Dataset Information

A Rapid, SuperSelective Method for Detection of Single Nucleotide Variants in Caenorhabditis elegans.

ABSTRACT: With the widespread use of single nucleotide variants generated through mutagenesis screens and genome editing technologies, there is pressing need for an efficient and low-cost strategy to genotype single nucleotide substitutions. We have developed a rapid and inexpensive method for detection of point mutants through optimization of SuperSelective (SS) primers for end-point PCR in Caenorhabditis elegans Each SS primer consists of a 5' "anchor" that hybridizes to the template, followed by a noncomplementary "bridge," and a "foot" corresponding to the target allele. The foot sequence is short, such that a single mismatch at the terminal 3' nucleotide destabilizes primer binding and prevents extension, enabling discrimination of different alleles. We explored how length and sequence composition of each SS primer segment affected selectivity and efficiency in various genetic contexts in order to develop simple rules for primer design that allow for differentiation between alleles over a broad range of annealing temperatures. Manipulating bridge length affected amplification efficiency, while modifying the foot sequence altered discriminatory power. Changing the anchor position enabled SS primers to be used for genotyping in regions with sequences that are challenging for standard primer design. After defining primer design parameters, we demonstrated the utility of SS primers for genotyping crude C. elegans lysates, suggesting that this approach could also be used for SNP mapping and screening of CRISPR mutants. Further, since SS primers reliably detect point mutations, this method has potential for broad application in all genetic systems.

SUBMITTER: Touroutine D

PROVIDER: S-EPMC7536863 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Rapid, SuperSelective Method for Detection of Single Nucleotide Variants in <i>Caenorhabditis elegans</i>.

Touroutine Denis D Tanis Jessica E JE

Genetics 20200817 2

With the widespread use of single nucleotide variants generated through mutagenesis screens and genome editing technologies, there is pressing need for an efficient and low-cost strategy to genotype single nucleotide substitutions. We have developed a rapid and inexpensive method for detection of point mutants through optimization of SuperSelective (SS) primers for end-point PCR in <i>Caenorhabditis elegans</i> Each SS primer consists of a 5' "anchor" that hybridizes to the template, followed by ...[more]

PMID: 32817008

Similar Datasets

Project description:BACKGROUND:Sensitive detection of low-frequency single nucleotide variants carries great significance in many applications. In cancer genetics research, tumor biopsies are a mixture of normal and tumor cells from various subpopulations due to tumor heterogeneity. Thus the frequencies of somatic variants from a subpopulation tend to be low. Liquid biopsies, which monitor circulating tumor DNA in blood to detect metastatic potential, also face the challenge of detecting low-frequency variants due to the small percentage of the circulating tumor DNA in blood. Moreover, in population genetics research, although pooled sequencing of a large number of individuals is cost-effective, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 2 % to 5 %; most fail to consider differential sequencing artifacts. RESULTS:We aimed to push down the frequency detection limit close to the position specific sequencing error rates by modeling the observed erroneous read counts with respect to genomic sequence contexts. 4 distributions suitable for count data modeling (using generalized linear models) were extensively characterized in terms of their goodness-of-fit as well as the performances on real sequencing data benchmarks, which were specifically designed for testing detection of low-frequency variants; two sequencing technologies with significantly different chemistry mechanisms were used to explore systematic errors. We found the zero-inflated negative binomial distribution generalized linear mode is superior to the other models tested, and the advantage is most evident at 0.5 % to 1 % range. This method is also generalizable to different sequencing technologies. Under standard sequencing protocols and depth given in the testing benchmarks, 95.3 % recall and 79.9 % precision for Ion Proton data, 95.6 % recall and 97.0 % precision for Illumina MiSeq data were achieved for SNVs with frequency?>?= 1 %, while the detection limit is around 0.5 %. CONCLUSIONS:Our method enables sensitive detection of low-frequency single nucleotide variants across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.

Project description:Summary In this work, we developed a simple and robust assay to rapidly detect SNPs in nucleic acid samples. Our approach combines loop-mediated isothermal amplification (LAMP)-based target amplification with fluorescent probes to detect SNPs with high specificity. A competitive “sink” strand preferentially binds to non-SNP amplicons and shifts the free energy landscape to favor specific activation by SNP products. We demonstrated the broad utility and reliability of our SNP-LAMP method by detecting three distinct SNPs across the human genome. We also designed an assay to rapidly detect highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from crude biological samples. This work demonstrates that competitive SNP-LAMP is a powerful and universal method that could be applied in point-of-care settings to detect any target SNP with high specificity and sensitivity. We additionally developed a publicly available web application for researchers to design SNP-LAMP probes for any target sequence of interest. Graphical abstract Highlights • A simple and rapid assay to detect specific SNPs in complex nucleic acid samples• Approach leverages competitive probes to specifically detect SNP over non-SNP sequences• Demonstrated utility across diverse targets and sample types• Web application for researchers to design SNP-LAMP probes for any target of interest Motivation Single-nucleotide polymorphisms (SNPs) are the most common source of genetic variation between individuals and have implications in human disease, pathogen drug resistance, and agriculture. SNPs are often detected using DNA sequencing or PCR, both of which can be difficult to deploy for on-site testing or in low-resource settings. There is a need for new SNP detection methods that can be performed rapidly without advanced laboratory equipment or a cold supply chain. Detecting single-nucleotide polymorphisms (SNPs) is important for understanding human disease, the emergence of pathogen variants, and the application of genetic agricultural breeding programs. Hyman et al. develop a simple and rapid assay to detect SNPs in complex nucleic acid samples. A web-based tool allows researchers to design custom SNP probes.

Dataset Information

A Rapid, SuperSelective Method for Detection of Single Nucleotide Variants in Caenorhabditis elegans.

Publications

A Rapid, SuperSelective Method for Detection of Single Nucleotide Variants in <i>Caenorhabditis elegans</i>.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets