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Pal S, Dhar R. Living in a noisy world-origins of gene expression noise and its impact on cellular decision-making. FEBS Lett 2024; 598:1673-1691. [PMID: 38724715 DOI: 10.1002/1873-3468.14898] [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: 12/21/2023] [Revised: 03/23/2024] [Accepted: 03/27/2024] [Indexed: 07/23/2024]
Abstract
The expression level of a gene can vary between genetically identical cells under the same environmental condition-a phenomenon referred to as gene expression noise. Several studies have now elucidated a central role of transcription factors in the generation of expression noise. Transcription factors, as the key components of gene regulatory networks, drive many important cellular decisions in response to cellular and environmental signals. Therefore, a very relevant question is how expression noise impacts gene regulation and influences cellular decision-making. In this Review, we summarize the current understanding of the molecular origins of expression noise, highlighting the role of transcription factors in this process, and discuss the ways in which noise can influence cellular decision-making. As advances in single-cell technologies open new avenues for studying expression noise as well as gene regulatory circuits, a better understanding of the influence of noise on cellular decisions will have important implications for many biological processes.
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Affiliation(s)
- Sampriti Pal
- Department of Bioscience and Biotechnology, IIT Kharagpur, India
| | - Riddhiman Dhar
- Department of Bioscience and Biotechnology, IIT Kharagpur, India
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2
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Sood V, Holewinski R, Andresson T, Larson DR, Misteli T. Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.08.597999. [PMID: 38903099 PMCID: PMC11188098 DOI: 10.1101/2024.06.08.597999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms for gene-specific stochastic bursting are largely unknown. We have developed and applied a high-throughput-imaging based screening strategy to identify cellular factors and molecular mechanisms that determine the bursting behavior of human genes. Focusing on epigenetic regulators, we find that protein acetylation is a strong acute modulator of burst frequency, burst size and heterogeneity of bursting. Acetylation globally affects the Off-time of genes but has gene-specific effects on the On-time. Yet, these effects are not strongly linked to promoter acetylation, which do not correlate with bursting properties, and forced promoter acetylation has variable effects on bursting. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting. Specifically, we find that elevated Integrator acetylation decreases bursting frequency. Taken together our results suggest a prominent role of non-histone proteins in determining gene bursting properties, and they identify histone-independent acetylation of a transcription cofactor as an allosteric modulator of bursting via a far-downstream bursting checkpoint.
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Affiliation(s)
- Varun Sood
- National Cancer Institute, Bethesda, MD, USA
| | - Ronald Holewinski
- Protein Characterization Laboratory, National Cancer Institute, Frederick, MD, USA
| | - Thorkell Andresson
- Protein Characterization Laboratory, National Cancer Institute, Frederick, MD, USA
| | | | - Tom Misteli
- National Cancer Institute, Bethesda, MD, USA
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3
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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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Breimann L, Bahry E, Zouinkhi M, Kolyvanov K, Street LA, Preibisch S, Ercan S. Analysis of developmental gene expression using smFISH and in silico staging of C. elegans embryos. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.15.594414. [PMID: 38798598 PMCID: PMC11118362 DOI: 10.1101/2024.05.15.594414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Regulation of transcription during embryogenesis is key to development and differentiation. To study transcript expression throughout Caenorhabditis elegans embryogenesis at single-molecule resolution, we developed a high-throughput single-molecule fluorescence in situ hybridization (smFISH) method that relies on computational methods to developmentally stage embryos and quantify individual mRNA molecules in single embryos. We applied our system to sdc-2, a zygotically transcribed gene essential for hermaphrodite development and dosage compensation. We found that sdc-2 is rapidly activated during early embryogenesis by increasing both the number of mRNAs produced per transcription site and the frequency of sites engaged in transcription. Knockdown of sdc-2 and dpy-27, a subunit of the dosage compensation complex (DCC), increased the number of active transcription sites for the X chromosomal gene dpy-23 but not the autosomal gene mdh-1, suggesting that the DCC reduces the frequency of dpy-23 transcription. The temporal resolution from in silico staging of embryos showed that the deletion of a single DCC recruitment element near the dpy-23 gene causes higher dpy-23 mRNA expression after the start of dosage compensation, which could not be resolved using mRNAseq from mixed-stage embryos. In summary, we have established a computational approach to quantify temporal regulation of transcription throughout C. elegans embryogenesis and demonstrated its potential to provide new insights into developmental gene regulation.
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Affiliation(s)
- Laura Breimann
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Ella Bahry
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
- Helmholtz Imaging, Max-Delbrück-Center for Molecular Medicine (MDC), Berlin, Germany
| | - Marwan Zouinkhi
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Klim Kolyvanov
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Lena Annika Street
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Sevinç Ercan
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
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5
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Ginley-Hidinger M, Abewe H, Osborne K, Richey A, Kitchen N, Mortenson KL, Wissink EM, Lis J, Zhang X, Gertz J. Cis-regulatory control of transcriptional timing and noise in response to estrogen. CELL GENOMICS 2024; 4:100542. [PMID: 38663407 PMCID: PMC11099348 DOI: 10.1016/j.xgen.2024.100542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 10/26/2023] [Accepted: 03/27/2024] [Indexed: 05/07/2024]
Abstract
Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.
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Affiliation(s)
- Matthew Ginley-Hidinger
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Hosiana Abewe
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Kyle Osborne
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Alexandra Richey
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Noel Kitchen
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Katelyn L Mortenson
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Erin M Wissink
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - John Lis
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Xiaoyang Zhang
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Jason Gertz
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA.
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6
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Ginley-Hidinger M, Abewe H, Osborne K, Richey A, Kitchen N, Mortenson KL, Wissink EM, Lis J, Zhang X, Gertz J. Cis-regulatory control of transcriptional timing and noise in response to estrogen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.14.532457. [PMID: 36993565 PMCID: PMC10054948 DOI: 10.1101/2023.03.14.532457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We find that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.
