Xingwang Li

CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription.

Spatial genome organization and its effect on transcription remains a fundamental question. We applied an advanced chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) strategy to comprehensively map higher-order chromosome folding and specific chromatin interactions mediated by CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) with haplotype specificity and nucleotide resolution in different human cell lineages. We find that CTCF/cohesin-mediated interaction anchors serve as structural foci for spatial organization of constitutive genes concordant with CTCF-motif orientation, whereas RNAPII interacts within these structures by selectively drawing cell-type-specific genes toward CTCF foci for coordinated transcription. Furthermore, we show that haplotype variants and allelic interactions have differential effects on chromosome configuration, influencing gene expression, and may provide mechanistic insights into functions associated with disease susceptibility. 3D genome simulation suggests a model of chromatin folding around chromosomal axes, where CTCF is involved in defining the interface between condensed and open compartments for structural regulation. Our 3D genome strategy thus provides unique insights in the topological mechanism of human variations and diseases.

Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non-coding RNAs

Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases.

The Energetics and Physiological Impact of Cohesin Extrusion

Cohesin extrusion is thought to play a central role in establishing the architecture of mammalian genomes. However, extrusion has not been visualized inxa0vivo, and thus, its functional impact and energetics are unknown. Using ultra-deep Hi-C, we show that loop domains form by a process that requires cohesin ATPases. Once formed, however, loops and compartments are maintained for hours without energy input. Strikingly, without ATP, we observe the emergence of hundreds of CTCF-independent loops that link regulatory DNA.xa0We also identify architectural stripes, where a loop anchor interacts with entire domains at highxa0frequency. Stripes often tether super-enhancers to cognate promoters, and in B cells, they facilitate Igh transcription and recombination. Stripe anchors represent major hotspots for topoisomerase-mediated lesions, which promote chromosomal translocations and cancer. In plasmacytomas, stripes can deregulate Igh-translocated oncogenes. We propose that higher organisms have coopted cohesin extrusion to enhance transcription and recombination, with implications for tumor development.

STAT5-mediated chromatin interactions in superenhancers activate IL-2 highly inducible genes: Functional dissection of the Il2ra gene locus

Significance Superenhancers regulate the expression of genes that specify cell type-specific development, but little is known regarding their function and regulation in vivo. Here, we study the cytokines IL-2 and IL-21, which critically control the immune response. These cytokines induce the binding of transcription factors STAT5 and STAT3, respectively, at superenhancers in a cytokine- and gene-specific manner. STAT5-bound superenhancers regulate genes highly induced by IL-2, with STAT5 mediating chromatin looping within such genes, including Il2ra, which mediates responsiveness to IL-2. By deleting three STAT5 binding sites that mediate IL-2–induced chromatin looping at the Il2ra locus, we demonstrate that superenhancer elements cooperatively control gene expression. Overall, we elucidate cytokine-dependent superenhancer function in general and provide detailed analysis of the Il2ra superenhancer. Cytokines critically control immune responses, but how regulatory programs are altered to allow T cells to differentially respond to distinct cytokine stimuli remains poorly understood. Here, we have globally analyzed enhancer elements bound by IL-2–activated STAT5 and IL-21–activated STAT3 in T cells and identified Il2ra as the top-ranked gene regulated by an IL-2–activated STAT5-bound superenhancer and one of the top genes regulated by STAT3-bound superenhancers. Moreover, we found that STAT5 binding was rapidly superenriched at genes highly induced by IL-2 and that IL-2–activated STAT5 binding induces new and augmented chromatin interactions within superenhancer-containing genes. Based on chromatin interaction analysis by paired-end tag (ChIA-PET) sequencing data, we used CRISPR-Cas9 gene editing to target three of the STAT5 binding sites within the Il2ra superenhancer in mice. Each mutation decreased STAT5 binding and altered IL-2–induced Il2ra gene expression, revealing that individual elements within the superenhancer were not functionally redundant and that all were required for normal gene expression. Thus, we demonstrate cooperative utilization of superenhancer elements to optimize gene expression and show that STAT5 mediates IL-2–induced chromatin looping at superenhancers to preferentially regulate highly inducible genes, thereby providing new insights into the mechanisms underlying cytokine-dependent superenhancer function.

Long-read ChIA-PET for base-pair-resolution mapping of haplotype-specific chromatin interactions

Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a robust method for capturing genome-wide chromatin interactions. Unlike other 3C-based methods, it includes a chromatin immunoprecipitation (ChIP) step that enriches for interactions mediated by specific target proteins. This unique feature allows ChIA-PET to provide the functional specificity and higher resolution needed to detect chromatin interactions, which chromosome conformation capture (3C)/Hi-C approaches have not achieved. The original ChIA-PET protocol generates short paired-end tags (2 × 20 base pairs (bp)) to detect two genomic loci that are far apart on linear chromosomes but are in spatial proximity in the folded genome. We have improved the original approach by developing long-read ChIA-PET, in which the length of the paired-end tags is increased (up to 2 × 250 bp). The longer PET reads not only improve the tag-mapping efficiency but also increase the probability of covering phased single-nucleotide polymorphisms (SNPs), which allows haplotype-specific chromatin interactions to be identified. Here, we provide the detailed protocol for long-read ChIA-PET that includes cell fixation and lysis, chromatin fragmentation by sonication, ChIP, proximity ligation with a bridge linker, Tn5 tagmentation, PCR amplification and high-throughput sequencing. For a well-trained molecular biologist, it typically takes 6 d from cell harvesting to the completion of library construction, up to a further 36 h for DNA sequencing and <20 h for processing of raw sequencing reads.

EndoC-βH1 multi-genomic profiling defines gene regulatory programs governing human pancreatic β cell identity and function

EndoC-βH1 is emerging as a critical human beta cell model to study the genetic and environmental etiologies of beta cell function, especially in the context of diabetes. Comprehensive knowledge of its molecular landscape is lacking yet required to fully take advantage of this model. Here, we report extensive chromosomal (spectral karyotyping), genetic (genotyping), epigenetic (ChIP-seq, ATAC-seq), chromatin interaction (Hi-C, Pol2 ChIA-PET), and transcriptomic (RNA-seq, miRNA-seq) maps of this cell model. Integrated analyses of these maps define known (e.g., PDX1, ISL1) and putative (e.g., PCSK1, mir-375) beta cell-specific chromatin interactions and transcriptional cis-regulatory networks, and identify allelic effects on cis-regulatory element use and expression. Importantly, comparative analyses with maps generated in primary human islets/beta cells indicate substantial preservation of chromatin looping, but also highlight chromosomal heterogeneity and fetal genomic signatures in EndoC-βH1. Together, these maps, and an interactive web application we have created for their exploration, provide important tools for the broad community in the design and success of experiments to probe and manipulate the genetic programs governing beta cell identity and (dys)function in diabetes.

Highlights from the 11th ISCB Student Council Symposium 2015: Dublin, Ireland. 10 July 2015

Table of contentsA1 Highlights from the eleventh ISCB Student Council Symposium 2015Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana RahmanO1 Prioritizing a drug’s targets using both gene expression and structural similarityGriet Laenen, Sander Willems, Lieven Thorrez, Yves MoreauO2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organismsNagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael GromihaO3 Detection of Heterogeneity in Single Particle Tracking TrajectoriesPaddy J Slator, Nigel J BurroughsO4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecturePrzemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz PlewczynskiO5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classificationGiulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni FeliciO6 A Systems Biology Compendium for Leishmania donovaniBart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris LaukensO7 Unravelling signal coordination from large scale phosphorylation kinetic dataWesta Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

Highlights from the 11th ISCB Student Council Symposium 2015

Table of contentsA1 Highlights from the eleventh ISCB Student Council Symposium 2015Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana RahmanO1 Prioritizing a drug’s targets using both gene expression and structural similarityGriet Laenen, Sander Willems, Lieven Thorrez, Yves MoreauO2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organismsNagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael GromihaO3 Detection of Heterogeneity in Single Particle Tracking TrajectoriesPaddy J Slator, Nigel J BurroughsO4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecturePrzemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz PlewczynskiO5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classificationGiulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni FeliciO6 A Systems Biology Compendium for Leishmania donovaniBart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris LaukensO7 Unravelling signal coordination from large scale phosphorylation kinetic dataWesta Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic