Optimizing Information in Next-Generation-Sequencing (NGS) Reads for Improving De Novo Genome Assembly

Next-Generation-Sequencing is advantageous because of its much higher data throughput and much lower cost compared with the traditional Sanger method. However, NGS reads are shorter than Sanger reads, making de novo genome assembly very challenging. Because genome assembly is essential for all downstream biological studies, great efforts have been made to enhance the completeness of genome assembly, which requires the presence of long reads or long distance information. To improve de novo genome assembly, we develop a computational program, ARF-PE, to increase the length of Illumina reads. ARF-PE takes as input Illumina paired-end (PE) reads and recovers the original DNA fragments from which two ends the paired reads are obtained. On the PE data of four bacteria, ARF-PE recovered >87% of the DNA fragments and achieved >98% of perfect DNA fragment recovery. Using Velvet, SOAPdenovo, Newbler, and CABOG, we evaluated the benefits of recovered DNA fragments to genome assembly. For all four bacteria, the recovered DNA fragments increased the assembly contiguity. For example, the N50 lengths of the P. brasiliensis contigs assembled by SOAPdenovo and Newbler increased from 80,524 bp to 166,573 bp and from 80,655 bp to 193,388 bp, respectively. ARF-PE also increased assembly accuracy in many cases. On the PE data of two fungi and a human chromosome, ARF-PE doubled and tripled the N50 length. However, the assembly accuracies dropped, but still remained >91%. In general, ARF-PE can increase both assembly contiguity and accuracy for bacterial genomes. For complex eukaryotic genomes, ARF-PE is promising because it raises assembly contiguity. But future error correction is needed for ARF-PE to also increase the assembly accuracy. ARF-PE is freely available at http://140.116.235.124/~tliu/arf-pe/.     

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.     

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.     

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.     

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.     

Functional gene networks based on the gene neighborhood in metagenomes

The gene neighborhood in prokaryotic genomes has been effectively utilized in inferring co-functional networks in various organisms. Previously, such genomic context information has been sought among completely assembled prokaryotic genomes. Here, we present a method to infer functional gene networks according to the gene neighborhood in metagenome contigs, which are incompletely assembled genomic fragments. Given that the amount of metagenome sequence data has now surpassed that of completely assembled prokaryotic genomes in the public domain, we expect benefits of inferring networks by the metagenome-based gene neighborhood. We generated co-functional networks for diverse taxonomical species using metagenomics contigs derived from the human microbiome and the ocean microbiome. We found that the networks based on the metagenome gene neighborhood outperformed those based on 1748 completely assembled prokaryotic genomes. We also demonstrated that the metagenome-based gene neighborhood could predict genes related to virulence-associated phenotypes in a bacterial pathogen, indicating that metagenome-based functional links could be sufficiently predictive for some phenotypes of medical importance. Owing to the exponential growth of metagenome sequence data in public repositories, metagenome-based inference of co-functional networks will facilitate understanding of gene functions and pathways in diverse species.     

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.     

A haplome alignment and reference sequence of the highly polymorphic <Emphasis Type="Italic">Ciona savignyi</Emphasis> genome

The sequence of Ciona savignyi was determined using a whole-genome shotgun strategy, but a high degree of polymorphism resulted in a fractured assembly wherein allelic sequences from the same genomic region assembled separately. We designed a multistep strategy to generate a nonredundant reference sequence from the original assembly by reconstructing and aligning the two 'haplomes' (haploid genomes). In the resultant 174 megabase reference sequence, each locus is represented once, misassemblies are corrected, and contiguity and continuity are dramatically improved.     

A whole-genome assembly of the domestic cow, Bos taurus

Background

The genome of the domestic cow, Bos taurus, was sequenced using a mixture of hierarchical and whole-genome shotgun sequencing methods.

Results

We have assembled the 35 million sequence reads and applied a variety of assembly improvement techniques, creating an assembly of 2.86 billion base pairs that has multiple improvements over previous assemblies: it is more complete, covering more of the genome; thousands of gaps have been closed; many erroneous inversions, deletions, and translocations have been corrected; and thousands of single-nucleotide errors have been corrected. Our evaluation using independent metrics demonstrates that the resulting assembly is substantially more accurate and complete than alternative versions.

Conclusions

By using independent mapping data and conserved synteny between the cow and human genomes, we were able to construct an assembly with excellent large-scale contiguity in which a large majority (approximately 91%) of the genome has been placed onto the 30 B. taurus chromosomes. We constructed a new cow-human synteny map that expands upon previous maps. We also identified for the first time a portion of the B. taurus Y chromosome.     

