MetaVelvet

BackgroundNext-generation sequencing (NGS) has greatly facilitated metagenomic analysis but also raised new challenges for metagenomic DNA sequence assembly, owing to its high-throughput nature and extremely short reads generated by sequencers such as Illumina. To date, how to generate a high-quality draft assembly for metagenomic sequencing projects has not been fully addressed.ResultsWe conducted a comprehensive assessment on state-of-the-art de novo assemblers and revealed that the performance of each assembler depends critically on the sequencing depth. To address this problem, we developed a pipeline named InteMAP to integrate three assemblers, ABySS, IDBA-UD and CABOG, which were found to complement each other in assembling metagenomic sequences. Making a decision of which assembling approaches to use according to the sequencing coverage estimation algorithm for each short read, the pipeline presents an automatic platform suitable to assemble real metagenomic NGS data with uneven coverage distribution of sequencing depth. By comparing the performance of InteMAP with current assemblers on both synthetic and real NGS metagenomic data, we demonstrated that InteMAP achieves better performance with a longer total contig length and higher contiguity, and contains more genes than others.ConclusionsWe developed a de novo pipeline, named InteMAP, that integrates existing tools for metagenomics assembly. The pipeline outperforms previous assembly methods on metagenomic assembly by providing a longer total contig length, a higher contiguity and covering more genes. InteMAP, therefore, could potentially be a useful tool for the research community of metagenomics.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0686-x) contains supplementary material, which is available to authorized users.

Detection of KMT2A Partial Tandem Duplication in Myeloid Samples By Pacbio® Long Read Sequencing

This paper deals with the analysis of the throughput performance of various logical topologies for Multihop Networks. In particular, ShuffleNets, De Bruijn graphs and Kautz graphs are analyzed. For the comparison, routing algorithms adopting minimum path length are considered. A hot-spot traffic scenario is adopted, modeling the presence of a centralized network resource to which a quota of the internal traffic is directed or originated from. The analysis is carried out by varying the traffic unbalance degree, from a uniform traffic distribution to a completely unbalanced one (all the traffic is concentrated in the hot-spot node). For ShuffleNets, simple analytical expressions of the actual throughput limits are utilized. In the case of De Bruijn and Kautz graphs, instead, a lower bound of the throughput is utilized, which coincides with the actual throughput in a wide range of values of the network size. The results obtained show that Shuffle and Kautz graphs always outperform De Bruijn topologies. Moreover, ShuffleNets present a further advantage on the other topologies; in fact, since the nodes are topologically equivalent, the placement of the hot-spot node does not affect the throughput performance.

Transferable linezolid resistance due to optrA, poxtA, cfr and cfr-like genes is increasingly detected in enterococci associated with animals and humans globally. We aimed to characterize the genetic environment of optrA in linezolid-resistant Enterococcus faecalis isolates from Scotland. Six linezolid-resistant E. faecalis isolated from urogenital samples were confirmed to carry the optrA gene by PCR. Short read (Illumina) sequencing showed the isolates were genetically distinct (>13900 core SNPs) and belonged to different MLST sequence types. Plasmid contents were examined using hybrid assembly of short and long read (Oxford Nanopore MinION) sequencing technologies. The optrA gene was located on distinct plasmids in each isolate, suggesting that transfer of a single plasmid did not contribute to optrA dissemination in this collection. pTM6294-2, BX5936-1 and pWE0438-1 were similar to optrA-positive plasmids from China and Japan, while the remaining three plasmids had limited similarity to other published examples. We identified the novel Tn6993 transposon in pWE0254-1 carrying linezolid (optrA), macrolide (ermB) and spectinomycin [ANT(9)-Ia] resistance genes. OptrA amino acid sequences differed by 0–20 residues. We report multiple variants of optrA on distinct plasmids in diverse strains of E. faecalis . It is important to identify the selection pressures driving the emergence and maintenance of resistance against linezolid to retain the clinical utility of this antibiotic.

The metagenomic paradigm allows for an understanding of the metabolic and functional potential of microbes in a community via a study of their proteins. The substrate for protein identification is either the set of individual nucleotide reads generated from metagenomic samples or the set of contig sequences produced by assembling these reads. However, a read-based strategy using reads generated by next-generation sequencing (NGS) technologies, results in an overwhelming majority of partial-length protein predictions. A nucleotide assembly-based strategy does not fare much better, as metagenomic assemblies are typically fragmented and also leave a large fraction of reads unassembled. Here, we present a method for reconstructing complete protein sequences directly from NGS metagenomic data. Our framework is based on a novel short peptide assembler (SPA) that assembles protein sequences from their constituent peptide fragments identified on short reads. The SPA algorithm is based on informed traversals of a de Bruijn graph, defined on an amino acid alphabet, to identify probable paths that correspond to proteins. Using large simulated and real metagenomic data sets, we show that our method outperforms the alternate approach of identifying genes on nucleotide sequence assemblies and generates longer protein sequences that can be more effectively analysed.

Here, we apply an alignment-free method (kPal) that leverages on k-mer frequencies to classify reads within a single long read metagenomic dataset. In addition to a series of simulated metagenomic datasets, we generated sequencing data from a bioreactor microbiome using the PacBio RSII single-molecule real-time sequencing platform. We show that distances obtained after the comparison of k-mer profiles can reveal relationships between reads within a single metagenome, leading to a clustering per species.

Metagenomics enables direct investigation of the gene content and potential functions of gut bacteria without isolation and culture. However, metagenome-assembled genomes are often incomplete and have low contiguity due to challenges in assembling repeated genomic elements. Long-read sequencing approaches have successfully yielded circular bacterial genomes directly from metagenomes, but these approaches require high DNA input and can have high error rates. Illumina has recently launched the Illumina Complete Long Read (ICLR) assay, a new approach for generating kilobase-scale reads with low DNA input requirements and high accuracy. Here, we evaluate the performance of ICLR sequencing for gut metagenomics for the first time. We sequenced a microbial mock community and 10 human gut microbiome samples with standard, shotgun 2 × 150 paired-end sequencing, ICLR sequencing, and nanopore long-read sequencing and compared performance in read lengths, assembly contiguity, and bin quality. We find that ICLR human metagenomic assemblies have higher N50 (119.5 ± 24.8 kilobases) than short read assemblies (9.9 ± 4.5 kilobases; P = 0.002), and comparable N50 to nanopore assemblies (91.0 ± 43.8 kilobases; P = 0.32). Additionally, we find that ICLR draft microbial genomes are more complete (94.0% ± 20.6%) than nanopore draft genomes (85.9% ± 23.0%; P ≤ 0.001), and that nanopore draft genomes have truncated gene lengths (924.6 ± 114.7 base pairs) relative to ICLR genomes (954.6 ± 71.5 base pairs; P ≤ 0.001). Overall, we find that ICLR sequencing is a promising method for the accurate assembly of microbial genomes from gut metagenomes.IMPORTANCEMetagenomic sequencing allows scientists to directly measure the genome content and structure of microbes residing in complex microbial communities. Traditional short-read metagenomic sequencing methods often yield fragmented genomes, whereas advanced long-read sequencing methods improve genome assembly quality but often suffer from high error rates and are logistically limited due to high input requirements. A new method, the Illumina Complete Long Read (ICLR) assay, is capable of generating highly accurate kilobase-scale sequencing reads with minimal input material. To evaluate the utility of ICLR in metagenomic contexts, we applied short-read, long-read, and ICLR methods to simple and complex microbial communities. We found that ICLR outperforms short-read methods and yields comparable metagenomic assemblies to standard long-read approaches while requiring less input material. Overall, ICLR represents an additional option for assembling complete genomes from complex metagenomes.

MotivationAlmost all de novo short-read genome and transcriptome assemblers start by building a representation of the de Bruijn Graph of the reads they are given as input. Even when other approaches are used for subsequent assembly (e.g. when one is using ‘long read’ technologies like those offered by PacBio or Oxford Nanopore), efficient k-mer processing is still crucial for accurate assembly, and state-of-the-art long-read error-correction methods use de Bruijn Graphs. Because of the centrality of de Bruijn Graphs, researchers have proposed numerous methods for representing de Bruijn Graphs compactly. Some of these proposals sacrifice accuracy to save space. Further, none of these methods store abundance information, i.e. the number of times that each k-mer occurs, which is key in transcriptome assemblers.ResultsWe present a method for compactly representing the weighted de Bruijn Graph (i.e. with abundance information) with essentially no errors. Our representation yields zero errors while increasing the space requirements by less than 18–28% compared to the approximate de Bruijn graph representation in Squeakr. Our technique is based on a simple invariant that all weighted de Bruijn Graphs must satisfy, and hence is likely to be of general interest and applicable in most weighted de Bruijn Graph-based systems.Availability and implementation https://github.com/splatlab/debgr.Supplementary information Supplementary data are available at Bioinformatics online.

De novo assembly of metagenome samples is a common approach to the study of microbial communities. Current metagenome assemblers developed for short sequence reads or noisy long reads were not optimized for accurate long reads. We thus developed hifiasm-meta, a metagenome assembler that exploits the high accuracy of recent data. Evaluated on seven empirical datasets, hifiasm-meta reconstructed tens to hundreds of complete circular bacterial genomes per dataset, consistently outperforming other metagenome assemblers.

The advances of next-generation sequencing technology have facilitated metagenomics research that attempts to determine directly the whole collection of genetic material within an environmental sample (i.e. the metagenome). Identification of genes directly from short reads has become an important yet challenging problem in annotating metagenomes, since the assembly of metagenomes is often not available. Gene predictors developed for whole genomes (e.g. Glimmer) and recently developed for metagenomic sequences (e.g. MetaGene) show a significant decrease in performance as the sequencing error rates increase, or as reads get shorter. We have developed a novel gene prediction method FragGeneScan, which combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads. The performance of FragGeneScan was comparable to Glimmer and MetaGene for complete genomes. But for short reads, FragGeneScan consistently outperformed MetaGene (accuracy improved ∼62% for reads of 400 bases with 1% sequencing errors, and ∼18% for short reads of 100 bases that are error free). When applied to metagenomes, FragGeneScan recovered substantially more genes than MetaGene predicted (>90% of the genes identified by homology search), and many novel genes with no homologs in current protein sequence database.

