Literature DB >> 28658281

Next-generation sequencing of the human TRPV1 gene and the regulating co-players LTB4R and LTB4R2 based on a custom AmpliSeq™ panel.

Dario Kringel1, Marco Sisignano1, Sebastian Zinn1, Jörn Lötsch1,2.   

Abstract

BACKGROUND: Transient receptor potential cation channel subfamily V member 1 (TRPV1) are sensitive to heat, capsaicin, pungent chemicals and other noxious stimuli. They play important roles in the pain pathway where in concert with proinflammatory factors such as leukotrienes they mediate sensitization and hyperalgesia. TRPV1 is the target of several novel analgesics drugs under development and therefore, TRPV1 genetic variants might represent promising candidates for pharmacogenetic modulators of drug effects.
METHODS: A next-generation sequencing (NGS) panel was created for the human TRPV1 gene and in addition, for the leukotriene receptors BLT1 and BLT2 recently described to modulate TRPV1 mediated sensitisation processes rendering the coding genes LTB4R and LTB4R2 important co-players in pharmacogenetic approaches involving TRPV1. The NGS workflow was based on a custom AmpliSeq™ panel and designed for sequencing of human genes on an Ion PGM™ Sequencer. A cohort of 80 healthy subjects of Western European descent was screened to evaluate and validate the detection of exomic sequences of the coding genes with 25 base pair exon padding.
RESULTS: The amplicons covered approximately 97% of the target sequence. A median of 2.81 x 106 reads per run was obtained. This identified approximately 140 chromosome loci where nucleotides deviated from the reference sequence GRCh37 hg19 comprising the three genes TRPV1, LTB4R and LTB4R2. Correspondence between NGS and Sanger derived nucleotide sequences was 100%.
CONCLUSIONS: Results suggested that the NGS approach based on AmpliSeq™ libraries and Ion Personal Genome Machine (PGM) sequencing is a highly efficient mutation detection method. It is suitable for large-scale sequencing of TRPV1 and functionally related genes. The method adds a large amount of genetic information as a basis for complete analysis of TRPV1 ion channel genetics and its functional consequences.

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Year:  2017        PMID: 28658281      PMCID: PMC5489211          DOI: 10.1371/journal.pone.0180116

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

The transient receptor potential (TRP) family comprises several non-selective cation channels [1] enabling or inhibiting the transmembrane transport of several ions. Various members of this ion channel family are expressed at nociceptors and via their excitation by chemical, thermal or mechanical stimuli involved in the perception of pain [2]. This makes them primary candidates for the discovery of novel analgesic drugs [3]. A query of the Thomson Reuters “Drugs and Biologics Search Tool” (http://integrity.thomsonpharma.com) in June 2016 indicated that by far the most frequently regarded TRP member in analgesic drug development is TRP cation channel, subfamily V, member 1 (TRPV1 [4]) for which more than 200 agonists or antagonists are currently under development, which bases on the concept that endogenous agonists or sensitizers acting on TRPV1 provide a major contribution to pathophysiological pain conditions [5, 6]. The pharmacological modulation of this mechanism employs (i) the approach of direct antagonism of the TRPV1 ion channel, (ii) the exposure to agonists such as capsaicin that initially activates TRPV1 but upon prolonged exposure induces a deactivation via a calcineurin-dependent channel dephosphorylation and desensitization [7] and (iii) to prevent a sensitization and hyperactivation of the TRPV1 channel [8]. Given the importance of TRPV1 in pain and analgesic drug discovery and development, TRPV1 genetics move into a focus of pharmacogenetic interest. A modulation of the effects of TRPV1 targeting analgesics is supported by observations that intronic TRPV1 variants were associated with insensitivity to capsaicin [9] while the coding TRPV1 variant rs8065080 was associated with altered responses to experimentally induced pain [10]. Moreover, gain-of-function mutations in TRPV1 have been associated with increased pain sensitivity [11], for which TRPV1 antagonists would enable a specific pharmacogenetics-based personalized cure. Hence, genetic variation of human TRPV1 is in a focus of pain and analgesic research. With the broader availability of next generation sequencing (NGS) [12], a limitation to already investigated variants has fallen in favor of unrestricted access to the whole genetic information in agreement with the wider acceptance of whole genomic information as a valuable method in clinical research [13]. In this report, the evaluation of a new NGS method based on a custom AmpliSeq™ library and Ion Torrent sequencing for the fast detection of genetic variations in the human TRPV1 gene is described. However, preclinical evidence indicates that leukotriene B4 mediates the inflammation via TRPV1 [14] and that the nociceptive function of TRPV1 is modulated by the activation of leukotriene receptors BLT1 and BLT2 [8] that are highly expressed in TRPV1 expressing dorsal root ganglion neurons. Both receptors form an antagonistic sensitizing system and have opposing roles in TRPV1 sensitisation. This renders them important co-players in pharmacogenetic approaches at analgesics aiming at modulation of the function of TRPV1. To provide a comprehensive basis for pharmacogenetic assessments of TRPV1 modulators, the present NGS panel was extended with human LTB4R and LTB4R2 genes that code for the leukotriene receptors of present interest.

