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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...

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Detalles Bibliográficos
Autores principales: McDaniel, Sophia, Komor, Alexis, Goren, Alon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
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.
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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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