Number Of Contigs Research Articles

Whole genome sequencing for typing and characterisation of Listeria monocytogenes isolated in a rabbit meat processing plant.

Listeria monocytogenes is a food-borne pathogen able to survive and grow in different environments including food processing plants where it can persist for month or years. In the present study the discriminatory power of Whole Genome Sequencing (WGS)-based analysis (cgMLST) was compared to that of molecular typing methods on 34 L. monocytogenes isolates collected over one year in the same rabbit meat processing plant and belonging to three genotypes (ST14, ST121, ST224). Each genotype included isolates indistinguishable by standard molecular typing methods. The virulence potential of all isolates was assessed by Multi Virulence-Locus Sequence Typing (MVLST) and the investigation of a representative database of virulence determinant genes. The whole genome of each isolate was sequenced on a MiSeq platform. The cgMLST, MVLST, and in silico identification of virulence genes were performed using publicly available tools. Draft genomes included a number of contigs ranging from 13 to 28 and N50 ranging from 456298 to 580604. The coverage ranged from 41 to 187X. The cgMLST showed a significantly superior discriminatory power only in comparison to ribotyping, nevertheless it allows the detection of two singletons belonging to ST14 that were not observed by other molecular methods. All ST14 isolates belonged to VT107, which 7-loci concatenated sequence differs for only 4 nucleotides to VT1 (Epidemic clone III). Analysis of virulence genes showed the presence of a fulllength inlA version in all ST14 isolates and of a mutated version including a premature stop codon (PMSC) associated to attenuated virulence in all ST121 isolates.

Generation of expressed sequence tags for discovery of genes responsible for floral traits of Chrysanthemum morifolium by next-generation sequencing technology

BackgroundChrysanthemum morifolium is one of the most economically valuable ornamental plants worldwide. Chrysanthemum is an allohexaploid plant with a large genome that is commercially propagated by vegetative reproduction. New cultivars with different floral traits, such as color, morphology, and scent, have been generated mainly by classical cross-breeding and mutation breeding. However, only limited genetic resources and their genome information are available for the generation of new floral traits.ResultsTo obtain useful information about molecular bases for floral traits of chrysanthemums, we read expressed sequence tags (ESTs) of chrysanthemums by high-throughput sequencing using the 454 pyrosequencing technology. We constructed normalized cDNA libraries, consisting of full-length, 3′-UTR, and 5′-UTR cDNAs derived from various tissues of chrysanthemums. These libraries produced a total number of 3,772,677 high-quality reads, which were assembled into 213,204 contigs. By comparing the data obtained with those of full genome-sequenced species, we confirmed that our chrysanthemum contig set contained the majority of all expressed genes, which was sufficient for further molecular analysis in chrysanthemums.ConclusionWe confirmed that our chrysanthemum EST set (contigs) contained a number of contigs that encoded transcription factors and enzymes involved in pigment and aroma compound metabolism that was comparable to that of other species. This information can serve as an informative resource for identifying genes involved in various biological processes in chrysanthemums. Moreover, the findings of our study will contribute to a better understanding of the floral characteristics of chrysanthemums including the myriad cultivars at the molecular level.

Transcriptome changes associated with Tomato spotted wilt virus infection in various life stages of its thrips vector, Frankliniella fusca (Hinds).

Persistent propagative viruses maintain intricate interactions with their arthropod vectors. In this study, we investigated the transcriptome-level responses associated with a persistent propagative phytovirus infection in various life stages of its vector using an Illumina HiSeq sequencing platform. The pathosystem components included a Tospovirus, Tomato spotted wilt virus (TSWV), its insect vector, Frankliniella fusca (Hinds), and a plant host, Arachis hypogaea (L.). We assembled (de novo) reads from three developmental stage groups of virus-exposed and non-virus-exposed F. fusca into one transcriptome consisting of 72 366 contigs and identified 1161 differentially expressed (DE) contigs. The number of DE contigs was greatest in adults (female) (562) when compared with larvae (first and second instars) (395) and pupae (pre- and pupae) (204). Upregulated contigs in virus-exposed thrips had blastx annotations associated with intracellular transport and virus replication. Upregulated contigs were also assigned blastx annotations associated with immune responses, including apoptosis and phagocytosis. In virus-exposed larvae, Blast2GO analysis identified functional groups, such as multicellular development with downregulated contigs, while reproduction, embryo development and growth were identified with upregulated contigs in virus-exposed adults. This study provides insights into differences in transcriptome-level responses modulated by TSWV in various life stages of an important vector, F. fusca.

Resolving plasmid structures in Enterobacteriaceae using the MinION nanopore sequencer: assessment of MinION and MinION/Illumina hybrid data assembly approaches.

This study aimed to assess the feasibility of using the Oxford Nanopore Technologies (ONT) MinION long-read sequencer in reconstructing fully closed plasmid sequences from eight Enterobacteriaceae isolates of six different species with plasmid populations of varying complexity. Species represented were Escherichia coli, Klebsiella pneumoniae, Citrobacter freundii, Enterobacter cloacae, Serratia marcescens and Klebsiella oxytoca, with plasmid populations ranging from 1–11 plasmids with sizes of 2–330 kb. Isolates were sequenced using Illumina (short-read) and ONT’s MinION (long-read) platforms, and compared with fully resolved PacBio (long-read) sequence assemblies for the same isolates. We compared the performance of different assembly approaches including SPAdes, plasmidSPAdes, hybridSPAdes, Canu, Canu+Pilon (canuPilon) and npScarf in recovering the plasmid structures of these isolates by comparing with the gold-standard PacBio reference sequences. Overall, canuPilon provided consistently good quality assemblies both in terms of assembly statistics (N50, number of contigs) and assembly accuracy [presence of single nucleotide polymorphisms (SNPs)/indels with respect to the reference sequence]. For plasmid reconstruction, Canu recovered 70 % of the plasmids in complete contigs, and combining three assembly approaches (Canu or canuPilon, hybridSPAdes and plasmidSPAdes) resulted in a total 78 % recovery rate for all the plasmids. The analysis demonstrated the potential of using MinION sequencing technology to resolve important plasmid structures in Enterobacteriaceae species independent of and in conjunction with Illumina sequencing data. A consensus assembly derived from several assembly approaches could present significant benefit in accurately resolving the greatest number of plasmid structures.

Tench (Tincatinca) high-throughput transcriptomics reveal feed dependent gut profiles

Tench, Tincatinca is a freshwater species which receives increasing attention as marine resources are overexploited and alternative feed components must be implemented to enable sustainable development of aquaculture. The aim of the study was to provide scientists and fish farmers with first high quality annotated tench transcriptome and open a new chapter in tench research, especially when practical diets are tested. Therefore, the second aim was to identify differentially expressed contigs (DECs) in tench gut after 86-day trial where adult tench females were fed with 0% and 100% replacement of fish meal (FM) with poultry by-product meal (PBM). De novo assembling using de novo RNA-Seq Assembly Pipeline (DRAP) produced 64070 contigs where these exceeding 1kbp were mostly annotated. Microsatellite search identified 23668 SSRs and SNPs were distributed in 118002 transitions and 83577 transversions. High quality of the assembly and annotation completeness of the tench transcriptome was confirmed using BUSCO and by mapping contigs against common carp, Cyprinuscarpio and zebrafish, Daniorerio data sets. Analysis of gene expression differences between gut samples tench fed with FM and PBM diets revealed 721 and 69 DECs using edgeR and DESeq2, respectively. Venn diagram for these results filtered out 57 DECs which were common for both analysis. Due to a low number of annotated DECs enrichment analysis provided a low number of useful contigs for pathway or functional analysis. Nevertheless, each contig in the set was analysed through BLASTn and BLASTx and eighteen DECs were characterised and identified as mainly involved in response to different immune stimuli and disease states (e.g. clusterofdifferentiation48, F-typelectin), cell adhesion (e.g. paracingulin), digestion (e.g. serine proteases) and signal transduction (e.g. neurexophilin3, complexin2). Moreover, study has shown that most of the identified in our study DECs (70.2%) were down regulated in gut samples of tench fed with PBM comparing to these with FM-based feed. This observation might indicate on disorganization of inter-epithelial junctions in ongoing inflammation process. Our de novo tench gut transcriptome assembly (online NGS Pipeline) provide a guide for further diverse studies because, understanding feed-gut interactions and intestinal homeostasis in farmed tench is important to maximise performance of this species and to ensure that freshwater aquaculture continues to be a sustainable source of food for a growing world population.

Phylogenetic position of the coral symbiont Ostreobium (Ulvophyceae) inferred from chloroplast genome data.

The green algal genus Ostreobium is an important symbiont of corals, playing roles in reef decalcification and providing photosynthates to the coral during bleaching events. A chloroplast genome of a cultured strain of Ostreobium was available, but low taxon sampling and Ostreobium's early-branching nature left doubt about its phylogenetic position. Here, we generate and describe chloroplast genomes from four Ostreobium strains as well as Avrainvillea mazei and Neomeris sp., strategically sampled early-branching lineages in the Bryopsidales and Dasycladales respectively. At 80,584bp, the chloroplast genome of Ostreobium sp. HV05042 is themost compact yet found in the Ulvophyceae. The Avrainvillea chloroplast genome is ~94kbp and contains introns in infA and cysT that have nearly complete sequence identity except for an open reading frame (ORF) in infA that is not present in cysT. In line with other bryopsidalean species, it also contains regions with possibly bacteria-derived ORFs. The Neomeris data did not assemble into a canonical circular chloroplast genome but a large number of contigs containing fragments of chloroplast genes and showing evidence of long introns and intergenic regions, and the Neomeris chloroplast genome size was estimated to exceed 1.87Mb. Chloroplast phylogenomics and 18S nrDNA data showed strong support for the Ostreobium lineage being sister to the remaining Bryopsidales. There were differences in branch support when outgroups were varied, but the overall support for the placement of Ostreobium was strong. These results permitted us to validate two suborders and introduce a third, the Ostreobineae.

Lentinula edodes Genome Survey and Postharvest Transcriptome Analysis.

Lentinula edodes is a popular, cultivated edible and medicinal mushroom. Lentinula edodes is susceptible to postharvest problems, such as gill browning, fruiting body softening, and lentinan degradation. We constructed a de novo assembly draft genome sequence and performed gene prediction for Lentinula edodesDe novo assembly was carried out using short reads from paired-end and mate-paired libraries and by using long reads by PacBio, resulting in a contig number of 1,951 and an N50 of 1 Mb. Furthermore, we predicted genes by Augustus using transcriptome sequencing (RNA-seq) data from the whole life cycle of Lentinula edodes, resulting in 12,959 predicted genes. This analysis revealed that Lentinula edodes lacks lignin peroxidase. To reveal genes involved in the loss of quality of Lentinula edodes postharvest fruiting bodies, transcriptome analysis was carried out using serial analysis of gene expression (SuperSAGE). This analysis revealed that many cell wall-related enzymes are upregulated after harvest, such as β-1,3-1,6-glucan-degrading enzymes in glycoside hydrolase (GH) families GH5, GH16, GH30, GH55, and GH128, and thaumatin-like proteins. In addition, we found that several chitin-related genes are upregulated, such as putative chitinases in GH family 18, exochitinases in GH20, and a putative chitosanase in GH family 75. The results suggest that cell wall-degrading enzymes synergistically cooperate for rapid fruiting body autolysis. Many putative transcription factor genes were upregulated postharvest, such as genes containing high-mobility-group (HMG) domains and zinc finger domains. Several cell death-related proteins were also upregulated postharvest.IMPORTANCE Our data collectively suggest that there is a rapid fruiting body autolysis system in Lentinula edodes The genes for the loss of postharvest quality newly found in this research will be targets for the future breeding of strains that keep fresh longer than present strains. De novoLentinula edodes genome assembly data will be used for the construction of a complete Lentinula edodes chromosome map for future breeding.