Methods

DNA template preparation and amplification

The investigation followed the Declaration of Helsinki on Biomedical Research Involving Human Subjects and was approved by the Ethics Committee of the Medical Faculty of the Goethe-University, Frankfurt, Germany. All participating subjects had provided informed written consent. Genomic DNA was available from venous blood samples drawn from a random sample of 80 healthy volunteers of Western European descent according to self-assignment. DNA was extracted from 200 μl blood on a BioRobot EZ1 workstation applying the blood and body fluid spin protocol provided in the EZ1 DNA Blood 200 μl Kit (Qiagen, Hilden, Germany). Exomic genotyping was performed for the TRPV1 gene (NCBI ID 7442), located on chromosome 17 and encoding for the TRPV1 ion channel and for the LTB4R and LTB4R2 genes (NCBI IDs 1241 and 56413), both located on chromosomes 14 and encoding for leukotriene B4 receptors BLT1 and BLT2. A multiplex PCR amplification strategy for the coding genes sequences was accomplished online (Ion Ampliseq™ Designer; http://www.ampliseq.com) to amplify the target region specified above (for primer sequences, see S1 Table) with 25 base pair exon padding. After comparison of several primer design options, the design providing the maximum target sequence coverage was chosen. The ordered amplicons covered 97.02% of the target sequence. A total of 10 ng DNA per sample were used for the target enrichment by a multiplex PCR and each DNA pool was amplified with the Ion Ampliseq™ Library Kit in conjunction with the Ion Ampliseq™ “custom Primer Pool”—protocols according to the manufacturer procedures (Life Technologies, Darmstadt, Germany). After each pool had undergone 17 PCR cycles, the PCR primers were removed with FuPa Reagent and the amplicons were ligated to the sequencing adapters with short stretches of index sequences (barcodes) that enabled sample multiplexing for subsequent steps (Ion Xpress™ Barcode Adapters Kit; Life Technologies). After purification with AMPure XP beads (Beckman Coulter, Krefeld, Germany), the barcoded libraries were quantified with a Qubit® 2.0 Fluorimeter (Life Technologies, Darmstadt, Germany) and normalized for DNA concentration to a final concentration of 20 pmol/L using the Ion Library Equalizer™ Kit (Life Technologies, Darmstadt, Germany). Equalized barcoded libraries from 11 to 40 samples at a time were pooled. To clonally amplify the library DNA onto the Ion Sphere Particles (ISPs; Life Technologies, Darmstadt, Germany), the library pool was subjected to emulsion PCR by using an IT OneTouch template kit on an IT OneTouch system (Life Technologies, Darmstadt, Germany) following the manufacturer’s protocol.

Sequencing

Enriched ISPs which carried many copies of the same DNA fragment were subjected to sequencing on an Ion 318 Chip to sequence pooled libraries with eleven to twelve samples. The 318 chip was chosen (instead of the low-capacity 314 or the middle-capacity 316 chip) to obtain a high sequencing depth of coverage which was averagely of 50x which means that, each base has been sequenced 50 times, when 40 samples were loaded. Sequencing was performed using the sequencing kit (Ion PGM 200 Sequencing Kit; Life Technologies, Darmstadt, Germany) as per the manufacturer’s instructions with the 200-bp single-end run configuration.

Bioinformatics generation of sequence information

The raw data (unmapped BAM-files) from the sequencing runs were processed using Torrent Suite Software (Version 4.4.2, Life Technologies, Darmstadt, Germany) to generate read alignments which are filtered by the software into mapped BAM-files using the reference genomic sequence (hg19) of target genes. Variant calling was performed with the Torrent Variant Caller Plugin using as key parameters: minimum quality = 10, minimum coverage = 20, and minimum coverage on either strand = 3. The annotation of called variants was done using the Ion Reporter Software (Version 5.0; Life Technologies, Darmstadt, Germany) and the variant classification tool of the SNP and Variation Suite software (Version 8.4.4; Golden Helix, Bozeman, MT, USA) for the VCF (variant call format) files that contained the nucleotide reads and the GenomeBrowse® software (Version 2.0.4, Golden Helix, Bozeman, MT, USA) to map the sequences to the reference sequences GRCh37 g1k (dated February 2009). On the basis of the observed allelic frequency, the expected number of homozygous and heterozygous carriers of the respective SNP (single nucleotide polymorphism) was calculated using the Hardy-Weinberg equation. Indicating that the study sample corresponded to a random sample of subjects, Fisher’s exact test [15] was used as proposed previously [16]. Only variants within the Hardy-Weinberg equilibrium were retained. The SNP and Variation Suite software (Version 8.4.4; Golden Helix, Bozeman, MT, USA) was used for the analysis of sequence quality, coverage and for variant identification.

