Viral Population Estimation Using Pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation–maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.     

Read length versus Depth of Coverage for Viral Quasispecies Reconstruction

Recent advancements of sequencing technology have opened up unprecedented opportunities in many application areas. Virus samples can now be sequenced efficiently with very deep coverage to infer the genetic diversity of the underlying virus populations. Several sequencing platforms with different underlying technologies and performance characteristics are available for viral diversity studies. Here, we investigate how the differences between two common platforms provided by 454/Roche and Illumina affect viral diversity estimation and the reconstruction of viral haplotypes. Using a mixture of ten HIV clones sequenced with both platforms and additional simulation experiments, we assessed the trade-off between sequencing coverage, read length, and error rate. For fixed costs, short Illumina reads can be generated at higher coverage and allow for detecting variants at lower frequencies. They can also be sufficient to assess the diversity of the sample if sequences are dissimilar enough, but, in general, assembly of full-length haplotypes is feasible only with the longer 454/Roche reads. The quantitative comparison highlights the advantages and disadvantages of both platforms and provides guidance for the design of viral diversity studies.     

Viral Quasispecies Assembly via Maximal Clique Enumeration

Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.     

Nature and Extent of Genetic Diversity of Dengue Viruses Determined by 454 Pyrosequencing

Dengue virus (DENV) populations are characteristically highly diverse. Regular lineage extinction and replacement is an important dynamic DENV feature, and most DENV lineage turnover events are associated with increased incidence of disease. The role of genetic diversity in DENV lineage extinctions is not understood. We investigated the nature and extent of genetic diversity in the envelope (E) gene of DENV serotype 1 representing different lineages histories. A region of the DENV genome spanning the E gene was amplified and sequenced by Roche/454 pyrosequencing. The pyrosequencing results identified distinct sub-populations (haplotypes) for each DENV-1 E gene. A phylogenetic tree was constructed with the consensus DENV-1 E gene nucleotide sequences, and the sequences of each constructed haplotype showed that the haplotypes segregated with the Sanger consensus sequence of the population from which they were drawn. Haplotypes determined through pyrosequencing identified a recombinant DENV genome that could not be identified through Sanger sequencing. Nucleotide level sequence diversities of DENV-1 populations determined from SNP analysis were very low, estimated from 0.009–0.01. There were also no stop codon, frameshift or non-frameshift mutations observed in the E genes of any lineage. No significant correlations between the accumulation of deleterious mutations or increasing genetic diversity and lineage extinction were observed (p>0.5). Although our hypothesis that accumulation of deleterious mutations over time led to the extinction and replacement of DENV lineages was ultimately not supported by the data, our data does highlight the significant technical issues that must be resolved in the way in which population diversity is measured for DENV and other viruses. The results provide an insight into the within-population genetic structure and diversity of DENV-1 populations.     

Full-length haplotype reconstruction to infer the structure of heterogeneous virus populations

Next-generation sequencing (NGS) technologies enable new insights into the diversity of virus populations within their hosts. Diversity estimation is currently restricted to single-nucleotide variants or to local fragments of no more than a few hundred nucleotides defined by the length of sequence reads. To study complex heterogeneous virus populations comprehensively, novel methods are required that allow for complete reconstruction of the individual viral haplotypes. Here, we show that assembly of whole viral genomes of ∼8600 nucleotides length is feasible from mixtures of heterogeneous HIV-1 strains derived from defined combinations of cloned virus strains and from clinical samples of an HIV-1 superinfected individual. Haplotype reconstruction was achieved using optimized experimental protocols and computational methods for amplification, sequencing and assembly. We comparatively assessed the performance of the three NGS platforms 454 Life Sciences/Roche, Illumina and Pacific Biosciences for this task. Our results prove and delineate the feasibility of NGS-based full-length viral haplotype reconstruction and provide new tools for studying evolution and pathogenesis of viruses.     

Hap-seqX: Expedite algorithm for haplotype phasing with imputation using sequence data

Haplotype phasing is one of the most important problems in population genetics as haplotypes can be used to estimate the relatedness of individuals and to impute genotype information which is a commonly performed analysis when searching for variants involved in disease. The problem of haplotype phasing has been well studied. Methodologies for haplotype inference from sequencing data either combine a set of reference haplotypes and collected genotypes using a Hidden Markov Model or assemble haplotypes by overlapping sequencing reads. A recent algorithm Hap-seq considers using both sequencing data and reference haplotypes and it is a hybrid of a dynamic programming algorithm and a Hidden Markov Model (HMM), which is shown to be optimal. However, the algorithm requires extremely large amount of memory which is not practical for whole genome datasets. The current algorithm requires saving intermediate results to disk and reads these results back when needed, which significantly affects the practicality of the algorithm. In this work, we proposed the expedited version of the algorithm Hap-seqX, which addressed the memory issue by using a posterior probability to select the records that should be saved in memory. We show that Hap-seqX can save all the intermediate results in memory and improves the execution time of the algorithm dramatically. Utilizing the strategy, Hap-seqX is able to predict haplotypes from whole genome sequencing data.     