Prediction of virus-host infectious association by supervised learning methods

BackgroundThe study of virus-host infectious association is important for understanding the functions and dynamics of microbial communities. Both cellular and fractionated viral metagenomic data generate a large number of viral contigs with missing host information. Although relative simple methods based on the similarity between the word frequency vectors of viruses and bacterial hosts have been developed to study virus-host associations, the problem is significantly understudied. We hypothesize that machine learning methods based on word frequencies can be efficiently used to study virus-host infectious associations.MethodsWe investigate four different representations of word frequencies of viral sequences including the relative word frequency and three normalized word frequencies by subtracting the number of expected from the observed word counts. We also study five machine learning methods including logistic regression, support vector machine, random forest, Gaussian naive Bayes and Bernoulli naive Bayes for separating infectious from non-infectious viruses for nine bacterial host genera with at least 45 infecting viruses. Area under the receiver operating characteristic curve (AUC) is used to compare the performance of different machine learning method and feature combinations. We then evaluate the performance of the best method for the identification of the hosts of contigs in metagenomic studies. We also develop a maximum likelihood method to estimate the fraction of true infectious viruses for a given host in viral tagging experiments.ResultsBased on nine bacterial host genera with at least 45 infectious viruses, we show that random forest together with the relative word frequency vector performs the best in identifying viruses infecting particular hosts. For all the nine host genera, the AUC is over 0.85 and for five of them, the AUC is higher than 0.98 when the word size is 6 indicating the high accuracy of using machine learning approaches for identifying viruses infecting particular hosts. We also show that our method can predict the hosts of viral contigs of length at least 1kbps in metagenomic studies with high accuracy. The random forest together with word frequency vector outperforms current available methods based on Manhattan and d_{2}^{*} dissimilarity measures. Based on word frequencies, we estimate that about 95% of the identified T4-like viruses in viral tagging experiment infect Synechococcus, while only about 29% of the identified non-T4-like viruses and 30% of the contigs in the study potentially infect Synechococcus.ConclusionsThe random forest machine learning method together with the relative word frequencies as features of viruses can be used to predict viruses and viral contigs for specific bacterial hosts. The maximum likelihood approach can be used to estimate the fraction of true infectious associated viruses in viral tagging experiments.

Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies.

BackgroundDe novo transcriptome assembly of short reads is now a common step in expression analysis of organisms lacking a reference genome sequence. Several software packages are available to perform this task. Even if their results are of good quality it is still possible to improve them in several ways including redundancy reduction or error correction. Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved.ResultsWe built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts.ConclusionTranscriptome assembly is a challenging computational task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available under GPL V3 license at http://www.sigenae.org/drap.

Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs.

This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ) to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST) from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS) and peptidoglycan (PGN)). Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO) showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs), carrier proteins/membrane transport (approximately 15%), effectors/modulators and cell communication (approximately 11%), nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5%) and intracellular transducers/signal transduction (approximately 5%). Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ) that provides a platform enriched for the study of gene expression in S. aurata with an emphasis upon immunity and the immune response.

Whole-transcriptome sequence analysis of differentially expressed genes in Phormium tenax under drought stress

Phormium tenax is a kind of drought resistant garden plant with its rich and colorful leaves. To clarify the molecular mechanism of drought resistance in Phormium tenax, transcriptome was sequenced by the Illumina sequencing technology under normal and drought stress, respectively. A large number of contigs, transcripts and unigenes were obtained. Among them, only 30,814 unigenes were annotated by comparing with the protein databases. A total of 4,380 genes were differentially expressed, 2,698 of which were finally annotated under drought stress. Differentially expression analysis was also performed upon drought treatment. In KEGG pathway, the mechanism of drought resistance in Phormium tenax was explained from three aspects of metabolism and signaling of hormones, osmotic adjustment and reactive oxygen species metabolism. These results are helpful to understand the drought tolerance mechanism of Phormium tenax and will provide a precious genetic resource for drought-resistant vegetation breeding and research.

Parasite infection of public databases: a data mining approach to identify apicomplexan contaminations in animal genome and transcriptome assemblies

BackgroundContaminations from various exogenous sources are a common problem in next-generation sequencing. Another possible source of contaminating DNA are endogenous parasites. On the one hand, undiscovered contaminations of animal sequence assemblies may lead to erroneous interpretation of data; on the other hand, when identified, parasite-derived sequences may provide a valuable source of information.ResultsHere we show that sequences deriving from apicomplexan parasites can be found in many animal genome and transcriptome projects, which in most cases derived from an infection of the sequenced host specimen. The apicomplexan sequences were extracted from the sequence assemblies using a newly developed bioinformatic pipeline (ContamFinder) and tentatively assigned to distinct taxa employing phylogenetic methods. We analysed 920 assemblies and found 20,907 contigs of apicomplexan origin in 51 of the datasets. The contaminating species were identified as members of the apicomplexan taxa Gregarinasina, Coccidia, Piroplasmida, and Haemosporida. For example, in the platypus genome assembly, we found a high number of contigs derived from a piroplasmid parasite (presumably Theileria ornithorhynchi). For most of the infecting parasite species, no molecular data had been available previously, and some of the datasets contain sequences representing large amounts of the parasite’s gene repertoire.ConclusionOur study suggests that parasite-derived contaminations represent a valuable source of information that can help to discover and identify new parasites, and provide information on previously unknown host-parasite interactions. We, therefore, argue that uncurated assembly data should routinely be made available in addition to the final assemblies.

