1
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Meyers S, Demeyer S, Cools J. CRISPR screening in hematology research: from bulk to single-cell level. J Hematol Oncol 2023; 16:107. [PMID: 37875911 PMCID: PMC10594891 DOI: 10.1186/s13045-023-01495-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/21/2023] [Indexed: 10/26/2023] Open
Abstract
The CRISPR genome editing technology has revolutionized the way gene function is studied. Genome editing can be achieved in single genes or for thousands of genes simultaneously in sensitive genetic screens. While conventional genetic screens are limited to bulk measurements of cell behavior, recent developments in single-cell technologies make it possible to combine CRISPR screening with single-cell profiling. In this way, cell behavior and gene expression can be monitored simultaneously, with the additional possibility of including data on chromatin accessibility and protein levels. Moreover, the availability of various Cas proteins leading to inactivation, activation, or other effects on gene function further broadens the scope of such screens. The integration of single-cell multi-omics approaches with CRISPR screening open the path to high-content information on the impact of genetic perturbations at single-cell resolution. Current limitations in cell throughput and data density need to be taken into consideration, but new technologies are rapidly evolving and are likely to easily overcome these limitations. In this review, we discuss the use of bulk CRISPR screening in hematology research, as well as the emergence of single-cell CRISPR screening and its added value to the field.
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Affiliation(s)
- Sarah Meyers
- Center for Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium
| | - Sofie Demeyer
- Center for Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium
| | - Jan Cools
- Center for Human Genetics, KU Leuven, Leuven, Belgium.
- Center for Cancer Biology, VIB, Leuven, Belgium.
- Leuvens Kanker Instituut (LKI), KU Leuven - UZ Leuven, Leuven, Belgium.
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2
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Audebert M, Assmann AS, Azqueta A, Babica P, Benfenati E, Bortoli S, Bouwman P, Braeuning A, Burgdorf T, Coumoul X, Debizet K, Dusinska M, Ertych N, Fahrer J, Fetz V, Le Hégarat L, López de Cerain A, Heusinkveld HJ, Hogeveen K, Jacobs MN, Luijten M, Raitano G, Recoules C, Rundén-Pran E, Saleh M, Sovadinová I, Stampar M, Thibol L, Tomkiewicz C, Vettorazzi A, Van de Water B, El Yamani N, Zegura B, Oelgeschläger M. New approach methodologies to facilitate and improve the hazard assessment of non-genotoxic carcinogens-a PARC project. FRONTIERS IN TOXICOLOGY 2023; 5:1220998. [PMID: 37492623 PMCID: PMC10364052 DOI: 10.3389/ftox.2023.1220998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 06/19/2023] [Indexed: 07/27/2023] Open
Abstract
Carcinogenic chemicals, or their metabolites, can be classified as genotoxic or non-genotoxic carcinogens (NGTxCs). Genotoxic compounds induce DNA damage, which can be detected by an established in vitro and in vivo battery of genotoxicity assays. For NGTxCs, DNA is not the primary target, and the possible modes of action (MoA) of NGTxCs are much more diverse than those of genotoxic compounds, and there is no specific in vitro assay for detecting NGTxCs. Therefore, the evaluation of the carcinogenic potential is still dependent on long-term studies in rodents. This 2-year bioassay, mainly applied for testing agrochemicals and pharmaceuticals, is time-consuming, costly and requires very high numbers of animals. More importantly, its relevance for human risk assessment is questionable due to the limited predictivity for human cancer risk, especially with regard to NGTxCs. Thus, there is an urgent need for a transition to new approach methodologies (NAMs), integrating human-relevant in vitro assays and in silico tools that better exploit the current knowledge of the multiple processes involved in carcinogenesis into a modern safety assessment toolbox. Here, we describe an integrative project that aims to use a variety of novel approaches to detect the carcinogenic potential of NGTxCs based on different mechanisms and pathways involved in carcinogenesis. The aim of this project is to contribute suitable assays for the safety assessment toolbox for an efficient and improved, internationally recognized hazard assessment of NGTxCs, and ultimately to contribute to reliable mechanism-based next-generation risk assessment for chemical carcinogens.
