Deep repeat resolution—the assembly of the Drosophila Histone Complex

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

10.1101/840447 ◽

2019 ◽

Cited By ~ 1

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

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Hapo-G, haplotype-aware polishing of genome assemblies with accurate reads

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab034 ◽

2021 ◽

Vol 3 (2) ◽

Author(s):

Jean-Marc Aury ◽

Benjamin Istace

Keyword(s):

Single Molecule ◽

Direct Consequence ◽

High Quality ◽

Sequencing Errors ◽

Coding Regions ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Long Read ◽

Genome Assemblies

Abstract Single-molecule sequencing technologies have recently been commercialized by Pacific Biosciences and Oxford Nanopore with the promise of sequencing long DNA fragments (kilobases to megabases order) and then, using efficient algorithms, provide high quality assemblies in terms of contiguity and completeness of repetitive regions. However, the error rate of long-read technologies is higher than that of short-read technologies. This has a direct consequence on the base quality of genome assemblies, particularly in coding regions where sequencing errors can disrupt the coding frame of genes. In the case of diploid genomes, the consensus of a given gene can be a mixture between the two haplotypes and can lead to premature stop codons. Several methods have been developed to polish genome assemblies using short reads and generally, they inspect the nucleotide one by one, and provide a correction for each nucleotide of the input assembly. As a result, these algorithms are not able to properly process diploid genomes and they typically switch from one haplotype to another. Herein we proposed Hapo-G (Haplotype-Aware Polishing Of Genomes), a new algorithm capable of incorporating phasing information from high-quality reads (short or long-reads) to polish genome assemblies and in particular assemblies of diploid and heterozygous genomes.

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Platanus_B: an accurate de novo assembler for bacterial genomes using an iterative error-removal process

DNA Research ◽

10.1093/dnares/dsaa014 ◽

2020 ◽

Vol 27 (3) ◽

Cited By ~ 1

Author(s):

Rei Kajitani ◽

Dai Yoshimura ◽

Yoshitoshi Ogura ◽

Yasuhiro Gotoh ◽

Tetsuya Hayashi ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

De Novo ◽

Bacterial Genomes ◽

Long Reads ◽

Wide Range ◽

Long Read ◽

Phylogenomic Analyses ◽

Error Removal ◽

Iterative Error

Abstract De novo assembly of short DNA reads remains an essential technology, especially for large-scale projects and high-resolution variant analyses in epidemiology. However, the existing tools often lack sufficient accuracy required to compare closely related strains. To facilitate such studies on bacterial genomes, we developed Platanus_B, a de novo assembler that employs iterations of multiple error-removal algorithms. The benchmarks demonstrated the superior accuracy and high contiguity of Platanus_B, in addition to its ability to enhance the hybrid assembly of both short and nanopore long reads. Although the hybrid strategies for short and long reads were effective in achieving near full-length genomes, we found that short-read-only assemblies generated with Platanus_B were sufficient to obtain ≥90% of exact coding sequences in most cases. In addition, while nanopore long-read-only assemblies lacked fine-scale accuracies, inclusion of short reads was effective in improving the accuracies. Platanus_B can, therefore, be used for comprehensive genomic surveillances of bacterial pathogens and high-resolution phylogenomic analyses of a wide range of bacteria.

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Impact of Chimera-less Long Reads on Metagenomics of Human Gut Viromes Treated With Multiple Displacement Amplification

10.21203/rs.3.rs-58640/v1 ◽

2020 ◽

Author(s):

Yuya Kiguchi ◽

Suguru Nishijima ◽

Naveen Kumar ◽

Masahira Hattori ◽

Wataru Suda

Keyword(s):

De Novo ◽

Multiple Displacement Amplification ◽

Read Length ◽

Human Gut ◽

Average Read Length ◽

Sequencing Technologies ◽

Genomic Complexity ◽

Long Reads ◽

Long Read ◽

The Impact

Abstract Background: The ecological and biological features of the indigenous phage community (virome) in the human gut microbiome are poorly understood, possibly due to many fragmented contigs and fewer complete genomes based on conventional short-read metagenomics. Long-read sequencing technologies have attracted attention as an alternative approach to reconstruct long and accurate contigs from microbial communities. However, the impact of long-read metagenomics on human gut virome analysis has not been well evaluated. Results: Here we present chimera-less PacBio long-read metagenomics of multiple displacement amplification (MDA)-treated human gut virome DNA. The method included the development of a novel bioinformatics tool, SACRA (Split Amplified Chimeric Read Algorithm), which efficiently detects and splits numerous chimeric reads in PacBio reads from the MDA-treated virome samples. SACRA treatment of PacBio reads from five samples markedly reduced the average chimera ratio from 72 to 1.5%, generating chimera-less PacBio reads with an average read-length of 1.8 kb. De novo assembly of the chimera-less long reads generated contigs with an average N50 length of 11.1 kb, whereas those of MiSeq short reads from the same samples were 0.7 kb, dramatically improving contig extension. Alignment of both contig sets generated 378 high-quality merged contigs (MCs) composed of the minimum scaffolds of 434 MiSeq and 637 PacBio contigs, respectively, and also identified numerous MiSeq short fragmented contigs ≤500 bp additionally aligned to MCs, which possibly originated from a small fraction of MiSeq chimeric reads. The alignment also revealed that fragmentations of the scaffolded MiSeq contigs were caused primarily by genomic complexity of the community, including local repeats, hypervariable regions, and highly conserved sequences in and between the phage genomes. We identified 142 complete and near-complete phage genomes including 108 novel genomes, varying from 5 to 185 kb in length, the majority of which were predicted to be Microviridae phages including several variants with homologous but distinct genomes, which were fragmented in MiSeq contigs. Conclusions: Long-read metagenomics coupled with SACRA provides an improved method to reconstruct accurate and extended phage genomes from MDA-treated virome samples of the human gut, and potentially from other environmental virome samples.

