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

Sequence assembly

Despite the rapidly increasing number of sequenced and re-sequenced genomes, many issues regarding the computational assembly of large-scale sequencing data have remain unresolved. Computational assembly is crucial in large genome projects as well for the evolving high-throughput technologies and plays an important role in processing the information generated by these methods. Here, we provide a comprehensive overview of the current publicly available sequence assembly programs. We describe the basic principles of computational assembly along with the main concerns, such as repetitive sequences in genomic DNA, highly expressed genes and alternative transcripts in EST sequences. We summarize existing comparisons of different assemblers and provide a detailed descriptions and directions for download of assembly programs at: http://genome.ku.dk/resources/assembly/methods.html.

De novo fragment assembly with short mate-paired reads: Does the read length matter?

Increasing read length is currently viewed as the crucial condition for fragment assembly with next-generation sequencing technologies. However, introducing mate-paired reads (separated by a gap of length, GapLength) opens a possibility to transform short mate-pairs into long mate-reads of length approximately GapLength, and thus raises the question as to whether the read length (as opposed to GapLength) even matters. We describe a new tool, EULER-USR, for assembling mate-paired short reads and use it to analyze the question of whether the read length matters. We further complement the ongoing experimental efforts to maximize read length by a new computational approach for increasing the effective read length. While the common practice is to trim the error-prone tails of the reads, we present an approach that substitutes trimming with error correction using repeat graphs. An important and counterintuitive implication of this result is that one may extend sequencing reactions that degrade with length "past their prime" to where the error rate grows above what is normally acceptable for fragment assembly.

De novo assembly using low-coverage short read sequence data from the rice pathogen Pseudomonas syringae pv. oryzae

We developed a novel approach for de novo genome assembly using only sequence data from high-throughput short read sequencing technologies. By combining data generated from 454 Life Sciences (Roche) and Illumina (formerly known as Solexa sequencing) sequencing platforms, we reliably assembled genomes into large scaffolds at a fraction of the traditional cost and without use of a reference sequence. We applied this method to two isolates of the phytopathogenic bacteria Pseudomonas syringae. Sequencing and reassembly of the well-studied tomato and Arabidopsis pathogen, Pto(DC3000), facilitated development and testing of our method. Sequencing of a distantly related rice pathogen, Por(1_)(6), demonstrated our method's efficacy for de novo assembly of novel genomes. Our assembly of Por(1_6) yielded an N50 scaffold size of 531,821 bp with >75% of the predicted genome covered by scaffolds over 100,000 bp. One of the critical phenotypic differences between strains of P. syringae is the range of plant hosts they infect. This is largely determined by their complement of type III effector proteins. The genome of Por(1_6) is the first sequenced for a P. syringae isolate that is a pathogen of monocots, and, as might be predicted, its complement of type III effectors differs substantially from the previously sequenced isolates of this species. The genome of Por(1_6) helps to define an expansion of the P. syringae pan-genome, a corresponding contraction of the core genome, and a further diversification of the type III effector complement for this important plant pathogen species.

MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes

Recent advances in DNA sequencers are accelerating genome sequencing, especially in microbes, and complete and draft genomes from various species have been sequenced in rapid succession. Here, we present a comprehensive gene prediction tool, the MetaGeneAnnotator (MGA), which precisely predicts all kinds of prokaryotic genes from a single or a set of anonymous genomic sequences having a variety of lengths. The MGA integrates statistical models of prophage genes, in addition to those of bacterial and archaeal genes, and also uses a self-training model from input sequences for predictions. As a result, the MGA sensitively detects not only typical genes but also atypical genes, such as horizontally transferred and prophage genes in a prokaryotic genome. In this paper, we also propose a novel approach for analyzing the ribosomal binding site (RBS), which enables us to detect species-specific patterns of the RBSs. The MGA has the ingenious RBS model based on this approach, and precisely predicts translation starts of genes. The MGA also succeeds in improving prediction accuracies for short sequences by using the adapted RBS models (96% sensitivity and 93% specificity for 700 bp fragments). These features of the MGA expedite wide ranges of microbial genome studies, such as genome annotations and metagenome analyses.

Probabilistic base calling of Solexa sequencing data

Background

Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology.

Results

We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads.

Conclusion

We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.

Gene-boosted assembly of a novel bacterial genome from very short reads

Recent improvements in technology have made DNA sequencing dramatically faster and more efficient than ever before. The new technologies produce highly accurate sequences, but one drawback is that the most efficient technology produces the shortest read lengths. Short-read sequencing has been applied successfully to resequence the human genome and those of other species but not to whole-genome sequencing of novel organisms. Here we describe the sequencing and assembly of a novel clinical isolate of Pseudomonas aeruginosa, strain PAb1, using very short read technology. From 8,627,900 reads, each 33 nucleotides in length, we assembled the genome into one scaffold of 76 ordered contiguous sequences containing 6,290,005 nucleotides, including one contig spanning 512,638 nucleotides, plus an additional 436 unordered contigs containing 416,897 nucleotides. Our method includes a novel gene-boosting algorithm that uses amino acid sequences from predicted proteins to build a better assembly. This study demonstrates the feasibility of very short read sequencing for the sequencing of bacterial genomes, particularly those for which a related species has been sequenced previously, and expands the potential application of this new technology to most known prokaryotic species.

