Draft genome of the scabies mite

Background

The disease scabies, caused by the ectoparasitic mite, Sarcoptes scabiei, causes significant morbidity in humans and other mammals worldwide. However, there is limited data available regarding the molecular basis of host specificity and host-parasite interactions. Therefore, we sought to produce a draft genome for S. scabiei and use this to identify molecular markers that will be useful for phylogenetic population studies and to identify candidate protein-coding genes that are critical to the unique biology of the parasite.

Methods

S. scabiei var. canis DNA was isolated from living mites and sequenced to ultra-deep coverage using paired-end technology. Sequence reads were assembled into gapped contigs using de Bruijn graph based algorithms. The assembled genome was examined for repetitive elements and gene annotation was performed using ab initio, and homology-based methods.

Results

The draft genome assembly was about 56.2 Mb and included a mitochondrial genome contig. The predicted proteome contained 10,644 proteins, ~67 % of which appear to have clear orthologs in other species. The genome also contained more than 140,000 simple sequence repeat loci that may be useful for population-level studies. The mitochondrial genome contained 13 protein coding loci and 20 transfer RNAs. Hundreds of candidate salivary gland protein genes were identified by comparing the scabies mite predicted proteome with sialoproteins and transcripts identified in ticks and other hematophagous arthropods. These include serpins, ferritins, reprolysins, apyrases and new members of the macrophage migration inhibitory factor (MIF) gene family. Numerous other genes coding for salivary proteins, metabolic enzymes, structural proteins, proteins that are potentially immune modulating, and vaccine candidates were identified. The genes encoding cysteine and serine protease paralogs as well as mu-type glutathione S-transferases are represented by gene clusters. S. scabiei possessed homologs for most of the 33 dust mite allergens.

Conclusion

The draft genome is useful for advancing our understanding of the host-parasite interaction, the biology of the mite and its phylogenetic relationship to other Acari. The identification of antigen-producing genes, candidate immune modulating proteins and pathways, and genes responsible for acaricide resistance offers opportunities for developing new methods for diagnosing, treating and preventing this disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-1198-2) contains supplementary material, which is available to authorized users.

Metabolic and genomic analysis elucidates strain-level variation in Microbacterium spp. isolated from chromate contaminated sediment

Hexavalent chromium [Cr(VI)] is a soluble carcinogen that has caused widespread contamination of soil and water in many industrial nations. Bacteria have the potential to aid remediation as certain strains can catalyze the reduction of Cr(VI) to insoluble and less toxic Cr(III). Here, we examine Cr(VI) reducing Microbacterium spp. (Cr-K1W, Cr-K20, Cr-K29, and Cr-K32) isolated from contaminated sediment (Seymore, Indiana) and show varying chromate responses despite the isolates' phylogenetic similarity (i.e., identical 16S rRNA gene sequences). Detailed analysis identified differences based on genomic metabolic potential, growth and general metabolic capabilities, and capacity to resist and reduce Cr(VI). Taken together, the discrepancies between the isolates demonstrate the complexity inter-strain variation can have on microbial physiology and related biogeochemical processes.

Potential and pitfalls of eukaryotic metagenome skimming: a test case for lichens

Whole-genome shotgun sequencing of multispecies communities using only a single library layout is commonly used to assess taxonomic and functional diversity of microbial assemblages. Here, we investigate to what extent such metagenome skimming approaches are applicable for in-depth genomic characterizations of eukaryotic communities, for example lichens. We address how to best assemble a particular eukaryotic metagenome skimming data, what pitfalls can occur, and what genome quality can be expected from these data. To facilitate a project-specific benchmarking, we introduce the concept of twin sets, simulated data resembling the outcome of a particular metagenome sequencing study. We show that the quality of genome reconstructions depends essentially on assembler choice. Individual tools, including the metagenome assemblers Omega and MetaVelvet, are surprisingly sensitive to low and uneven coverages. In combination with the routine of assembly parameter choice to optimize the assembly N50 size, these tools can preclude an entire genome from the assembly. In contrast, MIRA, an all-purpose overlap assembler, and SPAdes, a multisized de Bruijn graph assembler, facilitate a comprehensive view on the individual genomes across a wide range of coverage ratios. Testing assemblers on a real-world metagenome skimming data from the lichen Lasallia pustulata demonstrates the applicability of twin sets for guiding method selection. Furthermore, it reveals that the assembly outcome for the photobiont Trebouxia sp. falls behind the a priori expectation given the simulations. Although the underlying reasons remain still unclear, this highlights that further studies on this organism require special attention during sequence data generation and downstream analysis.

