1
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Zhang F, Zhou J, Lu P, Zhang X, Yang L, Wu J, Zhang L, Zhang L, Pang J, Xie H, Xie B, Jiang Y, Peng J. Lactylation of histone by BRD4 regulates astrocyte polarization after experimental subarachnoid hemorrhage. J Neuroinflammation 2024; 21:186. [PMID: 39080649 PMCID: PMC11290164 DOI: 10.1186/s12974-024-03185-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024] Open
Abstract
Under subarachnoid hemorrhage (SAH) conditions, astrocytes undergo a marked intensification of glycolytic activity, resulting in the generation of substantial amounts of lactate to maintain the energy demand for neurons and other brain cells. Lactate has garnered increasing attention in recent years because of its emerging role in critical biological processes such as inflammation regulation and neuroprotection, particularly through its histone lactylation. Bromodomain-containing protein 4 (BRD4) plays a crucial role in maintaining neural development and promoting memory formation in the central nervous system. Nonetheless, the function and regulatory mechanism of BRD4 and histone lactylation in astrocytes following SAH remain elusive. Our findings indicate that BRD4, a crucial epigenetic regulator, plays a definitive role in histone lactylation. Both in vitro and in vivo, these results demonstrated that targeted silencing of BRD4 in astrocytes can significantly reduce H4K8la lactylation, thereby aggravating the A1 polarization of astrocytes and ultimately affecting the recovery of neural function and prognosis in mice after SAH. In summary, BRD4 plays a pivotal role in modulating astrocyte polarization following SAH via histone lactylation. Targeting this mechanism might offer an efficient therapeutic strategy for SAH.
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Affiliation(s)
- Fan Zhang
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Jian Zhou
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Peng Lu
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Xianhui Zhang
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Lei Yang
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Jinpeng Wu
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Lihan Zhang
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Lifang Zhang
- Sichuan Clinical Research Center for Neurosurgery, The Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Jinwei Pang
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China
| | - Huangfan Xie
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
- Institute of Brain Science, Southwest Medical University, Luzhou, China
| | - Bingqing Xie
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China
- Institute of Brain Science, Southwest Medical University, Luzhou, China
| | - Yong Jiang
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China.
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
- Institute of Brain Science, Southwest Medical University, Luzhou, China.
- Sichuan Clinical Research Center for Neurosurgery, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
| | - Jianhua Peng
- Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, NO. 25 of Taiping Street, Luzhou, Sichuan, 646000, China.
- Laboratory of Neurological Diseases and Brain Function, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
- Academician (Expert) Workstation of Sichuan Province, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
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2
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Zhang T, Tan S, Tang N, Li Y, Zhang C, Sun J, Guo Y, Gao H, Cai Y, Sun W, Wang C, Fu L, Ma H, Wu Y, Hu X, Zhang X, Gee P, Yan W, Zhao Y, Chen Q, Guo B, Wang H, Zhang YE. Heterologous survey of 130 DNA transposons in human cells highlights their functional divergence and expands the genome engineering toolbox. Cell 2024; 187:3741-3760.e30. [PMID: 38843831 DOI: 10.1016/j.cell.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 07/14/2024]
Abstract
Experimental studies on DNA transposable elements (TEs) have been limited in scale, leading to a lack of understanding of the factors influencing transposition activity, evolutionary dynamics, and application potential as genome engineering tools. We predicted 130 active DNA TEs from 102 metazoan genomes and evaluated their activity in human cells. We identified 40 active (integration-competent) TEs, surpassing the cumulative number (20) of TEs found previously. With this unified comparative data, we found that the Tc1/mariner superfamily exhibits elevated activity, potentially explaining their pervasive horizontal transfers. Further functional characterization of TEs revealed additional divergence in features such as insertion bias. Remarkably, in CAR-T therapy for hematological and solid tumors, Mariner2_AG (MAG), the most active DNA TE identified, largely outperformed two widely used vectors, the lentiviral vector and the TE-based vector SB100X. Overall, this study highlights the varied transposition features and evolutionary dynamics of DNA TEs and increases the TE toolbox diversity.
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Affiliation(s)
- Tongtong Zhang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Shengjun Tan
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Na Tang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Yuanqing Li
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chenze Zhang
- National Key Laboratory of Efficacy and Mechanism on Chinese Medicine for Metabolic Diseases, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Jing Sun
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Guo
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Hui Gao
- Rengene Biotechnology Co., Ltd., Beijing 100036, China
| | - Yujia Cai
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Wen Sun
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Chenxin Wang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Liangzheng Fu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Huijing Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yachao Wu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoxuan Hu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Xuechun Zhang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Peter Gee
- MaxCyte Inc., Rockville, MD 20850, USA
| | - Weihua Yan
- Cold Spring Biotech Corp., Beijing 100031, China
| | - Yahui Zhao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Chen
- Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Baocheng Guo
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810008, China
| | - Haoyi Wang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China.
| | - Yong E Zhang
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
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3
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Li J, Wang Z, Tong L, Wang Q, Rajamani KT, Muñoz-Castañeda R, Mu S, Qi T, Zhang Y, Ngiam ZC, Ohte N, Hanashima C, Wu Z, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development. Cell 2024; 187:3236-3248.e21. [PMID: 38772369 PMCID: PMC11193654 DOI: 10.1016/j.cell.2024.04.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/30/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024]
Abstract
Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Sean K Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Grace S Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Jiwen Li
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Keerthi T Rajamani
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Rodrigo Muñoz-Castañeda
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Shang Mu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Tianbo Qi
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yunxiao Zhang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zi Chao Ngiam
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Naoto Ohte
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Carina Hanashima
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Zhuhao Wu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Joshua Z Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA.
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4
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Lalanne JB, Regalado SG, Domcke S, Calderon D, Martin BK, Li X, Li T, Suiter CC, Lee C, Trapnell C, Shendure J. Multiplex profiling of developmental cis-regulatory elements with quantitative single-cell expression reporters. Nat Methods 2024; 21:983-993. [PMID: 38724692 PMCID: PMC11166576 DOI: 10.1038/s41592-024-02260-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/22/2024] [Indexed: 06/13/2024]
Abstract
The inability to scalably and precisely measure the activity of developmental cis-regulatory elements (CREs) in multicellular systems is a bottleneck in genomics. Here we develop a dual RNA cassette that decouples the detection and quantification tasks inherent to multiplex single-cell reporter assays. The resulting measurement of reporter expression is accurate over multiple orders of magnitude, with a precision approaching the limit set by Poisson counting noise. Together with RNA barcode stabilization via circularization, these scalable single-cell quantitative expression reporters provide high-contrast readouts, analogous to classic in situ assays but entirely from sequencing. Screening >200 regions of accessible chromatin in a multicellular in vitro model of early mammalian development, we identify 13 (8 previously uncharacterized) autonomous and cell-type-specific developmental CREs. We further demonstrate that chimeric CRE pairs generate cognate two-cell-type activity profiles and assess gain- and loss-of-function multicellular expression phenotypes from CRE variants with perturbed transcription factor binding sites. Single-cell quantitative expression reporters can be applied in developmental and multicellular systems to quantitatively characterize native, perturbed and synthetic CREs at scale, with high sensitivity and at single-cell resolution.
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Affiliation(s)
| | - Samuel G Regalado
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Silvia Domcke
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Diego Calderon
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Beth K Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Tony Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Chase C Suiter
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Choli Lee
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
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5
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Graham JH, Schlachetzki JCM, Yang X, Breuss MW. Genomic Mosaicism of the Brain: Origin, Impact, and Utility. Neurosci Bull 2024; 40:759-776. [PMID: 37898991 PMCID: PMC11178748 DOI: 10.1007/s12264-023-01124-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 07/16/2023] [Indexed: 10/31/2023] Open
Abstract
Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.
