Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage.

Anaerobic oxidation of methane (AOM) is critical for controlling the flux of methane from anoxic environments. AOM coupled to iron, manganese and sulphate reduction have been demonstrated in consortia containing anaerobic methanotrophic (ANME) archaea. More recently it has been shown that the bacterium Candidatus 'Methylomirabilis oxyfera' can couple AOM to nitrite reduction through an intra-aerobic methane oxidation pathway. Bioreactors capable of AOM coupled to denitrification have resulted in the enrichment of 'M. oxyfera' and a novel ANME lineage, ANME-2d. However, as 'M. oxyfera' can independently couple AOM to denitrification, the role of ANME-2d in the process is unresolved. Here, a bioreactor fed with nitrate, ammonium and methane was dominated by a single ANME-2d population performing nitrate-driven AOM. Metagenomic, single-cell genomic and metatranscriptomic analyses combined with bioreactor performance and (13)C- and (15)N-labelling experiments show that ANME-2d is capable of independent AOM through reverse methanogenesis using nitrate as the terminal electron acceptor. Comparative analyses reveal that the genes for nitrate reduction were transferred laterally from a bacterial donor, suggesting selection for this novel process within ANME-2d. Nitrite produced by ANME-2d is reduced to dinitrogen gas through a syntrophic relationship with an anaerobic ammonium-oxidizing bacterium, effectively outcompeting 'M. oxyfera' in the system. We propose the name Candidatus 'Methanoperedens nitroreducens' for the ANME-2d population and the family Candidatus 'Methanoperedenaceae' for the ANME-2d lineage. We predict that 'M. nitroreducens' and other members of the 'Methanoperedenaceae' have an important role in linking the global carbon and nitrogen cycles in anoxic environments.

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes.

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of "marker" genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

Inferring short tandem repeat variation from paired-end short reads.

The advances of high-throughput sequencing offer an unprecedented opportunity to study genetic variation. This is challenged by the difficulty of resolving variant calls in repetitive DNA regions. We present a Bayesian method to estimate repeat-length variation from paired-end sequence read data. The method makes variant calls based on deviations in sequence fragment sizes, allowing the analysis of repeats at lengths of relevance to a range of phenotypes. We demonstrate the method's ability to detect and quantify changes in repeat lengths from short read genomic sequence data across genotypes. We use the method to estimate repeat variation among 12 strains of Arabidopsis thaliana and demonstrate experimentally that our method compares favourably against existing methods. Using this method, we have identified all repeats across the genome, which are likely to be polymorphic. In addition, our predicted polymorphic repeats also included the only known repeat expansion in A. thaliana, suggesting an ability to discover potential unstable repeats.

Crass: identification and reconstruction of CRISPR from unassembled metagenomic data.

Clustered regularly interspaced short palindromic repeats (CRISPR) constitute a bacterial and archaeal adaptive immune system that protect against bacteriophage (phage). Analysis of CRISPR loci reveals the history of phage infections and provides a direct link between phage and their hosts. All current tools for CRISPR identification have been developed to analyse completed genomes and are not well suited to the analysis of metagenomic data sets, where CRISPR loci are difficult to assemble owing to their repetitive structure and population heterogeneity. Here, we introduce a new algorithm, Crass, which is designed to identify and reconstruct CRISPR loci from raw metagenomic data without the need for assembly or prior knowledge of CRISPR in the data set. CRISPR in assembled data are often fragmented across many contigs/scaffolds and do not fully represent the population heterogeneity of CRISPR loci. Crass identified substantially more CRISPR in metagenomes previously analysed using assembly-based approaches. Using Crass, we were able to detect CRISPR that contained spacers with sequence homology to phage in the system, which would not have been identified using other approaches. The increased sensitivity, specificity and speed of Crass will facilitate comprehensive analysis of CRISPRs in metagenomic data sets, increasing our understanding of phage-host interactions and co-evolution within microbial communities.

Sequencing and assembly of low copy and genic regions of isolated Triticum aestivum chromosome arm 7DS.

The genome of bread wheat (Triticum aestivum) is predicted to be greater than 16 Gbp in size and consist predominantly of repetitive elements, making the sequencing and assembly of this genome a major challenge. We have reduced genome sequence complexity by isolating chromosome arm 7DS and applied second-generation technology and appropriate algorithmic analysis to sequence and assemble low copy and genic regions of this chromosome arm. The assembly represents approximately 40% of the chromosome arm and all known 7DS genes. Comparison of the 7DS assembly with the sequenced genomes of rice (Oryza sativa) and Brachypodium distachyon identified large regions of conservation. The syntenic relationship between wheat, B. distachyon and O. sativa, along with available genetic mapping data, has been used to produce an annotated draft 7DS syntenic build, which is publicly available at http://www.wheatgenome.info. Our results suggest that the sequencing of isolated chromosome arms can provide valuable information of the gene content of wheat and is a step towards whole-genome sequencing and variation discovery in this important crop.

De novo sequencing of plant genomes using second-generation technologies.

The ability to sequence the DNA of an organism has become one of the most important tools in modern biological research. Until recently, the sequencing of even small model genomes required substantial funds and international collaboration. The development of 'second-generation' sequencing technology has increased the throughput and reduced the cost of sequence generation by several orders of magnitude. These new methods produce vast numbers of relatively short reads, usually at the expense of read accuracy. Since the first commercial second-generation sequencing system was produced by 454 Technologies and commercialised by Roche, several other companies including Illumina, Applied Biosystems, Helicos Biosciences and Pacific Biosciences have joined the competition. Because of the relatively high error rate and lack of assembly tools, short-read sequence technology has mainly been applied to the re-sequencing of genomes. However, some recent applications have focused on the de novo assembly of these data. De novo assembly remains the greatest challenge for DNA sequencing and there are specific problems for second generation sequencing which produces short reads with a high error rate. However, a number of different approaches for short-read assembly have been proposed and some have been implemented in working software. In this review, we compare the current approaches for second-generation genome sequencing, explore the future direction of this technology and the implications for plant genome research.

CMap3D: a 3D visualization tool for comparative genetic maps.

UNLABELLED: Genetic linkage mapping enables the study of genome organization and the association of heritable traits with regions of sequenced genomes. Comparative genetic mapping is particularly powerful as it allows translation of information between related genomes and gives an insight into genome evolution. A common tool for the storage, comparison and visualization of genetic maps is CMap. However, current visualization in CMap is limited to the comparison of adjacent aligned maps. To overcome this limitation, we have developed CMap3D, a tool to compare multiple genetic maps in three-dimensional space. CMap3D is based on a client/server model ensuring operability with current CMap data repositories. This tool can be applied to any species where genetic map information is available and enables rapid, direct comparison between multiple aligned maps. AVAILABILITY AND IMPLEMENTATION: The software is a stand-alone application written in Processing and Java. Binaries are available for Windows, OSX and Linux, and require Sun Microsystems Java Runtime Environment 1.6 or later. The software is freely available for non-commercial use from http://flora.acpfg.com.au/.

AutoSNPdb: an annotated single nucleotide polymorphism database for crop plants.

Single nucleotide polymorphisms (SNPs) may be considered the ultimate genetic marker as they represent the finest resolution of a DNA sequence (a single nucleotide), are generally abundant in populations and have a low mutation rate. Analysis of assembled EST sequence data provides a cost-effective means to identify large numbers of SNPs associated with functional genes. We have developed an integrated SNP discovery pipeline, which identifies SNPs from assembled EST sequences. The results are maintained in a custom relational database along with EST source and annotation information. The current database hosts data for the important crops rice, barley and Brassica. Users may rapidly identify polymorphic sequences of interest through BLAST sequence comparison, keyword searches of annotations derived from UniRef90 and GenBank comparisons, GO annotations or in genes corresponding to syntenic regions of reference genomes. In addition, SNPs between specific varieties may be identified for targeted mapping and association studies. SNPs are viewed using a user-friendly graphical interface. The database is freely accessible at http://autosnpdb.qfab.org.au/.

