From contigs to chromosomes: automatic Improvement of Long Read Assemblies (ILRA)

Recent advances in long read technologies not only enable large consortia to aim to sequence all eukaryotes on Earth, but they also allow many laboratories to sequence their species of interest. Although there is a promise to obtain 'perfect genomes' with long read technologies, the number of contigs often exceeds the number of chromosomes significantly, containing many insertion and deletion errors around homopolymer tracks. To overcome these issues, we implemented ILRA to correct long reads-based assemblies, a pipeline that orders, names, merges, and circularizes contigs, filters erroneous small contigs and contamination, and corrects homopolymer errors with Illumina reads. We successfully tested our approach to assemble the genomes of four novel Plasmodium falciparum samples, and on existing assemblies of Trypanosoma brucei and Leptosphaeria spp. We found that correcting homopolymer tracks reduced the number of genes incorrectly annotated as pseudogenes, but an iterative correction seems to be needed to reduce high numbers of homopolymer errors. In summary, we described and compared the performance of a new tool, which improves the quality of long read assemblies. It can be used to correct genomes of a size of up to 300 Mb.

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SQANTI: extensive characterization of long read transcript sequences for quality control in full-length transcriptome identification and quantification

10.1101/118083 ◽

2017 ◽

Cited By ~ 9

Author(s):

Manuel Tardaguila ◽

Lorena de la Fuente ◽

Cristina Marti ◽

Cécile Pereira ◽

Francisco Jose Pardo-Palacios ◽

...

Keyword(s):

High Throughput Sequencing ◽

Full Length ◽

The Novel ◽

Extensive Evaluation ◽

Long Reads ◽

Long Read ◽

Novel Transcripts ◽

Mouse Transcriptome

ABSTRACTHigh-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in very well annotated organisms as mice and humans. Nonetheless, there is a need for studies and tools that characterize these novel isoforms. Here we present SQANTI, an automated pipeline for the classification of long-read transcripts that computes 47 descriptors that can be used to assess the quality of the data and of the preprocessing pipelines. We applied SQANTI to a neuronal mouse transcriptome using PacBio long reads and illustrate how the tool is effective in readily describing the composition of and characterizing the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach, and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, result more frequently in novel ORFs than novel UTRs and are enriched in both general metabolic and neural specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases we find that alternative isoforms are elusive to proteogenomics detection and are variable in protein changes with respect to the principal isoform of their genes. SQANTI allows the user to maximize the analytical outcome of long read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes. SQANTI is available at https://bitbucket.org/ConesaLab/sqanti.

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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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Overcoming uncollapsed haplotypes in long-read assemblies of non-model organisms

BMC Bioinformatics ◽

10.1186/s12859-021-04118-3 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Nadège Guiglielmoni ◽

Antoine Houtain ◽

Alessandro Derzelle ◽

Karine Van Doninck ◽

Jean-François Flot

Keyword(s):

Genome Assembly ◽

Model Organism ◽

Model Organisms ◽

Post Processing ◽

Diploid Genome ◽

Long Reads ◽

Long Read ◽

Eukaryote Genome ◽

Chromosome Level

Abstract Background Long-read sequencing is revolutionizing genome assembly: as PacBio and Nanopore technologies become more accessible in technicity and in cost, long-read assemblers flourish and are starting to deliver chromosome-level assemblies. However, these long reads are usually error-prone, making the generation of a haploid reference out of a diploid genome a difficult enterprise. Failure to properly collapse haplotypes results in fragmented and structurally incorrect assemblies and wreaks havoc on orthology inference pipelines, yet this serious issue is rarely acknowledged and dealt with in genomic projects, and an independent, comparative benchmark of the capacity of assemblers and post-processing tools to properly collapse or purge haplotypes is still lacking. Results We tested different assembly strategies on the genome of the rotifer Adineta vaga, a non-model organism for which high coverages of both PacBio and Nanopore reads were available. The assemblers we tested (Canu, Flye, NextDenovo, Ra, Raven, Shasta and wtdbg2) exhibited strikingly different behaviors when dealing with highly heterozygous regions, resulting in variable amounts of uncollapsed haplotypes. Filtering reads generally improved haploid assemblies, and we also benchmarked three post-processing tools aimed at detecting and purging uncollapsed haplotypes in long-read assemblies: HaploMerger2, purge_haplotigs and purge_dups. Conclusions We provide a thorough evaluation of popular assemblers on a non-model eukaryote genome with variable levels of heterozygosity. Our study highlights several strategies using pre and post-processing approaches to generate haploid assemblies with high continuity and completeness. This benchmark will help users to improve haploid assemblies of non-model organisms, and evaluate the quality of their own assemblies.

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BiSCoT: Improving large eukaryotic genome assemblies with optical maps

10.1101/674721 ◽

2019 ◽

Cited By ~ 1

Author(s):

Benjamin Istace ◽

Caroline Belser ◽

Jean-Marc Aury

Keyword(s):

Human Genome ◽

Fasta File ◽

Plant Genomes ◽

Link Type ◽

Long Reads ◽

Entire Chromosome ◽

Long Read ◽

Optical Maps ◽

Genome Assemblies

ABSTRACTMotivationLong read sequencing and Bionano Genomics optical maps are two techniques that, when used together, make it possible to reconstruct entire chromosome or chromosome arms structure. However, the existing tools are often too conservative and organization of contigs into scaffolds is not always optimal.ResultsWe developed BiSCoT (Bionano SCaffolding COrrection Tool), a tool that post-processes files generated during a Bionano scaffolding in order to produce an assembly of greater contiguity and quality. BiSCoT was tested on a human genome and four publicly available plant genomes sequenced with Nanopore long reads and improved significantly the contiguity and quality of the assemblies. BiSCoT generates a fasta file of the assembly as well as an AGP file which describes the new organization of the input assembly.AvailabilityBiSCoT and improved assemblies are freely available on Github at http://www.genoscope.cns.fr/biscot and Pypi at https://pypi.org/project/biscot/.