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Affiliation(s)
- Jared H Graham
- Department of Pediatrics, Section of Clinical Genetics and Metabolism, University of Colorado School of Medicine, Aurora, 80045-2581, CO, USA
| | - Johannes C M Schlachetzki
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, 92093-0021, San Diego, CA, USA
| | - Xiaoxu Yang
- Department of Neurosciences, University of California San Diego, La Jolla, 92093-0021, San Diego, CA, USA
- Rady Children's Institute for Genomic Medicine, San Diego, 92123, CA, USA
| | - Martin W Breuss
- Department of Pediatrics, Section of Clinical Genetics and Metabolism, University of Colorado School of Medicine, Aurora, 80045-2581, CO, USA.
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6
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Hong CKY, Ramu A, Zhao S, Cohen BA. Effect of genomic and cellular environments on gene expression noise. Genome Biol 2024; 25:137. [PMID: 38790076 PMCID: PMC11127367 DOI: 10.1186/s13059-024-03277-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. RESULTS To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci. CONCLUSIONS Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Siqi Zhao
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
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7
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Köhnke T, Nuno KA, Alder CC, Gars EJ, Phan P, Fan AC, Majeti R. Human ASXL1-Mutant Hematopoiesis Is Driven by a Truncated Protein Associated with Aberrant Deubiquitination of H2AK119. Blood Cancer Discov 2024; 5:202-223. [PMID: 38359087 PMCID: PMC11061584 DOI: 10.1158/2643-3230.bcd-23-0235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 02/17/2024] Open
Abstract
Mutations in additional sex combs like 1 (ASXL1) confer poor prognosis both in myeloid malignancies and in premalignant clonal hematopoiesis (CH). However, the mechanisms by which these mutations contribute to disease initiation remain unresolved, and mutation-specific targeting has remained elusive. To address this, we developed a human disease model that recapitulates the disease trajectory from ASXL1-mutant CH to lethal myeloid malignancy. We demonstrate that mutations in ASXL1 lead to the expression of a functional, truncated protein and determine that truncated ASXL1 leads to global redistribution of the repressive chromatin mark H2AK119Ub, increased transposase-accessible chromatin, and activation of both myeloid and stem cell gene-expression programs. Finally, we demonstrate that H2AK119Ub levels are tied to truncated ASXL1 expression levels and leverage this observation to demonstrate that inhibition of the PRC1 complex might be an ASXL1-mutant-specific therapeutic vulnerability in both premalignant CH and myeloid malignancy. SIGNIFICANCE Mutant ASXL1 is a common driver of CH and myeloid malignancy. Using primary human HSPCs, we determine that truncated ASXL1 leads to redistribution of H2AK119Ub and may affect therapeutic vulnerability to PRC1 inhibition.
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Affiliation(s)
- Thomas Köhnke
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
| | - Kevin A. Nuno
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
| | | | - Eric J. Gars
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
| | - Paul Phan
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
| | - Amy C. Fan
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
| | - Ravindra Majeti
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California
- Stanford School of Medicine, Stanford, California
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8
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Jeong D, Shi G, Li X, Thirumalai D. Structural basis for the preservation of a subset of topologically associating domains in interphase chromosomes upon cohesin depletion. eLife 2024; 12:RP88564. [PMID: 38502563 PMCID: PMC10950330 DOI: 10.7554/elife.88564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024] Open
Abstract
Compartment formation in interphase chromosomes is a result of spatial segregation between euchromatin and heterochromatin on a few megabase pairs (Mbp) scale. On the sub-Mbp scales, topologically associating domains (TADs) appear as interacting domains along the diagonal in the ensemble averaged Hi-C contact map. Hi-C experiments showed that most of the TADs vanish upon deleting cohesin, while the compartment structure is maintained, and perhaps even enhanced. However, closer inspection of the data reveals that a non-negligible fraction of TADs is preserved (P-TADs) after cohesin loss. Imaging experiments show that, at the single-cell level, TAD-like structures are present even without cohesin. To provide a structural basis for these findings, we first used polymer simulations to show that certain TADs with epigenetic switches across their boundaries survive after depletion of loops. More importantly, the three-dimensional structures show that many of the P-TADs have sharp physical boundaries. Informed by the simulations, we analyzed the Hi-C maps (with and without cohesin) in mouse liver and human colorectal carcinoma cell lines, which affirmed that epigenetic switches and physical boundaries (calculated using the predicted 3D structures using the data-driven HIPPS method that uses Hi-C as the input) explain the origin of the P-TADs. Single-cell structures display TAD-like features in the absence of cohesin that are remarkably similar to the findings in imaging experiments. Some P-TADs, with physical boundaries, are relevant to the retention of enhancer-promoter/promoter-promoter interactions. Overall, our study shows that preservation of a subset of TADs upon removing cohesin is a robust phenomenon that is valid across multiple cell lines.
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Affiliation(s)
- Davin Jeong
- Department of Chemistry, University of Texas at AustinAustinUnited States
| | - Guang Shi
- Department of Chemistry, University of Texas at AustinAustinUnited States
| | - Xin Li
- Department of Chemistry, University of Texas at AustinAustinUnited States
| | - D Thirumalai
- Department of Chemistry, University of Texas at AustinAustinUnited States
- Department of Physics, University of Texas at AustinAustinUnited States
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9
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Guo J, Zhang W, Chen X, Yen A, Chen L, Shively CA, Li D, Wang T, Dougherty JD, Mitra RD. Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data. Bioinformatics 2024; 40:btae070. [PMID: 38323623 PMCID: PMC10881108 DOI: 10.1093/bioinformatics/btae070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/25/2023] [Accepted: 02/05/2024] [Indexed: 02/08/2024] Open
Abstract
MOTIVATION Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data. RESULTS We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data. AVAILABILITY AND IMPLEMENTATION Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.
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Affiliation(s)
- Juanru Guo
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Wenjin Zhang
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Xuhua Chen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Allen Yen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Department of Psychiatry, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Lucy Chen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Christian A Shively
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Daofeng Li
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Ting Wang
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- McDonnell Genome Institute, , Washington University in St. Louis School of Medicine, Saint Louis, MO, 63110, United States
| | - Joseph D Dougherty
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Department of Psychiatry, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63108, United States
| | - Robi D Mitra
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- McDonnell Genome Institute, , Washington University in St. Louis School of Medicine, Saint Louis, MO, 63110, United States
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63108, United States
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10
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Lagunas T, Plassmeyer SP, Fischer AD, Friedman RZ, Rieger MA, Selmanovic D, Sarafinovska S, Sol YK, Kasper MJ, Fass SB, Aguilar Lucero AF, An JY, Sanders SJ, Cohen BA, Dougherty JD. A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo. Commun Biol 2023; 6:1151. [PMID: 37953348 PMCID: PMC10641075 DOI: 10.1038/s42003-023-05483-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023] Open
Abstract
The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3'UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.
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Affiliation(s)
- Tomas Lagunas
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Stephen P Plassmeyer
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Anthony D Fischer
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Ryan Z Friedman
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Michael A Rieger
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Din Selmanovic
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Yvette K Sol
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Michael J Kasper
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Stuart B Fass
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Alessandra F Aguilar Lucero
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, 94518, USA
| | - Joon-Yong An
- Department of Integrated Biomedical and Life Science, Korea University, Seoul, 02841, Republic of Korea
- School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, 02841, Republic of Korea
| | - Stephan J Sanders
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, 94518, USA
| | - Barak A Cohen
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
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11
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Wang Z, Tong L, Wang Q, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell type-specific transcriptional networks in cortical development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558077. [PMID: 37790302 PMCID: PMC10542124 DOI: 10.1101/2023.09.18.558077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Systematic analysis of gene function across diverse cell types in vivo is hindered by two challenges: obtaining sufficient cells from live tissues and accurately identifying each cell's perturbation in high-throughput single-cell assays. Leveraging AAV's versatile cell type tropism and high labeling capacity, we expanded the resolution and scale of in vivo CRISPR screens: allowing phenotypic analysis at single-cell resolution across a multitude of cell types in the embryonic brain, adult brain, and peripheral nervous system. We undertook extensive tests of 86 AAV serotypes, combined with a transposon system, to substantially amplify labeling and accelerate in vivo gene delivery from weeks to days. Using this platform, we performed an in utero genetic screen as proof-of-principle and identified pleiotropic regulatory networks of Foxg1 in cortical development, including Layer 6 corticothalamic neurons where it tightly controls distinct networks essential for cell fate specification. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% (mediated by lentivirus), and achieve analysis of over 30,000 cells in one experiment, thus enabling massively parallel in vivo Perturb-seq. Compatible with various perturbation techniques (CRISPRa/i) and phenotypic measurements (single-cell or spatial multi-omics), our platform presents a flexible, modular approach to interrogate gene function across diverse cell types in vivo, connecting gene variants to their causal functions.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Sean K. Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Grace S. Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Joshua Z. Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
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12
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Yen A, Mateusiak C, Sarafinovska S, Gachechiladze MA, Guo J, Chen X, Moudgil A, Cammack AJ, Hoisington-Lopez J, Crosby M, Brent MR, Mitra RD, Dougherty JD. Calling Cards: A Customizable Platform to Longitudinally Record Protein-DNA Interactions Over Time in Cells and Tissues. Curr Protoc 2023; 3:e883. [PMID: 37755132 PMCID: PMC10627244 DOI: 10.1002/cpz1.883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next-generation sequencing. Compared with other genomic assays, readouts of which provide a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile-specific transcription factor (TF) binding with custom TF-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Cards reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Preparation and delivery of Calling Cards reagents Support Protocol 1: Next-generation sequencing quantification of barcode distribution within self-reporting transposon plasmid pool and adeno-associated virus genome Basic Protocol 2: Sample collection and RNA purification Support Protocol 2: Library density quantitative PCR Basic Protocol 3: Sequencing library preparation Basic Protocol 4: Library pooling and sequencing Basic Protocol 5: Data analysis.
