Pyrosequencing Datasets Research Articles

Molecular diversity and biogeography of benthic ciliates in the Bohai Sea and Yellow Sea

This study explored the molecular diversity and biogeography of benthic ciliates in Chinese marginal seas, the Bohai Sea (BHS), North Yellow Sea (NYS) and South Yellow Sea (SYS). From a previous 18S rRNA gene pyrosequencing dataset of the benthic microeukaryotes, we retrieved the sequences affiliated with phylum Ciliophora and analyzed alpha and beta diversities of ciliate communities. We found that BHS had the highest ciliate operational taxonomic unit (OTU) richness than NYS and SYS, whereas the richness was not significantly different between summer and winter. Among all the measured environmental variables, water depth showed consistently the strongest correlations with alpha diversities. Overall, the class Spirotrichea (mostly Choreotrichia and unassigned lineages within the class) dominated the communities in terms of both relative proportion of sequences (77.0%) and OTU richness (66.5%). OTU-level ciliate community structure was significant different among the three basins, but not between the seasons. Structurally, significant differences in relative proportion among the basins were detected for the class Litostomatea, but not for other classes. Partial Mantel tests demonstrated that water depth difference was more important than geographic and environment distances in shaping the community structure of benthic ciliates in the studied area. About 60% OTUs were not assigned at a class or order level and at least 45% OTUs shared a sequence similarity no more than 97% with the described species, indicating a great potential for ciliate species discovery in the offshore sediments. Compared with previous morphology-based surveys, the spatial pattern of ciliate diversity (decreasing from NYS to SYS) is also identified in the present study. Nevertheless, structurally, the dominant class appeared to be Spirotrichea in the sequencing dataset, which differs from previous morphology-based results (dominance of classes Prostomatea and Karyorelictea in biomass). The potential causes for the discrepancies between molecular and morphological findings are also discussed.

Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants.

Microsatellites, or simple sequence repeats (SSRs), are one of the most informative and multi-purpose genetic markers exploited in plant functional genomics. However, the discovery of SSRs and development using traditional methods are laborious, time-consuming, and costly. Recently, the availability of high-throughput sequencing technologies has enabled researchers to identify a substantial number of microsatellites at less cost and effort than traditional approaches. Illumina is a noteworthy transcriptome sequencing technology that is currently used in SSR marker development. Although 454 pyrosequencing datasets can be used for SSR development, this type of sequencing is no longer supported. This review aims to present an overview of the next generation sequencing, with a focus on the efficient use of de novo transcriptome sequencing (RNA-Seq) and related tools for mining and development of microsatellites in plants.

Surface ocean metabarcoding confirms limited diversity in planktonic foraminifera but reveals unknown hyper-abundant lineages

Since the advent of DNA metabarcoding surveys, the planktonic realm is considered a treasure trove of diversity, inhabited by a small number of abundant taxa, and a hugely diverse and taxonomically uncharacterized consortium of rare species. Here we assess if the apparent underestimation of plankton diversity applies universally. We target planktonic foraminifera, a group of protists whose known morphological diversity is limited, taxonomically resolved and linked to ribosomal DNA barcodes. We generated a pyrosequencing dataset of ~100,000 partial 18S rRNA foraminiferal sequences from 32 size fractioned photic-zone plankton samples collected at 8 stations in the Indian and Atlantic Oceans during the Tara Oceans expedition (2009–2012). We identified 69 genetic types belonging to 41 morphotaxa in our metabarcoding dataset. The diversity saturated at local and regional scale as well as in the three size fractions and the two depths sampled indicating that the diversity of foraminifera is modest and finite. The large majority of the newly discovered lineages occur in the small size fraction, neglected by classical taxonomy. These unknown lineages dominate the bulk [>0.8 µm] size fraction, implying that a considerable part of the planktonic foraminifera community biomass has its origin in unknown lineages.

