scholarly journals Yet another de novo genome assembler

2019 ◽  
Author(s):  
Robert Vaser ◽  
Mile Šikić
Keyword(s):  
De Novo ◽  
Sequence Classification ◽  
De Novo Genome Assembly ◽  
Development Fund ◽  
European Regional Development Fund ◽  
Sequencing Technologies ◽  
Single Genome ◽  
Long Read ◽  
Metagenome Assembly ◽  
Genome Assemblies

AbstractAdvances in sequencing technologies have pushed the limits of genome assemblies beyond imagination. The sheer amount of long read data that is being generated enables the assembly for even the largest and most complex organism for which efficient algorithms are needed. We present a new tool, called Ra, for de novo genome assembly of long uncorrected reads. It is a fast and memory friendly assembler based on sequence classification and assembly graphs, developed with large genomes in mind. It is freely available at https://github.com/lbcb-sci/ra.This work has been supported in part by the Croatian Science Foundation under the project Single genome and metagenome assembly (IP-2018-01-5886), and in part by the European Regional Development Fund under the grant KK.01.1.1.01.0009 (DATACROSS). In addition, M.Š. is partly supported by funding from A*STAR, Singapore.

scholarly journals A high-quality genome assembly from a single, field-collected spotted lanternfly (Lycorma delicatula) using the PacBio Sequel II system

GigaScience ◽  
2019 ◽  
Vol 8 (10) ◽  
Author(s):  
Sarah B Kingan ◽  
Julie Urban ◽  
Christine C Lambert ◽  
Primo Baybayan ◽  
Anna K Childers ◽  
...  
Keyword(s):  
Invasive Species ◽  
Genome Assembly ◽  
De Novo ◽  
Fragment Size ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Lycorma Delicatula ◽  
Long Read ◽  
Genome Assemblies ◽  
High Quality Genome

ABSTRACT Background A high-quality reference genome is an essential tool for applied and basic research on arthropods. Long-read sequencing technologies may be used to generate more complete and contiguous genome assemblies than alternate technologies; however, long-read methods have historically had greater input DNA requirements and higher costs than next-generation sequencing, which are barriers to their use on many samples. Here, we present a 2.3 Gb de novo genome assembly of a field-collected adult female spotted lanternfly (Lycorma delicatula) using a single Pacific Biosciences SMRT Cell. The spotted lanternfly is an invasive species recently discovered in the northeastern United States that threatens to damage economically important crop plants in the region. Results The DNA from 1 individual was used to make 1 standard, size-selected library with an average DNA fragment size of ∼20 kb. The library was run on 1 Sequel II SMRT Cell 8M, generating a total of 132 Gb of long-read sequences, of which 82 Gb were from unique library molecules, representing ∼36× coverage of the genome. The assembly had high contiguity (contig N50 length = 1.5 Mb), completeness, and sequence level accuracy as estimated by conserved gene set analysis (96.8% of conserved genes both complete and without frame shift errors). Furthermore, it was possible to segregate more than half of the diploid genome into the 2 separate haplotypes. The assembly also recovered 2 microbial symbiont genomes known to be associated with L. delicatula, each microbial genome being assembled into a single contig. Conclusions We demonstrate that field-collected arthropods can be used for the rapid generation of high-quality genome assemblies, an attractive approach for projects on emerging invasive species, disease vectors, or conservation efforts of endangered species.

scholarly journals LongStitch: High-quality genome assembly correction and scaffolding using long reads

2021 ◽  
Author(s):  
Lauren Coombe ◽  
Janet X Li ◽  
Theodora Lo ◽  
Johnathan Wong ◽  
Vladimir Nikolic ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Draft Genome ◽  
Model Organisms ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Long Reads ◽  
Long Read ◽  
Genomic Regions ◽  
Genome Assemblies

Background Generating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads. Results LongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 2.0-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently runs in under five hours using less than 23GB of RAM. Conclusions Due to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch.

scholarly journals Comparative Annotation Toolkit (CAT) - simultaneous clade and personal genome annotation

2017 ◽  
Author(s):  
Ian T. Fiddes ◽  
Joel Armstrong ◽  
Mark Diekhans ◽  
Stefanie Nachtweide ◽  
Zev N. Kronenberg ◽  
...  
Keyword(s):  
Genome Annotation ◽  
De Novo ◽  
Low Cost ◽  
Great Apes ◽  
Personal Genome ◽  
Sequencing Technologies ◽  
Human Genomes ◽  
Long Read ◽  
Genome Assemblies ◽  
Rat Genome

ABSTRACTThe recent introductions of low-cost, long-read, and read-cloud sequencing technologies coupled with intense efforts to develop efficient algorithms have made affordable, high-quality de novo sequence assembly a realistic proposition. The result is an explosion of new, ultra-contiguous genome assemblies. To compare these genomes we need robust methods for genome annotation. We describe the fully open source Comparative Annotation Toolkit (CAT), which provides a flexible way to simultaneously annotate entire clades and identify orthology relationships. We show that CAT can be used to improve annotations on the rat genome, annotate the great apes, annotate a diverse set of mammals, and annotate personal, diploid human genomes. We demonstrate the resulting discovery of novel genes, isoforms and structural variants, even in genomes as well studied as rat and the great apes, and how these annotations improve cross-species RNA expression experiments.

scholarly journals HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution

2016 ◽  
Author(s):  
Govinda M. Kamath ◽  
Ilan Shomorony ◽  
Fei Xia ◽  
Thomas A. Courtade ◽  
David N. Tse
Keyword(s):  
Gold Standard ◽  
De Novo ◽  
Error Resilience ◽  
De Bruijn Graph ◽  
Sequencing Technologies ◽  
Long Read ◽  
De Bruijn ◽  
Genome Assemblies

ABSTRACTLong-read sequencing technologies have the potential to produce gold-standard de novo genome assemblies, but fully exploiting error-prone reads to resolve repeats remains a challenge. Aggressive approaches to repeat resolution often produce mis-assemblies, and conservative approaches lead to unnecessary fragmentation. We present HINGE, an assembler that seeks to achieve optimal repeat resolution by distinguishing repeats that can be resolved given the data from those that cannot. This is accomplished by adding "hinges" to reads for constructing an overlap graph where only unresolvable repeats are merged. As a result, HINGE combines the error resilience of overlap-based assemblers with repeat-resolution capabilities of de Bruijn graph assemblers. HINGE was evaluated on the long-read bacterial datasets from the NCTC project. HINGE produces more finished assemblies than Miniasm and the manual pipeline of NCTC based on the HGAP assembler and Circlator. HINGE also allows us to identify 40 datasets where unresolvable repeats prevent the reliable construction of a unique finished assembly. In these cases, HINGE outputs a visually interpretable assembly graph that encodes all possible finished assemblies consistent with the reads, while other approaches such as the NCTC pipeline and FALCON either fragment the assembly or resolve the ambiguity arbitrarily.

scholarly journals WENGAN: Efficient and high quality hybrid de novo assembly of human genomes

2019 ◽  
Author(s):  
Alex Di Genova ◽  
Elena Buena-Atienza ◽  
Stephan Ossowski ◽  
Marie-France Sagot
Keyword(s):  
De Novo ◽  
Computational Cost ◽  
Sequence Information ◽  
Sequencing Data ◽  
High Quality ◽  
Sequencing Technologies ◽  
Human Genomes ◽  
Long Reads ◽  
Long Read ◽  
Genome Assemblies

