1
|
Mai L, Wen Z, Zhang Y, Gao Y, Lin G, Lian Z, Yang X, Zhou J, Lin X, Luo C, Peng W, Chen C, Peng J, Liu D, Marjani SL, Tao Q, Cui Y, Zhang J, Wu X, Weissman SM, Pan X. Shortcut barcoding and early pooling for scalable multiplex single-cell reduced-representation CpG methylation sequencing at single nucleotide resolution. Nucleic Acids Res 2023; 51:e108. [PMID: 37870443 PMCID: PMC10681715 DOI: 10.1093/nar/gkad892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 09/25/2023] [Accepted: 10/04/2023] [Indexed: 10/24/2023] Open
Abstract
DNA methylation is essential for a wide variety of biological processes, yet the development of a highly efficient and robust technology remains a challenge for routine single-cell analysis. We developed a multiplex scalable single-cell reduced representation bisulfite sequencing (msRRBS) technology. It allows cell-specific barcoded DNA fragments of individual cells to be pooled before bisulfite conversion, free of enzymatic modification or physical capture of the DNA ends, and achieves read mapping rates of 62.5 ± 3.9%, covering 60.0 ± 1.4% of CpG islands and 71.6 ± 1.6% of promoters in K562 cells. Its reproducibility is shown in duplicates of bulk cells with close to perfect correlation (R = 0.97-0.99). At a low 1 Mb of clean reads, msRRBS provides highly consistent coverage of CpG islands and promoters, outperforming the conventional methods with orders of magnitude reduction in cost. Here, we use this method to characterize the distinct methylation patterns and cellular heterogeneity of six cell lines, plus leukemia and hepatocellular carcinoma models. Taking 4 h of hands-on time, msRRBS offers a unique, highly efficient approach for dissecting methylation heterogeneity in a variety of multicellular systems.
Collapse
Affiliation(s)
- Liyao Mai
- Department of Hepatobiliary Surgery II, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, Guangdong Province, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Zebin Wen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Yulong Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Yu Gao
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Guanchuan Lin
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Zhiwei Lian
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Xiang Yang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
- Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China
| | - Jingjing Zhou
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Xianwei Lin
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
- SequMed Institute of Biomedical Sciences, Guangzhou 510530, Guangdong Province, China
| | - Chaochao Luo
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Wanwan Peng
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Caiming Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Jiajia Peng
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Duolian Liu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
| | - Sadie L Marjani
- Department of Biology, Central Connecticut State University, New Britain, CT 06050, USA
| | - Qian Tao
- Cancer Epigenetics Laboratory, Department of Clinical Oncology, State Key Laboratory of Oncology in South China, Sir YK Pao Center for Cancer and Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, 999077 Hong Kong, China
| | - Yongping Cui
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen 518035, Guangdong, China
| | - Junxiao Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
- SequMed Institute of Biomedical Sciences, Guangzhou 510530, Guangdong Province, China
| | - Xuedong Wu
- Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China
| | - Sherman M Weissman
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Xinghua Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, and Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou 510515, Guangdong Province, China
- Department of Hepatobiliary Surgery II, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, Guangdong Province, China
- Department of Pediatrics, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen 518035, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou 510515, Guangdong Province, China
| |
Collapse
|
2
|
Zhang Y, Xu S, Wen Z, Gao J, Li S, Weissman SM, Pan X. Sample-multiplexing approaches for single-cell sequencing. Cell Mol Life Sci 2022; 79:466. [PMID: 35927335 DOI: 10.1007/s00018-022-04482-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/25/2022] [Accepted: 07/11/2022] [Indexed: 12/12/2022]
Abstract
Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.
Collapse
Affiliation(s)
- Yulong Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China.,Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Siwen Xu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China.,SequMed BioTechnology, Inc., Guangzhou, Guangdong, China
| | - Zebin Wen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
| | - Jinyu Gao
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
| | - Shuang Li
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Sherman M Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520-8005, USA
| | - Xinghua Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China. .,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China. .,Shenzhen Bay Laboratory, Shenzhen, Guangdong, China.
| |
Collapse
|
3
|
Lu Y, Liu M, Yang J, Weissman SM, Pan X, Katz SG, Wang S. Spatial transcriptome profiling by MERFISH reveals fetal liver hematopoietic stem cell niche architecture. Cell Discov 2021; 7:47. [PMID: 34183665 PMCID: PMC8238952 DOI: 10.1038/s41421-021-00266-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 03/25/2021] [Indexed: 12/17/2022] Open
Abstract
The hematopoietic stem cell (HSC) niche has been extensively studied in bone marrow, yet a more systematic investigation into the microenvironment regulation of hematopoiesis in fetal liver is necessary. Here we investigate the spatial organization and transcriptional profile of individual cells in both wild type (WT) and Tet2−/− fetal livers, by multiplexed error robust fluorescence in situ hybridization. We find that specific pairs of fetal liver cell types are preferentially positioned next to each other. Ligand-receptor signaling molecule pairs such as Kitl and Kit are enriched in neighboring cell types. The majority of HSCs are in direct contact with endothelial cells (ECs) in both WT and Tet2−/− fetal livers. Loss of Tet2 increases the number of HSCs, and upregulates Wnt and Notch signaling genes in the HSC niche. Two subtypes of ECs, arterial ECs and sinusoidal ECs, and other cell types contribute distinct signaling molecules to the HSC niche. Collectively, this study provides a comprehensive picture and bioinformatic foundation for HSC spatial regulation in fetal liver.
Collapse
Affiliation(s)
- Yanfang Lu
- Department of Genetics, Yale School of Medicine, New Haven, USA.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou, Guangdong, China
| | - Miao Liu
- Department of Genetics, Yale School of Medicine, New Haven, USA
| | - Jennifer Yang
- Department of Genetics, Yale School of Medicine, New Haven, USA
| | | | - Xinghua Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China. .,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou, Guangdong, China.
| | - Samuel G Katz
- Department of Pathology, Yale School of Medicine, New Haven, USA.
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, New Haven, USA. .,Department of Cell Biology, Yale School of Medicine, New Haven, USA.
| |
Collapse
|
4
|
Wang H, Gong P, Chen T, Gao S, Wu Z, Wang X, Li J, Marjani SL, Costa J, Weissman SM, Qi F, Pan X, Liu L. Colorectal Cancer Stem Cell States Uncovered by Simultaneous Single-Cell Analysis of Transcriptome and Telomeres. Adv Sci (Weinh) 2021; 8:2004320. [PMID: 33898197 PMCID: PMC8061397 DOI: 10.1002/advs.202004320] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/15/2020] [Indexed: 05/02/2023]
Abstract
Cancer stem cells (CSCs) presumably contribute to tumor progression and drug resistance, yet their definitive features have remained elusive. Here, simultaneous measurement of telomere length and transcriptome in the same cells enables systematic assessment of CSCs in primary colorectal cancer (CRC). The in-depth transcriptome profiled by SMART-seq2 is independently validated by high-throughput scRNA-seq using 10 × Genomics. It is found that rare CSCs exist in dormant state and display plasticity toward cancer epithelial cells (EPCs) that essentially are presumptive tumor-initiating cells (TICs), while both retaining the prominent signaling pathways including WNT, TGF-β, and HIPPO/YAP. Moreover, CSCs exhibit chromosome copy number variation (CNV) pattern resembling cancer EPCs but distinct from normal stem cells, suggesting the phylogenetic relationship between CSCs and cancer EPCs. Notably, CSCs maintain shorter telomeres and possess minimal telomerase activity consistent with their nonproliferative nature, unlike cancer EPCs. Additionally, the specific signature of CSCs particularly NOTUM, SMOC2, BAMBI, PHLDA1, and TNFRSF19 correlates with the prognosis of CRC. These findings characterize the heterogeneity of CSCs and their linkage to cancer EPCs/TICs, some of which are conventionally regarded as CSCs.
Collapse
Affiliation(s)
- Hua Wang
- State Key Laboratory of Medicinal Chemical BiologyNankai UniversityTianjin300350China
- Department of Cell Biology and GeneticsCollege of Life SciencesThe Key Laboratory of Bioactive Materials, Ministry of EducationNankai UniversityTianjin300071China
| | - Peng Gong
- State Key Laboratory of Medicinal Chemical BiologyNankai UniversityTianjin300350China
- Department of Cell Biology and GeneticsCollege of Life SciencesThe Key Laboratory of Bioactive Materials, Ministry of EducationNankai UniversityTianjin300071China
- Department of GeneticsYale School of MedicineNew HavenCT06520USA
| | - Tong Chen
- EHBIO Gene Technology co., LTDBeijing100029China
| | - Shan Gao
- Department of Cell Biology and GeneticsCollege of Life SciencesThe Key Laboratory of Bioactive Materials, Ministry of EducationNankai UniversityTianjin300071China
| | - Zhenfeng Wu
- School of Mathematical SciencesNankai UniversityTianjin300071China
| | - Xiaodong Wang
- Department of General SurgeryTianjin Medical University General HospitalTianjin300052China
| | - Jie Li
- State Key Laboratory of Medicinal Chemical BiologyNankai UniversityTianjin300350China
- Department of Cell Biology and GeneticsCollege of Life SciencesThe Key Laboratory of Bioactive Materials, Ministry of EducationNankai UniversityTianjin300071China
| | - Sadie L. Marjani
- Department of BiologyCentral Connecticut State UniversityNew BritainCT06050USA
| | - José Costa
- Department of Pathology, Yale School of MedicineNew HavenCT06520USA
| | | | - Feng Qi
- Department of General SurgeryTianjin Medical University General HospitalTianjin300052China
| | - Xinghua Pan
- Department of GeneticsYale School of MedicineNew HavenCT06520USA
- Department of Biochemistry and Molecular BiologySchool of Basic Medical SciencesSouthern Medical UniversityGuangzhouGuangdong Province510515China
- Guangdong Provincial Key Laboratory for Single Cell Technology and ApplicationGuangzhouGuangdong Province510515China
| | - Lin Liu
- State Key Laboratory of Medicinal Chemical BiologyNankai UniversityTianjin300350China
- Department of Cell Biology and GeneticsCollege of Life SciencesThe Key Laboratory of Bioactive Materials, Ministry of EducationNankai UniversityTianjin300071China
- Institute of Translational MedicineTianjin Union Medical CenterNankai UniversityTianjin300000China
| |
Collapse
|
5
|
Xiang Y, Tanaka Y, Patterson B, Hwang SM, Hysolli E, Cakir B, Kim KY, Wang W, Kang YJ, Clement EM, Zhong M, Lee SH, Cho YS, Patra P, Sullivan GJ, Weissman SM, Park IH. Dysregulation of BRD4 Function Underlies the Functional Abnormalities of MeCP2 Mutant Neurons. Mol Cell 2020; 79:84-98.e9. [PMID: 32526163 DOI: 10.1016/j.molcel.2020.05.016] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 03/04/2020] [Accepted: 05/12/2020] [Indexed: 12/22/2022]
Abstract
Rett syndrome (RTT), mainly caused by mutations in methyl-CpG binding protein 2 (MeCP2), is one of the most prevalent intellectual disorders without effective therapies. Here, we used 2D and 3D human brain cultures to investigate MeCP2 function. We found that MeCP2 mutations cause severe abnormalities in human interneurons (INs). Surprisingly, treatment with a BET inhibitor, JQ1, rescued the molecular and functional phenotypes of MeCP2 mutant INs. We uncovered that abnormal increases in chromatin binding of BRD4 and enhancer-promoter interactions underlie the abnormal transcription in MeCP2 mutant INs, which were recovered to normal levels by JQ1. We revealed cell-type-specific transcriptome impairment in MeCP2 mutant region-specific human brain organoids that were rescued by JQ1. Finally, JQ1 ameliorated RTT-like phenotypes in mice. These data demonstrate that BRD4 dysregulation is a critical driver for RTT etiology and suggest that targeting BRD4 could be a potential therapeutic opportunity for RTT.
