Significantly improving the quality of genome assemblies through curation

Abstract Genome sequence assemblies provide the basis for our understanding of biology. Generating error-free assemblies is therefore the ultimate, but sadly still unachieved goal of a multitude of research projects. Despite the ever-advancing improvements in data generation, assembly algorithms and pipelines, no automated approach has so far reliably generated near error-free genome assemblies for eukaryotes. Whilst working towards improved datasets and fully automated pipelines, assembly evaluation and curation is actively used to bridge this shortcoming and significantly reduce the number of assembly errors. In addition to this increase in product value, the insights gained from assembly curation are fed back into the automated assembly strategy and contribute to notable improvements in genome assembly quality. We describe our tried and tested approach for assembly curation using gEVAL, the genome evaluation browser. We outline the procedures applied to genome curation using gEVAL and also our recommendations for assembly curation in a gEVAL-independent context to facilitate the uptake of genome curation in the wider community.

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Significantly improving the quality of genome assemblies through curation

10.1101/2020.08.12.247734 ◽

2020 ◽

Cited By ~ 2

Author(s):

Kerstin Howe ◽

William Chow ◽

Joanna Collins ◽

Sarah Pelan ◽

Damon-Lee Pointon ◽

...

Keyword(s):

Data Sets ◽

Data Generation ◽

Research Projects ◽

Automated Assembly ◽

Assembly Quality ◽

Assembly Strategy ◽

Assembly Evaluation ◽

Assembly Algorithms ◽

Genome Assemblies

AbstractBackgroundGenome sequence assemblies provide the basis for our understanding of biology. Generating error-free assemblies is therefore the ultimate, but sadly still unachieved goal of a multitude of research projects. Despite the ever-advancing improvements in data generation, assembly algorithms and pipelines, no automated approach has so far reliably generated near error-free genome assemblies for eukaryotes.ResultsWhilst working towards improved data sets and fully automated pipelines, assembly evaluation and curation is actively employed to bridge this shortcoming and significantly reduce the number of assembly errors. In addition to this increase in product value, the insights gained from assembly curation are fed back into the automated assembly strategy and contribute to notable improvements in genome assembly quality.ConclusionsWe describe our tried and tested approach for assembly curation using gEVAL, the genome evaluation browser. We outline the procedures applied to genome curation using gEVAL and also our recommendations for assembly curation in an gEVAL-independent context to facilitate the uptake of genome curation in the wider community.

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Assessment the Quality of Genome Assemblies by using QUAST Tool for Metagenomics

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e6435.038620 ◽

2020 ◽

Vol 8 (6) ◽

pp. 4253-4259

Keyword(s):

Genome Sequencing ◽

Reference Genome ◽

Assessment Tool ◽

Quality Assessment Tool ◽

Assembly Evaluation ◽

Assembly Algorithms ◽

Genome Assemblies ◽

Modern Tool ◽

Assembly Software

Number of assembly algorithms have emerged out but due to constraints of genome sequencing techniques no one is perfect. Various methods for assembler’s comparison have been developed, but none is yet a recognized standard. The problem of evaluating assemblies of formerly unsequenced species has not been considered, because mostly existing methods for comparing assemblies are only applicable to new assemblies of finished genomes. For comparing and evaluating genome assemblies we have used QUAST (Quality Assessment Tool). This tool is used to assess the quality of leading assembly software by evaluating quality metrics. Assemblies with a reference genome, as well as without a reference can be evaluated by QUAST tool. For genome assembly evaluation based on alignment of contigs to a reference, it is a modern tool. In this study we demonstrate QUAST performance by comparing several leading genome assemblers on three metagenomic datasets.

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New approaches for assembly of short-read metagenomic data

10.7287/peerj.preprints.27332 ◽

2018 ◽

Author(s):

Martin Ayling ◽

Matthew D Clark ◽

Richard M Leggett

Keyword(s):

Genome Assembly ◽

Metagenomic Data ◽

Short Read ◽

New Approaches ◽

Single Genome ◽

New Type ◽

Multiple Genomes ◽

Assembly Algorithms ◽

Genome Assemblies

In recent years, the use of longer-range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic datasets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

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New approaches for metagenome assembly with short reads

Briefings in Bioinformatics ◽

10.1093/bib/bbz020 ◽

2019 ◽

Vol 21 (2) ◽

pp. 584-594 ◽

Cited By ~ 19

Author(s):

Martin Ayling ◽

Matthew D Clark ◽

Richard M Leggett

Keyword(s):

Genome Assembly ◽

Metagenomic Data ◽

Data Sets ◽

New Approaches ◽

Single Genome ◽

Metagenome Assembly ◽

New Type ◽

Assembly Algorithms ◽

Genome Assemblies

Abstract In recent years, the use of longer range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic data sets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

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New approaches for assembly of short-read metagenomic data

10.7287/peerj.preprints.27332v1 ◽

2018 ◽

Author(s):

Martin Ayling ◽

Matthew D Clark ◽

Richard M Leggett

Keyword(s):