Method validation

Method validation was accomplished by means of Sanger sequencing [17, 18] in an independent external laboratory (Eurofins Genomics, Ebersberg, Germany). For the detected variant type, i.e., single nucleotide polymorphisms (SNV), nucleotide insertions (Ins) and nucleotide deletions (Del), the variant with the highest frequency of the rare allele was chosen for external sequencing: 17:3493769-SNV, 17:3496181_Ins, 17:3512619_Del. In addition, the variant 17:3480447-SNV, which is the functional rs8065080 SNP previously associated with altered pain sensitivity [10], was added accommodating the present context of analgesics’ pharmacogenetic. Amplification of the respective DNA segments was done using PCR primer pairs (forward, reverse) of (i) 5´-CCATGTTGCGTCTCTCGATG-3´ and 5´-CAACCCGTTATTTCCTGTTCCCA-3´ (ii) 5´- CTCAGAGGTGAGCAGGCCTAGC -3´ and 5´- AAGGCCAGGATGCTTGACAGATG -3´, (iii) 5´- AAGGCACAAGACTCTGGAAGAAT-3´ and 5´- CGAGTTTGGGAAGCAGTCGTAT-3´ and (iv) 5´- ACCCAGTGCCTTCTCATTCAG-3´ and 5´- CACGTTCTCAAGACGCATCC-3´. Results of Sanger sequencing were aligned with the genomic sequence and analyzed using Chromas Lite® (Version 2.1.1, Technelysium Pty Ltd, South Brisbane, Australia) and the GenomeBrowse® (Version 2.0.4, Golden Helix, Bozeman, MT, USA) was used to compare the sequences obtained with NGS or Sanger techniques.

Results

The NGS assay of human TRPV1, LTB4R2 and LTB4R genes was established on 80 genomic DNA samples obtained from a random selection of healthy subjects of Caucasian ethnicity. As proposed previously [19], only exons and their boundary sequences for which read-depths > 20 for each nucleotide could be obtained were considered as successfully analyzed. Applying this criterion, complete or nearly complete coverage of the relevant sequences was obtained (Table 1; for details on missing variants, see S2 Table). The sequencing of the whole cohort required two separate runs with each 40 patients’ samples. Coverage statistics (Table 1) were comparable between both runs and were in the range of accepted quality criteria [20-22]. During the runs, a median of 2.81 · 106 reads per run was generated. The mean depth was near from 200 reads, the mean read length evaluated 198 bases and average chip loading was 66% (Fig 1). To ensure a high density of ISPs on a chip and hence, a high sequencing output, the chip loading value should be ≥ 60%. The observed NGS results agreed with the results obtained with conventional sequencing of random samples (Fig 2). In all validation samples, the correspondence between NGS and Sanger derived nucleotide sequences was 100%, all of the tested nucleotide variants could be verified.
Table 1

AmpliSeq™ amplicons and coverage details of the human LTB4R2, LTB4R and TRPV1 NGS assay.

GeneChr*Chr startChr endAmpliconsTotal basesCovered basesCoverageSum (total, covered, %)
LTBR42Chr1434634693346358808118711871.0003520, 3427, 98.3%
346369683463711111431431.000
346369683463713411661661.000
346372383463744222042041.000
346371913463744222512511.000
346375783463784822702510.930
346375183463784823302560.776
34634693346358808118711871.000
LTBR4Chr14346372383463744222042041.0005683, 5117, 97%
346371913463744222512511.000
346375783463784822702510.930
346375183463784823302560.776
34634693346358808118711871.000
346372383463744222042041.000
TRPV1Chr17246369682463711111431431.00023787, 21859, 98.8%
246369682463713411661661.000
246372382463744222042041.000
246371912463744222512511.000
246369682463713411661661.000
246372382463744222042041.000
246371912463744222512511.000
246369682463713411661661.000
246372382463744222042041.000
246371912463744222512511.000
246369682463713411661661.000
246372382463744222042041.000
246371912463744222512511.000
246371912463744222512511.000
246369682463713422702510.930
246372382463744223302560.776
24637191246374428118711871.000
246369682463713422512511.000
246372382463744222702510.930
246371912463744223302560.776
24636968246371348118711871.000

*: Chr: Chromosome.

Fig 1

Pseudo-color image of the Ion 318™ v2 chip plate showing percent loading across the physical surface.

This sequencing run had a 70% loading, which ensures a high ISP density. Every 318 chip contains more than 6 million wells and the color scale on the right side conduces as a loading indicator. Deep red coloration stays for a 100% loading, which means that every well in this area contains an ISP (templated and non-templated) whereas deep blue coloration implies that the wells in this area are empty.

Fig 2

Alignment of the ion torrent sequence of the TRPV1 gene illustrated by Golden Helix Genome Browse® readout versus the same sequence according to a Sanger electrophereogram.

Highlighted is the coding TRPV1 variant rs8065080 as a heterozygous mutation and a non-mutated wild type.

*: Chr: Chromosome.

Pseudo-color image of the Ion 318™ v2 chip plate showing percent loading across the physical surface.

