51
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Armendariz DA, Sundarrajan A, Hon GC. Breaking enhancers to gain insights into developmental defects. eLife 2023; 12:e88187. [PMID: 37497775 PMCID: PMC10374278 DOI: 10.7554/elife.88187] [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: 03/29/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.
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Affiliation(s)
- Daniel A Armendariz
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Anjana Sundarrajan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, United States
- Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States
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52
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Ren X, Yang H, Nierenberg JL, Sun Y, Chen J, Beaman C, Pham T, Nobuhara M, Takagi MA, Narayan V, Li Y, Ziv E, Shen Y. High throughput PRIME editing screens identify functional DNA variants in the human genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548736. [PMID: 37502948 PMCID: PMC10370011 DOI: 10.1101/2023.07.12.548736] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and base-pair resolution manner remains challenging. Here, we develop a novel pooled prime editing screen method, PRIME, which can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated saturation mutagenesis. Next, we applied PRIME to functionally characterize 1,304 non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate PRIME capable of characterizing genetic variants at base-pair resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.
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Affiliation(s)
- Xingjie Ren
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Han Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Jovia L. Nierenberg
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Yifan Sun
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Cooper Beaman
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Thu Pham
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Mai Nobuhara
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Maya Asami Takagi
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Vivek Narayan
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Elad Ziv
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of General Internal Medicine, Department of Medicine, and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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53
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Lue NZ, Liau BB. Base editor screens for in situ mutational scanning at scale. Mol Cell 2023; 83:2167-2187. [PMID: 37390819 PMCID: PMC10330937 DOI: 10.1016/j.molcel.2023.06.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 07/02/2023]
Abstract
A fundamental challenge in biology is understanding the molecular details of protein function. How mutations alter protein activity, regulation, and response to drugs is of critical importance to human health. Recent years have seen the emergence of pooled base editor screens for in situ mutational scanning: the interrogation of protein sequence-function relationships by directly perturbing endogenous proteins in live cells. These studies have revealed the effects of disease-associated mutations, discovered novel drug resistance mechanisms, and generated biochemical insights into protein function. Here, we discuss how this "base editor scanning" approach has been applied to diverse biological questions, compare it with alternative techniques, and describe the emerging challenges that must be addressed to maximize its utility. Given its broad applicability toward profiling mutations across the proteome, base editor scanning promises to revolutionize the investigation of proteins in their native contexts.
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Affiliation(s)
- Nicholas Z Lue
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brian B Liau
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
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54
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Tang YJ, Shuldiner EG, Karmakar S, Winslow MM. High-Throughput Identification, Modeling, and Analysis of Cancer Driver Genes In Vivo. Cold Spring Harb Perspect Med 2023; 13:a041382. [PMID: 37277208 PMCID: PMC10317066 DOI: 10.1101/cshperspect.a041382] [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] [Indexed: 06/07/2023]
Abstract
The vast number of genomic and molecular alterations in cancer pose a substantial challenge to uncovering the mechanisms of tumorigenesis and identifying therapeutic targets. High-throughput functional genomic methods in genetically engineered mouse models allow for rapid and systematic investigation of cancer driver genes. In this review, we discuss the basic concepts and tools for multiplexed investigation of functionally important cancer genes in vivo using autochthonous cancer models. Furthermore, we highlight emerging technical advances in the field, potential opportunities for future investigation, and outline a vision for integrating multiplexed genetic perturbations with detailed molecular analyses to advance our understanding of the genetic and molecular basis of cancer.
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Affiliation(s)
- Yuning J Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Emily G Shuldiner
- Department of Biology, Stanford University, Stanford, California 94305, USA
| | - Saswati Karmakar
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Monte M Winslow
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California 94305, USA
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55
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Stevenson ZC, Moerdyk-Schauwecker MJ, Banse SA, Patel DS, Lu H, Phillips PC. High-throughput library transgenesis in Caenorhabditis elegans via Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS). eLife 2023; 12:RP84831. [PMID: 37401921 PMCID: PMC10328503 DOI: 10.7554/elife.84831] [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] [Indexed: 07/05/2023] Open
Abstract
High-throughput transgenesis using synthetic DNA libraries is a powerful method for systematically exploring genetic function. Diverse synthesized libraries have been used for protein engineering, identification of protein-protein interactions, characterization of promoter libraries, developmental and evolutionary lineage tracking, and various other exploratory assays. However, the need for library transgenesis has effectively restricted these approaches to single-cell models. Here, we present Transgenic Arrays Resulting in Diversity of Integrated Sequences (TARDIS), a simple yet powerful approach to large-scale transgenesis that overcomes typical limitations encountered in multicellular systems. TARDIS splits the transgenesis process into a two-step process: creation of individuals carrying experimentally introduced sequence libraries, followed by inducible extraction and integration of individual sequences/library components from the larger library cassette into engineered genomic sites. Thus, transformation of a single individual, followed by lineage expansion and functional transgenesis, gives rise to thousands of genetically unique transgenic individuals. We demonstrate the power of this system using engineered, split selectable TARDIS sites in Caenorhabditis elegans to generate (1) a large set of individually barcoded lineages and (2) transcriptional reporter lines from predefined promoter libraries. We find that this approach increases transformation yields up to approximately 1000-fold over current single-step methods. While we demonstrate the utility of TARDIS using C. elegans, in principle the process is adaptable to any system where experimentally generated genomic loci landing pads and diverse, heritable DNA elements can be generated.