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Affiliation(s)
- Matthew Ginley-Hidinger
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Hosiana Abewe
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Kyle Osborne
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Alexandra Richey
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Noel Kitchen
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Katelyn L. Mortenson
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Erin M. Wissink
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - John Lis
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Xiaoyang Zhang
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Jason Gertz
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
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7
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Edwards DM, Davies P, Hebenstreit D. Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting. Genome Biol 2023; 24:138. [PMID: 37328900 PMCID: PMC10276402 DOI: 10.1186/s13059-023-02977-y] [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: 09/06/2022] [Accepted: 05/25/2023] [Indexed: 06/18/2023] Open
Abstract
Despite the recent rise of RNA-seq datasets combining single-cell (sc) resolution with 4-thiouridine (4sU) labelling, analytical methods exploiting their power to dissect transcriptional bursting are lacking. Here, we present a mathematical model and Bayesian inference implementation to facilitate genome-wide joint parameter estimation and confidence quantification (R package: burstMCMC). We demonstrate that, unlike conventional scRNA-seq, 4sU scRNA-seq resolves temporal parameters and furthermore boosts inference of dimensionless parameters via a synergy between single-cell resolution and 4sU labelling. We apply our method to published 4sU scRNA-seq data and linked with ChIP-seq data, we uncover previously obscured associations between different parameters and histone modifications.
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Affiliation(s)
| | - Philip Davies
- School of Life Sciences, University of Warwick, Coventry, UK
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8
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Luo S, Wang Z, Zhang Z, Zhou T, Zhang J. Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics. Nucleic Acids Res 2022; 51:68-83. [PMID: 36583343 PMCID: PMC9874261 DOI: 10.1093/nar/gkac1204] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/06/2022] [Accepted: 12/06/2022] [Indexed: 12/31/2022] Open
Abstract
Gene expression in mammalian cells is highly variable and episodic, resulting in a series of discontinuous bursts of mRNAs. A challenge is to understand how static promoter architecture and dynamic feedback regulations dictate bursting on a genome-wide scale. Although single-cell RNA sequencing (scRNA-seq) provides an opportunity to address this challenge, effective analytical methods are scarce. We developed an interpretable and scalable inference framework, which combined experimental data with a mechanistic model to infer transcriptional burst kinetics (sizes and frequencies) and feedback regulations. Applying this framework to scRNA-seq data generated from embryonic mouse fibroblast cells, we found Simpson's paradoxes, i.e. genome-wide burst kinetics exhibit different characteristics in two cases without and with distinguishing feedback regulations. We also showed that feedbacks differently modulate burst frequencies and sizes and conceal the effects of transcription start site distributions on burst kinetics. Notably, only in the presence of positive feedback, TATA genes are expressed with high burst frequencies and enhancer-promoter interactions mainly modulate burst frequencies. The developed inference method provided a flexible and efficient way to investigate transcriptional burst kinetics and the obtained results would be helpful for understanding cell development and fate decision.
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Affiliation(s)
| | | | - Zhenquan Zhang
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, 510275, P. R. China,School of Mathematics, Sun Yat-sen University, Guangzhou, Guangdong Province, 510275, P. R. China
| | - Tianshou Zhou
- Correspondence may also be addressed to Tianshou Zhou. Tel: +86 20 84134958;
| | - Jiajun Zhang
- To whom correspondence should be addressed. Tel: +86 20 84111829;
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9
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Parab L, Pal S, Dhar R. Transcription factor binding process is the primary driver of noise in gene expression. PLoS Genet 2022; 18:e1010535. [PMID: 36508455 PMCID: PMC9779669 DOI: 10.1371/journal.pgen.1010535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 12/22/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022] Open
Abstract
Noise in expression of individual genes gives rise to variations in activity of cellular pathways and generates heterogeneity in cellular phenotypes. Phenotypic heterogeneity has important implications for antibiotic persistence, mutation penetrance, cancer growth and therapy resistance. Specific molecular features such as the presence of the TATA box sequence and the promoter nucleosome occupancy have been associated with noise. However, the relative importance of these features in noise regulation is unclear and how well these features can predict noise has not yet been assessed. Here through an integrated statistical model of gene expression noise in yeast we found that the number of regulating transcription factors (TFs) of a gene was a key predictor of noise, whereas presence of the TATA box and the promoter nucleosome occupancy had poor predictive power. With an increase in the number of regulatory TFs, there was a rise in the number of cooperatively binding TFs. In addition, an increased number of regulatory TFs meant more overlaps in TF binding sites, resulting in competition between TFs for binding to the same region of the promoter. Through modeling of TF binding to promoter and application of stochastic simulations, we demonstrated that competition and cooperation among TFs could increase noise. Thus, our work uncovers a process of noise regulation that arises out of the dynamics of gene regulation and is not dependent on any specific transcription factor or specific promoter sequence.
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Affiliation(s)
- Lavisha Parab
- Department of Biotechnology, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, West Bengal, India
- Max-Planck-Institute for Evolutionary Biology, Plön, Germany
| | - Sampriti Pal
- Department of Biotechnology, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, West Bengal, India
| | - Riddhiman Dhar
- Department of Biotechnology, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, West Bengal, India
- * E-mail:
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10
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Li K, Kong J, Zhang S, Zhao T, Qian W. Distance-dependent inhibition of translation initiation by downstream out-of-frame AUGs is consistent with a Brownian ratchet process of ribosome scanning. Genome Biol 2022; 23:254. [PMID: 36510274 PMCID: PMC9743702 DOI: 10.1186/s13059-022-02829-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 12/01/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Eukaryotic ribosomes are widely presumed to scan mRNA for the AUG codon to initiate translation in a strictly 5'-3' movement (i.e., strictly unidirectional scanning model), so that ribosomes initiate translation exclusively at the 5' proximal AUG codon (i.e., the first-AUG rule). RESULTS We generate 13,437 yeast variants, each with an ATG triplet placed downstream (dATGs) of the annotated ATG (aATG) codon of a green fluorescent protein. We find that out-of-frame dATGs can inhibit translation at the aATG, but with diminishing strength over increasing distance between aATG and dATG, undetectable beyond ~17 nt. This phenomenon is best explained by a Brownian ratchet mechanism of ribosome scanning, in which the ribosome uses small-amplitude 5'-3' and 3'-5' oscillations with a net 5'-3' movement to scan the AUG codon, thereby leading to competition for translation initiation between aAUG and a proximal dAUG. This scanning model further predicts that the inhibitory effect induced by an out-of-frame upstream AUG triplet (uAUG) will diminish as uAUG approaches aAUG, which is indeed observed among the 15,586 uATG variants generated in this study. Computational simulations suggest that each triplet is scanned back and forth approximately ten times until the ribosome eventually migrates to downstream regions. Moreover, this scanning process could constrain the evolution of sequences downstream of the aATG to minimize proximal out-of-frame dATG triplets in yeast and humans. CONCLUSIONS Collectively, our findings uncover the basic process by which eukaryotic ribosomes scan for initiation codons, and how this process could shape eukaryotic genome evolution.