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Affiliation(s)
- Allen Yen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Chase Mateusiak
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Mariam A. Gachechiladze
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Juanru Guo
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Arnav Moudgil
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Alexander J. Cammack
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Jessica Hoisington-Lopez
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - MariaLynn Crosby
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Michael R. Brent
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Computer Science and Engineering, Washington University, Saint Louis, MO 63130
| | - Robi D. Mitra
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Joseph D. Dougherty
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63110
- Lead contact
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13
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Chehelgerdi M, Chehelgerdi M. The use of RNA-based treatments in the field of cancer immunotherapy. Mol Cancer 2023; 22:106. [PMID: 37420174 PMCID: PMC10401791 DOI: 10.1186/s12943-023-01807-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 06/13/2023] [Indexed: 07/09/2023] Open
Abstract
Over the past several decades, mRNA vaccines have evolved from a theoretical concept to a clinical reality. These vaccines offer several advantages over traditional vaccine techniques, including their high potency, rapid development, low-cost manufacturing, and safe administration. However, until recently, concerns over the instability and inefficient distribution of mRNA in vivo have limited their utility. Fortunately, recent technological advancements have mostly resolved these concerns, resulting in the development of numerous mRNA vaccination platforms for infectious diseases and various types of cancer. These platforms have shown promising outcomes in both animal models and humans. This study highlights the potential of mRNA vaccines as a promising alternative approach to conventional vaccine techniques and cancer treatment. This review article aims to provide a thorough and detailed examination of mRNA vaccines, including their mechanisms of action and potential applications in cancer immunotherapy. Additionally, the article will analyze the current state of mRNA vaccine technology and highlight future directions for the development and implementation of this promising vaccine platform as a mainstream therapeutic option. The review will also discuss potential challenges and limitations of mRNA vaccines, such as their stability and in vivo distribution, and suggest ways to overcome these issues. By providing a comprehensive overview and critical analysis of mRNA vaccines, this review aims to contribute to the advancement of this innovative approach to cancer treatment.
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Affiliation(s)
- Mohammad Chehelgerdi
- Novin Genome (NG) Lab, Research and Development Center for Biotechnology, Shahrekord, Iran.
- Young Researchers and Elite Club, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran.
| | - Matin Chehelgerdi
- Novin Genome (NG) Lab, Research and Development Center for Biotechnology, Shahrekord, Iran
- Young Researchers and Elite Club, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
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14
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Streb P, Kowarz E, Benz T, Reis J, Marschalek R. How chromosomal translocations arise to cause cancer: Gene proximity, trans-splicing, and DNA end joining. iScience 2023; 26:106900. [PMID: 37378346 PMCID: PMC10291325 DOI: 10.1016/j.isci.2023.106900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/01/2023] [Accepted: 05/12/2023] [Indexed: 06/29/2023] Open
Abstract
Chromosomal translocations (CTs) are a genetic hallmark of cancer. They could be identified as recurrent genetic aberrations in hemato-malignancies and solid tumors. More than 40% of all "cancer genes" were identified in recurrent CTs. Most of these CTs result in the production of oncofusion proteins of which many have been studied over the past decades. They influence signaling pathways and/or alter gene expression. However, a precise mechanism for how these CTs arise and occur in a nearly identical fashion in individuals remains to be elucidated. Here, we performed experiments that explain the onset of CTs: (1) proximity of genes able to produce prematurely terminated transcripts, which lead to the production of (2) trans-spliced fusion RNAs, and finally, the induction of (3) DNA double-strand breaks which are subsequently repaired via EJ repair pathways. Under these conditions, balanced chromosomal translocations could be specifically induced. The implications of these findings will be discussed.
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Affiliation(s)
- Patrick Streb
- Goethe-University, Department Biochemistry, Chemistry & Pharmacy, Institute of Pharmaceutical Biology, Max-von-Laue-Street 9, 60438 Frankfurt am Main, Germany
| | - Eric Kowarz
- Goethe-University, Department Biochemistry, Chemistry & Pharmacy, Institute of Pharmaceutical Biology, Max-von-Laue-Street 9, 60438 Frankfurt am Main, Germany
| | - Tamara Benz
- Goethe-University, Department Biochemistry, Chemistry & Pharmacy, Institute of Pharmaceutical Biology, Max-von-Laue-Street 9, 60438 Frankfurt am Main, Germany
| | - Jennifer Reis
- Goethe-University, Department Biochemistry, Chemistry & Pharmacy, Institute of Pharmaceutical Biology, Max-von-Laue-Street 9, 60438 Frankfurt am Main, Germany
| | - Rolf Marschalek
- Goethe-University, Department Biochemistry, Chemistry & Pharmacy, Institute of Pharmaceutical Biology, Max-von-Laue-Street 9, 60438 Frankfurt am Main, Germany
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15
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Recio PS, Mitra NJ, Shively CA, Song D, Jaramillo G, Lewis KS, Chen X, Mitra R. Zinc cluster transcription factors frequently activate target genes using a non-canonical half-site binding mode. Nucleic Acids Res 2023; 51:5006-5021. [PMID: 37125648 PMCID: PMC10250231 DOI: 10.1093/nar/gkad320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 04/11/2023] [Accepted: 04/14/2023] [Indexed: 05/02/2023] Open
Abstract
Gene expression changes are orchestrated by transcription factors (TFs), which bind to DNA to regulate gene expression. It remains surprisingly difficult to predict basic features of the transcriptional process, including in vivo TF occupancy. Existing thermodynamic models of TF function are often not concordant with experimental measurements, suggesting undiscovered biology. Here, we analyzed one of the most well-studied TFs, the yeast zinc cluster Gal4, constructed a Shea-Ackers thermodynamic model to describe its binding, and compared the results of this model to experimentally measured Gal4p binding in vivo. We found that at many promoters, the model predicted no Gal4p binding, yet substantial binding was observed. These outlier promoters lacked canonical binding motifs, and subsequent investigation revealed Gal4p binds unexpectedly to DNA sequences with high densities of its half site (CGG). We confirmed this novel mode of binding through multiple experimental and computational paradigms; we also found most other zinc cluster TFs we tested frequently utilize this binding mode, at 27% of their targets on average. Together, these results demonstrate a novel mode of binding where zinc clusters, the largest class of TFs in yeast, bind DNA sequences with high densities of half sites.
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Affiliation(s)
- Pamela S Recio
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Nikhil J Mitra
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Christian A Shively
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - David Song
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Grace Jaramillo
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Kristine Shady Lewis
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
| | - Robi D Mitra
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
- McDonnell Genome Institute, Washington University School of Medicine in St. Louis, St. Louis, MO 63108, USA
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16
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Chen J, Fuhler NA, Noguchi KK, Dougherty JD. MYT1L is required for suppressing earlier neuronal development programs in the adult mouse brain. Genome Res 2023; 33:541-556. [PMID: 37100461 PMCID: PMC10234307 DOI: 10.1101/gr.277413.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 03/09/2023] [Indexed: 04/28/2023]
Abstract
In vitro studies indicate the neurodevelopmental disorder gene myelin transcription factor 1-like (MYT1L) suppresses non-neuronal lineage genes during fibroblast-to-neuron direct differentiation. However, MYT1L's molecular and cellular functions in the adult mammalian brain have not been fully characterized. Here, we found that MYT1L loss leads to up-regulated deep layer (DL) gene expression, corresponding to an increased ratio of DL/UL neurons in the adult mouse cortex. To define potential mechanisms, we conducted Cleavage Under Targets & Release Using Nuclease (CUT&RUN) to map MYT1L binding targets and epigenetic changes following MYT1L loss in mouse developing cortex and adult prefrontal cortex (PFC). We found MYT1L mainly binds to open chromatin, but with different transcription factor co-occupancies between promoters and enhancers. Likewise, multiomic data set integration revealed that, at promoters, MYT1L loss does not change chromatin accessibility but increases H3K4me3 and H3K27ac, activating both a subset of earlier neuronal development genes as well as Bcl11b, a key regulator for DL neuron development. Meanwhile, we discovered that MYT1L normally represses the activity of neurogenic enhancers associated with neuronal migration and neuronal projection development by closing chromatin structures and promoting removal of active histone marks. Further, we showed that MYT1L interacts with HDAC2 and transcriptional repressor SIN3B in vivo, providing potential mechanisms underlying repressive effects on histone acetylation and gene expression. Overall, our findings provide a comprehensive map of MYT1L binding in vivo and mechanistic insights into how MYT1L loss leads to aberrant activation of earlier neuronal development programs in the adult mouse brain.
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Affiliation(s)
- Jiayang Chen
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Nicole A Fuhler
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Kevin K Noguchi
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA;
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
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17
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Penkov D, Zubkova E, Parfyonova Y. Tn5 DNA Transposase in Multi-Omics Research. Methods Protoc 2023; 6:mps6020024. [PMID: 36961044 PMCID: PMC10037646 DOI: 10.3390/mps6020024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
Tn5 transposase use in biotechnology has substantially advanced the sequencing applications of genome-wide analysis of cells. This is mainly due to the ability of Tn5 transposase to efficiently transpose DNA essentially randomly into any target DNA without the aid of other factors. This concise review is focused on the advances in Tn5 applications in multi-omics technologies, genome-wide profiling, and Tn5 hybrid molecule creation. The possibilities of other transposase uses are also discussed.
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Affiliation(s)
- Dmitry Penkov
- IRCCS San Raffaele Hospital, 20132 Milan, Italy
- National Medical Research Centre of Cardiology Named after E. I. Chazov, 121552 Moscow, Russia
| | - Ekaterina Zubkova
- National Medical Research Centre of Cardiology Named after E. I. Chazov, 121552 Moscow, Russia
| | - Yelena Parfyonova
- National Medical Research Centre of Cardiology Named after E. I. Chazov, 121552 Moscow, Russia
- Faculty of Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia
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18
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A single-cell massively parallel reporter assay detects cell-type-specific gene regulation. Nat Genet 2023; 55:346-354. [PMID: 36635387 PMCID: PMC9931678 DOI: 10.1038/s41588-022-01278-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 12/05/2022] [Indexed: 01/14/2023]
Abstract
Massively parallel reporter gene assays are key tools in regulatory genomics but cannot be used to identify cell-type-specific regulatory elements without performing assays serially across different cell types. To address this problem, we developed a single-cell massively parallel reporter assay (scMPRA) to measure the activity of libraries of cis-regulatory sequences (CRSs) across multiple cell types simultaneously. We assayed a library of core promoters in a mixture of HEK293 and K562 cells and showed that scMPRA is a reproducible, highly parallel, single-cell reporter gene assay that detects cell-type-specific cis-regulatory activity. We then measured a library of promoter variants across multiple cell types in live mouse retinas and showed that subtle genetic variants can produce cell-type-specific effects on cis-regulatory activity. We anticipate that scMPRA will be widely applicable for studying the role of CRSs across diverse cell types.
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19
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Luo W, Hickman AB, Genzor P, Ghirlando R, Furman C, Menshikh A, Haase A, Dyda F, Wilson M. Transposase N-terminal phosphorylation and asymmetric transposon ends inhibit piggyBac transposition in mammalian cells. Nucleic Acids Res 2022; 50:13128-13142. [PMID: 36537219 PMCID: PMC9825180 DOI: 10.1093/nar/gkac1191] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 11/09/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
DNA transposon systems are widely used in mammalian cells for genetic modification experiments, but their regulation remains poorly understood. We used biochemical and cell-based assays together with AlphaFold modeling and rational protein redesign to evaluate aspects of piggyBac transposition including the previously unexplained role of the transposase N-terminus and the need for asymmetric transposon ends for cellular activity. We found that phosphorylation at predicted casein kinase II sites in the transposase N-terminus inhibits transposition, most likely by preventing transposase-DNA interactions. Deletion of the region containing these sites releases inhibition thereby enhancing activity. We also found that the N-terminal domain promotes transposase dimerization in the absence of transposon DNA. When the N-terminus is deleted, the transposase gains the ability to carry out transposition using symmetric transposon left ends. This novel activity is also conferred by appending a second C-terminal domain. When combined, these modifications together result in a transposase that is highly active when symmetric transposon ends are used. Our results demonstrate that transposase N-terminal phosphorylation and the requirement for asymmetric transposon ends both negatively regulate piggyBac transposition in mammalian cells. These novel insights into the mechanism and structure of the piggyBac transposase expand its potential use for genomic applications.
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Affiliation(s)
- Wentian Luo
- Department of Medicine, Division and Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Alison B Hickman
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Pavol Genzor
- Laboratory of Cellular and Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Rodolfo Ghirlando
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Christopher M Furman
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Anna Menshikh
- Department of Medicine, Division and Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Astrid Haase
- Laboratory of Cellular and Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Fred Dyda
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Matthew H Wilson
- Department of Medicine, Division and Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Veterans Affairs, Nashville, TN 37212, USA
- Departments of Pharmacology and Cell and Developmental Biology, Vanderbilt University, Nashville, TN 37232, USA
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20
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Luo T, Chen SY, Qiu ZX, Miao YR, Ding Y, Pan XY, Li Y, Lei Q, Guo AY. Transcriptomic Features in a Single Extracellular Vesicle via Single-Cell RNA Sequencing. SMALL METHODS 2022; 6:e2200881. [PMID: 36068167 DOI: 10.1002/smtd.202200881] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/18/2022] [Indexed: 06/15/2023]
Abstract
Although many studies have investigated functional molecules in extracellular vesicles (EVs), the exact number of ribonucleic acid molecules in a single-EV is unknown. Therefore, it is critical to explore the transcriptomic features and heterogeneity at the level of a single-EV. Here, using the 10x Genomics platform, the RNA cargos are profiled in single EVs derived from human K562 and mesenchymal stem cells. The key steps are labeling intact EVs using calcein-AM, detecting the EV concentration via flow cytometry, and using the CB2 algorithm with adaptive thresholds to effectively distinguish real EVs from background. The gene number in a single-EV varied from 6 to 148, with a mean of 52. Ribosomal genes, mitochondrial genes, and eukaryotic translation elongation factor 1 alpha has a high EV percentage in all EV samples. Hemoglobin genes are uniquely highly expressed in K562-EVs, and cytoskeleton genes are enriched in MSC-EVs. Ten or more clusters with different marker genes in each single-EV dataset demonstrated EV heterogeneity. Moreover, integrating EVs and their parental cells reveal both EVs and cells in each cluster, indicating different cell origins of various EVs. To the best of the author's knowledge, this study provides the first high-throughput transcriptome at the single-EV level and improves the understanding of EVs.
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Affiliation(s)
- Tao Luo
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- Center for Artificial Intelligence Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Si-Yi Chen
- Center for Artificial Intelligence Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | | | - Ya-Ru Miao
- Center for Artificial Intelligence Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Yue Ding
- Wuhan Biobank, Wuhan, 430000, China
| | | | - Yirong Li
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Qian Lei
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - An-Yuan Guo
- Center for Artificial Intelligence Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
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21
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Lalli M, Yen A, Thopte U, Dong F, Moudgil A, Chen X, Milbrandt J, Dougherty JD, Mitra RD. Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes. NAR Genom Bioinform 2022; 4:lqac061. [PMID: 36062164 PMCID: PMC9428926 DOI: 10.1093/nargab/lqac061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/04/2022] [Accepted: 08/24/2022] [Indexed: 11/29/2022] Open
Abstract
Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2 and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.
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Affiliation(s)
- Matthew Lalli
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Allen Yen
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Urvashi Thopte
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Fengping Dong
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Arnav Moudgil
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Xuhua Chen
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Jeffrey Milbrandt
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Joseph D Dougherty
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Robi D Mitra
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
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22
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Hajheidari M, Huang SSC. Elucidating the biology of transcription factor-DNA interaction for accurate identification of cis-regulatory elements. CURRENT OPINION IN PLANT BIOLOGY 2022; 68:102232. [PMID: 35679803 PMCID: PMC10103634 DOI: 10.1016/j.pbi.2022.102232] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 05/03/2023]
Abstract
Transcription factors (TFs) play a critical role in determining cell fate decisions by integrating developmental and environmental signals through binding to specific cis-regulatory modules and regulating spatio-temporal specificity of gene expression patterns. Precise identification of functional TF binding sites in time and space not only will revolutionize our understanding of regulatory networks governing cell fate decisions but is also instrumental to uncover how genetic variations cause morphological diversity or disease. In this review, we discuss recent advances in mapping TF binding sites and characterizing the various parameters underlying the complexity of binding site recognition by TFs.
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Affiliation(s)
- Mohsen Hajheidari
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA
| | - Shao-Shan Carol Huang
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA.
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23
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Chen J, Yen A, Florian CP, Dougherty JD. MYT1L in the making: emerging insights on functions of a neurodevelopmental disorder gene. Transl Psychiatry 2022; 12:292. [PMID: 35869058 PMCID: PMC9307810 DOI: 10.1038/s41398-022-02058-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 06/27/2022] [Accepted: 07/01/2022] [Indexed: 12/03/2022] Open
Abstract
Large scale human genetic studies have shown that loss of function (LoF) mutations in MYT1L are implicated in neurodevelopmental disorders (NDDs). Here, we provide an overview of the growing number of published MYT1L patient cases, and summarize prior studies in cells, zebrafish, and mice, both to understand MYT1L's molecular and cellular role during brain development and consider how its dysfunction can lead to NDDs. We integrate the conclusions from these studies and highlight conflicting findings to reassess the current model of the role of MYT1L as a transcriptional activator and/or repressor based on the biological context. Finally, we highlight additional functional studies that are needed to understand the molecular mechanisms underlying pathophysiology and propose key questions to guide future preclinical studies.
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Affiliation(s)
- Jiayang Chen
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Allen Yen
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Colin P Florian
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
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24
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Pan L, Ku WL, Tang Q, Cao Y, Zhao K. scPCOR-seq enables co-profiling of chromatin occupancy and RNAs in single cells. Commun Biol 2022; 5:678. [PMID: 35804086 PMCID: PMC9270334 DOI: 10.1038/s42003-022-03584-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/14/2022] [Indexed: 11/30/2022] Open
Abstract
Cell-to-cell variation in gene expression is a widespread phenomenon, which may play important roles in cellular differentiation, function, and disease development1–9. Chromatin is implicated in contributing to the cellular heterogeneity in gene expression10–16. Fully understanding the mechanisms of cellular heterogeneity requires simultaneous measurement of RNA and occupancy of histone modifications and transcription factors on chromatin due to their critical roles in transcriptional regulation17,18. We generally term the occupancy of histone modifications and transcription factors as Chromatin occupancy. Here, we report a technique, termed scPCOR-seq (single-cell Profiling of Chromatin Occupancy and RNAs Sequencing), for simultaneously profiling genome-wide chromatin protein binding or histone modification marks and RNA expression in the same cell. We demonstrated that scPCOR-seq can profile either H3K4me3 or RNAPII and RNAs in a mixture of human H1, GM12878 and 293 T cells at a single-cell resolution and either H3K4me3, RNAPII, or RNA profile can correctly separate the cells. Application of scPCOR-seq to the in vitro differentiation of the erythrocyte precursor CD36 cells from human CD34 stem or progenitor cells revealed that H3K4me3 and RNA exhibit distinct properties in clustering cells during differentiation. Overall, our work provides a promising approach to understand the relationships among different omics layers. scPCOR-seq is a single-cell sequencing technique that enables simultaneous profiling of genome-wide chromatin protein binding or histone modification marks and RNA expression in the same cell.
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Affiliation(s)
- Lixia Pan
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wai Lim Ku
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Qingsong Tang
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yaqiang Cao
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Keji Zhao
- Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
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25
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Külp M, Siemund AL, Larghero P, Dietz A, Alten J, Cario G, Eckert C, Caye-Eude A, Cavé H, Bardini M, Cazzaniga G, De Lorenzo P, Valsecchi MG, Diehl L, Bonig H, Meyer C, Marschalek R. The immune checkpoint ICOSLG is a relapse-predicting biomarker and therapeutic target in infant t(4;11) acute lymphoblastic leukemia. iScience 2022; 25:104613. [PMID: 35800767 PMCID: PMC9253708 DOI: 10.1016/j.isci.2022.104613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/14/2022] [Accepted: 06/01/2022] [Indexed: 11/23/2022] Open
Abstract
The most frequent genetic aberration leading to infant ALL (iALL) is the chromosomal translocation t(4;11), generating the fusion oncogenes KMT2A:AFF1 and AFF1:KMT2A, respectively. KMT2A-r iALL displays a dismal prognosis through high relapse rates and relapse-associated mortality. Relapse occurs frequently despite ongoing chemotherapy and without the accumulation of secondary mutations. A rational explanation for the observed chemo-resistance and satisfactory treatment options remain to be elucidated. We found that elevated ICOSLG expression level at diagnosis was associated with inferior event free survival (EFS) in a cohort of 43 patients with t(4;-11) iALL and that a cohort of 18 patients with iALL at relapse displayed strongly increased ICOSLG expression. Furthermore, co-culturing t(4;11) ALL cells (ICOSLGhi) with primary T-cells resulted in the development of Tregs. This was impaired through treatment with a neutralizing ICOSLG antibody. These findings imply ICOSLG (1) as a relapse-predicting biomarker, and (2) as a therapeutic target involved in a potential immune evasion relapse-mechanism of infant t(4;11) ALL. Early growth response 3 (EGR3) is a direct transactivator of the immune checkpoint gene ICOSLG high ICOSLG expression at diagnosis is predictive for ALL relapse EGR3 and ICOSLG expressions are relapse-associated expression of ICOSLG on t(4;11) ALL cells leads to the rapid expansion of Tregs
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26
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Metabolic and epigenetic dysfunctions underlie the arrest of in vitro fertilized human embryos in a senescent-like state. PLoS Biol 2022; 20:e3001682. [PMID: 35771762 PMCID: PMC9246109 DOI: 10.1371/journal.pbio.3001682] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/19/2022] [Indexed: 12/18/2022] Open
Abstract
Around 60% of in vitro fertilized (IVF) human embryos irreversibly arrest before compaction between the 3- to 8-cell stage, posing a significant clinical problem. The mechanisms behind this arrest are unclear. Here, we show that the arrested embryos enter a senescent-like state, marked by cell cycle arrest, the down-regulation of ribosomes and histones and down-regulation of MYC and p53 activity. The arrested embryos can be divided into 3 types. Type I embryos fail to complete the maternal-zygotic transition, and Type II/III embryos have low levels of glycolysis and either high (Type II) or low (Type III) levels of oxidative phosphorylation. Treatment with the SIRT agonist resveratrol or nicotinamide riboside (NR) can partially rescue the arrested phenotype, which is accompanied by changes in metabolic activity. Overall, our data suggests metabolic and epigenetic dysfunctions underlie the arrest of human embryos.
