scholarly journals Oropouche virus cases identified in Ecuador using an optimised rRT-PCR informed by metagenomic sequencing

2019 ◽  
Author(s):  
Emma L. Wise ◽  
Sully Márquez ◽  
Jack Mellors ◽  
Verónica Paz ◽  
Barry Atkinson ◽  
...  
Keyword(s):  
Cell Culture ◽  
Whole Genome Amplification ◽  
Febrile Illness ◽  
Whole Genome ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Pcr Assay ◽  
Genome Coverage ◽  
Phylogenetic Cluster ◽  
Primer Mismatch

AbstractOropouche virus (OROV) is responsible for outbreaks of Oropouche fever in parts of South America. We recently identified and isolated OROV from a febrile Ecuadorian patient, however, a previously published rRT-PCR assay did not detect OROV in the patient sample. A primer mismatch to the Ecuadorian OROV lineage was identified from metagenomic sequencing data. We report the optimisation of an rRT-PCR assay for the Ecuadorian OROV lineage, which subsequently identified a further five cases in a cohort of 196 febrile patients. We isolated OROV via cell culture and developed an algorithmically-designed primer set for whole-genome amplification of the virus. Metagenomic sequencing of the patient samples provided OROV genome coverage ranging from 68 - 99%. The additional cases formed a single phylogenetic cluster together with the initial case. OROV should be considered as a differential diagnosis for Ecuadorian patients with febrile illness to avoid mis-diagnosis with other circulating pathogens.

scholarly journals Optimization of parasite DNA enrichment approaches to generate whole genome sequencing data for Plasmodium falciparum from low-parasitaemia samples

2020 ◽  
Author(s):  
Zalak Shah ◽  
Matthew Adams ◽  
Kara A Moser ◽  
Biraj Shrestha ◽  
Emily M Stucke ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Sequencing Data ◽  
Vacuum Filtration ◽  
Genome Coverage ◽  
Amplification Bias ◽  
Leukocyte Depletion

Abstract Background Owing to the large amount of host DNA in clinical samples, generation of high-quality Plasmodium falciparum whole genome sequencing (WGS) data requires enrichment for parasite DNA. Enrichment is often achieved by leukocyte depletion of infected blood prior to storage. However, leukocyte depletion is difficult in low-resource settings and limits analysis to prospectively-collected samples. As a result, approaches such as selective whole genome amplification (sWGA) are being used to enrich for parasite DNA. However, sWGA has had limited success in generating reliable sequencing data from low parasitaemia samples. In this study, enzymatic digestion with MspJI prior to sWGA and whole genome sequencing was evaluated to determine whether this approach improved genome coverage compared to sWGA alone. The potential of sWGA to cause amplification bias in polyclonal infections was also examined. Methods DNA extracted from laboratory-created dried blood spots was treated with a modification-dependent restriction endonuclease, MspJI, and filtered via vacuum filtration. Samples were then selectively amplified using a previously reported sWGA protocol and subjected to WGS. Genome coverage statistics were compared between the optimized sWGA approach and the previously reported sWGA approach performed in parallel. Differential amplification by sWGA was assessed by comparing WGS data generated from lab-created mixtures of parasite isolates, from the same geographical region, generated with or without sWGA. Results MspJI digestion did not enrich for parasite DNA. Samples that underwent vacuum filtration (without MspJI digestion) prior to sWGA had the highest parasite DNA concentration and displayed greater genome coverage compared to MspJI+sWGA and sWGA alone, particularly for low parasitaemia samples. The optimized sWGA (filtration + sWGA) approach was successfully used to generate WGS data from 218 non-leukocyte depleted field samples from Malawi. Sequences from lab-created mixtures of parasites did not show evidence of differential amplification of parasite strains compared to directly sequenced samples. Conclusion This optimized sWGA approach is a reliable method to obtain WGS data from non-leukocyte depleted, low parasitaemia samples. The absence of amplification bias in data generated from mixtures of isolates from the same geographic region suggests that this approach can be appropriately used for molecular epidemiological studies. Keywords Plasmodium falciparum , malaria, whole genome sequencing, selective whole genome amplification, vacuum filtration

scholarly journals Whole genome amplification with SurePlex results in better copy number alteration detection using sequencing data compared to the MALBAC method

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Lieselot Deleye ◽  
Dieter De Coninck ◽  
Christodoulos Christodoulou ◽  
Tom Sante ◽  
Annelies Dheedene ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Amplification

scholarly journals Optimization of parasite DNA enrichment approaches to generate whole genome sequencing data for Plasmodium falciparum from low-parasitemia samples

2019 ◽  
Author(s):  
Zalak Shah ◽  
Matthew Adams ◽  
Kara A Moser ◽  
Biraj Shrestha ◽  
Emily M Stucke ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Geographic Region ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Coverage ◽  
Amplification Bias ◽  
Leukocyte Depletion ◽  
Field Samples

Abstract Background: Owing to the large amount of host DNA in clinical samples, generation of high-quality Plasmodium falciparum whole genome sequencing (WGS) data requires enrichment for parasite DNA. Enrichment is often achieved by leukocyte depletion of infected blood prior to storage. However, leukocyte depletion is difficult in low-resource settings and limits analysis to prospectively-collected samples. As a result, approaches such as selective whole genome amplification (sWGA) are being used to enrich for parasite DNA, reducing the need for pre-processing of samples. However, sWGA has had limited success in generating reliable sequencing data from low parasitemia samples. In this study, we evaluated whether enzymatic digestion with MspJI prior to sWGA and whole genome sequencing improves genome coverage compared to sWGA alone when applied to samples representing a range of parasitemias. We also examined the potential of sWGA to cause amplification bias in polyclonal infections. Results: MspJI digestion did not enrich for parasite DNA. Samples that underwent filtration prior to sWGA had the highest parasite DNA yield and displayed higher genome coverage compared to MspJI+sWGA and sWGA only, particularly for low parasitemia samples. The optimized sWGA approach was successfully used to generate WGS data from 218 non-leukocyte depleted field samples from Malawi. Sequences from lab-created mixtures of parasite isolates from the same geographic region generated using the optimized sWGA did not show evidence of differential amplification of parasite strains compared to directly sequenced samples. Conclusion: The optimized sWGA approach is a reliable method to obtain WGS data from non-leukocyte depleted, low parasitemia samples. The absence of amplification bias in data generated from mixtures of isolates from the same geographic region suggests that this approach can be appropriately used for molecular epidemiological studies.

scholarly journals Comparison of single-cell whole-genome amplification strategies

2018 ◽  
Author(s):  
Nuria Estévez-Gómez ◽  
Tamara Prieto ◽  
Amy Guillaumet-Adkins ◽  
Holger Heyn ◽  
Sonia Prado-López ◽  
...  
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Amplification ◽  
Dna Yield ◽  
Amplification Bias ◽  
Random Amplification ◽  
Low Pass ◽  
Amplicon Size

Single-cell genomics is an alluring area that holds the potential to change the way we understand cell populations. Due to the small amount of DNA within a single cell, whole-genome amplification becomes a mandatory step in many single-cell applications. Unfortunately, single-cell whole-genome amplification (scWGA) strategies suffer from several technical biases that complicate the posterior interpretation of the data. Here we compared the performance of six different scWGA methods (GenomiPhi, REPLIg, TruePrime, Ampli1, MALBAC, and PicoPLEX) after amplifying and low-pass sequencing the complete genome of 230 healthy/tumoral human cells. Overall, REPLIg outperformed competing methods regarding DNA yield, amplicon size, amplification breadth, amplification uniformity –being the only method with a random amplification bias–, and false single-nucleotide variant calls. On the other hand, non-MDA methods, and in particular Ampli1, showed less allelic imbalance and ADO, more reliable copy-number profiles and less chimeric amplicons. While no single scWGA method showed optimal performance for every aspect, they clearly have distinct advantages. Our results provide a convenient guide for selecting a scWGA method depending on the question of interest while revealing relevant weaknesses that should be considered during the analysis and interpretation of single-cell sequencing data.

scholarly journals Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

2017 ◽  
Author(s):  
Tamir Biezuner ◽  
Ofir Raz ◽  
Shiran Amir ◽  
Lilach Milo ◽  
Rivka Adar ◽  
...  
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Targeted Sequencing ◽  
Whole Genome ◽  
Genome Coverage ◽  
Genome Amplification ◽  
Cell Experiment ◽  
Commercial Kits ◽  
Genomic Regions