KGCAK: a K-mer based database for genome-wide phylogeny and complexity evaluation

Background

The K-mer approach, treating genomic sequences as simple characters and counting the relative abundance of each string upon a fixed K, has been extensively applied to phylogeny inference for genome assembly, annotation, and comparison.

Results

To meet increasing demands for comparing large genome sequences and to promote the use of the K-mer approach, we develop a versatile database, KGCAK (http://kgcak.big.ac.cn/KGCAK/), containing ~8,000 genomes that include genome sequences of diverse life forms (viruses, prokaryotes, protists, animals, and plants) and cellular organelles of eukaryotic lineages. It builds phylogeny based on genomic elements in an alignment-free fashion and provides in-depth data processing enabling users to compare the complexity of genome sequences based on K-mer distribution.

Conclusion

We hope that KGCAK becomes a powerful tool for exploring relationship within and among groups of species in a tree of life based on genomic data.

Reviewers

This article was reviewed by Prof Mark Ragan and Dr Yuri Wolf.

Reference-free compression of high throughput sequencing data with a probabilistic de Bruijn graph

BACKGROUND

Data volumes generated by next-generation sequencing (NGS) technologies is now a major concern for both data storage and transmission. This triggered the need for more efficient methods than general purpose compression tools, such as the widely used gzip method.

RESULTS

We present a novel reference-free method meant to compress data issued from high throughput sequencing technologies. Our approach, implemented in the software LEON, employs techniques derived from existing assembly principles. The method is based on a reference probabilistic de Bruijn Graph, built de novo from the set of reads and stored in a Bloom filter. Each read is encoded as a path in this graph, by memorizing an anchoring kmer and a list of bifurcations. The same probabilistic de Bruijn Graph is used to perform a lossy transformation of the quality scores, which allows to obtain higher compression rates without losing pertinent information for downstream analyses.

CONCLUSIONS

LEON was run on various real sequencing datasets (whole genome, exome, RNA-seq or metagenomics). In all cases, LEON showed higher overall compression ratios than state-of-the-art compression software. On a C. elegans whole genome sequencing dataset, LEON divided the original file size by more than 20. LEON is an open source software, distributed under GNU affero GPL License, available for download at http://gatb.inria.fr/software/leon/.

Lighter: fast and memory-efficient sequencing error correction without counting

Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.

Best practices for evaluating single nucleotide variant calling methods for microbial genomics

Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards.

Genome analyses suggest the presence of polyploidy and recent human-driven expansions in eight global populations of the honeybee pathogen Nosema ceranae

Nosema ceranae is a microsporidian pathogen whose infections have been associated with recent global declines in the populations of western honeybees (Apis mellifera). Despite the outstanding economic and ecological threat that N. ceranae may represent for honeybees worldwide, many aspects of its biology, including its mode of reproduction, propagation and ploidy, are either very unclear or unknown. In the present study, we set to gain knowledge in these biological aspects by re-sequencing the genome of eight isolates (i.e. a population of spores isolated from one single beehive) of this species harvested from eight geographically distant beehives, and by investigating their level of polymorphism. Consistent with previous analyses performed using single gene sequences, our analyses uncovered the presence of very high genetic diversity within each isolate, but also very little hive-specific polymorphism. Surprisingly, the nature, location and distribution of this genetic variation suggest that beehives around the globe are infected by a population of N. ceranae cells that may be polyploid (4n or more), and possibly clonal. Lastly, phylogenetic analyses based on genome-wide single-nucleotide polymorphism data extracted from these parasites and mitochondrial sequences from their hosts all failed to support the current geographical structure of our isolates.

De Novo Assembly of Bitter Gourd Transcriptomes: Gene Expression and Sequence Variations in Gynoecious and Monoecious Lines

Bitter gourd (Momordica charantia L.) is a nutritious vegetable crop of Asian origin, used as a medicinal herb in Indian and Chinese traditional medicine. Molecular breeding in bitter gourd is in its infancy, due to limited molecular resources, particularly on functional markers for traits such as gynoecy. We performed de novo transcriptome sequencing of bitter gourd using Illumina next-generation sequencer, from root, flower buds, stem and leaf samples of gynoecious line (Gy323) and a monoecious line (DRAR1). A total of 65,540 transcripts for Gy323 and 61,490 for DRAR1 were obtained. Comparisons revealed SNP and SSR variations between these lines and, identification of gene classes. Based on available transcripts we identified 80 WRKY transcription factors, several reported in responses to biotic and abiotic stresses; 56 ARF genes which play a pivotal role in auxin-regulated gene expression and development. The data presented will be useful in both functions studies and breeding programs in bitter gourd.

Draft Genome Sequence of Lachancea lanzarotensis CBS 12615T, an Ascomycetous Yeast Isolated from Grapes

We report the genome sequencing of the yeast Lachancea lanzarotensis CBS 12615^T. The assembly comprises 24 scaffolds, for a total size of 11.46 Mbp. The annotation revealed 5,058 putative protein-coding genes. Detection of seven centromeres supports a chromosome fusion, which occurred after divergence from Lachancea thermotolerans and Lachancea kluyveri.

Establishment of Anthoceros agrestis as a model species for studying the biology of hornworts

BACKGROUND

Plants colonized terrestrial environments approximately 480 million years ago and have contributed significantly to the diversification of life on Earth. Phylogenetic analyses position a subset of charophyte algae as the sister group to land plants, and distinguish two land plant groups that diverged around 450 million years ago - the bryophytes and the vascular plants. Relationships between liverworts, mosses hornworts and vascular plants have proven difficult to resolve, and as such it is not clear which bryophyte lineage is the sister group to all other land plants and which is the sister to vascular plants. The lack of comparative molecular studies in representatives of all three lineages exacerbates this uncertainty. Such comparisons can be made between mosses and liverworts because representative model organisms are well established in these two bryophyte lineages. To date, however, a model hornwort species has not been available.

RESULTS

Here we report the establishment of Anthoceros agrestis as a model hornwort species for laboratory experiments. Axenic culture conditions for maintenance and vegetative propagation have been determined, and treatments for the induction of sexual reproduction and sporophyte development have been established. In addition, protocols have been developed for the extraction of DNA and RNA that is of a quality suitable for molecular analyses. Analysis of haploid-derived genome sequence data of two A. agrestis isolates revealed single nucleotide polymorphisms at multiple loci, and thus these two strains are suitable starting material for classical genetic and mapping experiments.

CONCLUSIONS

Methods and resources have been developed to enable A. agrestis to be used as a model species for developmental, molecular, genomic, and genetic studies. This advance provides an unprecedented opportunity to investigate the biology of hornworts.

An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data

Next-generation sequencing (NGS) approaches rapidly produce millions to billions of short reads, which allow pathogen detection and discovery in human clinical, animal and environmental samples. A major limitation of sequence homology-based identification for highly divergent microorganisms is the short length of reads generated by most highly parallel sequencing technologies. Short reads require a high level of sequence similarities to annotated genes to confidently predict gene function or homology. Such recognition of highly divergent homologues can be improved by reference-free (de novo) assembly of short overlapping sequence reads into larger contigs. We describe an ensemble strategy that integrates the sequential use of various de Bruijn graph and overlap-layout-consensus assemblers with a novel partitioned sub-assembly approach. We also proposed new quality metrics that are suitable for evaluating metagenome de novo assembly. We demonstrate that this new ensemble strategy tested using in silico spike-in, clinical and environmental NGS datasets achieved significantly better contigs than current approaches.

America's red gold: multiple lineages of cultivated cochineal in Mexico

Cultivated cochineal (Dactylopius coccus) produces carminic acid, a valuable red dye used to color textiles, cosmetics, and food. Extant native D. coccus is largely restricted to two populations in the Mexican and the Andean highlands, although the insect's ultimate center of domestication remains unclear. Moreover, due to Mexican D. coccus cultivation's near demise during the 19th century, the genetic diversity of current cochineal stock is unknown. Through genomic sequencing, we identified two divergent D. coccus populations in highland Mexico: one unique to Mexico and another that was more closely related to extant Andean cochineal. Relic diversity is preserved in the crops of small-scale Mexican cochineal farmers. Conversely, larger-scale commercial producers are cultivating the Andean-like cochineal, which may reflect clandestine 20th century importation.