Collapse
Affiliation(s)
- Yangfei Xiang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Benjamin Patterson
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Sung-Min Hwang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Eriona Hysolli
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Bilal Cakir
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Wanshan Wang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Young-Jin Kang
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Ethan M Clement
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Mei Zhong
- Department of Cell Biology, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Sang-Hun Lee
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Yee Sook Cho
- Regenerative Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 305-806, Republic of Korea
| | - Prabir Patra
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, University of Bridgeport, Bridgeport, CT 06604, USA
| | - Gareth J Sullivan
- Department of Molecular Medicine, Hybrid Technology Hub - Centre of Excellence, Institute of Basic Medical Sciences, Oslo University Hospital and University of Oslo, Oslo 0424, Norway; Department of Pediatric Research, Oslo University Hospital Rikshospitalet, Oslo 0372, Norway
| | - Sherman M Weissman
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA.
| |
Collapse
|
6
|
Rabinovich PM, Zhang J, Kerr SR, Cheng BH, Komarovskaya M, Bersenev A, Hurwitz ME, Krause DS, Weissman SM, Katz SG. A versatile flow-based assay for immunocyte-mediated cytotoxicity. J Immunol Methods 2019; 474:112668. [PMID: 31525367 DOI: 10.1016/j.jim.2019.112668] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 09/09/2019] [Accepted: 09/12/2019] [Indexed: 10/26/2022]
Abstract
Cell-mediated cytotoxicity is a critical function of the immune system in mounting defense against pathogens and cancers. Current methods that allow direct evaluation of cell-mediated cytotoxicity suffer from a wide-range of drawbacks. Here, we present a novel strategy to measure cytotoxicity that is direct, sensitive, rapid, and highly adaptable. Moreover, it allows accurate measurement of viability of both target and effector cells. Target cells are fluorescently labeled with a non-toxic, cell-permeable dye that covalently binds to cell proteins, including nuclear proteins. The labeled target cells are incubated with effector cells to begin killing. Following the killing reaction, the cell mixture is incubated with another dye that specifically stains proteins of dead cells, including nuclear proteins. In the final step, cell nuclei are released by Triton X-100, and analyzed by flow cytometry. This results in four nuclear staining patterns that separate target and effector nuclei as well as nuclei of live and dead cells. Analyzing nuclei, instead of cells, greatly reduces flow cytometry errors caused by the presence of target-effector cell aggregates. Target killing time can often be reduced to 2 h and the assay can be done in a high throughput format. We have successfully validated this assay in a variety of cytotoxicity scenarios including those mediated by NK-92 cells, Chimeric Antigen Receptor (CAR)-T cells, and Tumor Infiltrating Lymphocytes (TIL). Therefore, this technique is broadly applicable, highly sensitive and easily administered, making it a powerful tool to assess immunotherapy-based, cell-mediated cytotoxicity.
Collapse
Affiliation(s)
- Peter M Rabinovich
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA
| | - Jialing Zhang
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA
| | - Samuel R Kerr
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA
| | - Bao-Hui Cheng
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA
| | - Marina Komarovskaya
- Department of Laboratory Medicine, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06525, USA
| | - Alexey Bersenev
- Department of Laboratory Medicine, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06525, USA
| | - Michael E Hurwitz
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06525, USA; Yale Comprehensive Cancer Center, Yale School of Medicine, New Haven, CT 06525, USA
| | - Diane S Krause
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA; Department of Laboratory Medicine, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06525, USA; Yale Comprehensive Cancer Center, Yale School of Medicine, New Haven, CT 06525, USA
| | - Sherman M Weissman
- Department of Genetics, Yale School of Medicine, New Haven, CT 06525, USA
| | - Samuel G Katz
- Department of Pathology, Yale School of Medicine, New Haven, CT 06525, USA; Yale Comprehensive Cancer Center, Yale School of Medicine, New Haven, CT 06525, USA.
| |
Collapse
|
7
|
Gong P, Wang H, Zhang J, Fu Y, Zhu Z, Wang J, Yin Y, Wang H, Zhou Z, Yang J, Liu L, Gou M, Zeng M, Yuan J, Wang F, Pan X, Xiang R, Weissman SM, Qi F, Liu L. Telomere Maintenance-Associated PML Is a Potential Specific Therapeutic Target of Human Colorectal Cancer. Transl Oncol 2019; 12:1164-1176. [PMID: 31207547 PMCID: PMC6580093 DOI: 10.1016/j.tranon.2019.05.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 05/13/2019] [Indexed: 02/06/2023] Open
Abstract
Telomere length maintenance is essential for cell proliferation, which is particularly prominent in cancer. We validate that the primary colorectal tumors exhibit heterogeneous telomere lengths but mostly (90%) short telomeres relative to normal tissues. Intriguingly, relatively short telomeres are associated with tumor malignancy as indicated by poorly differentiated state, and these tumors contain more cancer stem-like cells (CSLCs) identified by several commonly used markers CD44, EPHB2 or LGR5. Moreover, promyelocytic leukemia (PML) and ALT-associated PML nuclear bodies (APBs) are frequently found in tumors with short telomeres and high proliferation. In contrast, distant normal tissues rarely or only minimally express PML. Inhibition of PML and APBs by an ATR inhibitor decreases proliferation of CSLCs and organoids, suggesting a potential therapeutic target to progressive colorectal tumors. Together, telomere maintenance underling tumor progression is connected with CSLCs.
Collapse
Affiliation(s)
- Peng Gong
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Hua Wang
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Jingsong Zhang
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yudong Fu
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Zhengmao Zhu
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Jinmiao Wang
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yu Yin
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Haiying Wang
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Zhongcheng Zhou
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Jiao Yang
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Linlin Liu
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Mo Gou
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Ming Zeng
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Jinghua Yuan
- Department of Genetics, Tianjin Medical University, Tianjin, 300070, China
| | - Feng Wang
- Department of Genetics, Tianjin Medical University, Tianjin, 300070, China
| | - Xinghua Pan
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Rong Xiang
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy
| | - Sherman M Weissman
- Department of Genetics, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Feng Qi
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Lin Liu
- State Key Laboratory of Medicinal Chemical Biology, 2011 Collaborative Innovation Center for Biotherapy; Department of Cell Biology and Genetics, College of Life Sciences, Nankai University, Tianjin, 300071, China.
| |
Collapse
|
8
|
Xiang Y, Tanaka Y, Cakir B, Patterson B, Kim KY, Sun P, Kang YJ, Zhong M, Liu X, Patra P, Lee SH, Weissman SM, Park IH. hESC-Derived Thalamic Organoids Form Reciprocal Projections When Fused with Cortical Organoids. Cell Stem Cell 2019; 24:487-497.e7. [PMID: 30799279 DOI: 10.1016/j.stem.2018.12.015] [Citation(s) in RCA: 244] [Impact Index Per Article: 48.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 10/01/2018] [Accepted: 12/20/2018] [Indexed: 12/22/2022]
Abstract
Human brain organoid techniques have rapidly advanced to facilitate investigating human brain development and diseases. These efforts have largely focused on generating telencephalon due to its direct relevance in a variety of forebrain disorders. Despite its importance as a relay hub between cortex and peripheral tissues, the investigation of three-dimensional (3D) organoid models for the human thalamus has not been explored. Here, we describe a method to differentiate human embryonic stem cells (hESCs) to thalamic organoids (hThOs) that specifically recapitulate the development of thalamus. Single-cell RNA sequencing revealed a formation of distinct thalamic lineages, which diverge from telencephalic fate. Importantly, we developed a 3D system to create the reciprocal projections between thalamus and cortex by fusing the two distinct region-specific organoids representing the developing thalamus or cortex. Our study provides a platform for understanding human thalamic development and modeling circuit organizations and related disorders in the brain.
Collapse
Affiliation(s)
- Yangfei Xiang
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Bilal Cakir
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Benjamin Patterson
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Pingnan Sun
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Young-Jin Kang
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Mei Zhong
- Department of Cell Biology, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Xinran Liu
- Department of Cell Biology, Center for Cellular and Molecular Imaging, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Prabir Patra
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, University of Bridgeport, Bridgeport, CT 06604, USA
| | - Sang-Hun Lee
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Sherman M Weissman
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA.
| |
Collapse
|
9
|
Yang MQ, Weissman SM, Yang W, Zhang J, Canaan A, Guan R. Correction to: MISC: missing imputation for single-cell RNA sequencing data. BMC Syst Biol 2019; 13:13. [PMID: 30670065 PMCID: PMC6343234 DOI: 10.1186/s12918-019-0681-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
It was highlighted that the original article [1] contained a typesetting error in the last name of Allon Canaan. This was incorrectly captured as Allon Canaann in the original article which has since been updated.
Collapse
Affiliation(s)
- Mary Qu Yang
- Joint Bioinformatics Program, University of Arkansas Little Rock George Washington Donaghey College of Engineering & IT and University of Arkansas for Medical Sciences, Little Rock, AR, 72204, USA.
| | | | - William Yang
- Department of Genetics, Yale University, New Haven, CT, 06512, USA.,Department of Computer Science, Carnegie Mellon University School of Computer Science, Pittsburgh, PA, 15213, USA
| | - Jialing Zhang
- Department of Genetics, Yale University, New Haven, CT, 06512, USA
| | - Allon Canaan
- Department of Genetics, Yale University, New Haven, CT, 06512, USA
| | - Renchu Guan
- Joint Bioinformatics Program, University of Arkansas Little Rock George Washington Donaghey College of Engineering & IT and University of Arkansas for Medical Sciences, Little Rock, AR, 72204, USA. .,College of Computer Science and Technology, Jilin University, Changchun, 130,012, Jilin, China.
| |
Collapse
|
10
|
Zhang X, Zhang Y, Zhu X, Purmann C, Haney MS, Ward T, Khechaduri A, Yao J, Weissman SM, Urban AE. Local and global chromatin interactions are altered by large genomic deletions associated with human brain development. Nat Commun 2018; 9:5356. [PMID: 30559385 PMCID: PMC6297223 DOI: 10.1038/s41467-018-07766-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 11/09/2018] [Indexed: 01/18/2023] Open
Abstract
Large copy number variants (CNVs) in the human genome are strongly associated with common neurodevelopmental, neuropsychiatric disorders such as schizophrenia and autism. Here we report on the epigenomic effects of the prominent large deletion CNVs on chromosome 22q11.2 and on chromosome 1q21.1. We use Hi-C analysis of long-range chromosome interactions, including haplotype-specific Hi-C analysis, ChIP-Seq analysis of regulatory histone marks, and RNA-Seq analysis of gene expression patterns. We observe changes on all the levels of analysis, within the deletion boundaries, in the deletion flanking regions, along chromosome 22q, and genome wide. We detect gene expression changes as well as pronounced and multilayered effects on chromatin states, chromosome folding and on the topological domains of the chromatin, that emanate from the large CNV locus. These findings suggest basic principles of how such large genomic deletions can alter nuclear organization and affect genomic molecular activity. Copy number variants in the human genome (CNVs) are associated with neurodevelopmental and psychiatric disorders such as schizophrenia and autism. Here the authors investigate how the large deletion CNV on chromosome 22q11.2 alters chromatin organization.
Collapse
Affiliation(s)
- Xianglong Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA
| | - Ying Zhang
- Department of Genetics, Yale University, New Haven, 06520, CT, USA.,Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai & Sema4 NYC Laboratory, New York, 10029, NY, USA
| | - Xiaowei Zhu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA
| | - Carolin Purmann
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA
| | - Michael S Haney
- Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA
| | - Thomas Ward
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA
| | - Arineh Khechaduri
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, 98109, WA, USA
| | - Jie Yao
- Department of Cell Biology, Yale University School of Medicine, New Haven, 06520, CT, USA.,Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | | | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, 94304, CA, USA. .,Department of Genetics, Stanford University School of Medicine, Stanford, 94304, CA, USA.
| |
Collapse
|
11
|
Abstract
BACKGROUND Single-cell RNA sequencing (scRNA-seq) technology provides an effective way to study cell heterogeneity. However, due to the low capture efficiency and stochastic gene expression, scRNA-seq data often contains a high percentage of missing values. It has been showed that the missing rate can reach approximately 30% even after noise reduction. To accurately recover missing values in scRNA-seq data, we need to know where the missing data is; how much data is missing; and what are the values of these data. METHODS To solve these three problems, we propose a novel model with a hybrid machine learning method, namely, missing imputation for single-cell RNA-seq (MISC). To solve the first problem, we transformed it to a binary classification problem on the RNA-seq expression matrix. Then, for the second problem, we searched for the intersection of the classification results, zero-inflated model and false negative model results. Finally, we used the regression model to recover the data in the missing elements. RESULTS We compared the raw data without imputation, the mean-smooth neighbor cell trajectory, MISC on chronic myeloid leukemia data (CML), the primary somatosensory cortex and the hippocampal CA1 region of mouse brain cells. On the CML data, MISC discovered a trajectory branch from the CP-CML to the BC-CML, which provides direct evidence of evolution from CP to BC stem cells. On the mouse brain data, MISC clearly divides the pyramidal CA1 into different branches, and it is direct evidence of pyramidal CA1 in the subpopulations. In the meantime, with MISC, the oligodendrocyte cells became an independent group with an apparent boundary. CONCLUSIONS Our results showed that the MISC model improved the cell type classification and could be instrumental to study cellular heterogeneity. Overall, MISC is a robust missing data imputation model for single-cell RNA-seq data.
Collapse
Affiliation(s)
- Mary Qu Yang
- Joint Bioinformatics Program, University of Arkansas Little Rock George Washington Donaghey College of Engineering & IT and University of Arkansas for Medical Sciences, Little Rock, AR, 72204, USA.
| | | | - William Yang
- Department of Genetics, Yale University, New Haven, CT, 06512, USA.,Department of Computer Science, Carnegie Mellon University School of Computer Science, Pittsburgh, PA, 15213, USA
| | - Jialing Zhang
- Department of Genetics, Yale University, New Haven, CT, 06512, USA
| | - Allon Canaann
- Department of Genetics, Yale University, New Haven, CT, 06512, USA
| | - Renchu Guan
- Joint Bioinformatics Program, University of Arkansas Little Rock George Washington Donaghey College of Engineering & IT and University of Arkansas for Medical Sciences, Little Rock, AR, 72204, USA. .,College of Computer Science and Technology, Jilin University, Changchun, Jilin, 130012, China.
| |
Collapse
|
12
|
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] [What about the content of this article? (0)] [Affiliation(s)] [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.