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Affiliation(s)
| | | | - Stephen A Banse
- Institute of Ecology and Evolution, University of OregonEugeneUnited States
| | - Dhaval S Patel
- School of Chemical & Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
- Petit Institute for Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
| | - Hang Lu
- School of Chemical & Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
- Petit Institute for Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
| | - Patrick C Phillips
- Institute of Ecology and Evolution, University of OregonEugeneUnited States
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56
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Li K, Ouyang M, Zhan J, Tian R. CRISPR-based functional genomics screening in human-pluripotent-stem-cell-derived cell types. CELL GENOMICS 2023; 3:100300. [PMID: 37228745 PMCID: PMC10203043 DOI: 10.1016/j.xgen.2023.100300] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
While our knowledge of gene expression in different human cell types is rapidly expanding with advances in transcriptomic profiling technologies, the next challenge is to understand gene function in each cell type. CRISPR-Cas9-based functional genomics screening offers a powerful approach to determine gene function in a high-throughput manner. With the maturation of stem cell technology, a variety of human cell types can be derived from human pluripotent stem cells (hPSCs). Recently, the integration of CRISPR screening with hPSC differentiation technologies opens up unprecedented opportunities to systematically examine gene function in different human cell types and identify mechanisms and therapeutic targets for human diseases. This review highlights recent progress in the development and applications of CRISPR-Cas9-based functional genomics screening in hPSC-derived cell types, discusses current challenges and limitations, and outlines future directions for this emerging field.
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Affiliation(s)
- Kun Li
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
| | - Miao Ouyang
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
| | - Jiangshan Zhan
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
| | - Ruilin Tian
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
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57
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Smith C, Kitzman JO. Benchmarking splice variant prediction algorithms using massively parallel splicing assays. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.04.539398. [PMID: 37205456 PMCID: PMC10187268 DOI: 10.1101/2023.05.04.539398] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes. Results We benchmarked eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compared experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, was lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieved the best overall performance at distinguishing disruptive and neutral variants. Controlling for overall call rate genome-wide, SpliceAI and Pangolin also showed superior overall sensitivity for identifying SDVs. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues. Conclusion SpliceAI and Pangolin showed the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.
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Affiliation(s)
- Cathy Smith
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Jacob O. Kitzman
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
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58
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Han JL, Entcheva E. Gene Modulation with CRISPR-based Tools in Human iPSC-Cardiomyocytes. Stem Cell Rev Rep 2023; 19:886-905. [PMID: 36656467 PMCID: PMC9851124 DOI: 10.1007/s12015-023-10506-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/09/2023] [Indexed: 01/20/2023]
Abstract
Precise control of gene expression (knock-out, knock-in, knockdown or overexpression) is at the heart of functional genomics - an approach to dissect the contribution of a gene/protein to the system's function. The development of a human in vitro system that can be patient-specific, induced pluripotent stem cells, iPSC, and the ability to obtain various cell types of interest, have empowered human disease modeling and therapeutic development. Scalable tools have been deployed for gene modulation in these cells and derivatives, including pharmacological means, DNA-based RNA interference and standard RNA interference (shRNA/siRNA). The CRISPR/Cas9 gene editing system, borrowed from bacteria and adopted for use in mammalian cells a decade ago, offers cell-specific genetic targeting and versatility. Outside genome editing, more subtle, time-resolved gene modulation is possible by using a catalytically "dead" Cas9 enzyme linked to an effector of gene transcription in combination with a guide RNA. The CRISPRi / CRISPRa (interference/activation) system evolved over the last decade as a scalable technology for performing functional genomics with libraries of gRNAs. Here, we review key developments of these approaches and their deployment in cardiovascular research. We discuss specific use with iPSC-cardiomyocytes and the challenges in further translation of these techniques.
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Affiliation(s)
- Julie Leann Han
- Department of Biomedical Engineering, The George Washington University, 800 22nd St NW, Suite 5000, Washington, DC, 20052, USA
| | - Emilia Entcheva
- Department of Biomedical Engineering, The George Washington University, 800 22nd St NW, Suite 5000, Washington, DC, 20052, USA.
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59
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Yu G, Kim HK, Park J, Kwak H, Cheong Y, Kim D, Kim J, Kim J, Kim HH. Prediction of efficiencies for diverse prime editing systems in multiple cell types. Cell 2023; 186:2256-2272.e23. [PMID: 37119812 DOI: 10.1016/j.cell.2023.03.034] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/02/2022] [Accepted: 03/29/2023] [Indexed: 05/01/2023]
Abstract
Applications of prime editing are often limited due to insufficient efficiencies, and it can require substantial time and resources to determine the most efficient pegRNAs and prime editors (PEs) to generate a desired edit under various experimental conditions. Here, we evaluated prime editing efficiencies for a total of 338,996 pairs of pegRNAs including 3,979 epegRNAs and target sequences in an error-free manner. These datasets enabled a systematic determination of factors affecting prime editing efficiencies. Then, we developed computational models, named DeepPrime and DeepPrime-FT, that can predict prime editing efficiencies for eight prime editing systems in seven cell types for all possible types of editing of up to 3 base pairs. We also extensively profiled the prime editing efficiencies at mismatched targets and developed a computational model predicting editing efficiencies at such targets. These computational models, together with our improved knowledge about prime editing efficiency determinants, will greatly facilitate prime editing applications.