Future tools for association mapping in crop plants.

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.

Discovering genetic polymorphisms in next-generation sequencing data.

The ongoing revolution in DNA sequencing technology now enables the reading of thousands of millions of nucleotide bases in a single instrument run. However, this data quantity is often compromised by poor confidence in the read quality. The identification of genetic polymorphisms from this data is therefore problematic and, combined with the vast quantity of data, poses a major bioinformatics challenge. However, once these difficulties have been addressed, next-generation sequencing will offer a means to identify and characterize the wealth of genetic polymorphisms underlying the vast phenotypic variation in biological systems. We describe the recent advances in next-generation sequencing technology, together with preliminary approaches that can be applied for single nucleotide polymorphism discovery in plant species.

Single nucleotide polymorphism discovery in barley using autoSNPdb.

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico, but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing. The SNP detection method autoSNP has been developed to identify SNPs from sequence data for any species. Confidence in the predicted SNPs is based on sequence redundancy, and haplotype co-segregation scores are calculated for a further independent measure of confidence. We have extended the autoSNP method to produce autoSNPdb, which integrates SNP and gene annotation information with a graphical viewer. We have applied this software to public barley expressed sequences, and the resulting database is available over the Internet. SNPs can be viewed and searched by sequence, functional annotation or predicted synteny with a reference genome, in this case rice. The correlation between SNPs and barley cultivar, expressed tissue type and development stage has been collated for ease of exploration. An average of one SNP per 240 bp was identified, with SNPs more prevalent in the 5' regions and simple sequence repeat (SSR) flanking sequences. Overall, autoSNPdb can provide a wealth of genetic polymorphism information for any species for which sequence data are available.

Genome sequencing approaches and successes.

Sequence data is crucial to our understanding of crop growth and development, as differences in DNA sequence are responsible for almost all of the heritable differences between crop varieties and ecotypes. The sequence of a genome is often referred to as the genetic blueprint, and is the foundation for all additional information from the genome to the phenome. The value of DNA sequence is leading to rapid improvements in sequencing technology, increasing throughput, and reducing costs, and technological advances are accelerating with the introduction of novel approaches that are replacing the traditional Sanger-based methods. As genome sequencing becomes cheaper, it will be applied to a greater number of species with increasingly large and complex genomes. This will increase our understanding of how differences in the sequence relate to phenotypic observations, heritable traits, speciation, and evolution. Our understanding of plants will be greatly enhanced by this flow of sequence information, with direct benefit for crop improvement.

GroopM: an automated tool for the recovery of population genomes from related metagenomes.

Metagenomic binning methods that leverage differential population abundances in microbial communities (differential coverage) are emerging as a complementary approach to conventional composition-based binning. Here we introduce GroopM, an automated binning tool that primarily uses differential coverage to obtain high fidelity population genomes from related metagenomes. We demonstrate the effectiveness of GroopM using synthetic and real-world metagenomes, and show that GroopM produces results comparable with more time consuming, labor-intensive methods.

An expanded genomic representation of the phylum cyanobacteria.

Molecular surveys of aphotic habitats have indicated the presence of major uncultured lineages phylogenetically classified as members of the Cyanobacteria. One of these lineages has recently been proposed as a nonphotosynthetic sister phylum to the Cyanobacteria, the Melainabacteria, based on recovery of population genomes from human gut and groundwater samples. Here, we expand the phylogenomic representation of the Melainabacteria through sequencing of six diverse population genomes from gut and bioreactor samples supporting the inference that this lineage is nonphotosynthetic, but not the assertion that they are strictly fermentative. We propose that the Melainabacteria is a class within the phylogenetically defined Cyanobacteria based on robust monophyly and shared ancestral traits with photosynthetic representatives. Our findings are consistent with theories that photosynthesis occurred late in the Cyanobacteria and involved extensive lateral gene transfer and extends the recognized functionality of members of this phylum.