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Complete and validated genomes from a metagenome

10.1101/2020.04.08.032540 ◽

2020 ◽

Cited By ~ 1

Author(s):

Daniel J Giguere ◽

Alexander T Bahcheli ◽

Benjamin R Joris ◽

Julie M Paulssen ◽

Lisa M Gieg ◽

...

Keyword(s):

Naphthenic Acid ◽

Short Read ◽

Long Reads ◽

Complete Genomes ◽

Long Read ◽

Genomic Characterization ◽

Metagenomic Assembly ◽

Candidate Phyla Radiation

0.1AbstractThe assembly and binning of metagenomically-assembled genomes (MAGs) using Illumina sequencing has improved the genomic characterization of unculturable communities. However, short-read-only metagenomic assemblies rarely result in completed genomes because of the difficulty assembling repetitive regions. Here, we present a strategy to complete and validate multiple MAGs from a bacterial community using a combination of short and ultra long reads (N50 > 25 kb). Our strategy is to perform an initial long read-only metagenomic assembly using metaFlye, followed by multiple rounds of polishing using both long and short reads. To validate the genomes, we verified that longs reads spanned the regions that were not supported by uniquely mapped paired-end Illumina sequences. We obtained multiple complete genomes from a naphthenic acid-degrading community, including one from the recently proposed Candidate Phyla Radiation. The majority of the population is represented by the assembled genomes; recruiting 63.77 % of Nanopore reads, and 64.38 % of Illumina reads. The pipeline we developed will enable researchers to validate genomes from metagenomic assemblies, increasing the quality of metagenomically assembled genomes through additional scrutiny.

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

Genome Biology ◽

10.1186/s13059-019-1910-1 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 54

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

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Estimating Assembly Base Errors Using K-mer Abundance Difference (KAD) Between Short Reads and Genome Assembled Sequences

10.1101/2020.03.17.994566 ◽

2020 ◽

Cited By ~ 1

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

ABSTRACTGenome 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. Therefore, 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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Transcriptome assembly from long-read RNA-seq alignments with StringTie2

10.1101/694554 ◽

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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BiSCoT: improving large eukaryotic genome assemblies with optical maps

PeerJ ◽

10.7717/peerj.10150 ◽

2020 ◽

Vol 8 ◽

pp. e10150

Author(s):

Benjamin Istace ◽

Caroline Belser ◽

Jean-Marc Aury

Keyword(s):

Human Genome ◽

Fasta File ◽

Plant Genomes ◽

Link Type ◽

Long Reads ◽

Entire Chromosome ◽

Long Read ◽

Optical Maps ◽

Genome Assemblies

Motivation Long read sequencing and Bionano Genomics optical maps are two techniques that, when used together, make it possible to reconstruct entire chromosome or chromosome arms structure. However, the existing tools are often too conservative and organization of contigs into scaffolds is not always optimal. Results We developed BiSCoT (Bionano SCaffolding COrrection Tool), a tool that post-processes files generated during a Bionano scaffolding in order to produce an assembly of greater contiguity and quality. BiSCoT was tested on a human genome and four publicly available plant genomes sequenced with Nanopore long reads and improved significantly the contiguity and quality of the assemblies. BiSCoT generates a fasta file of the assembly as well as an AGP file which describes the new organization of the input assembly. Availability BiSCoT and improved assemblies are freely available on GitHub at http://www.genoscope.cns.fr/biscot and Pypi at https://pypi.org/project/biscot/.

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Merfin: improved variant filtering and polishing via k-mer validation

10.1101/2021.07.16.452324 ◽

2021 ◽

Author(s):

Giulio Formenti ◽

Arang Rhie ◽

Brian P Walenz ◽

Francoise Thibaud-Nissen ◽

Kishwar Shafin ◽

...

Keyword(s):

Human Genome ◽

Variant Calling ◽

Read Mapping ◽

Mapping Algorithm ◽

Copy Numbers ◽

Long Reads ◽

Variant Filtering ◽

Long Read ◽

Finishing Tool

Read mapping and variant calling approaches have been widely used for accurate genotyping and improving consensus quality assembled from noisy long reads. Variant calling accuracy relies heavily on the read quality, the precision of the read mapping algorithm and variant caller, and the criteria adopted to filter the calls. However, it is impossible to define a single set of optimal parameters, as they vary depending on the quality of the read set, the variant caller of choice, and the quality of the unpolished assembly. To overcome this issue, we have devised a new tool called Merfin (k-mer based finishing tool), a k-mer based variant filtering algorithm for improved genotyping and polishing. Merfin evaluates the accuracy of a call based on expected k-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller internal score. Moreover, we introduce novel assembly quality and completeness metrics that account for the expected genomic copy numbers. Merfin significantly increased the precision of a variant call and reduced frameshift errors when applied to PacBio HiFi, PacBio CLR, or Nanopore long read based assemblies. We demonstrate the utility while polishing the first complete human genome, a fully phased human genome, and non-human high-quality genomes.

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