scholarly journals A targeted subgenomic approach for phylogenomics based on microfluidic PCR and high throughput sequencing

2015 ◽  
Author(s):  
Simon Uribe-Convers ◽  
Matthew L Settles ◽  
David C Tank
Keyword(s):  
High Throughput ◽  
Evolutionary Biology ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Phylogenetic Analyses ◽  
Nuclear Genome ◽  
Sequence Information ◽  
Biological Sequence ◽  
Bioinformatics Pipeline ◽  
Genomic Libraries

Advances in high-throughput sequencing (HTS) have allowed researchers to obtain large amounts of biological sequence information at speeds and costs unimaginable only a decade ago. Phylogenetics, and the study of evolution in general, is quickly migrating towards using HTS to generate larger and more complex molecular datasets. In this paper, we present a method that utilizes microfluidic PCR and HTS to generate large amounts of sequence data suitable for phylogenetic analyses. The approach uses a Fluidigm microfluidic PCR array and two sets of PCR primers to simultaneously amplify 48 target regions across 48 samples, incorporating sample-specific barcodes and HTS adapters (2,304 unique amplicons per microfluidic array). The final product is a pooled set of amplicons ready to be sequenced, and thus, there is no need to construct separate, costly genomic libraries for each sample. Further, we present a bioinformatics pipeline to process the raw HTS reads to either generate consensus sequences (with or without ambiguities) for every locus in every sample or—more importantly—recover the separate alleles from heterozygous target regions in each sample. This is important because it adds allelic information that is well suited for coalescent-based phylogenetic analyses that are becoming very common in conservation and evolutionary biology. To test our subgenomic method and bioinformatics pipeline, we sequenced 576 samples across 96 target regions belonging to the South American clade of the genus Bartsia L. in the plant family Orobanchaceae. After sequencing cleanup and alignment, the experiment resulted in ~25,300bp across 486 samples for a set of 48 primer pairs targeting the plastome, and ~13,500bp for 363 samples for a set of primers targeting regions in the nuclear genome. Finally, we constructed a combined concatenated matrix from all 96 primer combinations, resulting in a combined aligned length of ~40,500bp for 349 samples.

scholarly journals High-Throughput Genomic Data Reveal Complex Phylogenetic Relationships in Stylosanthes Sw (Leguminosae)

2021 ◽  
Vol 12 ◽  
Author(s):  
Maria Alice Silva Oliveira ◽  
Tomáz Nunes ◽  
Maria Aparecida Dos Santos ◽  
Danyelle Ferreira Gomes ◽  
Iara Costa ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
High Throughput ◽  
Phylogenetic Relationships ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Species Recognition ◽  
Phylogenetic Analyses ◽  
Nuclear Genome ◽  
Proximal Region ◽  
Legume Crop

Allopolyploidy is widely present across plant lineages. Though estimating the correct phylogenetic relationships and origin of allopolyploids may sometimes become a hard task. In the genus Stylosanthes Sw. (Leguminosae), an important legume crop, allopolyploidy is a key speciation force. This makes difficult adequate species recognition and breeding efforts on the genus. Based on comparative analysis of nine high-throughput sequencing (HTS) samples, including three allopolyploids (S. capitata Vogel cv. “Campo Grande,” S. capitata “RS024” and S. scabra Vogel) and six diploids (S. hamata Taub, S. viscosa (L.) Sw., S. macrocephala M. B. Ferreira and Sousa Costa, S. guianensis (Aubl.) Sw., S. pilosa M. B. Ferreira and Sousa Costa and S. seabrana B. L. Maass & 't Mannetje) we provide a working pipeline to identify organelle and nuclear genome signatures that allowed us to trace the origin and parental genome recognition of allopolyploids. First, organelle genomes were de novo assembled and used to identify maternal genome donors by alignment-based phylogenies and synteny analysis. Second, nuclear-derived reads were subjected to repetitive DNA identification with RepeatExplorer2. Identified repeats were compared based on abundance and presence on diploids in relation to allopolyploids by comparative repeat analysis. Third, reads were extracted and grouped based on the following groups: chloroplast, mitochondrial, satellite DNA, ribosomal DNA, repeat clustered- and total genomic reads. These sets of reads were then subjected to alignment and assembly free phylogenetic analyses and were compared to classical alignment-based phylogenetic methods. Comparative analysis of shared and unique satellite repeats also allowed the tracing of allopolyploid origin in Stylosanthes, especially those with high abundance such as the StyloSat1 in the Scabra complex. This satellite was in situ mapped in the proximal region of the chromosomes and made it possible to identify its previously proposed parents. Hence, with simple genome skimming data we were able to provide evidence for the recognition of parental genomes and understand genome evolution of two Stylosanthes allopolyploids.

