Long-read and chromosome-scale assembly of the hexaploid wheat genome achieves higher resolution for research and breeding

AbstractThe sequencing of the wheat (Triticum aestivum) genome has been a methodological challenge for many years due to its large size (15.5 Gb), repeat content, and hexaploidy. Many initiatives aiming at obtaining a reference genome of cultivar Chinese Spring have been launched in the past years and it was achieved in 2018 as the result of a huge effort to combine short-read whole genome sequencing with many other resources. Reference-quality genome assemblies were then produced for other accessions but the rapid evolution of sequencing technologies offers opportunities to reach high-quality standards at lower cost. Here, we report on an optimized procedure based on long-reads produced on the ONT (Oxford Nanopore Technology) PromethION device to assemble the genome of the French bread wheat cultivar Renan. We provide the most contiguous and complete chromosome-scale assembly of a bread wheat genome to date, a resource that will be valuable for the crop community and will facilitate the rapid selection of agronomically important traits. We also provide the methodological standards to generate high-quality assemblies of complex genomes.

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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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PhaseME: Automatic rapid assessment of phasing quality and phasing improvement

GigaScience ◽

10.1093/gigascience/giaa078 ◽

2020 ◽

Vol 9 (7) ◽

Cited By ~ 1

Author(s):

Sina Majidian ◽

Fritz J Sedlazeck

Keyword(s):

Rapid Assessment ◽

Linkage Data ◽

Universal Method ◽

High Quality ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Linkage Information ◽

Quality Assessments

Abstract Background The detection of which mutations are occurring on the same DNA molecule is essential to predict their consequences. This can be achieved by phasing the genomic variations. Nevertheless, state-of-the-art haplotype phasing is currently a black box in which the accuracy and quality of the reconstructed haplotypes are hard to assess. Findings Here we present PhaseME, a versatile method to provide insights into and improvement of sample phasing results based on linkage data. We showcase the performance and the importance of PhaseME by comparing phasing information obtained from Pacific Biosciences including both continuous long reads and high-quality consensus reads, Oxford Nanopore Technologies, 10x Genomics, and Illumina sequencing technologies. We found that 10x Genomics and Oxford Nanopore phasing can be significantly improved while retaining a high N50 and completeness of phase blocks. PhaseME generates reports and summary plots to provide insights into phasing performance and correctness. We observed unique phasing issues for each of the sequencing technologies, highlighting the necessity of quality assessments. PhaseME is able to decrease the Hamming error rate significantly by 22.4% on average across all 5 technologies. Additionally, a significant improvement is obtained in the reduction of long switch errors. Especially for high-quality consensus reads, the improvement is 54.6% in return for only a 5% decrease in phase block N50 length. Conclusions PhaseME is a universal method to assess the phasing quality and accuracy and improves the quality of phasing using linkage information. The package is freely available at https://github.com/smajidian/phaseme.

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Improving the Chromosome-Level Genome Assembly of the Siamese Fighting Fish (Betta splendens) in a University Master’s Course

G3 Genes|Genome|Genetics ◽

10.1534/g3.120.401205 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2179-2183 ◽

Cited By ~ 1

Author(s):

Stefan Prost ◽

Malte Petersen ◽

Martin Grethlein ◽

Sarah Joy Hahn ◽

Nina Kuschik-Maczollek ◽

...

Keyword(s):