Hypomethylation of the Interferon γ Gene as a Potential Risk Factor for Essential Hypertension: A Case-Control Study.

Essential hypertension (EH) is a multifactorial disease. Interferon-γ (IFN-γ) plays an important role in the onset of EH through cytokine-mediated systemic inflammatory responses. We aimed to determine whether the methylation status of the IFN-γ gene (IFNG) promoter is involved in the pathogenesis of EH. Six copies of CpG dinucleotides are distributed between 3,203 bp and 3,121 bp upstream from the transcription initiation site of IFNG, termed CpG1 to CpG6 in the 5'-to-3' direction. We recruited 96 patients with EH and 96 sex- and age-matched healthy subjects as controls. Using bisulfate pyrosequencing datasets, we analyzed the methylation status of the six CpG sites and thus found that CpG5 was consistently methylated in all of the 96 EH patients and 96 control subjects. Among the remaining five CpG sites, there was no significant difference in the methylation levels of CpG4 and CpG6 between the two groups. By contrast, CpG1 (P = 0.003) and CpG3 (P = 5.87 × 10-7) were highly methylated among the EH subjects compared with the controls, whereas CpG2 (P = 1.24 × 10-12) was significantly less methylated in among EH subjects. The methylation levels of CpG2 were still lower after adjustment with logistic regression (adjusted P = 0.032). The CpG2 methylation level was an effective marker of EH (area under curve = 0.384; P = 1.40 × 10-15). The present study shows that hypomethylation of the IFNG promoter is significantly related to the risk of EH, providing new insights into the pathogenesis of EH.

Higher DNA insert fragment sizes improve mitogenomic assemblies from metagenomic pyrosequencing datasets: an example using Limenitidinae butterflies (Lepidoptera, Nymphalidae)

A large number of diverse mitogenomic sequences can be obtained more easily and affordably via mitochondrial metagenomics, which generates high-throughput sequences directly from sheared DNA extractions and assembles mitogenomic sequences using a few bioinformatic processing steps. However, following de novo assembly analysis, the optimal DNA fragment insert size is unclear. In this study, four extracted Limenitidinae butterfly DNA samples were sonically fragmented, and two fragment size ranges (200–400 and 400–600 bp) of each sample were tagged with different barcodes, producing pyrosequencing datasets. The results show that the datasets generated from longer DNA insert fragments result in better coverage and more complete mitogenomic sequences, and the phylogenetic analysis shows high support at nodes, revealing that Athyma butterflies do not represent a monophyletic group. Therefore, we recommend using longer insert DNA fragment sizes to generate high-throughput datasets for obtaining complete mitogenomic sequences which can improve phylogenetic studies.

Exploring the oral microflora of preschool children.

The oral cavity is one of the most important and complicated habitats in our body and supports diverse microbial communities. In this study, we aimed to determine the bacterial diversity and composition of various oral micro-niches. Samples were collected from supragingival plaque, saliva, and tongue coating from 10 preschool children (30 samples total). 16S rRNA gene pyrosequencing dataset generated 314,639 clean reads with an average of 10,488 ± 2,787 reads per sample. The phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteria were predominant, accounting for more than 90% of the total sequences. We found the highest α diversity, microbial richness, and evenness in plaque, compared with saliva and tongue coating. Plaque was also distinguished from saliva and tongue coating by phylogenetic distances (weighted UniFrac). Taxa with different relative abundances were further identified, confirming the existence of microbial differences across the three niches. Core microbiomes were defined of each niche; however, only a small proportion of operational taxonomic units (8.07%) were shared by the three niches. Coaggregation between Actinomyces spp. and Streptococcus spp. and other correlations among periodontal pathogens, such as Prevotella, Fusobacteria, Capnocytophaga, and Tannerella, were shown by a co-occurrence network. In summary, our study provides a framework of oral microbial communities in the population of preschool children as a baseline for further studies of oral diseases related to microbes.

