De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer

Whole genome assembly of a natto production strain Bacillus subtilis natto from very short read data

Background

Bacillus subtilis natto is closely related to the laboratory standard strain B. subtilis Marburg 168, and functions as a starter for the production of the traditional Japanese food "natto" made from soybeans. Although re-sequencing whole genomes of several laboratory domesticated B. subtilis 168 derivatives has already been attempted using short read sequencing data, the assembly of the whole genome sequence of a closely related strain, B. subtilis natto, from very short read data is more challenging, particularly with our aim to assemble one fully connected scaffold from short reads around 35 bp in length.

Results

We applied a comparative genome assembly method, which combines de novo assembly and reference guided assembly, to one of the B. subtilis natto strains. We successfully assembled 28 scaffolds and managed to avoid substantial fragmentation. Completion of the assembly through long PCR experiments resulted in one connected scaffold for B. subtilis natto. Based on the assembled genome sequence, our orthologous gene analysis between natto BEST195 and Marburg 168 revealed that 82.4% of 4375 predicted genes in BEST195 are one-to-one orthologous to genes in 168, with two genes in-paralog, 3.2% are deleted in 168, 14.3% are inserted in BEST195, and 5.9% of genes present in 168 are deleted in BEST195. The natto genome contains the same alleles in the promoter region of degQ and the coding region of swrAA as the wild strain, RO-FF-1.

These are specific for γ-PGA production ability, which is related to natto production. Further, the B. subtilis natto strain completely lacked a polyketide synthesis operon, disrupted the plipastatin production operon, and possesses previously unidentified transposases.

Conclusions

The determination of the whole genome sequence of Bacillus subtilis natto provided detailed analyses of a set of genes related to natto production, demonstrating the number and locations of insertion sequences that B. subtilis natto harbors but B. subtilis 168 lacks. Multiple genome-level comparisons among five closely related Bacillus species were also carried out. The determined genome sequence of B. subtilis natto and gene annotations are available from the Natto genome browser http://natto-genome.org/.

A new strategy for genome assembly using short sequence reads and reduced representation libraries

We have developed a novel approach for using massively parallel short-read sequencing to generate fast and inexpensive de novo genomic assemblies comparable to those generated by capillary-based methods. The ultrashort (<100 base) sequences generated by this technology pose specific biological and computational challenges for de novo assembly of large genomes. To account for this, we devised a method for experimentally partitioning the genome using reduced representation (RR) libraries prior to assembly. We use two restriction enzymes independently to create a series of overlapping fragment libraries, each containing a tractable subset of the genome. Together, these libraries allow us to reassemble the entire genome without the need of a reference sequence. As proof of concept, we applied this approach to sequence and assembled the majority of the 125-Mb Drosophila melanogaster genome. We subsequently demonstrate the accuracy of our assembly method with meaningful comparisons against the current available D. melanogaster reference genome (dm3). The ease of assembly and accuracy for comparative genomics suggest that our approach will scale to future mammalian genome-sequencing efforts, saving both time and money without sacrificing quality.

Complete genome sequence of the fire blight pathogen Erwinia amylovora CFBP 1430 and comparison to other Erwinia spp

Fire blight, caused by the enterobacterium Erwinia amylovora, is a devastating disease of rosaceous plants that has global economic importance for apple and pear production and trade. The complete genome of E. amylovora CFBP 1430 was sequenced, annotated, and compared with the genomes of other Erwinia spp. Several singleton and shared features of the E. amylovora CFBP 1430 genome were identified that offer a first view into evolutionary aspects within the genus Erwinia. Comparative genomics identified or clarified virulence and fitness determinants and secretion systems. Novel insights revealed in the genome of E. amylovora CFBP 1430 hold potential for exploitation to improve the design of more effective fire blight control strategies.

Visualizing genomes: techniques and challenges

As our ability to generate sequencing data continues to increase, data analysis is replacing data generation as the rate-limiting step in genomics studies. Here we provide a guide to genomic data visualization tools that facilitate analysis tasks by enabling researchers to explore, interpret and manipulate their data, and in some cases perform on-the-fly computations. We will discuss graphical methods designed for the analysis of de novo sequencing assemblies and read alignments, genome browsing, and comparative genomics, highlighting the strengths and limitations of these approaches and the challenges ahead.

RNA-seq: from technology to biology

Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction

Background

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

Results

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

Conclusions

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

Complete genome sequence of the fire blight pathogen Erwinia pyrifoliae DSM 12163T and comparative genomic insights into plant pathogenicity

Background

Erwinia pyrifoliae is a newly described necrotrophic pathogen, which causes fire blight on Asian (Nashi) pear and is geographically restricted to Eastern Asia. Relatively little is known about its genetics compared to the closely related main fire blight pathogen E. amylovora.

