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Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
The study of populations of large size and high diversity is limited by the capability of collecting data. Moreover, for a pool of individuals, each associated with a unique characteristic feature, as the pool size grows, the possible interactions increase exponentially and quickly go beyond the lim...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217214/ https://www.ncbi.nlm.nih.gov/pubmed/31674719 http://dx.doi.org/10.1002/cbic.201900603 |
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author | Andrade, Helena Thomas, Alvin K. Lin, Weilin Reddavide, Francesco V. Zhang, Yixin |
author_facet | Andrade, Helena Thomas, Alvin K. Lin, Weilin Reddavide, Francesco V. Zhang, Yixin |
author_sort | Andrade, Helena |
collection | PubMed |
description | The study of populations of large size and high diversity is limited by the capability of collecting data. Moreover, for a pool of individuals, each associated with a unique characteristic feature, as the pool size grows, the possible interactions increase exponentially and quickly go beyond the limit of computation and experimental studies. Herein, the design of DNA libraries with various diversity is reported. By using a facile analytical method based on real‐time PCR, the diversity of a pool of DNA can be evaluated to allow extraordinarily high heterogenicity (e.g., >1 trillion). It is demonstrated that these DNA libraries can be used to model heterogeneous populations; these libraries exhibit functions such as self‐protection, suitability for biased expansion, and the possibility to evolve into amorphous structures. The method has shown the remarkable power of parallel computing with DNA, since it can resemble an analogue computer and be applied in selection‐based biotechnology methods, such as DNA‐encoded chemical libraries. As a chemical approach to solve problems traditionally for genetic and statistical analysis, the method provides a quick and cost‐efficient evaluation of library diversity for intermediate steps through a selection process. |
format | Online Article Text |
id | pubmed-7217214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72172142020-05-13 Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA Andrade, Helena Thomas, Alvin K. Lin, Weilin Reddavide, Francesco V. Zhang, Yixin Chembiochem Communications The study of populations of large size and high diversity is limited by the capability of collecting data. Moreover, for a pool of individuals, each associated with a unique characteristic feature, as the pool size grows, the possible interactions increase exponentially and quickly go beyond the limit of computation and experimental studies. Herein, the design of DNA libraries with various diversity is reported. By using a facile analytical method based on real‐time PCR, the diversity of a pool of DNA can be evaluated to allow extraordinarily high heterogenicity (e.g., >1 trillion). It is demonstrated that these DNA libraries can be used to model heterogeneous populations; these libraries exhibit functions such as self‐protection, suitability for biased expansion, and the possibility to evolve into amorphous structures. The method has shown the remarkable power of parallel computing with DNA, since it can resemble an analogue computer and be applied in selection‐based biotechnology methods, such as DNA‐encoded chemical libraries. As a chemical approach to solve problems traditionally for genetic and statistical analysis, the method provides a quick and cost‐efficient evaluation of library diversity for intermediate steps through a selection process. John Wiley and Sons Inc. 2020-01-07 2020-04-17 /pmc/articles/PMC7217214/ /pubmed/31674719 http://dx.doi.org/10.1002/cbic.201900603 Text en © 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Communications Andrade, Helena Thomas, Alvin K. Lin, Weilin Reddavide, Francesco V. Zhang, Yixin Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA |
title | Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
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title_full | Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
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title_fullStr | Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
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title_full_unstemmed | Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
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title_short | Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA
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title_sort | using a pcr‐based method to analyze and model large, heterogeneous populations of dna |
topic | Communications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217214/ https://www.ncbi.nlm.nih.gov/pubmed/31674719 http://dx.doi.org/10.1002/cbic.201900603 |
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