The diversity and structure of marine protists in the coastal waters of China revealed by morphological observation and 454 pyrosequencing

Pyrosequencing of the 18S rRNA gene has been widely adopted to study the eukaryotic diversity in various types of environments, and has an advantage over traditional morphology methods in exploring unknown microbial communities. To comprehensively assess the diversity and community composition of marine protists in the coastal waters of China, we applied both morphological observations and high-throughput sequencing of the V2 and V3 regions of 18S rDNA simultaneously to analyze samples collected from the surface layer of the Yellow and East China Seas. Dinoflagellates, diatoms and ciliates were the three dominant protistan groups as revealed by the two methods. Diatoms were the first dominant protistan group in the microscopic observations, with Skeletonema mainly distributed in the nearshore eutrophic waters and Chaetoceros in higher temperature and higher pH waters. The mixotrophic dinoflagellates, Gymnodinium and Gyrodinium, were more competitive in the oligotrophic waters. The pyrosequencing method revealed an extensive diversity of dinoflagellates. Chaetoceros was the only dominant diatom group in the pyrosequencing dataset. Gyrodinium represented the most abundant reads and dominated the offshore oligotrophic protistan community as they were in the microscopic observations. The dominance of parasitic dinoflagellates in the pyrosequencing dataset, which were overlooked in the morphological observations, indicates more attention should be paid to explore the potential role of this group. Both methods provide coherent clustering of samples. Nutrient levels, salinity and pH were the main factors influencing the distribution of protists. This study demonstrates that different primer pairs used in the pyrosequencing will indicate different protistan community structures. A suitable marker may reveal more comprehensive composition of protists and provide valuable information on environmental drivers.

Characterization of Pythium spp. Associated with Asymptomatic Soybean in Southeastern Pennsylvania

Soybean production in Pennsylvania has increased substantially over the past 20 years and is a highly valued field crop, together with corn. Soilborne pathogens such as Pythium spp. can contribute to soybean stand establishment issues, particularly under the conservation tillage practices that are common in the state. In this study, we collected soil samples from eight asymptomatic soybean-corn rotation fields across six counties in southeastern Pennsylvania between May and June 2012. Pythium spp. were isolated via baiting, and tested for aggressiveness on both soybean and corn using laboratory assays. In addition to our culture-based survey, we also assessed the use of cytochrome oxidase subunit 1 pyrosequencing as a culture-independent method for measuring Pythium spp. diversity from environmental samples. Diversity estimates were consistent between the culture-based and pyrosequencing datasets; however, important methodological biases inherent to culture-independent methods may have led to some differences. Our results show that several Pythium spp. previously characterized as soybean or corn pathogens are present in southeastern Pennsylvania, including Pythium irregulare, P. sylvaticum, and P. ultimum var. sporangiiferum, with isolates showing aggressive phenotypes in lab assays.

Assessing Bacterial Diversity in the Rhizosphere of Thymus zygis Growing in the Sierra Nevada National Park (Spain) through Culture-Dependent and Independent Approaches.

Little is known of the bacterial communities associated with the rhizosphere of wild plant species found in natural settings. The rhizosphere bacterial community associated with wild thyme, Thymus zygis L., plants was analyzed using cultivation, the creation of a near-full length 16S rRNA gene clone library and 454 amplicon pyrosequencing. The bacterial community was dominated by Proteobacteria (mostly Alphaproteobacteria and Betaproteobacteria), Actinobacteria, Acidobacteria, and Gemmatimonadetes. Although each approach gave a different perspective of the bacterial community, all classes/subclasses detected in the clone library and the cultured bacteria could be found in the pyrosequencing datasets. However, an exception caused by inconclusive taxonomic identification as a consequence of the short read length of pyrotags together with the detection of singleton sequences which corresponded to bacterial strains cultivated from the same sample highlight limitations and considerations which should be taken into account when analysing and interpreting amplicon datasets. Amplicon pyrosequencing of replicate rhizosphere soil samples taken a year later permit the definition of the core microbiome associated with Thymus zygis plants. Abundant bacterial families and predicted functional profiles of the core microbiome suggest that the main drivers of the bacterial community in the Thymus zygis rhizosphere are related to the nutrients originating from the plant root and to their participation in biogeochemical cycles thereby creating an intricate relationship with this aromatic plant to allow for a feedback ecological benefit.