AbstractAdvances in biochemical technologies have led to a boost in the field of single cell genomics. Observation of the genome at a single cell resolution is currently achieved by pre-amplification using whole genome amplification (WGA) techniques that differ by their biochemical aspects and as a result by biased amplification of the original molecule. Several comparisons between commercially available single cell dedicated WGA kits (scWGA) were performed, however, these comparisons are costly, were only performed on selected scWGA kit and more notably, are limited by the number of analyzed cells, making them limited for reproducibility analysis. We benchmarked an economical assay to compare all commercially available scWGA kits that is based on targeted sequencing of thousands of genomic regions, including highly mutable genomic regions (microsatellites), from a large cohort of human single cells (125 cells in total). Using this approach, we could analyze the genome coverage, the reproducibility of genome coverage and the error rate of each kit. Our experimental design provides an affordable and reliable comparative assay that simulates a real single cell experiment. Results demonstrate the needfor a dedicated kit selection depending on the desired single cell assay.

scholarly journals Environmental Whole-Genome Amplification To Access Microbial Populations in Contaminated Sediments

2006 ◽  
Vol 72 (5) ◽  
pp. 3291-3301 ◽  
Author(s):  
Carl B. Abulencia ◽  
Denise L. Wyborski ◽  
Joseph A. Garcia ◽  
Mircea Podar ◽  
Wenqiong Chen ◽  
...  
Keyword(s):  
Contaminated Soils ◽  
Whole Genome Amplification ◽  
Multiple Displacement Amplification ◽  
Department Of Energy ◽  
Contaminated Site ◽  
Small Subset ◽  
Whole Genome ◽  
Genome Coverage ◽  
Genome Amplification ◽  
Amplification Bias

ABSTRACT Low-biomass samples from nitrate and heavy metal contaminated soils yield DNA amounts that have limited use for direct, native analysis and screening. Multiple displacement amplification (MDA) using φ29 DNA polymerase was used to amplify whole genomes from environmental, contaminated, subsurface sediments. By first amplifying the genomic DNA (gDNA), biodiversity analysis and gDNA library construction of microbes found in contaminated soils were made possible. The MDA method was validated by analyzing amplified genome coverage from approximately five Escherichia coli cells, resulting in 99.2% genome coverage. The method was further validated by confirming overall representative species coverage and also an amplification bias when amplifying from a mix of eight known bacterial strains. We extracted DNA from samples with extremely low cell densities from a U.S. Department of Energy contaminated site. After amplification, small-subunit rRNA analysis revealed relatively even distribution of species across several major phyla. Clone libraries were constructed from the amplified gDNA, and a small subset of clones was used for shotgun sequencing. BLAST analysis of the library clone sequences showed that 64.9% of the sequences had significant similarities to known proteins, and “clusters of orthologous groups” (COG) analysis revealed that more than half of the sequences from each library contained sequence similarity to known proteins. The libraries can be readily screened for native genes or any target of interest. Whole-genome amplification of metagenomic DNA from very minute microbial sources, while introducing an amplification bias, will allow access to genomic information that was not previously accessible.

scholarly journals Variance of allele balance calculated from low coverage sequencing data infers departure from a diploid state.

2021 ◽  
Author(s):  
Kyle Fletcher ◽  
Rongkui Han ◽  
Diederik Smilde ◽  
Richard Michelmore
Keyword(s):  
Sequence Analysis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Bremia Lactucae ◽  
Sequencing Data ◽  
Sequence Coverage ◽  
Perl Script ◽  
Genome Sequence Analysis ◽  
Genome Coverage ◽  
Low Coverage

Polyploidy and heterokaryosis are common and consequential genetic phenomena that increase the number of haplotypes in an organism and complicate whole-genome sequence analysis. Allele balance has been used to infer polyploidy and heterokaryosis in diverse organisms using read sets sequenced to greater than 50x whole-genome coverage. However, Sequencing to adequate depth is costly if applied to multiple individuals or large genomes. We developed VCFvariance.pl to utilize the variance of allele balance to infer polyploidy and/or heterokaryosis at low sequence coverage. This analysis requires as little as 10x whole-genome coverage and reduces the allele balance profile down to a single value, which can be used to determine if an individual has two or more haplotypes. This approach was validated on simulated, synthetic, and authentic read sets from an oomycete, fungus, and plant. The approach was deployed to ascertain the genome status of multiple isolates of Bremia lactucae and Phytophthora infestans. VCFvariance.pl is a Perl script available at https://github.com/kfletcher88/VCFvariance.

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