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Affiliation(s)
- Ke Li
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jinhui Kong
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shuo Zhang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tong Zhao
- Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wenfeng Qian
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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11
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Hematopoietic differentiation is characterized by a transient peak of entropy at a single-cell level. BMC Biol 2022; 20:60. [PMID: 35260165 PMCID: PMC8905725 DOI: 10.1186/s12915-022-01264-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/22/2022] [Indexed: 12/11/2022] Open
Abstract
Background Mature blood cells arise from hematopoietic stem cells in the bone marrow by a process of differentiation along one of several different lineage trajectories. This is often represented as a series of discrete steps of increasing progenitor cell commitment to a given lineage, but as for differentiation in general, whether the process is instructive or stochastic remains controversial. Here, we examine this question by analyzing single-cell transcriptomic data from human bone marrow cells, assessing cell-to-cell variability along the trajectories of hematopoietic differentiation into four different types of mature blood cells. The instructive model predicts that cells will be following the same sequence of instructions and that there will be minimal variability of gene expression between them throughout the process, while the stochastic model predicts a role for cell-to-cell variability when lineage commitments are being made. Results Applying Shannon entropy to measure cell-to-cell variability among human hematopoietic bone marrow cells at the same stage of differentiation, we observed a transient peak of gene expression variability occurring at characteristic points in all hematopoietic differentiation pathways. Strikingly, the genes whose cell-to-cell variation of expression fluctuated the most over the course of a given differentiation trajectory are pathway-specific genes, whereas genes which showed the greatest variation of mean expression are common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes. Conclusions These data suggest that human hematopoietic differentiation could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination, and strongly support the stochastic view of differentiation. They also highlight the need to consider the role of stochastic gene expression in complex physiological processes and pathologies such as cancers, paving the way for possible noise-based therapies through epigenetic regulation. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01264-9.
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12
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Gowthaman U, Ivanov M, Schwarz I, Patel HP, Müller NA, García‐Pichardo D, Lenstra TL, Marquardt S. The Hda1 histone deacetylase limits divergent non-coding transcription and restricts transcription initiation frequency. EMBO J 2021; 40:e108903. [PMID: 34661296 PMCID: PMC8634119 DOI: 10.15252/embj.2021108903] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 08/31/2021] [Accepted: 09/28/2021] [Indexed: 01/01/2023] Open
Abstract
Nucleosome-depleted regions (NDRs) at gene promoters support initiation of RNA polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA and a divergent non-coding (DNC) transcript of unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. Using high-throughput reverse genetic screens based on quantitative single-cell fluorescence measurements, we identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC transcription. Nascent transcription profiling showed a genome-wide role of Hda1C in repression of DNC transcription. Live-cell imaging of transcription revealed that mutations in the Hda3 subunit increased the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC transcription regions, supporting DNC transcription repression by histone deacetylation. Our data support the interpretation that DNC transcription results as a consequence of the NDR-based architecture of eukaryotic promoters, but that it is governed by locus-specific repression to maintain genome fidelity.
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Affiliation(s)
- Uthra Gowthaman
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
| | - Maxim Ivanov
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
| | - Isabel Schwarz
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
| | - Heta P Patel
- Division of Gene RegulationThe Netherlands Cancer Institute (NKI)Oncode InstituteAmsterdamThe Netherlands
| | - Niels A Müller
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
- Present address:
Thünen Institute of Forest GeneticsGrosshansdorfGermany
| | - Desiré García‐Pichardo
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
| | - Tineke L Lenstra
- Division of Gene RegulationThe Netherlands Cancer Institute (NKI)Oncode InstituteAmsterdamThe Netherlands
| | - Sebastian Marquardt
- Copenhagen Plant Science CentreDepartment of Plant and Environmental SciencesUniversity of CopenhagenFrederiksberg CDenmark
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13
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Chen M, Zhou T, Zhang J. Correlation between external regulators governs the mean-noise relationship in stochastic gene expression. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:4713-4730. [PMID: 34198461 DOI: 10.3934/mbe.2021239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Gene transcription in single cells is inherently a probabilistic process. The relationship between variance ($ \sigma^{2} $) and mean expression ($ \mu $) is of paramount importance for investigations into the evolutionary origins and consequences of noise in gene expression. It is often formulated as $ \log \left({{{\sigma}^{2}}}/{{{\mu}^{2}}}\; \right) = \beta\log\mu+\log\alpha $, where $ \beta $ is a key parameter since its sign determines the qualitative dependence of noise on mean. We reveal that the sign of $ \beta $ is controlled completely by external regulation, but independent of promoter structure. Specifically, it is negative if regulators as stochastic variables are independent but positive if they are correlated. The essential mechanism revealed here can well interpret diverse experimental phenomena underlying expression noise. Our results imply that external regulation rather than promoter sequence governs the mean-noise relationship.
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Affiliation(s)
- Meiling Chen
- Guangdong Province Key Laboratory of Computational Science, Guangzhou 510275, China
- School of Mathematics, Sun Yat-Sen University, Guangzhou 510275, China
| | - Tianshou Zhou
- Guangdong Province Key Laboratory of Computational Science, Guangzhou 510275, China
- School of Mathematics, Sun Yat-Sen University, Guangzhou 510275, China
| | - Jiajun Zhang
- Guangdong Province Key Laboratory of Computational Science, Guangzhou 510275, China
- School of Mathematics, Sun Yat-Sen University, Guangzhou 510275, China
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14
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Capp J. Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability. Evol Appl 2021; 14:893-901. [PMID: 33897810 PMCID: PMC8061278 DOI: 10.1111/eva.13204] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 01/27/2021] [Accepted: 01/30/2021] [Indexed: 12/11/2022] Open
Abstract
Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.
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Affiliation(s)
- Jean‐Pascal Capp
- Toulouse Biotechnology InstituteINSACNRSINRAEUniversity of ToulouseToulouseFrance
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15
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Capturing and Understanding the Dynamics and Heterogeneity of Gene Expression in the Living Cell. Int J Mol Sci 2020; 21:ijms21218278. [PMID: 33167354 PMCID: PMC7663833 DOI: 10.3390/ijms21218278] [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: 09/23/2020] [Revised: 10/29/2020] [Accepted: 11/03/2020] [Indexed: 11/21/2022] Open
Abstract
The regulation of gene expression is a fundamental process enabling cells to respond to internal and external stimuli or to execute developmental programs. Changes in gene expression are highly dynamic and depend on many intrinsic and extrinsic factors. In this review, we highlight the dynamic nature of transient gene expression changes to better understand cell physiology and development in general. We will start by comparing recent in vivo procedures to capture gene expression in real time. Intrinsic factors modulating gene expression dynamics will then be discussed, focusing on chromatin modifications. Furthermore, we will dissect how cell physiology or age impacts on dynamic gene regulation and especially discuss molecular insights into acquired transcriptional memory. Finally, this review will give an update on the mechanisms of heterogeneous gene expression among genetically identical individual cells. We will mainly focus on state-of-the-art developments in the yeast model but also cover higher eukaryotic systems.
