Evaluation and Validation of Assembling Corrected PacBio Long Reads for Microbial Genome Completion via Hybrid Approaches

Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting that genome assembly could benefit from re-analyzing the available hybrid datasets that were not assembled in an optimal fashion.     

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing

Background

Whole genome sequence construction is becoming increasingly feasible because of advances in next generation sequencing (NGS), including increasing throughput and read length. By simply overlapping paired-end reads, we can obtain longer reads with higher accuracy, which can facilitate the assembly process. However, the influences of different library sizes and assembly methods on paired-end sequencing-based de novo assembly remain poorly understood.

Results

We used 250 bp Illumina Miseq paired-end reads of different library sizes generated from genomic DNA from Escherichia coli DH1 and Streptococcus parasanguinis FW213 to compare the assembly results of different library sizes and assembly approaches. Our data indicate that overlapping paired-end reads can increase read accuracy but sometimes cause insertion or deletions. Regarding genome assembly, merged reads only outcompete original paired-end reads when coverage depth is low, and larger libraries tend to yield better assembly results. These results imply that distance information is the most critical factor during assembly. Our results also indicate that when depth is sufficiently high, assembly from subsets can sometimes produce better results.

Conclusions

In summary, this study provides systematic evaluations of de novo assembly from paired end sequencing data. Among the assembly strategies, we find that overlapping paired-end reads is not always beneficial for bacteria genome assembly and should be avoided or used with caution especially for genomes containing high fraction of repetitive sequences. Because increasing numbers of projects aim at bacteria genome sequencing, our study provides valuable suggestions for the field of genomic sequence construction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1859-8) contains supplementary material, which is available to authorized users.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.     

Read Length and Repeat Resolution: Exploring Prokaryote Genomes Using Next-Generation Sequencing Technologies

Background

There are a growing number of next-generation sequencing technologies. At present, the most cost-effective options also produce the shortest reads. However, even for prokaryotes, there is uncertainty concerning the utility of these technologies for the de novo assembly of complete genomes. This reflects an expectation that short reads will be unable to resolve small, but presumably abundant, repeats.

Methodology/Principal Findings

Using a simple model of repeat assembly, we develop and test a technique that, for any read length, can estimate the occurrence of unresolvable repeats in a genome, and thus predict the number of gaps that would need to be closed to produce a complete sequence. We apply this technique to 818 prokaryote genome sequences. This provides a quantitative assessment of the relative performance of various lengths. Notably, unpaired reads of only 150nt can reconstruct approximately 50% of the analysed genomes with fewer than 96 repeat-induced gaps. Nonetheless, there is considerable variation amongst prokaryotes. Some genomes can be assembled to near contiguity using very short reads while others require much longer reads.

Conclusions

Given the diversity of prokaryote genomes, a sequencing strategy should be tailored to the organism under study. Our results will provide researchers with a practical resource to guide the selection of the appropriate read length.     

Rapid hybrid de novo assembly of a microbial genome using only short reads: Corynebacterium pseudotuberculosis I19 as a case study

Due to the advent of the so-called Next-Generation Sequencing (NGS) technologies the amount of monetary and temporal resources for whole-genome sequencing has been reduced by several orders of magnitude. Sequence reads can be assembled either by anchoring them directly onto an available reference genome (classical reference assembly), or can be concatenated by overlap (de novo assembly). The latter strategy is preferable because it tends to maintain the architecture of the genome sequence the however, depending on the NGS platform used, the shortness of read lengths cause tremendous problems the in the subsequent genome assembly phase, impeding closing of the entire genome sequence. To address the problem, we developed a multi-pronged hybrid de novo strategy combining De Bruijn graph and Overlap-Layout-Consensus methods, which was used to assemble from short reads the entire genome of Corynebacterium pseudotuberculosis strain I19, a bacterium with immense importance in veterinary medicine that causes Caseous Lymphadenitis in ruminants, principally ovines and caprines. Briefly, contigs were assembled de novo from the short reads and were only oriented using a reference genome by anchoring. Remaining gaps were closed using iterative anchoring of short reads by craning to gap flanks. Finally, we compare the genome sequence assembled using our hybrid strategy to a classical reference assembly using the same data as input and show that with the availability of a reference genome, it pays off to use the hybrid de novo strategy, rather than a classical reference assembly, because more genome sequences are preserved using the former.     

A comprehensive evaluation of assembly scaffolding tools

Background

Genome assembly is typically a two-stage process: contig assembly followed by the use of paired sequencing reads to join contigs into scaffolds. Scaffolds are usually the focus of reported assembly statistics; longer scaffolds greatly facilitate the use of genome sequences in downstream analyses, and it is appealing to present larger numbers as metrics of assembly performance. However, scaffolds are highly prone to errors, especially when generated using short reads, which can directly result in inflated assembly statistics.