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Affiliation(s)
- Marc Audebert
- INRAE: Toxalim, INRAE, INP-ENVT, INP-EI-Purpan, Université de Toulouse 3 Paul Sabatier, Toulouse, France
| | - Ann-Sophie Assmann
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
| | - Amaya Azqueta
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, UNAV: University of Navarra, Pamplona, Spain
| | - Pavel Babica
- RECETOX: RECETOX, Faculty of Science, Masaryk University, Brno, Czechia
| | - Emilio Benfenati
- IRFMN: Istituto di Ricerche Farmacologiche Mario Negri—IRCCS, Milan, Italy
| | - Sylvie Bortoli
- INSERM: INSERM UMR-S 1124 T3S—Université Paris Cité, Paris, France
| | - Peter Bouwman
- UL-LACDR: Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Albert Braeuning
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
| | - Tanja Burgdorf
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
| | - Xavier Coumoul
- INSERM: INSERM UMR-S 1124 T3S—Université Paris Cité, Paris, France
| | - Kloé Debizet
- INSERM: INSERM UMR-S 1124 T3S—Université Paris Cité, Paris, France
| | - Maria Dusinska
- Health Effects Laboratory, NILU: The Climate and Environmental Research Institute, Kjeller, Norway
| | - Norman Ertych
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
| | - Jörg Fahrer
- Department of Chemistry, RPTU: Division of Food Chemistry and Toxicology, Kaiserslautern, Germany
| | - Verena Fetz
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
| | - Ludovic Le Hégarat
- ANSES: French Agency for Food, Environmental and Occupational Health and Safety, Fougères Laboratory, Toxicology of Contaminants Unit, Fougères, France
| | - Adela López de Cerain
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, UNAV: University of Navarra, Pamplona, Spain
| | - Harm J. Heusinkveld
- RIVM: National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Kevin Hogeveen
- ANSES: French Agency for Food, Environmental and Occupational Health and Safety, Fougères Laboratory, Toxicology of Contaminants Unit, Fougères, France
| | - Miriam N. Jacobs
- Radiation, Chemical and Environmental Hazards, UKHSA: UK Health Security Agency, Chilton, Oxfordshire, United Kingdom
| | - Mirjam Luijten
- RIVM: National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Giuseppa Raitano
- IRFMN: Istituto di Ricerche Farmacologiche Mario Negri—IRCCS, Milan, Italy
| | - Cynthia Recoules
- INRAE: Toxalim, INRAE, INP-ENVT, INP-EI-Purpan, Université de Toulouse 3 Paul Sabatier, Toulouse, France
| | - Elise Rundén-Pran
- Health Effects Laboratory, NILU: The Climate and Environmental Research Institute, Kjeller, Norway
| | - Mariam Saleh
- ANSES: French Agency for Food, Environmental and Occupational Health and Safety, Fougères Laboratory, Toxicology of Contaminants Unit, Fougères, France
| | - Iva Sovadinová
- RECETOX: RECETOX, Faculty of Science, Masaryk University, Brno, Czechia
| | - Martina Stampar
- Department of Genetic Toxicology and Cancer Biology, NIB: National Institute of Biology, Ljubljana, Slovenia
| | - Lea Thibol
- Department of Chemistry, RPTU: Division of Food Chemistry and Toxicology, Kaiserslautern, Germany
| | | | - Ariane Vettorazzi
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, UNAV: University of Navarra, Pamplona, Spain
| | - Bob Van de Water
- UL-LACDR: Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Naouale El Yamani
- Health Effects Laboratory, NILU: The Climate and Environmental Research Institute, Kjeller, Norway
| | - Bojana Zegura
- Department of Genetic Toxicology and Cancer Biology, NIB: National Institute of Biology, Ljubljana, Slovenia
| | - Michael Oelgeschläger
- Department Experimental Toxicology and ZEBET, German Centre for the Protection of Laboratory Animals (Bf3R) and Department Food Safety, BfR: German Federal Institute for Risk Assessment, Berlin, Germany
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3
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Perez BC, Bink MCAM, Svenson KL, Churchill GA, Calus MPL. Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence. G3 (BETHESDA, MD.) 2022; 12:jkac258. [PMID: 36161485 PMCID: PMC9635642 DOI: 10.1093/g3journal/jkac258] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
