Dataset Information

NanoSim: nanopore sequence read simulator based on statistical characterization.

ABSTRACT: Background:The MinION sequencing instrument from Oxford Nanopore Technologies (ONT) produces long read lengths from single-molecule sequencing - valuable features for detailed genome characterization. To realize the potential of this platform, a number of groups are developing bioinformatics tools tuned for the unique characteristics of its data. We note that these development efforts would benefit from a simulator software, the output of which could be used to benchmark analysis tools. Results:Here, we introduce NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data and allows for adjustments upon improvement of nanopore sequencing technology. The first step of NanoSim is read characterization, which provides a comprehensive alignment-based analysis and generates a set of read profiles serving as the input to the next step, the simulation stage. The simulation stage uses the model built in the previous step to produce in silico reads for a given reference genome. NanoSim is written in Python and R. The source files and manual are available at the Genome Sciences Centre website: http://www.bcgsc.ca/platform/bioinfo/software/nanosim. Conclusion:In this work, we model the base-calling errors of ONT reads to inform the simulation of sequences with similar characteristics. We showcase the performance of NanoSim on publicly available datasets generated using the R7 and R7.3 chemistries and different sequencing kits and compare the resulting synthetic reads to those of other long-sequence simulators and experimental ONT reads. We expect NanoSim to have an enabling role in the field and benefit the development of scalable next-generation sequencing technologies for the long nanopore reads, including genome assembly, mutation detection, and even metagenomic analysis software.

SUBMITTER: Yang C

PROVIDER: S-EPMC5530317 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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NanoSim: nanopore sequence read simulator based on statistical characterization.

Yang Chen C Chu Justin J Warren René L RL Birol Inanç I

GigaScience 20170401 4

<h4>Background</h4>The MinION sequencing instrument from Oxford Nanopore Technologies (ONT) produces long read lengths from single-molecule sequencing - valuable features for detailed genome characterization. To realize the potential of this platform, a number of groups are developing bioinformatics tools tuned for the unique characteristics of its data. We note that these development efforts would benefit from a simulator software, the output of which could be used to benchmark analysis tools.< ...[more]

PMID: 28327957

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Project description:BackgroundThere are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data.ResultsWe present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approach to generate reads with lengths and quality values that closely match empirically-derived distributions. BEAR can emulate reads from various sequencing platforms, including Illumina, 454, and Ion Torrent. BEAR requires minimal user input, as it automatically determines appropriate parameter settings from user-supplied data. BEAR also uses a unique method for deriving run-specific error rates, and extracts useful statistics from the metagenomic data itself, such as quality-error models. Many existing simulators are specific to a particular sequencing technology; however, BEAR is not restricted in this way. Because of its flexibility, BEAR is particularly useful for emulating the behaviour of technologies like Ion Torrent, for which no dedicated sequencing simulators are currently available. BEAR is also the first metagenomic sequencing simulator program that automates the process of generating abundances, which can be an arduous task.ConclusionsBEAR is useful for evaluating data processing tools in genomics. It has many advantages over existing comparable software, such as generating more realistic reads and being independent of sequencing technology, and has features particularly useful for metagenomics work.

Project description:BackgroundThe coconut rhinoceros beetle (CRB, Oryctes rhinoceros) is a severe and invasive pest of coconut and other palms throughout Asia and the Pacific. The biocontrol agent, Oryctes rhinoceros nudivirus (OrNV), has successfully suppressed O. rhinoceros populations for decades but new CRB invasions started appearing after 2007. A single-SNP variant within the mitochondrial cox1 gene is used to distinguish the recently-invading CRB-G lineage from other haplotypes, but the lack of mitogenome sequence for this species hinders further development of a molecular toolset for biosecurity and management programmes against CRB. Here we report the complete circular sequence and annotation for CRB mitogenome, generated to support such efforts.MethodsSequencing data were generated using long-read Nanopore technology from genomic DNA isolated from a CRB-G female. The mitogenome was assembled with Flye v.2.5, using the short-read Illumina sequences to remove homopolymers with Pilon, and annotated with MITOS. Independently-generated transcriptome data were used to assess the O. rhinoceros mitogenome annotation and transcription. The aligned sequences of 13 protein-coding genes (PCGs) (with degenerate third codon position) from O. rhinoceros, 13 other Scarabaeidae taxa and two outgroup taxa were used for the phylogenetic reconstruction with the Maximum likelihood (ML) approach in IQ-TREE and Bayesian (BI) approach in MrBayes.ResultsThe complete circular mitogenome of O. rhinoceros is 20,898 bp in length, with a gene content canonical for insects (13 PCGs, two rRNA genes, and 22 tRNA genes), as well as one structural variation (rearrangement of trnQ and trnI) and a long control region (6,204 bp). Transcription was detected across all 37 genes, and interestingly, within three domains in the control region. ML and BI phylogenies had the same topology, correctly grouping O. rhinoceros with one other Dynastinae taxon, and recovering the previously reported relationship among lineages in the Scarabaeidae. In silico PCR-RFLP analysis recovered the correct fragment set that is diagnostic for the CRB-G haplogroup. These results validate the high-quality of the O. rhinoceros mitogenome sequence and annotation.

Dataset Information

NanoSim: nanopore sequence read simulator based on statistical characterization.

Publications

NanoSim: nanopore sequence read simulator based on statistical characterization.

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