SIV Genome-Wide Pyrosequencing Provides a Comprehensive and Unbiased View of Variation within and outside CD8 T Lymphocyte Epitopes

Deep sequencing technology is revolutionizing our understanding of HIV/SIV evolution. It is known that acute SIV sequence variation within CD8 T lymphocyte (CD8-TL) epitopes is similar among MHC-identical animals, but we do not know whether this persists into the chronic phase. We now determine whether chronic viral variation in MHC-identical animals infected with clonal SIV is similar throughout the entire coding sequence when using a sensitive deep sequencing approach. We pyrosequenced the entire coding sequence of the SIV genome isolated from a unique cohort of four SIVmac239-infected, MHC-identical Mauritian cynomolgus macaques (MCM) 48 weeks after infection; one MCM in the cohort became an elite controller. Among the three non-controllers, we found that genome-wide sequences were similar between animals and we detected increased sequence complexity within 64% of CD8-TL epitopes when compared to Sanger sequencing methods. When we compared sequences between the MHC-matched controller and the three non-controllers, we found the viral population in the controller was less diverse and accumulated different variants than the viral populations in the non-controllers. Importantly, we found that initial PCR amplification of viral cDNA did not significantly affect the sequences detected, suggesting that data obtained by pyrosequencing PCR-amplified viral cDNA accurately represents the diversity of sequences replicating within an animal. This demonstrates that chronic sequence diversity across the entire SIV coding sequence is similar among MHC-identical animals with comparable viral loads when infected with the same clonal virus stock. Additionally, our approach to genome-wide SIV sequencing accurately reflects the diversity of sequences present in the replicating viral population. In sum, our study suggests that genome-wide pyrosequencing of immunodeficiency viruses captures a thorough and unbiased picture of sequence diversity, and may be a useful approach to employ when evaluating which sequences to include as part of a vaccine immunogen.     

High diversity of alpha-globin haplotypes in a Senegalese population, including many previously unreported variants.

RFLP haplotypes at the alpha-globin gene complex have been examined in 190 individuals from the Niokolo Mandenka population of Senegal: haplotypes were assigned unambiguously for 210 chromosomes. The Mandenka share with other African populations a sample size-independent haplotype diversity that is much greater than that in any non-African population: the number of haplotypes observed in the Mandenka is typically twice that seen in the non-African populations sampled to date. Of these haplotypes, 17.3% had not been observed in any previous surveys, and a further 19.1% have previously been reported only in African populations. The haplotype distribution shows clear differences between African and non-African peoples, but this is on the basis of population-specific haplotypes combined with haplotypes common to all. The relationship of the newly reported haplotypes to those previously recorded suggests that several mutation processes, particularly recombination as homologous exchange or gene conversion, have been involved in their production. A computer program based on the expectation-maximization (EM) algorithm was used to obtain maximum-likelihood estimates of haplotype frequencies for the entire data set: good concordance between the unambiguous and EM-derived sets was seen for the overall haplotype frequencies. Some of the low-frequency haplotypes reported by the estimation algorithm differ greatly, in structure, from those haplotypes known to be present in human populations, and they may not represent haplotypes actually present in the sample.     

QSdpR: Viral quasispecies reconstruction via correlation clustering

RNA viruses are characterized by high mutation rates that give rise to populations of closely related genomes, known as viral quasispecies. Underlying heterogeneity enables the quasispecies to adapt to changing conditions and proliferate over the course of an infection. Determining genetic diversity of a virus (i.e., inferring haplotypes and their proportions in the population) is essential for understanding its mutation patterns, and for effective drug developments. Here, we present QSdpR, a method and software for the reconstruction of quasispecies from short sequencing reads. The reconstruction is achieved by solving a correlation clustering problem on a read-similarity graph and the results of the clustering are used to estimate frequencies of sub-species; the number of sub-species is determined using pseudo F index. Extensive tests on both synthetic datasets and experimental HIV-1 and Zika virus data demonstrate that QSdpR compares favorably to existing methods in terms of various performance metrics.     