Recent developments allowed generating multiple high-quality 'omics' data that could increase the predictive performance of genomic prediction for phenotypes and genetic merit in animals and plants. Here, we have assessed the performance of parametric and nonparametric models that leverage transcriptomics in genomic prediction for 13 complex traits recorded in 478 animals from an outbred mouse population. Parametric models were implemented using the best linear unbiased prediction, while nonparametric models were implemented using the gradient boosting machine algorithm. We also propose a new model named GTCBLUP that aims to remove between-omics-layer covariance from predictors, whereas its counterpart GTBLUP does not do that. While gradient boosting machine models captured more phenotypic variation, their predictive performance did not exceed the best linear unbiased prediction models for most traits. Models leveraging gene transcripts captured higher proportions of the phenotypic variance for almost all traits when these were measured closer to the moment of measuring gene transcripts in the liver. In most cases, the combination of layers was not able to outperform the best single-omics models to predict phenotypes. Using only gene transcripts, the gradient boosting machine model was able to outperform best linear unbiased prediction for most traits except body weight, but the same pattern was not observed when using both single nucleotide polymorphism genotypes and gene transcripts. Although the GTCBLUP model was not able to produce the most accurate phenotypic predictions, it showed the highest accuracies for breeding values for 9 out of 13 traits. We recommend using the GTBLUP model for prediction of phenotypes and using the GTCBLUP for prediction of breeding values.
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Affiliation(s)
- Bruno C Perez
- Hendrix Genetics B.V., Research and Technology Center (RTC), 5830 AC Boxmeer, The Netherlands
| | - Marco C A M Bink
- Hendrix Genetics B.V., Research and Technology Center (RTC), 5830 AC Boxmeer, The Netherlands
| | | | | | - Mario P L Calus
- Corresponding author: Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH Wageningen, The Netherlands.
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4
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Zhang Y, Xu S, Wen Z, Gao J, Li S, Weissman SM, Pan X. Sample-multiplexing approaches for single-cell sequencing. Cell Mol Life Sci 2022; 79:466. [PMID: 35927335 PMCID: PMC11073057 DOI: 10.1007/s00018-022-04482-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/25/2022] [Accepted: 07/11/2022] [Indexed: 12/12/2022]
Abstract
Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.
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Affiliation(s)
- Yulong Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Siwen Xu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
- SequMed BioTechnology, Inc., Guangzhou, Guangdong, China
| | - Zebin Wen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
| | - Jinyu Gao
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China
| | - Shuang Li
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, China
| | - Sherman M Weissman
- Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520-8005, USA
| | - Xinghua Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Shenzhen Bay Laboratory, Shenzhen, Guangdong, China.
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5
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Janjic A, Wange LE, Bagnoli JW, Geuder J, Nguyen P, Richter D, Vieth B, Vick B, Jeremias I, Ziegenhain C, Hellmann I, Enard W. Prime-seq, efficient and powerful bulk RNA sequencing. Genome Biol 2022; 23:88. [PMID: 35361256 PMCID: PMC8969310 DOI: 10.1186/s13059-022-02660-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/23/2022] [Indexed: 12/21/2022] Open
Abstract
Cost-efficient library generation by early barcoding has been central in propelling single-cell RNA sequencing. Here, we optimize and validate prime-seq, an early barcoding bulk RNA-seq method. We show that it performs equivalently to TruSeq, a standard bulk RNA-seq method, but is fourfold more cost-efficient due to almost 50-fold cheaper library costs. We also validate a direct RNA isolation step, show that intronic reads are derived from RNA, and compare cost-efficiencies of available protocols. We conclude that prime-seq is currently one of the best options to set up an early barcoding bulk RNA-seq protocol from which many labs would profit.