GFinisher: a new strategy to refine and finish bacterial genome assemblies.

Despite the development in DNA sequencing technology, improving the number and the length of reads, the process of reconstruction of complete genome sequences, the so called genome assembly, is still complex. Only 13% of the prokaryotic genome sequencing projects have been completed. Draft genome sequences deposited in public databases are fragmented in contigs and may lack the full gene complement. The aim of the present work is to identify assembly errors and improve the assembly process of bacterial genomes. The biological patterns observed in genomic sequences and the application of a priori information can allow the identification of misassembled regions, and the reorganization and improvement of the overall de novo genome assembly. GFinisher starts generating a Fuzzy GC skew graphs for each contig in an assembly and follows breaking down the contigs in critical points in order to reassemble and close them using jFGap. This has been successfully applied to dataset from 96 genome assemblies, decreasing the number of contigs by up to 86%. GFinisher can easily optimize assemblies of prokaryotic draft genomes and can be used to improve the assembly programs based on nucleotide sequence patterns in the genome. The software and source code are available at http://gfinisher.sourceforge.net/.

Improving Bacillus Altitudinis B-388 Genome Scaffolding Using Mate-Pair Next-Generation Sequencing

Bacillus species, generally regarded as soil microorganisms, are present in human gastrointestinal tract (GIT) in quantities, which cannot be explained by their entrance with food only. They are capable of growing in GIT and interacting with intestinal microbiota and host organism by excretion of enzymes and low-molecular weight compounds, which exert digestion-facilitating, antagonistic, immunomodulating, antiviral, anticancer properties or mediate cell communication. For better understanding of its probiotic potential, we have sequenced genome of Bacillus altitudinis B-388 using mate-pair technology. It allowed us to improve quality of the genome sequence. The number of contigs decreased from 59 to 8. N50 contig length increased by four times. The number of identified genes raised from 3730 to 3774 (3645 proteins and 73 RNAs) with the reduction of frameshifted genes. The calculated size of B. altitudinis B-388 genome is 3,743,699 bp, with a G + C content of 41.17 mol%. Additional incomplete prophage sequence in genome of B. altitudinis B-388 was revealed. It was found that cryptic plasmid encodes SoxR, an oxidative stress response regulator. To date, the reported sequence is the most thorough presentation of B. altitudinis genome among four whole-genome sequences of this species deposited in GenBank.

Comparison of bacterial genome assembly software for MinION data and their applicability to medical microbiology

Translating the Oxford Nanopore MinION sequencing technology into medical microbiology requires on-going analysis that keeps pace with technological improvements to the instrument and release of associated analysis software. Here, we use a multidrug-resistant Enterobacter kobei isolate as a model organism to compare open source software for the assembly of genome data, and relate this to the time taken to generate actionable information. Three software tools (PBcR, Canu and miniasm) were used to assemble MinION data and a fourth (SPAdes) was used to combine MinION and Illumina data to produce a hybrid assembly. All four had a similar number of contigs and were more contiguous than the assembly using Illumina data alone, with SPAdes producing a single chromosomal contig. Evaluation of the four assemblies to represent the genome structure revealed a single large inversion in the SPAdes assembly, which also incorrectly integrated a plasmid into the chromosomal contig. Almost 50 %, 80 % and 90 % of MinION pass reads were generated in the first 6, 9 and 12 h, respectively. Using data from the first 6 h alone led to a less accurate, fragmented assembly, but data from the first 9 or 12 h generated similar assemblies to that from 48 h sequencing. Assemblies were generated in 2 h using Canu, indicating that going from isolate to assembled data is possible in less than 48 h. MinION data identified that genes responsible for resistance were carried by two plasmids encoding resistance to carbapenem and to sulphonamides, rifampicin and aminoglycosides, respectively.

Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches.

