scholarly journals SmMIP-tools: a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

2021 ◽  
Author(s):  
Jessie J.F. Medeiros ◽  
Jose-Mario Capo-Chichi ◽  
Liran I. Shlush ◽  
John E. Dick ◽  
Andrea Arruda ◽  
...  
Keyword(s):  
Single Molecule ◽  
Genetic Research ◽  
Cost Effective ◽  
Data Interpretation ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Targeted Next Generation Sequencing ◽  
Wide Scale ◽  
Molecular Inversion Probes ◽  
Derived Data

Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two of the software's major components. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

scholarly journals Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Andrew Currin ◽  
Neil Swainston ◽  
Mark S Dunstan ◽  
Adrian J Jervis ◽  
Paul Mulherin ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Dna Sequencing ◽  
Cost Effective ◽  
Polymorphism Analysis ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Synthetic Dna ◽  
Design Build ◽  
Hardware Costs

Abstract Synthetic biology utilizes the Design–Build–Test–Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure’s low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

scholarly journals OptiDiff: structural variation detection from single optical mapping reads

2022 ◽  
Author(s):  
Mehmet Akdel ◽  
Dick de Ridder
Keyword(s):  
Single Molecule ◽  
Large Scale ◽  
Structural Variation ◽  
Optical Mapping ◽  
Cost Effective ◽  
Sequencing Data ◽  
Mapping Technology ◽  
Cost Effective Alternative ◽  
Algorithmic Approaches ◽  
Broad Interest

Detecting structural variation (SV) in eukaryotic genomes is of broad interest due to its often dramatic phenotypic effects, but remains a major, costly challenge based on DNA sequencing data. A cost-effective alternative in detecting large-scale SV has become available with advances in optical mapping technology. However, the algorithmic approaches to identifying SVs from optical mapping data are limited. Here, we propose a novel, open-source SV detection tool, OptiDiff, which employs a single molecule based approach to detect and classify homozygous and heterozygous SVs at coverages as low as 20x, showing better performance than the state of the art.

scholarly journals Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data

GigaScience ◽  
2020 ◽  
Vol 9 (6) ◽  
Author(s):  
Saber Hafezqorani ◽  
Chen Yang ◽  
Theodora Lo ◽  
Ka Ming Nip ◽  
René L Warren ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Single Molecule ◽  
Rapid Development ◽  
Cost Effective ◽  
Third Generation ◽  
Sequencing Data ◽  
Complementary Dna ◽  
Sequencing Technologies ◽  
Analytical Tools ◽  
Generation Sequencing

Abstract Background Compared with second-generation sequencing technologies, third-generation single-molecule RNA sequencing has unprecedented advantages; the long reads it generates facilitate isoform-level transcript characterization. In particular, the Oxford Nanopore Technology sequencing platforms have become more popular in recent years owing to their relatively high affordability and portability compared with other third-generation sequencing technologies. To aid the development of analytical tools that leverage the power of this technology, simulated data provide a cost-effective solution with ground truth. However, a nanopore sequence simulator targeting transcriptomic data is not available yet. Findings We introduce Trans-NanoSim, a tool that simulates reads with technical and transcriptome-specific features learnt from nanopore RNA-sequncing data. We comprehensively benchmarked Trans-NanoSim on direct RNA and complementary DNA datasets describing human and mouse transcriptomes. Through comparison against other nanopore read simulators, we show the unique advantage and robustness of Trans-NanoSim in capturing the characteristics of nanopore complementary DNA and direct RNA reads. Conclusions As a cost-effective alternative to sequencing real transcriptomes, Trans-NanoSim will facilitate the rapid development of analytical tools for nanopore RNA-sequencing data. Trans-NanoSim and its pre-trained models are freely accessible at https://github.com/bcgsc/NanoSim.

scholarly journals Chromosome-scale assembly comparison of the Korean Reference Genome KOREF from PromethION and PacBio with Hi-C mapping information