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Affiliation(s)
- Goosang Yu
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Hui Kwon Kim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jinman Park
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Hyunjong Kwak
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Yumin Cheong
- Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Dongyoung Kim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Jiyun Kim
- Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jisung Kim
- Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Hyongbum Henry Kim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of Korea; Yonsei-IBS Institute, Yonsei University, Seoul 03722, Republic of Korea; Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Otolaryngology, University of California, San Francisco, San Francisco, CA 94115, USA.
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60
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Ang RML, Chen SAA, Kern AF, Xie Y, Fraser HB. Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing. CELL GENOMICS 2023; 3:100260. [PMID: 37082144 PMCID: PMC10112194 DOI: 10.1016/j.xgen.2023.100260] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/27/2022] [Accepted: 01/06/2023] [Indexed: 04/22/2023]
Abstract
The phenotypic effect of any genetic variant can be altered by variation at other genomic loci. Known as epistasis, these genetic interactions shape the genotype-phenotype map of every species, yet their origins remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four strains of Saccharomyces cerevisiae. About 31% of variants affect fitness, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions and that these interactions can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis with single-nucleotide resolution, revealing widespread epistasis among beneficial variants.
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Affiliation(s)
- Roy Moh Lik Ang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Shi-An A. Chen
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Alexander F. Kern
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Yihua Xie
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Hunter B. Fraser
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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Li X, Chen W, Martin BK, Calderon D, Lee C, Choi J, Chardon FM, McDiarmid T, Kim H, Lalanne JB, Nathans JF, Shendure J. Chromatin context-dependent regulation and epigenetic manipulation of prime editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.12.536587. [PMID: 37090511 PMCID: PMC10120711 DOI: 10.1101/2023.04.12.536587] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Prime editing is a powerful means of introducing precise changes to specific locations in mammalian genomes. However, the widely varying efficiency of prime editing across target sites of interest has limited its adoption in the context of both basic research and clinical settings. Here, we set out to exhaustively characterize the impact of the cis- chromatin environment on prime editing efficiency. Using a newly developed and highly sensitive method for mapping the genomic locations of a randomly integrated "sensor", we identify specific epigenetic features that strongly correlate with the highly variable efficiency of prime editing across different genomic locations. Next, to assess the interaction of trans -acting factors with the cis -chromatin environment, we develop and apply a pooled genetic screening approach with which the impact of knocking down various DNA repair factors on prime editing efficiency can be stratified by cis -chromatin context. Finally, we demonstrate that we can dramatically modulate the efficiency of prime editing through epigenome editing, i.e. altering chromatin state in a locus-specific manner in order to increase or decrease the efficiency of prime editing at a target site. Looking forward, we envision that the insights and tools described here will broaden the range of both basic research and therapeutic contexts in which prime editing is useful.
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Ahmed M, Muffat J, Li Y. Understanding neural development and diseases using CRISPR screens in human pluripotent stem cell-derived cultures. Front Cell Dev Biol 2023; 11:1158373. [PMID: 37101616 PMCID: PMC10123288 DOI: 10.3389/fcell.2023.1158373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/30/2023] [Indexed: 04/28/2023] Open
Abstract
The brain is arguably the most complex part of the human body in form and function. Much remains unclear about the molecular mechanisms that regulate its normal and pathological physiology. This lack of knowledge largely stems from the inaccessible nature of the human brain, and the limitation of animal models. As a result, brain disorders are difficult to understand and even more difficult to treat. Recent advances in generating human pluripotent stem cells (hPSCs)-derived 2-dimensional (2D) and 3-dimensional (3D) neural cultures have provided an accessible system to model the human brain. Breakthroughs in gene editing technologies such as CRISPR/Cas9 further elevate the hPSCs into a genetically tractable experimental system. Powerful genetic screens, previously reserved for model organisms and transformed cell lines, can now be performed in human neural cells. Combined with the rapidly expanding single-cell genomics toolkit, these technological advances culminate to create an unprecedented opportunity to study the human brain using functional genomics. This review will summarize the current progress of applying CRISPR-based genetic screens in hPSCs-derived 2D neural cultures and 3D brain organoids. We will also evaluate the key technologies involved and discuss their related experimental considerations and future applications.