Distinct compositions of free-living, particle-associated and benthic communities of the Roseobacter group in the North Sea.

The Roseobacter group is one of the predominant lineages in the marine environment. While most investigations focus on pelagic roseobacters, the distribution and metabolic potential of benthic representatives is less understood. In this study, the diversity of the Roseobacter group was characterized in sediment and water samples along the German/Scandinavian North Sea coast by 16S rRNA gene analysis and cultivation-based methods. Molecular analysis indicated an increasing diversity between communities of the Roseobacter group from the sea surface to the seafloor and revealed distinct compositions of free-living and attached fractions. Culture media containing dimethyl sulfide (DMS), dimethyl sulfonium propionate (DMSP) or dimethyl sulfoxide (DMSO) stimulated growth of roseobacters showing highest most probable numbers (MPN) in DMSO-containing dilutions of surface sediments (2.1 × 10(7) roseobacterscm(-3)). Twenty roseobacters (12 from sediments) were isolated from DMSP- and DMS-containing cultures. Sequences of the isolates represented 0.04% of all Bacteria and 4.7% of all roseobacters in the pyrosequencing dataset from sediments. Growth experiments with the isolate Shimia sp. SK013 indicated that benthic roseobacters are able to switch between aerobic and anaerobic utilization of organic sulfur compounds. This response to changing redox conditions might be an adaptation to specific environmental conditions on particles and in sediments.

High-Throughput Sequencing-The Key to Rapid Biodiversity Assessment of Marine Metazoa?

The applications of traditional morphological and molecular methods for species identification are greatly restricted by processing speed and on a regional or greater scale are generally considered unfeasible. In this context, high-throughput sequencing, or metagenetics, has been proposed as an efficient tool to document biodiversity. Here we evaluated the effectiveness of 454 pyrosequencing in marine metazoan community analysis using the 18S rDNA: V1-V2 region. Multiplex pyrosequencing of the V1-V2 region was used to analyze two pooled samples of DNA, one comprising 118 and the other 37 morphologically identified species, and one natural sample taken directly from a North Sea zooplankton community. A DNA reference library comprising all species represented in the pooled samples was created by Sanger sequencing, and this was then used to determine the optimal similarity threshold for species delineation. The optimal threshold was found at 99% species similarity, with 85% identification success. Pyrosequencing was able to identify between fewer species: 67% and 78% of the species in the two pooled samples. Also, a large number of sequences for three species that were not included in the pooled samples were amplified by pyrosequencing, suggesting preferential amplification of some genotypes and the sensitivity of this approach to even low levels of contamination. Conversely, metagenetic analysis of the natural zooplankton sample identified many more species (particularly gelatinous zooplankton and meroplankton) than morphological analysis of a formalin-fixed sample from the same sampling site, suggesting an increased level of taxonomic resolution with pyrosequencing. The study demonstrated that, based on the V1-V2 region, 454 sequencing does not provide accurate species differentiation and reliable taxonomic classification, as it is required in most biodiversity monitoring. The analysis of artificially prepared samples indicated that species detection in pyrosequencing datasets is complicated by potential PCR-based biases and that the V1-V2 marker is poorly resolved for some taxa.

NGS-eval: NGS Error analysis and novel sequence VAriant detection tooL.

