1
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Boyd JR, Gao C, Quinn K, Fritz A, Stein J, Stein G, Glass K, Frietze S. peaksat: an R package for ChIP-seq peak saturation analysis. BMC Genomics 2023; 24:43. [PMID: 36698077 PMCID: PMC9878872 DOI: 10.1186/s12864-023-09109-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 01/02/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Epigenomic profiling assays such as ChIP-seq have been widely used to map the genome-wide enrichment profiles of chromatin-associated proteins and posttranslational histone modifications. Sequencing depth is a key parameter in experimental design and quality control. However, due to variable sequencing depth requirements across experimental conditions, it can be challenging to determine optimal sequencing depth, particularly for projects involving multiple targets or cell types. RESULTS We developed the peaksat R package to provide target read depth estimates for epigenomic experiments based on the analysis of peak saturation curves. We applied peaksat to establish the distinctive read depth requirements for ChIP-seq studies of histone modifications in different cell lines. Using peaksat, we were able to estimate the target read depth required per library to obtain high-quality peak calls for downstream analysis. In addition, peaksat was applied to other sequence-enrichment methods including CUT&RUN and ATAC-seq. CONCLUSION peaksat addresses a need for researchers to make informed decisions about whether their sequencing data has been generated to an adequate depth and subsequently sufficient meaningful peaks, and failing that, how many more reads would be required per library. peaksat is applicable to other sequence-based methods that include calling peaks in their analysis.
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Affiliation(s)
- Joseph R Boyd
- Department of Biomedical and Health Sciences, University of Vermont, 106 Carrigan Drive, 302 Rowell, VT, 04505, Burlington, USA
| | - Cong Gao
- Department of Biomedical and Health Sciences, University of Vermont, 106 Carrigan Drive, 302 Rowell, VT, 04505, Burlington, USA
| | - Kathleen Quinn
- Department of Biomedical and Health Sciences, University of Vermont, 106 Carrigan Drive, 302 Rowell, VT, 04505, Burlington, USA
| | - Andrew Fritz
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - Janet Stein
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
- University of Vermont Cancer Center, Burlington, VT, USA
| | - Gary Stein
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
- University of Vermont Cancer Center, Burlington, VT, USA
- Department of Surgery, University of Vermont, Burlington, VT, USA
| | - Karen Glass
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
- University of Vermont Cancer Center, Burlington, VT, USA
- Department of Pharmacology, University of Vermont, Burlington, VT, USA
| | - Seth Frietze
- Department of Biomedical and Health Sciences, University of Vermont, 106 Carrigan Drive, 302 Rowell, VT, 04505, Burlington, USA.
- Department of Biochemistry, University of Vermont, Burlington, VT, USA.
- University of Vermont Cancer Center, Burlington, VT, USA.
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2
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Xing L, Liu S, Zhang L, Yang H, Sun L. MITF Contributes to the Body Color Differentiation of Sea Cucumbers Apostichopus japonicus through Expression Differences and Regulation of Downstream Genes. BIOLOGY 2022; 12:biology12010001. [PMID: 36671694 PMCID: PMC9854957 DOI: 10.3390/biology12010001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/08/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
Melanin, which is a pigment produced in melanocytes, is an important contributor to sea cucumber body color. MITF is one of the most critical genes in melanocyte development and melanin synthesis pathways. However, how MITF regulates body color and differentiation in sea cucumbers is poorly understood. In this study, we analyzed the expression level and location of MITF in white, purple, and green sea cucumbers and identified the genes regulated by MITF using chromatin immunoprecipitation followed by sequencing. The mRNA and protein expression levels of MITF were all highest in purple morphs and lowest in white morphs. In situ hybridization indicated that MITF mRNA were mainly expressed in the epidermis. We also identified 984, 732, and 1191 peaks of MITF binding in green, purple, and white sea cucumbers, which were associated with 727, 557, and 887 genes, respectively. Our findings suggested that MITF contributed to the body color differentiation of green, purple, and white sea cucumbers through expression differences and regulation of downstream genes. These results provided a basis for future studies to determine the mechanisms underlying body color formation and provided insights into gene regulation in sea cucumbers.