Repetitive sequences and genomic variations mediated by repetitive sequences remain a barrier to our understanding of the function and dynamics of the human genome. Only recently have high throughput short and long reads sequencing provided an opportunity to overcome these challenges. In this thesis, I investigate the distribution, evolution and polymorphism of two types of repeats: subtelomeric and inverted repeats. I also investigate two distinct aspects of genomic mutations related to these repetitive sequences: inversion polymorphisms, and structural variation in chromosome subtelomeric regions.In the first chapter, I provide an overview of our current knowledge, as well as gaps in our understanding of the structure of the human genome. I also provide an overview of the sequencing technologies I will use in this thesis.In the second chapter, I show the performance of inversion detection by short read sequencing. Next, I develop and apply an approach for using long read nanopore sequencing data to detect inversion polymorphism. I show that using long reads it is possible to detect inversions mediated by long inverted repeats which are invisible to paired-end short read sequencing.In the third chapter, I investigate the distribution of inverted repeats in the human genome. I combined this information with existing maps of inversion polymorphisms to investigate the role of inverted repeats in mediating formation of inversions.In the fourth chapter, I apply BioNano data to anchor and extend chromosome ends. This analysis uncovers a surprising level of polymorphism in human chromosome end extension, suggesting an ongoing process of terminal loss and extension. I confirm these chromosome end extension using both nanopore and pacbio long read sequence data.In the fifth chapter, I investigate the evolution of chromosome termini. I identify ancient chromosome terminal ends by investigation of subtelomeric interstitial telomere sequences across multiple mammalian species. This analysis provides an estimate of the rate at which chromosome ends have extended.

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

Metagenomes present assembly challenges, when assembling multiple genomes from mixed reads of multiple species. An assembler for single genomes can’t adapt well when applied in this case. A metagenomic assembler, Genovo, is a de novo assembler for metagenomes under a generative probabilistic model. Genovo assembles all reads without discarding any reads in a preprocessing step, and is therefore able to extract more information from metagenomic data and, in principle, generate better assembly results. Paired end sequencing is currently widely-used yet Genovo was designed for 454 single end reads. In this research, we attempted to extend Genovo by incorporating paired-end information, named Xgenovo, so that it generates higher quality assemblies with paired end reads.First, we extended Genovo by adding a bonus parameter in the Chinese Restaurant Process used to get prior accounts for the unknown number of genomes in the sample. This bonus parameter intends for a pair of reads to be in the same contig and as an effort to solve chimera contig case. Second, we modified the sampling process of the location of a read in a contig. We used relative distance for the number of trials in the symmetric geometric distribution instead of using distance between the offset and the center of contig used in Genovo. Using this relative distance, a read sampled in the appropriate location has higher probability. Therefore a read will be mapped in the correct location.Results of extensive experiments on simulated metagenomic datasets from simple to complex with species coverage setting following uniform and lognormal distribution showed that Xgenovo can be superior to the original Genovo and the recently proposed metagenome assembler for 454 reads, MAP. Xgenovo successfully generated longer N50 than Genovo and MAP while maintaining the assembly quality even for very complex metagenomic datasets consisting of 115 species. Xgenovo also demonstrated the potential to decrease the computational cost. This means that our strategy worked well. The software and all simulated datasets are publicly available online at http://xgenovo.dna.bio.keio.ac.jp.

The intrinsic properties of the employed graphs in designing Peer-to-Peer overlay networks are crucial for the performance of the deployed Peer-to-Peer systems. Several structured topologies have been proposed based on meshes, enhanced rings, redundant tree structures, etc. Among them, de Bruijn graphs are promising alternatives since they provide some crucial asymptotically optimal characteristics. In this paper, we discuss the necessary algorithms and protocol messages to develop efficiently the employed routing procedure of Omicron, which is a hybrid overlay network based on de Bruijn graphs enriched with clustering and role specialization mechanisms. Enhancements of the original de Bruijn structure are advised to cope with the intrinsic issue of uneven distribution of the routing workload. The developed system is evaluated and compared with Chord, which is used as the reference point. The superiority of de Bruijn based overlay networks with respect to scalability is quantitatively demonstrated using simulation experiments. Further, the ability of the two systems to exploit the underlying network is investigated.

The author provides an overview of various key features of De Bruijn graph-based VLSI architectures. The advantages of De Bruijn architectures over such other architectures as cube and shuffle-exchange are discussed. Important differences between De Bruijn interconnects and others are also described. The evolution of the De Bruijn interconnect is described. The FFT architecture and the Viterbi decoder for convolutional codes are examined in detail. The issues of routing and fault tolerance are addressed. >