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Muffels IJ, Schene IF, Rehmann H, Massink MP, van der Wal MM, Bauder C, Labeur M, Armando NG, Lequin MH, Houben ML, Giltay JC, Haitjema S, Huisman A, Vansenne F, Bluvstein J, Pappas J, Shailee LV, Zarate YA, Mokry M, van Haaften GW, Nieuwenhuis EE, Refojo D, van Wijk F, Fuchs SA, van Hasselt PM. Bi-allelic variants in NAE1 cause intellectual disability, ischiopubic hypoplasia, stress-mediated lymphopenia and neurodegeneration. Am J Hum Genet 2023; 110:146-160. [PMID: 36608681 PMCID: PMC9892777 DOI: 10.1016/j.ajhg.2022.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 12/07/2022] [Indexed: 01/07/2023] Open
Abstract
Neddylation has been implicated in various cellular pathways and in the pathophysiology of numerous diseases. We identified four individuals with bi-allelic variants in NAE1, which encodes the neddylation E1 enzyme. Pathogenicity was supported by decreased NAE1 abundance and overlapping clinical and cellular phenotypes. To delineate how cellular consequences of NAE1 deficiency would lead to the clinical phenotype, we focused primarily on the rarest phenotypic features, based on the assumption that these would best reflect the pathophysiology at stake. Two of the rarest features, neuronal loss and lymphopenia worsening during infections, suggest that NAE1 is required during cellular stress caused by infections to protect against cell death. In support, we found that stressing the proteasome system with MG132-requiring upregulation of neddylation to restore proteasomal function and proteasomal stress-led to increased cell death in fibroblasts of individuals with NAE1 genetic variants. Additionally, we found decreased lymphocyte counts after CD3/CD28 stimulation and decreased NF-κB translocation in individuals with NAE1 variants. The rarest phenotypic feature-delayed closure of the ischiopubic rami-correlated with significant downregulation of RUN2X and SOX9 expression in transcriptomic data of fibroblasts. Both genes are involved in the pathophysiology of ischiopubic hypoplasia. Thus, we show that NAE1 plays a major role in (skeletal) development and cellular homeostasis during stress. Our approach suggests that a focus on rare phenotypic features is able to provide significant pathophysiological insights in diseases caused by mutations in genes with pleiotropic effects.
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Affiliation(s)
- Irena J.J. Muffels
- Department of Metabolic Diseases, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, the Netherlands,Center for Translational Immunology (CTI), Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Imre F. Schene
- Department of Metabolic Diseases, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, the Netherlands
| | - Holger Rehmann
- Department of Energy and Biotechnology, Flensburg University of Applied Sciences, Flensburg, Germany
| | - Maarten P.G. Massink
- Department of Genetics, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Maria M. van der Wal
- Center for Translational Immunology (CTI), Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Corinna Bauder
- Department of Neuroendocrinology, Max Planck Institute of Psychiatry, Munich, Germany,Institute of Developmental Genetics, Helmholtz Zentrum München, Munich, Germany
| | - Martha Labeur
- Department of Neuroendocrinology, Max Planck Institute of Psychiatry, Munich, Germany
| | - Natalia G. Armando
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina
| | - Maarten H. Lequin
- Division Imaging and Oncology University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Michiel L. Houben
- Department of General Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jaques C. Giltay
- Department of Genetics, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Saskia Haitjema
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Albert Huisman
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Fleur Vansenne
- Department of Medical Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Judith Bluvstein
- Dravet Center and Comprehensive Epilepsy Center, NYU School of Medicine, New York, NY, USA
| | - John Pappas
- NYU Clinical Genetic Services, NYU Grossman School of Medicine, New York, NY, USA
| | - Lala V. Shailee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yuri A. Zarate
- Section of Genetics and Metabolism, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Michal Mokry
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Gijs W. van Haaften
- Department of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Edward E.S. Nieuwenhuis
- Department of Biomedical and Life Sciences, University College Roosevelt, Middelburg, the Netherlands
| | - Damian Refojo
- Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina,Molecular Neurobiology, Max Planck Institute of Psychiatry, Munich, Germany
| | - Femke van Wijk
- Department of Genetics, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Sabine A. Fuchs
- Department of Metabolic Diseases, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, the Netherlands
| | - Peter M. van Hasselt
- Department of Metabolic Diseases, Division Pediatrics, Wilhelmina Children’s Hospital University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, the Netherlands,Corresponding author
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Revisiting AGAMOUS-LIKE15, a Key Somatic Embryogenesis Regulator, Using Next Generation Sequencing Analysis in Arabidopsis. Int J Mol Sci 2022; 23:ijms232315082. [PMID: 36499403 PMCID: PMC9736886 DOI: 10.3390/ijms232315082] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 11/23/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
AGAMOUS-like 15 (AGL15) is a member of the MADS-domain transcription factor (TF) family. MADS proteins are named for a conserved domain that was originally from an acronym derived from genes expressed in a variety of eukaryotes (MCM1-AGAMOUS-DEFICIENS-SERUM RESPONSE FACTOR). In plants, this family has expanded greatly, with more than one-hundred members generally found in dicots, and the proteins encoded by these genes have often been associated with developmental identity. AGL15 transcript and protein accumulate primarily in embryos and has been found to promote an important process called plant regeneration via somatic embryogenesis (SE). To understand how this TF performs this function, we have previously used microarray technologies to assess direct and indirect responsive targets of this TF. We have now revisited this question using next generation sequencing (NGS) to both characterize in vivo binding sites for AGL15 as well as response to the accumulation of AGL15. We compared these data to the prior microarray results to evaluate the different platforms. The new NGS data brought to light an interaction with brassinosteroid (BR) hormone signaling that was "missed" in prior Gene Ontology analysis from the microarray studies.
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Paul P, Joshi S, Tian R, Diogo Junior R, Chakrabarti M, Perry SE. The MADS-domain factor AGAMOUS-Like18 promotes somatic embryogenesis. PLANT PHYSIOLOGY 2022; 188:1617-1631. [PMID: 34850203 PMCID: PMC8896631 DOI: 10.1093/plphys/kiab553] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 10/29/2021] [Indexed: 05/08/2023]
Abstract
AGAMOUS-Like 18 (AGL18) is a MADS domain transcription factor (TF) that is structurally related to AGL15. Here we show that, like AGL15, AGL18 can promote somatic embryogenesis (SE) when ectopically expressed in Arabidopsis (Arabidopsis thaliana). Based on loss-of-function mutants, AGL15 and AGL18 have redundant functions in developmental processes such as SE. To understand the nature of this redundancy, we undertook a number of studies to look at the interaction between these factors. We studied the genome-wide direct targets of AGL18 to characterize its roles at the molecular level using chromatin immunoprecipitation (ChIP)-SEQ combined with RNA-SEQ. The results demonstrated that AGL18 binds to thousands of sites in the genome. Comparison of ChIP-SEQ data for AGL15 and AGL18 revealed substantial numbers of genes bound by both AGL15 and AGL18, but there were also differences. Gene ontology analysis revealed that target genes were enriched for seed, embryo, and reproductive development as well as hormone and stress responses. The results also demonstrated that AGL15 and AGL18 interact in a complex regulatory loop, where AGL15 inhibited transcript accumulation of AGL18, while AGL18 increased AGL15 transcript accumulation. Co-immunoprecipitation revealed an interaction between AGL18 and AGL15 in somatic embryo tissue. The binding and expression analyses revealed a complex crosstalk and interactions among embryo TFs and their target genes. In addition, our study also revealed that phosphorylation of AGL18 and AGL15 was crucial for the promotion of SE.