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Affiliation(s)
- Aleksandar Janjic
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany.,Graduate School of Systemic Neurosciences, Faculty of Biology, Ludwig-Maximilians University, Martinsried, Germany
| | - Lucas E Wange
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Johannes W Bagnoli
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Johanna Geuder
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Phong Nguyen
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Daniel Richter
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Beate Vieth
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Binje Vick
- Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Irmela Jeremias
- Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians University, Munich, Germany
| | - Christoph Ziegenhain
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
| | - Ines Hellmann
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany
| | - Wolfgang Enard
- Anthropology & Human Genomics, Faculty of Biology, Ludwig-Maximilians University, Großhaderner Str. 2, 82152, Martinsried, Germany.
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6
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Herholt A, Sahoo VK, Popovic L, Wehr MC, Rossner MJ. Dissecting intercellular and intracellular signaling networks with barcoded genetic tools. Curr Opin Chem Biol 2021; 66:102091. [PMID: 34644670 DOI: 10.1016/j.cbpa.2021.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/25/2021] [Accepted: 09/03/2021] [Indexed: 11/19/2022]
Abstract
The power of next-generation sequencing has stimulated the development of many analysis techniques for transcriptomics and genomics. More recently, the concept of 'molecular barcoding' has broadened the spectrum of sequencing-based applications to dissect different aspects of intracellular and intercellular signaling. In these assay formats, barcode reporters replace standard reporter genes. The virtually infinitive number of expressed barcode sequences allows high levels of multiplexing, hence accelerating experimental progress. Furthermore, reporter barcodes are used to quantitatively monitor a variety of biological events in living cells which has already provided much insight into complex cellular signaling and will further increase our knowledge in the future.
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Affiliation(s)
- Alexander Herholt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669 Munich, Germany
| | - Vivek K Sahoo
- Systasy Bioscience GmbH, Balanstr. 6, 81669 Munich, Germany
| | - Luksa Popovic
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669 Munich, Germany
| | - Michael C Wehr
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669 Munich, Germany
| | - Moritz J Rossner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany.
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7
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Cheng J, Liao J, Shao X, Lu X, Fan X. Multiplexing Methods for Simultaneous Large-Scale Transcriptomic Profiling of Samples at Single-Cell Resolution. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101229. [PMID: 34240574 PMCID: PMC8425911 DOI: 10.1002/advs.202101229] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 04/28/2021] [Indexed: 05/19/2023]
Abstract
Barcoding technology has greatly improved the throughput of cells and genes detected in single-cell RNA sequencing (scRNA-seq) studies. Recently, increasing studies have paid more attention to the use of this technology to increase the throughput of samples, as it has greatly reduced the processing time, technical batch effects, and library preparation costs, and lowered the per-sample cost. In this review, the various DNA-based barcoding methods for sample multiplexing are focused on, specifically, on the four major barcoding strategies. A detailed comparison of the barcoding methods is also presented, focusing on aspects such as sample/cell throughput and gene detection, and guidelines for choosing the most appropriate barcoding technique according to the personalized requirements are developed. Finally, the critical applications of sample multiplexing and technical challenges in combinatorial labeling, barcoding in vivo, and multimodal tagging at the spatially resolved resolution, as well as, the future prospects of multiplexed scRNA-seq, for example, prioritizing and predicting the severity of coronavirus disease 2019 (COVID-19) in patients of different gender and age are highlighted.