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.     

NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads

Background

The popularity of new sequencing technologies has led to an explosion of possible applications, including new approaches in biodiversity studies. However each of these sequencing technologies suffers from sequencing errors originating from different factors. For 16S rRNA metagenomics studies, the 454 pyrosequencing technology is one of the most frequently used platforms, but sequencing errors still lead to important data analysis issues (e.g. in clustering in taxonomic units and biodiversity estimation). Moreover, retaining a higher portion of the sequencing data by preserving as much of the read length as possible while maintaining the error rate within an acceptable range, will have important consequences at the level of taxonomic precision.

Results

The new error correction algorithm proposed in this work - NoDe (Noise Detector) - is trained to identify those positions in 454 sequencing reads that are likely to have an error, and subsequently clusters those error-prone reads with correct reads resulting in error-free representative read. A benchmarking study with other denoising algorithms shows that NoDe can detect up to 75% more errors in a large scale mock community dataset, and this with a low computational cost compared to the second best algorithm considered in this study. The positive effect of NoDe in 16S rRNA studies was confirmed by the beneficial effect on the precision of the clustering of pyrosequencing reads in operational taxonomic units.

Conclusions

NoDe was shown to be a computational efficient denoising algorithm for pyrosequencing reads, producing the lowest error rates in an extensive benchmarking study with other denoising algorithms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0520-5) contains supplementary material, which is available to authorized users.     

Correction of sequence-dependent ambiguous bases (Ns) from the 454 pyrosequencing system

Pyrosequencing of the 16S ribosomal RNA gene (16S) has become one of the most popular methods to assess microbial diversity. Pyrosequencing reads containing ambiguous bases (Ns) are generally discarded based on the assumptions of their non-sequence-dependent formation and high error rates. However, taxonomic composition differed by removal of reads with Ns. We determined whether Ns from pyrosequencing occur in a sequence-dependent manner. Our reads and the corresponding flow value data revealed occurrence of sequence-specific N errors with a common sequential pattern (a homopolymer + a few nucleotides with bases other than the homopolymer + N) and revealed that the nucleotide base of the homopolymer is the true base for the following N. Using an algorithm reflecting this sequence-dependent pattern, we corrected the Ns in the 16S (86.54%), bphD (81.37%) and nifH (81.55%) amplicon reads from a mock community with high precisions of 95.4, 96.9 and 100%, respectively. The new N correction method was applicable for determining most of Ns in amplicon reads from a soil sample, resulting in reducing taxonomic biases associated with N errors and in shotgun sequencing reads from public metagenome data. The method improves the accuracy and precision of microbial community analysis and genome sequencing using 454 pyrosequencing.     

A Cladistic Analysis of Phenotypic Associations with Haplotypes Inferred from Restriction Endonuclease Mapping and DNA Sequence Data. III. Cladogram Estimation

We previously developed a cladistic approach to identify subsets of haplotypes defined by restriction endonuclease mapping or DNA sequencing that are associated with significant phenotypic deviations. Our approach was limited to segments of DNA in which little recombination occurs. In such cases, a cladogram can be constructed from the restriction site or sequence data that represents the evolutionary steps that interrelate the observed haplotypes. The cladogram is used to define a nested statistical design to identify mutational steps associated with significant phenotypic deviations. The central assumption behind this strategy is that any undetected mutation causing a phenotypic effect is embedded within the same evolutionary history that is represented by the cladogram. The power of this approach depends upon the confidence one has in the particular cladogram used to draw inferences. In this paper, we present a strategy for estimating the set of cladograms that are consistent with a particular sample of either restriction site or nucleotide sequence data and that includes the possibility of recombination. We first evaluate the limits of parsimony in constructing cladograms. Once these limits have been determined, we construct the set of parsimonious and nonparsimonious cladograms that is consistent with these limits. Our estimation procedure also identifies haplotypes that are candidates for being products of recombination. If recombination is extensive, our algorithm subdivides the DNA region into two or more subsections, each having little or no internal recombination. We apply this estimation procedure to three data sets to illustrate varying degrees of cladogram ambiguity and recombination.     

