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Guo P, Mao L, Chen Y, Lee CN, Cardilla A, Li M, Bartosovic M, Deng Y. Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.13.612892. [PMID: 39345645 PMCID: PMC11429933 DOI: 10.1101/2024.09.13.612892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
The phenotypic and functional states of a cell are modulated by a complex interactive molecular hierarchy of multiple omics layers, involving the genome, epigenome, transcriptome, proteome, and metabolome. Spatial omics approaches have enabled the capture of information from different molecular layers directly in the tissue context. However, current technologies are limited to map one to two modalities at the same time, providing an incomplete representation of cellular identity. Such data is inadequate to fully understand complex biological systems and their underlying regulatory mechanisms. Here we present spatial-Mux-seq, a multi-modal spatial technology that allows simultaneous profiling of five different modalities, including genome-wide profiles of two histone modifications and open chromatin, whole transcriptome, and a panel of proteins at tissue scale and cellular level in a spatially resolved manner. We applied this technology to generate multi-modal tissue maps in mouse embryos and mouse brains, which discriminated more cell types and states than unimodal data. We investigated the spatiotemporal relationship between histone modifications, chromatin accessibility, gene and protein expression in neuron differentiation revealing the relationship between tissue organization, function, and gene regulatory networks. We were able to identify a radial glia spatial niche and revealed spatially changing gradient of epigenetic signals in this region. Moreover, we revealed previously unappreciated involvement of repressive histone marks in the mouse hippocampus. Collectively, the spatial multi-omics approach heralds a new era for characterizing tissue and cellular heterogeneity that single modality studies alone could not reveal.
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Affiliation(s)
- Pengfei Guo
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- These authors contributed equally
| | - Liran Mao
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Statistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- These authors contributed equally
| | - Yufan Chen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Chin Nien Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Angelysia Cardilla
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Mingyao Li
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Statistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marek Bartosovic
- Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Yanxiang Deng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Tsuruta Y, Senmatsu S, Oe H, Hoffman CS, Hirota K. Metabolic stress-induced long ncRNA transcription governs the formation of meiotic DNA breaks in the fission yeast fbp1 gene. PLoS One 2024; 19:e0294191. [PMID: 38252660 PMCID: PMC10802949 DOI: 10.1371/journal.pone.0294191] [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: 06/05/2023] [Accepted: 10/26/2023] [Indexed: 01/24/2024] Open
Abstract
Meiotic recombination is a pivotal process that ensures faithful chromosome segregation and contributes to the generation of genetic diversity in offspring, which is initiated by the formation of double-strand breaks (DSBs). The distribution of meiotic DSBs is not uniform and is clustered at hotspots, which can be affected by environmental conditions. Here, we show that non-coding RNA (ncRNA) transcription creates meiotic DSBs through local chromatin remodeling in the fission yeast fbp1 gene. The fbp1 gene is activated upon glucose starvation stress, in which a cascade of ncRNA-transcription in the fbp1 upstream region converts the chromatin configuration into an open structure, leading to the subsequent binding of transcription factors. We examined the distribution of meiotic DSBs around the fbp1 upstream region in the presence and absence of glucose and observed several new DSBs after chromatin conversion under glucose starvation conditions. Moreover, these DSBs disappeared when cis-elements required for ncRNA transcription were mutated. These results indicate that ncRNA transcription creates meiotic DSBs in response to stress conditions in the fbp1 upstream region. This study addressed part of a long-standing unresolved mechanism underlying meiotic recombination plasticity in response to environmental fluctuation.
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Affiliation(s)
- Yusuke Tsuruta
- Department of Chemistry, Graduate School of Science, Tokyo Metropolitan University, Hachioji-shi, Tokyo, Japan
| | - Satoshi Senmatsu
- Department of Chemistry, Graduate School of Science, Tokyo Metropolitan University, Hachioji-shi, Tokyo, Japan
| | - Hana Oe
- Department of Chemistry, Graduate School of Science, Tokyo Metropolitan University, Hachioji-shi, Tokyo, Japan
| | - Charles S. Hoffman
- Biology Department, Boston College, Chestnut Hill, MA, United States of America
| | - Kouji Hirota
- Department of Chemistry, Graduate School of Science, Tokyo Metropolitan University, Hachioji-shi, Tokyo, Japan
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Chandra O, Sharma M, Pandey N, Jha IP, Mishra S, Kong SL, Kumar V. Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes. Comput Struct Biotechnol J 2023; 21:3590-3603. [PMID: 37520281 PMCID: PMC10371796 DOI: 10.1016/j.csbj.2023.07.014] [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: 01/25/2023] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 08/01/2023] Open
Abstract
Understanding the biological roles of all genes only through experimental methods is challenging. A computational approach with reliable interpretability is needed to infer the function of genes, particularly for non-coding RNAs. We have analyzed genomic features that are present across both coding and non-coding genes like transcription factor (TF) and cofactor ChIP-seq (823), histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) to predict ontology-based functions of genes. Our approach for gene function prediction was reliable (>90% balanced accuracy) for 486 gene-sets. PubMed abstract mining and CRISPR screens supported the inferred association of genes with biological functions, for which our method had high accuracy. Further analysis revealed that TF-binding patterns at promoters have high predictive strength for multiple functions. TF-binding patterns at the promoter add an unexplored dimension of explainable regulatory aspects of genes and their functions. Therefore, we performed a comprehensive analysis for the functional-specificity of TF-binding patterns at promoters and used them for clustering functions to reveal many latent groups of gene-sets involved in common major cellular processes. We also showed how our approach could be used to infer the functions of non-coding genes using the CRISPR screens of coding genes, which were validated using a long non-coding RNA CRISPR screen. Thus our results demonstrated the generality of our approach by using gene-sets from CRISPR screens. Overall, our approach opens an avenue for predicting the involvement of non-coding genes in various functions.
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Affiliation(s)
- Omkar Chandra
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
| | - Madhu Sharma
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
| | - Neetesh Pandey
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
| | - Indra Prakash Jha
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
| | - Shreya Mishra
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
| | - Say Li Kong
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Vibhor Kumar
- Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Ph-III, New Delhi, India
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Li X, Pak HS, Huber F, Michaux J, Taillandier-Coindard M, Altimiras ER, Bassani-Sternberg M. A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics. CELL REPORTS METHODS 2023; 3:100479. [PMID: 37426762 PMCID: PMC10326370 DOI: 10.1016/j.crmeth.2023.100479] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 03/22/2023] [Accepted: 04/19/2023] [Indexed: 07/11/2023]
Abstract
Mass spectrometry (MS)-based immunopeptidomics is an attractive antigen discovery method with growing clinical implications. However, the current experimental approach to extract HLA-restricted peptides requires a bulky sample source, which remains a challenge for obtaining clinical specimens. We present an innovative workflow that requires a low sample volume, which streamlines the immunoaffinity purification (IP) and C18 peptide cleanup on a single microfluidics platform with automated liquid handling and minimal sample transfers, resulting in higher assay sensitivity. We also demonstrate how the state-of-the-art data-independent acquisition (DIA) method further enhances the depth of tandem MS spectra-based peptide sequencing. Consequently, over 4,000 and 5,000 HLA-I-restricted peptides were identified from as few as 0.2 million RA957 cells and a melanoma tissue of merely 5 mg, respectively. We also identified multiple immunogenic tumor-associated antigens and hundreds of peptides derived from non-canonical protein sources. This workflow represents a powerful tool for identifying the immunopeptidome of sparse samples.
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Affiliation(s)
- Xiaokang Li
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Hui Song Pak
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Florian Huber
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Justine Michaux
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Marie Taillandier-Coindard
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Emma Ricart Altimiras
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
| | - Michal Bassani-Sternberg
- Ludwig Institute for Cancer Research, University of Lausanne, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Rue du Bugnon 46, 1005 Lausanne, Switzerland
- Agora Cancer Research Centre, Rue du Bugnon 25A, 1005 Lausanne, Switzerland
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Downes DJ, Hughes JR. Natural and Experimental Rewiring of Gene Regulatory Regions. Annu Rev Genomics Hum Genet 2022; 23:73-97. [PMID: 35472292 DOI: 10.1146/annurev-genom-112921-010715] [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: 11/09/2022]
Abstract
The successful development and ongoing functioning of complex organisms depend on the faithful execution of the genetic code. A critical step in this process is the correct spatial and temporal expression of genes. The highly orchestrated transcription of genes is controlled primarily by cis-regulatory elements: promoters, enhancers, and insulators. The medical importance of this key biological process can be seen by the frequency with which mutations and inherited variants that alter cis-regulatory elements lead to monogenic and complex diseases and cancer. Here, we provide an overview of the methods available to characterize and perturb gene regulatory circuits. We then highlight mechanisms through which regulatory rewiring contributes to disease, and conclude with a perspective on how our understanding of gene regulation can be used to improve human health.
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Affiliation(s)
- Damien J Downes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
- MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
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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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