Genome Assembly ◽

High Throughput Sequencing ◽

Siamese Fighting Fish ◽

Betta Splendens ◽

High Quality ◽

Sequencing Platform ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

Chromosome Level

Ever decreasing costs along with advances in sequencing and library preparation technologies enable even small research groups to generate chromosome-level assemblies today. Here we report the generation of an improved chromosome-level assembly for the Siamese fighting fish (Betta splendens) that was carried out during a practical university master’s course. The Siamese fighting fish is a popular aquarium fish and an emerging model species for research on aggressive behavior. We updated the current genome assembly by generating a new long-read nanopore-based assembly with subsequent scaffolding to chromosome-level using previously published Hi-C data. The use of ∼35x nanopore-based long-read data sequenced on a MinION platform (Oxford Nanopore Technologies) allowed us to generate a baseline assembly of only 1,276 contigs with a contig N50 of 2.1 Mbp, and a total length of 441 Mbp. Scaffolding using the Hi-C data resulted in 109 scaffolds with a scaffold N50 of 20.7 Mbp. More than 99% of the assembly is comprised in 21 scaffolds. The assembly showed the presence of 96.1% complete BUSCO genes from the Actinopterygii dataset indicating a high quality of the assembly. We present an improved full chromosome-level assembly of the Siamese fighting fish generated during a university master’s course. The use of ∼35× long-read nanopore data drastically improved the baseline assembly in terms of continuity. We show that relatively in-expensive high-throughput sequencing technologies such as the long-read MinION sequencing platform can be used in educational settings allowing the students to gain practical skills in modern genomics and generate high quality results that benefit downstream research projects.

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Evaluation of Germline Structural Variant Calling Methods for Nanopore Sequencing Data

Frontiers in Genetics ◽

10.3389/fgene.2021.761791 ◽

2021 ◽

Vol 12 ◽

Author(s):

Davide Bolognini ◽

Alberto Magi

Keyword(s):

Variant Calling ◽

Research Report ◽

Nanopore Sequencing ◽

Sequencing Data ◽

Factors Affecting ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Sequencing Studies ◽

Long Read

Structural variants (SVs) are genomic rearrangements that involve at least 50 nucleotides and are known to have a serious impact on human health. While prior short-read sequencing technologies have often proved inadequate for a comprehensive assessment of structural variation, more recent long reads from Oxford Nanopore Technologies have already been proven invaluable for the discovery of large SVs and hold the potential to facilitate the resolution of the full SV spectrum. With many long-read sequencing studies to follow, it is crucial to assess factors affecting current SV calling pipelines for nanopore sequencing data. In this brief research report, we evaluate and compare the performances of five long-read SV callers across four long-read aligners using both real and synthetic nanopore datasets. In particular, we focus on the effects of read alignment, sequencing coverage, and variant allele depth on the detection and genotyping of SVs of different types and size ranges and provide insights into precision and recall of SV callsets generated by integrating the various long-read aligners and SV callers. The computational pipeline we propose is publicly available at https://github.com/davidebolo1993/EViNCe and can be adjusted to further evaluate future nanopore sequencing datasets.

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BleTIES: Annotation of natural genome editing in ciliates using long read sequencing

10.1101/2021.05.18.444610 ◽

2021 ◽

Author(s):

Brandon K. B. Seah ◽

Estienne C. Swart

Keyword(s):

Dna Sequences ◽

Sequence Data ◽

Low Complexity ◽

Supplementary Information ◽

Neighboring Element ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Long Read ◽

Element Elimination

Ciliates are single-celled eukaryotes that eliminate specific, interspersed DNA sequences (internally eliminated sequences, IESs) from their genomes during development. These are challenging to annotate and assemble because IES-containing sequences are much less abundant in the cell than those without, and IES sequences themselves often contain repetitive and low-complexity sequences. Long read sequencing technologies from Pacific Biosciences and Oxford Nanopore have the potential to reconstruct longer IESs than has been possible with short reads, and also the ability to detect correlations of neighboring element elimination. Here we present BleTIES, a software toolkit for detecting, assembling, and analyzing IESs using mapped long reads. Availability and implementation: BleTIES is implemented in Python 3. Source code is available at https://github.com/Swart-lab/bleties (MIT license), and also distributed via Bioconda. Contact: [email protected] Supplementary information: Benchmarking of BleTIES with published sequence data.

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Construction of a chromosome-scale long-read reference genome assembly for potato

GigaScience ◽

10.1093/gigascience/giaa100 ◽

2020 ◽

Vol 9 (9) ◽

Cited By ~ 3

Author(s):

Gina M Pham ◽

John P Hamilton ◽

Joshua C Wood ◽

Joseph T Burke ◽

Hainan Zhao ◽

...