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27
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Gallagher LA, Velazquez E, Peterson SB, Charity JC, Radey MC, Gebhardt MJ, Hsu F, Shull LM, Cutler KJ, Macareno K, de Moraes MH, Penewit KM, Kim J, Andrade PA, LaFramboise T, Salipante SJ, Reniere ML, de Lorenzo V, Wiggins PA, Dove SL, Mougous JD. Genome-wide protein-DNA interaction site mapping in bacteria using a double-stranded DNA-specific cytosine deaminase. Nat Microbiol 2022; 7:844-855. [PMID: 35650286 PMCID: PMC9159945 DOI: 10.1038/s41564-022-01133-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 04/25/2022] [Indexed: 12/20/2022]
Abstract
DNA-protein interactions are central to fundamental cellular processes, yet widely implemented technologies for measuring these interactions on a genome scale in bacteria are laborious and capture only a snapshot of binding events. We devised a facile method for mapping DNA-protein interaction sites in vivo using the double-stranded DNA-specific cytosine deaminase toxin DddA. In 3D-seq (DddA-sequencing), strains containing DddA fused to a DNA-binding protein of interest accumulate characteristic mutations in DNA sequence adjacent to sites occupied by the DNA-bound fusion protein. High-depth sequencing enables detection of sites of increased mutation frequency in these strains, yielding genome-wide maps of DNA-protein interaction sites. We validated 3D-seq for four transcription regulators in two bacterial species, Pseudomonas aeruginosa and Escherichia coli. We show that 3D-seq offers ease of implementation, the ability to record binding event signatures over time and the capacity for single-cell resolution.
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Affiliation(s)
- Larry A Gallagher
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Elena Velazquez
- Department of Microbiology, University of Washington, Seattle, WA, USA
- Systems Biology Department, National Center of Biotechnology CSIC, Madrid, Spain
| | - S Brook Peterson
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - James C Charity
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matthew C Radey
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Michael J Gebhardt
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - FoSheng Hsu
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Lauren M Shull
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Kevin J Cutler
- Department of Physics, University of Washington, Seattle, WA, USA
| | - Keven Macareno
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Kelsi M Penewit
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Jennifer Kim
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Pia A Andrade
- Department of Microbiology, University of Washington, Seattle, WA, USA
| | - Thomas LaFramboise
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Stephen J Salipante
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Victor de Lorenzo
- Systems Biology Department, National Center of Biotechnology CSIC, Madrid, Spain
| | - Paul A Wiggins
- Department of Microbiology, University of Washington, Seattle, WA, USA
- Department of Physics, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Simon L Dove
- Division of Infectious Diseases, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Joseph D Mougous
- Department of Microbiology, University of Washington, Seattle, WA, USA.
- Department of Biochemistry, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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28
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Dimitriu MA, Lazar-Contes I, Roszkowski M, Mansuy IM. Single-Cell Multiomics Techniques: From Conception to Applications. Front Cell Dev Biol 2022; 10:854317. [PMID: 35386194 PMCID: PMC8979110 DOI: 10.3389/fcell.2022.854317] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 02/14/2022] [Indexed: 01/16/2023] Open
Abstract
Recent advances in methods for single-cell analyses and barcoding strategies have led to considerable progress in research. The development of multiplexed assays offers the possibility to conduct parallel analyses of multiple factors and processes for comprehensive characterization of cellular and molecular states in health and disease. These technologies have expanded extremely rapidly in the past years and constantly evolve and provide better specificity, precision and resolution. This review summarizes recent progress in single-cell multiomics approaches, and focuses, in particular, on the most innovative techniques that integrate genome, epigenome and transcriptome profiling. It describes the methodologies, discusses their advantages and limitations, and explains how they have been applied to studies on cell heterogeneity and differentiation, and epigenetic reprogramming.
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Affiliation(s)
| | | | | | - Isabelle M. Mansuy
- Laboratory of Neuroepigenetics, Brain Research Institute, University of Zurich and Institute for Neuroscience, ETH Zurich, Zurich, Switzerland
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29
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Ribeiro-Dos-Santos AM, Hogan MS, Luther RD, Brosh R, Maurano MT. Genomic context sensitivity of insulator function. Genome Res 2022; 32:425-436. [PMID: 35082140 PMCID: PMC8896466 DOI: 10.1101/gr.276449.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/25/2022] [Indexed: 11/24/2022]
Abstract
The specificity of interactions between genomic regulatory elements and potential target genes is influenced by the binding of insulator proteins such as CTCF, which can act as potent enhancer blockers when interposed between an enhancer and a promoter in a reporter assay. But not all CTCF sites genome-wide function as insulator elements, depending on cellular and genomic context. To dissect the influence of genomic context on enhancer blocker activity, we integrated reporter constructs with promoter-only, promoter and enhancer, and enhancer blocker configurations at hundreds of thousands of genomic sites using the Sleeping Beauty transposase. Deconvolution of reporter activity by genomic position reveals distinct expression patterns subject to genomic context, including a compartment of enhancer blocker reporter integrations with robust expression. The high density of integration sites permits quantitative delineation of characteristic genomic context sensitivity profiles and their decomposition into sensitivity to both local and distant DNase I hypersensitive sites. Furthermore, using a single-cell expression approach to test the effect of integrated reporters for differential expression of nearby endogenous genes reveals that CTCF insulator elements do not completely abrogate reporter effects on endogenous gene expression. Collectively, our results lend new insight into genomic regulatory compartmentalization and its influence on the determinants of promoter–enhancer specificity.
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Affiliation(s)
| | - Megan S Hogan
- Institute for Systems Genetics, NYU Grossman School of Medicine
| | - Raven D Luther
- Institute for Systems Genetics, NYU Grossman School of Medicine
| | - Ran Brosh
- Institute for Systems Genetics, NYU Grossman School of Medicine
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30
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Li G, Fu S, Wang S, Zhu C, Duan B, Tang C, Chen X, Chuai G, Wang P, Liu Q. A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data. Genome Biol 2022; 23:20. [PMID: 35022082 PMCID: PMC8756637 DOI: 10.1186/s13059-021-02595-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 12/29/2021] [Indexed: 11/10/2022] Open
Abstract
Here, we present a multi-modal deep generative model, the single-cell Multi-View Profiler (scMVP), which is designed for handling sequencing data that simultaneously measure gene expression and chromatin accessibility in the same cell, including SNARE-seq, sci-CAR, Paired-seq, SHARE-seq, and Multiome from 10X Genomics. scMVP generates common latent representations for dimensionality reduction, cell clustering, and developmental trajectory inference and generates separate imputations for differential analysis and cis-regulatory element identification. scMVP can help mitigate data sparsity issues with imputation and accurately identify cell groups for different joint profiling techniques with common latent embedding, and we demonstrate its advantages on several realistic datasets.
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Affiliation(s)
- Gaoyang Li
- Tongji University Cancer Center, Shanghai Tenth People's Hospital of Tongji University, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Shuguang Wang
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Chenyu Zhu
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Bin Duan
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Chen Tang
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Xiaohan Chen
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Guohui Chuai
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China
| | - Ping Wang
- Tongji University Cancer Center, Shanghai Tenth People's Hospital of Tongji University, Tongji University, Shanghai, 200092, China.
| | - Qi Liu
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China.