Results

Here we provide the first independent evaluation of scaffolding tools for second-generation sequencing data. We find large variations in the quality of results depending on the tool and dataset used. Even extremely simple test cases of perfect input, constructed to elucidate the behaviour of each algorithm, produced some surprising results. We further dissect the performance of the scaffolders using real and simulated sequencing data derived from the genomes of Staphylococcus aureus, Rhodobacter sphaeroides, Plasmodium falciparum and Homo sapiens. The results from simulated data are of high quality, with several of the tools producing perfect output. However, at least 10% of joins remains unidentified when using real data.

Conclusions

The scaffolders vary in their usability, speed and number of correct and missed joins made between contigs. Results from real data highlight opportunities for further improvements of the tools. Overall, SGA, SOPRA and SSPACE generally outperform the other tools on our datasets. However, the quality of the results is highly dependent on the read mapper and genome complexity.     

SMRT sequencing only de novo assembly of the sugar beet (Beta vulgaris) chloroplast genome

Background

Third generation sequencing methods, like SMRT (Single Molecule, Real-Time) sequencing developed by Pacific Biosciences, offer much longer read length in comparison to Next Generation Sequencing (NGS) methods. Hence, they are well suited for de novo- or re-sequencing projects. Sequences generated for these purposes will not only contain reads originating from the nuclear genome, but also a significant amount of reads originating from the organelles of the target organism. These reads are usually discarded but they can also be used for an assembly of organellar replicons. The long read length supports resolution of repetitive regions and repeats within the organelles genome which might be problematic when just using short read data. Additionally, SMRT sequencing is less influenced by GC rich areas and by long stretches of the same base.

Results

We describe a workflow for a de novo assembly of the sugar beet (Beta vulgaris ssp. vulgaris) chloroplast genome sequence only based on data originating from a SMRT sequencing dataset targeted on its nuclear genome. We show that the data obtained from such an experiment are sufficient to create a high quality assembly with a higher reliability than assemblies derived from e.g. Illumina reads only. The chloroplast genome is especially challenging for de novo assembling as it contains two large inverted repeat (IR) regions. We also describe some limitations that still apply even though long reads are used for the assembly.

Conclusions

SMRT sequencing reads extracted from a dataset created for nuclear genome (re)sequencing can be used to obtain a high quality de novo assembly of the chloroplast of the sequenced organism. Even with a relatively small overall coverage for the nuclear genome it is possible to collect more than enough reads to generate a high quality assembly that outperforms short read based assemblies. However, even with long reads it is not always possible to clarify the order of elements of a chloroplast genome sequence reliantly which we could demonstrate with Fosmid End Sequences (FES) generated with Sanger technology. Nevertheless, this limitation also applies to short read sequencing data but is reached in this case at a much earlier stage during finishing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0726-6) contains supplementary material, which is available to authorized users.     

ISMapper: identifying transposase insertion sites in bacterial genomes from short read sequence data

Background

Insertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, directly from paired-end short read data.

Results

ISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 97 % of known IS insertions in the analysis of simulated reads, and 98 % in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was able to correctly detect insertions for average genome-wide read depths >20x, although read depths >50x were required to obtain confident calls that were highly-supported by evidence from reads. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-specific insertions and multiple insertion hotspots.

Conclusions

ISMapper provides a rapid and robust method for identifying IS insertion sites directly from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.     

MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads

An important step in ‘metagenomics’ analysis is the assembly of multiple genomes from mixed sequence reads of multiple species in a microbial community. Most conventional pipelines use a single-genome assembler with carefully optimized parameters. A limitation of a single-genome assembler for de novo metagenome assembly is that sequences of highly abundant species are likely misidentified as repeats in a single genome, resulting in a number of small fragmented scaffolds. We extended a single-genome assembler for short reads, known as ‘Velvet’, to metagenome assembly, which we called ‘MetaVelvet’, for mixed short reads of multiple species. Our fundamental concept was to first decompose a de Bruijn graph constructed from mixed short reads into individual sub-graphs, and second, to build scaffolds based on each decomposed de Bruijn sub-graph as an isolate species genome. We made use of two features, the coverage (abundance) difference and graph connectivity, for the decomposition of the de Bruijn graph. For simulated datasets, MetaVelvet succeeded in generating significantly higher N50 scores than any single-genome assemblers. MetaVelvet also reconstructed relatively low-coverage genome sequences as scaffolds. On real datasets of human gut microbial read data, MetaVelvet produced longer scaffolds and increased the number of predicted genes.     