PyroClean: Denoising Pyrosequences from Protein-Coding Amplicons for the Recovery of Interspecific and Intraspecific Genetic Variation

High-throughput parallel sequencing is a powerful tool for the quantification of microbial diversity through the amplification of nuclear ribosomal gene regions. Recent work has extended this approach to the quantification of diversity within otherwise difficult-to-study metazoan groups. However, nuclear ribosomal genes present both analytical challenges and practical limitations that are a consequence of the mutational properties of nuclear ribosomal genes. Here we exploit useful properties of protein-coding genes for cross-species amplification and denoising of 454 flowgrams. We first use experimental mixtures of species from the class Collembola to amplify and pyrosequence the 5′ region of the COI barcode, and we implement a new algorithm called PyroClean for the denoising of Roche GS FLX pyrosequences. Using parameter values from the analysis of experimental mixtures, we then analyse two communities sampled from field sites on the island of Tenerife. Cross-species amplification success of target mitochondrial sequences in experimental species mixtures is high; however, there is little relationship between template DNA concentrations and pyrosequencing read abundance. Homopolymer error correction and filtering against a consensus reference sequence reduced the volume of unique sequences to approximately 5% of the original unique raw reads. Filtering of remaining non-target sequences attributed to PCR error, sequencing error, or numts further reduced unique sequence volume to 0.8% of the original raw reads. PyroClean reduces or eliminates the need for an additional, time-consuming step to cluster reads into Operational Taxonomic Units, which facilitates the detection of intraspecific DNA sequence variation. PyroCleaned sequence data from field sites in Tenerife demonstrate the utility of our approach for quantifying evolutionary diversity and its spatial structure. Comparison of our sequence data to public databases reveals that we are able to successfully recover both interspecific and intraspecific sequence diversity.     

DNA bar coding and pyrosequencing to identify rare HIV drug resistance mutations

Treatment of HIV-infected individuals with antiretroviral agents selects for drug-resistant mutants, resulting in frequent treatment failures. Although the major antiretroviral resistance mutations are routinely characterized by DNA sequencing, treatment failures are still common, probably in part because undetected rare resistance mutations facilitate viral escape. Here we combined DNA bar coding and massively parallel pyrosequencing to quantify rare drug resistance mutations. Using DNA bar coding, we were able to analyze seven viral populations in parallel, overall characterizing 118093 sequence reads of average length 103bp. Analysis of a control HIV mixture showed that resistance mutations present as 5% of the population could be readily detected without false positive calls. In three samples of multidrug-resistant HIV populations from patients, all the drug-resistant mutations called by conventional analysis were identified, as well as four additional low abundance drug resistance mutations, some of which would be expected to influence the response to antiretroviral therapy. Methods for sensitive characterization of HIV resistance alleles have been reported, but only the pyrosequencing method allows all the positions at risk for drug resistance mutations to be interrogated deeply for many HIV populations in a single experiment.     

The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time--an ultra-deep approach

Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5-15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from http://www.bioinf.manchester.ac.uk/segminator/.     

A diverse bacterial community in an anoxic quinoline-degrading bioreactor determined by using pyrosequencing and clone library analysis

There is a concern of whether the structure and diversity of a microbial community can be effectively revealed by short-length pyrosequencing reads. In this study, we performed a microbial community analysis on a sample from a high-efficiency denitrifying quinoline-degrading bioreactor and compared the results generated by pyrosequencing with those generated by clone library technology. By both technologies, 16S rRNA gene analysis indicated that the bacteria in the sample were closely related to, for example, Proteobacteria, Actinobacteria, and Bacteroidetes. The sequences belonging to Rhodococcus were the most predominant, and Pseudomonas, Sphingomonas, Acidovorax, and Zoogloea were also abundant. Both methods revealed a similar overall bacterial community structure. However, the 622 pyrosequencing reads of the hypervariable V3 region of the 16S rRNA gene revealed much higher bacterial diversity than the 130 sequences from the full-length 16S rRNA gene clone library. The 92 operational taxonomic unit (OTUs) detected using pyrosequencing belonged to 45 families, whereas the 37 OTUs found in the clone library belonged to 25 families. Most sequences obtained from the clone library had equivalents in the pyrosequencing reads. However, 64 OTUs detected by pyrosequencing were not represented in the clone library. Our results demonstrate that pyrosequencing of the V3 region of the 16S rRNA gene is not only a powerful tool for discovering low-abundance bacterial populations but is also reliable for dissecting the bacterial community structure in a wastewater environment.     

Application of Ion Torrent Sequencing to the Assessment of the Effect of Alkali Ballast Water Treatment on Microbial Community Diversity

The impact of NaOH as a ballast water treatment (BWT) on microbial community diversity was assessed using the 16S rRNA gene based Ion Torrent sequencing with its new 400 base chemistry. Ballast water samples from a Great Lakes ship were collected from the intake and discharge of both control and NaOH (pH 12) treated tanks and were analyzed in duplicates. One set of duplicates was treated with the membrane-impermeable DNA cross-linking reagent propidium mono-azide (PMA) prior to PCR amplification to differentiate between live and dead microorganisms. Ion Torrent sequencing generated nearly 580,000 reads for 31 bar-coded samples and revealed alterations of the microbial community structure in ballast water that had been treated with NaOH. Rarefaction analysis of the Ion Torrent sequencing data showed that BWT using NaOH significantly decreased microbial community diversity relative to control discharge (p<0.001). UniFrac distance based principal coordinate analysis (PCoA) plots and UPGMA tree analysis revealed that NaOH-treated ballast water microbial communities differed from both intake communities and control discharge communities. After NaOH treatment, bacteria from the genus Alishewanella became dominant in the NaOH-treated samples, accounting for <0.5% of the total reads in intake samples but more than 50% of the reads in the treated discharge samples. The only apparent difference in microbial community structure between PMA-processed and non-PMA samples occurred in intake water samples, which exhibited a significantly higher amount of PMA-sensitive cyanobacteria/chloroplast 16S rRNA than their corresponding non-PMA total DNA samples. The community assembly obtained using Ion Torrent sequencing was comparable to that obtained from a subset of samples that were also subjected to 454 pyrosequencing. This study showed the efficacy of alkali ballast water treatment in reducing ballast water microbial diversity and demonstrated the application of new Ion Torrent sequencing techniques to microbial community studies.     

TBC: A clustering algorithm based on prokaryotic taxonomy

High-throughput DNA sequencing technologies have revolutionized the study of microbial ecology. Massive sequencing of PCR amplicons of the 16S rRNA gene has been widely used to understand the microbial community structure of a variety of environmental samples. The resulting sequencing reads are clustered into operational taxonomic units that are then used to calculate various statistical indices that represent the degree of species diversity in a given sample. Several algorithms have been developed to perform this task, but they tend to produce different outcomes. Herein, we propose a novel sequence clustering algorithm, namely Taxonomy-Based Clustering (TBC). This algorithm incorporates the basic concept of prokaryotic taxonomy in which only comparisons to the type strain are made and used to form species while omitting full-scale multiple sequence alignment. The clustering quality of the proposed method was compared with those of MOTHUR, BLASTClust, ESPRIT-Tree, CD-HIT, and UCLUST. A comprehensive comparison using three different experimental datasets produced by pyrosequencing demonstrated that the clustering obtained using TBC is comparable to those obtained using MOTHUR and ESPRIT-Tree and is computationally efficient. The program was written in JAVA and is available from .     

High-resolution SAR11 ecotype dynamics at the Bermuda Atlantic Time-series Study site by phylogenetic placement of pyrosequences

Advances in next-generation sequencing technologies are providing longer nucleotide sequence reads that contain more information about phylogenetic relationships. We sought to use this information to understand the evolution and ecology of bacterioplankton at our long-term study site in the Western Sargasso Sea. A bioinformatics pipeline called PhyloAssigner was developed to align pyrosequencing reads to a reference multiple sequence alignment of 16S ribosomal RNA (rRNA) genes and assign them phylogenetic positions in a reference tree using a maximum likelihood algorithm. Here, we used this pipeline to investigate the ecologically important SAR11 clade of Alphaproteobacteria. A combined set of 2.7 million pyrosequencing reads from the 16S rRNA V1–V2 regions, representing 9 years at the Bermuda Atlantic Time-series Study (BATS) site, was quality checked and parsed into a comprehensive bacterial tree, yielding 929 036 Alphaproteobacteria reads. Phylogenetic structure within the SAR11 clade was linked to seasonally recurring spatiotemporal patterns. This analysis resolved four new SAR11 ecotypes in addition to five others that had been described previously at BATS. The data support a conclusion reached previously that the SAR11 clade diversified by subdivision of niche space in the ocean water column, but the new data reveal a more complex pattern in which deep branches of the clade diversified repeatedly across depth strata and seasonal regimes. The new data also revealed the presence of an unrecognized clade of Alphaproteobacteria, here named SMA-1 (Sargasso Mesopelagic Alphaproteobacteria, group 1), in the upper mesopelagic zone. The high-resolution phylogenetic analyses performed herein highlight significant, previously unknown, patterns of evolutionary diversification, within perhaps the most widely distributed heterotrophic marine bacterial clade, and strongly links to ecosystem regimes.