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Affiliation(s)
- Priyanka Paul
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
| | - Sanjay Joshi
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
| | - Ran Tian
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
| | - Rubens Diogo Junior
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
| | - Manohar Chakrabarti
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
| | - Sharyn E Perry
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546-0312, USA
- Author for communication:
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KAIRI AMIT, SAHU TANMAYAKUMAR, RAO ATMAKURIRAMAKRISHNA. An information system on genomic elements and predicted protein structures of buffalo (Bubalus bubalis). THE INDIAN JOURNAL OF ANIMAL SCIENCES 2021. [DOI: 10.56093/ijans.v90i11.111494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Among the livestock species, buffalo remained as an integral part of the Indian rural economy. With the advent of genome sequencing technologies, it became possible to sequence the whole genome of Murrah buffalo. Also, significant amount of information on different genomic elements of buffalo is available at National Centre for Biotechnology Information (NCBI). However, the positions of these elements on the genome are not fully known. In addition, the 3D structures of buffalo proteins are not available and also there exist no browser to visualize important genic elements on buffalo genome. Hence, a study was taken up to develop a web-based information system having information on genomic elements, protein 3-D structures and genome browser. Initially, information on nucleotide and protein sequences were retrieved from NCBI and parsed suitably. Later, the protein structures were predicted, validated, refined and stabilized in silico. An Information System on Buffalo Genome (ISBG) with 3-tier architecture was developed containing the sequence and structural information. ISBG contains complete coding sequences (CDS), Mitochondrial DNAs, 1k upstream regions and Untranslated Regions (UTRs) of buffalo genome. The buffalo genes were also mapped onto the genome. The results revealed that maximum number of genes were found distributed on chromosome 4 followed by chromosome 18, which can also be visualized from the developed genome browser. ISBG can be accessed at http://cabgrid.res.in:8080/bgis. The proposed information system helps animal breeders and biotechnologist in animal improvement.
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Chromatin accessibility of circulating CD8 + T cells predicts treatment response to PD-1 blockade in patients with gastric cancer. Nat Commun 2021; 12:975. [PMID: 33579944 PMCID: PMC7881150 DOI: 10.1038/s41467-021-21299-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 01/15/2021] [Indexed: 02/07/2023] Open
Abstract
Although tumor genomic profiling has identified small subsets of gastric cancer (GC) patients with clinical benefit from anti-PD-1 treatment, not all responses can be explained by tumor sequencing alone. We investigate epigenetic elements responsible for the differential response to anti-PD-1 therapy by quantitatively assessing the genome-wide chromatin accessibility of circulating CD8+ T cells in patients’ peripheral blood. Using an assay for transposase-accessible chromatin using sequencing (ATAC-seq), we identify unique open regions of chromatin that significantly distinguish anti-PD-1 therapy responders from non-responders. GC patients with high chromatin openness of circulating CD8+ T cells are significantly enriched in the responder group. Concordantly, patients with high chromatin openness at specific genomic positions of their circulating CD8+ T cells demonstrate significantly better survival than those with closed chromatin. Here we reveal that epigenetic characteristics of baseline CD8+ T cells can be used to identify metastatic GC patients who may benefit from anti-PD-1 therapy. Anti-PD-1 therapy could induce a durable response in patients with gastric cancer, however biomarkers to predict response to immunotherapy are generally lacking. Here the authors report that openness of chromatin in circulating CD8+ T cells predicts treatment outcome in patients with metastatic gastric cancer treated with pembrolizumab.
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6
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Ko G, Kim PG, Cho Y, Jeong S, Kim JY, Kim KH, Lee HY, Han J, Yu N, Ham S, Jang I, Kang B, Shin S, Kim L, Lee SW, Nam D, Kim JF, Kim N, Kim SY, Lee S, Roh TY, Lee B. Bioinformatics services for analyzing massive genomic datasets. Genomics Inform 2020; 18:e8. [PMID: 32224841 PMCID: PMC7120352 DOI: 10.5808/gi.2020.18.1.e8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 03/11/2020] [Indexed: 11/25/2022] Open
Abstract
The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.
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Affiliation(s)
- Gunhwan Ko
- Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea
| | - Pan-Gyu Kim
- Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea
| | - Youngbum Cho
- Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
| | - Seongmun Jeong
- Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
| | - Jae-Yoon Kim
- Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
| | | | - Ho-Yeon Lee
- Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
| | - Jiyeon Han
- Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea
| | - Namhee Yu
- Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea
| | - Seokjin Ham
- Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea
| | - Insoon Jang
- Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea
| | - Byunghee Kang
- Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea
| | - Sunguk Shin
- Department of Systems, Biology Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea
| | - Lian Kim
- Bioposh Inc., Daejeon 34016, Korea
| | | | - Dougu Nam
- School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Jihyun F Kim
- Department of Systems, Biology Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.,Strategic Initiative for Microbiomes in Agriculture and Food, Yonsei University, Seoul 03722, Korea
| | - Namshin Kim
- Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
| | - Seon-Young Kim
- Genome Structure Research Center, KRIBB, Daejeon 34141, Korea
| | - Sanghyuk Lee
- Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea
| | - Tae-Young Roh
- Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea.,SysGenLab Inc., Pohang 37613, Korea
| | - Byungwook Lee
- Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea
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7
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Vervoort SJ, de Jong OG, Roukens MG, Frederiks CL, Vermeulen JF, Lourenço AR, Bella L, Vidakovic AT, Sandoval JL, Moelans C, van Amersfoort M, Dallman MJ, Bruna A, Caldas C, Nieuwenhuis E, van der Wall E, Derksen P, van Diest P, Verhaar MC, Lam EWF, Mokry M, Coffer PJ. Global transcriptional analysis identifies a novel role for SOX4 in tumor-induced angiogenesis. eLife 2018; 7:e27706. [PMID: 30507376 PMCID: PMC6277201 DOI: 10.7554/elife.27706] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 11/07/2018] [Indexed: 12/30/2022] Open
Abstract
The expression of the transcription factor SOX4 is increased in many human cancers, however, the pro-oncogenic capacity of SOX4 can vary greatly depending on the type of tumor. Both the contextual nature and the mechanisms underlying the pro-oncogenic SOX4 response remain unexplored. Here, we demonstrate that in mammary tumorigenesis, the SOX4 transcriptional network is dictated by the epigenome and is enriched for pro-angiogenic processes. We show that SOX4 directly regulates endothelin-1 (ET-1) expression and can thereby promote tumor-induced angiogenesis both in vitro and in vivo. Furthermore, in breast tumors, SOX4 expression correlates with blood vessel density and size, and predicts poor-prognosis in patients with breast cancer. Our data provide novel mechanistic insights into context-dependent SOX4 target gene selection, and uncover a novel pro-oncogenic role for this transcription factor in promoting tumor-induced angiogenesis. These findings establish a key role for SOX4 in promoting metastasis through exploiting diverse pro-tumorigenic pathways.