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Affiliation(s)
- Lili Xing
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shilin Liu
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Libin Zhang
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongsheng Yang
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Shandong Province Key Laboratory of Experimental Marine Biology, Qingdao 266071, China
- The Innovation of Seed Design, Chinese Academy of Sciences, Wuhan 430071, China
| | - Lina Sun
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Correspondence: ; Tel./Fax: +86-532-8289-8610
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3
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Steinhaus R, Gonzalez T, Seelow D, Robinson PN. Pervasive and CpG-dependent promoter-like characteristics of transcribed enhancers. Nucleic Acids Res 2020; 48:5306-5317. [PMID: 32338759 PMCID: PMC7261191 DOI: 10.1093/nar/gkaa223] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 03/23/2020] [Accepted: 03/25/2020] [Indexed: 12/17/2022] Open
Abstract
The temporal and spatial expression of genes is controlled by promoters and enhancers. Findings obtained over the last decade that not only promoters but also enhancers are characterized by bidirectional, divergent transcription have challenged the traditional notion that promoters and enhancers represent distinct classes of regulatory elements. Over half of human promoters are associated with CpG islands (CGIs), relatively CpG-rich stretches of generally several hundred nucleotides that are often associated with housekeeping genes. Only about 6% of transcribed enhancers defined by CAGE-tag analysis are associated with CGIs. Here, we present an analysis of enhancer and promoter characteristics and relate them to the presence or absence of CGIs. We show that transcribed enhancers share a number of CGI-dependent characteristics with promoters, including statistically significant local overrepresentation of core promoter elements. CGI-associated enhancers are longer, display higher directionality of transcription, greater expression, a lesser degree of tissue specificity, and a higher frequency of transcription-factor binding events than non-CGI-associated enhancers. Genes putatively regulated by CGI-associated enhancers are enriched for transcription regulator activity. Our findings show that CGI-associated transcribed enhancers display a series of characteristics related to sequence, expression and function that distinguish them from enhancers not associated with CGIs.
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Affiliation(s)
- Robin Steinhaus
- Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.,Institute of Medical Genetics and Human Genetics, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Tonatiuh Gonzalez
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.,Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA
| | - Dominik Seelow
- Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.,Institute of Medical Genetics and Human Genetics, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Peter N Robinson
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.,Institute for Systems Genomics, University of Connecticut, 263 Farmington Avenue, Farmington, CT 06030, USA
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4
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Ibn-Salem J, Andrade-Navarro MA. 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs. BMC Genomics 2019; 20:777. [PMID: 31653198 PMCID: PMC6814980 DOI: 10.1186/s12864-019-6088-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 09/09/2019] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Knowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range chromatin interactions genome-wide but are experimentally elaborate, have limited resolution and such data is only available for a limited number of cell types and tissues. RESULTS While ChIP-seq was not designed to detect chromatin interactions, the formaldehyde treatment in the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, also regions that are not directly bound by the targeted TF but interact with the binding site via chromatin looping are co-immunoprecipitated and sequenced. This produces minor ChIP-seq signals at loop anchor regions close to the directly bound site. We use the position and shape of ChIP-seq signals around CTCF motif pairs to predict whether they interact or not. We implemented this approach in a prediction method, termed Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C). We applied 7C to all CTCF motif pairs within 1 Mb in the human genome and validated predicted interactions with high-resolution Hi-C and ChIA-PET. A single ChIP-seq experiment from known architectural proteins (CTCF, Rad21, Znf143) but also from other TFs (like TRIM22 or RUNX3) predicts loops accurately. Importantly, 7C predicts loops in cell types and for TF ChIP-seq datasets not used in training. CONCLUSION 7C predicts chromatin loops which can help to associate TF binding sites to regulated genes. Furthermore, profiling of hundreds of ChIP-seq datasets results in novel candidate factors functionally involved in chromatin looping. Our method is available as an R/Bioconductor package: http://bioconductor.org/packages/sevenC .
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Affiliation(s)
- Jonas Ibn-Salem
- Faculty of Biology, Johannes Gutenberg University of Mainz, 55128, Mainz, Germany.