Collapse
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
| |
Collapse
|
13
|
Han L, Wu HJ, Zhu H, Kim KY, Marjani SL, Riester M, Euskirchen G, Zi X, Yang J, Han J, Snyder M, Park IH, Irizarry R, Weissman SM, Michor F, Fan R, Pan X. Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells. Nucleic Acids Res 2017; 45:e77. [PMID: 28126923 PMCID: PMC5605247 DOI: 10.1093/nar/gkx026] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 01/20/2017] [Indexed: 01/03/2023] Open
Abstract
Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population.
Collapse
Affiliation(s)
- Lin Han
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Hua-Jun Wu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02215, USA
| | - Haiying Zhu
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA.,Department of Cell Biology, Second Military Medical University, Shanghai 200433, China
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Sadie L Marjani
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Markus Riester
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02215, USA
| | - Ghia Euskirchen
- Department of Genetics, Stanford University, Palo Alto, CA 94305, USA
| | - Xiaoyuan Zi
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA.,Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.,Department of Cell Biology, Second Military Medical University, Shanghai 200433, China
| | - Jennifer Yang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Jasper Han
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Michael Snyder
- Department of Genetics, Stanford University, Palo Alto, CA 94305, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Rafael Irizarry
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02215, USA
| | - Sherman M Weissman
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Franziska Michor
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02215, USA
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Xinghua Pan
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, Guangzhou, China.,Guangdong Key Laboratory of Biochip Technology, Southern Medical University, Guangzhou 510515, Guangdong, China
| |
Collapse
|
14
|
Xiang Y, Tanaka Y, Patterson B, Kang YJ, Govindaiah G, Roselaar N, Cakir B, Kim KY, Lombroso AP, Hwang SM, Zhong M, Stanley EG, Elefanty AG, Naegele JR, Lee SH, Weissman SM, Park IH. Fusion of Regionally Specified hPSC-Derived Organoids Models Human Brain Development and Interneuron Migration. Cell Stem Cell 2017; 21:383-398.e7. [PMID: 28757360 DOI: 10.1016/j.stem.2017.07.007] [Citation(s) in RCA: 390] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Revised: 06/06/2017] [Accepted: 07/11/2017] [Indexed: 01/18/2023]
Abstract
Organoid techniques provide unique platforms to model brain development and neurological disorders. Whereas several methods for recapitulating corticogenesis have been described, a system modeling human medial ganglionic eminence (MGE) development, a critical ventral brain domain producing cortical interneurons and related lineages, has been lacking until recently. Here, we describe the generation of MGE and cortex-specific organoids from human pluripotent stem cells that recapitulate the development of MGE and cortex domains, respectively. Population and single-cell RNA sequencing (RNA-seq) profiling combined with bulk assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) analyses revealed transcriptional and chromatin accessibility dynamics and lineage relationships during MGE and cortical organoid development. Furthermore, MGE and cortical organoids generated physiologically functional neurons and neuronal networks. Finally, fusing region-specific organoids followed by live imaging enabled analysis of human interneuron migration and integration. Together, our study provides a platform for generating domain-specific brain organoids and modeling human interneuron migration and offers deeper insight into molecular dynamics during human brain development.
Collapse
Affiliation(s)
- Yangfei Xiang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Benjamin Patterson
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Young-Jin Kang
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Gubbi Govindaiah
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Naomi Roselaar
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Bilal Cakir
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Adam P Lombroso
- Department of Biology, Program in Neuroscience and Behavior, Hall-Atwater Laboratory, Wesleyan University, Middletown, CT 06459, USA
| | - Sung-Min Hwang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Mei Zhong
- Department of Cell Biology, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Edouard G Stanley
- Murdoch Childrens Research Institute, The Royal Children's Hospital, Parkville, VIC 3052, Australia; Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC 3052, Australia; Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Andrew G Elefanty
- Murdoch Childrens Research Institute, The Royal Children's Hospital, Parkville, VIC 3052, Australia; Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC 3052, Australia; Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Janice R Naegele
- Department of Biology, Program in Neuroscience and Behavior, Hall-Atwater Laboratory, Wesleyan University, Middletown, CT 06459, USA
| | - Sang-Hun Lee
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Sherman M Weissman
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA.
| |
Collapse
|
15
|
Zhu X, Ching T, Pan X, Weissman SM, Garmire L. Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization. PeerJ 2017; 5:e2888. [PMID: 28133571 PMCID: PMC5251935 DOI: 10.7717/peerj.2888] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 12/08/2016] [Indexed: 01/08/2023] Open
Abstract
Single-cell RNA-Sequencing (scRNA-Seq) is a fast-evolving technology that enables the understanding of biological processes at an unprecedentedly high resolution. However, well-suited bioinformatics tools to analyze the data generated from this new technology are still lacking. Here we investigate the performance of non-negative matrix factorization (NMF) method to analyze a wide variety of scRNA-Seq datasets, ranging from mouse hematopoietic stem cells to human glioblastoma data. In comparison to other unsupervised clustering methods including K-means and hierarchical clustering, NMF has higher accuracy in separating similar groups in various datasets. We ranked genes by their importance scores (D-scores) in separating these groups, and discovered that NMF uniquely identifies genes expressed at intermediate levels as top-ranked genes. Finally, we show that in conjugation with the modularity detection method FEM, NMF reveals meaningful protein-protein interaction modules. In summary, we propose that NMF is a desirable method to analyze heterogeneous single-cell RNA-Seq data. The NMF based subpopulation detection package is available at: https://github.com/lanagarmire/NMFEM.
Collapse
Affiliation(s)
- Xun Zhu
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa, Honolulu, United States
| | - Travers Ching
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa, Honolulu, United States
| | - Xinghua Pan
- Department of Genetics, Yale University , New Haven , CT , United States
| | - Sherman M Weissman
- Department of Genetics, Yale University , New Haven , CT , United States
| | - Lana Garmire
- Epidemiology Program, University of Hawaii Cancer Center , Honolulu , HI , United States
| |
Collapse
|
16
|
Wu H, Zhang XY, Hu Z, Hou Q, Zhang H, Li Y, Li S, Yue J, Jiang Z, Weissman SM, Pan X, Ju BG, Wu S. Evolution and heterogeneity of non-hereditary colorectal cancer revealed by single-cell exome sequencing. Oncogene 2016; 36:2857-2867. [PMID: 27941887 DOI: 10.1038/onc.2016.438] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/22/2016] [Accepted: 10/04/2016] [Indexed: 12/13/2022]
Abstract
Recently single-cell whole-exome sequencing (scWES) has deeply expanded and sharpened our knowledge of cancer evolution and subclonality. Herein, with scWES and matched bulk whole-exome sequencing (bulk WES) on two colorectal cancer (CRC) patients with normal or adenomatous polyps, we found that both the adenoma and cancer were of monoclonal origin, and both shared partial mutations in the same signaling pathways, but each showed a specific spectrum of heterogeneous somatic mutations. In addition, the adenoma and cancer further developed intratumor heterogeneity with the accumulation of nonrandom somatic mutations specifically in GPCR, PI3K-Akt and FGFR signaling pathways. We identified novel driver mutations that developed during adenoma and cancer evolution, particularly in OR1B1 (GPCR signaling pathway) for adenoma evolution, and LAMA1 (PI3K-Akt signaling pathway) and ADCY3 (FGFR signaling pathway) for CRC evolution. In summary, we demonstrated that both colorectal adenoma and CRC are monoclonal in origin, and the CRCs further diversified into different subclones with heterogeneous mutation profiles accumulating in GPCR, PI3K-Akt and FGFR signaling pathways. ScWES provides evidence for the importance of mutations in certain pathways that would not be as apparent from bulk sequencing of tumors, and can potentially establish whether specific mutations are mutually exclusive or occur sequentially in the same subclone of cells.
Collapse
Affiliation(s)
- H Wu
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China.,Department of Life Science, Sogang University, Seoul, South Korea
| | - X-Y Zhang
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - Z Hu
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - Q Hou
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - H Zhang
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - Y Li
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - S Li
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - J Yue
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - Z Jiang
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| | - S M Weissman
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - X Pan
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - B-G Ju
- Department of Life Science, Sogang University, Seoul, South Korea
| | - S Wu
- Cancer Research Institute, Hangzhou Cancer Hospital, Hangzhou, China
| |
Collapse
|
17
|
Hysolli E, Tanaka Y, Su J, Kim KY, Zhong T, Janknecht R, Zhou XL, Geng L, Qiu C, Pan X, Jung YW, Cheng J, Lu J, Zhong M, Weissman SM, Park IH. Regulation of the DNA Methylation Landscape in Human Somatic Cell Reprogramming by the miR-29 Family. Stem Cell Reports 2016; 7:43-54. [PMID: 27373925 PMCID: PMC4945581 DOI: 10.1016/j.stemcr.2016.05.014] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2015] [Revised: 05/31/2016] [Accepted: 05/31/2016] [Indexed: 02/05/2023] Open
Abstract
Reprogramming to pluripotency after overexpression of OCT4, SOX2, KLF4, and MYC is accompanied by global genomic and epigenomic changes. Histone modification and DNA methylation states in induced pluripotent stem cells (iPSCs) have been shown to be highly similar to embryonic stem cells (ESCs). However, epigenetic differences still exist between iPSCs and ESCs. In particular, aberrant DNA methylation states found in iPSCs are a major concern when using iPSCs in a clinical setting. Thus, it is critical to find factors that regulate DNA methylation states in reprogramming. Here, we found that the miR-29 family is an important epigenetic regulator during human somatic cell reprogramming. Our global DNA methylation and hydroxymethylation analysis shows that DNA demethylation is a major event mediated by miR-29a depletion during early reprogramming, and that iPSCs derived from miR-29a depletion are epigenetically closer to ESCs. Our findings uncover an important miRNA-based approach to generate clinically robust iPSCs.
Collapse
Affiliation(s)
- Eriona Hysolli
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Juan Su
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA; Department of Cell Biology, Second Military Medical University, Shanghai 200433, P.R. China
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Tianyu Zhong
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA; Department of Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi 341000, P.R. China
| | - Ralf Janknecht
- Department of Cell Biology, University of Oklahoma Health Sciences Center, 975 Northeast, 10th Street, Oklahoma City, OK 73104, USA
| | - Xiao-Ling Zhou
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA; Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, 515041, P.R. China
| | - Lin Geng
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Caihong Qiu
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Xinghua Pan
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Yong-Wook Jung
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA; Department of Obstetrics and Gynecology, CHA Gangnam Medical Center, CHA University, Seoul 135-081, Republic of Korea
| | - Jijun Cheng
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Jun Lu
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - Mei Zhong
- Department of Cell Biology, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Sherman M Weissman
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, 10 Amistad, 201B, New Haven, CT 06520, USA.
| |
Collapse
|
18
|
Cheng J, Roden CA, Pan W, Zhu S, Baccei A, Pan X, Jiang T, Kluger Y, Weissman SM, Guo S, Flavell RA, Ding Y, Lu J. A Molecular Chipper technology for CRISPR sgRNA library generation and functional mapping of noncoding regions. Nat Commun 2016; 7:11178. [PMID: 27025950 PMCID: PMC4820989 DOI: 10.1038/ncomms11178] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Accepted: 02/26/2016] [Indexed: 12/12/2022] Open
Abstract
Clustered regularly-interspaced palindromic repeats (CRISPR)-based genetic screens using single-guide-RNA (sgRNA) libraries have proven powerful to identify genetic regulators. Applying CRISPR screens to interrogate functional elements in noncoding regions requires generating sgRNA libraries that are densely covering, and ideally inexpensive, easy to implement and flexible for customization. Here we present a Molecular Chipper technology for generating dense sgRNA libraries for genomic regions of interest, and a proof-of-principle screen that identifies novel cis-regulatory domains for miR-142 biogenesis. The Molecular Chipper approach utilizes a combination of random fragmentation and a type III restriction enzyme to derive a densely covering sgRNA library from input DNA. Applying this approach to 17 microRNAs and their flanking regions and with a reporter for miR-142 activity, we identify both the pre-miR-142 region and two previously unrecognized cis-domains important for miR-142 biogenesis, with the latter regulating miR-142 processing. This strategy will be useful for identifying functional noncoding elements in mammalian genomes.