Microarray meta-analysis database (M2DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

Background

With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and apply it to de novo sequencing of new organisms. As an example, this paper demonstrates how such extra information can be used to improve de novo assemblies by augmenting the overlapping step. Finding all pairs of overlapping reads is a key task in many genome assemblers, and to this end, highly efficient algorithms have been developed to find alignments in large collections of sequences. It is well known that due to repeated sequences, many aligned pairs of reads nevertheless do not overlap. But no overlapping algorithm to date takes a rigorous approach to separating aligned but non-overlapping read pairs from true overlaps.

Results

We present an approach that extends the Minimus assembler by a data driven step to classify overlaps as true or false prior to contig construction. We trained several different classification models within the Weka framework using various statistics derived from overlaps of reads available from prior sequencing projects. These statistics included percent mismatch and k-mer frequencies within the overlaps as well as a comparative genomics score derived from mapping reads to multiple reference genomes. We show that in real whole-genome sequencing data from the E. coli and S. aureus genomes, by providing a curated set of overlaps to the contigging phase of the assembler, we nearly doubled the median contig length (N50) without sacrificing coverage of the genome or increasing the number of mis-assemblies.

Conclusions

Machine learning methods that use comparative and non-comparative features to classify overlaps as true or false can be used to improve the quality of a sequence assembly.     

Efficient and accurate whole genome assembly and methylome profiling of E. coli

Background

With the price of next generation sequencing steadily decreasing, bacterial genome assembly is now accessible to a wide range of researchers. It is therefore necessary to understand the best methods for generating a genome assembly, specifically, which combination of sequencing and bioinformatics strategies result in the most accurate assemblies. Here, we sequence three E. coli strains on the Illumina MiSeq, Life Technologies Ion Torrent PGM, and Pacific Biosciences RS. We then perform genome assemblies on all three datasets alone or in combination to determine the best methods for the assembly of bacterial genomes.

Results

Three E. coli strains – BL21(DE3), Bal225, and DH5α – were sequenced to a depth of 100× on the MiSeq and Ion Torrent machines and to at least 125× on the PacBio RS. Four assembly methods were examined and compared. The previously published BL21(DE3) genome [GenBank:{"type":"entrez-nucleotide","attrs":{"text":"AM946981.2","term_id":"313848522","term_text":"AM946981.2"}}AM946981.2], allowed us to evaluate the accuracy of each of the BL21(DE3) assemblies. BL21(DE3) PacBio-only assemblies resulted in a 90% reduction in contigs versus short read only assemblies, while N50 numbers increased by over 7-fold. Strikingly, the number of SNPs in PacBio-only assemblies were less than half that seen with short read assemblies (~20 SNPs vs. ~50 SNPs) and indels also saw dramatic reductions (~2 indel >5 bp in PacBio-only assemblies vs. ~12 for short-read only assemblies). Assemblies that used a mixture of PacBio and short read data generally fell in between these two extremes. Use of PacBio sequencing reads also allowed us to call covalent base modifications for the three strains. Each of the strains used here had a known covalent base modification genotype, which was confirmed by PacBio sequencing.

Conclusion

Using data generated solely from the Pacific Biosciences RS, we were able to generate the most complete and accurate de novo assemblies of E. coli strains. We found that the addition of other sequencing technology data offered no improvements over use of PacBio data alone. In addition, the sequencing data from the PacBio RS allowed for sensitive and specific calling of covalent base modifications.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-675) contains supplementary material, which is available to authorized users.     

Establishment of an eHAP1 human haploid cell line hybrid reference genome assembled from short and long reads

Haploid cell lines are a valuable research tool with broad applicability for genetic assays. As such the fully haploid human cell line, eHAP1, has been used in a wide array of studies. However, the absence of a corresponding reference genome sequence for this cell line has limited the potential for more widespread applications to experiments dependent on available sequence, like capture-clone methodologies. We generated ~15× coverage Nanopore long reads from ten GridION flowcells and utilized this data to assemble a de novo draft genome using minimap and miniasm and subsequently polished using Racon. This assembly was further polished using previously generated, low-coverage, Illumina short reads with Pilon and ntEdit. This resulted in a hybrid eHAP1 assembly with >90% complete BUSCO scores. We further assessed the eHAP1 long read data for structural variants using Sniffles and identify a variety of rearrangements, including a previously established Philadelphia translocation. Finally, we demonstrate how some of these variants overlap open chromatin regions, potentially impacting regulatory regions. By integrating both long and short reads, we generated a high-quality reference assembly for eHAP1 cells. The union of long and short reads demonstrates the utility in combining sequencing platforms to generate a high-quality reference genome de novo solely from low coverage data. We expect the resulting eHAP1 genome assembly to provide a useful resource to enable novel experimental applications in this important model cell line.     