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31
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Hong CKY, Cohen BA. Genomic environments scale the activities of diverse core promoters. Genome Res 2022; 32:85-96. [PMID: 34961747 PMCID: PMC8744677 DOI: 10.1101/gr.276025.121] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 11/15/2021] [Indexed: 11/24/2022]
Abstract
A classical model of gene regulation is that enhancers provide specificity whereas core promoters provide a modular site for the assembly of the basal transcriptional machinery. However, examples of core promoter specificity have led to an alternate hypothesis in which specificity is achieved by core promoters with different sequence motifs that respond differently to genomic environments containing different enhancers and chromatin landscapes. To distinguish between these models, we measured the activities of hundreds of diverse core promoters in four different genomic locations and, in a complementary experiment, six different core promoters at thousands of locations across the genome. Although genomic locations had large effects on expression, the intrinsic activities of different classes of promoters were preserved across genomic locations, suggesting that core promoters are modular regulatory elements whose activities are independently scaled up or down by different genomic locations. This scaling of promoter activities is nonlinear and depends on the genomic location and the strength of the core promoter. Our results support the classical model of regulation in which diverse core promoter motifs set the intrinsic strengths of core promoters, which are then amplified or dampened by the activities of their genomic environments.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri 63110, USA
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32
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Wade AA, van den Ameele J, Cheetham SW, Yakob R, Brand AH, Nord AS. In vivo targeted DamID identifies CHD8 genomic targets in fetal mouse brain. iScience 2021; 24:103234. [PMID: 34746699 PMCID: PMC8551073 DOI: 10.1016/j.isci.2021.103234] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 08/11/2021] [Accepted: 10/04/2021] [Indexed: 01/15/2023] Open
Abstract
Genetic studies of autism have revealed causal roles for chromatin remodeling gene mutations. Chromodomain helicase DNA binding protein 8 (CHD8) encodes a chromatin remodeler with significant de novo mutation rates in sporadic autism. However, relationships between CHD8 genomic function and autism-relevant biology remain poorly elucidated. Published studies utilizing ChIP-seq to map CHD8 protein-DNA interactions have high variability, consistent with technical challenges and limitations associated with this method. Thus, complementary approaches are needed to establish CHD8 genomic targets and regulatory functions in developing brain. We used in utero CHD8 Targeted DamID followed by sequencing (TaDa-seq) to characterize CHD8 binding in embryonic mouse cortex. CHD8 TaDa-seq reproduced interaction patterns observed from ChIP-seq and further highlighted CHD8 distal interactions associated with neuronal loci. This study establishes TaDa-seq as a useful alternative for mapping protein-DNA interactions in vivo and provides insights into the regulatory targets of CHD8 and autism-relevant pathophysiology associated with CHD8 mutations.
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Affiliation(s)
- A. Ayanna Wade
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95616, USA
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA 95616, USA
| | - Jelle van den Ameele
- The Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 1TN, UK
| | - Seth W. Cheetham
- The Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 1TN, UK
| | - Rebecca Yakob
- The Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 1TN, UK
| | - Andrea H. Brand
- The Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 1TN, UK
| | - Alex S. Nord
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95616, USA
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA 95616, USA
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33
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Salnikov PA, Khabarova AA, Koksharova GS, Mungalov RV, Belokopytova PS, Pristyazhnuk IE, Nurislamov AR, Somatich P, Gridina MM, Fishman VS. Here and there: the double-side transgene localization. Vavilovskii Zhurnal Genet Selektsii 2021; 25:607-612. [PMID: 34755021 PMCID: PMC8553977 DOI: 10.18699/vj21.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/22/2021] [Accepted: 07/01/2021] [Indexed: 11/19/2022] Open
Abstract
Random transgene integration is a powerful tool for developing new genome-wide screening approaches. These techniques have already been used for functional gene annotation by transposon-insertion sequencing, for identif ication of transcription factor binding sites and regulatory sequences, and for dissecting chromatin position effects. Precise localization of transgenes and accurate artifact f iltration are essential for this type of method. To date, many mapping assays have been developed, including Inverse-PCR, TLA, LAM-PCR, and splinkerette PCR. However, none of them is able to ensure localization of both transgene’s f lanking regions simultaneously, which would be necessary for some applications. Here we proposed a cheap and simple NGS-based approach that overcomes this limitation. The developed assay requires using intentionally designed vectors that lack recognition sites of one or a set of restriction enzymes used for DNA fragmentation. By looping and sequencing these DNA fragments, we obtain special data that allows us to link the two f lanking regions of the transposon. This can be useful for precise insertion mapping and for screening approaches in the f ield of chromosome engineering, where chromosomal recombination events between transgenes occur in a cell population. To demonstrate the method’s feasibility, we applied it for mapping SB transposon integration in the human HAP1 cell line. Our technique allowed us to eff iciently localize genomic transposon integrations, which was conf irmed via PCR analysis. For practical application of this approach, we proposed a set of recommendations and a normalization strategy. The developed method can be used for multiplex transgene localization and detection of rearrangements between them.
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Affiliation(s)
- P A Salnikov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A A Khabarova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - G S Koksharova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - R V Mungalov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - P S Belokopytova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - I E Pristyazhnuk
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A R Nurislamov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - P Somatich
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - M M Gridina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - V S Fishman
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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34
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Shiau F, Ruzycki PA, Clark BS. A single-cell guide to retinal development: Cell fate decisions of multipotent retinal progenitors in scRNA-seq. Dev Biol 2021; 478:41-58. [PMID: 34146533 PMCID: PMC8386138 DOI: 10.1016/j.ydbio.2021.06.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 12/20/2022]
Abstract
Recent advances in high throughput single-cell RNA sequencing (scRNA-seq) technology have enabled the simultaneous transcriptomic profiling of thousands of individual cells in a single experiment. To investigate the intrinsic process of retinal development, researchers have leveraged this technology to quantify gene expression in retinal cells across development, in multiple species, and from numerous important models of human disease. In this review, we summarize recent applications of scRNA-seq and discuss how these datasets have complemented and advanced our understanding of retinal progenitor cell competence, cell fate specification, and differentiation. Finally, we also highlight the outstanding questions in the field that advances in single-cell data generation and analysis will soon be able to answer.
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Affiliation(s)
- Fion Shiau
- John F Hardesty, MD Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A Ruzycki
- John F Hardesty, MD Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian S Clark
- John F Hardesty, MD Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA; Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.
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35
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Zhang M, Huang L, Yang J, Xu W, Su H, Cao J, Wang Q, Pu J, Qian K. Ultra-Fast Label-Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101333. [PMID: 34323397 PMCID: PMC8456274 DOI: 10.1002/advs.202101333] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/19/2021] [Indexed: 05/07/2023]
Abstract
Although mass spectrometry (MS) of metabolites has the potential to provide real-time monitoring of patient status for diagnostic purposes, the diagnostic application of MS is limited due to sample treatment and data quality/reproducibility. Here, the generation of a deep stabilizer for ultra-fast, label-free MS detection and the application of this method for serum metabolic diagnosis of coronary heart disease (CHD) are reported. Nanoparticle-assisted laser desorption/ionization-MS is used to achieve direct metabolic analysis of trace unprocessed serum in seconds. Furthermore, a deep stabilizer is constructed to map native MS results to high-quality results obtained by established methods. Finally, using the newly developed protocol and diagnosis variation characteristic surface to characterize sensitivity/specificity and variation, CHD is diagnosed with advanced accuracy in a high-throughput/speed manner. This work advances design of metabolic analysis tools for disease detection as it provides a direct label-free, ultra-fast, and stabilized platform for future protocol development in clinics.