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16
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Cortijo S, Locke JCW. Does Gene Expression Noise Play a Functional Role in Plants? TRENDS IN PLANT SCIENCE 2020; 25:1041-1051. [PMID: 32467064 DOI: 10.1016/j.tplants.2020.04.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 04/22/2020] [Accepted: 04/28/2020] [Indexed: 05/20/2023]
Abstract
Gene expression in individual cells can be surprisingly noisy. In unicellular organisms this noise can be functional; for example, by allowing a subfraction of the population to prepare for environmental stress. The role of gene expression noise in multicellular organisms has, however, remained unclear. In this review, we discuss how new techniques are revealing an unexpected level of variability in gene expression between and within genetically identical plants. We describe recent progress as well as speculate on the function of transcriptional noise as a mechanism for generating functional phenotypic diversity in plants.
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Affiliation(s)
- Sandra Cortijo
- Sainsbury Laboratory, University of Cambridge, Cambridge CB2 1LR, UK
| | - James C W Locke
- Sainsbury Laboratory, University of Cambridge, Cambridge CB2 1LR, UK.
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17
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Liu J, Frochaux M, Gardeux V, Deplancke B, Robinson-Rechavi M. Inter-embryo gene expression variability recapitulates the hourglass pattern of evo-devo. BMC Biol 2020; 18:129. [PMID: 32950053 PMCID: PMC7502200 DOI: 10.1186/s12915-020-00842-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The evolution of embryological development has long been characterized by deep conservation. In animal development, the phylotypic stage in mid-embryogenesis is more conserved than either early or late stages among species within the same phylum. Hypotheses to explain this hourglass pattern have focused on purifying the selection of gene regulation. Here, we propose an alternative-genes are regulated in different ways at different stages and have different intrinsic capacities to respond to perturbations on gene expression. RESULTS To eliminate the influence of natural selection, we quantified the expression variability of isogenetic single embryo transcriptomes throughout fly Drosophila melanogaster embryogenesis. We found that the expression variability is lower at the phylotypic stage, supporting that the underlying regulatory architecture in this stage is more robust to stochastic variation on gene expression. We present evidence that the phylotypic stage is also robust to genetic variations on gene expression. Moreover, chromatin regulation appears to play a key role in the variation and evolution of gene expression. CONCLUSIONS We suggest that a phylum-level pattern of embryonic conservation can be explained by the intrinsic difference of gene regulatory mechanisms in different stages.
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Affiliation(s)
- Jialin Liu
- Department of Ecology and Evolution, University of Lausanne, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
| | - Michael Frochaux
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Vincent Gardeux
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bart Deplancke
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Marc Robinson-Rechavi
- Department of Ecology and Evolution, University of Lausanne, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
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18
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Hu Q, Greene CS, Heller EA. Specific histone modifications associate with alternative exon selection during mammalian development. Nucleic Acids Res 2020; 48:4709-4724. [PMID: 32319526 PMCID: PMC7229819 DOI: 10.1093/nar/gkaa248] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/23/2020] [Accepted: 04/02/2020] [Indexed: 12/29/2022] Open
Abstract
Alternative splicing (AS) is frequent during early mouse embryonic development. Specific histone post-translational modifications (hPTMs) have been shown to regulate exon splicing by either directly recruiting splice machinery or indirectly modulating transcriptional elongation. In this study, we hypothesized that hPTMs regulate expression of alternatively spliced genes for specific processes during differentiation. To address this notion, we applied an innovative machine learning approach to relate global hPTM enrichment to AS regulation during mammalian tissue development. We found that specific hPTMs, H3K36me3 and H3K4me1, play a role in skipped exon selection among all the tissues and developmental time points examined. In addition, we used iterative random forest model and found that interactions of multiple hPTMs most strongly predicted splicing when they included H3K36me3 and H3K4me1. Collectively, our data demonstrated a link between hPTMs and alternative splicing which will drive further experimental studies on the functional relevance of these modifications to alternative splicing.
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Affiliation(s)
- Qiwen Hu
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Casey S Greene
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth A Heller
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
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19
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Tang J, Wu Z, Tian Y, Yang R. ICGEC: a comparative method for measuring epigenetic conservation of genes via the integrated signal from multiple histone modifications between cell types. BMC Genomics 2020; 21:356. [PMID: 32398001 PMCID: PMC7216622 DOI: 10.1186/s12864-020-6771-1] [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: 09/29/2019] [Accepted: 05/04/2020] [Indexed: 11/17/2022] Open
Abstract
Background Histone post-translational modifications play crucial roles in epigenetic regulation of gene expression and are known to be associated with the phenotypic differences of different cell types. Therefore, it is of fundamental importance to dissect the genes and pathways involved in such a phenotypic variation at the level of epigenetics. However, the existing comparative approaches are largely based on the differences, especially the absolute difference in the levels of individual histone modifications of genes under contrasting conditions. Thus, a method for measuring the overall change in the epigenetic circumstance of each gene underpinned by multiple types of histone modifications between cell types is lacking. Results To address this challenge, we developed ICGEC, a new method for estimating the degree of epigenetic conservation of genes between two cell lines. Different from existing comparative methods, ICGEC provides a reliable score for measuring the relative change in the epigenetic context of corresponding gene between two conditions and simultaneously produces a score for each histone mark. The application of ICGEC to the human embryonic stem cell line H1 and four H1-derived cell lines with available epigenomic data for the same 16 types of histone modifications indicated high robustness and reliability of ICGEC. Furthermore, the analysis of the epigenetically dynamic and conserved genes which were defined based on the ICGEC output results demonstrated that ICGEC can deepen our understanding of the biological processes of cell differentiation to overcome the limitations of traditional expression analysis. Specifically, the ICGEC-derived differentiation-direction-specific genes were shown to have putative functions that are well-matched with cell identity. Additionally, H3K79me1 and H3K27ac were found to be the main histone marks accounting for whether an epigenetically dynamic gene was differentially expressed between two cell lines. Conclusions The use of ICGEC creates a convenient and robust way to measure the overall epigenetic conservation of individual genes and marks between two conditions. Thus, it provides a basis for exploring the epigenotype-phenotype relationship. ICGEC can be deemed a state-of-the-art method tailored for comparative epigenomic analysis of changes in cell dynamics.