The continuous improvement of long-read sequencing technologies along with the development of ad-doc algorithms has launched a new de novo assembly era that promises high-quality genomes. However, it has proven difficult to use only long reads to generate accurate genome assemblies of large, repeat-rich human genomes. To date, most of the human genomes assembled from long error-prone reads add accurate short reads to further polish the consensus quality. Here, we report the development of a novel algorithm for hybrid assembly, WENGAN, and the de novo assembly of four human genomes using a combination of sequencing data generated on ONT PromethION, PacBio Sequel, Illumina and MGI technology. WENGAN implements efficient algorithms that exploit the sequence information of short and long reads to tackle assembly contiguity as well as consensus quality. The resulting genome assemblies have high contiguity (contig NG50:16.67-62.06 Mb), few assembly errors (contig NGA50:10.9-45.91 Mb), good consensus quality (QV:27.79-33.61), and high gene completeness (BUSCO complete: 94.6-95.1%), while consuming low computational resources (CPU hours:153-1027). In particular, the WENGAN assembly of the haploid CHM13 sample achieved a contig NG50 of 62.06 Mb (NGA50:45.91 Mb), which surpasses the contiguity of the current human reference genome (GRCh38 contig NG50:57.88 Mb). Providing highest quality at low computational cost, WENGAN is an important step towards the democratization of the de novo assembly of human genomes. The WENGAN assembler is available at https://github.com/adigenova/wengan

scholarly journals De novo Nanopore read quality improvement using deep learning

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang
Keyword(s):  
Error Correction ◽  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Error Rates ◽  
De Novo Genome Assembly ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Read Error Correction

Abstract Background Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. Results Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. Conclusions MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub.

scholarly journals Benchmarking metagenomic classification tools for long-read sequencing data

2020 ◽  
Author(s):  
Josip Marić ◽  
Krešimir Križanović ◽  
Sylvain Riondet ◽  
Niranjan Nagarajan ◽  
Mile Šikić
Keyword(s):  
De Novo ◽  
Real Life ◽  
Metagenomic Analysis ◽  
Sequencing Data ◽  
De Novo Genome Assembly ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Species Abundances ◽  
Long Read ◽  
Eukaryotic Genomes

ABSTRACTIn recent years, both long-read sequencing and metagenomic analysis have been significantly advanced. Although long-read sequencing technologies have been primarily used for de novo genome assembly, they are rapidly maturing for widespread use in other applications. In particular, long reads could potentially lead to more precise taxonomic identification, which has sparked an interest in using them for metagenomic analysis.Here we present a benchmark of several state-of-the-art tools for metagenomic taxonomic classification, tested on in-silico datasets constructed using real long reads from isolate sequencing. We compare tools that were either newly developed or modified to work with long reads, including k-mer based tools Kraken2, Centrifuge and CLARK, and mapping-based tools MetaMaps and MEGAN-LR. The test datasets were constructed with varying numbers of bacterial and eukaryotic genomes to simulate different real-life metagenomic applications. The tools were tested to detect species accurately and precisely estimate species abundances in the samples.Our analysis shows that all tested classifiers provide useful results, and the composition of the used database strongly influences the performance. Using the same database, tested tools achieve comparable results except for MetaMaps, which slightly outperform others in most metrics, but it is significantly slower than k-mer based tools.We deem there is significant room for improvement for all tested tools, especially in lowering the number of false-positive detections.

scholarly journals Higher quality de novo genome assemblies from degraded museum specimens: a linked-read approach to museomics

2019 ◽  
Author(s):  
Jocelyn P. Colella ◽  
Anna Tigano ◽  
Matthew D. MacManes
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Deer Mouse ◽  
Cost Effective ◽  
Molecular Data ◽  
Degraded Dna ◽  
Museum Specimens ◽  
Sequencing Technologies ◽  
Long Read ◽  
Genome Assemblies