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Affiliation(s)
- Stephin J Vervoort
- Department of Cell Biology, Center for Molecular MedicineUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Olivier G de Jong
- Department of Nephrology and HypertensionUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - M Guy Roukens
- Department of Cell Biology, Center for Molecular MedicineUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Cynthia L Frederiks
- Department of Cell Biology, Center for Molecular MedicineUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jeroen F Vermeulen
- Department of PathologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Ana Rita Lourenço
- Department of Cell Biology, Center for Molecular MedicineUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Laura Bella
- Department of Surgery and CancerImperial Centre for Translational and Experimental Medicine, Imperial College London, Hammersmith Hospital CampusLondonUnited Kingdom
| | | | - José L Sandoval
- Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUnited Kingdom
| | - Cathy Moelans
- Department of PathologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | - Margaret J Dallman
- Department of Life Sciences, Division of Cell and Molecular BiologyImperial College LondonLondonUnited Kingdom
| | - Alejandra Bruna
- Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUnited Kingdom
| | - Carlos Caldas
- Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUnited Kingdom
| | - Edward Nieuwenhuis
- Division of Pediatrics, Wilhelmina Children’s HospitalUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | - Patrick Derksen
- Department of PathologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Paul van Diest
- Department of PathologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and HypertensionUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Eric W-F Lam
- Department of Surgery and CancerImperial Centre for Translational and Experimental Medicine, Imperial College London, Hammersmith Hospital CampusLondonUnited Kingdom
| | - Michal Mokry
- Division of Pediatrics, Wilhelmina Children’s HospitalUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Paul J Coffer
- Department of Cell Biology, Center for Molecular MedicineUniversity Medical Center UtrechtUtrechtThe Netherlands
- Division of Pediatrics, Wilhelmina Children’s HospitalUniversity Medical Center UtrechtUtrechtThe Netherlands
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8
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Yu M, Du G, Xu Q, Huang Z, Huang X, Qin Y, Han L, Fan Y, Zhang Y, Han X, Jiang Z, Xia Y, Wang X, Lu C. Integrated analysis of DNA methylome and transcriptome identified CREB5 as a novel risk gene contributing to recurrent pregnancy loss. EBioMedicine 2018; 35:334-344. [PMID: 30100398 PMCID: PMC6154871 DOI: 10.1016/j.ebiom.2018.07.042] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 07/29/2018] [Accepted: 07/30/2018] [Indexed: 01/09/2023] Open
Abstract
Background Aberrant DNA methylation is considered to be a potential cause of recurrent pregnancy loss (RPL), while potential mechanism has not yet been elucidated. Methods In order to uncover the contribution of the perturbation of DNA methylation in RPL, we performed genome-wide DNA methylation analysis combined with genome-wide gene expression in decidua tissue. Findings Totally, 539 differentially methylated regions (DMRs) were identified and significantly correlated with gene expressions. We observed that hypo-methylated DMR near CREB5 recruited transcription factors binding, such as P53 and SP1, and in turn upregulated CREB5. Compromised cell migration and apoptosis were observed in human CREB5 overexpression trophoblast cell lines, indicating dysfunctional trophoblast cells might contribute to RPL after hypo-methylation of CREB5. In addition, overexpression of CREB5 altered cell cycle. Interpretation Our data highlights a role of CREB5 involved in the pathogenesis of RPL, and CREB5 maybe a potential diagnostic biomarker for RPL.
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Affiliation(s)
- Mingming Yu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Guizhen Du
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Qiaoqiao Xu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Zhenyao Huang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Xiaomin Huang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Yufeng Qin
- Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Li Han
- Department of Obstetrics, Huai-An First Affiliated Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Yun Fan
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Yan Zhang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Xiumei Han
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Ziyan Jiang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Xinru Wang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China
| | - Chuncheng Lu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing 210029, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 210029, China.
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9
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Brignall R, Cauchy P, Bevington SL, Gorman B, Pisco AO, Bagnall J, Boddington C, Rowe W, England H, Rich K, Schmidt L, Dyer NP, Travis MA, Ott S, Jackson DA, Cockerill PN, Paszek P. Integration of Kinase and Calcium Signaling at the Level of Chromatin Underlies Inducible Gene Activation in T Cells. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2017; 199:2652-2667. [PMID: 28904128 PMCID: PMC5632840 DOI: 10.4049/jimmunol.1602033] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 08/21/2017] [Indexed: 01/20/2023]
Abstract
TCR signaling pathways cooperate to activate the inducible transcription factors NF-κB, NFAT, and AP-1. In this study, using the calcium ionophore ionomycin and/or PMA on Jurkat T cells, we show that the gene expression program associated with activation of TCR signaling is closely related to specific chromatin landscapes. We find that calcium and kinase signaling cooperate to induce chromatin remodeling at ∼2100 chromatin regions, which demonstrate enriched binding motifs for inducible factors and correlate with target gene expression. We found that these regions typically function as inducible enhancers. Many of these elements contain composite NFAT/AP-1 sites, which typically support cooperative binding, thus further reinforcing the need for cooperation between calcium and kinase signaling in the activation of genes in T cells. In contrast, treatment with PMA or ionomycin alone induces chromatin remodeling at far fewer regions (∼600 and ∼350, respectively), which mostly represent a subset of those induced by costimulation. This suggests that the integration of TCR signaling largely occurs at the level of chromatin, which we propose plays a crucial role in regulating T cell activation.
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Affiliation(s)
- Ruth Brignall
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Pierre Cauchy
- Institute of Biomedical Research, College of Medicine and Dentistry, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Sarah L Bevington
- Institute of Biomedical Research, College of Medicine and Dentistry, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Bethany Gorman
- Institute of Biomedical Research, College of Medicine and Dentistry, University of Birmingham, Birmingham B15 2TT, United Kingdom
| | - Angela O Pisco
- Centre for Stem Cells and Regenerative Medicine, King's College London, London SE1 9RT, United Kingdom
| | - James Bagnall
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Christopher Boddington
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - William Rowe
- Department of Chemistry, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Hazel England
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Kevin Rich
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Collaborative Centre for Inflammation Research, University of Manchester, Manchester M13 9PT, United Kingdom
- Wellcome Trust Centre for Cell-Matrix Research, University of Manchester, Manchester M13 9PT, United Kingdom; and
| | - Lorraine Schmidt
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Nigel P Dyer
- Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Mark A Travis
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Collaborative Centre for Inflammation Research, University of Manchester, Manchester M13 9PT, United Kingdom
- Wellcome Trust Centre for Cell-Matrix Research, University of Manchester, Manchester M13 9PT, United Kingdom; and
| | - Sascha Ott
- Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Dean A Jackson
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
| | - Peter N Cockerill
- Institute of Biomedical Research, College of Medicine and Dentistry, University of Birmingham, Birmingham B15 2TT, United Kingdom;
| | - Pawel Paszek
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom;
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10
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Liu B, Yang J, Li Y, McDermaid A, Ma Q. An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq data. Brief Bioinform 2017; 19:1069-1081. [DOI: 10.1093/bib/bbx026] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Indexed: 01/06/2023] Open
Affiliation(s)
- Bingqiang Liu
- School of Mathematics, Shandong University, Jinan Shandong, P. R. China
| | - Jinyu Yang
- Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA
| | - Yang Li
- School of Mathematics, Shandong University, Jinan Shandong, P. R. China
| | - Adam McDermaid
- Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA
| | - Qin Ma
- Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD, USA
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11
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Mokry M, Harakalova M, Asselbergs FW, de Bakker PIW, Nieuwenhuis EES. Extensive Association of Common Disease Variants with Regulatory Sequence. PLoS One 2016; 11:e0165893. [PMID: 27875544 PMCID: PMC5119736 DOI: 10.1371/journal.pone.0165893] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 10/19/2016] [Indexed: 12/11/2022] Open
Abstract
Overlap between non-coding DNA regulatory sequences and common variant associations can help to identify specific cell and tissue types that are relevant for particular diseases. In a systematic manner, we analyzed variants from 94 genome-wide association studies (reporting at least 12 loci at p<5x10-8) by projecting them onto 466 epigenetic datasets (characterizing DNase I hypersensitive sites; DHSs) derived from various adult and fetal tissue samples and cell lines including many biological replicates. We were able to confirm many expected associations, such as the involvement of specific immune cell types in immune-related diseases and tissue types in diseases that affect specific organs, for example, inflammatory bowel disease and coronary artery disease. Other notable associations include adrenal glands in coronary artery disease, the immune system in Alzheimer’s disease, and the kidney for bone marrow density. The association signals for some GWAS (for example, myopia or age at menarche) did not show a clear pattern with any of the cell or tissue types studied. In general, the identified variants from GWAS tend to be located outside coding regions. Altogether, we have performed an extensive characterization of GWAS signals in relation to cell and tissue-specific DHSs, demonstrating a key role for regulatory mechanisms in common diseases and complex traits.
