scholarly journals Tigmint: Correcting Assembly Errors Using Linked Reads From Large Molecules

2018 ◽  
Author(s):  
Shaun D Jackman ◽  
Lauren Coombe ◽  
Justin Chu ◽  
Rene L Warren ◽  
Benjamin P Vandervalk ◽  
...  
Keyword(s):  
Single Molecule ◽  
Sequencing Data ◽  
Long Distance ◽  
Distance Information ◽  
Single Molecule Sequencing ◽  
Large Molecules ◽  
Mate Pair ◽  
A Genome ◽  
Original Genome

Genome sequencing yields the sequence of many short snippets of DNA (reads) from a genome. Genome assembly attempts to reconstruct the original genome from which these reads were derived. This task is difficult due to gaps and errors in the sequencing data, repetitive sequence in the underlying genome, and heterozygosity, and assembly errors are common. These misassemblies may be identified by comparing the sequencing data to the assembly, and by looking for discrepancies between the two. Once identified, these misassemblies may be corrected, improving the quality of the assembly. Although tools exist to identify and correct misassemblies using Illumina pair-end and mate-pair sequencing, no such tool yet exists that makes use of the long distance information of the large molecules provided by linked reads, such as those offered by the 10x Genomics Chromium platform. We have developed the tool Tigmint for this purpose. To demonstrate the effectiveness of Tigmint, we corrected assemblies of a human genome using short reads assembled with ABySS 2.0 and other assemblers. Tigmint reduced the number of misassemblies identified by QUAST in the ABySS assembly by 216 (27%). While scaffolding with ARCS alone more than doubled the scaffold NGA50 of the assembly from 3 to 8 Mbp, the combination of Tigmint and ARCS improved the scaffold NGA50 of the assembly over five-fold to 16.4 Mbp. This notable improvement in contiguity highlights the utility of assembly correction in refining assemblies. We demonstrate its usefulness in correcting the assemblies of multiple tools, as well as in using Chromium reads to correct and scaffold assemblies of long single-molecule sequencing. The source code of Tigmint is available for download from https://github.com/bcgsc/tigmint, and is distributed under the GNU GPL v3.0 license.

scholarly journals Genome assembly of the maize inbred line A188 provides a new reference genome for functional genomics

2021 ◽  
Author(s):  
Fei Ge ◽  
Jingtao Qu ◽  
Peng Liu ◽  
Lang Pan ◽  
Chaoying Zou ◽  
...  
Keyword(s):  
Single Molecule ◽  
Inbred Line ◽  
Genome Mapping ◽  
Maize Inbred Line ◽  
Sequencing Data ◽  
Structural Variations ◽  
Single Molecule Sequencing ◽  
Maize Genetic ◽  
Induction Ratio ◽  
Phenotypic Variations

Heretofore, little is known about the mechanism underlying the genotype-dependence of embryonic callus (EC) induction, which has severely inhibited the development of maize genetic engineering. Here, we report the genome sequence and annotation of a maize inbred line with high EC induction ratio, A188, which is assembled from single-molecule sequencing and optical genome mapping. We assembled a 2,210 Mb genome with a scaffold N50 size of 11.61 million bases (Mb), compared to those of 9.73 Mb for B73 and 10.2 Mb for Mo17. Comparative analysis revealed that ~30% of the predicted A188 genes had large structural variations to B73, Mo17 and W22 genomes, which caused considerable protein divergence and might lead to phenotypic variations between the four inbred lines. Combining our new A188 genome, previously reported QTLs and RNA sequencing data, we reveal 8 large structural variation genes and 4 differentially expressed genes playing potential roles in EC induction.

scholarly journals Assembly of chromosome-scale contigs by efficiently resolving repetitive sequences with long reads

2018 ◽  
Author(s):  
Huilong Du ◽  
Chengzhi Liang
Keyword(s):  
Single Molecule ◽  
High Efficiency ◽  
Reference Genome ◽  
Repetitive Sequences ◽  
Sequencing Data ◽  
High Quality ◽  
Single Molecule Sequencing ◽  
Genome Maps ◽  
Long Reads ◽  
Novel Method