Keyword(s):

Genome Sequence ◽

Reference Genome ◽

Agronomic Traits ◽

Solanum Tuberosum L ◽

Fold Increase ◽

High Quality ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

Oxford Nanopore Technologies

Abstract Background Worldwide, the cultivated potato, Solanum tuberosum L., is the No. 1 vegetable crop and a critical food security crop. The genome sequence of DM1–3 516 R44, a doubled monoploid clone of S. tuberosum Group Phureja, was published in 2011 using a whole-genome shotgun sequencing approach with short-read sequence data. Current advanced sequencing technologies now permit generation of near-complete, high-quality chromosome-scale genome assemblies at minimal cost. Findings Here, we present an updated version of the DM1–3 516 R44 genome sequence (v6.1) using Oxford Nanopore Technologies long reads coupled with proximity-by-ligation scaffolding (Hi-C), yielding a chromosome-scale assembly. The new (v6.1) assembly represents 741.6 Mb of sequence (87.8%) of the estimated 844 Mb genome, of which 741.5 Mb is non-gapped with 731.2 Mb anchored to the 12 chromosomes. Use of Oxford Nanopore Technologies full-length complementary DNA sequencing enabled annotation of 32,917 high-confidence protein-coding genes encoding 44,851 gene models that had a significantly improved representation of conserved orthologs compared with the previous annotation. The new assembly has improved contiguity with a 595-fold increase in N50 contig size, 99% reduction in the number of contigs, a 44-fold increase in N50 scaffold size, and an LTR Assembly Index score of 13.56, placing it in the category of reference genome quality. The improved assembly also permitted annotation of the centromeres via alignment to sequencing reads derived from CENH3 nucleosomes. Conclusions Access to advanced sequencing technologies and improved software permitted generation of a high-quality, long-read, chromosome-scale assembly and improved annotation dataset for the reference genotype of potato that will facilitate research aimed at improving agronomic traits and understanding genome evolution.

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A benchmark of structural variation detection by long reads through a realistic simulated model

10.1101/2020.12.25.424397 ◽

2020 ◽

Author(s):

Nicolas Dierckxsens ◽

Tong Li ◽

Joris R. Vermeesch ◽

Zhi Xie

Keyword(s):

Structural Variation ◽

Rapid Evolution ◽

Detection Methods ◽

Sequencing Data ◽

Simulated Model ◽

Sequencing Technologies ◽

Long Reads ◽

Long Read ◽

Sequencing Platforms ◽

The Impact

ABSTRACTDespite the rapid evolution of new sequencing technologies, structural variation detection remains poorly ascertained. The high discrepancy between the results of structural variant analysis programs makes it difficult to assess their performance on real datasets. Accurate simulations of structural variation distributions and sequencing data of the human genome are crucial for the development and benchmarking of new tools. In order to gain a better insight into the detection of structural variation with long sequencing reads, we created a realistic simulated model to thoroughly compare SV detection methods and the impact of the chosen sequencing technology and sequencing depth. To achieve this, we developed Sim-it, a straightforward tool for the simulation of both structural variation and long-read data. These simulations from Sim-it revealed the strengths and weaknesses for current available structural variation callers and long read sequencing platforms. Our findings were also supported by the latest structural variation benchmark set developed by the GIAB Consortium. With these findings, we developed a new method (combiSV) that can combine the results from five different SV callers into a superior call set with increased recall and precision. Both Sim-it and combiSV are open source and can be downloaded at https://github.com/ndierckx/.

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SVJedi: Genotyping structural variations with long reads

10.1101/849208 ◽

2019 ◽

Author(s):

Lolita Lecompte ◽

Pierre Peterlongo ◽

Dominique Lavenier ◽

Claire Lemaitre

Keyword(s):

Sequencing Data ◽

Structural Variations ◽

Short Read ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Clinical Diagnoses ◽