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Affiliation(s)
- Mengji Zhang
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Lin Huang
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Jing Yang
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Wei Xu
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Haiyang Su
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Jing Cao
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Qian Wang
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Jun Pu
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
| | - Kun Qian
- State Key Laboratory for Oncogenes and Related GenesSchool of Biomedical EngineeringInstitute of Medical Robotics and Med‐X Research InstituteShanghai Jiao Tong UniversityShanghai200030P. R. China
- State Key Laboratory for Oncogenes and Related GenesDivision of CardiologyRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai Cancer Institute160 Pujian RoadShanghai200127P. R. China
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36
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Moudgil A, Li D, Hsu S, Purushotham D, Wang T, Mitra RD. The qBED track: a novel genome browser visualization for point processes. Bioinformatics 2021; 37:1168-1170. [PMID: 32941613 DOI: 10.1093/bioinformatics/btaa771] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/10/2020] [Accepted: 09/15/2020] [Indexed: 01/25/2023] Open
Abstract
SUMMARY Transposon calling cards is a genomic assay for identifying transcription factor binding sites in both bulk and single cell experiments. Here, we describe the qBED format, an open, text-based standard for encoding and analyzing calling card data. In parallel, we introduce the qBED track on the WashU Epigenome Browser, a novel visualization that enables researchers to inspect calling card data in their genomic context. Finally, through examples, we demonstrate that qBED files can be used to visualize non-calling card datasets, such as Combined Annotation-Dependent Depletion scores and GWAS/eQTL hits, and thus may have broad utility to the genomics community. AVAILABILITY AND IMPLEMENTATION The qBED track is available on the WashU Epigenome Browser (http://epigenomegateway.wustl.edu/browser), beginning with version 46. Source code for the WashU Epigenome Browser with qBED support is available on GitHub (http://github.com/arnavm/eg-react and http://github.com/lidaof/eg-react). A complete definition of the qBED format is available as part of the WashU Epigenome Browser documentation (https://eg.readthedocs.io/en/latest/tracks.html#qbed-track). We have also released a tutorial on how to upload qBED data to the browser (http://dx.doi.org/10.17504/protocols.io.bca8ishw).
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Affiliation(s)
- Arnav Moudgil
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA.,Medical Scientist Training Program, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA
| | - Daofeng Li
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Silas Hsu
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Deepak Purushotham
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Ting Wang
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Robi D Mitra
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
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37
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Xiong H, Luo Y, Wang Q, Yu X, He A. Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions. Nat Methods 2021; 18:652-660. [PMID: 33958790 DOI: 10.1038/s41592-021-01129-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/29/2021] [Indexed: 02/02/2023]
Abstract
Deciphering mechanisms in cell-fate decisions requires single-cell holistic reconstructions of multidimensional epigenomic states in transcriptional regulation. Here we develop CoTECH, a combinatorial barcoding method allowing high-throughput single-cell joint detection of chromatin occupancy and transcriptome. We used CoTECH to examine bivalent histone marks (H3K4me3 and H3K27me3) with transcription from naive to primed mouse embryonic stem cells. We also derived concurrent bivalent marks in pseudosingle cells using transcriptome as an anchor for resolving pseudotemporal bivalency trajectories and disentangling a context-specific interplay between H3K4me3/H3K27me3 and transcription level. Next, we revealed the regulatory basis of endothelial-to-hematopoietic transition in two waves of hematopoietic cells and distinctive enhancer-gene-linking schemes guiding hemogenic endothelial cell emergence, indicating a unique epigenetic control of transcriptional regulation for hematopoietic stem cell priming. CoTECH provides an efficient framework for single-cell coassay of chromatin occupancy and transcription, thus enabling higher-dimensional epigenomic reconstructions.
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Affiliation(s)
- Haiqing Xiong
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yingjie Luo
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Qianhao Wang
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xianhong Yu
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Aibin He
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
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Li H, Humphreys BD. Single Cell Technologies: Beyond Microfluidics. KIDNEY360 2021; 2:1196-1204. [PMID: 35368355 PMCID: PMC8786099 DOI: 10.34067/kid.0001822021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 05/13/2021] [Indexed: 02/04/2023]
Abstract
Single-cell RNA-sequencing (scRNA-seq) has been widely adopted in recent years due to standardized protocols and automation, reliability, and standardized bioinformatic pipelines. The most widely adopted platform is the 10× Genomics solution. Although powerful, this system is limited by its high cost, moderate throughput, and the inability to customize due to fixed kit components. This study will cover new approaches that do not rely on microfluidics and thus have low entry costs, are highly customizable, and are within the reach of any laboratory possessing molecular biology expertise.
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Affiliation(s)
| | - Benjamin D. Humphreys
- Division of Nephrology, Washington University in St. Louis School of Medicine, St. Louis, Missouri,Department of Developmental Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
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Yuan X, Scott IC, Wilson MD. Heart Enhancers: Development and Disease Control at a Distance. Front Genet 2021; 12:642975. [PMID: 33777110 PMCID: PMC7987942 DOI: 10.3389/fgene.2021.642975] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 01/29/2021] [Indexed: 12/14/2022] Open
Abstract
Bound by lineage-determining transcription factors and signaling effectors, enhancers play essential roles in controlling spatiotemporal gene expression profiles during development, homeostasis and disease. Recent synergistic advances in functional genomic technologies, combined with the developmental biology toolbox, have resulted in unprecedented genome-wide annotation of heart enhancers and their target genes. Starting with early studies of vertebrate heart enhancers and ending with state-of-the-art genome-wide enhancer discovery and testing, we will review how studying heart enhancers in metazoan species has helped inform our understanding of cardiac development and disease.
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Affiliation(s)
- Xuefei Yuan
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Ian C. Scott
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Michael D. Wilson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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Abstract
Therapeutic resistance continues to be an indominable foe in our ambition for curative cancer treatment. Recent insights into the molecular determinants of acquired treatment resistance in the clinical and experimental setting have challenged the widely held view of sequential genetic evolution as the primary cause of resistance and brought into sharp focus a range of non-genetic adaptive mechanisms. Notably, the genetic landscape of the tumour and the non-genetic mechanisms used to escape therapy are frequently linked. Remarkably, whereas some oncogenic mutations allow the cancer cells to rapidly adapt their transcriptional and/or metabolic programme to meet and survive the therapeutic pressure, other oncogenic drivers convey an inherent cellular plasticity to the cancer cell enabling lineage switching and/or the evasion of anticancer immunosurveillance. The prevalence and diverse array of non-genetic resistance mechanisms pose a new challenge to the field that requires innovative strategies to monitor and counteract these adaptive processes. In this Perspective we discuss the key principles of non-genetic therapy resistance in cancer. We provide a perspective on the emerging data from clinical studies and sophisticated cancer models that have studied various non-genetic resistance pathways and highlight promising therapeutic avenues that may be used to negate and/or counteract the non-genetic adaptive pathways.
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Affiliation(s)
- Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, VIB Center for Cancer Biology, KU Leuven, Leuven, Belgium.
- Department of Oncology, KU Leuven, Leuven, Belgium.
| | - Sarah-Jane Dawson
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia.
- Center for Cancer Research, The University of Melbourne, Melbourne, VIC, Australia.
| | - Mark A Dawson
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia.
- Center for Cancer Research, The University of Melbourne, Melbourne, VIC, Australia.
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Carrelha J, Lin DS, Rodriguez-Fraticelli AE, Luis TC, Wilkinson AC, Cabezas-Wallscheid N, Tremblay CS, Haas S. Single-cell lineage tracing approaches in hematology research: technical considerations. Exp Hematol 2020; 89:26-36. [PMID: 32735908 PMCID: PMC7894992 DOI: 10.1016/j.exphem.2020.07.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/21/2020] [Accepted: 07/24/2020] [Indexed: 01/27/2023]
Abstract
The coordinated differentiation of hematopoietic stem and progenitor cells (HSPCs) into the various mature blood cell types is responsible for sustaining blood and immune system homeostasis. The cell fate decisions underlying this important biological process are made at the level of single cells. Methods to trace the fate of single cells are therefore essential for understanding hematopoietic system activity in health and disease and have had a major impact on how we understand and represent hematopoiesis. Here, we discuss the basic methodologies and technical considerations for three important clonal assays: single-cell transplantation, lentiviral barcoding, and Sleeping Beauty barcoding. This perspective is a synthesis of presentations and discussions from the 2019 International Society for Experimental Hematology (ISEH) Annual Meeting New Investigator Technology Session and the 2019 ISEH Winter Webinar.
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Affiliation(s)
- Joana Carrelha
- Haematopoietic Stem Cell Laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Dawn S Lin
- Immunology, The Walter & Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia; Faculty of Medicine, Dentistry & Health Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Alejo E Rodriguez-Fraticelli
- Stem Cell Program, Boston Children's Hospital, Boston, Massachusetts, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Tiago C Luis
- Department of Life Sciences, Imperial College London, London, UK
| | - Adam C Wilkinson
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Cedric S Tremblay
- Australian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, Australia
| | - Simon Haas
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany.
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