Results

The genome of the type strain of E. pyrifoliae strain DSM 12163^T, was sequenced using both 454 and Solexa pyrosequencing and annotated. The genome contains a circular chromosome of 4.026 Mb and four small plasmids. Based on their respective role in virulence in E. amylovora or related organisms, we identified several putative virulence factors, including type III and type VI secretion systems and their effectors, flagellar genes, sorbitol metabolism, iron uptake determinants, and quorum-sensing components. A deletion in the rpoS gene covering the most conserved region of the protein was identified which may contribute to the difference in virulence/host-range compared to E. amylovora. Comparative genomics with the pome fruit epiphyte Erwinia tasmaniensis Et1/99 showed that both species are overall highly similar, although specific differences were identified, for example the presence of some phage gene-containing regions and a high number of putative genomic islands containing transposases in the E. pyrifoliae DSM 12163^T genome.

Conclusions

The E. pyrifoliae genome is an important addition to the published genome of E. tasmaniensis and the unfinished genome of E. amylovora providing a foundation for re-sequencing additional strains that may shed light on the evolution of the host-range and virulence/pathogenicity of this important group of plant-associated bacteria.

Sequencing and genome assembly using next-generation technologies

Several sequencing technologies have been introduced in recent years that dramatically outperform the traditional Sanger technology in terms of throughput and cost. The data generated by these technologies are characterized by generally shorter read lengths (as low as 35 bp) and different error characteristics than Sanger data. Existing software tools for assembly and analysis of sequencing data are, therefore, ill-suited to handle the new types of data generated. This paper surveys the recent software packages aimed specifically at analyzing new generation sequencing data.

Molecular Pathology and Infectious Diseases

This chapter discusses the pathogenesis and progression of infectious diseases. Agricultural and industrial development has resulted in the increased density of humans living in close proximity to each other. This lifestyle change from more rural existence has brought humans in closer proximity to wild animals that harbor potential future human pathogens. Most diseases are transmitted by insect vectors. Molecular diagnostic tests can be divided into two primary groups. The first are tests designed to detect the presence of mutations in the human genome that are associated with specific diseases. These tests need to be performed only once in a specific individual’s lifetime. The second group of molecular diagnostic assays is designed to detect infectious agents or the recurrence of a mutation specifically associated with a tumor the patient has had in the past. Bacterial, viral, fungal, or parasitic infections can be eradicated and recur at a time in the future requiring repetition of the same molecular assay for detection. Minimal residual disease detection refers to the analysis of tissue/cells in a patient previously diagnosed with a malignancy to evaluate if therapy was completed successfully or if rare malignant cells are present.

Whole genome sequencing

Whole genome sequencing provides the most comprehensive collection of an individual's genetic variation. With the falling costs of sequencing technology, we envision paradigm shift from microarray-based genotyping studies to whole genome sequencing. We review methodologies for whole genome sequencing. There are two approaches for assembling short shotgun sequence reads into longer contiguous genomic sequences. In the de novo assembly approach, sequence reads are compared to each other, and then overlapped to build longer contiguous sequences. The reference-based assembly approach involves mapping each read to a reference genome sequence. We discuss methods for identifying genetic variation (single nucleotide polymorphisms, small indels, and copy number variants) and building haplotypes from genome assemblies, and discuss potential pitfalls. We expect methodologies to evolve rapidly as sequencing technologies improve and more human genomes are sequenced.

High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach

BACKGROUND

With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive.

METHODS/PRINCIPAL FINDINGS

We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA.

CONCLUSIONS/SIGNIFICANCE

This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

Pebble and rock band: heuristic resolution of repeats and scaffolding in the velvet short-read de novo assembler

Background

Despite the short length of their reads, micro-read sequencing technologies have shown their usefulness for de novo sequencing. However, especially in eukaryotic genomes, complex repeat patterns are an obstacle to large assemblies.

Principal Findings

We present a novel heuristic algorithm, Pebble, which uses paired-end read information to resolve repeats and scaffold contigs to produce large-scale assemblies. In simulations, we can achieve weighted median scaffold lengths (N50) of above 1 Mbp in Bacteria and above 100 kbp in more complex organisms. Using real datasets we obtained a 96 kbp N50 in Pseudomonas syringae and a unique 147 kbp scaffold of a ferret BAC clone. We also present an efficient algorithm called Rock Band for the resolution of repeats in the case of mixed length assemblies, where different sequencing platforms are combined to obtain a cost-effective assembly.

Conclusions

These algorithms extend the utility of short read only assemblies into large complex genomes. They have been implemented and made available within the open-source Velvet short-read de novo assembler.

De novo assembly of human genomes with massively parallel short read sequencing

Next-generation massively parallel DNA sequencing technologies provide ultrahigh throughput at a substantially lower unit data cost; however, the data are very short read length sequences, making de novo assembly extremely challenging. Here, we describe a novel method for de novo assembly of large genomes from short read sequences. We successfully assembled both the Asian and African human genome sequences, achieving an N50 contig size of 7.4 and 5.9 kilobases (kb) and scaffold of 446.3 and 61.9 kb, respectively. The development of this de novo short read assembly method creates new opportunities for building reference sequences and carrying out accurate analyses of unexplored genomes in a cost-effective way.

New approaches for functional genomic studies in staphylococci

Functional transcriptomics studies have resulted in interesting insights into Staphylococcus aureus diversity and pathogenicity. Here we review the principles, advantages and disadvantages of recent technical developments in the field of transcriptomics and their potential impact on S. aureus research.

BOAT: Basic Oligonucleotide Alignment Tool

Background

Next-generation DNA sequencing technologies generate tens of millions of sequencing reads in one run. These technologies are now widely used in biology research such as in genome-wide identification of polymorphisms, transcription factor binding sites, methylation states, and transcript expression profiles. Mapping the sequencing reads to reference genomes efficiently and effectively is one of the most critical analysis tasks. Although several tools have been developed, their performance suffers when both multiple substitutions and insertions/deletions (indels) occur together.

Results

We report a new algorithm, Basic Oligonucleotide Alignment Tool (BOAT) that can accurately and efficiently map sequencing reads back to the reference genome. BOAT can handle several substitutions and indels simultaneously, a useful feature for identifying SNPs and other genomic structural variations in functional genomic studies. For better handling of low-quality reads, BOAT supports a "3'-end Trimming Mode" to build local optimized alignment for sequencing reads, further improving sensitivity. BOAT calculates an E-value for each hit as a quality assessment and provides customizable post-mapping filters for further mapping quality control.

Conclusion

Evaluations on both real and simulation datasets suggest that BOAT is capable of mapping large volumes of short reads to reference sequences with better sensitivity and lower memory requirement than other currently existing algorithms. The source code and pre-compiled binary packages of BOAT are publicly available for download at http://boat.cbi.pku.edu.cn under GNU Public License (GPL). BOAT can be a useful new tool for functional genomics studies.

Increasing phylogenetic resolution at low taxonomic levels using massively parallel sequencing of chloroplast genomes

BACKGROUND

Molecular evolutionary studies share the common goal of elucidating historical relationships, and the common challenge of adequately sampling taxa and characters. Particularly at low taxonomic levels, recent divergence, rapid radiations, and conservative genome evolution yield limited sequence variation, and dense taxon sampling is often desirable. Recent advances in massively parallel sequencing make it possible to rapidly obtain large amounts of sequence data, and multiplexing makes extensive sampling of megabase sequences feasible. Is it possible to efficiently apply massively parallel sequencing to increase phylogenetic resolution at low taxonomic levels?

RESULTS

We reconstruct the infrageneric phylogeny of Pinus from 37 nearly-complete chloroplast genomes (average 109 kilobases each of an approximately 120 kilobase genome) generated using multiplexed massively parallel sequencing. 30/33 ingroup nodes resolved with > or = 95% bootstrap support; this is a substantial improvement relative to prior studies, and shows massively parallel sequencing-based strategies can produce sufficient high quality sequence to reach support levels originally proposed for the phylogenetic bootstrap. Resampling simulations show that at least the entire plastome is necessary to fully resolve Pinus, particularly in rapidly radiating clades. Meta-analysis of 99 published infrageneric phylogenies shows that whole plastome analysis should provide similar gains across a range of plant genera. A disproportionate amount of phylogenetic information resides in two loci (ycf1, ycf2), highlighting their unusual evolutionary properties.

CONCLUSION

Plastome sequencing is now an efficient option for increasing phylogenetic resolution at lower taxonomic levels in plant phylogenetic and population genetic analyses. With continuing improvements in sequencing capacity, the strategies herein should revolutionize efforts requiring dense taxon and character sampling, such as phylogeographic analyses and species-level DNA barcoding.

Simultaneous assay of every Salmonella Typhi gene using one million transposon mutants

Very high-throughput sequencing technologies need to be matched by high-throughput functional studies if we are to make full use of the current explosion in genome sequences. We have generated a very large bacterial mutant pool, consisting of an estimated 1.1 million transposon mutants and we have used genomic DNA from this mutant pool, and Illumina nucleotide sequencing to prime from the transposon and sequence into the adjacent target DNA. With this method, which we have called TraDIS (transposon directed insertion-site sequencing), we have been able to map 370,000 unique transposon insertion sites to the Salmonella enterica serovar Typhi chromosome. The unprecedented density and resolution of mapped insertion sites, an average of one every 13 base pairs, has allowed us to assay simultaneously every gene in the genome for essentiality and generate a genome-wide list of candidate essential genes. In addition, the semiquantitative nature of the assay allowed us to identify genes that are advantageous and those that are disadvantageous for growth under standard laboratory conditions. Comparison of the mutant pool following growth in the presence or absence of ox bile enabled every gene to be assayed for its contribution toward bile tolerance, a trait required of any enteric bacterium and for carriage of S. Typhi in the gall bladder. This screen validated our hypothesis that we can simultaneously assay every gene in the genome to identify niche-specific essential genes.

Maximum likelihood genome assembly

Whole genome shotgun assembly is the process of taking many short sequenced segments (reads) and reconstructing the genome from which they originated. We demonstrate how the technique of bidirected network flow can be used to explicitly model the double-stranded nature of DNA for genome assembly. By combining an algorithm for the Chinese Postman Problem on bidirected graphs with the construction of a bidirected de Bruijn graph, we are able to find the shortest double-stranded DNA sequence that contains a given set of k-long DNA molecules. This is the first exact polynomial time algorithm for the assembly of a double-stranded genome. Furthermore, we propose a maximum likelihood framework for assembling the genome that is the most likely source of the reads, in lieu of the standard maximum parsimony approach (which finds the shortest genome subject to some constraints). In this setting, we give a bidirected network flow-based algorithm that, by taking advantage of high coverage, accurately estimates the copy counts of repeats in a genome. Our second algorithm combines these predicted copy counts with matepair data in order to assemble the reads into contigs. We run our algorithms on simulated read data from Escherichia coli and predict copy counts with extremely high accuracy, while assembling long contigs.

Comparative genomic and phylogeographic analysis of Mycobacterium leprae

Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38x coverage) and NHDP63 (46x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy.

RNA-seq: from technology to biology

Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

Large scale single nucleotide polymorphism discovery in unsequenced genomes using second generation high throughput sequencing technology: applied to turkey

BACKGROUND

The development of second generation sequencing methods has enabled large scale DNA variation studies at moderate cost. For the high throughput discovery of single nucleotide polymorphisms (SNPs) in species lacking a sequenced reference genome, we set-up an analysis pipeline based on a short read de novo sequence assembler and a program designed to identify variation within short reads. To illustrate the potential of this technique, we present the results obtained with a randomly sheared, enzymatically generated, 2-3 kbp genome fraction of six pooled Meleagris gallopavo (turkey) individuals.

RESULTS

A total of 100 million 36 bp reads were generated, representing approximately 5-6% (approximately 62 Mbp) of the turkey genome, with an estimated sequence depth of 58. Reads consisting of bases called with less than 1% error probability were selected and assembled into contigs. Subsequently, high throughput discovery of nucleotide variation was performed using sequences with more than 90% reliability by using the assembled contigs that were 50 bp or longer as the reference sequence. We identified more than 7,500 SNPs with a high probability of representing true nucleotide variation in turkeys. Increasing the reference genome by adding publicly available turkey BAC-end sequences increased the number of SNPs to over 11,000. A comparison with the sequenced chicken genome indicated that the assembled turkey contigs were distributed uniformly across the turkey genome. Genotyping of a representative sample of 340 SNPs resulted in a SNP conversion rate of 95%. The correlation of the minor allele count (MAC) and observed minor allele frequency (MAF) for the validated SNPs was 0.69.

CONCLUSION

We provide an efficient and cost-effective approach for the identification of thousands of high quality SNPs in species currently lacking a sequenced genome and applied this to turkey. The methodology addresses a random fraction of the genome, resulting in an even distribution of SNPs across the targeted genome.

Novel software package for cross-platform transcriptome analysis (CPTRA)

Background

Next-generation sequencing techniques enable several novel transcriptome profiling approaches. Recent studies indicated that digital gene expression profiling based on short sequence tags has superior performance as compared to other transcriptome analysis platforms including microarrays. However, the transcriptomic analysis with tag-based methods often depends on available genome sequence. The use of tag-based methods in species without genome sequence should be complemented by other methods such as cDNA library sequencing. The combination of different next generation sequencing techniques like 454 pyrosequencing and Illumina Genome Analyzer (Solexa) will enable high-throughput and accurate global gene expression profiling in species with limited genome information. The combination of transcriptome data acquisition methods requires cross-platform transcriptome data analysis platforms, including a new software package for data processing.

Results

Here we presented a software package, CPTRA: Cross-Platform TRanscriptome Analysis, to analyze transcriptome profiling data from separate methods. The software package is available at http://people.tamu.edu/~syuan/cptra/cptra.html. It was applied to the case study of non-target site glyphosate resistance in horseweed; and the data was mined to discover resistance target gene(s). For the software, the input data included a long-read sequence dataset with proper annotation, and a short-read sequence tag dataset for the quantification of transcripts. By combining the two datasets, the software carries out the unique sequence tag identification, tag counting for transcript quantification, and cross-platform sequence matching functions, whereby the short sequence tags can be annotated with a function, level of expression, and Gene Ontology (GO) classification. Multiple sequence search algorithms were implemented and compared. The analysis highlighted the importance of transport genes in glyphosate resistance and identified several candidate genes for down-stream analysis.

Conclusion

CPTRA is a powerful software package for next generation sequencing-based transcriptome profiling in species with limited genome information. According to our case study, the strategy can greatly broaden the application of the next generation sequencing for transcriptome analysis in species without reference genome sequence.

Genome structure of a Saccharomyces cerevisiae strain widely used in bioethanol production

Bioethanol is a biofuel produced mainly from the fermentation of carbohydrates derived from agricultural feedstocks by the yeast Saccharomyces cerevisiae. One of the most widely adopted strains is PE-2, a heterothallic diploid naturally adapted to the sugar cane fermentation process used in Brazil. Here we report the molecular genetic analysis of a PE-2 derived diploid (JAY270), and the complete genome sequence of a haploid derivative (JAY291). The JAY270 genome is highly heterozygous (approximately 2 SNPs/kb) and has several structural polymorphisms between homologous chromosomes. These chromosomal rearrangements are confined to the peripheral regions of the chromosomes, with breakpoints within repetitive DNA sequences. Despite its complex karyotype, this diploid, when sporulated, had a high frequency of viable spores. Hybrid diploids formed by outcrossing with the laboratory strain S288c also displayed good spore viability. Thus, the rearrangements that exist near the ends of chromosomes do not impair meiosis, as they do not span regions that contain essential genes. This observation is consistent with a model in which the peripheral regions of chromosomes represent plastic domains of the genome that are free to recombine ectopically and experiment with alternative structures. We also explored features of the JAY270 and JAY291 genomes that help explain their high adaptation to industrial environments, exhibiting desirable phenotypes such as high ethanol and cell mass production and high temperature and oxidative stress tolerance. The genomic manipulation of such strains could enable the creation of a new generation of industrial organisms, ideally suited for use as delivery vehicles for future bioenergy technologies.

ALLPATHS 2: small genomes assembled accurately and with high continuity from short paired reads

Allpaths2, a method for accurately assembling small genomes with high continuity using short paired reads.

We demonstrate that genome sequences approaching finished quality can be generated from short paired reads. Using 36 base (fragment) and 26 base (jumping) reads from five microbial genomes of varied GC composition and sizes up to 40 Mb, ALLPATHS2 generated assemblies with long, accurate contigs and scaffolds. Velvet and EULER-SR were less accurate. For example, for Escherichia coli, the fraction of 10-kb stretches that were perfect was 99.8% (ALLPATHS2), 68.7% (Velvet), and 42.1% (EULER-SR).

Parametric complexity of sequence assembly: theory and applications to next generation sequencing

In recent years, a flurry of new DNA sequencing technologies have altered the landscape of genomics, providing a vast amount of sequence information at a fraction of the costs that were previously feasible. The task of assembling these sequences into a genome has, however, still remained an algorithmic challenge that is in practice answered by heuristic solutions. In order to design better assembly algorithms and exploit the characteristics of sequence data from new technologies, we need an improved understanding of the parametric complexity of the assembly problem. In this article, we provide a first theoretical study in this direction, exploring the connections between repeat complexity, read lengths, overlap lengths and coverage in determining the "hard" instances of the assembly problem. Our work suggests at least two ways in which existing assemblers can be extended in a rigorous fashion, in addition to delineating directions for future theoretical investigations.

PAVE: program for assembling and viewing ESTs

Background

New sequencing technologies are rapidly emerging. Many laboratories are simultaneously working with the traditional Sanger ESTs and experimenting with ESTs generated by the 454 Life Science sequencers. Though Sanger ESTs have been used to generate contigs for many years, no program takes full advantage of the 5' and 3' mate-pair information, hence, many tentative transcripts are assembled into two separate contigs. The new 454 technology has the benefit of high-throughput expression profiling, but introduces time and space problems for assembling large contigs.

Results

The PAVE (Program for Assembling and Viewing ESTs) assembler takes advantage of the 5' and 3' mate-pair information by requiring that the mate-pairs be assembled into the same contig and joined by n's if the two sub-contigs do not overlap. It handles the depth of 454 data sets by "burying" similar ESTs during assembly, which retains the expression level information while circumventing time and space problems. PAVE uses MegaBLAST for the clustering step and CAP3 for assembly, however it assembles incrementally to enforce the mate-pair constraint, bury ESTs, and reduce incorrect joins and splits. The PAVE data management system uses a MySQL database to store multiple libraries of ESTs along with their metadata; the management system allows multiple assemblies with variations on libraries and parameters. Analysis routines provide standard annotation for the contigs including a measure of differentially expressed genes across the libraries. A Java viewer program is provided for display and analysis of the results. Our results clearly show the benefit of using the PAVE assembler to explicitly use mate-pair information and bury ESTs for large contigs.

Conclusion

The PAVE assembler provides a software package for assembling Sanger and/or 454 ESTs. The assembly software, data management software, Java viewer and user's guide are freely available.

A draft genome sequence and functional screen reveals the repertoire of type III secreted proteins of Pseudomonas syringae pathovar tabaci 11528

Background

Pseudomonas syringae is a widespread bacterial pathogen that causes disease on a broad range of economically important plant species. Pathogenicity of P. syringae strains is dependent on the type III secretion system, which secretes a suite of up to about thirty virulence 'effector' proteins into the host cytoplasm where they subvert the eukaryotic cell physiology and disrupt host defences. P. syringae pathovar tabaci naturally causes disease on wild tobacco, the model member of the Solanaceae, a family that includes many crop species as well as on soybean.

Results

We used the 'next-generation' Illumina sequencing platform and the Velvet short-read assembly program to generate a 145X deep 6,077,921 nucleotide draft genome sequence for P. syringae pathovar tabaci strain 11528. From our draft assembly, we predicted 5,300 potential genes encoding proteins of at least 100 amino acids long, of which 303 (5.72%) had no significant sequence similarity to those encoded by the three previously fully sequenced P. syringae genomes. Of the core set of Hrp Outer Proteins that are conserved in three previously fully sequenced P. syringae strains, most were also conserved in strain 11528, including AvrE1, HopAH2, HopAJ2, HopAK1, HopAN1, HopI, HopJ1, HopX1, HrpK1 and HrpW1. However, the hrpZ1 gene is partially deleted and hopAF1 is completely absent in 11528. The draft genome of strain 11528 also encodes close homologues of HopO1, HopT1, HopAH1, HopR1, HopV1, HopAG1, HopAS1, HopAE1, HopAR1, HopF1, and HopW1 and a degenerate HopM1'. Using a functional screen, we confirmed that hopO1, hopT1, hopAH1, hopM1', hopAE1, hopAR1, and hopAI1' are part of the virulence-associated HrpL regulon, though the hopAI1' and hopM1' sequences were degenerate with premature stop codons. We also discovered two additional HrpL-regulated effector candidates and an HrpL-regulated distant homologue of avrPto1.

Conclusion

The draft genome sequence facilitates the continued development of P. syringae pathovar tabaci on wild tobacco as an attractive model system for studying bacterial disease on plants. The catalogue of effectors sheds further light on the evolution of pathogenicity and host-specificity as well as providing a set of molecular tools for the study of plant defence mechanisms. We also discovered several large genomic regions in Pta 11528 that do not share detectable nucleotide sequence similarity with previously sequenced Pseudomonas genomes. These regions may include horizontally acquired islands that possibly contribute to pathogenicity or epiphytic fitness of Pta 11528.

High-throughput sequencing reveals suppressors of Vibrio cholerae rpoE mutations: one fewer porin is enough

Analyses of suppressor mutations have been extremely valuable in understanding gene function. However, techniques for mapping suppressor mutations are not available for most bacterial species. Here, we used high-throughput sequencing technology to identify spontaneously arising suppressor mutations that enabled disruption of rpoE (which encodes sigma(E)) in Vibrio cholerae, the agent of cholera. The alternative sigma factor sigma(E), which is activated by envelope stress, promotes expression of factors that help preserve and/or restore cell envelope integrity. In Escherichia coli, rpoE is an essential gene that can only be disrupted in the presence of additional suppressor mutations. Among a panel of independent V. cholerae rpoE mutants, more than 75% contain suppressor mutations that reduce production of OmpU, V. cholerae's principal outer membrane porin. OmpU appears to be a key determinant of V. cholerae's requirement for and production of sigma(E). Such dependence upon a single factor contrasts markedly with regulation of sigma(E) in E. coli, in which numerous factors contribute to its activation and none is dominant. We also identified a suppressor mutation that differs from all previously described suppressors in that it elevates, rather than reduces, sigma(E)'s activity. Finally, analyses of a panel of rpoE mutants shed light on the mechanisms by which suppressor mutations may arise in V. cholerae.

Genome sequencing of linezolid-resistant Streptococcus pneumoniae mutants reveals novel mechanisms of resistance

Linezolid is a member of a novel class of antibiotics, with resistance already being reported. We used whole-genome sequencing on three independent Streptococcus pneumoniae strains made resistant to linezolid in vitro in a step-by-step fashion. Analysis of the genome assemblies revealed mutations in the 23S rRNA gene in all mutants including, notably, G2576T, a previously recognized resistance mutation. Mutations in an additional 31 genes were also found in at least one of the three sequenced genomes. We concentrated on three new mutations that were found in at least two independent mutants. All three mutations were experimentally confirmed to be involved in antibiotic resistance. Mutations upstream of the ABC transporter genes spr1021 and spr1887 were correlated with increased expression of these genes and neighboring genes of the same operon. Gene inactivation supported a role for these ABC transporters in resistance to linezolid and other antibiotics. The hypothetical protein spr0333 contains an RNA methyltransferase domain, and mutations within that domain were found in all S. pneumoniae linezolid-resistant strains. Primer extension experiments indicated that spr0333 methylates G2445 of the 23S rRNA and mutations in spr0333 abolished this methylation. Reintroduction of a nonmutated version of spr0333 in resistant bacteria reestablished G2445 methylation and led to cells being more sensitive to linezolid and other antibiotics. Interestingly, the spr0333 ortholog was also mutated in a linezolid-resistant clinical Staphylococcus aureus isolate. Whole-genome sequencing and comparative analyses of S. pneumoniae resistant isolates was useful for discovering novel resistance mutations.

SHREC: a short-read error correction method

MOTIVATION

Second-generation sequencing technologies produce a massive amount of short reads in a single experiment. However, sequencing errors can cause major problems when using this approach for de novo sequencing applications. Moreover, existing error correction methods have been designed and optimized for shotgun sequencing. Therefore, there is an urgent need for the design of fast and accurate computational methods and tools for error correction of large amounts of short read data.