Long Read ◽

Reference Sequences ◽

The One

AbstractMotivationStudies on structural variants (SV) are expanding rapidly. As a result, and thanks to third generation sequencing technologies, the number of discovered SVs is increasing, especially in the human genome. At the same time, for several applications such as clinical diagnoses, it is important to genotype newly sequenced individuals on well defined and characterized SVs. Whereas several SV genotypers have been developed for short read data, there is a lack of such dedicated tool to assess whether known SVs are present or not in a new long read sequenced sample, such as the one produced by Pacific Biosciences or Oxford Nanopore Technologies.ResultsWe present a novel method to genotype known SVs from long read sequencing data. The method is based on the generation of a set of reference sequences that represent the two alleles of each structural variant. Long reads are aligned to these reference sequences. Alignments are then analyzed and filtered out to keep only informative ones, to quantify and estimate the presence of each SV allele and the allele frequencies. We provide an implementation of the method, SVJedi, to genotype insertions and deletions with long reads. The tool has been applied to both simulated and real human datasets and achieves high genotyping accuracy. We also demonstrate that SV genotyping is considerably improved with SVJedi compared to other approaches, namely SV discovery and short read SV genotyping approaches.Availabilityhttps://github.com/llecompte/[email protected]

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Rapid multi-locus sequence typing direct from uncorrected long reads using Krocus

10.1101/259150 ◽

2018 ◽

Author(s):

Andrew J. Page ◽

Jacqueline A. Keane

Keyword(s):

Error Rates ◽

Multi Locus Sequence Typing ◽

Short Read Sequencing ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Standard Tool ◽

Long Read ◽

Sequence Types ◽

Very High

AbstractGenome sequencing is rapidly being adopted in reference labs and hospitals for bacterial outbreak investigation and diagnostics where time is critical. Seven gene multi-locus sequence typing is a standard tool for broadly classifying samples into sequence types, allowing, in many cases, to rule a sample in or out of an outbreak, or allowing for general characteristics about a bacterial strain to be inferred. Long read sequencing technologies, such as from PacBio or Oxford Nanopore, can produce read data within minutes of an experiment starting, unlike short read sequencing technologies which require many hours/days. However, the error rates of raw uncorrected long read data are very high. We present Krocus which can predict a sequence type directly from uncorrected long reads, and which was designed to consume read data as it is produced, providing results in minutes. It is the only tool which can do this from uncorrected long reads. We tested Krocus on over 600 samples sequenced with using long read sequencing technologies from PacBio and Oxford Nanopore. It provides sequence types on average within 90 seconds, with a sensitivity of 94% and specificity of 97%, directly from uncorrected raw sequence reads. The software is written in Python and is available under the open source license GNU GPL version 3.

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Improving the chromosome-level genome assembly of the Siamese fighting fish (Betta splendens) in a university Master’s course

10.1101/2020.03.06.981332 ◽

2020 ◽

Author(s):

Stefan Prost ◽

Malte Petersen ◽

Martin Grethlein ◽

Sarah Joy Hahn ◽

Nina Kuschik-Maczollek ◽

...

Keyword(s):

Genome Assembly ◽

High Throughput Sequencing ◽

Siamese Fighting Fish ◽

Betta Splendens ◽

High Quality ◽

Sequencing Platform ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

Chromosome Level

AbstractBackgroundEver decreasing costs along with advances in sequencing and library preparation technologies enable even small research groups to generate chromosome-level assemblies today. Here we report the generation of an improved chromosome-level assembly for the Siamese fighting fish (Betta splendens) that was carried out during a practical university Master’s course. The Siamese fighting fish is a popular aquarium fish and an emerging model species for research on aggressive behaviour. We updated the current genome assembly by generating a new long-read nanopore-based assembly with subsequent scaffolding to chromosome-level using previously published HiC data.FindingsThe use of nanopore-based long-read data sequenced on a MinION platform (Oxford Nanopore Technologies) allowed us to generate a baseline assembly of only 1,276 contigs with a contig N50 of 2.1 Mbp, and a total length of 441 Mbp. Scaffolding using previously published HiC data resulted in 109 scaffolds with a scaffold N50 of 20.7 Mbp. More than 99% of the assembly is comprised in 21 scaffolds. The assembly showed the presence of 95.8% complete BUSCO genes from the Actinopterygii dataset indicating a high quality of the assembly.ConclusionWe present an improved full chromosome-level assembly of the Siamese fighting fish generated during a university Master’s course. The use of ~35× long-read nanopore data drastically improved the baseline assembly in terms of continuity. We show that relatively in-expensive high-throughput sequencing technologies such as the long-read MinION sequencing platform can be used in educational settings allowing the students to gain practical skills in modern genomics and generate high quality results that benefit downstream research projects.

Download Full-text