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5
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Nakato R, Shirahige K. Sensitive and robust assessment of ChIP-seq read distribution using a strand-shift profile. Bioinformatics 2019. [PMID: 29528371 DOI: 10.1093/bioinformatics/bty137] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Motivation Chromatin immunoprecipitation followed by sequencing (ChIP-seq) can detect read-enriched DNA loci for point-source (e.g. transcription factor binding) and broad-source factors (e.g. various histone modifications). Although numerous quality metrics for ChIP-seq data have been developed, the 'peaks' thus obtained are still difficult to assess with respect to signal-to-noise ratio (S/N) and the percentage of false positives. Results We developed a quality-assessment tool for ChIP-seq data, strand-shift profile (SSP), which quantifies S/N and peak reliability without peak calling. We validated SSP in-depth using ≥ 1000 publicly available ChIP-seq datasets along with virtual data to demonstrate that SSP provides a quantifiable and sensitive score to different S/Ns for both point- and broad-source factors, which can be standardized across diverse cell types and read depths. SSP also provides an effective criterion to judge whether a specific normalization or a rejection is required for each sample, which cannot be estimated by quality metrics currently available. Finally, we show that 'hidden-duplicate reads' cause aberrantly high S/Ns, and SSP provides an additional metric to avoid them, which can also contribute to estimation of peak mode (point- or broad-source) of samples. Availability and implementation SSP is open source software written in C++ and can be downloaded at https://github.com/rnakato/SSP. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ryuichiro Nakato
- Research Center for Epigenetic Disease, Institute of Molecular and Cellular Biosciences, University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, Japan
| | - Katsuhiko Shirahige
- Research Center for Epigenetic Disease, Institute of Molecular and Cellular Biosciences, University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, Japan
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6
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Grygoryev D, Rountree MR, Rwatambuga F, Ohlrich A, Kukino A, Butler MP, Allen CN, Turker MS. Rapid Response and Slow Recovery of the H3K4me3 Epigenomic Marker in the Liver after Light-mediated Phase Advances of the Circadian Clock. J Biol Rhythms 2018; 33:363-375. [PMID: 29888643 DOI: 10.1177/0748730418779958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Mammalian tissues display circadian rhythms in transcription, translation, and histone modifications. Here we asked how an advance of the light-dark cycle alters daily rhythms in the liver epigenome at the H3K4me3 (trimethylation of lysine 4 on histone 3) modification, which is found at active and poised gene promoters. H3K4me3 levels were first measured at 4 time points (zeitgeber time [ZT] 3, 8, 15, and 20) during a normal 12L:12D light-dark cycle. Peak levels were observed during the early dark phase at ZT15 and dropped to low levels around lights-on (ZT0) between ZT20 and ZT3. A 6-h phase advance at ZT18 (new lights-on after only 6 h of darkness) led to a transient extension of peak H3K4me3 levels. Although locomotor activity reentrained within a week after the phase advance, H3K4me3 rhythms failed to do so, with peak levels remaining in the light phase at the 1-week recovery time point. Eight weekly phase advances, with 1-week recovery times between each phase advance, further disrupted the H3K4me3 rhythms. Finally, we used the mPer2Luc knockin mouse to determine whether the phase advance also disrupted Per2 protein expression. Similar to the results from the histone work, we found both a rapid response to the phase advance and a delayed recovery, the latter in sync with H3K4me3 levels. A model to explain these results is offered.
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Affiliation(s)
- Dmytro Grygoryev
- 1 These authors contributed equally to this study.,Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon
| | - Michael R Rountree
- 1 These authors contributed equally to this study.,Nzumbe Inc., Portland, Oregon
| | - Furaha Rwatambuga
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon
| | - Anna Ohlrich
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon
| | - Ayaka Kukino
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon
| | - Matthew P Butler
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon.,Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon
| | - Charles N Allen
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon.,Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon
| | - Mitchell S Turker
- Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon.,Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, Oregon
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7
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Zhang Y, Pitchiaya S, Cieślik M, Niknafs YS, Tien JCY, Hosono Y, Iyer MK, Yazdani S, Subramaniam S, Shukla SK, Jiang X, Wang L, Liu TY, Uhl M, Gawronski AR, Qiao Y, Xiao L, Dhanasekaran SM, Juckette KM, Kunju LP, Cao X, Patel U, Batish M, Shukla GC, Paulsen MT, Ljungman M, Jiang H, Mehra R, Backofen R, Sahinalp CS, Freier SM, Watt AT, Guo S, Wei JT, Feng FY, Malik R, Chinnaiyan AM. Analysis of the androgen receptor-regulated lncRNA landscape identifies a role for ARLNC1 in prostate cancer progression. Nat Genet 2018; 50:814-824. [PMID: 29808028 PMCID: PMC5980762 DOI: 10.1038/s41588-018-0120-1] [Citation(s) in RCA: 161] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Accepted: 03/23/2018] [Indexed: 12/23/2022]
Abstract
The androgen receptor (AR) plays a critical role in the development of the normal prostate as well as prostate cancer. Using an integrative transcriptomic analysis of prostate cancer cell lines and tissues, we identified ARLNC1 (AR-regulated long non-coding RNA 1) as an important long non-coding RNA that is strongly associated with AR signaling in prostate cancer progression. Not only was ARLNC1 induced by AR protein, ARLNC1 stabilized the AR transcript via RNA-RNA interaction. ARLNC1 knockdown suppressed AR expression, global AR signaling, and prostate cancer growth in vitro and in vivo. Taken together, these data support a role for ARLNC1 in maintaining a positive feedback loop that potentiates AR signaling during prostate cancer progression, and identifies ARLNC1 as a novel therapeutic target.
