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8 results for “PCR bias”
Data from: Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias
Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers (16S and COI) and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico less than 75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided greater than 90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 different insect orders and one arachnid. We PCR-amplified the blend using five primers sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR, and that researchers should be wary of potential bias when selecting metabarcoding markers.
Data from: Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias
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Exploring protocol bias in airway microbiome studies: One versus two PCR steps and 16S rRNA gene region V3 V4 versus V4
<p>Background: Studies on the airway microbiome have been performed using a wide range of laboratory protocols for high-throughput sequencing of the bacterial 16S ribosomal RNA (16S rRNA) gene. We sought to determine the impact of number of polymerase chain reaction (PCR) steps (1- or 2-steps) and choice of target marker gene region (V3 V4 and V4) on the presentation of the upper and lower airway microbiome. Our analyses included lllumina MiSeq sequencing following three setups: Setup 1 (2-step PCR; V3 V4 region), Setup 2 (2-step PCR; V4 region), Setup 3 (1-step PCR; V4 region). Samples included oral wash, protected specimen brushes and protected bronchoalveolar lavage (healthy and obstructive lung disease), and negative controls. Results: The number of sequences and amplicon sequence variants (ASV) decreased in order setup1>setup2>setup3. This trend appeared to be associated with an increased taxonomic resolution when sequencing the V3 V4 region (setup 1) and an increased number of small ASVs in setups 1 and 2. The latter was considered a result of contamination in the two-step PCR protocols as well as sequencing across multiple runs (setup 1). Although genera <i>Streptococcus</i>, <i>Prevotella</i>, <i>Veillonella</i> and <i>Rothia</i> dominated, differences in relative abundance were observed across all setups. Analyses of beta-diversity revealed that while oral wash samples (high biomass) clustered together regardless of number of PCR steps, samples from the lungs (low biomass) separated. The removal of contaminants identified using the Decontam package in R, did not resolve differences in results between sequencing setups. Conclusions: Differences in number of PCR steps will have an impact of final bacterial community descriptions, and more so for samples of low bacterial load. Our findings could not be explained by differences in contamination levels alone, and more research is needed to understand how variations in PCR-setups and reagents may be contributing to the observed protocol bias.</p>
Exploring protocol bias in airway microbiome studies: One versus two PCR steps and 16S rRNA gene region V3 V4 versus V4
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PCR cycles affect gibbs free energy bias
GEO Series GSE149914. Homo sapiens. 4 samples. Type: Other.
Data from: Indexed PCR primers induce template-specific bias in large-scale DNA sequencing studies
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Distinct 5′ and 3′ Coverage Biases Shape Transcriptome Interpretation in Nanopore Direct RNA versus PCR-cDNA Sequencing
GEO Series GSE306225. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Investigating PCR bias in TnSeq
GEO Series GSE162988. Staphylococcus aureus. 22 samples. Type: Other.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.