Collapse
Affiliation(s)
- Jijun Cheng
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
| | - Christine A. Roden
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
- Graduate Program in Biological and Biomedical Sciences, Yale University, New Haven, Connecticut 06510, USA
| | - Wen Pan
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
| | - Shu Zhu
- Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
| | - Anna Baccei
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
- Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
| | - Xinghua Pan
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
| | - Tingting Jiang
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
| | - Yuval Kluger
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
| | - Sherman M. Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
| | - Shangqin Guo
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
- Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
| | - Richard A. Flavell
- Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
| | - Ye Ding
- Wadsworth Center, New York State Department of Health, Albany, New York 12208, USA
| | - Jun Lu
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA
- Yale Stem Cell Center, Yale Cancer Center, New Haven, Connecticut 06520, USA
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
- Yale Center for RNA Science and Medicine, New Haven, Connecticut 06520, USA
| |
Collapse
|
19
|
Zhang X, Marjani SL, Hu Z, Weissman SM, Pan X, Wu S. Single-Cell Sequencing for Precise Cancer Research: Progress and Prospects. Cancer Res 2016; 76:1305-12. [PMID: 26941284 DOI: 10.1158/0008-5472.can-15-1907] [Citation(s) in RCA: 84] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Accepted: 10/22/2015] [Indexed: 11/16/2022]
Abstract
Advances in genomic technology have enabled the faithful detection and measurement of mutations and the gene expression profile of cancer cells at the single-cell level. Recently, several single-cell sequencing methods have been developed that permit the comprehensive and precise analysis of the cancer-cell genome, transcriptome, and epigenome. The use of these methods to analyze cancer cells has led to a series of unanticipated discoveries, such as the high heterogeneity and stochastic changes in cancer-cell populations, the new driver mutations and the complicated clonal evolution mechanisms, and the novel identification of biomarkers of variant tumors. These methods and the knowledge gained from their utilization could potentially improve the early detection and monitoring of rare cancer cells, such as circulating tumor cells and disseminated tumor cells, and promote the development of personalized and highly precise cancer therapy. Here, we discuss the current methods for single cancer-cell sequencing, with a strong focus on those practically used or potentially valuable in cancer research, including single-cell isolation, whole genome and transcriptome amplification, epigenome profiling, multi-dimensional sequencing, and next-generation sequencing and analysis. We also examine the current applications, challenges, and prospects of single cancer-cell sequencing.
Collapse
Affiliation(s)
- Xiaoyan Zhang
- Hangzhou Cancer Institution, Hangzhou Cancer Hospital, Hangzhou, Zhejiang Province, P. R. China
| | - Sadie L Marjani
- Department of Biology, Central Connecticut State University, New Britain, Connecticut
| | - Zhaoyang Hu
- Hangzhou Cancer Institution, Hangzhou Cancer Hospital, Hangzhou, Zhejiang Province, P. R. China
| | - Sherman M Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut
| | - Xinghua Pan
- Hangzhou Cancer Institution, Hangzhou Cancer Hospital, Hangzhou, Zhejiang Province, P. R. China. Department of Genetics, Yale University School of Medicine, New Haven, Connecticut. Department of Biochemistry, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong Province, P.R. China.
| | - Shixiu Wu
- Hangzhou Cancer Institution, Hangzhou Cancer Hospital, Hangzhou, Zhejiang Province, P. R. China.
| |
Collapse
|
20
|
Yue F, Cheng Y, Breschi A, Vierstra J, Wu W, Ryba T, Sandstrom R, Ma Z, Davis C, Pope BD, Shen Y, Pervouchine DD, Djebali S, Thurman RE, Kaul R, Rynes E, Kirilusha A, Marinov GK, Williams BA, Trout D, Amrhein H, Fisher-Aylor K, Antoshechkin I, DeSalvo G, See LH, Fastuca M, Drenkow J, Zaleski C, Dobin A, Prieto P, Lagarde J, Bussotti G, Tanzer A, Denas O, Li K, Bender MA, Zhang M, Byron R, Groudine MT, McCleary D, Pham L, Ye Z, Kuan S, Edsall L, Wu YC, Rasmussen MD, Bansal MS, Kellis M, Keller CA, Morrissey CS, Mishra T, Jain D, Dogan N, Harris RS, Cayting P, Kawli T, Boyle AP, Euskirchen G, Kundaje A, Lin S, Lin Y, Jansen C, Malladi VS, Cline MS, Erickson DT, Kirkup VM, Learned K, Sloan CA, Rosenbloom KR, Lacerda de Sousa B, Beal K, Pignatelli M, Flicek P, Lian J, Kahveci T, Lee D, Kent WJ, Ramalho Santos M, Herrero J, Notredame C, Johnson A, Vong S, Lee K, Bates D, Neri F, Diegel M, Canfield T, Sabo PJ, Wilken MS, Reh TA, Giste E, Shafer A, Kutyavin T, Haugen E, Dunn D, Reynolds AP, Neph S, Humbert R, Hansen RS, De Bruijn M, Selleri L, Rudensky A, Josefowicz S, Samstein R, Eichler EE, Orkin SH, Levasseur D, Papayannopoulou T, Chang KH, Skoultchi A, Gosh S, Disteche C, Treuting P, Wang Y, Weiss MJ, Blobel GA, Cao X, Zhong S, Wang T, Good PJ, Lowdon RF, Adams LB, Zhou XQ, Pazin MJ, Feingold EA, Wold B, Taylor J, Mortazavi A, Weissman SM, Stamatoyannopoulos JA, Snyder MP, Guigo R, Gingeras TR, Gilbert DM, Hardison RC, Beer MA, Ren B. A comparative encyclopedia of DNA elements in the mouse genome. Nature 2015; 515:355-64. [PMID: 25409824 PMCID: PMC4266106 DOI: 10.1038/nature13992] [Citation(s) in RCA: 1135] [Impact Index Per Article: 126.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 10/24/2014] [Indexed: 12/11/2022]
Abstract
The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
Collapse
Affiliation(s)
- Feng Yue
- 1] Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Department of Biochemistry and Molecular Biology, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania 17033, USA
| | - Yong Cheng
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Alessandra Breschi
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Jeff Vierstra
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Weisheng Wu
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Tyrone Ryba
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Zhihai Ma
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Carrie Davis
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Benjamin D Pope
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Yin Shen
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Dmitri D Pervouchine
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Sarah Djebali
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Eric Rynes
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Anthony Kirilusha
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Georgi K Marinov
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Brian A Williams
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Diane Trout
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Henry Amrhein
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Katherine Fisher-Aylor
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Igor Antoshechkin
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Gilberto DeSalvo
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - Lei-Hoon See
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Meagan Fastuca
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Jorg Drenkow
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Chris Zaleski
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Alex Dobin
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Pablo Prieto
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Julien Lagarde
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Giovanni Bussotti
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Andrea Tanzer
- 1] Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain. [2] Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Waehringerstrasse 17/3/303, A-1090 Vienna, Austria
| | - Olgert Denas
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - Kanwei Li
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - M A Bender
- 1] Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA. [2] Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Miaohua Zhang
- Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Rachel Byron
- Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Mark T Groudine
- 1] Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. [2] Department of Radiation Oncology, University of Washington, Seattle, Washington 98195, USA
| | - David McCleary
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Long Pham
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Zhen Ye
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Samantha Kuan
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Lee Edsall
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Yi-Chieh Wu
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Matthew D Rasmussen
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Mukul S Bansal
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - Manolis Kellis
- 1] Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA. [2] Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Cheryl A Keller
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Christapher S Morrissey
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Tejaswini Mishra
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Deepti Jain
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Nergiz Dogan
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Robert S Harris
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Philip Cayting
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Trupti Kawli
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Alan P Boyle
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Ghia Euskirchen
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Shin Lin
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Yiing Lin
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Camden Jansen
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
| | - Venkat S Malladi
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Melissa S Cline
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Drew T Erickson
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Vanessa M Kirkup
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Katrina Learned
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Cricket A Sloan
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Kate R Rosenbloom
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Beatriz Lacerda de Sousa
- Departments of Obstetrics/Gynecology and Pathology, and Center for Reproductive Sciences, University of California San Francisco, San Francisco, California 94143, USA
| | - Kathryn Beal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Miguel Pignatelli
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jin Lian
- Yale University, Department of Genetics, PO Box 208005, 333 Cedar Street, New Haven, Connecticut 06520-8005, USA
| | - Tamer Kahveci
- Computer &Information Sciences &Engineering, University of Florida, Gainesville, Florida 32611, USA
| | - Dongwon Lee
- McKusick-Nathans Institute of Genetic Medicine and Department of Biomedical Engineering, Johns Hopkins University, 733 N. Broadway, BRB 573 Baltimore, Maryland 21205, USA
| | - W James Kent
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California 95064, USA
| | - Miguel Ramalho Santos
- Departments of Obstetrics/Gynecology and Pathology, and Center for Reproductive Sciences, University of California San Francisco, San Francisco, California 94143, USA
| | - Javier Herrero
- 1] European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. [2] Bill Lyons Informatics Centre, UCL Cancer Institute, University College London, London WC1E 6DD, UK
| | - Cedric Notredame
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Audra Johnson
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Shinny Vong
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Kristen Lee
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Daniel Bates
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Fidencio Neri
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Morgan Diegel
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Matthew S Wilken
- Department of Biological Structure, University of Washington, HSB I-516, 1959 NE Pacific Street, Seattle, Washington 98195, USA
| | - Thomas A Reh
- Department of Biological Structure, University of Washington, HSB I-516, 1959 NE Pacific Street, Seattle, Washington 98195, USA
| | - Erika Giste
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Anthony Shafer
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Tanya Kutyavin
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Eric Haugen
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Douglas Dunn
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Alex P Reynolds
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Shane Neph
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Richard Humbert
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - R Scott Hansen
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Marella De Bruijn
- MRC Molecular Haemotology Unit, University of Oxford, Oxford OX3 9DS, UK
| | - Licia Selleri
- Department of Cell and Developmental Biology, Weill Cornell Medical College, New York, New York 10065, USA
| | - Alexander Rudensky
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Steven Josefowicz
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Robert Samstein
- HHMI and Ludwig Center at Memorial Sloan Kettering Cancer Center, Immunology Program, Memorial Sloan Kettering Cancer Canter, New York, New York 10065, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Stuart H Orkin
- Dana Farber Cancer Institute, Harvard Medical School, Cambridge, Massachusetts 02138, USA
| | - Dana Levasseur
- University of Iowa Carver College of Medicine, Department of Internal Medicine, Iowa City, Iowa 52242, USA
| | - Thalia Papayannopoulou
- Division of Hematology, Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Kai-Hsin Chang
- University of Iowa Carver College of Medicine, Department of Internal Medicine, Iowa City, Iowa 52242, USA
| | - Arthur Skoultchi
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Srikanta Gosh
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Christine Disteche
- Department of Pathology, University of Washington, Seattle, Washington 98195, USA
| | - Piper Treuting
- Department of Comparative Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Yanli Wang
- Bioinformatics and Genomics program, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Mitchell J Weiss
- Department of Hematology, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Gerd A Blobel
- 1] Division of Hematology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA. [2] Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Xiaoyi Cao
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Sheng Zhong
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Ting Wang
- Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Peter J Good
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Rebecca F Lowdon
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Leslie B Adams
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Xiao-Qiao Zhou
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Michael J Pazin
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Elise A Feingold
- NHGRI, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA
| | - Barbara Wold
- Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
| | - James Taylor
- Departments of Biology and Mathematics and Computer Science, Emory University, O. Wayne Rollins Research Center, 1510 Clifton Road NE, Atlanta, Georgia 30322, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
| | - Sherman M Weissman
- Yale University, Department of Genetics, PO Box 208005, 333 Cedar Street, New Haven, Connecticut 06520-8005, USA
| | | | - Michael P Snyder
- Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, California 94305, USA
| | - Roderic Guigo
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain
| | - Thomas R Gingeras
- Functional Genomics, Cold Spring Harbor Laboratory, Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - David M Gilbert
- Department of Biological Science, 319 Stadium Drive, Florida State University, Tallahassee, Florida 32306-4295, USA
| | - Ross C Hardison
- Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Michael A Beer
- McKusick-Nathans Institute of Genetic Medicine and Department of Biomedical Engineering, Johns Hopkins University, 733 N. Broadway, BRB 573 Baltimore, Maryland 21205, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research and University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, California 92093, USA
| | | |
Collapse
|
21
|
Han L, Zi X, Garmire LX, Wu Y, Weissman SM, Pan X, Fan R. Co-detection and sequencing of genes and transcripts from the same single cells facilitated by a microfluidics platform. Sci Rep 2014; 4:6485. [PMID: 25255798 PMCID: PMC4175731 DOI: 10.1038/srep06485] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 09/05/2014] [Indexed: 01/12/2023] Open
Abstract
Despite the recent advance of single-cell gene expression analyses, co-measurement of both genomic and transcriptional signatures at the single-cell level has not been realized. However such analysis is necessary in order to accurately delineate how genetic information is transcribed, expressed, and regulated to give rise to an enormously diverse range of cell phenotypes. Here we report on a microfluidics-facilitated approach that allows for controlled separation of cytoplasmic and nuclear contents of a single cell followed by on-chip amplification of genomic DNA and cytoplasmic mRNA. When coupled with off-chip polymerase chain reaction, gel electrophoresis and Sanger sequencing, a panel of genes and transcripts from the same single cell can be co-detected and sequenced. This platform is potentially an enabling tool to permit multiple genomic measurements performed on the same single cells and opens new opportunities to tackle a range of fundamental biology questions including non-genetic cell-to-cell variability, epigenetic regulation, and stem cell fate control. It also helps address clinical challenges such as diagnosing intra-tumor heterogeneity and dissecting complex cellular immune responses.
Collapse
Affiliation(s)
- Lin Han
- 1] Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA [2]
| | - Xiaoyuan Zi
- 1] Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA [2] Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA [3] Department of Cell Biology, Second Military Medical University, Shanghai 200433, China [4]
| | - Lana X Garmire
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813 USA
| | - Yu Wu
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Sherman M Weissman
- 1] Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA [2] Yale Comprehensive Cancer Center, New Haven, CT 06520, USA
| | - Xinghua Pan
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Rong Fan
- 1] Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA [2] Yale Comprehensive Cancer Center, New Haven, CT 06520, USA
| |
Collapse
|
22
|
Zhang X, Weissman SM, Newburger PE. Long intergenic non-coding RNA HOTAIRM1 regulates cell cycle progression during myeloid maturation in NB4 human promyelocytic leukemia cells. RNA Biol 2014; 11:777-87. [PMID: 24824789 DOI: 10.4161/rna.28828] [Citation(s) in RCA: 132] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
HOTAIRM1 is a long intergenic non-coding RNA encoded in the human HOXA gene cluster, with gene expression highly specific for maturing myeloid cells. Knockdown of HOTAIRM1 in the NB4 acute promyelocytic leukemia cell line retarded all-trans retinoid acid (ATRA)-induced granulocytic differentiation, resulting in a significantly larger population of immature and proliferating cells that maintained cell cycle progression from G1 to S phases. Correspondingly, HOTAIRM1 knockdown resulted in retained expression of many otherwise ATRA-suppressed cell cycle and DNA replication genes, and abated ATRA induction of cell surface leukocyte activation, defense response, and other maturation-related genes. Resistance to ATRA-induced cell cycle arrest at the G1/S phase transition in knockdown cells was accompanied by retained expression of ITGA4 (CD49d) and decreased induction of ITGAX (CD11c). The coupling of cell cycle progression with temporal dynamics in the expression patterns of these integrin genes suggests a regulated switch to control the transit from the proliferative phase to granulocytic maturation. Furthermore, ITGAX was among a small number of genes showing perturbation in transcript levels upon HOTAIRM1 knockdown even without ATRA treatment, suggesting a direct pathway of regulation. These results indicate that HOTAIRM1 provides a regulatory link in myeloid maturation by modulating integrin-controlled cell cycle progression at the gene expression level.
Collapse
Affiliation(s)
- Xueqing Zhang
- Department of Pediatrics; University of Massachusetts Medical School; Worcester, MA USA
| | | | - Peter E Newburger
- Department of Pediatrics; University of Massachusetts Medical School; Worcester, MA USA; Department of Cancer Biology; University of Massachusetts Medical School; Worcester, MA USA
| |
Collapse
|
23
|
Guo S, Zi X, Schulz VP, Cheng J, Zhong M, Koochaki SHJ, Megyola CM, Pan X, Heydari K, Weissman SM, Gallagher PG, Krause DS, Fan R, Lu J. Nonstochastic reprogramming from a privileged somatic cell state. Cell 2014; 156:649-62. [PMID: 24486105 DOI: 10.1016/j.cell.2014.01.020] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Revised: 11/04/2013] [Accepted: 01/10/2014] [Indexed: 12/29/2022]
Abstract
Reprogramming somatic cells to induced pluripotency by Yamanaka factors is usually slow and inefficient and is thought to be a stochastic process. We identified a privileged somatic cell state, from which acquisition of pluripotency could occur in a nonstochastic manner. Subsets of murine hematopoietic progenitors are privileged whose progeny cells predominantly adopt the pluripotent fate with activation of endogenous Oct4 locus after four to five divisions in reprogramming conditions. Privileged cells display an ultrafast cell cycle of ∼8 hr. In fibroblasts, a subpopulation cycling at a similar ultrafast speed is observed after 6 days of factor expression and is increased by p53 knockdown. This ultrafast cycling population accounts for >99% of the bulk reprogramming activity in wild-type or p53 knockdown fibroblasts. Our data demonstrate that the stochastic nature of reprogramming can be overcome in a privileged somatic cell state and suggest that cell-cycle acceleration toward a critical threshold is an important bottleneck for reprogramming. PAPERCLIP:
Collapse
Affiliation(s)
- Shangqin Guo
- Department of Cell Biology, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA.
| | - Xiaoyuan Zi
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Cell Biology, Second Military Medical University, Shanghai 200433, China
| | - Vincent P Schulz
- Department of Pediatrics, Yale University, New Haven, CT 06520, USA
| | - Jijun Cheng
- Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Genetics, Yale University, New Haven, CT 06520, USA
| | - Mei Zhong
- Department of Cell Biology, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA
| | - Sebastian H J Koochaki
- Department of Cell Biology, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA
| | - Cynthia M Megyola
- Department of Cell Biology, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA
| | - Xinghua Pan
- Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Genetics, Yale University, New Haven, CT 06520, USA
| | - Kartoosh Heydari
- Department of Immunobiology, Yale Flow Cytometry Core Facility, Yale University, New Haven, CT 06520, USA
| | - Sherman M Weissman
- Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Genetics, Yale University, New Haven, CT 06520, USA; Yale Comprehensive Cancer Center, Yale University, New Haven, CT 06520, USA
| | - Patrick G Gallagher
- Department of Pediatrics, Yale University, New Haven, CT 06520, USA; Department of Genetics, Yale University, New Haven, CT 06520, USA; Department of Pathology, Yale University, New Haven, CT 06520, USA
| | - Diane S Krause
- Department of Cell Biology, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Laboratory Medicine, Yale University, New Haven, CT 06520, USA
| | - Rong Fan
- Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Yale Comprehensive Cancer Center, Yale University, New Haven, CT 06520, USA
| | - Jun Lu
- Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA; Department of Genetics, Yale University, New Haven, CT 06520, USA; Yale Comprehensive Cancer Center, Yale University, New Haven, CT 06520, USA
| |
Collapse
|
24
|
Charos AE, Reed BD, Raha D, Szekely AM, Weissman SM, Snyder M. A highly integrated and complex PPARGC1A transcription factor binding network in HepG2 cells. Genome Res 2013; 22:1668-79. [PMID: 22955979 PMCID: PMC3431484 DOI: 10.1101/gr.127761.111] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
PPARGC1A is a transcriptional coactivator that binds to and coactivates a variety of transcription factors (TFs) to regulate the expression of target genes. PPARGC1A plays a pivotal role in regulating energy metabolism and has been implicated in several human diseases, most notably type II diabetes. Previous studies have focused on the interplay between PPARGC1A and individual TFs, but little is known about how PPARGC1A combines with all of its partners across the genome to regulate transcriptional dynamics. In this study, we describe a core PPARGC1A transcriptional regulatory network operating in HepG2 cells treated with forskolin. We first mapped the genome-wide binding sites of PPARGC1A using chromatin-IP followed by high-throughput sequencing (ChIP-seq) and uncovered overrepresented DNA sequence motifs corresponding to known and novel PPARGC1A network partners. We then profiled six of these site-specific TF partners using ChIP-seq and examined their network connectivity and combinatorial binding patterns with PPARGC1A. Our analysis revealed extensive overlap of targets including a novel link between PPARGC1A and HSF1, a TF regulating the conserved heat shock response pathway that is misregulated in diabetes. Importantly, we found that different combinations of TFs bound to distinct functional sets of genes, thereby helping to reveal the combinatorial regulatory code for metabolic and other cellular processes. In addition, the different TFs often bound near the promoters and coding regions of each other's genes suggesting an intricate network of interdependent regulation. Overall, our study provides an important framework for understanding the systems-level control of metabolic gene expression in humans.
Collapse
Affiliation(s)
- Alexandra E Charos
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520, USA
| | | | | | | | | | | |
Collapse
|
25
|
|
26
|
Stamatoyannopoulos JA, Snyder M, Hardison R, Ren B, Gingeras T, Gilbert DM, Groudine M, Bender M, Kaul R, Canfield T, Giste E, Johnson A, Zhang M, Balasundaram G, Byron R, Roach V, Sabo PJ, Sandstrom R, Stehling AS, Thurman RE, Weissman SM, Cayting P, Hariharan M, Lian J, Cheng Y, Landt SG, Ma Z, Wold BJ, Dekker J, Crawford GE, Keller CA, Wu W, Morrissey C, Kumar SA, Mishra T, Jain D, Byrska-Bishop M, Blankenberg D, Lajoie1 BR, Jain G, Sanyal A, Chen KB, Denas O, Taylor J, Blobel GA, Weiss MJ, Pimkin M, Deng W, Marinov GK, Williams BA, Fisher-Aylor KI, Desalvo G, Kiralusha A, Trout D, Amrhein H, Mortazavi A, Edsall L, McCleary D, Kuan S, Shen Y, Yue F, Ye Z, Davis CA, Zaleski C, Jha S, Xue C, Dobin A, Lin W, Fastuca M, Wang H, Guigo R, Djebali S, Lagarde J, Ryba T, Sasaki T, Malladi VS, Cline MS, Kirkup VM, Learned K, Rosenbloom KR, Kent WJ, Feingold EA, Good PJ, Pazin M, Lowdon RF, Adams LB. An encyclopedia of mouse DNA elements (Mouse ENCODE). Genome Biol 2012; 13:418. [PMID: 22889292 PMCID: PMC3491367 DOI: 10.1186/gb-2012-13-8-418] [Citation(s) in RCA: 343] [Impact Index Per Article: 28.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome.
Collapse
Affiliation(s)
- John A Stamatoyannopoulos
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Michael Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Ross Hardison
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Thomas Gingeras
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - David M Gilbert
- Department of Biological Science, Florida State University, Tallahassee, Florida, USA
| | - Mark Groudine
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Michael Bender
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Rajinder Kaul
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Theresa Canfield
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Erica Giste
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Audra Johnson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Mia Zhang
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Gayathri Balasundaram
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Rachel Byron
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Vaughan Roach
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Peter J Sabo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Richard Sandstrom
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - A Sandra Stehling
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | - Robert E Thurman
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA
| | | | - Philip Cayting
- Department of Genetics, Yale University, New Haven, Connecticut, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA
| | - Manoj Hariharan
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Jin Lian
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
| | - Yong Cheng
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Stephen G Landt
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Zhihai Ma
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Barbara J Wold
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Job Dekker
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachussetts, USA
| | - Gregory E Crawford
- Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, USA
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
| | - Cheryl A Keller
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Weisheng Wu
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Christopher Morrissey
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Swathi A Kumar
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Tejaswini Mishra
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Deepti Jain
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Marta Byrska-Bishop
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Daniel Blankenberg
- Center for Comparative Genomics and Bioinformatics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Bryan R Lajoie1
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Gaurav Jain
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachussetts, USA
| | - Amartya Sanyal
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachussetts, USA
| | - Kaun-Bei Chen
- Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, USA
| | - Olgert Denas
- Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, USA
| | - James Taylor
- Department of Mathematics and Computer Science, Emory University, Atlanta, Georgia, USA
| | - Gerd A Blobel
- Div. of Hematology, Children's Hospital of Philadelphia, Abramson Research Center, Philadelphia, Pennsylvania, USA
| | - Mitchell J Weiss
- Div. of Hematology, Children's Hospital of Philadelphia, Abramson Research Center, Philadelphia, Pennsylvania, USA
| | - Max Pimkin
- Div. of Hematology, Children's Hospital of Philadelphia, Abramson Research Center, Philadelphia, Pennsylvania, USA
| | - Wulan Deng
- Div. of Hematology, Children's Hospital of Philadelphia, Abramson Research Center, Philadelphia, Pennsylvania, USA
| | - Georgi K Marinov
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Brian A Williams
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | | | - Gilberto Desalvo
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Anthony Kiralusha
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Diane Trout
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Henry Amrhein
- Div. of Biology, California Institute of Technology, Pasadena, California, USA
| | - Ali Mortazavi
- Dept. of Developmental and Cell Biology, University of California Irvine, Irvine California, USA
| | - Lee Edsall
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - David McCleary
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Samantha Kuan
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Yin Shen
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Feng Yue
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Zhen Ye
- Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Carrie A Davis
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Chris Zaleski
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Sonali Jha
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Chenghai Xue
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Alex Dobin
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Wei Lin
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Meagan Fastuca
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Huaien Wang
- Dept. of Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Roderic Guigo
- Division of Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalunya, Spain
| | - Sarah Djebali
- Division of Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalunya, Spain
| | - Julien Lagarde
- Division of Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalunya, Spain
| | - Tyrone Ryba
- Department of Biological Science, Florida State University, Tallahassee, Florida, USA
| | - Takayo Sasaki
- Department of Biological Science, Florida State University, Tallahassee, Florida, USA
| | - Venkat S Malladi
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - Melissa S Cline
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - Vanessa M Kirkup
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - Katrina Learned
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - Kate R Rosenbloom
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - W James Kent
- Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), Santa Cruz, California, USA
| | - Elise A Feingold
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Peter J Good
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Michael Pazin
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Rebecca F Lowdon
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Leslie B Adams
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| |
Collapse
|
27
|
Karmakar S, Mahajan MC, Schulz V, Boyapaty G, Weissman SM. A multiprotein complex necessary for both transcription and DNA replication at the β-globin locus. EMBO J 2010; 29:3260-71. [PMID: 20808282 DOI: 10.1038/emboj.2010.204] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2010] [Accepted: 07/29/2010] [Indexed: 12/17/2022] Open
Abstract
DNA replication, repair, transcription and chromatin structure are intricately associated nuclear processes, but the molecular links between these events are often obscure. In this study, we have surveyed the protein complexes that bind at β-globin locus control region, and purified and characterized the function of one such multiprotein complex from human erythroleukemic K562 cells. We further validated the existence of this complex in human CD34+ cell-derived normal erythroid cells. This complex contains ILF2/ILF3 transcription factors, p300 acetyltransferase and proteins associated with DNA replication, transcription and repair. RNAi knockdown of ILF2, a DNA-binding component of this complex, abrogates the recruitment of the complex to its cognate DNA sequence and inhibits transcription, histone acetylation and usage of the origin of DNA replication at the β-globin locus. These results imply a direct link between mammalian DNA replication, transcription and histone acetylation mediated by a single multiprotein complex.