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Affiliation(s)
- Mai Ahmed
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Julien Muffat
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Yun Li
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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63
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Pfrieger FW. The Niemann-Pick type diseases – A synopsis of inborn errors in sphingolipid and cholesterol metabolism. Prog Lipid Res 2023; 90:101225. [PMID: 37003582 DOI: 10.1016/j.plipres.2023.101225] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/27/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023]
Abstract
Disturbances of lipid homeostasis in cells provoke human diseases. The elucidation of the underlying mechanisms and the development of efficient therapies represent formidable challenges for biomedical research. Exemplary cases are two rare, autosomal recessive, and ultimately fatal lysosomal diseases historically named "Niemann-Pick" honoring the physicians, whose pioneering observations led to their discovery. Acid sphingomyelinase deficiency (ASMD) and Niemann-Pick type C disease (NPCD) are caused by specific variants of the sphingomyelin phosphodiesterase 1 (SMPD1) and NPC intracellular cholesterol transporter 1 (NPC1) or NPC intracellular cholesterol transporter 2 (NPC2) genes that perturb homeostasis of two key membrane components, sphingomyelin and cholesterol, respectively. Patients with severe forms of these diseases present visceral and neurologic symptoms and succumb to premature death. This synopsis traces the tortuous discovery of the Niemann-Pick diseases, highlights important advances with respect to genetic culprits and cellular mechanisms, and exposes efforts to improve diagnosis and to explore new therapeutic approaches.
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64
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Gundry M, Sankaran VG. Hacking hematopoiesis - emerging tools for examining variant effects. Dis Model Mech 2023; 16:dmm049857. [PMID: 36826849 PMCID: PMC9983777 DOI: 10.1242/dmm.049857] [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] [Indexed: 02/25/2023] Open
Abstract
Hematopoiesis is a continuous process of blood and immune cell production. It is orchestrated by thousands of gene products that respond to extracellular signals by guiding cell fate decisions to meet the needs of the organism. Although much of our knowledge of this process comes from work in model systems, we have learned a great deal from studies on human genetic variation. Considerable insight has emerged from studies on presumed monogenic blood disorders, which continue to provide key insights into the mechanisms critical for hematopoiesis. Furthermore, the emergence of large-scale biobanks and cohorts has uncovered thousands of genomic loci associated with blood cell traits and diseases. Some of these blood cell trait-associated loci act as modifiers of what were once thought to be monogenic blood diseases. However, most of these loci await functional validation. Here, we discuss the validation bottleneck and emerging methods to more effectively connect variant to function. In particular, we highlight recent innovations in genome editing, which have paved the path forward for high-throughput functional assessment of loci. Finally, we discuss existing barriers to progress, including challenges in manipulating the genomes of primary hematopoietic cells.
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Affiliation(s)
- Michael Gundry
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vijay G. Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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65
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Chen PJ, Liu DR. Prime editing for precise and highly versatile genome manipulation. Nat Rev Genet 2023; 24:161-177. [PMID: 36344749 PMCID: PMC10989687 DOI: 10.1038/s41576-022-00541-1] [Citation(s) in RCA: 152] [Impact Index Per Article: 152.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/30/2022] [Indexed: 11/09/2022]
Abstract
Programmable gene-editing tools have transformed the life sciences and have shown potential for the treatment of genetic disease. Among the CRISPR-Cas technologies that can currently make targeted DNA changes in mammalian cells, prime editors offer an unusual combination of versatility, specificity and precision. Prime editors do not require double-strand DNA breaks and can make virtually any substitution, small insertion and small deletion within the DNA of living cells. Prime editing minimally requires a programmable nickase fused to a polymerase enzyme, and an extended guide RNA that both specifies the target site and templates the desired genome edit. In this Review, we summarize prime editing strategies to generate programmed genomic changes, highlight their limitations and recent developments that circumvent some of these bottlenecks, and discuss applications and future directions.
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Affiliation(s)
- Peter J Chen
- Merkin Institute of Transformative Technologies in Healthcare, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
| | - David R Liu
- Merkin Institute of Transformative Technologies in Healthcare, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA.
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66
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Costain G, Andrade DM. Third-generation computational approaches for genetic variant interpretation. Brain 2023; 146:411-412. [PMID: 36691296 DOI: 10.1093/brain/awad011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 12/20/2022] [Indexed: 01/25/2023] Open
Abstract
This scientific commentary refers to ‘Delineation of functionally essential protein regions for 242 neurodevelopmental genes’ by Iqbal et al. (https://doi.org/10.1093/brain/awac381).
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Affiliation(s)
- Gregory Costain
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, and Program in Genetics & Genome Biology, SickKids Research Institute, Toronto, ON, Canada.,Department of Paediatrics, University of Toronto, Toronto, ON, Canada.,Departments of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Danielle M Andrade
- Adult Genetic Epilepsy (AGE) Program, Toronto Western Hospital, Krembil Brain Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
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67
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Huang S, Baskin JM. Adding a Chemical Biology Twist to CRISPR Screening. Isr J Chem 2023; 63:e202200056. [PMID: 37588264 PMCID: PMC10427134 DOI: 10.1002/ijch.202200056] [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: 08/21/2022] [Indexed: 11/09/2022]
Abstract
In less than a decade, CRISPR screening has revolutionized forward genetics and cell and molecular biology. Advances in screening technologies, including sgRNA libraries, Cas9-expressing cell lines, and streamlined sequencing pipelines, have democratized pooled CRISPR screens at genome-wide scale. Initially, many such screens were survival-based, identifying essential genes in physiological or perturbed processes. With the application of new chemical biology tools to CRISPR screening, the phenotypic space is no longer limited to live/dead selection or screening for levels of conventional fluorescent protein reporters. Further, the resolution has been increased from cell populations to single cells or even the subcellular level. We highlight advances in pooled CRISPR screening, powered by chemical biology, that have expanded phenotypic space, resolution, scope, and scalability as well as strengthened the CRISPR/Cas enzyme toolkit to enable biological hypothesis generation and discovery.