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Affiliation(s)
- Michal Mokry
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, 3584 EA, The Netherlands
- * E-mail: (MM); (EESN)
| | - Magdalena Harakalova
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht, 3508 GA, The Netherlands
| | - Folkert W. Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht, 3508 GA, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, 3501 DG, The Netherlands
- Institute of Cardiovascular Science, faculty of Population Health Sciences, University College London, London, WC1E 6BT, United Kingdom
| | - Paul I. W. de Bakker
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, 3508 GA, The Netherlands
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, 3508 GA, The Netherlands
| | - Edward E. S. Nieuwenhuis
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, 3584 EA, The Netherlands
- * E-mail: (MM); (EESN)
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12
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Si H, Lu H, Yang X, Mattox A, Jang M, Bian Y, Sano E, Viadiu H, Yan B, Yau C, Ng S, Lee SK, Romano RA, Davis S, Walker RL, Xiao W, Sun H, Wei L, Sinha S, Benz CC, Stuart JM, Meltzer PS, Van Waes C, Chen Z. TNF-α modulates genome-wide redistribution of ΔNp63α/TAp73 and NF-κB cREL interactive binding on TP53 and AP-1 motifs to promote an oncogenic gene program in squamous cancer. Oncogene 2016; 35:5781-5794. [PMID: 27132513 PMCID: PMC5093089 DOI: 10.1038/onc.2016.112] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 01/11/2016] [Accepted: 01/19/2016] [Indexed: 12/11/2022]
Abstract
The Cancer Genome Atlas (TCGA) network study of 12 cancer types (PanCancer 12) revealed frequent mutation of TP53, and amplification and expression of related TP63 isoform ΔNp63 in squamous cancers. Further, aberrant expression of inflammatory genes and TP53/p63/p73 targets were detected in the PanCancer 12 project, reminiscent of gene programs comodulated by cREL/ΔNp63/TAp73 transcription factors we uncovered in head and neck squamous cell carcinomas (HNSCCs). However, how inflammatory gene signatures and cREL/p63/p73 targets are comodulated genome wide is unclear. Here, we examined how the inflammatory factor tumor necrosis factor-α (TNF-α) broadly modulates redistribution of cREL with ΔNp63α/TAp73 complexes and signatures genome wide in the HNSCC model UM-SCC46 using chromatin immunoprecipitation sequencing (ChIP-seq). TNF-α enhanced genome-wide co-occupancy of cREL with ΔNp63α on TP53/p63 sites, while unexpectedly promoting redistribution of TAp73 from TP53 to activator protein-1 (AP-1) sites. cREL, ΔNp63α and TAp73 binding and oligomerization on NF-κB-, TP53- or AP-1-specific sequences were independently validated by ChIP-qPCR (quantitative PCR), oligonucleotide-binding assays and analytical ultracentrifugation. Function of the binding activity was confirmed using TP53-, AP-1- and NF-κB-specific REs or p21, SERPINE1 and IL-6 promoter luciferase reporter activities. Concurrently, TNF-α regulated a broad gene network with cobinding activities for cREL, ΔNp63α and TAp73 observed upon array profiling and reverse transcription-PCR. Overlapping target gene signatures were observed in squamous cancer subsets and in inflamed skin of transgenic mice overexpressing ΔNp63α. Furthermore, multiple target genes identified in this study were linked to TP63 and TP73 activity and increased gene expression in large squamous cancer samples from PanCancer 12 TCGA by CircleMap. PARADIGM inferred pathway analysis revealed the network connection of TP63 and NF-κB complexes through an AP-1 hub, further supporting our findings. Thus, inflammatory cytokine TNF-α mediates genome-wide redistribution of the cREL/p63/p73, and AP-1 interactome, to diminish TAp73 tumor suppressor function and reciprocally activate NF-κB and AP-1 gene programs implicated in malignancy.
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Affiliation(s)
- Han Si
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Hai Lu
- Orthopaedic Center, Zhujiang Hospital Guangzhou, Guangdong,
China
| | - Xinping Yang
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Austin Mattox
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Minyoung Jang
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Yansong Bian
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Eleanor Sano
- Department of Chemistry and Biochemistry, University of
California, San Diego, La Jolla, CA
| | - Hector Viadiu
- Instituto de Química, Universidad Nacional
Autónoma de México (UNAM), Circuito Exterior, Ciudad Universitaria,
Mexico City, D.F. 04510, MÉXICO
| | - Bin Yan
- LKS Faculty of Medicine and School of Biomedical Sciences,
LKS Faculty of Medicine and Center of Genome Sciences, The University of Hong Kong,
Hong Kong, China
| | | | - Sam Ng
- Department of Biomolecular Engineering, Center for
Biomolecular Sciences and Engineering, University of California, Santa Cruz, Santa
Cruz, CA
| | - Steven K. Lee
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Rose-Anne Romano
- Department of Biochemistry, State University of New York at
Buffalo, Center for Excellence in Bioinformatics and Life Sciences, Buffalo, New
York, USA
| | - Sean Davis
- Cancer Genetics Branch, National Cancer Institute,
Bethesda, Maryland, USA
| | - Robert L. Walker
- Cancer Genetics Branch, National Cancer Institute,
Bethesda, Maryland, USA
| | - Wenming Xiao
- Division of Bioinformatics and Biostatistics, National
Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson,
Arkansas
| | - Hongwei Sun
- Biodata Mining and Discovery Section, National Institute
of Arthritis, Musculoskeletal and Skin Diseases, Bethesda, Maryland, USA
| | - Lai Wei
- Clinical Immunology Section, National Eye Institute, NIH,
Bethesda, Maryland, USA
- State Key Laboratory of Ophthalmology, Zhongshan
Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Satrajit Sinha
- Department of Biochemistry, State University of New York at
Buffalo, Center for Excellence in Bioinformatics and Life Sciences, Buffalo, New
York, USA
| | | | - Joshua M. Stuart
- Department of Biomolecular Engineering, Center for
Biomolecular Sciences and Engineering, University of California, Santa Cruz, Santa
Cruz, CA
| | - Paul S. Meltzer
- Cancer Genetics Branch, National Cancer Institute,
Bethesda, Maryland, USA
| | - Carter Van Waes
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
| | - Zhong Chen
- Tumor Biology Section, Head and Neck Surgery Branch,
National Institute on Deafness and Other Communication Disorders, NIH, Bethesda,
Maryland, USA
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13
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He X, Ohba S, Hojo H, McMahon AP. AP-1 family members act with Sox9 to promote chondrocyte hypertrophy. Development 2016; 143:3012-23. [PMID: 27471255 DOI: 10.1242/dev.134502] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 07/08/2016] [Indexed: 12/17/2022]
Abstract
An analysis of Sox9 binding profiles in developing chondrocytes identified marked enrichment of an AP-1-like motif. Here, we have explored the functional interplay between Sox9 and AP-1 in mammalian chondrocyte development. Among AP-1 family members, Jun and Fosl2 were highly expressed within prehypertrophic and early hypertrophic chondrocytes. Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) showed a striking overlap in Jun- and Sox9-bound regions throughout the chondrocyte genome, reflecting direct binding of each factor to the same enhancers and a potential for protein-protein interactions within AP-1- and Sox9-containing complexes. In vitro reporter analysis indicated that direct co-binding of Sox9 and AP-1 at target motifs promoted gene activity. By contrast, where only one factor can engage its DNA target, the presence of the other factor suppresses target activation consistent with protein-protein interactions attenuating transcription. Analysis of prehypertrophic chondrocyte removal of Sox9 confirmed the requirement of Sox9 for hypertrophic chondrocyte development, and in vitro and ex vivo analyses showed that AP-1 promotes chondrocyte hypertrophy. Sox9 and Jun co-bound and co-activated a Col10a1 enhancer in Sox9 and AP-1 motif-dependent manners consistent with their combined action promoting hypertrophic gene expression. Together, the data support a model in which AP-1 family members contribute to Sox9 action in the transition of chondrocytes to the hypertrophic program.
