scholarly journals A chromosome-scale assembly of the sorghum genome using nanopore sequencing and optical mapping

2018 ◽  
Author(s):  
Stáphane Deschamps ◽  
Yun Zhang ◽  
Victor Llaca ◽  
Liang Ye ◽  
Gregory May ◽  
...  

The advent of long-read sequencing technologies has greatly facilitated assemblies of large eukaryotic genomes. In this paper, Oxford Nanopore sequences generated on a MinION sequencer were combined with BioNano Genomics Direct Label and Stain (DLS) optical maps to generate a chromosome-scale de novo assembly of the repeat-rich Sorghum bicolor Tx430 genome. The final hybrid assembly consists of 29 scaffolds, encompassing in most cases entire chromosome arms. It has a scaffold N50 value of 33.28Mbps and covers >90% of Sorghum bicolor expected genome length. A sequence accuracy of 99.67% was obtained in unique regions after aligning contigs against Illumina Tx430 data. Alignments showed that 99.4% of the 34,211 public gene models are present in the assembly, including 94.2% mapping end-to-end. Comparisons of the DLS optical maps against the public Sorghum Bicolor v3.0.1 BTx623 genome assembly suggest the presence of substantial genomic rearrangements whose origin remains to be determined.

Author(s):  
Arash Bayat ◽  
Hasindu Gamaarachchi ◽  
Nandan P. Deshpande ◽  
Marc R. Wilkins ◽  
Sri Parameswaran

Despite advances in algorithms and computational platforms, de-novo genome assembly remains a challenging process. Due to the constant innovation in sequencing technologies (Sanger, SOLiD, Illumina, 454, PacBio and Oxford Nanopore), genome assembly has evolved to respond to the changes in input data type. This paper includes a broad and comparative review of the most recent short-read, long-read and hybrid assembly techniques. In this review, we provide (1) an algorithmic description of the important processes in the workflow that introduces fundamental concepts and improvements; (2) a review of existing software that explains possible options for genome assembly; and (3) a comparison of the accuracy and the performance of existing methods executed on the same computer using the same processing capabilities and using the same set of real and synthetic datasets. Such evaluation allows a fair and precise comparison of accuracy in all aspects. As a result, this paper identifies both the strengths and weaknesses of each method. This comparative review is unique in providing a detailed comparison of a broad spectrum of cutting-edge algorithms and methods.


2017 ◽  
Author(s):  
Alex Di Genova ◽  
Gonzalo A. Ruz ◽  
Marie-France Sagot ◽  
Alejandro Maass

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).


2020 ◽  
Author(s):  
Xiao Du ◽  
Lili Li ◽  
Fan Liang ◽  
Sanyang Liu ◽  
Wenxin Zhang ◽  
...  

AbstractThe importance of structural variants (SVs) on phenotypes and human diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of those approaches, our work established an Asian reference material comprising identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8,938 SVs in an EBV immortalized B lymphocyte line, by integrating four alignment-based SV callers [from 109× PacBio continuous long read (CLR), 22× PacBio circular consensus sequencing (CCS) reads, 104× Oxford Nanopore long reads, and 114× optical mapping platform (Bionano)] and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR and Sanger sequencing, proofing the robustness of our SV calls. Combining trio-binning based haplotype assemblies, we established an SV benchmark for identification of false negatives and false positives by constructing the continuous high confident regions (CHCRs), which cover 1.46Gb and 6,882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical diagnosis.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang

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.


2020 ◽  
Author(s):  
Josip Marić ◽  
Krešimir Križanović ◽  
Sylvain Riondet ◽  
Niranjan Nagarajan ◽  
Mile Šikić

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.


F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 618 ◽  
Author(s):  
Michael Liem ◽  
Hans J. Jansen ◽  
Ron P. Dirks ◽  
Christiaan V. Henkel ◽  
G. Paul H. van Heusden ◽  
...  

Background: The introduction of the MinION sequencing device by Oxford Nanopore Technologies may greatly accelerate whole genome sequencing. Nanopore sequence data offers great potential for de novo assembly of complex genomes without using other technologies. Furthermore, Nanopore data combined with other sequencing technologies is highly useful for accurate annotation of all genes in the genome. In this manuscript we used nanopore sequencing as a tool to classify yeast strains. Methods: We compared various technical and software developments for the nanopore sequencing protocol, showing that the R9 chemistry is, as predicted, higher in quality than R7.3 chemistry. The R9 chemistry is an essential improvement for assembly of the extremely AT-rich mitochondrial genome. We double corrected assemblies from four different assemblers with PILON and assessed sequence correctness before and after PILON correction with a set of 290 Fungi genes using BUSCO. Results: In this study, we used this new technology to sequence and de novo assemble the genome of a recently isolated ethanologenic yeast strain, and compared the results with those obtained by classical Illumina short read sequencing. This strain was originally named Candida vartiovaarae (Torulopsis vartiovaarae) based on ribosomal RNA sequencing. We show that the assembly using nanopore data is much more contiguous than the assembly using short read data. We also compared various technical and software developments for the nanopore sequencing protocol, showing that nanopore-derived assemblies provide the highest contiguity. Conclusions: The mitochondrial and chromosomal genome sequences showed that our strain is clearly distinct from other yeast taxons and most closely related to published Cyberlindnera species. In conclusion, MinION-mediated long read sequencing can be used for high quality de novo assembly of new eukaryotic microbial genomes.