Polishing the Oxford Nanopore long-read assemblies of bacterial pathogens with Illumina short reads to improve genomic analyses

Oxford Nanopore sequencing has been widely used to achieve complete genomes of bacterial pathogens. However, the error rates of Oxford Nanopore long reads are high. Various polishing algorithms using Illumina short reads to correct the errors in Oxford Nanopore long-read assemblies have been developed. The impact of polishing the Oxford Nanopore long-read assemblies of bacterial pathogens with Illumina short reads on improving genomic analyses was evaluated using both simulated and real reads. Ten species (10 strains) were selected for simulated reads, while real reads were tested on 11 species (11 strains). Oxford Nanopore long reads were assembled with Unicycler to produce a draft assembly, followed by three rounds of polishing with Illumina short reads using two polishing tools, Pilon and NextPolish. One round of NextPolish polishing generated genome completeness and accuracy parameters similar to the reference genomes, whereas two or three rounds of Pilon polishing were needed, though contiguity remained unchanged after polishing. The polished assemblies of Escherichia coli O157:H7, Salmonella Typhimurium, and Cronobacter sakazakii with simulated reads did not provide accurate plasmid identifications. One round of NextPolish polishing was needed for accurately identifying plasmids in Staphylococcus aureus and E. coli O26:H11 with real reads, whereas one and two rounds of Pilon polishing were necessary for these two strains, respectively. Polishing failed to provide an accurate antimicrobial resistance (AMR) genotype for S. aureus with real reads. One round of polishing recovered an accurate AMR genotype for Klebsiella pneumoniae with real reads. The reference genome and draft assembly of Citrobacter braakii with real reads differed, which carried blaCMY-83 and fosA6, respectively, while both genes were present after one round of polishing. However, polishing did not improve the assembly of E. coli O26:H11 with real reads to achieve numbers of virulence genes similar to the reference genome. The draft and polished assemblies showed a phylogenetic tree topology comparable with the reference genomes. For multilocus sequence typing and pan-genome analyses, one round of NextPolish polishing was sufficient to obtain accurate results, while two or three rounds of Pilon polishing were needed. Overall, NextPolish outperformed Pilon for polishing the Oxford Nanopore long-read assemblies of bacterial pathogens, though both polishing strategies improved genomic analyses compared to the draft assemblies.     

Protein Domain Analysis of Genomic Sequence Data Reveals Regulation of LRR Related Domains in Plant Transpiration in Ficus

Predicting protein domains is essential for understanding a protein’s function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.     

An improved genome reference for the African cichlid,Metriaclima zebra

Background

Problems associated with using draft genome assemblies are well documented and have become more pronounced with the use of short read data for de novo genome assembly. We set out to improve the draft genome assembly of the African cichlid fish, Metriaclima zebra, using a set of Pacific Biosciences SMRT sequencing reads corresponding to 16.5× coverage of the genome. Here we characterize the improvements that these long reads allowed us to make to the state-of-the-art draft genome previously assembled from short read data.

Results

Our new assembly closed 68 % of the existing gaps and added 90.6Mbp of new non-gap sequence to the existing draft assembly of M. zebra. Comparison of the new assembly to the sequence of several bacterial artificial chromosome clones confirmed the accuracy of the new assembly. The closure of sequence gaps revealed thousands of new exons, allowing significant improvement in gene models. We corrected one known misassembly, and identified and fixed other likely misassemblies. 63.5 Mbp (70 %) of the new sequence was classified as repetitive and the new sequence allowed for the assembly of many more transposable elements.

Conclusions

Our improvements to the M. zebra draft genome suggest that a reasonable investment in long reads could greatly improve many comparable vertebrate draft genome assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1930-5) contains supplementary material, which is available to authorized users.     

Hybrid De Novo Genome Assembly Using MiSeq and SOLiD Short Read Data

A hybrid de novo assembly pipeline was constructed to utilize both MiSeq and SOLiD short read data in combination in the assembly. The short read data were converted to a standard format of the pipeline, and were supplied to the pipeline components such as ABySS and SOAPdenovo. The assembly pipeline proceeded through several stages, and either MiSeq paired-end data, SOLiD mate-paired data, or both of them could be specified as input data at each stage separately. The pipeline was examined on the filamentous fungus Aspergillus oryzae RIB40, by aligning the assembly results against the reference sequences. Using both the MiSeq and the SOLiD data in the hybrid assembly, the alignment length was improved by a factor of 3 to 8, compared with the assemblies using either one of the data types. The number of the reproduced gene cluster regions encoding secondary metabolite biosyntheses (SMB) was also improved by the hybrid assemblies. These results imply that the MiSeq data with long read length are essential to construct accurate nucleotide sequences, while the SOLiD mate-paired reads with long insertion length enhance long-range arrangements of the sequences. The pipeline was also tested on the actinomycete Streptomyces avermitilis MA-4680, whose gene is known to have high-GC content. Although the quality of the SOLiD reads was too low to perform any meaningful assemblies by themselves, the alignment length to the reference was improved by a factor of 2, compared with the assembly using only the MiSeq data.