This sequencing run had a 70% loading, which ensures a high ISP density. Every 318 chip contains more than 6 million wells and the color scale on the right side conduces as a loading indicator. Deep red coloration stays for a 100% loading, which means that every well in this area contains an ISP (templated and non-templated) whereas deep blue coloration implies that the wells in this area are empty.

Alignment of the ion torrent sequence of the TRPV1 gene illustrated by Golden Helix Genome Browse® readout versus the same sequence according to a Sanger electrophereogram.

Highlighted is the coding TRPV1 variant rs8065080 as a heterozygous mutation and a non-mutated wild type. Following elimination of nucleotides agreeing with the standard human genome sequence GRCh37 g1k (dated February 2009), the result of the NGS consisted of a vector of nucleotide information about the LTB4R2, LTB4R and TRPV1 genes for each individual DNA sample (Fig 3). This vector had a length equaling the set union of the number of chromosomal positions in which a non-reference nucleotide had been found in any probe of the actual cohort of randomly chosen healthy subjects. Specifically, a total of 156 genetic variants was found, of which 11, 28 and 117 were located in the LTB4R2, LTB4R and TRPV1 genes, respectively (Fig 3). Of the observed variants, 38 were located in coding parts of the genes (Table 2), 56 were located in introns, 33 in the 3’-UTR, 16 in the 5’-UTR, 5 variants were assigned to both UTR’s and 8 were located downstream. The nucleotidic and, if present, the resulting amino acid exchanges, of the coding variants are listed in Table 2. The allelic frequencies corresponded to those expected based on the Hardy-Weinberg equilibrium (Fisher’s exact tests: p always > 0.05) and, for variants with reported clinical functional association, the observed allelic frequency was comparable to reported frequencies (Table 3). Most of the observed variants were single nucleotide polymorphisms (n = 135; 9, 25 and 101 in the LTB4R2, LTB4R and TRPV1 genes, respectively) whereas classified as mixed polymorphisms (n = 8), nucleotide insertions (n = 6), nucleotide deletions (n = 5) or multinucleotide polymorphisms (n = 2) were more rarely found in the present cohort.
Fig 3

LTB4R2, LTB4R and TRPV1 genetic pattern of 80 healthy volunteers of Caucasian ethnicity.

The mosaic plot shows the occurrence of variants (lines) per DNA sample (columns) as vectors of a length corresponding to the number of gene loci in which a non-reference nucleotide was found in any sample of the whole cohort. The vectors are composed of information about the number of non-reference alleles found at the respective locus in the respective sample, color codes as white, 0 non-reference alleles = wild type genotype, yellow, heterozygous, and red, 2 non-reference alleles). The bar plot on the top shows the number of variant alleles found in the cohort.

Table 2

A list of variants found in the coding parts of the LTB4R2, LTB4R and TRPV1 genes in a random sample of 80 healthy volunteers of Caucasian ethnicity.

GeneVariantChr*PositionClassificationExonCodingProtein
LTB4R214:24779946-SNV1424779946Nonsyn SNV2c.76T>Cp.Phe26Leu
14:24779959-SNV1424779959Nonsyn SNV2c.89C>Tp.Ala30Val
14:24779961-SNV1424779961Nonsyn SNV2c.91G>Ap.Ala31Thr
14:24779994-SNV1424779994Nonsyn SNV2c.124G>Ap.Val42Met
14:24780010-Del1424780010Frameshift Del2c.140_164delp.Ala51fs
14:24780503-SNV1424780503Synonymous2c.633C>Tp.=
14:24780847-SNV1424780847Nonsyn SNV2c.977A>Gp.Glu326Gly
LTB4R14:24784911-SNV1424784911Synonymous2c.54T>Cp.=
14:24785083-SNV1424785083Nonsyn SNV2c.226C>Tp.His76Tyr
14:24785633-SNV1424785633Nonsyn SNV2c.776T>Cp.Val259Ala
14:24785784-SNV1424785784Synonymous2c.927C>Tp.=
TRPV117:3474927-SNV173474927Synonymous14c.2238C>Tp.=
17:3475435-SNV173475435Nonsyn SNV13c.2212G>Tp.Asp738Tyr
17:3475459-SNV173475459Nonsyn SNV13c.2188G>Ap.Gly730Arg
17:3475490-SNV173475490Synonymous13c.2157G>Ap.=
17:3476990-SNV173476990Synonymous12c.2040C>Tp.=
17:3477000-SNV173477000Nonsyn SNV12c.2030A>Gp.Asn677Ser
17:3480432-SNV173480432Nonsyn SNV11c.1768G>Ap.Gly590Arg
17:3480447-SNV173480447Nonsyn SNV11c.1753A>Gp.Ile585Val
17:3480910-SNV173480910Synonymous10c.1695T>Cp.=
17:3483785-SNV173483785Nonsyn SNV9c.1513A>Gp.Thr505Ala
17:3486702-SNV173486702Nonsyn SNV8c.1406C>Tp.Thr469Ile
17:3486703-SNV173486703Nonsyn SNV8c.1405A>Tp.Thr469Ser
17:3489068-SNV173489068Synonymous7c.1377T>Cp.=
17:3491499-SNV173491499Nonsyn SNV6c.1207A>Gp.Ser403Gly
17:3493200-SNV173493200Nonsyn SNV5c.945G>Cp.Met315Ile
17:3494361-SNV173494361Synonymous3c.501C>Tp.=
17:3494388-SNV173494388Synonymous3c.474T>Cp.=
17:3494533-SNV173494533Synonymous2c.399G>Ap.=
17:3494562-SNV173494562Stopgain2c.370C>Tp.Gln124*
17:3494603-SNV173494603Nonsyn SNV2c.329T>Cp.Leu110Pro
17:3495374-SNV173495374Nonsyn SNV1c.271C>Tp.Pro91Ser
17:3495391-SNV173495391Nonsyn SNV1c.254A>Gp.Gln85Arg
17:3495407-SNV173495407Nonsyn SNV1c.238C>Tp.Pro80Ser
17:3495456-SNV173495456Synonymous1c.189C>Tp.=
17:3495550-SNV173495550Nonsyn SNV1c.95G>Tp.Arg32Met
17:3495607-SNV173495607Nonsyn SNV1c.38C>Tp.Ala13Val
17:3495618-SNV173495618Nonsyn SNV1c.27G>Cp.Leu9Phe