AbstractDue to the large number of repetitive sequences in complex eukaryotic genomes, fragmented and incompletely assembled genomes lose value as reference sequences, often due to short contigs that cannot be anchored or mispositioned onto chromosomes. Here we report a novel method Highly Efficient Repeat Assembly (HERA), which includes a new concept called a connection graph as well as algorithms for constructing the graph. HERA resolves repeats at high efficiency with single-molecule sequencing data, and enables the assembly of chromosome-scale contigs by further integrating genome maps and Hi-C data. We tested HERA with the genomes of rice R498, maize B73, human HX1 and Tartary buckwheat Pinku1. HERA can correctly assemble most of the tandemly repetitive sequences in rice using single-molecule sequencing data only. Using the same maize and human sequencing data published by Jiao et al. (2017) and Shi et al. (2016), respectively, we dramatically improved on the sequence contiguity compared with the published assemblies, increasing the contig N50 from 1.3 Mb to 61.2 Mb in maize B73 assembly and from 8.3 Mb to 54.4 Mb in human HX1 assembly with HERA. We provided a high-quality maize reference genome with 96.9% of the gaps filled (only 76 gaps left) and several incorrectly positioned sequences fixed compared with the B73 RefGen_v4 assembly. Comparisons between the HERA assembly of HX1 and the human GRCh38 reference genome showed that many gaps in GRCh38 could be filled, and that GRCh38 contained some potential errors that could be fixed. We assembled the Pinku1 genome into 12 scaffolds with a contig N50 size of 27.85 Mb. HERA serves as a new genome assembly/phasing method to generate high quality sequences for complex genomes and as a curation tool to improve the contiguity and completeness of existing reference genomes, including the correction of assembly errors in repetitive regions.

Critical assessment of bioinformatics methods for the characterization of pathological repeat expansions with single-molecule sequencing data

2019 ◽  
Vol 21 (6) ◽  
pp. 1971-1986 ◽  
Author(s):  
Matteo Chiara ◽  
Federico Zambelli ◽  
Ernesto Picardi ◽  
David S Horner ◽  
Graziano Pesole
Keyword(s):  
Single Molecule ◽  
Tandem Repeats ◽  
Simulated Data ◽  
Detailed Comparison ◽  
Sequencing Data ◽  
Single Molecule Sequencing ◽  
Sequencing Technologies ◽  
Repeat Expansions

Abstract A number of studies have reported the successful application of single-molecule sequencing technologies to the determination of the size and sequence of pathological expanded microsatellite repeats over the last 5 years. However, different custom bioinformatics pipelines were employed in each study, preventing meaningful comparisons and somewhat limiting the reproducibility of the results. In this review, we provide a brief summary of state-of-the-art methods for the characterization of expanded repeats alleles, along with a detailed comparison of bioinformatics tools for the determination of repeat length and sequence, using both real and simulated data. Our reanalysis of publicly available human genome sequencing data suggests a modest, but statistically significant, increase of the error rate of single-molecule sequencing technologies at genomic regions containing short tandem repeats. However, we observe that all the methods herein tested, irrespective of the strategy used for the analysis of the data (either based on the alignment or assembly of the reads), show high levels of sensitivity in both the detection of expanded tandem repeats and the estimation of the expansion size, suggesting that approaches based on single-molecule sequencing technologies are highly effective for the detection and quantification of tandem repeat expansions and contractions.

scholarly journals Evaluation of Single-Molecule Sequencing Technologies for Structural Variant Detection in Two Swedish Human Genomes

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1444
Author(s):  
Nazeefa Fatima ◽  
Anna Petri ◽  
Ulf Gyllensten ◽  
Lars Feuk ◽  
Adam Ameur
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Single Molecule ◽  
Large Scale ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Structural Variations ◽  
Single Molecule Sequencing ◽  
Human Samples