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Affiliation(s)
- Junyun Cheng
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China
| | - Jie Liao
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China
| | - Xin Shao
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China
| | - Xiaoyan Lu
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China
| | - Xiaohui Fan
- Pharmaceutical Informatics InstituteCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China
- Innovation Center in Zhejiang UniversityState Key Laboratory of Component‐Based Chinese MedicineHangzhou310058China
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8
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Song D, Li K, Hemminger Z, Wollman R, Li JJ. scPNMF: sparse gene encoding of single cells to facilitate gene selection for targeted gene profiling. Bioinformatics 2021; 37:i358-i366. [PMID: 34252925 PMCID: PMC8275345 DOI: 10.1093/bioinformatics/btab273] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Motivation Single-cell RNA sequencing (scRNA-seq) captures whole transcriptome information of individual cells. While scRNA-seq measures thousands of genes, researchers are often interested in only dozens to hundreds of genes for a closer study. Then, a question is how to select those informative genes from scRNA-seq data. Moreover, single-cell targeted gene profiling technologies are gaining popularity for their low costs, high sensitivity and extra (e.g. spatial) information; however, they typically can only measure up to a few hundred genes. Then another challenging question is how to select genes for targeted gene profiling based on existing scRNA-seq data. Results Here, we develop the single-cell Projective Non-negative Matrix Factorization (scPNMF) method to select informative genes from scRNA-seq data in an unsupervised way. Compared with existing gene selection methods, scPNMF has two advantages. First, its selected informative genes can better distinguish cell types. Second, it enables the alignment of new targeted gene profiling data with reference data in a low-dimensional space to facilitate the prediction of cell types in the new data. Technically, scPNMF modifies the PNMF algorithm for gene selection by changing the initialization and adding a basis selection step, which selects informative bases to distinguish cell types. We demonstrate that scPNMF outperforms the state-of-the-art gene selection methods on diverse scRNA-seq datasets. Moreover, we show that scPNMF can guide the design of targeted gene profiling experiments and the cell-type annotation on targeted gene profiling data. Availability and implementation The R package is open-access and available at https://github.com/JSB-UCLA/scPNMF. The data used in this work are available at Zenodo: https://doi.org/10.5281/zenodo.4797997. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Dongyuan Song
- Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA 90095-7246, USA
| | - Kexin Li
- Department of Statistics, University of California, Los Angeles, CA 90095-1554, USA
| | - Zachary Hemminger
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA 90095, USA.,Department of Integrative Biology and Physiology, University of California, Los Angeles, CA 90095-7239, USA
| | - Roy Wollman
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA 90095, USA.,Department of Integrative Biology and Physiology, University of California, Los Angeles, CA 90095-7239, USA.,Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095-1569, USA
| | - Jingyi Jessica Li
- Department of Statistics, University of California, Los Angeles, CA 90095-1554, USA.,Department of Human Genetics, University of California, Los Angeles, CA 90095-7088, USA.,Department of Computational Medicine, University of California, Los Angeles, CA 90095-1766, USA.,Department of Biostatistics, University of California Los Angeles, CA 90095-1772, USA
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9
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Michel S, Wagner C, Nosenko T, Steiner B, Samad-Zamini M, Buerstmayr M, Mayer K, Buerstmayr H. Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat. Genes (Basel) 2021; 12:114. [PMID: 33477759 PMCID: PMC7832326 DOI: 10.3390/genes12010114] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/14/2021] [Accepted: 01/16/2021] [Indexed: 01/13/2023] Open
Abstract
Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future.
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Affiliation(s)
- Sebastian Michel
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
| | - Christian Wagner
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
| | - Tetyana Nosenko
- PGSB Plant Genome and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany; (T.N.); (K.M.)
- Research Unit Environmental Simulation (EUS) at the Institute of Biochemical Plant Pathology (BIOP), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Barbara Steiner
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
| | - Mina Samad-Zamini
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
- Saatzucht Edelhof GmbH, 3910 Zwettl, Austria
| | - Maria Buerstmayr
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
| | - Klaus Mayer
- PGSB Plant Genome and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany; (T.N.); (K.M.)
| | - Hermann Buerstmayr
- Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria; (C.W.); (B.S.); (M.S.-Z.); (M.B.); (H.B.)