*: Chr: Chromosome.

Table 3

A list of human variants of the LTB4R and TRPV1 genes, found in the present random sample of 80 healthy volunteers of Caucasian ethnicity, for which functional associations in clinical or human experimental settings have been reported.

GeneVariantdbSNP# accession numberAllelic frequency [%] (CI*) Present cohort* HAPMAP CEUKnown clinical associationReference
LTB4R14:24786060-SNVrs104658746.2 (38.7–54)47.4Asthma susceptibility[28]
14:24786293-SNVrs498150328.1 (21.7–35.4)-Asthma susceptibility[29]
TRPV117:3469853-SNVrs479052249.4 (41.7–57)56.2Bronchial asthma susceptibility[30, 31, 66]
Susceptibility to cough[67]
Altered pain sensitivity[35]
17:3480447-SNVrs806508033.7 (26.9–41.4)35.8Altered cold pain sensitivity[10]
Painful knee osteoarthritis[36]
Altered salt taste perception[68]
Higher risk of type 2 diabetes[33]
17:3486702-SNVrs22453430 (23.4–37.5)33.5Sickle cell pain[69]
17:3493200-SNVrs22274725.6 (19.5–32.9)18.3Functional dyspepsia[34]
Ménière's disease[70]
17:3495391-SNVrs559168851.2 (0.3–4.4)-Cerebellar hypoplasia[71]

*: CI denotes 95% binomial confidence intervals of the allelic frequencies are given in parentheses after the observed frequency.

#: Database of Single Nucleotide Polymorphisms (dbSNP). Bethesda (MD): National Center for Biotechnology Information, National Library of Medicine. Available from: http://www.ncbi.nlm.nih.gov/SNP/ [72]

LTB4R2, LTB4R and TRPV1 genetic pattern of 80 healthy volunteers of Caucasian ethnicity.

The mosaic plot shows the occurrence of variants (lines) per DNA sample (columns) as vectors of a length corresponding to the number of gene loci in which a non-reference nucleotide was found in any sample of the whole cohort. The vectors are composed of information about the number of non-reference alleles found at the respective locus in the respective sample, color codes as white, 0 non-reference alleles = wild type genotype, yellow, heterozygous, and red, 2 non-reference alleles). The bar plot on the top shows the number of variant alleles found in the cohort. *: Chr: Chromosome. *: CI denotes 95% binomial confidence intervals of the allelic frequencies are given in parentheses after the observed frequency. #: Database of Single Nucleotide Polymorphisms (dbSNP). Bethesda (MD): National Center for Biotechnology Information, National Library of Medicine. Available from: http://www.ncbi.nlm.nih.gov/SNP/ [72]