Collapse
Affiliation(s)
- Subhradip Karmakar
- Department of Genetics, The Anlyan Center, Yale University School of Medicine, New Haven, CT, USA
| | | | | | | | | |
Collapse
|
28
|
Kasowski M, Grubert F, Heffelfinger C, Hariharan M, Asabere A, Waszak SM, Habegger L, Rozowsky J, Shi M, Urban AE, Hong MY, Karczewski KJ, Huber W, Weissman SM, Gerstein MB, Korbel JO, Snyder M. Variation in transcription factor binding among humans. Science 2010; 328:232-5. [PMID: 20299548 PMCID: PMC2938768 DOI: 10.1126/science.1183621] [Citation(s) in RCA: 423] [Impact Index Per Article: 30.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Differences in gene expression may play a major role in speciation and phenotypic diversity. We examined genome-wide differences in transcription factor (TF) binding in several humans and a single chimpanzee by using chromatin immunoprecipitation followed by sequencing. The binding sites of RNA polymerase II (PolII) and a key regulator of immune responses, nuclear factor kappaB (p65), were mapped in 10 lymphoblastoid cell lines, and 25 and 7.5% of the respective binding regions were found to differ between individuals. Binding differences were frequently associated with single-nucleotide polymorphisms and genomic structural variants, and these differences were often correlated with differences in gene expression, suggesting functional consequences of binding variation. Furthermore, comparing PolII binding between humans and chimpanzee suggests extensive divergence in TF binding. Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences.
Collapse
Affiliation(s)
- Maya Kasowski
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
| | - Fabian Grubert
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
| | - Christopher Heffelfinger
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
| | - Manoj Hariharan
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
| | - Akwasi Asabere
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
| | - Sebastian M. Waszak
- Genome Biology Research Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Biotechnology and Bioinformatics, Weihenstephan-Triesdorf University of Applied Sciences, 85350 Freising, Germany
| | - Lukas Habegger
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520
| | - Joel Rozowsky
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520
| | - Minyi Shi
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
| | - Alexander E. Urban
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
- Department Genetics, Yale University School of Medicine, New Haven, CT 08520
| | - Mi-Young Hong
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
| | - Konrad J. Karczewski
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
| | - Wolfgang Huber
- Genome Biology Research Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Sherman M. Weissman
- Department Genetics, Yale University School of Medicine, New Haven, CT 08520
| | - Mark B. Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520
- Department of Computer Science, Yale University, New Haven, CT 06520
| | - Jan O. Korbel
- Genome Biology Research Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Michael Snyder
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520
- Department Genetics, Yale University School of Medicine, New Haven, CT 08520
| |
Collapse
|
29
|
Mahajan MC, Karmakar S, Newburger PE, Krause DS, Weissman SM. Dynamics of alpha-globin locus chromatin structure and gene expression during erythroid differentiation of human CD34(+) cells in culture. Exp Hematol 2009; 37:1143-1156.e3. [PMID: 19607874 DOI: 10.1016/j.exphem.2009.07.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2009] [Revised: 06/05/2009] [Accepted: 07/07/2009] [Indexed: 01/17/2023]
Abstract
OBJECTIVE The aim of the present study has been to establish serum-free culture conditions for ex vivo expansion and differentiation of human CD34(+) cells into erythroid lineage and to study the chromatin structure, gene expression, and transcription factor recruitment at the alpha-globin locus in the developing erythron. MATERIALS AND METHODS A basal Iscove's modified Dulbecco's medium cell culture medium with 1% bovine serum albumin as a serum replacement and a combination of cytokines and growth factors was used for expansion and differentiation of the CD34(+) cells. Expression patterns of the alpha- and beta-like genes at various stages of erythropoiesis was studied by reverse transcriptase quantitative polymerase chain reaction analysis, profile of key erythroid transcription factors was investigated by Western blotting, and the chromatin structure and transcription factor recruitment at the alpha-globin locus was investigated by chromatin immunoprecipitation quantitative polymerase chain reaction analysis. RESULTS Human CD34(+) cells in the serum-free medium undergo near synchronous erythroid differentiation to yield large amount of cells at different differentiation stages. We observe distinct patterns of the histone modifications and transcription factor binding at the alpha-globin locus during erythroid differentiation of CD34(+) cells. Nuclear factor erythroid-derived 2 (NF-E2) was present at upstream activator sites even before addition of erythropoietin (EPO), while bound GATA-1 was only detectable after EPO treatment. After 7 days of EPO treatment, H3K4Me2 modification uniformly increases throughout the alpha-globin locus. Acetylation at H3K9 and binding of Pol II, NF-E2, and GATA-1 were restricted to certain hypersensitive sites of the enhancer and theta gene, and were conspicuously low at the alpha-like globin promoters. Rearrangement of the insulator binding factor CTCF took place at and around the alpha-globin locus as CD34(+) cells differentiated into erythroid pathway. CONCLUSION Our results indicate that remodeling of the upstream elements may be the primary event in activation of alpha-globin gene expression. Activation of alpha-globin genes upon EPO treatment involves initial binding of Pol II, downregulation of pre-existing factors like NF-E2, removal of CTCF from the locus, then rebinding of CTCF in an altered pattern, and concurrent or subsequent binding of transcription factors like GATA-1.
Collapse
Affiliation(s)
- Milind C Mahajan
- Department of Genetics, The Anlyan Center, Yale University School of Medicine, New Haven, CT 06510, USA
| | | | | | | | | |
Collapse
|
30
|
Koga Y, Pelizzola M, Cheng E, Krauthammer M, Sznol M, Ariyan S, Narayan D, Molinaro AM, Halaban R, Weissman SM. Genome-wide screen of promoter methylation identifies novel markers in melanoma. Genome Res 2009; 19:1462-70. [PMID: 19491193 DOI: 10.1101/gr.091447.109] [Citation(s) in RCA: 139] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
DNA methylation is an important component of epigenetic modifications, which influences the transcriptional machinery aberrant in many human diseases. In this study we present the first genome-wide integrative analysis of promoter methylation and gene expression for the identification of methylation markers in melanoma. Genome-wide promoter methylation and gene expression of eight early-passage human melanoma cell strains were compared with newborn and adult melanocytes. We used linear mixed effect models (LME) in combination with a series of filters based on the localization of promoter methylation relative to the transcription start site, overall promoter CpG content, and differential gene expression to discover DNA methylation markers. This approach identified 76 markers, of which 68 were hyper- and eight hypomethylated (LME, P < 0.05). Promoter methylation and differential gene expression of five markers (COL1A2, NPM2, HSPB6, DDIT4L, MT1G) were validated by sequencing of bisulfite-modified DNA and real-time reverse transcriptase PCR, respectively. Importantly, the incidence of promoter methylation of the validated markers increased moderately in early and significantly in advanced-stage melanomas, using early-passage cell strains and snap-frozen tissues (n = 18 and n = 24, respectively) compared with normal melanocytes and nevi (n = 11 and n = 9, respectively). Our approach allows robust identification of methylation markers that can be applied to other studies involving genome-wide promoter methylation. In conclusion, this study represents the first unbiased systematic effort to determine methylation markers in melanoma and revealed several novel genes regulated by promoter methylation that were not described in cancer cells before.
Collapse
Affiliation(s)
- Yasuo Koga
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520-8059, USA
| | | | | | | | | | | | | | | | | | | |
Collapse
|
31
|
Rabinovich PM, Komarovskaya ME, Wrzesinski SH, Alderman JL, Budak-Alpdogan T, Karpikov A, Guo H, Flavell RA, Cheung NK, Weissman SM, Bahceci E. Chimeric receptor mRNA transfection as a tool to generate antineoplastic lymphocytes. Hum Gene Ther 2009; 20:51-61. [PMID: 19025415 PMCID: PMC2855249 DOI: 10.1089/hum.2008.068] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2008] [Accepted: 10/15/2008] [Indexed: 11/12/2022] Open
Abstract
mRNA transfection is a useful approach for temporal cell reprogramming with minimal risk of transgene-mediated mutagenesis. We applied this to redirect lymphocyte cytotoxicity toward malignant cells. Using the chimeric immune receptor (CIR) constructs anti-CD19 CIR and 8H9 CIR, we achieved uniform expression of CIRs on virtually the entire population of lymphocytes. We reprogrammed CD3+ CD8+, CD3+ CD4+, and natural killer (NK ) cells toward autologous and allogeneic targets such as B cells, Daudi lymphoma, primary melanoma, breast ductal carcinoma, breast adenocarcinoma, and rhabdomyosarcoma. The reprogramming procedure is fast. Although most of the experiments were performed on lymphocytes obtained after 7-day activation, only 1-day activation of T cells with anti-CD3, anti-CD28 antibodies, and interleukin-2 is sufficient to develop both lymphocyte cytotoxicity and competence for mRNA transfer. The entire procedure, which includes lymphocyte activation and reprogramming, can be completed in 2 days. The efficiency of mRNA-modified human T cells was tested in a murine xenograft model. Human CD3+CD8+ lymphocytes expressing anti-CD19 CIR mRNA inhibited Daudi lymphoma growth in NOD=SCID mice. These results demonstrate that a mixed population of cytotoxic lymphocytes, including T cells together with NK cells, can be quickly and simultaneously reprogrammed by mRNA against autologous malignancies. With relatively minor modifications the described method of lymphocyte reprogramming can be scaled up for cancer therapy.
Collapse
Affiliation(s)
- Peter M. Rabinovich
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520
| | - Marina E. Komarovskaya
- Section of Medical Oncology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06520
| | - Stephen H. Wrzesinski
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520
- Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06520
| | - Jonathan L. Alderman
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520
| | | | - Alexander Karpikov
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT 06520
| | - Hongfen Guo
- Department of Pediatrics, Memorial Sloan-Kettering Cancer Center, New York, NY 10021
| | - Richard A. Flavell
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520
- Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, CT 06520
| | - Nai-Kong Cheung
- Department of Pediatrics, Memorial Sloan-Kettering Cancer Center, New York, NY 10021
| | - Sherman M. Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520
| | - Erkut Bahceci
- Section of Medical Oncology, Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06520
| |
Collapse
|
32
|
Rabinovich PM, Komarovskaya ME, Wrzesinski SH, Alderman JL, Budak-Alpdogan T, Karpikov A, Guo H, Flavell RA, Cheung NK, Weissman SM, Bahceci E. Chimeric Receptor mRNA Transfection as a Tool to Generate Antineoplastic Lymphocytes. Hum Gene Ther 2008. [DOI: 10.1089/hgt.2008.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
|
33
|
Reed BD, Charos AE, Szekely AM, Weissman SM, Snyder M. Genome-wide occupancy of SREBP1 and its partners NFY and SP1 reveals novel functional roles and combinatorial regulation of distinct classes of genes. PLoS Genet 2008; 4:e1000133. [PMID: 18654640 PMCID: PMC2478640 DOI: 10.1371/journal.pgen.1000133] [Citation(s) in RCA: 167] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2008] [Accepted: 06/18/2008] [Indexed: 01/23/2023] Open
Abstract
The sterol regulatory element-binding protein (SREBP) family member SREBP1 is a critical transcriptional regulator of cholesterol and fatty acid metabolism and has been implicated in insulin resistance, diabetes, and other diet-related diseases. We globally identified the promoters occupied by SREBP1 and its binding partners NFY and SP1 in a human hepatocyte cell line using chromatin immunoprecipitation combined with genome tiling arrays (ChIP-chip). We find that SREBP1 occupies the promoters of 1,141 target genes involved in diverse biological pathways, including novel targets with roles in lipid metabolism and insulin signaling. We also identify a conserved SREBP1 DNA-binding motif in SREBP1 target promoters, and we demonstrate that many SREBP1 target genes are transcriptionally activated by treatment with insulin and glucose using gene expression microarrays. Finally, we show that SREBP1 cooperates extensively with NFY and SP1 throughout the genome and that unique combinations of these factors target distinct functional pathways. Our results provide insight into the regulatory circuitry in which SREBP1 and its network partners coordinate a complex transcriptional response in the liver with cues from the diet. Transcription factors (TFs) are DNA-binding proteins that regulate the transcription of their target genes. TFs typically bind in proximity to the transcription start sites of their target genes in a region called the promoter. SREBP1 is a TF that increases the transcription of numerous genes involved in cholesterol and fat metabolism and has been linked to diet-related diseases such as insulin resistance and type 2 diabetes. Using microarray technology, we identified all of the promoters in the human genome that are bound by SREBP1 and two associated TFs called NFY and SP1 in a human liver cell line. Our findings greatly expand the number of genes and biological pathways that may be regulated by SREBP1 and reveal that different combinations of SREBP1 and its partners preferentially target genes involved in different pathways. Thus, in contrast to traditional studies that focus on individual genes, we have used a genomics approach to provide a novel global view of the regulatory circuitry in which SREBP1 and its partners coordinate a transcriptional response in the liver with cues from the diet.