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Affiliation(s)
- Jing Tang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Zefeng Wu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yuhan Tian
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Ruolin Yang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
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20
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Sun M, Zhang J. Allele-specific single-cell RNA sequencing reveals different architectures of intrinsic and extrinsic gene expression noises. Nucleic Acids Res 2020; 48:533-547. [PMID: 31799601 PMCID: PMC6954418 DOI: 10.1093/nar/gkz1134] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 10/19/2019] [Accepted: 11/20/2019] [Indexed: 01/13/2023] Open
Abstract
Gene expression noise refers to the variation of the expression level of a gene among isogenic cells in the same environment, and has two sources: extrinsic noise arising from the disparity of the cell state and intrinsic noise arising from the stochastic process of gene expression in the same cell state. Due to the low throughput of the existing method for measuring the two noise components, the architectures of intrinsic and extrinsic expression noises remain elusive. Using allele-specific single-cell RNA sequencing, we here estimate the two noise components of 3975 genes in mouse fibroblast cells. Our analyses verify predicted influences of several factors such as the TATA-box and microRNA targeting on intrinsic or extrinsic noises and reveal gene function-associated noise trends implicating the action of natural selection. These findings unravel differential regulations, optimizations, and biological consequences of intrinsic and extrinsic noises and can aid the construction of desired synthetic circuits.
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Affiliation(s)
- Mengyi Sun
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
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21
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Abstract
An important capacity of genes is the rapid change of expression levels to cope with the environment, known as expression responsiveness or plasticity. Elucidating the genomic mechanisms determining expression plasticity is critical for understanding the molecular basis of phenotypic plasticity, fitness and adaptation. In this study, we systematically quantified gene expression plasticity in four metazoan species by integrating changes of expression levels under a large number of genetic and environmental conditions. From this, we demonstrated that expression plasticity measures a distinct feature of gene expression that is orthogonal to other well-studied features, including gene expression level and tissue specificity/broadness. Expression plasticity is conserved across species with important physiological implications. The magnitude of expression plasticity is highly correlated with gene function and genes with high plasticity are implicated in disease susceptibility. Genome-wide analysis identified many conserved promoter cis-elements, trans-acting factors (such as CTCF), and gene body histone modifications (H3K36me3, H3K79me2 and H4K20me1) that are significantly associated with expression plasticity. Analysis of expression changes in perturbation experiments further validated a causal role of specific transcription factors and histone modifications. Collectively, this work reveals the general properties, physiological implications and multivariable regulation of gene expression plasticity in metazoans, extending the mechanistic understanding of gene regulation.
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Affiliation(s)
- Long Xiao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China.,University of Chinese Academy of Sciences, Beijing 10049, People's Republic of China
| | - Zhiguang Zhao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China.,University of Chinese Academy of Sciences, Beijing 10049, People's Republic of China
| | - Fei He
- Biology Department, Brookhaven National Lab, Upton, NY 11967, USA
| | - Zhuo Du
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China.,University of Chinese Academy of Sciences, Beijing 10049, People's Republic of China
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22
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You ST, Jhou YT, Kao CF, Leu JY. Experimental evolution reveals a general role for the methyltransferase Hmt1 in noise buffering. PLoS Biol 2019; 17:e3000433. [PMID: 31613873 PMCID: PMC6814240 DOI: 10.1371/journal.pbio.3000433] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 10/25/2019] [Accepted: 09/27/2019] [Indexed: 11/19/2022] Open
Abstract
Cell-to-cell heterogeneity within an isogenic population has been observed in prokaryotic and eukaryotic cells. Such heterogeneity often manifests at the level of individual protein abundance and may have evolutionary benefits, especially for organisms in fluctuating environments. Although general features and the origins of cellular noise have been revealed, details of the molecular pathways underlying noise regulation remain elusive. Here, we used experimental evolution of Saccharomyces cerevisiae to select for mutations that increase reporter protein noise. By combining bulk segregant analysis and CRISPR/Cas9-based reconstitution, we identified the methyltransferase Hmt1 as a general regulator of noise buffering. Hmt1 methylation activity is critical for the evolved phenotype, and we also show that two of the Hmt1 methylation targets can suppress noise. Hmt1 functions as an environmental sensor to adjust noise levels in response to environmental cues. Moreover, Hmt1-mediated noise buffering is conserved in an evolutionarily distant yeast species, suggesting broad significance of noise regulation. Experimental evolution in yeast reveals that the methyltransferase Hmt1 functions as a mediator connecting environmental stimuli to cellular noise; Hmt1-mediated noise buffering is conserved in an evolutionarily distant yeast.
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Affiliation(s)
- Shu-Ting You
- Molecular and Cell Biology, Taiwan International Graduate Program, Graduate Institute of Life Sciences, National Defense Medical Center and Academia Sinica, Taipei, Taiwan
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Yu-Ting Jhou
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Cheng-Fu Kao
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan
| | - Jun-Yi Leu
- Molecular and Cell Biology, Taiwan International Graduate Program, Graduate Institute of Life Sciences, National Defense Medical Center and Academia Sinica, Taipei, Taiwan
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
- * E-mail:
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23
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de Jong TV, Moshkin YM, Guryev V. Gene expression variability: the other dimension in transcriptome analysis. Physiol Genomics 2019; 51:145-158. [DOI: 10.1152/physiolgenomics.00128.2018] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Transcriptome sequencing is a powerful technique to study molecular changes that underlie the differences in physiological conditions and disease progression. A typical question that is posed in such studies is finding genes with significant changes between sample groups. In this respect expression variability is regarded as a nuisance factor that is primarily of technical origin and complicates the data analysis. However, it is becoming apparent that the biological variation in gene expression might be an important molecular phenotype that can affect physiological parameters. In this review we explore the recent literature on technical and biological variability in gene expression, sources of expression variability, (epi-)genetic hallmarks, and evolutionary constraints in genes with robust and variable gene expression. We provide an overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it. We discuss metrics and tools that were developed for quantification of expression variability and highlight the importance of future studies in this direction. To assist the adoption of expression variability analysis, we also provide a detailed description and computer code, which can easily be utilized by other researchers. We also provide a reanalysis of recently published data to highlight the value of the analysis method.