Long-read single molecule sequencing is increasingly used in human genomics research, as it allows to accurately detect large-scale DNA rearrangements such as structural variations (SVs) at high resolution. However, few studies have evaluated the performance of different single molecule sequencing platforms for SV detection in human samples. Here we performed Oxford Nanopore Technologies (ONT) whole-genome sequencing of two Swedish human samples (average 32× coverage) and compared the results to previously generated Pacific Biosciences (PacBio) data for the same individuals (average 66× coverage). Our analysis inferred an average of 17k and 23k SVs from the ONT and PacBio data, respectively, with a majority of them overlapping with an available multi-platform SV dataset. When comparing the SV calls in the two Swedish individuals, we find a higher concordance between ONT and PacBio SVs detected in the same individual as compared to SVs detected by the same technology in different individuals. Downsampling of PacBio reads, performed to obtain similar coverage levels for all datasets, resulted in 17k SVs per individual and improved overlap with the ONT SVs. Our results suggest that ONT and PacBio have a similar performance for SV detection in human whole genome sequencing data, and that both technologies are feasible for population-scale studies.

scholarly journals Assembly of chromosome-scale contigs by efficiently resolving repetitive sequences with long reads

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Huilong Du ◽  
Chengzhi Liang
Keyword(s):  
Single Molecule ◽  
Repetitive Sequences ◽  
Tartary Buckwheat ◽  
Gene Sequences ◽  
Assembly Method ◽  
Long Reads ◽  
A Genome ◽  
Genome Assemblies ◽  
Reference Genomes

AbstractThe abundant repetitive sequences in complex eukaryotic genomes cause fragmented assemblies, which lose value as reference genomes, often due to incomplete gene sequences and unanchored or mispositioned contigs on chromosomes. Here we report a genome assembly method HERA, which resolves repeats efficiently by constructing a connection graph from an overlap graph. We test HERA on the genomes of rice, maize, human, and Tartary buckwheat with single-molecule sequencing and mapping data. HERA correctly assembles most of the previously unassembled regions, resulting in dramatically improved, highly contiguous genome assemblies with newly assembled gene sequences. For example, the maize contig N50 size reaches 61.2 Mb and the Tartary buckwheat genome comprises only 20 contigs. HERA can also be used to fill gaps and fix errors in reference genomes. The application of HERA will greatly improve the quality of new or existing assemblies of complex genomes.

scholarly journals Resolving structural diversity of Carbapenemase-producing gram-negative bacteria using single molecule sequencing

2018 ◽  
Author(s):  
Nicholas Noll ◽  
Eric Urich ◽  
Daniel Wüthrich ◽  
Vladimira Hinic ◽  
Adrian Egli ◽  
...  
Keyword(s):  
Single Molecule ◽  
Structural Diversity ◽  
Genomic Variation ◽  
Species Boundaries ◽  
Health Crisis ◽  
Single Molecule Sequencing ◽  
Oxford Nanopore ◽  
Almost All ◽  
Sequence Types

Carbapenemase-producing bacteria are resistant against almost all commonly used betalactam and cephalosporin antibiotics and represent a growing public health crisis. Carbapenemases reside predominantly in mobile genetic elements and rapidly spread across genetic backgrounds and species boundaries. Here, we report more than one hundred finished, high quality genomes of carbapenemase producing enterobacteriaceae, P. aeruginosa and A. baumannii sequenced with Oxford Nanopore and Illumina technologies. We developed a number of high-throughput criteria to assess the quality of fully assembled genomes for which curated references do not exist. Using this diverse collection of closed genomes and plasmids, we demonstrate rapid movement of carbapenemase between genomic neighborhoods, sequence types, and across species boundaries with distinct patterns for different carbapenemases. Lastly, we present evidence of multiple ancestral recombination events between different Enterobacteriaceae MLSTs. Taken together, our samples suggest a hierarchical picture of genomic variation produced by the evolution of carbapenemase producing bacteria that will require new models to adequately understand and track.