HyDA-Vista: towards optimal guided selection of k-mer size for sequence assembly

Motivation

Intimately tied to assembly quality is the complexity of the de Bruijn graph built by the assembler. Thus, there have been many paradigms developed to decrease the complexity of the de Bruijn graph. One obvious combinatorial paradigm for this is to allow the value of k to vary; having a larger value of k where the graph is more complex and a smaller value of k where the graph would likely contain fewer spurious edges and vertices. One open problem that affects the practicality of this method is how to predict the value of k prior to building the de Bruijn graph. We show that optimal values of k can be predicted prior to assembly by using the information contained in a phylogenetically-close genome and therefore, help make the use of multiple values of k practical for genome assembly.

Results

We present HyDA-Vista, which is a genome assembler that uses homology information to choose a value of k for each read prior to the de Bruijn graph construction. The chosen k is optimal if there are no sequencing errors and the coverage is sufficient. Fundamental to our method is the construction of the maximal sequence landscape, which is a data structure that stores for each position in the input string, the largest repeated substring containing that position. In particular, we show the maximal sequence landscape can be constructed in O(n + n log n)-time and O(n)-space. HyDA-Vista first constructs the maximal sequence landscape for a homologous genome. The reads are then aligned to this reference genome, and values of k are assigned to each read using the maximal sequence landscape and the alignments. Eventually, all the reads are assembled by an iterative de Bruijn graph construction method. Our results and comparison to other assemblers demonstrate that HyDA-Vista achieves the best assembly of E. coli before repeat resolution or scaffolding.

Availability

HyDA-Vista is freely available [1]. The code for constructing the maximal sequence landscape and choosing the optimal value of k for each read is also separately available on the website and could be incorporated into any genome assembler.

Draft Genome Sequence of Taylorella equigenitalis Strain MCE529, Isolated from a Belgian Warmblood Horse

Taylorella equigenitalis is the causative agent of contagious equine metritis (CEM), a sexually transmitted infection of horses. We herein report the genome sequence of T. equigenitalis strain MCE529, isolated in 2009 from the urethral fossa of a 15-year-old Belgian Warmblood horse in France.

KmerStream: streaming algorithms for k-mer abundance estimation

MOTIVATION

Several applications in bioinformatics, such as genome assemblers and error corrections methods, rely on counting and keeping track of k-mers (substrings of length k). Histograms of k-mer frequencies can give valuable insight into the underlying distribution and indicate the error rate and genome size sampled in the sequencing experiment.

RESULTS

We present KmerStream, a streaming algorithm for estimating the number of distinct k-mers present in high-throughput sequencing data. The algorithm runs in time linear in the size of the input and the space requirement are logarithmic in the size of the input. We derive a simple model that allows us to estimate the error rate of the sequencing experiment, as well as the genome size, using only the aggregate statistics reported by KmerStream. As an application we show how KmerStream can be used to compute the error rate of a DNA sequencing experiment. We run KmerStream on a set of 2656 whole genome sequenced individuals and compare the error rate to quality values reported by the sequencing equipment. We discover that while the quality values alone are largely reliable as a predictor of error rate, there is considerable variability in the error rates between sequencing runs, even when accounting for reported quality values.

GABenchToB: a genome assembly benchmark tuned on bacteria and benchtop sequencers

De novo genome assembly is the process of reconstructing a complete genomic sequence from countless small sequencing reads. Due to the complexity of this task, numerous genome assemblers have been developed to cope with different requirements and the different kinds of data provided by sequencers within the fast evolving field of next-generation sequencing technologies. In particular, the recently introduced generation of benchtop sequencers, like Illumina's MiSeq and Ion Torrent's Personal Genome Machine (PGM), popularized the easy, fast, and cheap sequencing of bacterial organisms to a broad range of academic and clinical institutions. With a strong pragmatic focus, here, we give a novel insight into the line of assembly evaluation surveys as we benchmark popular de novo genome assemblers based on bacterial data generated by benchtop sequencers. Therefore, single-library assemblies were generated, assembled, and compared to each other by metrics describing assembly contiguity and accuracy, and also by practice-oriented criteria as for instance computing time. In addition, we extensively analyzed the effect of the depth of coverage on the genome assemblies within reasonable ranges and the k-mer optimization problem of de Bruijn Graph assemblers. Our results show that, although both MiSeq and PGM allow for good genome assemblies, they require different approaches. They not only pair with different assembler types, but also affect assemblies differently regarding the depth of coverage where oversampling can become problematic. Assemblies vary greatly with respect to contiguity and accuracy but also by the requirement on the computing power. Consequently, no assembler can be rated best for all preconditions. Instead, the given kind of data, the demands on assembly quality, and the available computing infrastructure determines which assembler suits best. The data sets, scripts and all additional information needed to replicate our results are freely available at ftp://ftp.cebitec.uni-bielefeld.de/pub/GABenchToB.