GigaScience ◽  
2019 ◽  
Vol 8 (12) ◽  
Author(s):  
Hui-Su Kim ◽  
Sungwon Jeon ◽  
Changjae Kim ◽  
Yeon Kyung Kim ◽  
Yun Sung Cho ◽  
...  
Keyword(s):  
Human Genome ◽  
Single Molecule ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Low Cost ◽  
Cost Effective ◽  
Sequencing Data ◽  
Smrt Sequencing ◽  
Human Genome Assembly

Abstract Background Long DNA reads produced by single-molecule and pore-based sequencers are more suitable for assembly and structural variation discovery than short-read DNA fragments. For de novo assembly, Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are the favorite options. However, PacBio's SMRT sequencing is expensive for a full human genome assembly and costs more than $40,000 US for 30× coverage as of 2019. ONT PromethION sequencing, on the other hand, is 1/12 the price of PacBio for the same coverage. This study aimed to compare the cost-effectiveness of ONT PromethION and PacBio's SMRT sequencing in relation to the quality. Findings We performed whole-genome de novo assemblies and comparison to construct an improved version of KOREF, the Korean reference genome, using sequencing data produced by PromethION and PacBio. With PromethION, an assembly using sequenced reads with 64× coverage (193 Gb, 3 flowcell sequencing) resulted in 3,725 contigs with N50s of 16.7 Mb and a total genome length of 2.8 Gb. It was comparable to a KOREF assembly constructed using PacBio at 62× coverage (188 Gb, 2,695 contigs, and N50s of 17.9 Mb). When we applied Hi-C–derived long-range mapping data, an even higher quality assembly for the 64× coverage was achieved, resulting in 3,179 scaffolds with an N50 of 56.4 Mb. Conclusion The pore-based PromethION approach provided a high-quality chromosome-scale human genome assembly at a low cost with long maximum contig and scaffold lengths and was more cost-effective than PacBio at comparable quality measurements.

scholarly journals Reference-free reconstruction and quantification of transcriptomes from Nanopore long-read sequencing

2020 ◽  
Author(s):  
Ivan de la Rubia ◽  
Joel A. Indi ◽  
Silvia Carbonell-Sala ◽  
Julien Lagarde ◽  
M Mar Albà ◽  
...  
Keyword(s):  
Single Molecule ◽  
Reference Genome ◽  
Simulated Data ◽  
Cost Effective ◽  
Dna Assembly ◽  
Sequencing Data ◽  
Consensus Sequences ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Long Read

AbstractSingle-molecule long-read sequencing with Nanopore provides an unprecedented opportunity to measure transcriptomes from any sample1–3. However, current analysis methods rely on the comparison with a reference genome or transcriptome2,4,5, or the use of multiple sequencing technologies6,7, thereby precluding cost-effective studies in species with no genome assembly available, in individuals underrepresented in the existing reference, and for the discovery of disease-specific transcripts not directly identifiable from a reference genome. Methods for DNA assembly8–10 cannot be directly transferred to transcriptomes since their consensus sequences lack the required interpretability for genes with multiple transcript isoforms. To address these challenges, we have developed RATTLE, the first tool to perform reference-free reconstruction and quantification of transcripts from Nanopore long reads. Using simulated data, isoform spike-ins, and sequencing data from tissues and cell lines, we demonstrate that RATTLE accurately determines transcript sequence and abundance, is comparable to reference-based methods, and shows saturation in the number of predicted transcripts with increasing number of input reads.

scholarly journals Role of germline aberrations affecting CTNNA1, MAP3K6 and MYD88 in gastric cancer susceptibility

2018 ◽  
Vol 55 (10) ◽  
pp. 669-674 ◽  
Author(s):  
Robbert D A Weren ◽  
Rachel S van der Post ◽  
Ingrid P Vogelaar ◽  
J Han van Krieken ◽  
Liesbeth Spruijt ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Molecule ◽  
Cancer Susceptibility ◽  
Germline Mutations ◽  
The Novel ◽  
Germline Variants ◽  
Targeted Next Generation Sequencing ◽  
Predisposing Genes ◽  
Molecular Inversion Probes