scholarly journals Assembly of Long Error-Prone Reads Using Repeat Graphs

2018 ◽  
Author(s):  
Mikhail Kolmogorov ◽  
Jeffrey Yuan ◽  
Yu Lin ◽  
Pavel. A. Pevzner
Keyword(s):  
Single Molecule ◽  
State Of The Art ◽  
De Bruijn Graph ◽  
Single Molecule Sequencing ◽  
Short Read ◽  
Initial Stage ◽  
A Genome ◽  
De Bruijn ◽  
Initial Assembly

ABSTRACTThe problem of genome assembly is ultimately linked to the problem of the characterization of all repeat families in a genome as a repeat graph. The key reason the de Bruijn graph emerged as a popular short read assembly approach is because it offered an elegant representation of all repeats in a genome that reveals their mosaic structure. However, most algorithms for assembling long error-prone reads use an alternative overlap-layout-consensus (OLC) approach that does not provide a repeat characterization. We present the Flye algorithm for constructing the A-Bruijn (assembly) graph from long error-prone reads, that, in contrast to the k-mer-based de Bruijn graph, assembles genomes using an alignment-based A-Bruijn graph. In difference from existing assemblers, Flye does not attempt to construct accurate contigs (at least at the initial assembly stage) but instead simply generates arbitrary paths in the (unknown) assembly graph and further constructs an assembly graph from these paths. Counter-intuitively, this fast but seemingly reckless approach results in the same graph as the assembly graph constructed from accurate contigs. Flye constructs (overlapping) contigs with possible assembly errors at the initial stage, combines them into an accurate assembly graph, resolves repeats in the assembly graph using small variations between various repeat instances that were left unresolved during the initial assembly stage, constructs a new, less tangled assembly graph based on resolved repeats, and finally outputs accurate contigs as paths in this graph. We benchmark Flye against several state-of-the-art Single Molecule Sequencing assemblers and demonstrate that it generates better or comparable assemblies for all analyzed datasets.

scholarly journals Transcriptome assembly from long-read RNA-seq alignments with StringTie2

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Sam Kovaka ◽  
Aleksey V. Zimin ◽  
Geo M. Pertea ◽  
Roham Razaghi ◽  
Steven L. Salzberg ◽  
...  
Keyword(s):  
Single Molecule ◽  
Transcriptome Assembly ◽  
Rna Seq ◽  
Ability To Work ◽  
Single Molecule Sequencing ◽  
Short Read ◽  
New Methods ◽  
Long Reads ◽  
Long Read

AbstractRNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new methods to handle the high error rate of long reads and offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of short-read assemblies. StringTie2 is more accurate and faster and uses less memory than all comparable short-read and long-read analysis tools.

scholarly journals Transcriptome assembly from long-read RNA-seq alignments with StringTie2

2019 ◽  
Author(s):  
Sam Kovaka ◽  
Aleksey V. Zimin ◽  
Geo M. Pertea ◽  
Roham Razaghi ◽  
Steven L. Salzberg ◽  
...  
Keyword(s):  
Single Molecule ◽  
Transcriptome Assembly ◽  
Rna Seq ◽  
High Error Rate ◽  
Sequencing Technology ◽  
Ability To Work ◽  
Single Molecule Sequencing ◽  
Long Reads ◽  
Long Read

AbstractRNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new computational methods to handle the high error rate of long-read sequencing technology, which previous assemblers could not tolerate. It also offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of assemblies. On 33 short-read datasets from humans and two plant species, StringTie2 is 47.3% more precise and 3.9% more sensitive than Scallop. On multiple long read datasets, StringTie2 on average correctly assembles 8.3 and 2.6 times as many transcripts as FLAIR and Traphlor, respectively, with substantially higher precision. StringTie2 is also faster and has a smaller memory footprint than all comparable tools.

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