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Affiliation(s)
- Yajia Zhang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA.,Molecular and Cellular Pathology Program, University of Michigan, Ann Arbor, MI, USA.,Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
| | - Sethuramasundaram Pitchiaya
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Marcin Cieślik
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Yashar S Niknafs
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI, USA
| | - Jean C-Y Tien
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Yasuyuki Hosono
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Matthew K Iyer
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
| | - Sahr Yazdani
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Shruthi Subramaniam
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Sudhanshu K Shukla
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, India
| | - Xia Jiang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Lisha Wang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Tzu-Ying Liu
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Uhl
- Department of Computer Science and Centre for Biological Signaling Studies (BIOSS), University of Freiburg, Freiburg, Germany
| | - Alexander R Gawronski
- School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Yuanyuan Qiao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA.,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Lanbo Xiao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Saravana M Dhanasekaran
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kristin M Juckette
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Lakshmi P Kunju
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Department of Pathology, University of Michigan, Ann Arbor, MI, USA.,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Xuhong Cao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI, USA
| | - Utsav Patel
- New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Mona Batish
- New Jersey Medical School, Rutgers University, Newark, NJ, USA.,Department of Medical Laboratory Sciences, University of Delaware, Newark, DE, USA
| | - Girish C Shukla
- Department of Biological, Geological and Environmental Sciences, Center for Gene Regulation in Health and Disease, Cleveland State Univesity, Cleveland, OH, USA
| | - Michelle T Paulsen
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Mats Ljungman
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Hui Jiang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Rohit Mehra
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.,Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Rolf Backofen
- Department of Computer Science and Centre for Biological Signaling Studies (BIOSS), University of Freiburg, Freiburg, Germany
| | - Cenk S Sahinalp
- School of Informatics and Computing, Indiana University, Bloomington, IN, USA.,Vancouver Prostate Centre, Vancouver, British Columbia, Canada
| | | | | | | | - John T Wei
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Felix Y Feng
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.,Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.,Breast Oncology Program, University of Michigan, Ann Arbor, MI, USA.,Departments of Radiation Oncology, Urology, and Medicine, Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, CA, USA
| | - Rohit Malik
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.,Bristol-Myers Squibb, Princeton, NJ, USA
| | - Arul M Chinnaiyan
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA. .,Department of Pathology, University of Michigan, Ann Arbor, MI, USA. .,Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA. .,Department of Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI, USA. .,Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA. .,Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI, USA. .,Department of Urology, University of Michigan, Ann Arbor, MI, USA.
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8
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Stanton KP, Jin J, Lederman RR, Weissman SM, Kluger Y. Ritornello: high fidelity control-free chromatin immunoprecipitation peak calling. Nucleic Acids Res 2017; 45:e173. [PMID: 28981893 PMCID: PMC5716106 DOI: 10.1093/nar/gkx799] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Accepted: 08/30/2017] [Indexed: 02/03/2023] Open
Abstract
With the advent of next generation high-throughput DNA sequencing technologies, omics experiments have become the mainstay for studying diverse biological effects on a genome wide scale. Chromatin immunoprecipitation (ChIP-seq) is the omics technique that enables genome wide localization of transcription factor (TF) binding or epigenetic modification events. Since the inception of ChIP-seq in 2007, many methods have been developed to infer ChIP-target binding loci from the resultant reads after mapping them to a reference genome. However, interpreting these data has proven challenging, and as such these algorithms have several shortcomings, including susceptibility to false positives due to artifactual peaks, poor localization of binding sites and the requirement for a total DNA input control which increases the cost of performing these experiments. We present Ritornello, a new approach for finding TF-binding sites in ChIP-seq, with roots in digital signal processing that addresses all of these problems. We show that Ritornello generally performs equally or better than the peak callers tested and recommended by the ENCODE consortium, but in contrast, Ritornello does not require a matched total DNA input control to avoid false positives, effectively decreasing the sequencing cost to perform ChIP-seq. Ritornello is freely available at https://github.com/KlugerLab/Ritornello.