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Affiliation(s)
- Xinjun He
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, W.M. Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Shinsuke Ohba
- Department of Bioengineering, the University of Tokyo, Tokyo 113-0033, Japan
| | - Hironori Hojo
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, W.M. Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Andrew P McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, W.M. Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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14
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Sliva A, Kuang Z, Meluh PB, Boeke JD. Barcode Sequencing Screen Identifies SUB1 as a Regulator of Yeast Pheromone Inducible Genes. G3 (BETHESDA, MD.) 2016; 6:881-92. [PMID: 26837954 PMCID: PMC4825658 DOI: 10.1534/g3.115.026757] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2015] [Accepted: 01/27/2016] [Indexed: 11/18/2022]
Abstract
The yeast pheromone response pathway serves as a valuable model of eukaryotic mitogen-activated protein kinase (MAPK) pathways, and transcription of their downstream targets. Here, we describe application of a screening method combining two technologies: fluorescence-activated cell sorting (FACS), and barcode analysis by sequencing (Bar-Seq). Using this screening method, and pFUS1-GFP as a reporter for MAPK pathway activation, we readily identified mutants in known mating pathway components. In this study, we also include a comprehensive analysis of the FUS1 induction properties of known mating pathway mutants by flow cytometry, featuring single cell analysis of each mutant population. We also characterized a new source of false positives resulting from the design of this screen. Additionally, we identified a deletion mutant, sub1Δ, with increased basal expression of pFUS1-GFP. Here, in the first ChIP-Seq of Sub1, our data shows that Sub1 binds to the promoters of about half the genes in the genome (tripling the 991 loci previously reported), including the promoters of several pheromone-inducible genes, some of which show an increase upon pheromone induction. Here, we also present the first RNA-Seq of a sub1Δ mutant; the majority of genes have no change in RNA, but, of the small subset that do, most show decreased expression, consistent with biochemical studies implicating Sub1 as a positive transcriptional regulator. The RNA-Seq data also show that certain pheromone-inducible genes are induced less in the sub1Δ mutant relative to the wild type, supporting a role for Sub1 in regulation of mating pathway genes. The sub1Δ mutant has increased basal levels of a small subset of other genes besides FUS1, including IMD2 and FIG1, a gene encoding an integral membrane protein necessary for efficient mating.
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Affiliation(s)
- Anna Sliva
- Institute for Systems Genetics, New York University Langone School of Medicine, New York 10016 Human Genetics Program, Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Zheng Kuang
- Institute for Systems Genetics, New York University Langone School of Medicine, New York 10016
| | - Pamela B Meluh
- Calico Life Sciences, Google Inc., San Francisco, California 94080
| | - Jef D Boeke
- Institute for Systems Genetics, New York University Langone School of Medicine, New York 10016
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15
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An interactive environment for agile analysis and visualization of ChIP-sequencing data. Nat Struct Mol Biol 2016; 23:349-57. [PMID: 26926434 DOI: 10.1038/nsmb.3180] [Citation(s) in RCA: 176] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 01/29/2016] [Indexed: 02/08/2023]
Abstract
To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.
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16
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van den Broek T, Delemarre EM, Janssen WJM, Nievelstein RAJ, Broen JC, Tesselaar K, Borghans JAM, Nieuwenhuis EES, Prakken BJ, Mokry M, Jansen NJG, van Wijk F. Neonatal thymectomy reveals differentiation and plasticity within human naive T cells. J Clin Invest 2016; 126:1126-36. [PMID: 26901814 DOI: 10.1172/jci84997] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Accepted: 01/07/2016] [Indexed: 12/22/2022] Open
Abstract
The generation of naive T cells is dependent on thymic output, but in adults, the naive T cell pool is primarily maintained by peripheral proliferation. Naive T cells have long been regarded as relatively quiescent cells; however, it was recently shown that IL-8 production is a signatory effector function of naive T cells, at least in newborns. How this functional signature relates to naive T cell dynamics and aging is unknown. Using a cohort of children and adolescents who underwent neonatal thymectomy, we demonstrate that the naive CD4+ T cell compartment in healthy humans is functionally heterogeneous and that this functional diversity is lost after neonatal thymectomy. Thymic tissue regeneration later in life resulted in functional restoration of the naive T cell compartment, implicating the thymus as having functional regenerative capacity. Together, these data shed further light on functional differentiation within the naive T cell compartment and the importance of the thymus in human naive T cell homeostasis and premature aging. In addition, these results affect and alter our current understanding on the identification of truly naive T cells and recent thymic emigrants.
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17
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Lucas ES, Dyer NP, Murakami K, Lee YH, Chan YW, Grimaldi G, Muter J, Brighton PJ, Moore JD, Patel G, Chan JKY, Takeda S, Lam EWF, Quenby S, Ott S, Brosens JJ. Loss of Endometrial Plasticity in Recurrent Pregnancy Loss. Stem Cells 2015; 34:346-56. [PMID: 26418742 DOI: 10.1002/stem.2222] [Citation(s) in RCA: 137] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 07/30/2015] [Accepted: 09/04/2015] [Indexed: 12/15/2022]
Abstract
Menstruation drives cyclic activation of endometrial progenitor cells, tissue regeneration, and maturation of stromal cells, which differentiate into specialized decidual cells prior to and during pregnancy. Aberrant responsiveness of human endometrial stromal cells (HESCs) to deciduogenic cues is strongly associated with recurrent pregnancy loss (RPL), suggesting a defect in cellular maturation. MeDIP-seq analysis of HESCs did not reveal gross perturbations in CpG methylation in RPL cultures, although quantitative differences were observed in or near genes that are frequently deregulated in vivo. However, RPL was associated with a marked reduction in methylation of defined CA-rich motifs located throughout the genome but enriched near telomeres. Non-CpG methylation is a hallmark of cellular multipotency. Congruently, we demonstrate that RPL is associated with a deficiency in endometrial clonogenic cell populations. Loss of epigenetic stemness features also correlated with intragenic CpG hypomethylation and reduced expression of HMGB2, coding high mobility group protein 2. We show that knockdown of this sequence-independent chromatin protein in HESCs promotes senescence and impairs decidualization, exemplified by blunted time-dependent secretome changes. Our findings indicate that stem cell deficiency and accelerated stromal senescence limit the differentiation capacity of the endometrium and predispose for pregnancy failure.