BackgroundIn approximately 10% of all gastric cancer (GC) cases, a heritable cause is suspected. A subset of these cases have a causative germline CDH1 mutation; however, in most cases the cause remains unknown. Our objective was to assess to what extent these remaining cases may be explained by germline mutations in the novel candidate GC predisposing genes CTNNA1, MAP3K6 or MYD88.MethodsWe sequenced a large cohort of unexplained young and/or familial patients with GC (n=286) without a CDH1germline mutation for germline variants affecting CTNNA1, MAP3K6 and MYD88 using a targeted next-generation sequencing approach based on single-molecule molecular inversion probes.ResultsPredicted deleterious germline variants were not encountered in MYD88, but recurrently observed in CTNNA1 (n=2) and MAP3K6 (n=3) in our cohort of patients with GC. In contrast to deleterious variants in CTNNA1, deleterious variants in MAP3K6 also occur frequently in the general population.ConclusionsBased on our results MAP3K6 should no longer be considered a GC predisposition gene, whereas deleterious CTNNA1 variants are confirmed as an infrequent cause of GC susceptibility. Biallelic MYD88 germline mutations are at most a very rare cause of GC susceptibility as no additional cases were identified.

scholarly journals Chromosome-scale assembly comparison of the Korean Reference Genome KOREF from PromethION and PacBio with Hi-C mapping information

2019 ◽  
Author(s):  
Hui-Su Kim ◽  
Sungwon Jeon ◽  
Changjae Kim ◽  
Yeon Kyung Kim ◽  
Yun Sung Cho ◽  
...  
Keyword(s):  
Human Genome ◽  
Single Molecule ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Low Cost ◽  
Cost Effective ◽  
Sequencing Data ◽  
Smrt Sequencing ◽  
Human Genome Assembly

AbstractBackgroundLong DNA reads produced by single molecule and pore-based sequencers are more suitable for assembly and structural variation discovery than short read DNA fragments. For de novo assembly, PacBio and Oxford Nanopore Technologies (ONT) are favorite options. However, PacBio’s SMRT sequencing is expensive for a full human genome assembly and costs over 40,000 USD for 30x coverage as of 2019. ONT PromethION sequencing, on the other hand, is one-twelfth the price of PacBio for the same coverage. This study aimed to compare the cost-effectiveness of ONT PromethION and PacBio’s SMRT sequencing in relation to the quality.FindingsWe performed whole genome de novo assemblies and comparison to construct an improved version of KOREF, the Korean reference genome, using sequencing data produced by PromethION and PacBio. With PromethION, an assembly using sequenced reads with 64x coverage (193 Gb, 3 flowcell sequencing) resulted in 3,725 contigs with N50s of 16.7 Mbp and a total genome length of 2.8 Gbp. It was comparable to a KOREF assembly constructed using PacBio at 62x coverage (188 Gbp, 2,695 contigs and N50s of 17.9 Mbp). When we applied Hi-C-derived long-range mapping data, an even higher quality assembly for the 64x coverage was achieved, resulting in 3,179 scaffolds with an N50 of 56.4 Mbp.ConclusionThe pore-based PromethION approach provides a good quality chromosome-scale human genome assembly at a low cost with long maximum contig and scaffold lengths and is more cost-effective than PacBio at comparable quality measurements.

scholarly journals Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes

2021 ◽  
Author(s):  
Eric S Tvedte ◽  
Mark Gasser ◽  
Benjamin C Sparklin ◽  
Jane Michalski ◽  
Carl E Hjelmen ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Hybrid Approach ◽  
Cost Effective ◽  
Fruit Fly ◽  
Drosophila Ananassae ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
E Coli ◽  
Hybrid Approaches ◽  
Long Read

Abstract The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

scholarly journals NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

2021 ◽  
Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Research ◽  
Likelihood Estimation ◽  
Software Tool ◽  
Estimation Methods ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

scholarly journals Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ratanond Koonchanok ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Khairi Reda ◽  
Sarath Chandra Janga
Keyword(s):  
Single Molecule ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Direct Sequencing ◽  
Visual Exploration ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Rna Sequences ◽  
Sequencing Technologies ◽  
Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

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