Discussion

An NGS assay for the exons and regulatory parts of the human genes coding for the TRPV1 ion channel and those coding for its recently associated co-players comprising the leukotriene receptors BLT1 and BLT2 (LTB4R, LTB4R2). The NGS assay produced valid nucleotide sequences corresponding to those obtained with the classical Sanger sequencing technique. The NGS assay is suitable for small to large-scale experimental setups aiming at accessing the information about any nucleotide in a study cohort, with a selection of those that differ from the reference nucleotide. TRPV1 ion channels mediate pain induced by noxious heat (> 43°C) [23]. A most striking phenotype of Trpv1 –/– mice is a severe deficit of inflammation-induced thermal hyperalgesia [24]. In addition to heat, TRPV1 expression is largely associated with small diameter primary afferent nerve fibers, which are sensitive to various chemical excitants including protons (low pH), capsaicin, lipoxygenase, resiniferatoxin, ethanol, N-arachidonoyl-dopamine and the endogenous cannabinoid anandamide [3, 25]. Based on evidence that TRPV1 channels are necessary for the development of inflammatory hyperalgesia to thermal stimuli [24] their role in pain has been acknowledged for more than two decades [24, 26]. Currently, they are used as target of capsaicin containing analgesics. However, TRPV1 remains a primary candidate for the discovery of novel analgesic drugs [3] and approximately 200 modulators of this target are currently under development (http://integrity.thomsonpharma.com). This establishes a strong future pharmacogenetic context of TRPV1 considering the increasing acknowledgment that the treatment of pain will benefit from individualized approaches including those based on the patient’s genotype [8]. Research on the genetic variation of variants in human TRPV1 or leukotriene receptor genes is an active topic that has already provided several clinically relevant functional associations. A query of the 156 genetic variants in various publicly available data sources (Online Mendelian Inheritance in Man” (OMIM®) database at http://www.ncbi.nlm.nih.gov/omim, NCBI gene index database at http://www.ncbi.nlm.nih.gov/gene; GeneCards at http://www.genecards.org [27] and the “1000 Genomes Browser” at https://www.ncbi.nlm.nih.gov/variation/tools/1000genomes; all accessed in May 2017) yielded 13 clinical associations (Table 3). The clinical associations included a variety of pathologies such as pain, asthma or osteoarthritis. Specifically, variants in both, TRPV1 and LTB4R have been associated with a higher susceptibility to bronchial asthma [28-32]. Moreover, TRPV1 variants have been associated with a higher risk of type 2 diabetes [33] or of functional dyspepsia [34]. Finally, of potential importance for a pharmacogenetic modulation of the effects of future analgesics, TRPV1 variants have been associated with altered pain phenotypes in clinical or human experimental settings [10, 35, 36]. This fits to the particular role of TRPV1 as a major target for novel analgesic drugs under development. Winter and colleagues recently created an overview of site-directed mutagenesis studies on Trpv1 receptor in rodents [37]. Their study summarized information about several mutated sites along the Trpv1, which influenced the effect or binding of different compounds like agonists, antagonists, and channel blockers and alter the responsiveness to heat and influence the regulation of the receptor function. Of peculiar interest is the c-terminus part of the receptor, because it contained several mutations implicated in binding of capsaicin. To reference this information to our study, we took out an alignment blast with http://www.uniprot.org/blast/, which is a search tool to find regions of local similarity between sequences and can be used to infer functional and evolutionary relationships between sequences revealed that TRPV1 is highly conserved. With the present NGS assay, several functional SNPs could be identified in the coding area of TRPV1; one variant (17:3477000-SNV) was located in exactly the c-terminus area mentioned above. On this basis, the impact of this variant on nociception can be prospectively studied. A pharmacogenetic modulation of the effects of TRPV1-targeting analgesics is supported by evidence of associations of rare and of common variants in the human TRPV1 gene with pain-related clinical phenotypes. Based upon the direction of change of each phenotype and cumulative changes in each SNP, three functional categories of TRPV1 variants were proposed: gain of function (hTRPV1 Q85R, P91S, and T469I), loss of function (I585V), and mixed (M315I) [38]. These in vitro results support clinical observations of TRPV1 genotypic effects. A Korean subject who was insensitive to capsaicin and displayed mRNA and protein expression levels of TRPV1 reduced by 50% from average subjects was found to carry seven intronic TRPV1 single nucleotide polymorphisms (SNPs) [9]. Similarly, women carrying a coding TRPV1 variant were found to be less sensitive to cold [10]. The association possibly involves interactions among TRP channels [39] based on evidence that TRPA1 channels are often co-expressed with heat (> 43°C [4]) gated TRPV1 [40, 41]) and the channels act in concert. TRPV1 can oligomerize with other TRP family subunits including TRPV3 and TRPA1 [42-44] and the heteromerization can affect the calcium signaling pathways of TRPA1 homomers [44]. While heat hyperalgesia was initially attributed solely to TRPV1, currently TRPA1 and TRPV1 are regarded to be regulated downstream of PLC-coupled bradykinin (BK2) receptors [45] contributing together to hypersensitivity to heat [46]. Hence, this evidence supports a possible pharmacogenetic importance. Further evidence about functional associations of TRPV1 gene variants has been raised in Spanish Caucasian migraine patients in whom the presence of the TRPV1 rs222741 variant conferred a disease risk [47]. The addition of leukotriene B4 (LTB4) receptors to the TRPV1 gene panel anticipates a possible pharmacogenetic role in TRPV1 targeting analgesics