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Affiliation(s)
- Kelly P Stanton
- Department of Pathology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA.,Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Jiaqi Jin
- Department of Genetics, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA
| | - Roy R Lederman
- Program of Applied Mathematics, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.,Department of Mathematics and PACM, Princeton University, Fine Hall, Washington Road, Princeton, NJ 08544-1000, USA
| | - Sherman M Weissman
- Department of Genetics, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA
| | - Yuval Kluger
- Department of Pathology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA.,Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.,Program of Applied Mathematics, Yale University, 51 Prospect Street, New Haven, CT 06511, USA
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9
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Nakato R, Shirahige K. Recent advances in ChIP-seq analysis: from quality management to whole-genome annotation. Brief Bioinform 2017; 18:279-290. [PMID: 26979602 PMCID: PMC5444249 DOI: 10.1093/bib/bbw023] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Indexed: 02/06/2023] Open
Abstract
Chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis can detect protein/DNA-binding and histone-modification sites across an entire genome. Recent advances in sequencing technologies and analyses enable us to compare hundreds of samples simultaneously; such large-scale analysis has potential to reveal the high-dimensional interrelationship level for regulatory elements and annotate novel functional genomic regions de novo. Because many experimental considerations are relevant to the choice of a method in a ChIP-seq analysis, the overall design and quality management of the experiment are of critical importance. This review offers guiding principles of computation and sample preparation for ChIP-seq analyses, highlighting the validity and limitations of the state-of-the-art procedures at each step. We also discuss the latest challenges of single-cell analysis that will encourage a new era in this field.
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Affiliation(s)
- Ryuichiro Nakato
- Research Center for Epigenetic Disease, Institute of Molecular and Cellular Biosciences, The University of Tokyo, Tokyo, Japan
| | - Katsuhiko Shirahige
- Research Center for Epigenetic Disease, Institute of Molecular and Cellular Biosciences, The University of Tokyo, Tokyo, Japan.,Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Kawaguchi, Japan
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10
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Angarica VE, Del Sol A. Bioinformatics Tools for Genome-Wide Epigenetic Research. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 978:489-512. [PMID: 28523562 DOI: 10.1007/978-3-319-53889-1_25] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Epigenetics play a central role in the regulation of many important cellular processes, and dysregulations at the epigenetic level could be the source of serious pathologies, such as neurological disorders affecting brain development, neurodegeneration, and intellectual disability. Despite significant technological advances for epigenetic profiling, there is still a need for a systematic understanding of how epigenetics shapes cellular circuitry, and disease pathogenesis. The development of accurate computational approaches for analyzing complex epigenetic profiles is essential for disentangling the mechanisms underlying cellular development, and the intricate interaction networks determining and sensing chromatin modifications and DNA methylation to control gene expression. In this chapter, we review the recent advances in the field of "computational epigenetics," including computational methods for processing different types of epigenetic data, prediction of chromatin states, and study of protein dynamics. We also discuss how "computational epigenetics" has complemented the fast growth in the generation of epigenetic data for uncovering the main differences and similarities at the epigenetic level between individuals and the mechanisms underlying disease onset and progression.
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Affiliation(s)
- Vladimir Espinosa Angarica
- Computational Biology Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6 Avenue du Swing, 4366 Belvaux, Luxembourg.
| | - Antonio Del Sol
- Computational Biology Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6 Avenue du Swing, 4366 Belvaux, Luxembourg
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11
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Reinert K, Dadi TH, Ehrhardt M, Hauswedell H, Mehringer S, Rahn R, Kim J, Pockrandt C, Winkler J, Siragusa E, Urgese G, Weese D. The SeqAn C++ template library for efficient sequence analysis: A resource for programmers. J Biotechnol 2017; 261:157-168. [PMID: 28888961 DOI: 10.1016/j.jbiotec.2017.07.017] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Revised: 07/17/2017] [Accepted: 07/19/2017] [Indexed: 11/27/2022]
Abstract
BACKGROUND The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome (Venter et al., 2001) would not have been possible without advanced assembly algorithms and the development of practical BWT based read mappers have been instrumental for NGS analysis. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there was a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. We previously addressed this by introducing the SeqAn library of efficient data types and algorithms in 2008 (Döring et al., 2008). RESULTS The SeqAn library has matured considerably since its first publication 9 years ago. In this article we review its status as an established resource for programmers in the field of sequence analysis and its contributions to many analysis tools. CONCLUSIONS We anticipate that SeqAn will continue to be a valuable resource, especially since it started to actively support various hardware acceleration techniques in a systematic manner.
