Development of an AmpliSeqTM panel for next-generation sequencing of a set of genetic predictors of persisting pain

  • Background: Many gene variants modulate the individual perception of pain and possibly also its persistence. The limited selection of single functional variants is increasingly being replaced by analyses of the full coding and regulatory sequences of pain-relevant genes accessible by means of next generation sequencing (NGS). Methods: An NGS panel was created for a set of 77 human genes selected following different lines of evidence supporting their role in persisting pain. To address the role of these candidate genes, we established a sequencing assay based on a custom AmpliSeqTM panel to assess the exomic sequences in 72 subjects of Caucasian ethnicity. To identify the systems biology of the genes, the biological functions associated with these genes were assessed by means of a computational over-representation analysis. Results: Sequencing generated a median of 2.85 ⋅ 106 reads per run with a mean depth close to 200 reads, mean read length of 205 called bases and an average chip loading of 71%. A total of 3,185 genetic variants were called. A computational functional genomics analysis indicated that the proposed NGS gene panel covers biological processes identified previously as characterizing the functional genomics of persisting pain. Conclusion: Results of the NGS assay suggested that the produced nucleotide sequences are comparable to those earned with the classical Sanger sequencing technique. The assay is applicable for small to large-scale experimental setups to target the accessing of information about any nucleotide within the addressed genes in a study cohort.

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Author:Dario Kringel, Mari A. Kaunisto, Catharina Lippmann, Eija Kalso, Jörn LötschORCiDGND
URN:urn:nbn:de:hebis:30:3-476814
DOI:https://doi.org/10.3389/fphar.2018.01008
ISSN:1663-9812
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/30283335
Parent Title (English):Frontiers in pharmacology
Publisher:Frontiers Media
Place of publication:Lausanne
Contributor(s):Ulrich M. Zanger
Document Type:Article
Language:English
Year of Completion:2018
Date of first Publication:2018/09/19
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2018/10/11
Tag:data science; functional genomics; knowledge discovery; next generation sequencing (NGS); pain
Volume:9
Issue:Art. 1008
Page Number:22
First Page:1
Last Page:22
Note:
Copyright © 2018 Kringel, Kaunisto, Lippmann, Kalso and Lötsch. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
HeBIS-PPN:439189535
Institutes:Medizin / Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Open-Access-Publikationsfonds:Medizin
Licence (German):License LogoCreative Commons - Namensnennung 4.0