Collapse
Affiliation(s)
- Brian D. Reed
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America
| | - Alexandra E. Charos
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America
| | - Anna M. Szekely
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Sherman M. Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Michael Snyder
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America
- Molecular Biophysics and Biochemistry Department, Yale University, New Haven, Connecticut, United States of America
- * E-mail:
| |
Collapse
|
34
|
Lian Z, Karpikov A, Lian J, Mahajan MC, Hartman S, Gerstein M, Snyder M, Weissman SM. A genomic analysis of RNA polymerase II modification and chromatin architecture related to 3' end RNA polyadenylation. Genome Res 2008; 18:1224-37. [PMID: 18487515 DOI: 10.1101/gr.075804.107] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Genomic analyses have been applied extensively to analyze the process of transcription initiation in mammalian cells, but less to transcript 3' end formation and transcription termination. We used a novel approach to prepare 3' end fragments from polyadenylated RNA, and mapped the position of the poly(A) addition site using oligonucleotide arrays tiling 1% of the human genome. This approach revealed more 3' ends than had been annotated. The distribution of these ends relative to RNA polymerase II (PolII) and di- and trimethylated lysine 4 and lysine 36 of histone H3 was compared. A substantial fraction of unannotated 3' ends of RNA are intronic and antisense to the embedding gene. Poly(A) ends of annotated messages lie on average 2 kb upstream of the end of PolII binding (termination). Near the termination sites, and in some internal sites, unphosphorylated and C-terminal domain (CTD) serine 2 phosphorylated PolII (POLR2A) accumulate, suggesting pausing of the polymerase and perhaps dephosphorylation prior to release. Lysine 36 trimethylation occurs across transcribed genes, sometimes alternating with stretches of DNA in which lysine 36 dimethylation is more prominent. Lysine 36 methylation decreases at or near the site of polyadenylation, sometimes disappearing before disappearance of phosphorylated RNA PolII or release of PolII from DNA. Our results suggest that transcription termination loss of histone 3 lysine 36 methylation and later release of RNA polymerase. The latter is often associated with polymerase pausing. Overall, our study reveals extensive sites of poly(A) addition and provides insights into the events that occur during 3' end formation.
Collapse
Affiliation(s)
- Zheng Lian
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520-8005, USA
| | | | | | | | | | | | | | | |
Collapse
|
35
|
Abstract
The developmental changes in expression of the beta like genes from embryonic to adult stages of human life are controlled at least partially at the level of the promoter sequences of these genes and their binding factors, and competition for promoter specific interactions with the locus control region (LCR). In recent years, the control of beta globin genes has also been investigated at the level of chromatin structure involving the chemical modification of histones and their remodelling by DNA dependent ATPases (SMARCA) containing protein complexes. The role of intergenic RNA is also being investigated with renewed interest. Although a wealth of information on the structure/function relationship of the LCR and globin promoters has been gathered over more than two decades, the fundamental nature of the control of these genes at the molecular level is still not completely understood. In the following pages, we intend to briefly describe the progress made in the field and discuss future directions.
Collapse
Affiliation(s)
- Milind C Mahajan
- Department of Human Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
| | | | | |
Collapse
|
36
|
Korbel JO, Urban AE, Affourtit JP, Godwin B, Grubert F, Simons JF, Kim PM, Palejev D, Carriero NJ, Du L, Taillon BE, Chen Z, Tanzer A, Saunders ACE, Chi J, Yang F, Carter NP, Hurles ME, Weissman SM, Harkins TT, Gerstein MB, Egholm M, Snyder M. Paired-end mapping reveals extensive structural variation in the human genome. Science 2007; 318:420-6. [PMID: 17901297 PMCID: PMC2674581 DOI: 10.1126/science.1149504] [Citation(s) in RCA: 900] [Impact Index Per Article: 52.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Structural variation of the genome involves kilobase- to megabase-sized deletions, duplications, insertions, inversions, and complex combinations of rearrangements. We introduce high-throughput and massive paired-end mapping (PEM), a large-scale genome-sequencing method to identify structural variants (SVs) approximately 3 kilobases (kb) or larger that combines the rescue and capture of paired ends of 3-kb fragments, massive 454 sequencing, and a computational approach to map DNA reads onto a reference genome. PEM was used to map SVs in an African and in a putatively European individual and identified shared and divergent SVs relative to the reference genome. Overall, we fine-mapped more than 1000 SVs and documented that the number of SVs among humans is much larger than initially hypothesized; many of the SVs potentially affect gene function. The breakpoint junction sequences of more than 200 SVs were determined with a novel pooling strategy and computational analysis. Our analysis provided insights into the mechanisms of SV formation in humans.
Collapse
Affiliation(s)
- Jan O Korbel
- Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT 06520, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
37
|
Korbel JO, Urban AE, Grubert F, Du J, Royce TE, Starr P, Zhong G, Emanuel BS, Weissman SM, Snyder M, Gerstein MB. Systematic prediction and validation of breakpoints associated with copy-number variants in the human genome. Proc Natl Acad Sci U S A 2007; 104:10110-5. [PMID: 17551006 PMCID: PMC1891248 DOI: 10.1073/pnas.0703834104] [Citation(s) in RCA: 61] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Copy-number variants (CNVs) are an abundant form of genetic variation in humans. However, approaches for determining exact CNV breakpoint sequences (physical deletion or duplication boundaries) across individuals, crucial for associating genotype to phenotype, have been lacking so far, and the vast majority of CNVs have been reported with approximate genomic coordinates only. Here, we report an approach, called BreakPtr, for fine-mapping CNVs (available from http://breakptr.gersteinlab.org). We statistically integrate both sequence characteristics and data from high-resolution comparative genome hybridization experiments in a discrete-valued, bivariate hidden Markov model. Incorporation of nucleotide-sequence information allows us to take into account the fact that recently duplicated sequences (e.g., segmental duplications) often coincide with breakpoints. In anticipation of an upcoming increase in CNV data, we developed an iterative, "active" approach to initially scoring with a preliminary model, performing targeted validations, retraining the model, and then rescoring, and a flexible parameterization system that intuitively collapses from a full model of 2,503 parameters to a core one of only 10. Using our approach, we accurately mapped >400 breakpoints on chromosome 22 and a region of chromosome 11, refining the boundaries of many previously approximately mapped CNVs. Four predicted breakpoints flanked known disease-associated deletions. We validated an additional four predicted CNV breakpoints by sequencing. Overall, our results suggest a predictive resolution of approximately 300 bp. This level of resolution enables more precise correlations between CNVs and across individuals than previously possible, allowing the study of CNV population frequencies. Further, it enabled us to demonstrate a clear Mendelian pattern of inheritance for one of the CNVs.
Collapse
Affiliation(s)
- Jan O. Korbel
- Departments of *Molecular Biophysics and Biochemistry and
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
- To whom correspondence may be addressed. E-mail: , , or
| | - Alexander Eckehart Urban
- Genetics, Yale University School of Medicine, New Haven, CT 06520
- Departments of Molecular, Cellular, and Developmental Biology and
| | - Fabian Grubert
- Genetics, Yale University School of Medicine, New Haven, CT 06520
| | - Jiang Du
- Computer Science, Yale University, New Haven, CT 06520; and
| | | | - Peter Starr
- Departments of *Molecular Biophysics and Biochemistry and
| | - Guoneng Zhong
- Departments of *Molecular Biophysics and Biochemistry and
| | - Beverly S. Emanuel
- **Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104
| | | | - Michael Snyder
- Departments of Molecular, Cellular, and Developmental Biology and
- To whom correspondence may be addressed. E-mail: , , or
| | - Mark B. Gerstein
- Departments of *Molecular Biophysics and Biochemistry and
- Computer Science, Yale University, New Haven, CT 06520; and
- To whom correspondence may be addressed. E-mail: , , or
| |
Collapse
|
38
|
Yang X, Cheng T, Sung LY, Gao S, Shen H, Yu H, Song Y, Smith SL, Tuck DP, Inoue K, Weissman SM. Reply to “On the cloning of animals from terminally differentiated cells”. Nat Genet 2007. [DOI: 10.1038/ng0207-137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
39
|
Rabinovich PM, Komarovskaya ME, Ye ZJ, Imai C, Campana D, Bahceci E, Weissman SM. Synthetic messenger RNA as a tool for gene therapy. Hum Gene Ther 2007; 17:1027-35. [PMID: 17007566 DOI: 10.1089/hum.2006.17.1027] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Transfection of human cells with DNA in biomedical applications carries the risk of insertional mutagenesis. Transfection with mRNA avoids this problem; however, in vitro production of mRNA, based on preliminary DNA template cloning in special vectors, is a laborious and time-consuming procedure. We report an efficient vectorfree method of mRNA production from polymerase chain reaction-generated DNA templates. For all cell types tested mRNA was transfected more readily than DNA, and its expression was highly uniform in cell populations. Even cell types relatively resistant to transfection with DNA could express transfected mRNA well. The level of mRNA expression could be controlled over a wide range by changing the amount of input RNA. Cells could be efficiently and simultaneously loaded with several different transcripts. To test a potential clinical application of this method, we transfected human T lymphocytes with mRNA encoding a chimeric immune receptor directed against CD19, a surface antigen widely expressed in leukemia and lymphoma. The transfected mRNA conferred powerful cytotoxicity to T cells against CD19+ targets from the same donor. These results demonstrate that this method can be applied to generate autologous T lymphocytes directed toward malignant cells.
Collapse
Affiliation(s)
- Peter M Rabinovich
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, and Department of Hematology-Oncology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
| | | | | | | | | | | | | |
Collapse
|
40
|
Sung LY, Gao S, Shen H, Yu H, Song Y, Smith SL, Chang CC, Inoue K, Kuo L, Lian J, Li A, Tian XC, Tuck DP, Weissman SM, Yang X, Cheng T. Differentiated cells are more efficient than adult stem cells for cloning by somatic cell nuclear transfer. Nat Genet 2006; 38:1323-8. [PMID: 17013394 DOI: 10.1038/ng1895] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2006] [Accepted: 09/05/2006] [Indexed: 01/29/2023]
Abstract
Since the creation of Dolly via somatic cell nuclear transfer (SCNT), more than a dozen species of mammals have been cloned using this technology. One hypothesis for the limited success of cloning via SCNT (1%-5%) is that the clones are likely to be derived from adult stem cells. Support for this hypothesis comes from the findings that the reproductive cloning efficiency for embryonic stem cells is five to ten times higher than that for somatic cells as donors and that cloned pups cannot be produced directly from cloned embryos derived from differentiated B and T cells or neuronal cells. The question remains as to whether SCNT-derived animal clones can be derived from truly differentiated somatic cells. We tested this hypothesis with mouse hematopoietic cells at different differentiation stages: hematopoietic stem cells, progenitor cells and granulocytes. We found that cloning efficiency increases over the differentiation hierarchy, and terminally differentiated postmitotic granulocytes yield cloned pups with the greatest cloning efficiency.
Collapse
Affiliation(s)
- Li-Ying Sung
- Center for Regenerative Biology and Department of Animal Science, University of Connecticut, Storrs, Connecticut 06269, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
41
|
Rabinovich PM, Komarovskaya ME, Ye ZJ, Imai C, Campana D, Bahceci E, Weissman SM. Synthetic Messenger RNA as a Tool for Gene Therapy. Hum Gene Ther 2006. [DOI: 10.1089/hum.2006.17.ft-249] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
42
|
Canaan A, Yu X, Booth CJ, Lian J, Lazar I, Gamfi SL, Castille K, Kohya N, Nakayama Y, Liu YC, Eynon E, Flavell R, Weissman SM. FAT10/diubiquitin-like protein-deficient mice exhibit minimal phenotypic differences. Mol Cell Biol 2006; 26:5180-9. [PMID: 16782901 PMCID: PMC1489174 DOI: 10.1128/mcb.00966-05] [Citation(s) in RCA: 84] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The FAT10 gene encodes a diubiquitin-like protein containing two tandem head-to-tail ubiquitin-like domains. There is a high degree of similarity between murine and human FAT10 sequences at both the mRNA and protein levels. In various cell lines, FAT10 expression was shown to be induced by gamma interferon or by tumor necrosis factor alpha. In addition, FAT10 expression was found to be up-regulated in some Epstein-Barr virus-infected B-cell lines, in activated dendritic cells, and in several epithelial tumors. However, forced expression of FAT10 in cultured cells was also found to produce apoptotic cell death. Overall, these findings suggest that FAT10 may modulate cellular growth or cellular viability. Here we describe the steps to generate, by genetic targeting, a FAT10 gene knockout mouse model. The FAT10 knockout homozygous mice are viable and fertile. No gross lesions or obvious histological differences were found in these mutated mice. Examination of lymphocyte populations from spleen, thymus, and bone marrow did not reveal any abnormalities. However, flow cytometry analysis demonstrated that the lymphocytes of FAT10 knockout mice were, on average, more prone to spontaneous apoptotic death. Physiologically, these mice demonstrated a high level of sensitivity toward endotoxin challenge. These findings indicate that FAT10 may function as a survival factor.
