登录" 10.1016/j.celrep.2018.12.083

Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

V体育平台登录 - Nathan Lawlor et al. Cell Rep. 2019.

. 2019 Jan 15;26(3):788-801.e6.

doi: 10.1016/j.celrep.2018.12.083.

V体育官网 - Authors

Affiliations

¹ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
² Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
³ National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
⁴ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA.
⁵ Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
⁶ Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA.
⁷ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
⁸ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA.
⁹ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA.
¹⁰ Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
¹¹ Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA.
¹² Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
¹³ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA.
¹⁴ Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
¹⁵ The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA. Electronic address: michael.stitzel@qiuluzeuv.cn.

PMID: 30650367
PMCID: PMC6389269
DOI: 10.1016/j.celrep.2018.12.083

Abstract

EndoC-βH1 is emerging as a critical human β cell model to study the genetic and environmental etiologies of β cell (dys)function and diabetes VSports手机版. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-βH1. Analyses of these maps define known (e. g. , PDX1 and ISL1) and putative (e. g. , PCSK1 and mir-375) β cell-specific transcriptional cis-regulatory networks and identify allelic effects on cis-regulatory element use. Importantly, comparison with maps generated in primary human islets and/or β cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-βH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing β cell identity and (dys)function in diabetes. .

Keywords: (epi)genome; EndoC-βH1; Hi-C; Pol2 ChIA-PET; genetics; human pancreatic islets; karyotype; transcriptome; type 2 diabetes; β cell V体育安卓版. .

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V体育2025版 - Conflict of interest statement

DECLARATION OF INTERESTS

The authors declare no competing interests.

Figures

**Figure 1.. Extensive Karyotyping and Genotyping of EndoC-βH1**
(A) SKY of EndoC-βH1 for a representative metaphase. (B) Summary of the frequency of chromosomal abnormalities across 14 metaphases. Black boxes indicate the presence of an event, while white boxes indicate an absence. (C) Bar plots highlighting the risk allele burden of NHGRI-EBI GWAS Catalog diabetes-associated GWAS loci in EndoC-βH1. T1D, type 1 diabetes; T2D, type 2 diabetes. Glucose traits include fasting plasma-glucose- and fasting glucose-related traits interacting with BMI from the NHGRI-EBI GWAS catalog (MacArthur et al., 2017). Insulin traits include proinsulin and fasting insulin traits interacting with BMI. (D) Chromosome cartoons illustrating EndoC-βH1 genotypes and the reported locus at glucose trait GWAS SNPs. Cases in which independent association signals mapped to the same locus are indicated by the locus name followed by parentheses containing numbers of SNPs with each risk genotype. Chromosomes 10 and 20 are marked with asterisks to indicate that the previously observed copy-number alterations (illustrated in Figure 1B) may obfuscate interpretation of variant genotypes on these chromosomes. See also Figure S1 and Table S1.

**Figure 2.. Multiomic Comparative Analysis of EndoC-βH1 and Human Pancreatic Islets**
(A) Integrated view of the EndoC-βH1 and human islet (epi)genomic and transcriptomic features surrounding the *PCSK1* locus on chromosome 5. Histone modification ChIP-seq data from EndoC-βH1, human islets, and five Epigenome Roadmap cell types and/or tissues (Roadmap Epigenomics Consortium et al., 2015) were jointly analyzed to determine ChromHMM-based chromatin states in a uniform manner. (B) Spearman correlation between EndoC-βH1 ATAC-seq profiles and their corresponding profiles from islets, sorted α or β cells, and other cell types and tissues (STAR Methods). α, primary islet α cells; β, primary islet β cells; CD4T, CD4⁺ T immune cell; GM12878, B-lymphoblast cell line; skeletal, skeletal muscle; PBMC, peripheral blood mononuclear cells. EndoC-βH1 exhibits greatest similarity to islets and their cellular constituents. (C) Heatmap illustrating Z scores of HOMER enrichment p values for TF motifs in cell-type-specific OCRs. (D) Comparison of chromatin states between EndoC-βH1 and human islets. Blue box highlights putative enhancer *cis-*REs in both EndoC-βH1 and human islets; orange box indicates putative EndoC-βH1 enhancers that are repressed in islets. (E) TF motifs enriched in genomic regions containing putative enhancer *cis-*REs in both EndoC-βH1 and islets (blue) or EndoC-βH1 only (orange). Points in gray denote TFs that are not enriched in either category. See also Figure S2 and Table S3.