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10
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Marshall JL, Doughty BR, Subramanian V, Guckelberger P, Wang Q, Chen LM, Rodriques SG, Zhang K, Fulco CP, Nasser J, Grinkevich EJ, Noel T, Mangiameli S, Bergman DT, Greka A, Lander ES, Chen F, Engreitz JM. HyPR-seq: Single-cell quantification of chosen RNAs via hybridization and sequencing of DNA probes. Proc Natl Acad Sci U S A 2020; 117:33404-33413. [PMID: 33376219 PMCID: PMC7776864 DOI: 10.1073/pnas.2010738117] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of hundreds of chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell-type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome single-cell RNA-sequencing, making HyPR-seq a powerful method for targeted RNA profiling in single cells.
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Affiliation(s)
| | | | | | - Philine Guckelberger
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biology, Chemistry, and Pharmacy, Freie Universität Berlin, 14195 Berlin, Germany
| | - Qingbo Wang
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA 02115
| | - Linlin M Chen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Samuel G Rodriques
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Kaite Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Joseph Nasser
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Teia Noel
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | | | - Anna Greka
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Fei Chen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
| | - Jesse M Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
- Basic Science and Engineering Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA 94305
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11
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Yeldell SB, Yang L, Lee J, Eberwine JH, Dmochowski IJ. Oligonucleotide Probe for Transcriptome in Vivo Analysis (TIVA) of Single Neurons with Minimal Background. ACS Chem Biol 2020; 15:2714-2721. [PMID: 32902259 DOI: 10.1021/acschembio.0c00499] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Messenger RNA (mRNA) isolated from single cells can generate powerful biological insights, including the discovery of new cell types with unique functions as well as markers potentially predicting a cell's response to various therapeutic agents. We previously introduced an oligonucleotide-based technique for site-selective, photoinduced biotinylation and capture of mRNA within a living cell called transcriptome in vivo analysis (TIVA). Successful application of the TIVA technique hinges upon its oligonucleotide probe remaining completely inert (or "caged") to mRNA unless photoactivated. To improve the reliability of TIVA probe caging in diverse and challenging biological conditions, we applied a rational design process involving iterative modifications to the oligonucleotide construct. In this work, we discuss these design motivations and present an optimized probe with minimal background binding to mRNA prior to photolysis. We assess its caging performance through multiple in vitro assays including FRET analysis, native gel comigration, and pull down with model mRNA transcripts. Finally, we demonstrate that this improved probe can also isolate mRNA from single living neurons in brain tissue slices with excellent caging control.
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Affiliation(s)
- Sean B. Yeldell
- Department of Chemistry, University of Pennsylvania, 231 South 34 Street, Philadelphia, Pennsylvania 19104-6323, United States
| | - Linlin Yang
- Department of Chemistry, University of Pennsylvania, 231 South 34 Street, Philadelphia, Pennsylvania 19104-6323, United States
| | - Jaehee Lee
- Department of Pharmacology, University of Pennsylvania, 38 John Morgan Building, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104-6084, United States
| | - James H. Eberwine
- Department of Pharmacology, University of Pennsylvania, 38 John Morgan Building, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104-6084, United States
| | - Ivan J. Dmochowski
- Department of Chemistry, University of Pennsylvania, 231 South 34 Street, Philadelphia, Pennsylvania 19104-6323, United States
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12