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Affiliation(s)
- Shiying Huang
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853 USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853 USA
| | - Jeremy M Baskin
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853 USA
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853 USA
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68
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Abstract
The advent of clustered regularly interspaced short palindromic repeat (CRISPR) genome editing, coupled with advances in computing and imaging capabilities, has initiated a new era in which genetic diseases and individual disease susceptibilities are both predictable and actionable. Likewise, genes responsible for plant traits can be identified and altered quickly, transforming the pace of agricultural research and plant breeding. In this Review, we discuss the current state of CRISPR-mediated genetic manipulation in human cells, animals, and plants along with relevant successes and challenges and present a roadmap for the future of this technology.
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Affiliation(s)
- Joy Y Wang
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA.,Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Jennifer A Doudna
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, USA.,Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA.,Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.,California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA.,Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Gladstone Institutes, University of California, San Francisco, San Francisco, CA, USA.,Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
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69
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Cologna SM, Pathmasiri KC, Pergande MR, Rosenhouse-Dantsker A. Alterations in Cholesterol and Phosphoinositides Levels in the Intracellular Cholesterol Trafficking Disorder NPC. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1422:143-165. [PMID: 36988880 DOI: 10.1007/978-3-031-21547-6_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Lipid mistrafficking is a biochemical hallmark of Niemann-Pick Type C (NPC) disease and is classically characterized with endo/lysosomal accumulation of unesterified cholesterol due to genetic mutations in the cholesterol transporter proteins NPC1 and NPC2. Storage of this essential signaling lipid leads to a sequence of downstream events, including oxidative stress, calcium imbalance, neuroinflammation, and progressive neurodegeneration, another hallmark of NPC disease. These observations have been validated in a growing number of studies ranging from NPC cell cultures and animal models to patient specimens. In recent reports, alterations in the levels of another class of critical signaling lipids, namely phosphoinositides, have been described in NPC disease. Focusing on cholesterol and phosphoinositides, the chapter begins by reviewing the interactions of NPC proteins with cholesterol and their role in cholesterol transport. It then continues to describe the modulation of cholesterol efflux in NPC disease. The chapter concludes with a summary of findings related to the functional consequences of perturbations in phosphoinositides in this fatal disease.
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Affiliation(s)
| | | | - Melissa R Pergande
- Department of Chemistry, University of Illinois Chicago, Chicago, IL, USA
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70
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Scott A, Hernandez F, Chamberlin A, Smith C, Karam R, Kitzman JO. Saturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome. Genome Biol 2022; 23:266. [PMID: 36550560 PMCID: PMC9773515 DOI: 10.1186/s13059-022-02839-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Lynch syndrome (LS) is a cancer predisposition syndrome affecting more than 1 in every 300 individuals worldwide. Clinical genetic testing for LS can be life-saving but is complicated by the heavy burden of variants of uncertain significance (VUS), especially missense changes. RESULT To address this challenge, we leverage a multiplexed analysis of variant effect (MAVE) map covering >94% of the 17,746 possible missense variants in the key LS gene MSH2. To establish this map's utility in large-scale variant reclassification, we overlay it on clinical databases of >15,000 individuals with LS gene variants uncovered during clinical genetic testing. We validate these functional measurements in a cohort of individuals with paired tumor-normal test results and find that MAVE-based function scores agree with the clinical interpretation for every one of the MSH2 missense variants with an available classification. We use these scores to attempt reclassification for 682 unique missense VUS, among which 34 scored as deleterious by our function map, in line with previously published rates for other cancer predisposition genes. Combining functional data and other evidence, ten missense VUS are reclassified as pathogenic/likely pathogenic, and another 497 could be moved to benign/likely benign. Finally, we apply these functional scores to paired tumor-normal genetic tests and identify a subset of patients with biallelic somatic loss of function, reflecting a sporadic Lynch-like Syndrome with distinct implications for treatment and relatives' risk. CONCLUSION This study demonstrates how high-throughput functional assays can empower scalable VUS resolution and prospectively generate strong evidence for variant classification.
