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Dataset results
20 results for “sequence contamination”
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.25% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 0.25% contaminant spike-in.</p>
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 1% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 1% contaminant spike-in.</p>
Data from: Intraspecific DNA contamination distorts subtle population structure in a marine fish: decontamination of herring samples before restriction-site associated (RAD) sequencing and its effects on population genetic statistics
Wild specimens are often collected in challenging field conditions, where samples may be contaminated with the DNA of conspecific individuals. This contamination can result in false genotype calls, which are difficult to detect, but may also cause inaccurate estimates of heterozygosity, allele frequencies, and genetic differentiation. Marine broadcast spawners are especially problematic, because population genetic differentiation is low and samples are often collected in bulk and sometimes from active spawning aggregations. Here, we used contaminated and clean Pacific herring (Clupea pallasi) samples to test (i) the efficacy of bleach decontamination, (ii) the effect of decontamination on RAD genotypes, and (iii) the consequences of contaminated samples on population genetic analyses. We collected fin tissue samples from actively spawning (and thus contaminated) wild herring and non-spawning (uncontaminated) herring. Samples were soaked for 10 minutes in bleach or left untreated, and extracted DNA was used to prepare DNA libraries using a restriction-site associated DNA (RAD) approach. Our results demonstrate that intraspecific DNA contamination affects patterns of individual and population variability, causes an excess of heterozygotes, and biases estimates of population structure. Bleach decontamination was effective at removing intraspecific DNA contamination and compatible with RAD sequencing, producing high-quality sequences, reproducible genotypes, and low levels of missing data. Although sperm contamination may be specific to broadcast spawners, intraspecific contamination of samples may be common and difficult to detect from high-throughput sequencing data, and can impact downstream analyses.
Draft Genome sequencing of Nocardia sp. strain WB46 Isolated from Salix purpurea Growing in a Site Chronically Contaminated by Petroleum Hydrocarbons
<p>Assembled contigs of the genome of <em>Nocardia</em> sp. strain WB46 isolated from <em>the rhizosphere of Salix purpurea </em>growing in a site chronically contaminated by petroleum hydrocarbons located at Varennes, Qubec, Canada.</p>
Data from: Intraspecific DNA contamination distorts subtle population structure in a marine fish: decontamination of herring samples before restriction-site associated (RAD) sequencing and its effects on population genetic statistics
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Figure 1 in A fossil protein chimera; difficulties in discriminating dinosaur peptide sequences from modern cross-contamination
Figure 1. Tandem mass spectrum from high-resolution (HCD) fragmentation analysis of the peptide sequence (GPPGESGAVGPAGPIGSR) matched from our analysis of ostrich bone collagen that is homologous to the peptide proposed as unique to T. rex and B. canadensis.
Figure 2 in A fossil protein chimera; difficulties in discriminating dinosaur peptide sequences from modern cross-contamination
Figure 2. Tandem mass spectrum of the peptide sequence claimed as being endogenous to both dinosaurs with sequence (GLPGESGAVGPAGPPGSR) downloaded from the B. canadensis analysis by Schweitzer et al. [14].
Supplementary Materials for: Discovery of a novel merbecovirus DNA clone contaminating agricultural rice sequencing datasets from Wuhan, China
<p>Supplementary Materials for</p><p><strong>Discovery of a novel merbecovirus DNA clone contaminating agricultural rice sequencing datasets from Wuhan, China</strong></p><p>Adrian Jones, Daoyu Zhang, Steven E. Massey, Yuri Deigin, Louis R. Nemzer, Steven C. Quay</p>
Bins with greater than 50% completeness and less than 10% contamination from the paper "Benchmarking Metagenomic Binning Tools on Real Datasets Across Sequencing Platforms and Binning Modes".