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Harris T, Sheel A, Zong Y, Hutchinson LM, Cornejo KM, Bubendorf L, Yates J, Fischer AH. Cytologically targeted next-generation sequencing: a synergy for diagnosing urothelial carcinoma. J Am Soc Cytopathol 2020; 10:94-102. [PMID: 33184010 DOI: 10.1016/j.jasc.2020.10.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/05/2020] [Accepted: 10/06/2020] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Cytology and cystoscopy are used to detect urothelial carcinoma (UC), but together they still fail to detect some UC cases and are not suitable for screening asymptomatic individuals. Mutations are present in more than 98% of UC, mutations have therapeutic significance, and they can be detected by next generation sequencing (NGS) in urine samples. We review the role of NGS in UC detection. MATERIALS AND METHODS Comprehensive literature review on UC genetics, economics of NGS, and previous reports of UC detection by NGS. RESULTS The raw costs of NGS have decreased to about 14,000 base pairs per penny, making it appear economically feasible to use NGS widely. Reported NGS assays fall short of predicted sensitivity. Decreased sensitivity is attributed to a low frequency of mutant alleles in many urine samples. Attempts to increase the percentage of mutant alleles, by using cell-free urinary DNA, or by using cell sorting and microfluidics, have been unsuccessful or remain unproven. However, cytologic examination can immediately enable NGS: Urine cytologies with sufficient proportions of abnormal cells could be directly triaged to NGS with high sensitivity for UC detection. For cases with a low proportion of abnormal cells, cytologically targeted microdissection of cells for NGS should maintain sensitivity and decrease sequencing costs. Cytologically targeted urothelial cells for NGS could allow a screening test for low grade UC. CONCLUSIONS Cytology is immediately poised to allow NGS to improve the diagnosis of UC, allowing NGS to be an ancillary test for atypical cytologies, and potentially allowing a screening test for low-grade UC.
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Affiliation(s)
- Taylor Harris
- University of Massachusetts Medical School, Worcester, Massachusetts
| | - Ankur Sheel
- University of Massachusetts Medical School, Worcester, Massachusetts
| | - Yang Zong
- Department of Pathology, University of Massachusetts Memorial Health Care, Worcester, Massachusetts
| | - Lloyd M Hutchinson
- Department of Pathology, University of Massachusetts Memorial Health Care, Worcester, Massachusetts
| | - Kristine M Cornejo
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Lukas Bubendorf
- Department of Pathology, University of Basel, Basel, Switzerland
| | - Jennifer Yates
- Department of Urology, University of Massachusetts Memorial Health Care, Worcester, Massachusetts
| | - Andrew H Fischer
- Department of Pathology, University of Massachusetts Memorial Health Care, Worcester, Massachusetts.
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13
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Schraivogel D, Gschwind AR, Milbank JH, Leonce DR, Jakob P, Mathur L, Korbel JO, Merten CA, Velten L, Steinmetz LM. Targeted Perturb-seq enables genome-scale genetic screens in single cells. Nat Methods 2020; 17:629-635. [PMID: 32483332 DOI: 10.1038/s41592-020-0837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 04/15/2020] [Indexed: 05/28/2023]
Abstract
The transcriptome contains rich information on molecular, cellular and organismal phenotypes. However, experimental and statistical limitations constrain sensitivity and throughput of genetic screening with single-cell transcriptomics readout. To overcome these limitations, we introduce targeted Perturb-seq (TAP-seq), a sensitive, inexpensive and platform-independent method focusing single-cell RNA-seq coverage on genes of interest, thereby increasing the sensitivity and scale of genetic screens by orders of magnitude. TAP-seq permits routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. We apply TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5% of the human genome. We thereby show that enhancer-target association is jointly determined by three-dimensional contact frequency and epigenetic states, allowing accurate prediction of enhancer targets throughout the genome. In addition, we demonstrate that TAP-seq can identify cell subtypes with only 100 sequencing reads per cell.
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Affiliation(s)
- Daniel Schraivogel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Andreas R Gschwind
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jennifer H Milbank
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Daniel R Leonce
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Petra Jakob
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Lukas Mathur
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Christoph A Merten
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Lars Velten
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
- Center for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.
| | - Lars M Steinmetz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Genome Technology Center, Palo Alto, CA, USA.