scholarly journals MiDRMpol: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors

Viruses ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 806
Author(s):  
Shambhu G. Aralaguppe ◽  
Anoop T. Ambikan ◽  
Manickam Ashokkumar ◽  
Milner M. Kumar ◽  
Luke Elizabeth Hanna ◽  
...  
Keyword(s):  
Drug Resistance ◽  
High Throughput ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Polymorphism Analysis ◽  
Resistance Mutations ◽  
Subtype C ◽  
Bioinformatics Pipeline ◽  
Drug Resistance Mutations ◽  
Hiv 1

The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRMpol, to quantify DRM from the HIV-1 pol region. The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq (Polymorphism Analysis by Sequencing). Based on an error rate of <1%, a value of >1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the <5% level by MiDRMpol but not by PASeq. MiDRMpol is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (<20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM.

scholarly journals Comprehensive pathogen detection in sera of Kawasaki disease patients by high-throughput sequencing: a retrospective exploratory study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yuka Torii ◽  
Kazuhiro Horiba ◽  
Satoshi Hayano ◽  
Taichi Kato ◽  
Takako Suzuki ◽  
...  
Keyword(s):  
Kawasaki Disease ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Early Stage ◽  
Rna Virus ◽  
Systemic Vasculitis ◽  
Human Herpesvirus ◽  
Acute Stage ◽  
Serum Samples

Abstract Background Kawasaki disease (KD) is an idiopathic systemic vasculitis that predominantly damages coronary arteries in children. Various pathogens have been investigated as triggers for KD, but no definitive causative pathogen has been determined. As KD is diagnosed by symptoms, several days are needed for diagnosis. Therefore, at the time of diagnosis of KD, the pathogen of the trigger may already be diminished. The aim of this study was to explore comprehensive pathogens in the sera at the acute stage of KD using high-throughput sequencing (HTS). Methods Sera of 12 patients at an extremely early stage of KD and 12 controls were investigated. DNA and RNA sequences were read separately using HTS. Sequence data were imported into the home-brew meta-genomic analysis pipeline, PATHDET, to identify the pathogen sequences. Results No RNA virus reads were detected in any KD case except for that of equine infectious anemia, which is known as a contaminant of commercial reverse transcriptase. Concerning DNA viruses, human herpesvirus 6B (HHV-6B, two cases) and Anelloviridae (eight cases) were detected among KD cases as well as controls. Multiple bacterial reads were obtained from KD and controls. Bacteria of the genera Acinetobacter, Pseudomonas, Delfita, Roseomonas, and Rhodocyclaceae appeared to be more common in KD sera than in the controls. Conclusion No single pathogen was identified in serum samples of patients at the acute phase of KD. With multiple bacteria detected in the serum samples, it is difficult to exclude the possibility of contamination; however, it is possible that these bacteria might stimulate the immune system and induce KD.

scholarly journals Assessing Genome-Wide Diversity in European Hantaviruses through Sequence Capture from Natural Host Samples

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 749 ◽  
Author(s):  
Melanie Hiltbrunner ◽  
Gerald Heckel
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Phylogenetic Analyses ◽  
Common Vole ◽  
Natural Host ◽  
Sequence Information ◽  
Coding Region ◽  
Sequence Capture ◽  
Genome Wide ◽  
The Impact