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Affiliation(s)
- Tristan V. de Jong
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Yuri M. Moshkin
- Institute of Cytology and Genetics, Siberian Branch of RAS, Novosibirsk, Russia
- Institute of Molecular and Cellular Biology, Siberian Branch of RAS, Novosibirsk, Russia
| | - Victor Guryev
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
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24
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Chen Y, Wang G, Cai H, Sun Y, Ouyang L, Liu B. Deciphering the Rules of in Silico Autophagy Methods for Expediting Medicinal Research. J Med Chem 2019; 62:6831-6842. [PMID: 30888814 DOI: 10.1021/acs.jmedchem.8b01673] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Autophagy is a highly evolutionarily conserved cellular catabolic process responsible for degradation of damaged organelles and long-lived proteins. It is not surprising that scientific interest in the connection of autophagy and diseases has been growing. Over the past 2 decades, many new experimental approaches have been emerging in the field of targeting autophagy for medicinal research. Interestingly, in addition to experimental methods, a number of databases, Web servers, mathematics models, omics approaches, and systems biology network approaches related to autophagy have become available online, which may be collectively considered to be "in silico autophagy methods" for expediting current medicinal research. Thus, we have summarized a series of relevant in silico autophagy approaches for promoting the most appropriate usage of these resources for potential therapeutic purposes.
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Affiliation(s)
- Yi Chen
- State Key Laboratory of Biotherapy and Cancer Center and Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu 610041 , China
| | - Guan Wang
- State Key Laboratory of Biotherapy and Cancer Center and Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu 610041 , China
| | - Haoyang Cai
- Center of Growth, Metabolism, and Aging, Key Laboratory of Bio-Resources and Eco-Environment, College of Life Sciences , Sichuan University , Chengdu 610064 , China
| | - Yang Sun
- State Key Laboratory of Pharmaceutical Biotechnology, Department of Biotechnology and Pharmaceutical Sciences, School of Life Sciences , Nanjing University , Nanjing 210023 , China
| | - Liang Ouyang
- State Key Laboratory of Biotherapy and Cancer Center and Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu 610041 , China
| | - Bo Liu
- State Key Laboratory of Biotherapy and Cancer Center and Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu 610041 , China
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25
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Liu S, Lu M, Li H, Zuo Y. Prediction of Gene Expression Patterns With Generalized Linear Regression Model. Front Genet 2019; 10:120. [PMID: 30886626 PMCID: PMC6409355 DOI: 10.3389/fgene.2019.00120] [Citation(s) in RCA: 132] [Impact Index Per Article: 26.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 02/04/2019] [Indexed: 01/10/2023] Open
Abstract
Cell reprogramming has played important roles in medical science, such as tissue repair, organ reconstruction, disease treatment, new drug development, and new species breeding. Oct4, a core pluripotency factor, has especially played a key role in somatic cell reprogramming through transcriptional control and affects the expression level of genes by its combination intensity. However, the quantitative relationship between Oct4 combination intensity and target gene expression is still not clear. Therefore, firstly, a generalized linear regression method was constructed to predict gene expression values in promoter regions affected by Oct4 combination intensity. Training data, including Oct4 combination intensity and target gene expression, were from promoter regions of genes with different cell development stages. Additionally, the quantitative relationship between gene expression and Oct4 combination intensity was analyzed with the proposed model. Then, the quantitative relationship between gene expression and Oct4 combination intensity at each stage of cell development was classified into high and low levels. Experimental analysis showed that the combination height of Oct4-inhibited gene expression decremented by a temporal exponential value, whereas the combination width of Oct4-promoted gene expression incremented by a temporal logarithmic value. Experimental results showed that the proposed method can achieve goodness of fit with high confidence.
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Affiliation(s)
- Shuai Liu
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
- College of Computer Science, Inner Mongolia University, Hohhot, China
| | - Mengye Lu
- College of Computer Science, Inner Mongolia University, Hohhot, China
| | - Hanshuang Li
- College of Life Sciences, Inner Mongolia University, Hohhot, China
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot, China
| | - Yongchun Zuo
- College of Life Sciences, Inner Mongolia University, Hohhot, China
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot, China
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26
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Chen LF, Lin YT, Gallegos DA, Hazlett MF, Gómez-Schiavon M, Yang MG, Kalmeta B, Zhou AS, Holtzman L, Gersbach CA, Grandl J, Buchler NE, West AE. Enhancer Histone Acetylation Modulates Transcriptional Bursting Dynamics of Neuronal Activity-Inducible Genes. Cell Rep 2019; 26:1174-1188.e5. [PMID: 30699347 PMCID: PMC6376993 DOI: 10.1016/j.celrep.2019.01.032] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 12/13/2018] [Accepted: 01/09/2019] [Indexed: 12/16/2022] Open
Abstract
Neuronal activity-inducible gene transcription correlates with rapid and transient increases in histone acetylation at promoters and enhancers of activity-regulated genes. Exactly how histone acetylation modulates transcription of these genes has remained unknown. We used single-cell in situ transcriptional analysis to show that Fos and Npas4 are transcribed in stochastic bursts in mouse neurons and that membrane depolarization increases mRNA expression by increasing burst frequency. We then expressed dCas9-p300 or dCas9-HDAC8 fusion proteins to mimic or block activity-induced histone acetylation locally at enhancers. Adding histone acetylation increased Fos transcription by prolonging burst duration and resulted in higher Fos protein levels and an elevation of resting membrane potential. Inhibiting histone acetylation reduced Fos transcription by reducing burst frequency and impaired experience-dependent Fos protein induction in the hippocampus in vivo. Thus, activity-inducible histone acetylation tunes the transcriptional dynamics of experience-regulated genes to affect selective changes in neuronal gene expression and cellular function.
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Affiliation(s)
- Liang-Fu Chen
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Yen Ting Lin
- Center for Nonlinear Studies (T-CNLS) and Theoretical Biology and Biophysics Group (T-6), Theoretical Division, Los Alamos National Laboratory, NM 87545, USA
| | - David A Gallegos
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Mariah F Hazlett
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Mariana Gómez-Schiavon
- Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27710, USA; Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA; Department of Biology, Duke University, Durham, NC 27710, USA
| | - Marty G Yang
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Breanna Kalmeta
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Allen S Zhou
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Liad Holtzman
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
| | - Charles A Gersbach
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA; Department of Orthopaedic Surgery, Duke University, Durham, NC 27710, USA
| | - Jörg Grandl
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Nicolas E Buchler
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27710, USA; Department of Biology, Duke University, Durham, NC 27710, USA; Department of Molecular Biomedical Sciences, North Carolina State University, Raleigh, NC 27606, USA.
| | - Anne E West
- Department of Neurobiology, Duke University, Durham, NC 27710, USA.
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27
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Cortijo S, Aydin Z, Ahnert S, Locke JC. Widespread inter-individual gene expression variability in Arabidopsis thaliana. Mol Syst Biol 2019; 15:e8591. [PMID: 30679203 PMCID: PMC6346214 DOI: 10.15252/msb.20188591] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.
