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Comparison of three PCR-based assays for SNP genotyping in plants.

ABSTRACT: Background:PCR allelic discrimination technologies have broad applications in the detection of single nucleotide polymorphisms (SNPs) in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeted SNP detection, but assay costs and error rates could be improved to increase genotyping efficiency. A new assay, rhAmp, based on RNase H2-dependent PCR (rhPCR) combined with a universal reporter system attempts to reduce error rates from primer/primer and primer/probe dimers while lowering costs compared to existing technologies. Before rhAmp can be widely adopted, more experimentation is required to validate its effectiveness versus established methods. Results:The aim of this study was to compare the accuracy, sensitivity and costs of TaqMan, KASP, and rhAmp SNP genotyping methods in sugar beet (Beta vulgaris L.). For each approach, assays were designed to genotype 33 SNPs in a set of 96 sugar beet individuals obtained from 12 parental lines. The assay sensitivity was tested using a series of dilutions from 100 to 0.1 ng per PCR reaction. PCR was carried out on the QuantStudio 12K Flex Real-Time PCR System (Thermo Fisher Scientific, USA). The call-rate, defined as the percentage of genotype calls relative to the possible number of calls, was 97.0, 97.6, and 98.1% for TaqMan, KASP, and rhAmp, respectively. For rhAmp SNP, 24 of the 33 SNPs demonstrated 100% concordance with other two technologies. The genotype concordance with either technologies for the other 9 targets was above 99% (99.34-99.89%). Conclusion:The sensitivity test demonstrated that TaqMan and rhAmp were able to successfully determine SNP genotypes using as little as 0.2 ng DNA per reaction, while the KASP was unable to ascertain SNP states below 0.9 ng of DNA per reaction. Comparative cost per reaction was also analyzed with rhAmp SNP offering the lowest cost per reaction. In conclusion, rhAmp produced more calls than either TaqMan or KASP, higher signal to NTC data while offering the lowest cost per reaction.

SUBMITTER: Broccanello C

PROVIDER: S-EPMC5872507 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Comparison of three PCR-based assays for SNP genotyping in plants.

Broccanello Chiara C Chiodi Claudia C Funk Andrew A McGrath J Mitchell JM Panella Lee L Stevanato Piergiorgio P

Plant methods 20180328

<h4>Background</h4>PCR allelic discrimination technologies have broad applications in the detection of single nucleotide polymorphisms (SNPs) in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeted SNP detection, but assay costs and error rates could be improved to increase genotyping efficiency. A new assay, rhAmp, based on RNase H2-dependent PCR (rhPCR) combined with a universal reporter system attempts to reduce error rates from primer/primer and pri ...[more]

PMID: 29610576

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Project description:We compared two consensus primer PCR human papillomavirus (HPV) genotyping methods for the detection of individual HPV genotypes and carcinogenic HPV genotypes as a group, using a stratified sample of enrollment cervical specimens from sexually active women participating in the NCI/Costa Rica HPV16/18 Vaccine Efficacy Trial. For the SPF(10) method, DNA was extracted from 0.1% of the cervical specimen by using a MagNA Pure LC instrument, a 65-bp region of the HPV L1 gene was targeted for PCR amplification by using SPF(10) primers, and 25 genotypes were detected by reverse-line blot hybridization of the amplicons. For the Linear Array (LA) method, DNA was extracted from 0.5% of the cervical specimen by using an MDx robot, a 450-bp region of the HPV L1 gene was targeted for PCR amplification by using PGMY09/11 L1 primers, and 37 genotypes were detected by reverse-line blot hybridization of the amplicons. Specimens (n = 1,427) for testing by the LA method were randomly selected from strata defined on the basis of enrollment test results from the SPF(10) method, cytology, and Hybrid Capture 2. LA results were extrapolated to the trial cohort (n = 5,659). The LA and SPF(10) methods detected 21 genotypes in common; HPV16, -18, -31, -33, -35, -39, -45, -51, -52, -56, -58, -59, -66, -68, and -73 were considered the carcinogenic HPV genotypes. There was no difference in the overall results for grouped detection of carcinogenic HPV by the SPF(10) and LA methods (35.3% versus 35.9%, respectively; P = 0.5), with a 91.8% overall agreement and a kappa value of 0.82. In comparisons of individual HPV genotypes, the LA method detected significantly more HPV16, HPV18, HPV39, HPV58, HPV59, HPV66, and HPV68/73 and less HPV31 and HPV52 than the SPF(10) method; inclusion of genotype-specific testing for HPV16 and HPV18 for those specimens testing positive for HPV by the SPF(10) method but for which no individual HPV genotype was detected abrogated any differences between the LA and SPF(10) methods. The LA method detected more carcinogenic-HPV-genotype infections per specimen than the SPF(10) method (P < 0.001). In conclusion, the LA method and the SPF(10) method with HPV16 and HPV18 genotype-specific detection among ungenotyped HPV-positive specimens were comparable for detection of HPV16 and HPV18, the two HPV genotypes targeted by current prophylactic HPV vaccines. Both approaches are suitable for monitoring the impact of HPV16/18 vaccines in clinical trials.

Project description:BackgroundMicrobial forensics is important in tracking the source of a pathogen, whether the disease is a naturally occurring outbreak or part of a criminal investigation.ResultsA method and SPR Opt (SNP and PCR-RFLP Optimization) software to perform a comprehensive, whole-genome analysis to forensically discriminate multiple sequences is presented. Tools for the optimization of forensic typing using Single Nucleotide Polymorphism (SNP) and PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) analyses across multiple isolate sequences of a species are described. The PCR-RFLP analysis includes prediction and selection of optimal primers and restriction enzymes to enable maximum isolate discrimination based on sequence information. SPR Opt calculates all SNP or PCR-RFLP variations present in the sequences, groups them into haplotypes according to their co-segregation across those sequences, and performs combinatoric analyses to determine which sets of haplotypes provide maximal discrimination among all the input sequences. Those set combinations requiring that membership in the fewest haplotypes be queried (i.e. the fewest assays be performed) are found. These analyses highlight variable regions based on existing sequence data. These markers may be heterogeneous among unsequenced isolates as well, and thus may be useful for characterizing the relationships among unsequenced as well as sequenced isolates. The predictions are multi-locus. Analyses of mumps and SARS viruses are summarized. Phylogenetic trees created based on SNPs, PCR-RFLPs, and full genomes are compared for SARS virus, illustrating that purported phylogenies based only on SNP or PCR-RFLP variations do not match those based on multiple sequence alignment of the full genomes.ConclusionThis is the first software to optimize the selection of forensic markers to maximize information gained from the fewest assays, accepting whole or partial genome sequence data as input. As more sequence data becomes available for multiple strains and isolates of a species, automated, computational approaches such as those described here will be essential to make sense of large amounts of information, and to guide and optimize efforts in the laboratory. The software and source code for SPR Opt is publicly available and free for non-profit use at http://www.llnl.gov/IPandC/technology/software/softwaretitles/spropt.php.

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Comparison of three PCR-based assays for SNP genotyping in plants.

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Comparison of three PCR-based assays for SNP genotyping in plants.

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