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Affiliation(s)
- Anthony Scott
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Division of Genetic Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Felicia Hernandez
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA
| | - Adam Chamberlin
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA
| | - Cathy Smith
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Rachid Karam
- grid.465138.d0000 0004 0455 211XAmbry Genetics, Aliso Viejo, CA 92656 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Jacob O. Kitzman
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA
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71
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Sreenivasan VKA, Henck J, Spielmann M. Single-cell sequencing: promises and challenges for human genetics. MED GENET-BERLIN 2022; 34:261-273. [PMID: 38836091 PMCID: PMC11006387 DOI: 10.1515/medgen-2022-2156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Over the last decade, single-cell sequencing has transformed many fields. It has enabled the unbiased molecular phenotyping of even whole organisms with unprecedented cellular resolution. In the field of human genetics, where the phenotypic consequences of genetic and epigenetic alterations are of central concern, this transformative technology promises to functionally annotate every region in the human genome and all possible variants within them at a massive scale. In this review aimed at the clinicians in human genetics, we describe the current status of the field of single-cell sequencing and its role for human genetics, including how the technology works as well as how it is being applied to characterize and monitor diseases, to develop human cell atlases, and to annotate the genome.
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Affiliation(s)
- Varun K A Sreenivasan
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, 23562 Lübeck, 24105 Kiel, Germany
| | - Jana Henck
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, 23562 Lübeck, 24105 Kiel, Germany
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany
| | - Malte Spielmann
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck and Kiel University, 23562 Lübeck, 24105 Kiel, Germany
- Human Molecular Genomics Group, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany
- DZHK e. V. (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, 23538 Lübeck, Germany
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72
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Dace P, Findlay GM. Reducing uncertainty in genetic testing with Saturation Genome Editing. MED GENET-BERLIN 2022; 34:297-304. [PMID: 38836089 PMCID: PMC11006300 DOI: 10.1515/medgen-2022-2159] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Accurate interpretation of human genetic data is critical for optimizing outcomes in the era of genomic medicine. Powerful methods for testing genetic variants for functional effects are allowing researchers to characterize thousands of variants across disease genes. Here, we review experimental tools enabling highly scalable assays of variants, focusing specifically on Saturation Genome Editing (SGE). We discuss examples of how this technique is being implemented for variant testing at scale and describe how SGE data for BRCA1 have been clinically validated and used to aid variant interpretation. The initial success at predicting variant pathogenicity with SGE has spurred efforts to expand this and related techniques to many more genes.
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Affiliation(s)
- Phoebe Dace
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
| | - Gregory M Findlay
- The Genome Function Laboratory, The Francis Crick Institute, 1 Midland Rd, London, United Kingdom
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73
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Tabet D, Parikh V, Mali P, Roth FP, Claussnitzer M. Scalable Functional Assays for the Interpretation of Human Genetic Variation. Annu Rev Genet 2022; 56:441-465. [PMID: 36055970 DOI: 10.1146/annurev-genet-072920-032107] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.
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Affiliation(s)
- Daniel Tabet
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Victoria Parikh
- Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Prashant Mali
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Frederick P Roth
- Donnelly Centre, Department of Molecular Genetics, and Department of Computer Science, University of Toronto, Toronto, Ontario, Canada;
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Genomic Medicine and Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA;
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74
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Hopkins CE, Brock T, Caulfield TR, Bainbridge M. Phenotypic screening models for rapid diagnosis of genetic variants and discovery of personalized therapeutics. Mol Aspects Med 2022; 91:101153. [PMID: 36411139 PMCID: PMC10073243 DOI: 10.1016/j.mam.2022.101153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/22/2022] [Accepted: 10/23/2022] [Indexed: 11/19/2022]
Abstract
Precision medicine strives for highly individualized treatments for disease under the notion that each individual's unique genetic makeup and environmental exposures imprints upon them not only a disposition to illness, but also an optimal therapeutic approach. In the realm of rare disorders, genetic predisposition is often the predominant mechanism driving disease presentation. For such, mostly, monogenic disorders, a causal gene to phenotype association is likely. As a result, it becomes important to query the patient's genome for the presence of pathogenic variations that are likely to cause the disease. Determining whether a variant is pathogenic or not is critical to these analyses and can be challenging, as many disease-causing variants are novel and, ergo, have no available functional data to help categorize them. This problem is exacerbated by the need for rapid evaluation of pathogenicity, since many genetic diseases present in young children who will experience increased morbidity and mortality without rapid diagnosis and therapeutics. Here, we discuss the utility of animal models, with a focus mainly on C. elegans, as a contrast to tissue culture and in silico approaches, with emphasis on how these systems are used in determining pathogenicity of variants with uncertain significance and then used to screen for novel therapeutics.
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Affiliation(s)
| | | | - Thomas R Caulfield
- Mayo Clinic, Department of Neuroscience, Department of Computational Biology, Department of Clinical Genomics, Jacksonville, FL, 32224, Rochester, MN, 55905, USA
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75
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Leng K, Kampmann M. Towards elucidating disease-relevant states of neurons and glia by CRISPR-based functional genomics. Genome Med 2022; 14:130. [PMID: 36401300 PMCID: PMC9673433 DOI: 10.1186/s13073-022-01134-7] [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: 05/04/2022] [Accepted: 11/02/2022] [Indexed: 11/19/2022] Open
Abstract
Our understanding of neurological diseases has been tremendously enhanced over the past decade by the application of new technologies. Genome-wide association studies have highlighted glial cells as important players in diseases. Single-cell profiling technologies are providing descriptions of disease states of neurons and glia at unprecedented molecular resolution. However, significant gaps remain in our understanding of the mechanisms driving disease-associated cell states, and how these states contribute to disease. These gaps in our understanding can be bridged by CRISPR-based functional genomics, a powerful approach to systematically interrogate gene function. In this review, we will briefly review the current literature on neurological disease-associated cell states and introduce CRISPR-based functional genomics. We discuss how advances in CRISPR-based screens, especially when implemented in the relevant brain cell types or cellular environments, have paved the way towards uncovering mechanisms underlying neurological disease-associated cell states. Finally, we will delineate current challenges and future directions for CRISPR-based functional genomics to further our understanding of neurological diseases and potential therapeutic strategies.