**Figure 3.. Generating a Genome-wide Map of Looping in EndoC-βH1 and Human Pancreatic Islets (Hi-C)**
(A) Aggregate peak analysis (APA) plots showing the total signal across all loops (top three panels) and EndoC-βH1-specific loops (bottom three panels) in EndoC-βH1 (left), human islet (center), and GM12878 (right) cells. Of note, islets exhibit similar contact point enrichments at EndoC-βH1-specific peaks compared to GM12878. (B) Cartoon illustrating the different classes of Hi-C loops between example common (gray peaks) or cell-specific (black peaks) ATAC-seq OCRs for two different theoretical cell types. (C) TF motifs enriched in GM12878 (blue) or EndoC-βH1 (red) Hi-C looping anchors that overlap cell-specific ATAC-seq peaks loop classes B and C in panel B above). (D) Hi-C contact maps highlighting a specific loop at the *SLC30A8* locus (denoted by dotted black circle) observed in both EndoC-βH1 (left) and primary human islets (center) but absent in GM12878 (right). (E) Multiomics view of Hi-C, ChIA-PET (Pol2), chromatin states, ATAC-seq, RNA-seq, and gene tracks at the *SLC30A8* neighborhood containing the Hi-C contact point highlighted in (D). Tracks corresponding to EndoC-βH1, human islet, and GM12878 are colored red, black, and blue, respectively. Dark blue boxes below each gene name represent the reference transcript annotations derived from Gencode v19. The red arrow at the bottom of the image indicates the putative EndoC-βH1- and islet-specific promoter for *SLC30A8*. The black arrow indicates the putative embryonic stem cell and K562 cell-specific promoter for *SLC30A8* (Roadmap Epigenomics Consortium et al., 2015). See also Figure S3 and Table S4.

**Figure 4.. RNA Polymerase 2 ChIA-PET Identifies Chromatin Interactions in EndoC-βH1**
(A) Heatmap showing the chromatin states of EndoC-βH1 ChIA-PET interaction nodes. (B) Example of a Pol2 ChIA-PET interaction between active enhancer (blue box) and active promoter (green box) *cis-*REs in the *ISL1* locus on chromosome 5. Asterisks under EndoC-βH1 ChIA-PET interactions (red) indicate interacting sites in the *ISL1* locus detected in human islet 4C-seq analyses (Pasquali et al., 2014). (C) ChIA-PET network connectivity of gene promoters in EndoC-βH1 containing at least three interactions with other regulatory elements. For each gene, the number of connections between other regulatory elements (e.g., active enhancer and weak enhancer) and the proportion of total links in which the chromatin states are EndoC-βH1-specific (blue) or identical in both human islet and EndoC-βH1 (green) are shown in bar plots on the right. The remaining proportions that are neither EndoC-βH1 specific nor common to islet and EndoC-βH1 are not shown. Red font denotes loci containing genes crucial for β cell identity and development. (D) Top: Bar plot illustrating the proportions of chromatin states at the Pol2 ChIA-PET interacting sites (nodes) shared between EndoC-βH1, islets, and additional Epigenomics Roadmap tissues and cell lines. Bottom: Heatmap demonstrating the chromatin states of EndoC-βH1 Pol2 ChIA-PET interacting sites (nodes) in islets (left) or stomach smooth muscle (right). See also Figure S4.

**Figure 5.. Allelic Effects on EndoC-βH1 Transcriptional Regulatory Features**
(A) EndoC-βH1 genotype information was integrated with ATAC-seq, H3K27ac, and RNA-seq data to identify sequence variants altering *cis-*RE accessibility and/or activity (ATAC-seq and H3K27ac) or mRNA levels (RNA-seq) in EndoC-βH1. Pie charts summarize the proportions of variants exhibit significant AIs (blue; FDR < 10%) in each of the corresponding sequencing profiles. (B) Cartoon representation of approach to identify systematic allelic effects on EndoC-βH1 *cis-*regulatory networks. (C) Multiomic view highlighting allelic effects on the *SAMD5* locus *cis*-regulatory network in EndoC-βH1. A variant site exhibiting significant AI in H3K27 acetylation (denoted by blue arrow) is linked (red ChIA-PET interaction) to the transcription start site (TSS) of *SAMD5*. Within the *SAMD5* locus, five transcribed SNPs exhibited significant allelic bias in gene expression (RNA-seq) in a direction consistent with the H3K27ac allelic bias. (D) Left: Bar plots summarizing the proportions of variants with ATAC-seq/H3K27ac imbalance (blue bars; FDR < 10%) that overlap ChIA-PET interacting loci. Right: Pie charts specifying the chromatin state (ChromHMM) annotations of the overlapping variants. See also Figure S5 and Table S5.

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Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

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Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

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V体育2025版 - Conflict of interest statement

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