These are not the k-mers you are looking for: efficient online k-mer counting using a probabilistic data structure

K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix arrays, and trie structures, khmer relies entirely on a simple probabilistic data structure, a Count-Min Sketch. The Count-Min Sketch permits online updating and retrieval of k-mer counts in memory which is necessary to support online k-mer analysis algorithms. On sparse data sets this data structure is considerably more memory efficient than any exact data structure. In exchange, the use of a Count-Min Sketch introduces a systematic overcount for k-mers; moreover, only the counts, and not the k-mers, are stored. Here we analyze the speed, the memory usage, and the miscount rate of khmer for generating k-mer frequency distributions and retrieving k-mer counts for individual k-mers. We also compare the performance of khmer to several other k-mer counting packages, including Tallymer, Jellyfish, BFCounter, DSK, KMC, Turtle and KAnalyze. Finally, we examine the effectiveness of profiling sequencing error, k-mer abundance trimming, and digital normalization of reads in the context of high khmer false positive rates. khmer is implemented in C++ wrapped in a Python interface, offers a tested and robust API, and is freely available under the BSD license at github.com/ged-lab/khmer.

Evaluation and validation of de novo and hybrid assembly techniques to derive high-quality genome sequences

MOTIVATION

To assess the potential of different types of sequence data combined with de novo and hybrid assembly approaches to improve existing draft genome sequences.

RESULTS

Illumina, 454 and PacBio sequencing technologies were used to generate de novo and hybrid genome assemblies for four different bacteria, which were assessed for quality using summary statistics (e.g. number of contigs, N50) and in silico evaluation tools. Differences in predictions of multiple copies of rDNA operons for each respective bacterium were evaluated by PCR and Sanger sequencing, and then the validated results were applied as an additional criterion to rank assemblies. In general, assemblies using longer PacBio reads were better able to resolve repetitive regions. In this study, the combination of Illumina and PacBio sequence data assembled through the ALLPATHS-LG algorithm gave the best summary statistics and most accurate rDNA operon number predictions. This study will aid others looking to improve existing draft genome assemblies.

AVAILABILITY AND IMPLEMENTATION

All assembly tools except CLC Genomics Workbench are freely available under GNU General Public License.

CONTACT

brownsd@ornl.gov

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of nontypable Haemophilus influenzae isolates recovered from adult patients with underlying chronic lung disease reveals genotypic and phenotypic traits associated with persistent infection

Nontypable Haemophilus influenzae (NTHi) has emerged as an important opportunistic pathogen causing infection in adults suffering obstructive lung diseases. Existing evidence associates chronic infection by NTHi to the progression of the chronic respiratory disease, but specific features of NTHi associated with persistence have not been comprehensively addressed. To provide clues about adaptive strategies adopted by NTHi during persistent infection, we compared sequential persistent isolates with newly acquired isolates in sputa from six patients with chronic obstructive lung disease. Pulse field gel electrophoresis (PFGE) identified three patients with consecutive persistent strains and three with new strains. Phenotypic characterisation included infection of respiratory epithelial cells, bacterial self-aggregation, biofilm formation and resistance to antimicrobial peptides (AMP). Persistent isolates differed from new strains in showing low epithelial adhesion and inability to form biofilms when grown under continuous-flow culture conditions in microfermenters. Self-aggregation clustered the strains by patient, not by persistence. Increasing resistance to AMPs was observed for each series of persistent isolates; this was not associated with lipooligosaccharide decoration with phosphorylcholine or with lipid A acylation. Variation was further analyzed for the series of three persistent isolates recovered from patient 1. These isolates displayed comparable growth rate, natural transformation frequency and murine pulmonary infection. Genome sequencing of these three isolates revealed sequential acquisition of single-nucleotide variants in the AMP permease sapC, the heme acquisition systems hgpB, hgpC, hup and hxuC, the 3-deoxy-D-manno-octulosonic acid kinase kdkA, the long-chain fatty acid transporter ompP1, and the phosphoribosylamine glycine ligase purD. Collectively, we frame a range of pathogenic traits and a repertoire of genetic variants in the context of persistent infection by NTHi.