Research on the ecology and evolution of viruses is often hampered by the limitation of sequence information to short parts of the genomes or single genomes derived from cultures. In this study, we use hybrid sequence capture enrichment in combination with high-throughput sequencing to provide efficient access to full genomes of European hantaviruses from rodent samples obtained in the field. We applied this methodology to Tula (TULV) and Puumala (PUUV) orthohantaviruses for which analyses from natural host samples are typically restricted to partial sequences of their tri-segmented RNA genome. We assembled a total of ten novel hantavirus genomes de novo with very high coverage (on average >99%) and sequencing depth (average >247×). A comparison with partial Sanger sequences indicated an accuracy of >99.9% for the assemblies. An analysis of two common vole (Microtus arvalis) samples infected with two TULV strains each allowed for the de novo assembly of all four TULV genomes. Combining the novel sequences with all available TULV and PUUV genomes revealed very similar patterns of sequence diversity along the genomes, except for remarkably higher diversity in the non-coding region of the S-segment in PUUV. The genomic distribution of polymorphisms in the coding sequence was similar between the species, but differed between the segments with the highest sequence divergence of 0.274 for the M-segment, 0.265 for the S-segment, and 0.248 for the L-segment (overall 0.258). Phylogenetic analyses showed the clustering of genome sequences consistent with their geographic distribution within each species. Genome-wide data yielded extremely high node support values, despite the impact of strong mutational saturation that is expected for hantavirus sequences obtained over large spatial distances. We conclude that genome sequencing based on capture enrichment protocols provides an efficient means for ecological and evolutionary investigations of hantaviruses at an unprecedented completeness and depth.

scholarly journals SARS-CoV-2 Evolution among Oncological Population: In-Depth Virological Analysis of a Clinical Cohort

2021 ◽  
Vol 9 (10) ◽  
pp. 2145
Author(s):  
Florian Laubscher ◽  
Samuel Cordey ◽  
Alex Friedlaender ◽  
Cecilia Schweblin ◽  
Sarah Noetzlin ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Cohort Analysis ◽  
Rapid Evolution ◽  
Nasopharyngeal Swab ◽  
Bioinformatics Pipeline ◽  
Oncological Patient ◽  
Patient Cohort ◽  
Oncological Patients ◽  
Minority Variants

Background: Oncological patients have a higher risk of prolonged SARS-CoV-2 shedding, which, in turn, can lead to evolutionary mutations and emergence of novel viral variants. The aim of this study was to analyze biological samples of a cohort of oncological patients by deep sequencing to detect any significant viral mutations. Methods: High-throughput sequencing was performed on selected samples from a SARS-CoV-2-positive oncological patient cohort. Analysis of variants and minority variants was performed using a validated bioinformatics pipeline. Results: Among 54 oncological patients, we analyzed 12 samples of 6 patients, either serial nasopharyngeal swab samples or samples from the upper and lower respiratory tracts, by high-throughput sequencing. We identified amino acid changes D614G and P4715L as well as mutations at nucleotide positions 241 and 3037 in all samples. There were no other significant mutations, but we observed intra-host evolution in some minority variants, mainly in the ORF1ab gene. There was no significant mutation identified in the spike region and no minority variants common to several hosts. Conclusions: There was no major and rapid evolution of viral strains in this oncological patient cohort, but there was minority variant evolution, reflecting a dynamic pattern of quasi-species replication.

scholarly journals High-throughput metabarcoding characterises fungal endophyte diversity in the phyllosphere of a barley crop

2021 ◽  
Author(s):  
Carla Bridget Milazzo ◽  
Katherine Grace Zulak ◽  
Mariano Jordi Muria-Gonzalez ◽  
Darcy Jones ◽  
Matthew Power ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Large Subunit ◽  
Fungal Endophytes ◽  
Environmental Dna ◽  
Fungal Endophyte ◽  
Bioinformatics Pipeline ◽  
Pests And Diseases ◽  
Key Factor ◽  
Agroecosystem Management

Over the last decade, the microbiome has received increasing attention as a key factor in macroorganism fitness. Sustainable pest management requires an understanding of the complex microbial endophyte communities existing symbiotically within plants and the way synthetic pesticides interact with them. Fungal endophytes are known to benefit plant growth and fitness and may deter pests and diseases. Recent advances in high-throughput sequencing (HTS) have enabled integrative microbiome studies especially in agricultural contexts. Here we profile the fungal endophyte community in the phyllosphere of two barley (Hordeum vulgare) cultivars exposed to two systemic foliar fungicides using metabarcoding, a HTS tool that constructs community profiles from environmental DNA (eDNA). We studied the fungal nuclear ribosomal large subunit (LSU) D2 and ITS2 DNA markers through a bioinformatics pipeline introduced here. We found 88 and 128 unique amplicon sequence variants (ASVs) using the D2 and ITS2 metabarcoding assays, respectively. With principal coordinate analysis (PCoA) and PERMANOVA, ASV diversity did not change in response to barley cultivar or fungicide treatment, however the community structure of unsprayed plants did change between two collection times eight days apart. The workflow described here can be applied to other microbiome studies in agriculture and we hope it encourages further research into crop microbiomes to improve agroecosystem management.