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Affiliation(s)
- Sandra Cortijo
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - Zeynep Aydin
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - Sebastian Ahnert
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - James Cw Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
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Role of noise and parametric variation in the dynamics of gene regulatory circuits. NPJ Syst Biol Appl 2018; 4:40. [PMID: 30416751 PMCID: PMC6218471 DOI: 10.1038/s41540-018-0076-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Revised: 10/14/2018] [Accepted: 10/16/2018] [Indexed: 12/21/2022] Open
Abstract
Stochasticity in gene expression impacts the dynamics and functions of gene regulatory circuits. Intrinsic noises, including those that are caused by low copy number of molecules and transcriptional bursting, are usually studied by stochastic simulations. However, the role of extrinsic factors, such as cell-to-cell variability and heterogeneity in the microenvironment, is still elusive. To evaluate the effects of both the intrinsic and extrinsic noises, we develop a method, named sRACIPE, by integrating stochastic analysis with random circuit perturbation (RACIPE) method. RACIPE uniquely generates and analyzes an ensemble of models with random kinetic parameters. Previously, we have shown that the gene expression from random models form robust and functionally related clusters. In sRACIPE we further develop two stochastic simulation schemes, aiming to reduce the computational cost without sacrificing the convergence of statistics. One scheme uses constant noise to capture the basins of attraction, and the other one uses simulated annealing to detect the stability of states. By testing the methods on several synthetic gene regulatory circuits and an epithelial-mesenchymal transition network in squamous cell carcinoma, we demonstrate that sRACIPE can interpret the experimental observations from single-cell gene expression data. We observe that parametric variation (the spread of parameters around a median value) increases the spread of the gene expression clusters, whereas high noise merges the states. Our approach quantifies the robustness of a gene circuit in the presence of noise and sheds light on a new mechanism of noise-induced hybrid states. We have implemented sRACIPE as an R package.
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29
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Grabowski P, Kustatscher G, Rappsilber J. Epigenetic Variability Confounds Transcriptome but Not Proteome Profiling for Coexpression-based Gene Function Prediction. Mol Cell Proteomics 2018; 17:2082-2090. [PMID: 30042154 PMCID: PMC6210221 DOI: 10.1074/mcp.ra118.000935] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 07/09/2018] [Indexed: 12/15/2022] Open
Abstract
Genes are often coexpressed with their genomic neighbors, even if these are functionally unrelated. For small expression changes driven by genetic variation within the same cell type, non-functional mRNA coexpression is not propagated to the protein level. However, it is unclear if protein levels are also buffered against any non-functional mRNA coexpression accompanying large, regulated changes in the gene expression program, such as those occurring during cell differentiation. Here, we address this question by analyzing mRNA and protein expression changes for housekeeping genes across 20 mouse tissues. We find that a large proportion of mRNA coexpression is indeed non-functional and does not lead to coexpressed proteins. Chromosomal proximity of genes explains a proportion of this nonfunctional mRNA coexpression. However, the main driver of non-functional mRNA coexpression across mouse tissues is epigenetic similarity. Both factors together provide an explanation for why monitoring protein coexpression outperforms mRNA coexpression data in gene function prediction. Furthermore, this suggests that housekeeping genes translocating during evolution within genomic subcompartments might maintain their broad expression pattern.
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Affiliation(s)
- Piotr Grabowski
- From the ‡Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Georg Kustatscher
- §Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Juri Rappsilber
- From the ‡Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany; .,§Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK
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30
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Nicolas D, Zoller B, Suter DM, Naef F. Modulation of transcriptional burst frequency by histone acetylation. Proc Natl Acad Sci U S A 2018; 115:7153-7158. [PMID: 29915087 PMCID: PMC6142243 DOI: 10.1073/pnas.1722330115] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Many mammalian genes are transcribed during short bursts of variable frequencies and sizes that substantially contribute to cell-to-cell variability. However, which molecular mechanisms determine bursting properties remains unclear. To probe putative mechanisms, we combined temporal analysis of transcription along the circadian cycle with multiple genomic reporter integrations, using both short-lived luciferase live microscopy and single-molecule RNA-FISH. Using the Bmal1 circadian promoter as our model, we observed that rhythmic transcription resulted predominantly from variations in burst frequency, while the genomic position changed the burst size. Thus, burst frequency and size independently modulated Bmal1 transcription. We then found that promoter histone-acetylation level covaried with burst frequency, being greatest at peak expression and lowest at trough expression, while remaining unaffected by the genomic location. In addition, specific deletions of ROR-responsive elements led to constitutively elevated histone acetylation and burst frequency. We then investigated the suggested link between histone acetylation and burst frequency by dCas9p300-targeted modulation of histone acetylation, revealing that acetylation levels influence burst frequency more than burst size. The correlation between acetylation levels at the promoter and burst frequency was also observed in endogenous circadian genes and in embryonic stem cell fate genes. Thus, our data suggest that histone acetylation-mediated control of transcription burst frequency is a common mechanism to control mammalian gene expression.
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Affiliation(s)
- Damien Nicolas
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland
| | - Benjamin Zoller
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland
| | - David M Suter
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland
| | - Felix Naef
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland
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31
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Morgan MD, Marioni JC. CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness. Genome Biol 2018; 19:81. [PMID: 29945659 PMCID: PMC6020341 DOI: 10.1186/s13059-018-1461-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 06/04/2018] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Population phenotypic variation can arise from genetic differences between individuals, or from cellular heterogeneity in an isogenic group of cells or organisms. The emergence of gene expression differences between genetically identical cells is referred to as gene expression noise, the sources of which are not well understood. RESULTS In this work, by studying gene expression noise between multiple cell lineages and mammalian species, we find consistent evidence of a role for CpG islands as sources of gene expression noise. Variation in noise among CpG island promoters can be partially attributed to differences in island size, in which short islands have noisier gene expression. Building on these findings, we investigate the potential for short CpG islands to act as fast response elements to environmental stimuli. Specifically, we find that these islands are enriched amongst primary response genes in SWI/SNF-independent stimuli, suggesting that expression noise is an indicator of promoter responsiveness. CONCLUSIONS Thus, through the integration of single-cell RNA expression profiling, chromatin landscape and temporal gene expression dynamics, we have uncovered a role for short CpG island promoters as fast response elements.
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Affiliation(s)
- Michael D Morgan
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
| | - John C Marioni
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Li Ka Shing Centre, Cambridge, CB2 0RE, UK.