Collapse
Affiliation(s)
- Allon Canaan
- Department of Genetics, The Anlyan Center, Yale University School of Medicine, 300 Cedar St., TAC S-310, New Haven, CT 06510, USA
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
43
|
Liu MM, Weissman SM, Tang L. Identification of coding single nucleotide polymorphisms and mutations by combination of genome tiling arrays and enrichment/depletion of mismatch cDNAs. Anal Biochem 2006; 356:117-24. [PMID: 16777053 DOI: 10.1016/j.ab.2006.05.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2006] [Revised: 05/11/2006] [Accepted: 05/11/2006] [Indexed: 11/27/2022]
Abstract
Genome tiling array technology combined with a method for both enrichment and depletion of mismatch-containing cDNA fragments offers a useful approach for detecting coding single nucleotide polymorphisms (cSNPs) and mutations in pooled cDNA samples. Enriched mismatch and perfect match cDNA samples from human primary melanoma cells and normal melanocytes were obtained by selection using mismatch repair thymine DNA glycosylase-bound beads. These cDNA samples were then labeled and hybridized to Encyclopedia of DNA Elements genome tiling arrays. The results revealed that the hybridization intensity values of potential cDNA variation regions of the enriched mismatch samples increased, whereas the hybridization intensity values of corresponding regions of the enriched perfect match samples decreased. Six potential mutations were confirmed by polymerase chain reaction product sequencing, including two novel heterozygous mutations in melanoma cells. We suggest that this strategy should increase the efficiency of both cSNP and mutation detection throughout the entire human genome and decrease the cost and complexity of genomewide analysis of cDNA variations.
Collapse
Affiliation(s)
- Meng-Min Liu
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA.
| | | | | |
Collapse
|
44
|
Urban AE, Korbel JO, Selzer R, Richmond T, Hacker A, Popescu GV, Cubells JF, Green R, Emanuel BS, Gerstein MB, Weissman SM, Snyder M. High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays. Proc Natl Acad Sci U S A 2006; 103:4534-9. [PMID: 16537408 PMCID: PMC1450206 DOI: 10.1073/pnas.0511340103] [Citation(s) in RCA: 118] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Deletions and amplifications of the human genomic sequence (copy number polymorphisms) are the cause of numerous diseases and a potential cause of phenotypic variation in the normal population. Comparative genomic hybridization (CGH) has been developed as a useful tool for detecting alterations in DNA copy number that involve blocks of DNA several kilobases or larger in size. We have developed high-resolution CGH (HR-CGH) to detect accurately and with relatively little bias the presence and extent of chromosomal aberrations in human DNA. Maskless array synthesis was used to construct arrays containing 385,000 oligonucleotides with isothermal probes of 45-85 bp in length; arrays tiling the beta-globin locus and chromosome 22q were prepared. Arrays with a 9-bp tiling path were used to map a 622-bp heterozygous deletion in the beta-globin locus. Arrays with an 85-bp tiling path were used to analyze DNA from patients with copy number changes in the pericentromeric region of chromosome 22q. Heterozygous deletions and duplications as well as partial triploidies and partial tetraploidies of portions of chromosome 22q were mapped with high resolution (typically up to 200 bp) in each patient, and the precise breakpoints of two deletions were confirmed by DNA sequencing. Additional peaks potentially corresponding to known and novel additional CNPs were also observed. Our results demonstrate that HR-CGH allows the detection of copy number changes in the human genome at an unprecedented level of resolution.
Collapse
Affiliation(s)
- Alexander Eckehart Urban
- *Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Genetics and
| | - Jan O. Korbel
- Molecular Biophysics and Biochemistry Department, Yale University School of Medicine, New Haven, CT 06520
| | - Rebecca Selzer
- NimbleGen Systems, Inc., 1 Science Court, Madison, WI 53711
| | - Todd Richmond
- NimbleGen Systems, Inc., 1 Science Court, Madison, WI 53711
| | - April Hacker
- The Children’s Hospital of Philadelphia, Philadelphia, PA 19104
| | - George V. Popescu
- *Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520
- Department of Genetics and
| | - Joseph F. Cubells
- **Departments of Human Genetics, and Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30322
| | - Roland Green
- NimbleGen Systems, Inc., 1 Science Court, Madison, WI 53711
| | - Beverly S. Emanuel
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104; and
| | - Mark B. Gerstein
- Molecular Biophysics and Biochemistry Department, Yale University School of Medicine, New Haven, CT 06520
| | - Sherman M. Weissman
- Department of Genetics and
- To whom correspondence may be addressed. E-mail:
or
| | - Michael Snyder
- *Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520
- To whom correspondence may be addressed. E-mail:
or
| |
Collapse
|
45
|
Abstract
Biochemical analysis of the beta-globin gene function has led to the identification of several multi-protein complexes at the locus control region (LCR), insulator and promoters. This review briefly summarizes these multi-protein complexes and discusses their contribution towards the regulation of the beta-globin gene expression.
Collapse
Affiliation(s)
- Milind C Mahajan
- Department of Genetics, The Anlyan Center, Yale University School of Medicine, 300 Cedar St., New Haven, CT 06510, USA
| | | |
Collapse
|
46
|
Nakayama Y, Stabach P, Maher SE, Mahajan MC, Masiar P, Liao C, Zhang X, Ye ZJ, Tuck D, Bothwell ALM, Newburger PE, Weissman SM. A limited number of genes are involved in the differentiation of germinal center B cells. J Cell Biochem 2006; 99:1308-25. [PMID: 16795035 DOI: 10.1002/jcb.20952] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Mature B cells, upon activation, progressively differentiate through centroblasts into centrocytes and finally to plasmacytes that express large amounts of selected immunoglobulins. A significant part of this maturation is thought to involve induction of the unfolded protein response (UPR). We have compared gene expression in normal germinal center centroblasts, centrocytes, lymphoblastoid cells undergoing induced UPR, and the CCL155 plasmacytoma cell line. In the centroblast to centrocyte transition there is a change in the expression of a relatively small number of genes. These include a limited subset of the genes upregulated by a fully activated UPR as well as a small number of other transcription factors, some disulphide isomerases, and other genes. This is consistent with a model in which this transition is mediated by changes in the levels of expression of transcription factor B-lymphocyte-induced maturation protein 1 (Blimp1) (PRDM1), BACH2, X-box binding protein 1 (XBP1), interferon regulatory factor 4 (IRF4), and possibly vitamin D receptor (VDR) expression, together with post-transcriptional changes and a limited induction of aspects of the UPR.
Collapse
Affiliation(s)
- Yasuhiro Nakayama
- Department of Genetics, Yale University School of Medicine, 300 Cedar St., New Haven, Connecticut 06510, USA.
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
47
|
Abstract
The biochemistry of early stages of hematopoietic differentiation is difficult to study because only relatively small numbers of precursor cells are available. The murine EML cell line is a multipotential cell line that can be used to model some of these steps. We found that the lineage- EML precursor cells can be separated into two populations based on cell surface markers including CD34. Both populations contain similar levels of stem cell factor (SCF) receptor (c-Kit) but only the CD34+ population shows a growth response when treated with SCF. Conversely, the CD34- population will grow in the presence of the cytokine IL-3. The human beta-globin locus control region hypersensitive site 2 plays different roles on beta-globin transcription in the CD34+ and CD34- populations. The two populations are present in about equal amounts in culture, and the CD34+ population rapidly regenerates the mixed population when grown in the presence of SCF. We suggest that this system may mimic a normal developmental transition in hematopoiesis.
Collapse
Affiliation(s)
- Zhi-jia Ye
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06519, USA
| | | | | | | |
Collapse
|
48
|
Szekely AM, Bleichert F, Nümann A, Van Komen S, Manasanch E, Ben Nasr A, Canaan A, Weissman SM. Werner protein protects nonproliferating cells from oxidative DNA damage. Mol Cell Biol 2005; 25:10492-506. [PMID: 16287861 PMCID: PMC1291253 DOI: 10.1128/mcb.25.23.10492-10506.2005] [Citation(s) in RCA: 75] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2004] [Revised: 01/10/2005] [Accepted: 08/31/2005] [Indexed: 02/06/2023] Open
Abstract
Werner syndrome, caused by mutations of the WRN gene, mimics many changes of normal aging. Although roles for WRN protein in DNA replication, recombination, and telomere maintenance have been suggested, the pathology of rapidly dividing cells is not a feature of Werner syndrome. To identify cellular events that are specifically vulnerable to WRN deficiency, we used RNA interference (RNAi) to knockdown WRN or BLM (the RecQ helicase mutated in Bloom syndrome) expression in primary human fibroblasts. Withdrawal of WRN or BLM produced accelerated cellular senescence phenotype and DNA damage response in normal fibroblasts, as evidenced by induction of gammaH2AX and 53BP1 nuclear foci. After WRN depletion, the induction of these foci was seen most prominently in nondividing cells. Growth in physiological (3%) oxygen or in the presence of an antioxidant prevented the development of the DNA damage foci in WRN-depleted cells, whereas acute oxidative stress led to inefficient repair of the lesions. Furthermore, WRN RNAi-induced DNA damage was suppressed by overexpression of the telomere-binding protein TRF2. These conditions, however, did not prevent the DNA damage response in BLM-ablated cells, suggesting a distinct role for WRN in DNA homeostasis in vivo. Thus, manifestations of Werner syndrome may reflect an impaired ability of slowly dividing cells to limit oxidative DNA damage.
Collapse
Affiliation(s)
- Anna M Szekely
- Department of Genetics, Yale University School of Medicine, TAC Bldg., Rm. S319, 300 Cedar St., New Haven, CT 06510, USA
| | | | | | | | | | | | | | | |
Collapse
|
49
|
Mahajan MC, Narlikar GJ, Boyapaty G, Kingston RE, Weissman SM. Heterogeneous nuclear ribonucleoprotein C1/C2, MeCP1, and SWI/SNF form a chromatin remodeling complex at the beta-globin locus control region. Proc Natl Acad Sci U S A 2005; 102:15012-7. [PMID: 16217013 PMCID: PMC1257739 DOI: 10.1073/pnas.0507596102] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Locus control regions (LCRs) are regulatory DNA sequences that are situated many kilobases away from their cognate promoters. LCRs protect transgenes from position effect variegation and heterochromatinization and also promote copy-number dependence of the levels of transgene expression. In this work, we describe the biochemical purification of a previously undescribed LCR-associated remodeling complex (LARC) that consists of heterogeneous nuclear ribonucleoprotein C1/C2, nucleosome remodeling SWI/SNF, and nucleosome remodeling and deacetylating (NuRD)/MeCP1 as a single homogeneous complex. LARC binds to the hypersensitive 2 (HS2)-Maf recognition element (MARE) DNA in a sequence-specific manner and remodels nucleosomes. Heterogeneous nuclear ribonucleoprotein C1/C2, previously known as a general RNA binding protein, provides a sequence-specific DNA recognition element for LARC, and the LARC DNA-recognition sequence is essential for the enhancement of transcription by HS2. Independently of the initiation of transcription, LARC becomes associated with beta-like globin promoters.
Collapse
Affiliation(s)
- Milind C Mahajan
- Department of Genetics, The Anlyan Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | | | | | | | | |
Collapse
|
50
|
Kluger Y, Tuck DP, Chang JT, Nakayama Y, Poddar R, Kohya N, Lian Z, Ben Nasr A, Halaban HR, Krause DS, Zhang X, Newburger PE, Weissman SM. Lineage specificity of gene expression patterns. Proc Natl Acad Sci U S A 2004; 101:6508-13. [PMID: 15096607 PMCID: PMC404075 DOI: 10.1073/pnas.0401136101] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The hematopoietic system offers many advantages as a model for understanding general aspects of lineage choice and specification. Using oligonucleotide microarrays, we compared gene expression patterns of multiple purified hematopoietic cell populations, including neutrophils, monocytes, macrophages, resting, centrocytic, and centroblastic B lymphocytes, dendritic cells, and hematopoietic stem cells. Some of these cells were studied under both resting and stimulated conditions. We studied the collective behavior of subsets of genes derived from the Biocarta database of functional pathways, hand-tuned groupings of genes into broad functional categories based on the Gene Ontology database, and the metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes database. Principal component analysis revealed strikingly pervasive differences in relative levels of gene expression among cell lineages that involve most of the subsets examined. These results indicate that many processes in these cells behave differently in different lineages. Much of the variation among lineages was captured by the first few principal components. Principal components biplots were found to provide a convenient visual display of the contributions of the various genes within the subsets in lineage discrimination. Moreover, by applying tree-constructing methodologies borrowed from phylogenetics to the expression data from differentiated cells and stem cells, we reconstructed a tree of relationships that resembled the established hematopoietic program of lineage development. Thus, the mRNA expression data implicitly contained information about developmental relationships among cell types.
Collapse
Affiliation(s)
- Yuval Kluger
- Department of Cell Biology, New York University School of Medicine, New York, NY 10016, USA
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|