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Affiliation(s)
- Emma S Lucas
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Nigel P Dyer
- Warwick Systems Biology Centre, University of Warwick, Coventry, England, United Kingdom
| | - Keisuke Murakami
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Yie Hou Lee
- Interdisciplinary Research Groups of BioSystems and Micromechanics, and Infectious Diseases, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore
| | - Yi-Wah Chan
- Warwick Systems Biology Centre, University of Warwick, Coventry, England, United Kingdom
| | - Giulia Grimaldi
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Joanne Muter
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Paul J Brighton
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Jonathan D Moore
- Warwick Systems Biology Centre, University of Warwick, Coventry, England, United Kingdom
| | - Gnyaneshwari Patel
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Jerry K Y Chan
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore
| | - Satoru Takeda
- Department of Obstetrics and Gynaecology, Juntendo University Faculty of Medicine, Tokyo, Japan
| | - Eric W-F Lam
- Department of Surgery and Cancer, Imperial College London, Imperial Centre for Translational and Experimental Medicine (ICTEM), London, United Kingdom
| | - Siobhan Quenby
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
| | - Sascha Ott
- Warwick Systems Biology Centre, University of Warwick, Coventry, England, United Kingdom
| | - Jan J Brosens
- Division of Reproductive Health, Clinical Science Research Laboratories, Warwick Medical School, University of Warwick, Coventry, England, United Kingdom
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18
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Need EF, Selth LA, Trotta AP, Leach DA, Giorgio L, O'Loughlin MA, Smith E, Gill PG, Ingman WV, Graham JD, Buchanan G. The unique transcriptional response produced by concurrent estrogen and progesterone treatment in breast cancer cells results in upregulation of growth factor pathways and switching from a Luminal A to a Basal-like subtype. BMC Cancer 2015; 15:791. [PMID: 26498662 PMCID: PMC4620010 DOI: 10.1186/s12885-015-1819-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2015] [Accepted: 10/16/2015] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND In breast cancer, progesterone receptor (PR) positivity or abundance is positively associated with survival and treatment response. It was initially believed that PR was a useful diagnostic marker of estrogen receptor activity, but increasingly PR has been recognised to play an important biological role in breast homeostasis, carcinogenesis and metastasis. Although PR expression is almost exclusively observed in estrogen receptor positive tumors, few studies have investigated the cellular mechanisms of PR action in the context of ongoing estrogen signalling. METHODS In this study, we contrast PR function in estrogen pretreated ZR-75-1 breast cancer cells with vehicle treated ZR-75-1 and T-47D breast cancer cells using expression microarrays and chromatin immunoprecipitation-sequencing. RESULTS Estrogen cotreatment caused a dramatic increase in the number of genes regulated by progesterone in ZR-75-1 cells. In T-47D cells that have naturally high levels of PR, estrogen and progesterone cotreatment resulted in a reduction in the number of regulated genes in comparison to treatment with either hormone alone. At a genome level, estrogen pretreatment of ZR-75-1 cells led to a 10-fold increase in the number of PR DNA binding sites detected using ChIP-sequencing. Time course assessment of progesterone regulated genes in the context of estrogen pretreatment highlighted a series of important regulatory pathways, including those driven by epithelial growth factor receptor (EGFR). Importantly, progesterone applied to cells pretreated with estradiol resulted in switching of the PAM50-determined intrinsic breast cancer subtype from Luminal A to Basal-like, and increased the Oncotype DX® Unscaled Recurrence Score. CONCLUSION Estrogen pretreatment of breast cancer cells increases PR steady state levels, resulting in an unequivocal progesterone response that upregulates key members of growth factor pathways. The transformative changes progesterone exerts on the breast cancer subtype suggest that these subtyping tools should be used with caution in premenopausal women.
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Affiliation(s)
- Eleanor F Need
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia.
| | - Luke A Selth
- Dame Roma Mitchell Cancer Research Laboratories and Adelaide Prostate Cancer Research Centre, The University of Adelaide, Adelaide, South Australia, Australia. .,Freemasons Foundation Centre for Men's Health, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Andrew P Trotta
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia. .,Present address: Icahn School of Medicine at Mount Sinai, Department of Oncological Sciences, Manhattan, New York, USA.
| | - Damien A Leach
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia.
| | - Lauren Giorgio
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia.
| | - Melissa A O'Loughlin
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia.
| | - Eric Smith
- Solid Cancer Regulation Research Group, The Basil Hetzel Institute for Translational Health Research Discipline of Surgery, The University of Adelaide, South Australia, Australia.
| | - Peter G Gill
- School of Medicine, Department of Surgery, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Wendy V Ingman
- School of Medicine at The Queen Elizabeth Hospital, University of Adelaide, South Australia, Australia. .,Robinson Research Institute, University of Adelaide, South Australia, Australia.
| | - J Dinny Graham
- Centre for Cancer Research, Westmead Millennium Institute, University of Sydney Medical School, Westmead, New South Wales, 2145, Australia.
| | - Grant Buchanan
- Cancer Biology Group, The Basil Hetzel Institute for Translational Health Research, School of Medicine, The University of Adelaide, DX465701, 28 Woodville Road, Woodville South, 5011, South Australia, Australia. .,Freemasons Foundation Centre for Men's Health, The University of Adelaide, Adelaide, South Australia, Australia.
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19
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Trends in IT Innovation to Build a Next Generation Bioinformatics Solution to Manage and Analyse Biological Big Data Produced by NGS Technologies. BIOMED RESEARCH INTERNATIONAL 2015; 2015:904541. [PMID: 26125026 PMCID: PMC4466500 DOI: 10.1155/2015/904541] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Revised: 04/01/2015] [Accepted: 04/01/2015] [Indexed: 02/07/2023]
Abstract
Sequencing the human genome began in 1994, and 10 years of work were necessary in order to provide a nearly complete sequence. Nowadays, NGS technologies allow sequencing of a whole human genome in a few days. This deluge of data challenges scientists in many ways, as they are faced with data management issues and analysis and visualization drawbacks due to the limitations of current bioinformatics tools. In this paper, we describe how the NGS Big Data revolution changes the way of managing and analysing data. We present how biologists are confronted with abundance of methods, tools, and data formats. To overcome these problems, focus on Big Data Information Technology innovations from web and business intelligence. We underline the interest of NoSQL databases, which are much more efficient than relational databases. Since Big Data leads to the loss of interactivity with data during analysis due to high processing time, we describe solutions from the Business Intelligence that allow one to regain interactivity whatever the volume of data is. We illustrate this point with a focus on the Amadea platform. Finally, we discuss visualization challenges posed by Big Data and present the latest innovations with JavaScript graphic libraries.