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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32
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Megaridis MR, Lu Y, Tevonian EN, Junger KM, Moy JM, Bohn-Wippert K, Dar RD. Fine-tuning of noise in gene expression with nucleosome remodeling. APL Bioeng 2018; 2:026106. [PMID: 31069303 PMCID: PMC6481717 DOI: 10.1063/1.5021183] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 03/16/2018] [Indexed: 01/08/2023] Open
Abstract
Engineering stochastic fluctuations of gene expression (or “noise”) is integral to precisely bias cellular-fate decisions and statistical phenotypes in both single-cell and multi-cellular systems. Epigenetic regulation has been shown to constitute a large source of noise, and thus, engineering stochasticity is deeply intertwined with epigenetics. Here, utilizing chromatin remodeling, we report that Caffeic acid phenethyl ester (CA) and Pyrimethamine (PYR), two inhibitors of BAF250a, a subunit of the Brahma-associated factor (BAF) nucleosome remodeling complex, enable differential and tunable control of noise in transcription and translation from the human immunodeficiency virus long terminal repeat promoter in a dose and time-dependent manner. CA conserves noise levels while increasing mean abundance, resulting in direct tuning of the transcriptional burst size, while PYR strictly increases transcriptional initiation frequency while conserving a constant transcriptional burst size. Time-dependent treatment with CA reveals non-continuous tuning with noise oscillating at a constant mean abundance at early time points and the burst size increasing for treatments after 5 h. Treatments combining CA and Protein Kinase C agonists result in an even larger increase of abundance while conserving noise levels with a highly non-linear increase in variance of up to 63× untreated controls. Finally, drug combinations provide non-antagonistic combinatorial tuning of gene expression noise and map a noise phase space for future applications with viral and synthetic gene vectors. Active remodeling of nucleosomes and BAF-mediated control of gene expression noise expand a toolbox for the future design and engineering of stochasticity in living systems.
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Affiliation(s)
- Melina R Megaridis
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Yiyang Lu
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Erin N Tevonian
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Kendall M Junger
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Jennifer M Moy
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Kathrin Bohn-Wippert
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
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33
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Román AC, Vicente-Page J, Pérez-Escudero A, Carvajal-González JM, Fernández-Salguero PM, de Polavieja GG. Histone H4 acetylation regulates behavioral inter-individual variability in zebrafish. Genome Biol 2018; 19:55. [PMID: 29695303 PMCID: PMC5922312 DOI: 10.1186/s13059-018-1428-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 03/29/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Animals can show very different behaviors even in isogenic populations, but the underlying mechanisms to generate this variability remain elusive. We use the zebrafish (Danio rerio) as a model to test the influence of histone modifications on behavior. RESULTS We find that laboratory and isogenic zebrafish larvae show consistent individual behaviors when swimming freely in identical wells or in reaction to stimuli. This behavioral inter-individual variability is reduced when we impair the histone deacetylation pathway. Individuals with high levels of histone H4 acetylation, and specifically H4K12, behave similarly to the average of the population, but those with low levels deviate from it. More precisely, we find a set of genomic regions whose histone H4 acetylation is reduced with the distance between the individual and the average population behavior. We find evidence that this modulation depends on a complex of Yin-yang 1 (YY1) and histone deacetylase 1 (HDAC1) that binds to and deacetylates these regions. These changes are not only maintained at the transcriptional level but also amplified, as most target regions are located near genes encoding transcription factors. CONCLUSIONS We suggest that stochasticity in the histone deacetylation pathway participates in the generation of genetic-independent behavioral inter-individual variability.
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Affiliation(s)
- Angel-Carlos Román
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Avenida Brasília s/n, 1400-038, Lisbon, Portugal. .,Instituto Cajal, Consejo Superior de Investigaciones Científicas, Av. Doctor Arce, 37, 28002, Madrid, Spain.
| | - Julián Vicente-Page
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Avenida Brasília s/n, 1400-038, Lisbon, Portugal.,Instituto Cajal, Consejo Superior de Investigaciones Científicas, Av. Doctor Arce, 37, 28002, Madrid, Spain
| | - Alfonso Pérez-Escudero
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Av. Doctor Arce, 37, 28002, Madrid, Spain.,Physics Department, MIT, Cambridge, Massachusetts, USA
| | - Jose M Carvajal-González
- Departamento de Bioquímica y Biología Molecular y Genética, Universidad de Extremadura, Av. de Elvas s/n, 06071, Badajoz, Spain
| | - Pedro M Fernández-Salguero
- Departamento de Bioquímica y Biología Molecular y Genética, Universidad de Extremadura, Av. de Elvas s/n, 06071, Badajoz, Spain
| | - Gonzalo G de Polavieja
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Avenida Brasília s/n, 1400-038, Lisbon, Portugal. .,Instituto Cajal, Consejo Superior de Investigaciones Científicas, Av. Doctor Arce, 37, 28002, Madrid, Spain.
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34
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Sun S, Sun X, Zheng Y. Higher-order partial least squares for predicting gene expression levels from chromatin states. BMC Bioinformatics 2018; 19:113. [PMID: 29671394 PMCID: PMC5907142 DOI: 10.1186/s12859-018-2100-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Background Extensive studies have shown that gene expression levels are strongly affected by chromatin mark combinations via at least two mechanisms, i.e., activation or repression. But their combinatorial patterns are still unclear. To further understand the relationship between histone modifications and gene expression levels, here in this paper, we introduce a purely geometric higher-order representation, tensor (also called multidimensional array), which might borrow more unknown interactions in chromatin states to predicting gene expression levels. Results The prediction models were learned from regions around upstream 10k base pairs and downstream 10k base pairs of the transcriptional start sites (TSSs) on three species (i.e., Human, Rhesus Macaque, and Chimpanzee) with five histone modifications (i.e., H3K4me1, H3K4me3, H3K27ac, H3K27me3, and Pol II). Experimental results demonstrate that the proposed method is more powerful to predicting gene expression levels than several other popular methods. Specifically, our method enable to get more powerful performance on both commonly used criteria, R and RMSE, as high as 1.7% and 11%, respectively. Conclusions The overall aim of this work is to show that the higher-order representation is able to include more unknown interaction information between histone modifications across different species.
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Affiliation(s)
- Shiquan Sun
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, Shaanxi, People's Republic of China. .,Department of Biostatistics, University of Michigan, Ann Arbor, 48109, MI, USA.
| | - Xifang Sun
- School of Science, Xi'an Shiyou University, Xi'an, 710065, Shaanxi, People's Republic of China
| | - Yan Zheng
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, Shaanxi, People's Republic of China
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