Genome Assembly ◽

Metagenomic Data ◽

Short Read ◽

New Approaches ◽

Single Genome ◽

New Type ◽

Multiple Genomes ◽

Assembly Algorithms ◽

Genome Assemblies

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PDR: a new genome assembly evaluation metric based on genetics concerns

Bioinformatics ◽

10.1093/bioinformatics/btaa704 ◽

2020 ◽

Author(s):

Luyu Xie ◽

Limsoon Wong

Keyword(s):

Genome Assembly ◽

Pairwise Distance ◽

Supplementary Information ◽

Supplementary Data ◽

Assembly Quality ◽

Genetic Studies ◽

A Genome ◽

Assembly Evaluation ◽

Evaluation Metric

Abstract Motivation Existing genome assembly evaluation metrics provide only limited insight on specific aspects of genome assembly quality, and sometimes even disagree with each other. For better integrative comparison between assemblies, we propose, here, a new genome assembly evaluation metric, Pairwise Distance Reconstruction (PDR). It derives from a common concern in genetic studies, and takes completeness, contiguity, and correctness into consideration. We also propose an approximation implementation to accelerate PDR computation. Results Our results on publicly available datasets affirm PDR’s ability to integratively assess the quality of a genome assembly. In fact, this is guaranteed by its definition. The results also indicated the error introduced by approximation is extremely small and thus negligible. Availabilityand implementation https://github.com/XLuyu/PDR. Supplementary information Supplementary data are available at Bioinformatics online.

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Assessing species coverage and assembly quality of rapidly accumulating sequenced genomes

10.1101/2021.10.15.464561 ◽

2021 ◽

Author(s):

Romain Feron ◽

Robert Michael Waterhouse

Keyword(s):

Large Scale ◽

Automated Analysis ◽

Single Copy ◽

The United States ◽

Community Resource ◽

Assembly Quality ◽

Sequencing Technologies ◽

Analysis Workflow ◽

Genome Assemblies

Ambitious initiatives to coordinate genome sequencing of Earth's biodiversity mean that the accumulation of genomic data is growing rapidly. In addition to cataloguing biodiversity, these data provide the basis for understanding biological function and evolution. Accurate and complete genome assemblies offer a comprehensive and reliable foundation upon which to advance our understanding of organismal biology at genetic, species, and ecosystem levels. However, ever-changing sequencing technologies and analysis methods mean that available data are often heterogeneous in quality. In order to guide forthcoming genome generation efforts and promote efficient prioritisation of resources, it is thus essential to define and monitor taxonomic coverage and quality of the data. Here we present an automated analysis workflow that surveys genome assemblies from the United States National Center for Biotechnology Information (NCBI), assesses their completeness using the relevant Benchmarking Universal Single-Copy Orthologue (BUSCO) datasets, and collates the results into an interactively browsable resource. We apply our workflow to produce a community resource of available assemblies from the phylum Arthropoda, the Arthropoda Assembly Assessment Catalogue. Using this resource, we survey current taxonomic coverage and assembly quality at the NCBI, we examine how key assembly metrics relate to gene content completeness, and we compare results from using different BUSCO lineage datasets. These results demonstrate how the workflow can be used to build a community resource that enables large-scale assessments to survey species coverage and data quality of available genome assemblies, and to guide prioritisations for ongoing and future sampling, sequencing, and genome generation initiatives.

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Quality of prokaryote genome assembly: Indispensable issues of factors affecting prokaryote genome assembly quality

Gene ◽

10.1016/j.gene.2012.06.016 ◽

2012 ◽

Vol 505 (2) ◽

pp. 365-367 ◽

Cited By ~ 8

Author(s):

Adriana R. Carneiro ◽

Rommel Thiago Jucá Ramos ◽

Hivana Patricia Melo Barbosa ◽

Maria Paula C. Schneider ◽

Debmalya Barh ◽

...

Keyword(s):

Genome Assembly ◽

Assembly Quality ◽

Factors Affecting

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Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils

Molecular Biology and Evolution ◽

10.1093/molbev/msz191 ◽

2019 ◽

Vol 36 (12) ◽

pp. 2906-2921 ◽

Cited By ~ 20

Author(s):

Austin H Patton ◽

Mark J Margres ◽

Amanda R Stahlke ◽

Sarah Hendricks ◽

Kevin Lewallen ◽

...

Keyword(s):

Population Size ◽

Frequency Spectrum ◽

Genome Assembly ◽

Genomic Sequence ◽

Demographic History ◽

Tasmanian Devil ◽

Assembly Quality ◽

Reconstruction Methods ◽

Site Frequency Spectrum ◽

Genome Assemblies

Abstract Reconstructing species’ demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species’ effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.

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dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

BMC Genomics ◽

10.1186/s12864-019-6070-x ◽

2019 ◽

Vol 20 (1) ◽

Author(s):

Gokhan Yavas ◽

Huixiao Hong ◽

Wenming Xiao

Keyword(s):

Quality Assessment ◽

Genome Assembly ◽

Reference Genome ◽

De Novo ◽

Quality Score ◽

De Novo Genome Assembly ◽

Genome Assemblies ◽

Reference Genomes ◽

Better Than

Abstract Background Accurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly. Results To address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies. Conclusions The dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

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