BackgroundImproved DNA sequencing methods have transformed the field of genomics over the last decade. This has become possible due to the development of inexpensive short read sequencing technologies which have now resulted in three generations of sequencing platforms. More recently, a new fourth generation of Nanopore based single molecule sequencing technology, was developed based on MinION® sequencer which is portable, inexpensive and fast. It is capable of generating reads of length greater than 100 kb. Though it has many specific advantages, the two major limitations of the MinION reads are high error rates and the need for the development of downstream pipelines. The algorithms for error correction have already emerged, while development of pipelines is still at nascent stage.ResultsIn this study, we benchmarked available assembler algorithms to find an appropriate framework that can efficiently assemble Nanopore sequenced reads. To address this, we employed genome-scale Nanopore sequenced datasets available for E. coli and yeast genomes respectively. In order to comprehensively evaluate multiple algorithmic frameworks, we included assemblers based on de Bruijn graphs (Velvet and ABySS), Overlap Layout Consensus (OLC) (Celera) and Greedy extension (SSAKE) approaches. We analyzed the quality, accuracy of the assemblies as well as the computational performance of each of the assemblers included in our benchmark. Our analysis unveiled that OLC-based algorithm, Celera, could generate a high quality assembly with ten times higher N50 & mean contig values as well as one-fifth the number of total number of contigs compared to other tools. Celera was also found to exhibit an average genome coverage of 12 % in E. coli dataset and 70 % in Yeast dataset as well as relatively lesser run times. In contrast, de Bruijn graph based assemblers Velvet and ABySS generated the assemblies of moderate quality, in less time when there is no limitation on the memory allocation, while greedy extension based algorithm SSAKE generated an assembly of very poor quality but with genome coverage of 90 % on yeast dataset.ConclusionOLC can be considered as a favorable algorithmic framework for the development of assembler tools for Nanopore-based data, followed by de Bruijn based algorithms as they consume relatively less or similar run times as OLC-based algorithms for generating assembly, irrespective of the memory allocated for the task. However, few improvements must be made to the existing de Bruijn implementations in order to generate an assembly with reasonable quality. Our findings should help in stimulating the development of novel assemblers for handling Nanopore sequence data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2895-8) contains supplementary material, which is available to authorized users.

Comparative performance of transcriptome assembly methods for non-model organisms.

BackgroundThe technological revolution in next-generation sequencing has brought unprecedented opportunities to study any organism of interest at the genomic or transcriptomic level. Transcriptome assembly is a crucial first step for studying the molecular basis of phenotypes of interest using RNA-Sequencing (RNA-Seq). However, the optimal strategy for assembling vast amounts of short RNA-Seq reads remains unresolved, especially for organisms without a sequenced genome. This study compared four transcriptome assembly methods, including a widely used de novo assembler (Trinity), two transcriptome re-assembly strategies utilizing proteomic and genomic resources from closely related species (reference-based re-assembly and TransPS) and a genome-guided assembler (Cufflinks).ResultsThese four assembly strategies were compared using a comprehensive transcriptomic database of Aedes albopictus, for which a genome sequence has recently been completed. The quality of the various assemblies was assessed by the number of contigs generated, contig length distribution, percent paired-end read mapping, and gene model representation via BLASTX. Our results reveal that de novo assembly generates a similar number of gene models relative to genome-guided assembly with a fragmented reference, but produces the highest level of redundancy and requires the most computational power. Using a closely related reference genome to guide transcriptome assembly can generate biased contig sequences. Increasing the number of reads used in the transcriptome assembly tends to increase the redundancy within the assembly and decrease both median contig length and percent identity between contigs and reference protein sequences.ConclusionsThis study provides general guidance for transcriptome assembly of RNA-Seq data from organisms with or without a sequenced genome. The optimal transcriptome assembly strategy will depend upon the subsequent downstream analyses. However, our results emphasize the efficacy of de novo assembly, which can be as effective as genome-guided assembly when the reference genome assembly is fragmented. If a genome assembly and sufficient computational resources are available, it can be beneficial to combine de novo and genome-guided assemblies. Caution should be taken when using a closely related reference genome to guide transcriptome assembly. The quantity of read pairs used in the transcriptome assembly does not necessarily correlate with the quality of the assembly.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2923-8) contains supplementary material, which is available to authorized users.