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Affiliation(s)
- Knut Reinert
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany.
| | - Temesgen Hailemariam Dadi
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - Marcel Ehrhardt
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - Hannes Hauswedell
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - Svenja Mehringer
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - René Rahn
- Algorithmic Bioinformatics, Institute for Bioinformatics, FU Berlin, Takustrasse 9, 14195 Berlin, Germany
| | - Jongkyu Kim
- Efficient Algorithms for -Omics Data, Max Planck Institute for Molecular Genetics, Ihnestrasse 62-73, 14195 Berlin, Germany
| | - Christopher Pockrandt
- Efficient Algorithms for -Omics Data, Max Planck Institute for Molecular Genetics, Ihnestrasse 62-73, 14195 Berlin, Germany
| | - Jörg Winkler
- Efficient Algorithms for -Omics Data, Max Planck Institute for Molecular Genetics, Ihnestrasse 62-73, 14195 Berlin, Germany
| | | | - Gianvito Urgese
- Department of Control and Computer Engineering, Politecnico di Torino, Italy
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12
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Arthur RK, An N, Khan S, McNerney ME. The haploinsufficient tumor suppressor, CUX1, acts as an analog transcriptional regulator that controls target genes through distal enhancers that loop to target promoters. Nucleic Acids Res 2017; 45:6350-6361. [PMID: 28369554 PMCID: PMC5499738 DOI: 10.1093/nar/gkx218] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2016] [Revised: 03/21/2017] [Accepted: 03/24/2017] [Indexed: 01/19/2023] Open
Abstract
One third of tumor suppressors are haploinsufficient transcriptional regulators, yet it remains unknown how a 50% reduction of a transcription factor is translated at the cis-regulatory level into a malignant transcriptional program. We studied CUX1, a haploinsufficient transcription factor that is recurrently mutated in hematopoietic and solid tumors. We determined CUX1 DNA-binding and target gene regulation in the wildtype and haploinsufficient states. CUX1 binds with transcriptional activators and cohesin at distal enhancers across three different human cell types. Haploinsufficiency of CUX1 altered the expression of a large number of genes, including cell cycle regulators, with concomitant increased cellular proliferation. Surprisingly, CUX1 occupancy decreased genome-wide in the haploinsufficient state, and binding site affinity did not correlate with differential gene expression. Instead, differentially expressed genes had multiple, low-affinity CUX1 binding sites, features of analog gene regulation. A machine-learning algorithm determined that chromatin accessibility, enhancer activity, and distance to the transcription start site are features of dose-sensitive CUX1 transcriptional regulation. Moreover, CUX1 is enriched at sites of DNA looping, as determined by Hi-C analysis, and these loops connect CUX1 to the promoters of regulated genes. We propose an analog model for haploinsufficient transcriptional deregulation mediated by higher order genome architecture.
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Affiliation(s)
- Robert K. Arthur
- Department of Pathology, Department of Pediatrics, Section of Hematology/Oncology, and The University of Chicago Medicine Comprehensive Cancer Center, The University of Chicago, Chicago, IL 60637, USA
| | - Ningfei An
- Department of Pathology, Department of Pediatrics, Section of Hematology/Oncology, and The University of Chicago Medicine Comprehensive Cancer Center, The University of Chicago, Chicago, IL 60637, USA
| | - Saira Khan
- Department of Pathology, Department of Pediatrics, Section of Hematology/Oncology, and The University of Chicago Medicine Comprehensive Cancer Center, The University of Chicago, Chicago, IL 60637, USA
| | - Megan E. McNerney
- Department of Pathology, Department of Pediatrics, Section of Hematology/Oncology, and The University of Chicago Medicine Comprehensive Cancer Center, The University of Chicago, Chicago, IL 60637, USA
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13
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Andrey G, Schöpflin R, Jerković I, Heinrich V, Ibrahim DM, Paliou C, Hochradel M, Timmermann B, Haas S, Vingron M, Mundlos S. Characterization of hundreds of regulatory landscapes in developing limbs reveals two regimes of chromatin folding. Genome Res 2016; 27:223-233. [PMID: 27923844 PMCID: PMC5287228 DOI: 10.1101/gr.213066.116] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 12/06/2016] [Indexed: 11/24/2022]
Abstract
Complex regulatory landscapes control the pleiotropic transcriptional activities of developmental genes. For most genes, the number, location, and dynamics of their associated regulatory elements are unknown. In this work, we characterized the three-dimensional chromatin microarchitecture and regulatory landscape of 446 limb-associated gene loci in mouse using Capture-C, ChIP-seq, and RNA-seq in forelimb, hindlimb at three developmental stages, and midbrain. The fine mapping of chromatin interactions revealed a strong preference for functional genomic regions such as repressed or active domains. By combining chromatin marks and interaction peaks, we annotated more than 1000 putative limb enhancers and their associated genes. Moreover, the analysis of chromatin interactions revealed two regimes of chromatin folding, one producing interactions stable across tissues and stages and another one associated with tissue and/or stage-specific interactions. Whereas stable interactions associate strongly with CTCF/RAD21 binding, the intensity of variable interactions correlates with changes in underlying chromatin modifications, specifically at the viewpoint and at the interaction site. In conclusion, this comprehensive data set provides a resource for the characterization of hundreds of limb-associated regulatory landscapes and a framework to interpret the chromatin folding dynamics observed during embryogenesis.