Long-read sequence assembly: a technical evaluation in barley

Sequence assembly of large and repeat-rich plant genomes has been challenging, requiring substantial computational resources and often several complementary sequence assembly and genome mapping approaches. The recent development of fast and accurate long-read sequencing by circular consensus sequencing (CCS) on the PacBio platform may greatly increase the scope of plant pan-genome projects. Here, we compare current long-read sequencing platforms regarding their ability to rapidly generate contiguous sequence assemblies in pan-genome studies of barley (Hordeum vulgare). Most long-read assemblies are clearly superior to the current barley reference sequence based on short-reads. Assemblies derived from accurate long reads excel in most metrics, but the CCS approach was the most cost-effective strategy for assembling tens of barley genomes. A downsampling analysis indicated that 20-fold CCS coverage can yield very good sequence assemblies, while even five-fold CCS data may capture the complete sequence of most genes. We present an updated reference genome assembly for barley with near-complete representation of the repeat-rich intergenic space. Long-read assembly can underpin the construction of accurate and complete sequences of multiple genomes of a species to build pan-genome infrastructures in Triticeae crops and their wild relatives.

A greatly improved reference genome sequence of barley was assembled from accurate long reads.     

Assessment of urban microbiome assemblies with the help of targeted in silico gold standards

Background

Microbial communities play a crucial role in our environment and may influence human health tremendously. Despite being the place where human interaction is most abundant we still know little about the urban microbiome. This is highlighted by the large amount of unclassified DNA reads found in urban metagenome samples. The only in silico approach that allows us to find unknown species, is the assembly and classification of draft genomes from a metagenomic dataset. In this study we (1) investigate the applicability of an assembly and binning approach for urban metagenome datasets, and (2) develop a new method for the generation of in silico gold standards to better understand the specific challenges of such datasets and provide a guide in the selection of available software.

Results

We applied combinations of three assembly (Megahit, SPAdes and MetaSPAdes) and three binning tools (MaxBin, MetaBAT and CONCOCT) to whole genome shotgun datasets from the CAMDA 2017 Challenge. Complex in silico gold standards with a simulated bacterial fraction were generated for representative samples of each surface type and city. Using these gold standards, we found the combination of SPAdes and MetaBAT to be optimal for urban metagenome datasets by providing the best trade-off between the number of high-quality genome draft bins (MIMAG standards) retrieved, the least amount of misassemblies and contamination. The assembled draft genomes included known species like Propionibacterium acnes but also novel species according to respective ANI values.

Conclusions

In our work, we showed that, even for datasets with high diversity and low sequencing depth from urban environments, assembly and binning-based methods can provide high-quality genome drafts. Of vital importance to retrieve high-quality genome drafts is sequence depth but even more so a high proportion of the bacterial sequence fraction too achieve high coverage for bacterial genomes. In contrast to read-based methods relying on database knowledge, genome-centric methods as applied in this study can provide valuable information about unknown species and strains as well as functional contributions of single community members within a sample. Furthermore, we present a method for the generation of sample-specific highly complex in silico gold standards.

Reviewers

This article was reviewed by Craig Herbold, Serghei Mangul and Yana Bromberg.

     

Semi-Automatic In Silico Gap Closure Enabled De Novo Assembly of Two Dehalobacter Genomes from Metagenomic Data

Typically, the assembly and closure of a complete bacterial genome requires substantial additional effort spent in a wet lab for gap resolution and genome polishing. Assembly is further confounded by subspecies polymorphism when starting from metagenome sequence data. In this paper, we describe an in silico gap-resolution strategy that can substantially improve assembly. This strategy resolves assembly gaps in scaffolds using pre-assembled contigs, followed by verification with read mapping. It is capable of resolving assembly gaps caused by repetitive elements and subspecies polymorphisms. Using this strategy, we realized the de novo assembly of the first two Dehalobacter genomes from the metagenomes of two anaerobic mixed microbial cultures capable of reductive dechlorination of chlorinated ethanes and chloroform. Only four additional PCR reactions were required even though the initial assembly with Newbler v. 2.5 produced 101 contigs within 9 scaffolds belonging to two Dehalobacter strains. By applying this strategy to the re-assembly of a recently published genome of Bacteroides, we demonstrate its potential utility for other sequencing projects, both metagenomic and genomic.     