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14
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Schraivogel D, Gschwind AR, Milbank JH, Leonce DR, Jakob P, Mathur L, Korbel JO, Merten CA, Velten L, Steinmetz LM. Targeted Perturb-seq enables genome-scale genetic screens in single cells. Nat Methods 2020; 17:629-635. [PMID: 32483332 PMCID: PMC7610614 DOI: 10.1038/s41592-020-0837-5] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 04/15/2020] [Indexed: 12/15/2022]
Abstract
The transcriptome contains rich information on molecular, cellular and organismal phenotypes. However, experimental and statistical limitations constrain sensitivity and throughput of genetic screening with single-cell transcriptomics readout. To overcome these limitations, we introduce targeted Perturb-seq (TAP-seq), a sensitive, inexpensive and platform-independent method focusing single-cell RNA-seq coverage on genes of interest, thereby increasing the sensitivity and scale of genetic screens by orders of magnitude. TAP-seq permits routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. We apply TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5% of the human genome. We thereby show that enhancer-target association is jointly determined by three-dimensional contact frequency and epigenetic states, allowing accurate prediction of enhancer targets throughout the genome. In addition, we demonstrate that TAP-seq can identify cell subtypes with only 100 sequencing reads per cell.
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Affiliation(s)
- Daniel Schraivogel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Andreas R Gschwind
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jennifer H Milbank
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Daniel R Leonce
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Petra Jakob
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Lukas Mathur
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Christoph A Merten
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Lars Velten
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
- Center for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.
| | - Lars M Steinmetz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Genome Technology Center, Palo Alto, CA, USA.
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15
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Herholt A, Galinski S, Geyer PE, Rossner MJ, Wehr MC. Multiparametric Assays for Accelerating Early Drug Discovery. Trends Pharmacol Sci 2020; 41:318-335. [PMID: 32223968 DOI: 10.1016/j.tips.2020.02.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/21/2020] [Accepted: 02/27/2020] [Indexed: 02/07/2023]
Abstract
Drug discovery campaigns are hampered by substantial attrition rates largely due to a lack of efficacy and safety reasons associated with candidate drugs. This is true in particular for genetically complex diseases, where insufficient knowledge of the modulatory actions of candidate drugs on targets and entire target pathways further adds to the problem of attrition. To better profile compound actions on targets, potential off-targets, and disease-linked pathways, new innovative technologies need to be developed that can elucidate the complex cellular signaling networks in health and disease. Here, we discuss progress in genetically encoded multiparametric assays and mass spectrometry (MS)-based proteomics, which both represent promising toolkits to profile multifactorial actions of drug candidates in disease-relevant cellular systems to promote drug discovery and personalized medicine.
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Affiliation(s)
- Alexander Herholt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany
| | - Sabrina Galinski
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany
| | - Philipp E Geyer
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Planegg, Germany; NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; OmicEra Diagnostics GmbH, Am Klopferspitz 19, 82152, Planegg, Germany
| | - Moritz J Rossner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany
| | - Michael C Wehr
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstr. 7, 80336 Munich, Germany; Systasy Bioscience GmbH, Balanstr. 6, 81669, Munich, Germany.
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16
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Uzbas F, Opperer F, Sönmezer C, Shaposhnikov D, Sass S, Krendl C, Angerer P, Theis FJ, Mueller NS, Drukker M. BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis. Genome Biol 2019; 20:155. [PMID: 31387612 PMCID: PMC6683345 DOI: 10.1186/s13059-019-1748-6] [Citation(s) in RCA: 15] [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: 06/01/2019] [Accepted: 06/25/2019] [Indexed: 01/22/2023] Open
Abstract
We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/β-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.
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Affiliation(s)
- Fatma Uzbas
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Florian Opperer
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Can Sönmezer
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Dmitry Shaposhnikov
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Steffen Sass
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Christian Krendl
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Philipp Angerer
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Fabian J. Theis
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Department of Mathematics, Technical University Munich, 85748 Garching, Germany
| | - Nikola S. Mueller
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Micha Drukker
- Institute of Stem Cell Research, Helmholtz Center Munich, 85764 Neuherberg, Germany
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