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Affiliation(s)
- Guillaume Andrey
- RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Robert Schöpflin
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Ivana Jerković
- RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Verena Heinrich
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Daniel M Ibrahim
- RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.,Institute for Medical and Human Genetics, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany
| | - Christina Paliou
- RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Myriam Hochradel
- Max Planck Institute for Molecular Genetics, Sequencing Core Facility, 14195 Berlin, Germany
| | - Bernd Timmermann
- Max Planck Institute for Molecular Genetics, Sequencing Core Facility, 14195 Berlin, Germany
| | - Stefan Haas
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Martin Vingron
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Stefan Mundlos
- RG Development & Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.,Institute for Medical and Human Genetics, Charité Universitätsmedizin Berlin, 13353 Berlin, Germany.,Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité Universitätsmedizin Berlin, 13353 Berlin, Germany
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14
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Hansen P, Hecht J, Ibn-Salem J, Menkuec BS, Roskosch S, Truss M, Robinson PN. Q-nexus: a comprehensive and efficient analysis pipeline designed for ChIP-nexus. BMC Genomics 2016; 17:873. [PMID: 27814676 PMCID: PMC5097360 DOI: 10.1186/s12864-016-3164-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Accepted: 10/12/2016] [Indexed: 12/22/2022] Open
Abstract
Background ChIP-nexus, an extension of the ChIP-exo protocol, can be used to map the borders of protein-bound DNA sequences at nucleotide resolution, requires less input DNA and enables selective PCR duplicate removal using random barcodes. However, the use of random barcodes requires additional preprocessing of the mapping data, which complicates the computational analysis. To date, only a very limited number of software packages are available for the analysis of ChIP-exo data, which have not yet been systematically tested and compared on ChIP-nexus data. Results Here, we present a comprehensive software package for ChIP-nexus data that exploits the random barcodes for selective removal of PCR duplicates and for quality control. Furthermore, we developed bespoke methods to estimate the width of the protected region resulting from protein-DNA binding and to infer binding positions from ChIP-nexus data. Finally, we applied our peak calling method as well as the two other methods MACE and MACS2 to the available ChIP-nexus data. Conclusions The Q-nexus software is efficient and easy to use. Novel statistics about duplication rates in consideration of random barcodes are calculated. Our method for the estimation of the width of the protected region yields unbiased signatures that are highly reproducible for biological replicates and at the same time very specific for the respective factors analyzed. As judged by the irreproducible discovery rate (IDR), our peak calling algorithm shows a substantially better reproducibility. An implementation of Q-nexus is available at http://charite.github.io/Q/. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3164-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Peter Hansen
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany.,Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Jochen Hecht
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Jonas Ibn-Salem
- Faculty of Biology, Johannes Gutenberg University Mainz, Ackermannweg 4, Mainz, 55128, Germany.,Institute of Molecular Biology, Ackermannweg 4, Mainz, 55128, Germany
| | - Benjamin S Menkuec
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Sebastian Roskosch
- Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 14, Berlin, 14195, Germany
| | - Matthias Truss
- Labor für Pädiatrische Molekularbiologie, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Peter N Robinson
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany. .,Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany. .,Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 14, Berlin, 14195, Germany. .,Max Planck Institute for Molecular Genetics, Inhestr. 63-73, Berlin, 14195, Germany. .,Current address: The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, 06032, CT, USA.