Spatial uniformity of microbial diversity in a continuous bioelectrochemical system.

Bioelectrochemical systems (BESs) are emerging as a technology with diverse future applications. Anode-associated microbial diversity and activity are known to change over time, but the consequences of these dynamics on BES functioning are poorly understood. A novel BES with exchangeable anodic electrodes that facilitates characterisation of microbial communities over time was constructed. The BES, received a mixture of volatile fatty acids and produced 0.13 mA cm(-2) of anodic electrode surface, leading to the removal of 14 g chemical oxygen demand per m2 electrode per day at a coulombic efficiency of 76%. Pyrosequencing of 16S rRNA genes revealed no differences in the diversity of microbial communities associated with different electrodes within a single time point. This finding validates the design for temporal studies as changes in microbial diversity observed over time can be related to community development rather than spatial variation within the reactor.

Bioinformatics tools and databases for analysis of next-generation sequence data.

Genome sequencing has been revolutionized by next-generation technologies, which can rapidly produce vast quantities of data at relatively low cost. With data production now no longer being limited, there is a huge challenge to analyse the data flood and interpret biological meaning. Bioinformatics scientists have risen to the challenge and a large number of software tools and databases have been produced and these continue to evolve with this rapidly advancing field. Here, we outline some of the tools and databases commonly used for the analysis of next-generation sequence data with comment on their utility.

Capturing the biofuel wellhead and powerhouse: the chloroplast and mitochondrial genomes of the leguminous feedstock tree Pongamia pinnata.

Pongamia pinnata (syn. Millettia pinnata) is a novel, fast-growing arboreal legume that bears prolific quantities of oil-rich seeds suitable for the production of biodiesel and aviation biofuel. Here, we have used Illumina® 'Second Generation DNA Sequencing (2GS)' and a new short-read de novo assembler, SaSSY, to assemble and annotate the Pongamia chloroplast (152,968 bp; cpDNA) and mitochondrial (425,718 bp; mtDNA) genomes. We also show that SaSSY can be used to accurately assemble 2GS data, by re-assembling the Lotus japonicus cpDNA and in the process assemble its mtDNA (380,861 bp). The Pongamia cpDNA contains 77 unique protein-coding genes and is almost 60% gene-dense. It contains a 50 kb inversion common to other legumes, as well as a novel 6.5 kb inversion that is responsible for the non-disruptive, re-orientation of five protein-coding genes. Additionally, two copies of an inverted repeat firmly place the species outside the subclade of the Fabaceae lacking the inverted repeat. The Pongamia and L. japonicus mtDNA contain just 33 and 31 unique protein-coding genes, respectively, and like other angiosperm mtDNA, have expanded intergenic and multiple repeat regions. Through comparative analysis with Vigna radiata we measured the average synonymous and non-synonymous divergence of all three legume mitochondrial (1.59% and 2.40%, respectively) and chloroplast (8.37% and 8.99%, respectively) protein-coding genes. Finally, we explored the relatedness of Pongamia within the Fabaceae and showed the utility of the organellar genome sequences by mapping transcriptomic data to identify up- and down-regulated stress-responsive gene candidates and confirm in silico predicted RNA editing sites.

Targeted identification of genomic regions using TAGdb.

BACKGROUND: The introduction of second generation sequencing technology has enabled the cost effective sequencing of genomes and the identification of large numbers of genes and gene promoters. However, the assembly of DNA sequences to create a representation of the complete genome sequence remains costly, especially for the larger and more complex plant genomes. RESULTS: We have developed an online database, TAGdb, that enables researchers to identify paired read sequences that share identity with a submitted query sequence. These tags can be used to design oligonucleotide primers for the PCR amplification of the region in the target genome. CONCLUSIONS: The ability to produce large numbers of paired read genome tags using second generation sequencing provides a cost effective method for the identification of genes and promoters in large, complex or orphan species without the need for whole genome assembly.