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Fur: Find unique genomic regions for diagnostic PCR

MOTIVATION: Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions. RESULT...

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Autores principales: Haubold, Bernhard, Klötzl, Fabian, Hellberg, Lars, Thompson, Daniel, Cavalar, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352509/
https://www.ncbi.nlm.nih.gov/pubmed/33515232
http://dx.doi.org/10.1093/bioinformatics/btab059
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author Haubold, Bernhard
Klötzl, Fabian
Hellberg, Lars
Thompson, Daniel
Cavalar, Markus
author_facet Haubold, Bernhard
Klötzl, Fabian
Hellberg, Lars
Thompson, Daniel
Cavalar, Markus
author_sort Haubold, Bernhard
collection PubMed
description MOTIVATION: Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions. RESULTS: Fur takes as input a sample of target sequences and a sample of closely related neighbors. It returns the regions present in all targets and absent from all neighbors. The recently published program genmap can also be used for this purpose and we compared it to fur. When analyzing a sample of 33 genomes representing the major phylogroups of E.coli, fur was 40 times faster than genmap but used three times more memory. On the other hand, genmap yielded three times more markers, but they were less accurate when tested in silico on a sample of 237 E.coli genomes. We also designed phylogroup-specific PCR primers based on the markers proposed by genmap and fur, and tested them by analyzing their virtual amplicons in GenBank. Finally, we used fur to design primers specific to a Lactobacillus species, and found excellent sensitivity and specificity in vitro. AVAILABILITY AND IMPLEMENTATION: Fur sources and documentation are available from https://github.com/evolbioinf/fur. The compiled software is posted as a docker container at https://hub.docker.com/r/haubold/fox. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-83525092021-08-10 Fur: Find unique genomic regions for diagnostic PCR Haubold, Bernhard Klötzl, Fabian Hellberg, Lars Thompson, Daniel Cavalar, Markus Bioinformatics Original Papers MOTIVATION: Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions. RESULTS: Fur takes as input a sample of target sequences and a sample of closely related neighbors. It returns the regions present in all targets and absent from all neighbors. The recently published program genmap can also be used for this purpose and we compared it to fur. When analyzing a sample of 33 genomes representing the major phylogroups of E.coli, fur was 40 times faster than genmap but used three times more memory. On the other hand, genmap yielded three times more markers, but they were less accurate when tested in silico on a sample of 237 E.coli genomes. We also designed phylogroup-specific PCR primers based on the markers proposed by genmap and fur, and tested them by analyzing their virtual amplicons in GenBank. Finally, we used fur to design primers specific to a Lactobacillus species, and found excellent sensitivity and specificity in vitro. AVAILABILITY AND IMPLEMENTATION: Fur sources and documentation are available from https://github.com/evolbioinf/fur. The compiled software is posted as a docker container at https://hub.docker.com/r/haubold/fox. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-01-30 /pmc/articles/PMC8352509/ /pubmed/33515232 http://dx.doi.org/10.1093/bioinformatics/btab059 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Haubold, Bernhard
Klötzl, Fabian
Hellberg, Lars
Thompson, Daniel
Cavalar, Markus
Fur: Find unique genomic regions for diagnostic PCR
title Fur: Find unique genomic regions for diagnostic PCR
title_full Fur: Find unique genomic regions for diagnostic PCR
title_fullStr Fur: Find unique genomic regions for diagnostic PCR
title_full_unstemmed Fur: Find unique genomic regions for diagnostic PCR
title_short Fur: Find unique genomic regions for diagnostic PCR
title_sort fur: find unique genomic regions for diagnostic pcr
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352509/
https://www.ncbi.nlm.nih.gov/pubmed/33515232
http://dx.doi.org/10.1093/bioinformatics/btab059
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