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Affiliation(s)
- Kun Leng
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA.
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
- Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
| | - Martin Kampmann
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA.
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
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76
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Walton RT, Singh A, Blainey PC. Pooled genetic screens with image-based profiling. Mol Syst Biol 2022; 18:e10768. [PMID: 36366905 PMCID: PMC9650298 DOI: 10.15252/msb.202110768] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 11/13/2022] Open
Abstract
Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.
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Affiliation(s)
- Russell T Walton
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
| | - Avtar Singh
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Present address:
Department of Cellular and Tissue GenomicsGenentechSouth San FranciscoCAUSA
| | - Paul C Blainey
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
- Koch Institute for Integrative Cancer ResearchMITCambridgeMAUSA
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77
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Doman JL, Sousa AA, Randolph PB, Chen PJ, Liu DR. Designing and executing prime editing experiments in mammalian cells. Nat Protoc 2022; 17:2431-2468. [PMID: 35941224 PMCID: PMC9799714 DOI: 10.1038/s41596-022-00724-4] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/19/2022] [Indexed: 02/07/2023]
Abstract
Prime editing (PE) is a precision gene editing technology that enables the programmable installation of substitutions, insertions and deletions in cells and animals without requiring double-strand DNA breaks (DSBs). The mechanism of PE makes it less dependent on cellular replication and endogenous DNA repair than homology-directed repair-based approaches, and its ability to precisely install edits without creating DSBs minimizes indels and other undesired outcomes. The capabilities of PE have also expanded since its original publication. Enhanced PE systems, PE4 and PE5, manipulate DNA repair pathways to increase PE efficiency and reduce indels. Other advances that improve PE efficiency include engineered pegRNAs (epegRNAs), which include a structured RNA motif to stabilize and protect pegRNA 3' ends, and the PEmax architecture, which improves editor expression and nuclear localization. New applications such as twin PE (twinPE) can precisely insert or delete hundreds of base pairs of DNA and can be used in tandem with recombinases to achieve gene-sized (>5 kb) insertions and inversions. Achieving optimal PE requires careful experimental design, and the large number of parameters that influence PE outcomes can be daunting. This protocol describes current best practices for conducting PE and twinPE experiments and describes the design and optimization of pegRNAs. We also offer guidelines for how to select the proper PE system (PE1 to PE5 and twinPE) for a given application. Finally, we provide detailed instructions on how to perform PE in mammalian cells. Compared with other procedures for editing human cells, PE offers greater precision and versatility, and can be completed within 2-4 weeks.
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Affiliation(s)
- Jordan L Doman
- Merkin Institute of Transformative Technologies in Healthcare, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
| | - Alexander A Sousa
- Merkin Institute of Transformative Technologies in Healthcare, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
| | - Peyton B Randolph
- Merkin Institute of Transformative Technologies in Healthcare, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
| | - Peter J Chen
- Merkin Institute of Transformative Technologies in Healthcare, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA
| | - David R Liu
- Merkin Institute of Transformative Technologies in Healthcare, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA.
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78
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Abstract
CRISPR-Cas is a powerful genome editing tool for various species and human cell lines, widely used in many research areas including studying the mechanisms, targets, and gene therapies of human diseases. Recent developments have even allowed high-throughput genetic screening using the CRISPR system. However, due to the practical and ethical limitations in human gene editing research, little is known about whether CRISPR-editable DNA segments could influence human complex traits or diseases. Here, we investigated the human genomic regions condensed with different CRISPR Cas enzymes’ protospacer-adjacent motifs (PAMs). We found that Cas enzymes with GC-rich PAMs could interfere more with the genomic regions that harbor enriched heritability for human complex traits and diseases. The results linked GC content across the genome to the functional genomic elements in the heritability enrichment of human complex traits. We provide a genetic overview of the effects of high-throughput genome editing on human complex traits. An analysis of different CRISPR protospacer-adjacent motifs (PAMs) from various Cas enzymes shows that GC-rich PAMs are more abundant in genomic regions that harbour enriched heritability for human complex traits.
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79
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Cooper YA, Guo Q, Geschwind DH. Multiplexed functional genomic assays to decipher the noncoding genome. Hum Mol Genet 2022; 31:R84-R96. [PMID: 36057282 PMCID: PMC9585676 DOI: 10.1093/hmg/ddac194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 11/14/2022] Open
Abstract
Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.
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Affiliation(s)
- Yonatan A Cooper
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Qiuyu Guo
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California Los Angeles, Los Angeles, CA, USA
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80
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Hu C, Susswein LR, Roberts ME, Yang H, Marshall ML, Hiraki S, Berkofsky-Fessler W, Gupta S, Shen W, Dunn CA, Huang H, Na J, Domchek SM, Yadav S, Monteiro AN, Polley EC, Hart SN, Hruska KS, Couch FJ. Classification of BRCA2 Variants of Uncertain Significance (VUS) Using an ACMG/AMP Model Incorporating a Homology-Directed Repair (HDR) Functional Assay. Clin Cancer Res 2022; 28:3742-3751. [PMID: 35736817 PMCID: PMC9433957 DOI: 10.1158/1078-0432.ccr-22-0203] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/03/2022] [Accepted: 06/20/2022] [Indexed: 01/09/2023]
Abstract
PURPOSE The identification of variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes by hereditary cancer testing poses great challenges for the clinical management of variant carriers. The ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology) variant classification framework, which incorporates multiple sources of evidence, has the potential to establish the clinical relevance of many VUS. We sought to classify the clinical relevance of 133 single-nucleotide substitution variants encoding missense variants in the DNA-binding domain (DBD) of BRCA2 by incorporating results from a validated functional assay into an ACMG/AMP-variant classification model from a hereditary cancer-testing laboratory. EXPERIMENTAL DESIGN The 133 selected VUS were evaluated using a validated homology-directed double-strand DNA break repair (HDR) functional assay. Results were combined with clinical and genetic data from variant carriers in a rules-based variant classification model for BRCA2. RESULTS Of 133 missense variants, 44 were designated as non-functional and 89 were designated as functional in the HDR assay. When combined with genetic and clinical information from a single diagnostic laboratory in an ACMG/AMP-variant classification framework, 66 variants previously classified by the diagnostic laboratory were correctly classified, and 62 of 67 VUS (92.5%) were reclassified as likely pathogenic (n = 22) or likely benign (n = 40). In total, 44 variants were classified as pathogenic/likely pathogenic, 84 as benign/likely benign, and 5 remained as VUS. CONCLUSIONS Incorporation of HDR functional analysis into an ACMG/AMP framework model substantially improves BRCA2 VUS re-classification and provides an important tool for determining the clinical relevance of individual BRCA2 VUS.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Wei Shen
- Mayo Clinic, Rochester, Minnesota
| | | | | | - Jie Na
- Mayo Clinic, Rochester, Minnesota
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81
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Koczwara KE, Lake NJ, DeSimone AM, Lek M. Neuromuscular disorders: finding the missing genetic diagnoses. Trends Genet 2022; 38:956-971. [PMID: 35908999 DOI: 10.1016/j.tig.2022.07.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/01/2022] [Accepted: 07/04/2022] [Indexed: 11/24/2022]
Abstract
Neuromuscular disorders (NMDs) are a wide-ranging group of diseases that seriously affect the quality of life of affected individuals. The development of next-generation sequencing revolutionized the diagnosis of NMD, enabling the discovery of hundreds of NMD genes and many more pathogenic variants. However, the diagnostic yield of genetic testing in NMD cohorts remains incomplete, indicating a large number of genetic diagnoses are not identified through current methods. Fortunately, recent advancements in sequencing technologies, analytical tools, and high-throughput functional screening provide an opportunity to circumvent current challenges. Here, we discuss reasons for missing genetic diagnoses in NMD, how emerging technologies and tools can overcome these hurdles, and examine future approaches to improving diagnostic yields in NMD.
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Affiliation(s)
- Katherine E Koczwara
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Nicole J Lake
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Alec M DeSimone
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Monkol Lek
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA.
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82
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Du PP, Liu K, Bassik MC, Hess GT. Pathogenic or benign? Nat Biotechnol 2022; 40:834-836. [PMID: 35578021 DOI: 10.1038/s41587-022-01333-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Peter P Du
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Katherine Liu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael C Bassik
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.,Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.,Program in Chemistry, Engineering, and Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA, USA
| | - Gaelen T Hess
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA. .,Center for Human Genomics and Precision Medicine, University of Wisconsin-Madison, Madison, WI, USA.
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83
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Abstract
Over the past decade, CRISPR has become as much a verb as it is an acronym, transforming biomedical research and providing entirely new approaches for dissecting all facets of cell biology. In cancer research, CRISPR and related tools have offered a window into previously intractable problems in our understanding of cancer genetics, the noncoding genome and tumour heterogeneity, and provided new insights into therapeutic vulnerabilities. Here, we review the progress made in the development of CRISPR systems as a tool to study cancer, and the emerging adaptation of these technologies to improve diagnosis and treatment.
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Affiliation(s)
- Alyna Katti
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell Graduate School of Medical Science, Weill Cornell Medicine, New York, NY, USA
| | - Bianca J Diaz
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell Graduate School of Medical Science, Weill Cornell Medicine, New York, NY, USA
| | - Christina M Caragine
- Department of Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Neville E Sanjana
- Department of Biology, New York University, New York, NY, USA.
- New York Genome Center, New York, NY, USA.
| | - Lukas E Dow
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
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