Quality control of next-generation sequencing data without a reference

Next-generation sequencing (NGS) technologies have dramatically expanded the breadth of genomics. Genome-scale data, once restricted to a small number of biomedical model organisms, can now be generated for virtually any species at remarkable speed and low cost. Yet non-model organisms often lack a suitable reference to map sequence reads against, making alignment-based quality control (QC) of NGS data more challenging than cases where a well-assembled genome is already available. Here we show that by generating a rapid, non-optimized draft assembly of raw reads, it is possible to obtain reliable and informative QC metrics, thus removing the need for a high quality reference. We use benchmark datasets generated from control samples across a range of genome sizes to illustrate that QC inferences made using draft assemblies are broadly equivalent to those made using a well-established reference, and describe QC tools routinely used in our production facility to assess the quality of NGS data from non-model organisms.

Automated ensemble assembly and validation of microbial genomes

Background

The continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible.

Results

To encourage best practices supported by the community, we present iMetAMOS, an automated ensemble assembly pipeline; iMetAMOS encapsulates the process of running, validating, and selecting a single assembly from multiple assemblies. iMetAMOS packages several leading open-source tools into a single binary that automates parameter selection and execution of multiple assemblers, scores the resulting assemblies based on multiple validation metrics, and annotates the assemblies for genes and contaminants. We demonstrate the utility of the ensemble process on 225 previously unassembled Mycobacterium tuberculosis genomes as well as a Rhodobacter sphaeroides benchmark dataset. On these real data, iMetAMOS reliably produces validated assemblies and identifies potential contamination without user intervention. In addition, intelligent parameter selection produces assemblies of R. sphaeroides comparable to or exceeding the quality of those from the GAGE-B evaluation, affecting the relative ranking of some assemblers.

Conclusions

Ensemble assembly with iMetAMOS provides users with multiple, validated assemblies for each genome. Although computationally limited to small or mid-sized genomes, this approach is the most effective and reproducible means for generating high-quality assemblies and enables users to select an assembly best tailored to their specific needs.

BLESS: bloom filter-based error correction solution for high-throughput sequencing reads

MOTIVATION

Rapid advances in next-generation sequencing (NGS) technology have led to exponential increase in the amount of genomic information. However, NGS reads contain far more errors than data from traditional sequencing methods, and downstream genomic analysis results can be improved by correcting the errors. Unfortunately, all the previous error correction methods required a large amount of memory, making it unsuitable to process reads from large genomes with commodity computers.

RESULTS

We present a novel algorithm that produces accurate correction results with much less memory compared with previous solutions. The algorithm, named BLoom-filter-based Error correction Solution for high-throughput Sequencing reads (BLESS), uses a single minimum-sized Bloom filter, and is also able to tolerate a higher false-positive rate, thus allowing us to correct errors with a 40× memory usage reduction on average compared with previous methods. Meanwhile, BLESS can extend reads like DNA assemblers to correct errors at the end of reads. Evaluations using real and simulated reads showed that BLESS could generate more accurate results than existing solutions. After errors were corrected using BLESS, 69% of initially unaligned reads could be aligned correctly. Additionally, de novo assembly results became 50% longer with 66% fewer assembly errors.

AVAILABILITY AND IMPLEMENTATION

Freely available at http://sourceforge.net/p/bless-ec

CONTACT

dchen@illinois.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring genome characteristics and sequence quality without a reference

MOTIVATION

The de novo assembly of large, complex genomes is a significant challenge with currently available DNA sequencing technology. While many de novo assembly software packages are available, comparatively little attention has been paid to assisting the user with the assembly.

RESULTS

This article addresses the practical aspects of de novo assembly by introducing new ways to perform quality assessment on a collection of sequence reads. The software implementation calculates per-base error rates, paired-end fragment-size distributions and coverage metrics in the absence of a reference genome. Additionally, the software will estimate characteristics of the sequenced genome, such as repeat content and heterozygosity that are key determinants of assembly difficulty.

Determining the quality and complexity of next-generation sequencing data without a reference genome

We describe an open-source kPAL package that facilitates an alignment-free assessment of the quality and comparability of sequencing datasets by analyzing k-mer frequencies. We show that kPAL can detect technical artefacts such as high duplication rates, library chimeras, contamination and differences in library preparation protocols. kPAL also successfully captures the complexity and diversity of microbiomes and provides a powerful means to study changes in microbial communities. Together, these features make kPAL an attractive and broadly applicable tool to determine the quality and comparability of sequence libraries even in the absence of a reference sequence. kPAL is freely available at https://github.com/LUMC/kPAL webcite.