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Fast-SG: An alignment-free algorithm for hybrid assembly

10.1101/209122 ◽

2017 ◽

Author(s):

Alex Di Genova ◽

Gonzalo A. Ruz ◽

Marie-France Sagot ◽

Alejandro Maass

Keyword(s):

De Novo ◽

Reference Level ◽

Hybrid Assembly ◽

Short Read ◽

Sequencing Technologies ◽

Alignment Free ◽

Long Reads ◽

Long Read ◽

Definition Of ◽

Large Genomes

ABSTRACTLong read sequencing technologies are the ultimate solution for genome repeats, allowing near reference level reconstructions of large genomes. However, long read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods which combine short and long read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes. In this paper, we propose a new method, called FAST-SG, which uses a new ultra-fast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. FAST-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how FAST-SG outperforms the state-of-the-art short read aligners when building the scaffolding graph, and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using FAST-SG with shallow long read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878).

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Factorial estimating assembly base errors using k-mer abundance difference (KAD) between short reads and genome assembled sequences

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqaa075 ◽

2020 ◽

Vol 2 (3) ◽

Author(s):

Cheng He ◽

Guifang Lin ◽

Hairong Wei ◽

Haibao Tang ◽

Frank F White ◽

...

Keyword(s):

Copy Number ◽

Error Rates ◽

Genome Sequences ◽

Short Reads ◽

Sequencing Technologies ◽

Insertion And Deletion ◽

Novel Approach ◽

Long Reads ◽

Long Read ◽

Genome Assemblies

Abstract Genome sequences provide genomic maps with a single-base resolution for exploring genetic contents. Sequencing technologies, particularly long reads, have revolutionized genome assemblies for producing highly continuous genome sequences. However, current long-read sequencing technologies generate inaccurate reads that contain many errors. Some errors are retained in assembled sequences, which are typically not completely corrected by using either long reads or more accurate short reads. The issue commonly exists, but few tools are dedicated for computing error rates or determining error locations. In this study, we developed a novel approach, referred to as k-mer abundance difference (KAD), to compare the inferred copy number of each k-mer indicated by short reads and the observed copy number in the assembly. Simple KAD metrics enable to classify k-mers into categories that reflect the quality of the assembly. Specifically, the KAD method can be used to identify base errors and estimate the overall error rate. In addition, sequence insertion and deletion as well as sequence redundancy can also be detected. Collectively, KAD is valuable for quality evaluation of genome assemblies and, potentially, provides a diagnostic tool to aid in precise error correction. KAD software has been developed to facilitate public uses.

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

10.1101/2021.06.17.448848 ◽

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.

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Clustering de Novo by Gene of Long Reads from Transcriptomics Data

10.1101/170035 ◽

2017 ◽

Cited By ~ 3

Author(s):

Camille Marchet ◽

Lolita Lecompte ◽

Corinne Da Silva ◽

Corinne Cruaud ◽

Jean-Marc Aury ◽

...

Keyword(s):

De Novo ◽

Free Access ◽

Sequencing Data ◽

Base Pairs ◽

Long Reads ◽

Oxford Nanopore ◽

Processing Step ◽

Whole Transcriptome Sequencing ◽

Long Read ◽

Transcriptomics Data

AbstractLong-read sequencing currently provides sequences of several thousand base pairs. This allows to obtain complete transcripts, which offers an un-precedented vision of the cellular transcriptome.However the literature is lacking tools to cluster such data de novo, in particular for Oxford Nanopore Technologies reads, because of the inherent high error rate compared to short reads.Our goal is to process reads from whole transcriptome sequencing data accurately and without a reference genome in order to reliably group reads coming from the same gene. This de novo approach is therefore particularly suitable for non-model species, but can also serve as a useful pre-processing step to improve read mapping. Our contribution is both to propose a new algorithm adapted to clustering of reads by gene and a practical and free access tool that permits to scale the complete processing of eukaryotic transcriptomes.We sequenced a mouse RNA sample using the MinION device, this dataset is used to compare our solution to other algorithms used in the context of biological clustering. We demonstrate its is better-suited for transcriptomics long reads. When a reference is available thus mapping possible, we show that it stands as an alternative method that predicts complementary clusters.

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

10.1101/231118 ◽

2017 ◽

Cited By ~ 6

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.

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Highly-accurate long-read sequencing improves variant detection and assembly of a human genome

10.1101/519025 ◽

2019 ◽

Cited By ~ 27

Author(s):

Aaron M. Wenger ◽

Paul Peluso ◽

William J. Rowell ◽

Pi-Chuan Chang ◽

Richard J. Hall ◽

...

Keyword(s):

Single Molecule ◽

De Novo ◽

Structural Variants ◽

Short Reads ◽

Sequencing Technologies ◽

Long Reads ◽

Long Read ◽

Variant Detection ◽

High Quality Genome ◽

Circular Consensus Sequencing

AbstractThe major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

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