RESULTS

We present SHREC, a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches. SHREC is available as an efficient open-source Java implementation that allows processing of 10 million of short reads on a standard workstation.

A fast hybrid short read fragment assembly algorithm

SUMMARY

The shorter and vastly more numerous reads produced by second-generation sequencing technologies require new tools that can assemble massive numbers of reads in reasonable time. Existing short-read assembly tools can be classified into two categories: greedy extension-based and graph-based. While the graph-based approaches are generally superior in terms of assembly quality, the computer resources required for building and storing a huge graph are very high. In this article, we present Taipan, an assembly algorithm which can be viewed as a hybrid of these two approaches. Taipan uses greedy extensions for contig construction but at each step realizes enough of the corresponding read graph to make better decisions as to how assembly should continue. We show that this approach can achieve an assembly quality at least as good as the graph-based approaches used in the popular Edena and Velvet assembly tools using a moderate amount of computing resources.

Genome assembly reborn: recent computational challenges

Research into genome assembly algorithms has experienced a resurgence due to new challenges created by the development of next generation sequencing technologies. Several genome assemblers have been published in recent years specifically targeted at the new sequence data; however, the ever-changing technological landscape leads to the need for continued research. In addition, the low cost of next generation sequencing data has led to an increased use of sequencing in new settings. For example, the new field of metagenomics relies on large-scale sequencing of entire microbial communities instead of isolate genomes, leading to new computational challenges. In this article, we outline the major algorithmic approaches for genome assembly and describe recent developments in this domain.

Next-generation sequencing approaches in genetic rodent model systems to study functional effects of human genetic variation

Rapid advances in DNA sequencing improve existing techniques and enable new approaches in genetics and functional genomics, bringing about unprecedented coverage, resolution and sensitivity. Enhanced toolsets can facilitate the untangling of connections between genomic variation, environmental factors and phenotypic effects, providing novel opportunities, but may also pose challenges in data interpretation, especially in highly heterogeneous human populations. Laboratory rodent strains, however, offer a variety of tailored model systems with controlled genetic backgrounds, facilitating complex genotype/phenotype relationship studies. In this review we discuss the advent of massively parallel sequencing, its methodological advantage for molecular analysis in model organisms and the expectation of increased understanding of biologically relevant consequences of human genetic variation.

Application of 'next-generation' sequencing technologies to microbial genetics

New sequencing methods generate data that can allow the assembly of microbial genome sequences in days. With such revolutionary advances in technology come new challenges in methodologies and informatics. In this article, we review the capabilities of high-throughput sequencing technologies and discuss the many options for getting useful information from the data.

ABySS: a parallel assembler for short read sequence data

Widespread adoption of massively parallel deoxyribonucleic acid (DNA) sequencing instruments has prompted the recent development of de novo short read assembly algorithms. A common shortcoming of the available tools is their inability to efficiently assemble vast amounts of data generated from large-scale sequencing projects, such as the sequencing of individual human genomes to catalog natural genetic variation. To address this limitation, we developed ABySS (Assembly By Short Sequences), a parallelized sequence assembler. As a demonstration of the capability of our software, we assembled 3.5 billion paired-end reads from the genome of an African male publicly released by Illumina, Inc. Approximately 2.76 million contigs > or =100 base pairs (bp) in length were created with an N50 size of 1499 bp, representing 68% of the reference human genome. Analysis of these contigs identified polymorphic and novel sequences not present in the human reference assembly, which were validated by alignment to alternate human assemblies and to other primate genomes.

Next-generation sequencing: from basic research to diagnostics

BACKGROUND

For the past 30 years, the Sanger method has been the dominant approach and gold standard for DNA sequencing. The commercial launch of the first massively parallel pyrosequencing platform in 2005 ushered in the new era of high-throughput genomic analysis now referred to as next-generation sequencing (NGS).

CONTENT

This review describes fundamental principles of commercially available NGS platforms. Although the platforms differ in their engineering configurations and sequencing chemistries, they share a technical paradigm in that sequencing of spatially separated, clonally amplified DNA templates or single DNA molecules is performed in a flow cell in a massively parallel manner. Through iterative cycles of polymerase-mediated nucleotide extensions or, in one approach, through successive oligonucleotide ligations, sequence outputs in the range of hundreds of megabases to gigabases are now obtained routinely. Highlighted in this review are the impact of NGS on basic research, bioinformatics considerations, and translation of this technology into clinical diagnostics. Also presented is a view into future technologies, including real-time single-molecule DNA sequencing and nanopore-based sequencing.

SUMMARY

In the relatively short time frame since 2005, NGS has fundamentally altered genomics research and allowed investigators to conduct experiments that were previously not technically feasible or affordable. The various technologies that constitute this new paradigm continue to evolve, and further improvements in technology robustness and process streamlining will pave the path for translation into clinical diagnostics.