AbstractHigh-throughput sequencing technologies are a proposed solution for accessing the molecular data in historic specimens. However, degraded DNA combined with the computational demands of short-read assemblies has posed significant laboratory and bioinformatics challenges. Linked-read or ‘synthetic long-read’ sequencing technologies, such as 10X Genomics, may provide a cost-effective alternative solution to assemble higher quality de novo genomes from degraded specimens. Here, we compare assembly quality (e.g., genome contiguity and completeness, presence of orthogroups) between four published genomes assembled from a single shotgun library and four deer mouse (Peromyscus spp.) genomes assembled using 10X Genomics technology. At a similar price-point, these approaches produce vastly different assemblies, with linked-read assemblies having overall higher quality, measured by larger N50 values and greater gene content. Although not without caveats, our results suggest that linked-read sequencing technologies may represent a viable option to build de novo genomes from historic museum specimens, which may prove particularly valuable for extinct, rare, or difficult to collect taxa.

scholarly journals Human Genome Assembly in 100 Minutes

2019 ◽  
Author(s):  
Chen-Shan Chin ◽  
Asif Khalak
Keyword(s):  
Single Molecule ◽  
Dna Sequences ◽  
Genome Assembly ◽  
De Novo ◽  
Critical Factor ◽  
Read Length ◽  
De Novo Genome Assembly ◽  
Small Indels ◽  
Sequencing Technologies ◽  
Long Read

AbstractDe novo genome assembly provides comprehensive, unbiased genomic information and makes it possible to gain insight into new DNA sequences not present in reference genomes. Many de novo human genomes have been published in the last few years, leveraging a combination of inexpensive short-read and single-molecule long-read technologies. As long-read DNA sequencers become more prevalent, the computational burden of generating assemblies persists as a critical factor. The most common approach to long-read assembly, using an overlap-layout-consensus (OLC) paradigm, requires all-to-all read comparisons, which quadratically scales in computational complexity with the number of reads. We assert that recently achievements in sequencing technology (i.e. with accuracy ~99% and read length ~10-15k) enables a fundamentally better strategy for OLC that is effectively linear rather than quadratic. Our genome assembly implementation, Peregrine uses sparse hierarchical minimizers (SHIMMER) to index reads thereby avoiding the need for an all-to-all read comparison step. Peregrine can assemble 30x human PacBio CCS read datasets in less than 30 CPU hours and around 100 wall-clock minutes to a high contiguity assembly (N50 > 20Mb). The continued advance of sequencing technologies coupled with the Peregrine assembler enables routine generation of human de novo assemblies. This will allow for population scale measurements of more comprehensive genomic variations -- beyond SNPs and small indels -- as well as novel applications requiring rapid access to de novo assemblies.

scholarly journals Deep repeat resolution—the assembly of the Drosophila Histone Complex

2018 ◽  
Vol 47 (3) ◽  
pp. e18-e18 ◽  
Author(s):  
Philipp Bongartz ◽  
Siegfried Schloissnig
Keyword(s):  
De Novo ◽  
Machine Learning Algorithms ◽  
Single Nucleotide Variants ◽  
Major Step ◽  
Base Pairs ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Wide Range ◽  
Long Read ◽  
Genome Assemblies

Abstract Though the advent of long-read sequencing technologies has led to a leap in contiguity of de novo genome assemblies, current reference genomes of higher organisms still do not provide unbroken sequences of complete chromosomes. Despite reads in excess of 30 000 base pairs, there are still repetitive structures that cannot be resolved by current state-of-the-art assemblers. The most challenging of these structures are tandemly arrayed repeats, which occur in the genomes of all eukaryotes. Untangling tandem repeat clusters is exceptionally difficult, since the rare differences between repeat copies are obscured by the high error rate of long reads. Solving this problem would constitute a major step towards computing fully assembled genomes. Here, we demonstrate by example of the Drosophila Histone Complex that via machine learning algorithms, it is possible to exploit the underlying distinguishing patterns of single nucleotide variants of repeats from very noisy data to resolve a large and highly conserved repeat cluster. The ideas explored in this paper are a first step towards the automated assembly of complex repeat structures and promise to be applicable to a wide range of eukaryotic genomes.

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