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15
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Lo YH, Chung E, Li Z, Wan YW, Mahe MM, Chen MS, Noah TK, Bell KN, Yalamanchili HK, Klisch TJ, Liu Z, Park JS, Shroyer NF. Transcriptional Regulation by ATOH1 and its Target SPDEF in the Intestine. Cell Mol Gastroenterol Hepatol 2016; 3:51-71. [PMID: 28174757 PMCID: PMC5247424 DOI: 10.1016/j.jcmgh.2016.10.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 10/13/2016] [Indexed: 01/08/2023]
Abstract
BACKGROUND & AIMS The transcription factor atonal homolog 1 (ATOH1) controls the fate of intestinal progenitors downstream of the Notch signaling pathway. Intestinal progenitors that escape Notch activation express high levels of ATOH1 and commit to a secretory lineage fate, implicating ATOH1 as a gatekeeper for differentiation of intestinal epithelial cells. Although some transcription factors downstream of ATOH1, such as SPDEF, have been identified to specify differentiation and maturation of specific cell types, the bona fide transcriptional targets of ATOH1 still largely are unknown. Here, we aimed to identify ATOH1 targets and to identify transcription factors that are likely to co-regulate gene expression with ATOH1. METHODS We used a combination of chromatin immunoprecipitation and messenger RNA-based high-throughput sequencing (ChIP-seq and RNA-seq), together with cell sorting and transgenic mice, to identify direct targets of ATOH1, and establish the epistatic relationship between ATOH1 and SPDEF. RESULTS By using unbiased genome-wide approaches, we identified more than 700 genes as ATOH1 transcriptional targets in adult small intestine and colon. Ontology analysis indicated that ATOH1 directly regulates genes involved in specification and function of secretory cells. De novo motif analysis of ATOH1 targets identified SPDEF as a putative transcriptional co-regulator of ATOH1. Functional epistasis experiments in transgenic mice show that SPDEF amplifies ATOH1-dependent transcription but cannot independently initiate transcription of ATOH1 target genes. CONCLUSIONS This study unveils the direct targets of ATOH1 in the adult intestines and illuminates the transcriptional events that initiate the specification and function of intestinal secretory lineages.
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Key Words
- ATOH1
- ATOH1, atonal homolog 1
- Atoh1Flag
- Atoh1GFP
- CRC, colorectal cancer
- ChIP, chromatin immunoprecipitation
- ChIP-seq, chromatin immunoprecipitation sequencing
- DBZ, dibenzazepine
- FACS, fluorescence-activated cell sorting
- FDR, false-discovery rate
- GFP, green fluorescent protein
- GO, gene ontology
- Gfi1, growth factor independent 1
- ISC, intestinal stem cell
- Intestinal Epithelium
- PBS, phosphate-buffered saline
- PCR, polymerase chain reaction
- QES, Q-enrichment-score
- RT-qPCR, reverse-transcription quantitative polymerase chain reaction
- SPDEF
- Spdef, SAM pointed domain containing ETS transcription factor
- TRE-Spdef
- TSS, transcription start site
- Transcription
- Villin-creER
- mRNA, messenger RNA
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Affiliation(s)
- Yuan-Hung Lo
- Integrative Molecular and Biomedical Sciences Graduate Program, Baylor College of Medicine, Houston, Texas
| | - Eunah Chung
- Division of Pediatric Urology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Zhaohui Li
- Jan and Dan Duncan Neurological Research Institute, Houston, Texas
| | - Ying-Wooi Wan
- Jan and Dan Duncan Neurological Research Institute, Houston, Texas
| | - Maxime M. Mahe
- Department of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Min-Shan Chen
- Integrative Molecular and Biomedical Sciences Graduate Program, Baylor College of Medicine, Houston, Texas
| | - Taeko K. Noah
- Division of Gastroenterology, Hepatology, and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Kristin N. Bell
- Graduate Program in Molecular Developmental Biology, University of Cincinnati, Cincinnati, Cincinnati, Ohio
| | | | - Tiemo J. Klisch
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Zhandong Liu
- Department of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Joo-Seop Park
- Division of Pediatric Urology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
- Joo-Seop Park, PhD, Divisions of Pediatric Urology and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.Divisions of Pediatric Urology and Developmental BiologyCincinnati Children's Hospital Medical CenterCincinnatiOhio
| | - Noah F. Shroyer
- Integrative Molecular and Biomedical Sciences Graduate Program, Baylor College of Medicine, Houston, Texas
- Division of Medicine, Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas
- Correspondence Address correspondence to: Noah F. Shroyer, PhD, Division of Medicine, Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas.Division of MedicineSection of Gastroenterology and HepatologyBaylor College of MedicineHoustonTexas
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16
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Park SJ, Saito-Adachi M, Komiyama Y, Nakai K. Advances, practice, and clinical perspectives in high-throughput sequencing. Oral Dis 2016; 22:353-64. [DOI: 10.1111/odi.12403] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Revised: 11/16/2015] [Accepted: 11/16/2015] [Indexed: 01/06/2023]
Affiliation(s)
- S-J Park
- Human Genome Center; The Institute of Medical Science; The University of Tokyo; Tokyo Japan
| | - M Saito-Adachi
- Division of Cancer Genomics; National Cancer Center Research Institute; Tokyo Japan
| | - Y Komiyama
- Human Genome Center; The Institute of Medical Science; The University of Tokyo; Tokyo Japan
| | - K Nakai
- Human Genome Center; The Institute of Medical Science; The University of Tokyo; Tokyo Japan
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