QSRA: a quality-value guided de novo short read assembler

BACKGROUND

New rapid high-throughput sequencing technologies have sparked the creation of a new class of assembler. Since all high-throughput sequencing platforms incorporate errors in their output, short-read assemblers must be designed to account for this error while utilizing all available data.

RESULTS

We have designed and implemented an assembler, Quality-value guided Short Read Assembler, created to take advantage of quality-value scores as a further method of dealing with error. Compared to previous published algorithms, our assembler shows significant improvements not only in speed but also in output quality.

CONCLUSION

QSRA generally produced the highest genomic coverage, while being faster than VCAKE. QSRA is extremely competitive in its longest contig and N50/N80 contig lengths, producing results of similar quality to those of EDENA and VELVET. QSRA provides a step closer to the goal of de novo assembly of complex genomes, improving upon the original VCAKE algorithm by not only drastically reducing runtimes but also increasing the viability of the assembly algorithm through further error handling capabilities.

Parallel short sequence assembly of transcriptomes

Background

The de novo assembly of genomes and transcriptomes from short sequences is a challenging problem. Because of the high coverage needed to assemble short sequences as well as the overhead of modeling the assembly problem as a graph problem, the methods for short sequence assembly are often validated using data from BACs or small sized prokaryotic genomes.

Results

We present a parallel method for transcriptome assembly from large short sequence data sets. Our solution uses a rigorous graph theoretic framework and tames the computational and space complexity using parallel computers. First, we construct a distributed bidirected graph that captures overlap information. Next, we compact all chains in this graph to determine long unique contigs using undirected parallel list ranking, a problem for which we present an algorithm. Finally, we process this compacted distributed graph to resolve unique regions that are separated by repeats, exploiting the naturally occurring coverage variations arising from differential expression.

Conclusion

We demonstrate the validity of our method using a synthetic high coverage data set generated from the predicted coding regions of Zea mays. We assemble 925 million sequences consisting of 40 billion nucleotides in a few minutes on a 1024 processor Blue Gene/L. Our method is the first fully distributed method for assembling a non-hierarchical short sequence data set and can scale to large problem sizes.

Crystallizing short-read assemblies around seeds

Background

New short-read sequencing technologies produce enormous volumes of 25–30 base paired-end reads. The resulting reads have vastly different characteristics than produced by Sanger sequencing, and require different approaches than the previous generation of sequence assemblers. In this paper, we present a short-read de novo assembler particularly targeted at the new ABI SOLiD sequencing technology.

Results

This paper presents what we believe to be the first de novo sequence assembly results on real data from the emerging SOLiD platform, introduced by Applied Biosystems. Our assembler SHORTY augments short-paired reads using a trivially small number (5 – 10) of seeds of length 300 – 500 bp. These seeds enable us to produce significant assemblies using short-read coverage no more than 100×, which can be obtained in a single run of these high-capacity sequencers. SHORTY exploits two ideas which we believe to be of interest to the short-read assembly community: (1) using single seed reads to crystallize assemblies, and (2) estimating intercontig distances accurately from multiple spanning paired-end reads.

Conclusion

We demonstrate effective assemblies (N50 contig sizes ~40 kb) of three different bacterial species using simulated SOLiD data. Sequencing artifacts limit our performance on real data, however our results on this data are substantially better than those achieved by competing assemblers.

Metagenomics: Facts and Artifacts, and Computational Challenges*

Metagenomics is the study of microbial communities sampled directly from their natural environment, without prior culturing. By enabling an analysis of populations including many (so-far) unculturable and often unknown microbes, metagenomics is revolutionizing the field of microbiology, and has excited researchers in many disciplines that could benefit from the study of environmental microbes, including those in ecology, environmental sciences, and biomedicine. Specific computational and statistical tools have been developed for metagenomic data analysis and comparison. New studies, however, have revealed various kinds of artifacts present in metagenomics data caused by limitations in the experimental protocols and/or inadequate data analysis procedures, which often lead to incorrect conclusions about a microbial community. Here, we review some of the artifacts, such as overestimation of species diversity and incorrect estimation of gene family frequencies, and discuss emerging computational approaches to address them. We also review potential challenges that metagenomics may encounter with the extensive application of next-generation sequencing (NGS) techniques.

Next-generation DNA sequencing

DNA sequence represents a single format onto which a broad range of biological phenomena can be projected for high-throughput data collection. Over the past three years, massively parallel DNA sequencing platforms have become widely available, reducing the cost of DNA sequencing by over two orders of magnitude, and democratizing the field by putting the sequencing capacity of a major genome center in the hands of individual investigators. These new technologies are rapidly evolving, and near-term challenges include the development of robust protocols for generating sequencing libraries, building effective new approaches to data-analysis, and often a rethinking of experimental design. Next-generation DNA sequencing has the potential to dramatically accelerate biological and biomedical research, by enabling the comprehensive analysis of genomes, transcriptomes and interactomes to become inexpensive, routine and widespread, rather than requiring significant production-scale efforts.