scholarly journals A novel post hoc method for detecting index switching finds no evidence for increased switching on the Illumina HiSeq X

2017 ◽  
Author(s):  
Gregory L. Owens ◽  
Marco Todesco ◽  
Emily B. M. Drummond ◽  
Sam Yeaman ◽  
Loren H. Rieseberg
Keyword(s):  
Allele Frequency ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Molecular Ecology ◽  
Whole Genome Shotgun ◽  
Whole Genome ◽  
Illumina Hiseq ◽  
Illumina Hiseq Platform ◽  
Post Hoc

AbstractHigh throughput sequencing using the Illumina HiSeq platform is a pervasive and critical molecular ecology resource, and has provided the data underlying many recent advances. A recent study has suggested that ‘index switching’, where reads are misattributed to the wrong sample, may be higher in new versions of the HiSeq platform. This has the potential to invalidate both published and in-progress work across the field. Here, we test for evidence of index switching in an exemplar whole genome shotgun dataset sequenced on both the Illumina HiSeq 2500, which should not have the problem, and the Illumina HiSeq X, which may. We leverage unbalanced heterozygotes, which may be produced by index switching, and ask whether the under-sequenced allele is more likely to be found in other samples in the same lane than expected based on the allele frequency. Although we validate the sensitivity of this method using simulations, we find that neither the HiSeq 2500 nor the HiSeq X have evidence of index switching. This suggests that, thankfully, index switching may not be a ubiquitous problem in HiSeq X sequence data. Lastly, we provide scripts for applying our method so that index switching can be tested for in other datasets.

scholarly journals SECAPR - A bioinformatics pipeline for the rapid and user-friendly alignment of hybrid enrichment sequences, from raw reads to alignments

2018 ◽  
Author(s):  
Tobias Andermann ◽  
Angela Cano ◽  
Alexander Zizka ◽  
Christine Bacon ◽  
Alexandre Antonelli
Keyword(s):  
Evolutionary Biology ◽  
Sequence Data ◽  
Model Organisms ◽  
Sequencing Data ◽  
Bioinformatics Pipeline ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Sequence Capture ◽  
Sequencing Platforms ◽  
User Friendly

Evolutionary biology has entered an era of unprecedented amounts of DNA sequence data, as new sequencing platforms such as Massive Parallel Sequencing (MPS) can generate billions of nucleotides within less than a day. The current bottleneck is how to efficiently handle, process, and analyze such large amounts of data in an automated and reproducible way. To tackle these challenges we introduce the Sequence Capture Processor (SECAPR) pipeline for processing raw sequencing data into multiple sequence alignments for downstream phylogenetic and phylogeographic analyses. SECAPR is user-friendly and we provide an exhaustive tutorial intended for users with no prior experience with analyzing MPS output. SECAPR is particularly useful for the processing of sequence capture (= hybrid enrichment) datasets for non-model organisms, as we demonstrate using an empirical dataset of the palm genus Geonoma (Arecaceae). Various quality control and plotting functions help the user to decide on the most suitable settings for even challenging datasets. SECAPR is an easy-to-use, free, and versatile pipeline, aimed to enable efficient and reproducible processing of MPS data for many samples in parallel.

scholarly journals Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies

2019 ◽  
Vol 109 (3) ◽  
pp. 488-497 ◽  
Author(s):  
Sebastien Massart ◽  
Michela Chiumenti ◽  
Kris De Jonghe ◽  
Rachel Glover ◽  
Annelies Haegeman ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Performance Test ◽  
Virus Detection ◽  
Performance Testing ◽  
Plant Viruses ◽  
Reference Sequence ◽  
Bioinformatics Pipeline ◽  
Double Blind

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

Sign in / Sign up

Export Citation Format

Share Document