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Wang P, Qin J, Qin Y, Zhu Y, Wang LY, Li MJ, Zhang MQ, Wang J. ChIP-Array 2: integrating multiple omics data to construct gene regulatory networks. Nucleic Acids Res 2015; 43:W264-9. [PMID: 25916854 PMCID: PMC4489297 DOI: 10.1093/nar/gkv398] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2015] [Accepted: 04/15/2015] [Indexed: 12/17/2022] Open
Abstract
Transcription factors (TFs) play an important role in gene regulation. The interconnections among TFs, chromatin interactions, epigenetic marks and cis-regulatory elements form a complex gene transcription apparatus. Our previous work, ChIP-Array, combined TF binding and transcriptome data to construct gene regulatory networks (GRNs). Here we present an enhanced version, ChIP-Array 2, to integrate additional types of omics data including long-range chromatin interaction, open chromatin region and histone modification data to dissect more comprehensive GRNs involving diverse regulatory components. Moreover, we substantially extended our motif database for human, mouse, rat, fruit fly, worm, yeast and Arabidopsis, and curated large amount of omics data for users to select as input or backend support. With ChIP-Array 2, we compiled a library containing regulatory networks of 18 TFs/chromatin modifiers in mouse embryonic stem cell (mESC). The web server and the mESC library are publicly free and accessible athttp://jjwanglab.org/chip-array.
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Affiliation(s)
- Panwen Wang
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
| | - Jing Qin
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
| | - Yiming Qin
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Yun Zhu
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
| | - Lily Yan Wang
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
| | - Mulin Jun Li
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
| | - Michael Q Zhang
- Bioinformatics Division, TNLIST, Tsinghua University, Beijing 100084, China Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas at Dallas, Dallas, TX 75080, USA
| | - Junwen Wang
- Centre for Genomic Sciences and Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, China
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21
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Jiang H, Salzman J. A penalized likelihood approach for robust estimation of isoform expression. STATISTICS AND ITS INTERFACE 2015; 8:437-445. [PMID: 27239250 PMCID: PMC4879778 DOI: 10.4310/sii.2015.v8.n4.a3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Ultra high-throughput sequencing of transcriptomes (RNA-Seq) has enabled the accurate estimation of gene expression at individual isoform level. However, systematic biases introduced during the sequencing and mapping processes as well as incompleteness of the transcript annotation databases may cause the estimates of isoform abundances to be unreliable, and in some cases, highly inaccurate. This paper introduces a penalized likelihood approach to detect and correct for such biases in a robust manner. Our model extends those previously proposed by introducing bias parameters for reads. An L1 penalty is used for the selection of non-zero bias parameters. We introduce an efficient algorithm for model fitting and analyze the statistical properties of the proposed model. Our experimental studies on both simulated and real datasets suggest that the model has the potential to improve isoform-specific gene expression estimates and identify incompletely annotated gene models.
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Affiliation(s)
- Hui Jiang
- Department of Biostatistics, Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Julia Salzman
- Department of Biochemistry, Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA
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Mokry M, Middendorp S, Wiegerinck CL, Witte M, Teunissen H, Meddens CA, Cuppen E, Clevers H, Nieuwenhuis EES. Many inflammatory bowel disease risk loci include regions that regulate gene expression in immune cells and the intestinal epithelium. Gastroenterology 2014; 146:1040-7. [PMID: 24333384 DOI: 10.1053/j.gastro.2013.12.003] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 11/30/2013] [Accepted: 12/03/2013] [Indexed: 12/12/2022]
Abstract
BACKGROUND & AIMS The contribution of genetic factors to the pathogenesis of inflammatory bowel disease (IBD) has been established by twin, targeted-sequencing, and genome-wide association studies. These studies identified many risk loci, and research is underway to identify causal variants. These studies have focused mainly on protein-coding genes. We investigated other functional elements in the human genome, such as regulatory regions. METHODS Using acetylated histone 3 lysine 27 chromatin immunoprecipitation and sequencing, we identified tens of thousands of potential regulatory regions that are active in intestinal epithelium (primary intestinal crypts and cultured organoids) isolated from resected material and from biopsies collected during ileo-colonoscopies and immune cells (monocytes, macrophages, CD34(+), CD4(+), and CD8(+)). We correlated these regions with susceptibility loci for IBD. RESULTS We have generated acetylated histone 3 lysine 27 profiles from primary intestinal epithelium and cultured organoids, which we have made publically available. We found that 45 of 163 single nucleotide polymorphisms (SNPs) associated with IBD overlap specifically with active regulatory elements. In addition, by taking strong linkage disequilibrium into account, another 47 IBD-associated SNPs colocalized with active regulatory elements through other SNPs in their vicinity. Altogether, 92 of 163 IBD-associated SNPs correlated with distinct active regulatory elements-a frequency 2.5- to 3.5-fold greater than that expected from random sampling. The variations in these SNPs often create or disrupt known binding motifs; they might affect the binding of transcriptional regulators to alter expression of regulated genes. CONCLUSIONS In addition to variants in protein coding genes, variants in noncoding DNA regulatory regions that are active in intestinal epithelium and immune cells are potentially involved in the pathogenesis of IBD.
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Affiliation(s)
- Michal Mokry
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sabine Middendorp
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Caroline L Wiegerinck
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Merlijn Witte
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; Hubrecht Institute for Stem Cell Research, Utrecht, The Netherlands
| | - Hans Teunissen
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; Hubrecht Institute for Stem Cell Research, Utrecht, The Netherlands
| | - Claartje A Meddens
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Edwin Cuppen
- Hubrecht Institute for Stem Cell Research, Utrecht, The Netherlands; Department of Medical Genetics, Medical Center Utrecht, Utrecht, The Netherlands
| | - Hans Clevers
- Hubrecht Institute for Stem Cell Research, Utrecht, The Netherlands
| | - Edward E S Nieuwenhuis
- Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands.
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Shi Y, Jiang H. rSeqDiff: detecting differential isoform expression from RNA-Seq data using hierarchical likelihood ratio test. PLoS One 2013; 8:e79448. [PMID: 24260225 PMCID: PMC3832546 DOI: 10.1371/journal.pone.0079448] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2013] [Accepted: 09/23/2013] [Indexed: 12/29/2022] Open
Abstract
High-throughput sequencing of transcriptomes (RNA-Seq) has recently become a powerful tool for the study of gene expression. We present rSeqDiff, an efficient algorithm for the detection of differential expression and differential splicing of genes from RNA-Seq experiments across multiple conditions. Unlike existing approaches which detect differential expression of transcripts, our approach considers three cases for each gene: 1) no differential expression, 2) differential expression without differential splicing and 3) differential splicing. We specify statistical models characterizing each of these three cases and use hierarchical likelihood ratio test for model selection. Simulation studies show that our approach achieves good power for detecting differentially expressed or differentially spliced genes. Comparisons with competing methods on two real RNA-Seq datasets demonstrate that our approach provides accurate estimates of isoform abundances and biological meaningful rankings of differentially spliced genes. The proposed approach is implemented as an R package named rSeqDiff.
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Affiliation(s)
- Yang Shi
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Hui Jiang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
- Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- * E-mail:
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Wang T, Liu J, Shen L, Tonti-Filippini J, Zhu Y, Jia H, Lister R, Whitaker JW, Ecker JR, Millar AH, Ren B, Wang W. STAR: an integrated solution to management and visualization of sequencing data. Bioinformatics 2013; 29:3204-10. [PMID: 24078702 DOI: 10.1093/bioinformatics/btt558] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
MOTIVATION Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data. RESULTS STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data. AVAILABILITY AND IMPLEMENTATION STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser.
