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The use of base editing technology to characterize single nucleotide variants
Single nucleotide variants (SNVs) represent the most common type of polymorphism in the human genome. However, in many cases the phenotypic impacts of such variants are not well understood. Intriguingly, while some SNVs cause debilitating diseases, other variants in the same gene may have no, or lim...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010703/ https://www.ncbi.nlm.nih.gov/pubmed/35465164 http://dx.doi.org/10.1016/j.csbj.2022.03.031 |
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author | McDaniel, Sophia Komor, Alexis Goren, Alon |
author_facet | McDaniel, Sophia Komor, Alexis Goren, Alon |
author_sort | McDaniel, Sophia |
collection | PubMed |
description | Single nucleotide variants (SNVs) represent the most common type of polymorphism in the human genome. However, in many cases the phenotypic impacts of such variants are not well understood. Intriguingly, while some SNVs cause debilitating diseases, other variants in the same gene may have no, or limited, impact. The mechanisms underlying these complex patterns are difficult to study at scale. Additionally, current data and research is mainly focused on European populations, and the mechanisms underlying genetic traits in other populations are poorly studied. Novel technologies may be able to mitigate this disparity and improve the applicability of personalized healthcare to underserved populations. In this review we discuss base editing technologies and their potential to accelerate progress in this field, particularly in combination with single-cell RNA sequencing. We further explore how base editing screens can help link SNVs to distinct disease phenotypes. We then highlight several studies that take advantage of single-cell RNA sequencing and CRISPR screens to emphasize the current limitations and future potential of this technique. Lastly, we consider the use of such approaches to potentially accelerate the study of genetic mechanisms in non-European populations. |
format | Online Article Text |
id | pubmed-9010703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-90107032022-04-21 The use of base editing technology to characterize single nucleotide variants McDaniel, Sophia Komor, Alexis Goren, Alon Comput Struct Biotechnol J Review Single nucleotide variants (SNVs) represent the most common type of polymorphism in the human genome. However, in many cases the phenotypic impacts of such variants are not well understood. Intriguingly, while some SNVs cause debilitating diseases, other variants in the same gene may have no, or limited, impact. The mechanisms underlying these complex patterns are difficult to study at scale. Additionally, current data and research is mainly focused on European populations, and the mechanisms underlying genetic traits in other populations are poorly studied. Novel technologies may be able to mitigate this disparity and improve the applicability of personalized healthcare to underserved populations. In this review we discuss base editing technologies and their potential to accelerate progress in this field, particularly in combination with single-cell RNA sequencing. We further explore how base editing screens can help link SNVs to distinct disease phenotypes. We then highlight several studies that take advantage of single-cell RNA sequencing and CRISPR screens to emphasize the current limitations and future potential of this technique. Lastly, we consider the use of such approaches to potentially accelerate the study of genetic mechanisms in non-European populations. Research Network of Computational and Structural Biotechnology 2022-03-31 /pmc/articles/PMC9010703/ /pubmed/35465164 http://dx.doi.org/10.1016/j.csbj.2022.03.031 Text en © 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review McDaniel, Sophia Komor, Alexis Goren, Alon The use of base editing technology to characterize single nucleotide variants |
title | The use of base editing technology to characterize single nucleotide variants |
title_full | The use of base editing technology to characterize single nucleotide variants |
title_fullStr | The use of base editing technology to characterize single nucleotide variants |
title_full_unstemmed | The use of base editing technology to characterize single nucleotide variants |
title_short | The use of base editing technology to characterize single nucleotide variants |
title_sort | use of base editing technology to characterize single nucleotide variants |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010703/ https://www.ncbi.nlm.nih.gov/pubmed/35465164 http://dx.doi.org/10.1016/j.csbj.2022.03.031 |
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