Rapid Genome Mapping in Nanochannel Arrays for Highly Complete and Accurate De Novo Sequence Assembly of the Complex Aegilops tauschii Genome

Next-generation sequencing (NGS) technologies have enabled high-throughput and low-cost generation of sequence data; however, de novo genome assembly remains a great challenge, particularly for large genomes. NGS short reads are often insufficient to create large contigs that span repeat sequences and to facilitate unambiguous assembly. Plant genomes are notorious for containing high quantities of repetitive elements, which combined with huge genome sizes, makes accurate assembly of these large and complex genomes intractable thus far. Using two-color genome mapping of tiling bacterial artificial chromosomes (BAC) clones on nanochannel arrays, we completed high-confidence assembly of a 2.1-Mb, highly repetitive region in the large and complex genome of Aegilops tauschii, the D-genome donor of hexaploid wheat (Triticum aestivum). Genome mapping is based on direct visualization of sequence motifs on single DNA molecules hundreds of kilobases in length. With the genome map as a scaffold, we anchored unplaced sequence contigs, validated the initial draft assembly, and resolved instances of misassembly, some involving contigs <2 kb long, to dramatically improve the assembly from 75% to 95% complete.     

Common Contaminants in Next-Generation Sequencing That Hinder Discovery of Low-Abundance Microbes

Unbiased high-throughput sequencing of whole metagenome shotgun DNA libraries is a promising new approach to identifying microbes in clinical specimens, which, unlike other techniques, is not limited to known sequences. Unlike most sequencing applications, it is highly sensitive to laboratory contaminants as these will appear to originate from the clinical specimens. To assess the extent and diversity of sequence contaminants, we aligned 57 “1000 Genomes Project” sequencing runs from six centers against the four largest NCBI BLAST databases, detecting reads of diverse contaminant species in all runs and identifying the most common of these contaminant genera (Bradyrhizobium) in assembled genomes from the NCBI Genome database. Many of these microorganisms have been reported as contaminants of ultrapure water systems. Studies aiming to identify novel microbes in clinical specimens will greatly benefit from not only preventive measures such as extensive UV irradiation of water and cross-validation using independent techniques, but also a concerted effort to sequence the complete genomes of common contaminants so that they may be subtracted computationally.     

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.     

The SAMBA tool uses long reads to improve the contiguity of genome assemblies

Third-generation sequencing technologies can generate very long reads with relatively high error rates. The lengths of the reads, which sometimes exceed one million bases, make them invaluable for resolving complex repeats that cannot be assembled using shorter reads. Many high-quality genome assemblies have already been produced, curated, and annotated using the previous generation of sequencing data, and full re-assembly of these genomes with long reads is not always practical or cost-effective. One strategy to upgrade existing assemblies is to generate additional coverage using long-read data, and add that to the previously assembled contigs. SAMBA is a tool that is designed to scaffold and gap-fill existing genome assemblies with additional long-read data, resulting in substantially greater contiguity. SAMBA is the only tool of its kind that also computes and fills in the sequence for all spanned gaps in the scaffolds, yielding much longer contigs. Here we compare SAMBA to several similar tools capable of re-scaffolding assemblies using long-read data, and we show that SAMBA yields better contiguity and introduces fewer errors than competing methods. SAMBA is open-source software that is distributed at https://github.com/alekseyzimin/masurca.     

Insight into the plasmid metagenome of wastewater treatment plant bacteria showing reduced susceptibility to antimicrobial drugs analysed by the 454-pyrosequencing technology

Wastewater treatment plants (WWTPs) are a reservoir for bacteria harbouring antibiotic resistance plasmids. To get a comprehensive overview on the plasmid metagenome of WWTP bacteria showing reduced susceptibility to certain antimicrobial drugs an ultrafast sequencing approach applying the 454-technology was carried out. One run on the GS 20 System yielded 346,427 reads with an average read length of 104 bases resulting in a total of 36,071,493 bases sequence data. The obtained plasmid metagenome was analysed and functionally annotated by means of the Sequence Analysis and Management System (SAMS) software package. Known plasmid genes could be identified within the WWTP plasmid metagenome data set by BLAST searches using the NCBI Plasmid Database. Most abundant hits represent genes involved in plasmid replication, stability, mobility and transposition. Mapping of plasmid metagenome reads to completely sequenced plasmids revealed that many sequences could be assigned to the cryptic pAsa plasmids previously identified in Aeromonas salmonicida subsp. salmonicida and to the accessory modules of the conjugative IncU resistance plasmid pFBAOT6 of Aeromonas punctata. Matches of sequence reads to antibiotic resistance genes indicate that plasmids from WWTP bacteria encode resistances to all major classes of antimicrobial drugs. Plasmid metagenome sequence reads could be assembled into 605 contigs with a minimum length of 500 bases. Contigs predominantly encode plasmid survival functions and transposition enzymes.