Sequencing of natural strains of Arabidopsis thaliana with short reads

Whole-genome hybridization studies have suggested that the nuclear genomes of accessions (natural strains) of Arabidopsis thaliana can differ by several percent of their sequence. To examine this variation, and as a first step in the 1001 Genomes Project for this species, we produced 15- to 25-fold coverage in Illumina sequencing-by-synthesis (SBS) reads for the reference accession, Col-0, and two divergent strains, Bur-0 and Tsu-1. We aligned reads to the reference genome sequence to assess data quality metrics and to detect polymorphisms. Alignments revealed 823,325 unique single nucleotide polymorphisms (SNPs) and 79,961 unique 1- to 3-bp indels in the divergent accessions at a specificity of >99%, and over 2000 potential errors in the reference genome sequence. We also identified >3.4 Mb of the Bur-0 and Tsu-1 genomes as being either extremely dissimilar, deleted, or duplicated relative to the reference genome. To obtain sequences for these regions, we incorporated the Velvet assembler into a targeted de novo assembly method. This approach yielded 10,921 high-confidence contigs that were anchored to flanking sequences and harbored indels as large as 641 bp. Our methods are broadly applicable for polymorphism discovery in moderate to large genomes even at highly diverged loci, and we established by subsampling the Illumina SBS coverage depth required to inform a broad range of functional and evolutionary studies. Our pipeline for aligning reads and predicting SNPs and indels, SHORE, is available for download at http://1001genomes.org.

High-precision, whole-genome sequencing of laboratory strains facilitates genetic studies

Whole-genome sequencing is a powerful technique for obtaining the reference sequence information of multiple organisms. Its use can be dramatically expanded to rapidly identify genomic variations, which can be linked with phenotypes to obtain biological insights. We explored these potential applications using the emerging next-generation sequencing platform Solexa Genome Analyzer, and the well-characterized model bacterium Bacillus subtilis. Combining sequencing with experimental verification, we first improved the accuracy of the published sequence of the B. subtilis reference strain 168, then obtained sequences of multiple related laboratory strains and different isolates of each strain. This provides a framework for comparing the divergence between different laboratory strains and between their individual isolates. We also demonstrated the power of Solexa sequencing by using its results to predict a defect in the citrate signal transduction pathway of a common laboratory strain, which we verified experimentally. Finally, we examined the molecular nature of spontaneously generated mutations that suppress the growth defect caused by deletion of the stringent response mediator relA. Using whole-genome sequencing, we rapidly mapped these suppressor mutations to two small homologs of relA. Interestingly, stable suppressor strains had mutations in both genes, with each mutation alone partially relieving the relA growth defect. This supports an intriguing three-locus interaction module that is not easily identifiable through traditional suppressor mapping. We conclude that whole-genome sequencing can drastically accelerate the identification of suppressor mutations and complex genetic interactions, and it can be applied as a standard tool to investigate the genetic traits of model organisms.

In this manuscript, we describe novel applications of the newly developed Solexa sequencing technology. We aim to provide insights into the following questions: (1) Can whole-genome sequencing, while rapidly surveying mega-bases of genome information, also reliably identify variations at the base-pair resolution? (2) Can it be used to identify the differences between isolates of the same laboratory strain and between different laboratory strains? (3) Can it be used as a genetic tool to predict phenotypes and identify suppressors? To this end, we performed whole-genome shotgun sequencing of several related strains of the widely studied model bacterium Bacillus subtilis, we identified genomic variations that potentially underlie strain-specific phenotypes, which occur frequently in biological studies, and we found multiple suppressor mutations within a single strain that are difficult to discern through traditional methods. We conclude that whole-genome sequencing can be directly used to guide genetic studies.

The new paradigm of flow cell sequencing

DNA sequencing is in a period of rapid change, in which capillary sequencing is no longer the technology of choice for most ultra-high-throughput applications. A new generation of instruments that utilize primed synthesis in flow cells to obtain, simultaneously, the sequence of millions of different DNA templates has changed the field. We compare and contrast these new sequencing platforms in terms of stage of development, instrument configuration, template format, sequencing chemistry, throughput capability, operating cost, data handling issues, and error models. While these platforms outperform capillary instruments in terms of bases per day and cost per base, the short length of sequence reads obtained from most instruments and the limited number of samples that can be run simultaneously imposes some practical constraints on sequencing applications. However, recently developed methods for paired-end sequencing and for array-based direct selection of desired templates from complex mixtures extend the utility of these platforms for genome analysis. Given the ever increasing demand for DNA sequence information, we can expect continuous improvement of this new generation of instruments and their eventual replacement by even more powerful technology.