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Affiliation(s)
- Tao Wang
- Department of Chemistry and Biochemistry, University of California, San Diego, CA 92093, USA, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA, The ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, Western Australia 6009, Australia, Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China, Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA, Department of Cellular and Molecular Medicine, University of California, San Diego, CA 92093, USA and Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
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Valekunja UK, Edgar RS, Oklejewicz M, van der Horst GTJ, O’Neill JS, Tamanini F, Turner DJ, Reddy AB. Histone methyltransferase MLL3 contributes to genome-scale circadian transcription. Proc Natl Acad Sci U S A 2013; 110:1554-9. [PMID: 23297224 PMCID: PMC3557088 DOI: 10.1073/pnas.1214168110] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Daily cyclical expression of thousands of genes in tissues such as the liver is orchestrated by the molecular circadian clock, the disruption of which is implicated in metabolic disorders and cancer. Although we understand much about the circadian transcription factors that can switch gene expression on and off, it is still unclear how global changes in rhythmic transcription are controlled at the genomic level. Here, we demonstrate circadian modification of an activating histone mark at a significant proportion of gene loci that undergo daily transcription, implicating widespread epigenetic modification as a key node regulated by the clockwork. Furthermore, we identify the histone-remodelling enzyme mixed lineage leukemia (MLL)3 as a clock-controlled factor that is able to directly and indirectly modulate over a hundred epigenetically targeted circadian "output" genes in the liver. Importantly, catalytic inactivation of the histone methyltransferase activity of MLL3 also severely compromises the oscillation of "core" clock gene promoters, including Bmal1, mCry1, mPer2, and Rev-erbα, suggesting that rhythmic histone methylation is vital for robust transcriptional oscillator function. This highlights a pathway by which the clockwork exerts genome-wide control over transcription, which is critical for sustaining temporal programming of tissue physiology.
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Affiliation(s)
- Utham K. Valekunja
- Department of Clinical Neurosciences, University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Rachel S. Edgar
- Department of Clinical Neurosciences, University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Malgorzata Oklejewicz
- Department of Genetics, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands; and
| | | | - John S. O’Neill
- Department of Clinical Neurosciences, University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Filippo Tamanini
- Department of Genetics, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands; and
| | - Daniel J. Turner
- Wellcome Trust Sanger Institute, Cambridge CB10 1SA, United Kingdom
| | - Akhilesh B. Reddy
- Department of Clinical Neurosciences, University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
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26
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Park JS, Ma W, O'Brien LL, Chung E, Guo JJ, Cheng JG, Valerius MT, McMahon JA, Wong WH, McMahon AP. Six2 and Wnt regulate self-renewal and commitment of nephron progenitors through shared gene regulatory networks. Dev Cell 2012; 23:637-51. [PMID: 22902740 DOI: 10.1016/j.devcel.2012.07.008] [Citation(s) in RCA: 188] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2011] [Revised: 05/24/2012] [Accepted: 07/15/2012] [Indexed: 01/09/2023]
Abstract
A balance between Six2-dependent self-renewal and canonical Wnt signaling-directed commitment regulates mammalian nephrogenesis. Intersectional studies using chromatin immunoprecipitation and transcriptional profiling identified direct target genes shared by each pathway within nephron progenitors. Wnt4 and Fgf8 are essential for progenitor commitment; cis-regulatory modules flanking each gene are cobound by Six2 and β-catenin and are dependent on conserved Lef/Tcf binding sites for activity. In vitro and in vivo analyses suggest that Six2 and Lef/Tcf factors form a regulatory complex that promotes progenitor maintenance while entry of β-catenin into this complex promotes nephrogenesis. Alternative transcriptional responses associated with Six2 and β-catenin cobinding events occur through non-Lef/Tcf DNA binding mechanisms, highlighting the regulatory complexity downstream of Wnt signaling in the developing mammalian kidney.
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Affiliation(s)
- Joo-Seop Park
- Division of Pediatric Urology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
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Qin J, Li MJ, Wang P, Zhang MQ, Wang J. ChIP-Array: combinatory analysis of ChIP-seq/chip and microarray gene expression data to discover direct/indirect targets of a transcription factor. Nucleic Acids Res 2011; 39:W430-6. [PMID: 21586587 PMCID: PMC3125757 DOI: 10.1093/nar/gkr332] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Chromatin immunoprecipitation (ChIP) coupled with high-throughput techniques (ChIP-X), such as next generation sequencing (ChIP-Seq) and microarray (ChIP–chip), has been successfully used to map active transcription factor binding sites (TFBS) of a transcription factor (TF). The targeted genes can be activated or suppressed by the TF, or are unresponsive to the TF. Microarray technology has been used to measure the actual expression changes of thousands of genes under the perturbation of a TF, but is unable to determine if the affected genes are direct or indirect targets of the TF. Furthermore, both ChIP-X and microarray methods produce a large number of false positives. Combining microarray expression profiling and ChIP-X data allows more effective TFBS analysis for studying the function of a TF. However, current web servers only provide tools to analyze either ChIP-X or expression data, but not both. Here, we present ChIP-Array, a web server that integrates ChIP-X and expression data from human, mouse, yeast, fruit fly and Arabidopsis. This server will assist biologists to detect direct and indirect target genes regulated by a TF of interest and to aid in the functional characterization of the TF. ChIP-Array is available at http://jjwanglab.hku.hk/ChIP-Array, with free access to academic users.
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Affiliation(s)
- Jing Qin
- Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong SAR, China
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Abstract
Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. This paper introduces a statistical model for estimating isoform abundance from RNA-Seq data and is flexible enough to accommodate both single end and paired end RNA-Seq data and sampling bias along the length of the transcript. Based on the derivation of minimal sufficient statistics for the model, a computationally feasible implementation of the maximum likelihood estimator of the model is provided. Further, it is shown that using paired end RNA-Seq provides more accurate isoform abundance estimates than single end sequencing at fixed sequencing depth. Simulation studies are also given.
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Affiliation(s)
- Julia Salzman
- Research Associate in the Department of Statistics and Biochemistry, Stanford University, Stanford, California 94305, USA
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29
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Abstract
Chromatin immunoprecipitation coupled with ultra-high-throug put parallel DNA sequencing (ChIP-seq) is an effective technology for the investigation of genome-wide protein-DNA interactions. Examples of applications include the studies of RNA polymerases transcription, transcriptional regulation, and histone modifications. The technology provides accurate and high-resolution mapping of the protein-DNA binding loci that are important in the understanding of many processes in development and diseases. Since the introduction of ChIP-seq experiments in 2007, many statistical and computational methods have been developed to support the analysis of the massive datasets from these experiments. However, because of the complex, multistaged analysis workflow, it is still difficult for an experimental investigator to conduct the analysis of his or her own ChIP-seq data. In this chapter, we review the basic design of ChIP-seq experiments and provide an in-depth tutorial on how to prepare, to preprocess, and to analyze ChIP-seq datasets. The tutorial is based on a revised version of our software package CisGenome, which was designed to encompass most standard tasks in ChIP-seq data analysis. Relevant statistical and computational issues will be highlighted, discussed, and illustrated by means of real data examples.
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Affiliation(s)
- Wenxiu Ma
- Department of Computer Science, Stanford University, Stanford, California, USA
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