2018 ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang

AbstractLong read sequencing technologies such as Oxford Nanopore can greatly de-crease the complexity of de novo genome assembly and large structural variation iden-tification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. Many methods for resolving these errors require access to reference genomes, high-fidelity short reads, or reference genomes, which are often not available. De novo error correction modules are available, often as part of assembly tools, but large-scale errors still remain in resulting assemblies, motivating further innovation in this area. We developed a novel Convolutional Neu-ral Network (CNN) based method, called MiniScrub, for de novo identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments. MiniScrub first generates read-to-read alignments by MiniMap, then encodes the alignments into images, and finally builds CNN models to predict low-quality segments that could be scrubbed based on a customized quality cutoff. Applying MiniScrub to real world con-trol datasets under several different parameters, we show that it robustly improves read quality. Compared to raw reads, de novo genome assembly with scrubbed reads pro-duces many fewer mis-assemblies and large indel errors. 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


F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 618 ◽  
Author(s):  
Hans J. Jansen ◽  
Ron P. Dirks ◽  
Michael Liem ◽  
Christiaan V. Henkel ◽  
G. Paul H. van Heusden ◽  
...  

Background: The introduction of the MinIONTM sequencing device by Oxford Nanopore Technologies may greatly accelerate whole genome sequencing. It has been shown that the nanopore sequence data, in combination with other sequencing technologies, is highly useful for accurate annotation of all genes in the genome. However, it also offers great potential for de novo assembly of complex genomes without using other technologies. In this manuscript we used nanopore sequencing as a tool to classify yeast strains. Methods: We compared various technical and software developments for the nanopore sequencing protocol, showing that the R9 chemistry is, as predicted, higher in quality than R7.3 chemistry. The R9 chemistry is an essential improvement for assembly of the extremely AT-rich mitochondrial genome. Results: In this study, we used this new technology to sequence and de novo assemble the genome of a recently isolated ethanologenic yeast strain, and compared the results with those obtained by classical Illumina short read sequencing. This strain was originally named Candida vartiovaarae (Torulopsis vartiovaarae) based on ribosomal RNA sequencing. We show that the assembly using nanopore data is much more contiguous than the assembly using short read data. Conclusions: The mitochondrial and chromosomal genome sequences showed that our strain is clearly distinct from other yeast taxons and most closely related to published Cyberlindnera species. In conclusion, MinION-mediated long read sequencing can be used for high quality de novo assembly of new eukaryotic microbial genomes.


GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Valentine Murigneux ◽  
Subash Kumar Rai ◽  
Agnelo Furtado ◽  
Timothy J C Bruxner ◽  
Wei Tian ◽  
...  

Abstract Background Sequencing technologies have advanced to the point where it is possible to generate high-accuracy, haplotype-resolved, chromosome-scale assemblies. Several long-read sequencing technologies are available, and a growing number of algorithms have been developed to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology, as well as the most appropriate software for assembly and polishing. It is thus important to benchmark different approaches applied to the same sample. Results Here, we report a comparison of 3 long-read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION), and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of Pacific Biosciences and Nanopore reads. Results obtained from combining long-read technologies or short-read and long-read technologies are also presented. The assemblies were compared for contiguity, base accuracy, and completeness, as well as sequencing costs and DNA material requirements. Conclusions The 3 long-read technologies produced highly contiguous and complete genome assemblies of M. jansenii. At the time of sequencing, the cost associated with each method was significantly different, but continuous improvements in technologies have resulted in greater accuracy, increased throughput, and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.


2021 ◽  
Author(s):  
Aurélie Canaguier ◽  
Romane Guilbaud ◽  
Erwan Denis ◽  
Ghislaine Magdelenat ◽  
Caroline Belser ◽  
...  

AbstractBackgroundStructural Variations (SVs) are very diverse genomic rearrangements. In the past, their detection was restricted to cytological approaches, then to NGS read size and partitionned assemblies. Due to the current capabilities of technologies such as long read sequencing and optical mapping, larger SVs detection are becoming more and more accessible.This study proposes a comparison in SVs detection and characterization from long-read sequencing obtained with the MinION device developed by Oxford Nanopore Technologies and from optical mapping produced by the Saphyr device commercialized by Bionano Genomics. The genomes of the two Arabidopsis thaliana ecotypes Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1) were chosen to guide the use of one or the other technology.ResultsWe described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 on the public reference Col-0 TAIR10.1. After filtering, 1 184 and 591 Ler-1 SVs were retained from ONT and BioNano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations in both technologies. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted.ConclusionsStructural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference, most of detected SVs were found in same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the later being more efficient to characterize large SVs. Even if both technologies are obvious complementary approaches, ONT data appears to be more adapted to large scale populations study, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.


Sign in / Sign up

Export Citation Format

Share Document