Here We Are, But Where Do We Go? A Systematic Review of Crustacean Transcriptomic Studies from 2014–2015

Despite their economic, ecological, and experimental importance, genomic resources remain scarce for crustaceans. In lieu of genomes, many researchers have taken advantage of technological advancements to instead sequence and assemble crustacean transcriptomes de novo However, there is little consensus on what standard operating procedures are, or should be, for the field. Here, we systematically reviewed 53 studies published during 2014-2015 that utilized transcriptomic resources from this taxonomic group in an effort to identify commonalities as well as potential weaknesses that have applicability beyond just crustaceans. In general, these studies utilized RNA-Seq data, both novel and publicly available, to characterize transcriptomes and/or identify differentially expressed genes (DEGs) between treatments. Although the software suite Trinity was popular in assembly pipelines and other programs were also commonly employed, many studies failed to report crucial details regarding bioinformatic methodologies, including read mappers and the utilized parameters in identifying and characterizing DEGs. Annotation percentages for assembled transcriptomic contigs were low, averaging 32% overall. While other metrics, such as numbers of contigs and DEGs reported, correlated with the number of sequence reads utilized per sample, these did reach apparent saturation with increasing sequencing depth. Most disturbingly, a number of studies (55%) reported DEGs based on non-replicated experimental designs and single biological replicates for each treatment. Given this, we suggest future RNA-Seq experiments targeting transcriptome characterization conduct deeper (i.e., 50-100 M reads) sequencing while those examining differential expression instead focus more on increased biological replicates at shallower (i.e., ∼10-20 M reads/sample) sequencing depths. Moreover, the community must avoid submitting for review, or accepting for publication, non-replicated differential expression studies. Finally, mining the ever growing publicly available transcriptomic data from crustaceans will allow future studies to focus on hypothesis-driven research instead of continuing to simply characterize transcriptomes. As an example of this, we utilized neurotoxin sequences from the recently described remipede venom gland transcriptome in conjunction with publicly available crustacean transcriptomic data to derive preliminary results and hypotheses regarding the evolution of venom in crustaceans.

De Novo Assembly of Human Herpes Virus Type 1 (HHV-1) Genome, Mining of Non-Canonical Structures and Detection of Novel Drug-Resistance Mutations Using Short- and Long-Read Next Generation Sequencing Technologies.

Human herpesvirus type 1 (HHV-1) has a large double-stranded DNA genome of approximately 152 kbp that is structurally complex and GC-rich. This makes the assembly of HHV-1 whole genomes from short-read sequencing data technically challenging. To improve the assembly of HHV-1 genomes we have employed a hybrid genome assembly protocol using data from two sequencing technologies: the short-read Roche 454 and the long-read Oxford Nanopore MinION sequencers. We sequenced 18 HHV-1 cell culture-isolated clinical specimens collected from immunocompromised patients undergoing antiviral therapy. The susceptibility of the samples to several antivirals was determined by plaque reduction assay. Hybrid genome assembly resulted in a decrease in the number of contigs in 6 out of 7 samples and an increase in N(G)50 and N(G)75 of all 7 samples sequenced by both technologies. The approach also enhanced the detection of non-canonical contigs including a rearrangement between the unique (UL) and repeat (T/IRL) sequence regions of one sample that was not detectable by assembly of 454 reads alone. We detected several known and novel resistance-associated mutations in UL23 and UL30 genes. Genome-wide genetic variability ranged from <1% to 53% of amino acids in each gene exhibiting at least one substitution within the pool of samples. The UL23 gene had one of the highest genetic variabilities at 35.2% in keeping with its role in development of drug resistance. The assembly of accurate, full-length HHV-1 genomes will be useful in determining genetic determinants of drug resistance, virulence, pathogenesis and viral evolution. The numerous, complex repeat regions of the HHV-1 genome currently remain a barrier towards this goal.

Unsupervised Binning of Metagenomic Assembled Contigs Using Improved Fuzzy C-Means Method

Metagenomic contigs binning is a necessary step of metagenome analysis. After assembly, the number of contigs belonging to different genomes is usually unequal. So a metagenomic contigs dataset is a kind of imbalanced dataset and traditional fuzzy c-means method (FCM) fails to handle it very well. In this paper, we will introduce an improved version of fuzzy c-means method (IFCM) into metagenomic contigs binning. First, tetranucleotide frequencies are calculated for every contig. Second, the number of bins is roughly estimated by the distribution of genome lengths of a complete set of non-draft sequenced microbial genomes from NCBI. Then, IFCM is used to cluster DNA contigs with the estimated result. Finally, a clustering validity function is utilized to determine the binning result. We tested this method on a synthetic and two real datasets and experimental results have showed the effectiveness of this method compared with other tools.