<p>These bins, which exhibit greater than 50% completeness and less than 10% contamination, including MQ, NC, and HQ bins, were recovered from seven different data-binning combinations across five real-world datasets.</p> <p>CheckM2 results for the bins generated from each sample were also provided to corroborate the findings.</p> <p>Completeness and contamination were evaluated using CheckM 2 (version 1.0.2). We noted that the results from running CheckM2 may exhibit slight variations, but these differences do not affect the overall assessment.</p>
Accumulation of airborne, eukaryotic environmental DNA contamination: Raw sequencing data and demultiplexing info
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Data from: RAD-sequencing reveals within-generation polygenic selection in response to anthropogenic organic and metal contamination in North Atlantic Eels
Measuring the effects of selection on the genome imposed by human-altered environment is currently a major goal in ecological genomics. Given the polygenic basis of most phenotypic traits, quantitative genetic theory predicts that selection is expected to cause subtle allelic changes among covarying loci rather than pronounced changes at few loci of large effects. The goal of this study was to test for the occurrence of polygenic selection in both North Atlantic eels (European Eel, Anguilla anguilla and American Eel, A. rostrata), using a method that searches for covariation among loci that would discriminate eels from "control" vs. "polluted" environments and be associated with specific contaminants acting as putative selective agents. RAD-seq libraries resulted in 23,659 and 14,755 filtered loci for the European and American Eels respectively. A total of 142 and 141 covarying markers discriminating European and American Eels from "control" vs. "polluted" sampling localities were obtained using the Random Forest algorithm. Distance-based redundancy analyses (db-RDAs) were used to assess the relationships between these covarying markers and concentration of 34 contaminants measured for each individual eel. PCB153, 4'4'DDE and selenium were associated with covarying markers for both species, thus pointing to these contaminants as major selective agents in contaminated sites . Gene enrichment analyses suggested that sterol regulation plays an important role in the differential survival of eels in "polluted" environment. This study illustrates the power of combining methods for detecting signals of polygenic selection and for associating variation of markers with putative selective agents in studies aiming at documenting the dynamics of selection at the genomic level, and particularly so in human altered environments.
Data from: Raw whole Drosophila genome sequence traces have contaminant sequences from bacterial symbionts
Many Drosophila genomes have been sequenced and assembled recently, and many more genome sequencing projects are in progress. However, Drosophila have bacterial, fungal, and protozoan symbionts, and the DNA of these symbionts may be isolated in the process of sequencing Drosophila genomes. Here, we assess how much sequence is isolated from these symbionts and if the sequence contamination affected how these Drosophila genomes were assembled. We do find raw sequence from bacterial symbionts and humans in Drosophila genome sequence traces analyzed. Surprisingly, the four most-common contaminant species were shared among the Drosophila genomes. However, we do not find evidence of bacterial sequences in two published Drosophila genome assemblies.
Data from: Amplicon pyrosequencing late Pleistocene permafrost: the removal of putative contaminant sequences and small-scale reproducibility
DNA sequencing of ancient permafrost samples can be used to reconstruct past plant, animal and bacterial communities. In this study, we assess the small-scale reproducibility of taxonomic composition obtained from sequencing four molecular markers (mitochondrial 12S ribosomal DNA (rDNA), prokaryote 16S rDNA, mitochondrial cox1 and chloroplast trnL intron) from two soil cores sampled 10 cm apart. In addition, sequenced control reactions were used to produce a contaminant library that was used to filter similar sequences from sample libraries. Contaminant filtering resulted in the removal of 1% of reads or 0.3% of operational taxonomic units. We found similar richness, overlap, abundance and taxonomic diversity from the 12S, 16S and trnL markers from each soil core. Jaccard dissimilarity across the two soil cores was highest for metazoan taxa detected by the 12S and cox1 markers. Taxonomic community distances were similar for each marker across the two soil cores when the chi-squared metric was used; however, the 12S and cox1 markers did not cluster well when the Goodall similarity metric was used. A comparison of plant macrofossil vs. read abundance corroborates previous work that suggests eastern Beringia was dominated by grasses and forbs during cold stages of the Pleistocene, a habitat that is restricted to isolated sites in the present-day Yukon.
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.5% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 0.5% contaminant spike-in. </p>
Data from: Amplicon pyrosequencing late Pleistocene permafrost: the removal of putative contaminant sequences and small-scale reproducibility
Open the record for dataset details and reuse information.
Data from: Raw whole Drosophila genome sequence traces have contaminant sequences from bacterial symbionts
Open the record for dataset details and reuse information.
Data from: Distinguishing potential bacteria-tumor associations from contamination in a secondary data analysis of public cancer genome sequence data
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Data from: RAD-sequencing reveals within-generation polygenic selection in response to anthropogenic organic and metal contamination in North Atlantic Eels
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Data from: Origin of land plants revisited in the light of sequence contamination and missing data
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Bryophyte bacterial contamination 16s sequencing
<p>List of all sequenced 16s bacterial colonies from bryophyte contamination.</p>
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