resulting from recent evidence about a co-expression of the receptors at nociceptive neurons and functional their interplay [8]. LTB4 is a potent proinflammatory agent and its signaling pathway involves two distinct G protein coupled receptors of which BLT1 is a high-affinity and BLT2 a low-affinity LTB4 receptor [48]. The interaction of LTB4 at these receptors is a contributing factor in the pathogenesis of inflammatory diseases [49]. Studies involving the targeted deletion of murine BLT1 and the effect of antagonizing LTB4 receptors in inflammatory models have highlighted the therapeutic potential of BLT receptors with regard to inflammatory diseases [49]. LTB4 has also been shown to activate the TRPV1 channel [50, 51] which leads to excitation of nociceptors and evokes pain-related behaviors [25]. While variants in the two LTB4 receptors potentially affect TRPV1 modulation based analgesic therapies, evidence about functional polymorphisms in these genes is sparse. Studies have suggested a role of polymorphisms overreaching leukotriene pathway genes in determining leukotriene production and susceptibility to allergic disorders, such as inflammatory cell chemotaxis and asthma [52]. Both receptor genes were shown to be polymorphic, in addition, LTB4R and LTB4R2 show splice variations at multiple regions, however, the functional significance has yet to be determined [53]. The present NGS method is suitable for large-scale sequencing of an extended set of human genes involving the main target, TRPV1, and recently identified co-players, LTB4R and LTB4R2. By covering almost, the complete relevant coding and regulatory parts of these genes, the method includes all variants studied so far for functional associations and adds a large amount of genetic information as a basis for complete analysis of human TRPV1 ion channel genetics and its functional consequences. The assay aimed at the complete coding and regulatory information of the selected genes, which regards the increasing acknowledgment of the insufficiency of addressing a limited selection of published functional genetic variants in providing a satisfactory genetic diagnosis of the clinical phenotype. Research interest in the complete genomic information dates back to the seventies of last century when the selective incorporation of chain-terminating dideoxynucleotides by DNA polymerase during in vitro DNA replication had been introduced [17, 18]. Techniques significantly improved during the last decades with the development of contemporary machines in the late 1990s re-leased to the market around the year 2005. The term “next generation” DNA sequencing refers to high-throughput technologies capable of parallel analyzes of large numbers of different DNA sequences in a single reaction [54]. NGS has been attributed the potential to accelerate biomedical research [12, 55, 56]. Currently, two commercial NGS platforms are widely used for diagnostic purposes: the MiSeq/HiSeq/NextSeq (Illumina, Hayward, CA, USA) and the Ion Torrent PGM (Life Technologies, Carlsbad, CA, USA). Both platforms combine conceptually similar workflows, starting with the creation of the genetic sample, which commences library preparation involving fragmentation of genomic DNA, purifying to uniform and desired fragment size and ligation to sequencing adapters specific to the platform. Differences apply to the reaction biochemistry and the way how the sequencing information is read [54]. In the present ion semiconductor sequencing method, libraries are immobilized to beads and amplified in microdroplets of aqueous solution and oil using emulsion PCR. Individual nucleotide bases are incorporated via DNA polymerase, which in the case of success triggers the release of a proton. The semiconductor chip that acts as a pH meter [57] providing the final readout. Alternative techniques use the detection of light instead, i.e., from optical fluorescence signals in the case of successful nucleotide incorporation the DNA nucleotide sequence is assembled. The different techniques differ with respect to the obtained throughput and accuracy, but multiple studies have shown that both NGS platforms provide reliable sequencing results in routine clinical diagnostics [58-61] and a recent study came up with a 100% concordance between NGS and an alternative diagnostic approach in mutant allele detection [62]. The high throughput and comprehensive information about DNA sequences are presently reflected in the assay costs. The sequencing of the TRPV1, LTB4R and LTB4R2 receptor genes of 80 patients required € 1,500 for the AmpliSeq™ custom panel, € 5,880 for library preparation, € 980 for template preparation and € 1,400 for sequencing. In addition, approximately € 600 were spent for consumables and laboratory supplies. With 40 barcoded samples loaded on two chips, respectively, analysis costs for a single patient’s gene sequence were approximately € 130. NGS costs are expected to quickly fall in near future [63]. However, despite this rapid technological progress, the analysis of the generated large data sets remains challenging [64]. As the sequencing process is only the beginning of the procedure, the analysis of the resulting “big data” requires substantial computational power, bioinformatics expertise and “up to date” databases of genomic variations. NGS technologies seem to shift the workload essentially away from the laboratory sample preparation toward various data analysis processes. We report a NGS assay based on AmpliSeq™ libraries and Ion Personal Genome Machine (PGM) suitable for large-scale sequencing of TRPV1 and functionally related genes. While the aim of assay development had the pharmacogenetics of TRPV1-targeting novel analgesics in mind, the roles of TRPV1 and the two LTB4 receptors are not restricted to this setting. By contrast, the expression of TRPV1 is also observed in non-neuronal sites such as the epithelium of bladder and lungs and in hair cells of the cochlea. At these sites, TRPV1 serves as a potential drug target for treating various diseases such as cystitis, asthma and hearing loss [65].

A list of PCR primer used for the NGS assay.

(DOCX) Click here for additional data file.

A list of missed parts from the gene panel.

(DOCX) Click here for additional data file.

The accession numbers of the original data at the BioProject database.

(DOCX) Click here for additional data file.
  69 in total

1.  Induction of total insensitivity to capsaicin and hypersensitivity to garlic extract in human by decreased expression of TRPV1.

Authors:  Joong Jean Park; Jaehee Lee; Myung Ah Kim; Seung Keun Back; Seung Kil Hong; Heung Sik Na
Journal:  Neurosci Lett       Date:  2006-11-15       Impact factor: 3.046

Review 2.  Next-generation DNA sequencing methods.

Authors:  Elaine R Mardis
Journal:  Annu Rev Genomics Hum Genet       Date:  2008       Impact factor: 8.929

3.  Vanilloid receptor-1 is essential for inflammatory thermal hyperalgesia.

Authors:  J B Davis; J Gray; M J Gunthorpe; J P Hatcher; P T Davey; P Overend; M H Harries; J Latcham; C Clapham; K Atkinson; S A Hughes; K Rance; E Grau; A J Harper; P L Pugh; D C Rogers; S Bingham; A Randall; S A Sheardown
Journal:  Nature       Date:  2000-05-11       Impact factor: 49.962

4.  The cloned capsaicin receptor integrates multiple pain-producing stimuli.

Authors:  M Tominaga; M J Caterina; A B Malmberg; T A Rosen; H Gilbert; K Skinner; B E Raumann; A I Basbaum; D Julius
Journal:  Neuron       Date:  1998-09       Impact factor: 17.173

5.  Quantitative assessment of mutant allele burden in solid tumors by semiconductor-based next-generation sequencing.

Authors:  Bryce P Portier; Rashmi Kanagal-Shamanna; Rajyalakshmi Luthra; Rajesh Singh; Mark J Routbort; Brian Handal; Neelima Reddy; Bedia A Barkoh; Zhuang Zuo; L Jeffrey Medeiros; Kenneth Aldape; Keyur P Patel
Journal:  Am J Clin Pathol       Date:  2014-04       Impact factor: 2.493

Review 6.  The TRP ion channel family.

Authors:  D E Clapham; L W Runnels; C Strübing
Journal:  Nat Rev Neurosci       Date:  2001-06       Impact factor: 34.870

Review 7.  Hot channels in airways: pharmacology of the vanilloid receptor.

Authors:  Sun Wook Hwang; Uhtaek Oh
Journal:  Curr Opin Pharmacol       Date:  2002-06       Impact factor: 5.547

8.  [TRPV1 UTR-3 polymorphism and susceptibility of childhood asthma of the Han Nationality in Beijing].

Authors:  Qiang Wang; Xuetao Bai; Donggang Xu; Dongqun Xu; Hong Li; Jianlong Fang; He Zhu; Wenliang Fu; Xin Cai; Jinfeng Wang; Zhe Jin; Qin Wang; Chunyu Xu; Junrui Chang
Journal:  Wei Sheng Yan Jiu       Date:  2009-09

9.  Leukotriene B4 receptor locus gene characterisation and association studies in asthma.

Authors:  Asif S Tulah; Bianca Beghé; Sheila J Barton; John W Holloway; Ian Sayers
Journal:  BMC Med Genet       Date:  2012-11-20       Impact factor: 2.103

10.  Agonist-dependence of functional properties for common nonsynonymous variants of human transient receptor potential vanilloid 1.

Authors:  Sen Wang; John Joseph; Luda Diatchenko; Jin Y Ro; Man-Kyo Chung
Journal:  Pain       Date:  2016-07       Impact factor: 7.926

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  4 in total

1.  Machine-Learned Association of Next-Generation Sequencing-Derived Variants in Thermosensitive Ion Channels Genes with Human Thermal Pain Sensitivity Phenotypes.

Authors:  Jörn Lötsch; Dario Kringel; Gerd Geisslinger; Bruno G Oertel; Eduard Resch; Sebastian Malkusch
Journal:  Int J Mol Sci       Date:  2020-06-19       Impact factor: 5.923

2.  Machine-learned analysis of the association of next-generation sequencing-based human TRPV1 and TRPA1 genotypes with the sensitivity to heat stimuli and topically applied capsaicin.

Authors:  Dario Kringel; Gerd Geisslinger; Eduard Resch; Bruno G Oertel; Michael C Thrun; Sarah Heinemann; Jörn Lötsch
Journal:  Pain       Date:  2018-07       Impact factor: 6.961

3.  Computational Functional Genomics-Based AmpliSeq™ Panel for Next-Generation Sequencing of Key Genes of Pain.

Authors:  Dario Kringel; Sebastian Malkusch; Eija Kalso; Jörn Lötsch
Journal:  Int J Mol Sci       Date:  2021-01-16       Impact factor: 5.923

4.  Development of an AmpliSeqTM Panel for Next-Generation Sequencing of a Set of Genetic Predictors of Persisting Pain.

Authors:  Dario Kringel; Mari A Kaunisto; Catharina Lippmann; Eija Kalso; Jörn Lötsch
Journal:  Front Pharmacol       Date:  2018-09-19       Impact factor: 5.810

  4 in total

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