Massively parallel sequencing of microbial genetic markers (MGMs) is used to uncover the species composition in a multitude of ecological niches. These sequencing runs often contain a sample with known composition that can be used to evaluate the sequencing quality or to detect novel sequence variants. With NGS-eval, the reads from such (mock) samples can be used to (i) explore the differences between the reads and their references and to (ii) estimate the sequencing error rate. This tool maps these reads to references and calculates as well as visualizes the different types of sequencing errors. Clearly, sequencing errors can only be accurately calculated if the reference sequences are correct. However, even with known strains, it is not straightforward to select the correct references from databases. We previously analysed a pyrosequencing dataset from a mock sample to estimate sequencing error rates and detected sequence variants in our mock community, allowing us to obtain an accurate error estimation. Here, we demonstrate the variant detection and error analysis capability of NGS-eval with Illumina MiSeq reads from the same mock community. While tailored towards the field of metagenomics, this server can be used for any type of MGM-based reads. NGS-eval is available at http://www.ibi.vu.nl/programs/ngsevalwww/.

CATCh, an ensemble classifier for chimera detection in 16S rRNA sequencing studies.

In ecological studies, microbial diversity is nowadays mostly assessed via the detection of phylogenetic marker genes, such as 16S rRNA. However, PCR amplification of these marker genes produces a significant amount of artificial sequences, often referred to as chimeras. Different algorithms have been developed to remove these chimeras, but efforts to combine different methodologies are limited. Therefore, two machine learning classifiers (reference-based and de novo CATCh) were developed by integrating the output of existing chimera detection tools into a new, more powerful method. When comparing our classifiers with existing tools in either the reference-based or de novo mode, a higher performance of our ensemble method was observed on a wide range of sequencing data, including simulated, 454 pyrosequencing, and Illumina MiSeq data sets. Since our algorithm combines the advantages of different individual chimera detection tools, our approach produces more robust results when challenged with chimeric sequences having a low parent divergence, short length of the chimeric range, and various numbers of parents. Additionally, it could be shown that integrating CATCh in the preprocessing pipeline has a beneficial effect on the quality of the clustering in operational taxonomic units.

Pooled assembly of marine metagenomic datasets: enriching annotation through chimerism

Despite advances in high-throughput sequencing, marine metagenomic samples remain largely opaque. A typical sample contains billions of microbial organisms from thousands of genomes and quadrillions of DNA base pairs. Its derived metagenomic dataset underrepresents this complexity by orders of magnitude because of the sparseness and shortness of sequencing reads. Read shortness and sequencing errors pose a major challenge to accurate species and functional annotation. This includes distinguishing known from novel species. Often the majority of reads cannot be annotated and thus cannot help our interpretation of the sample. Here, we demonstrate quantitatively how careful assembly of marine metagenomic reads within, but also across, datasets can alleviate this problem. For 10 simulated datasets, each with species complexity modeled on a real counterpart, chimerism remained within the same species for most contigs (97%). For 42 real pyrosequencing ('454') datasets, assembly increased the proportion of annotated reads, and even more so when datasets were pooled, by on average 1.6% (max 6.6%) for species, 9.0% (max 28.7%) for Pfam protein domains and 9.4% (max 22.9%) for PANTHER gene families. Our results outline exciting prospects for data sharing in the metagenomics community. While chimeric sequences should be avoided in other areas of metagenomics (e.g. biodiversity analyses), conservative pooled assembly is advantageous for annotation specificity and sensitivity. Intriguingly, our experiment also found potential prospects for (low-cost) discovery of new species in 'old' data. dgerloff@ffame.org Supplementary data are available at Bioinformatics online.

Analysis of the evolution and structure of a complex intrahost viral population in chronic hepatitis C virus mapped by ultradeep pyrosequencing.

Hepatitis C virus (HCV) causes chronic infection in up to 50% to 80% of infected individuals. Hypervariable region 1 (HVR1) variability is frequently studied to gain an insight into the mechanisms of HCV adaptation during chronic infection, but the changes to and persistence of HCV subpopulations during intrahost evolution are poorly understood. In this study, we used ultradeep pyrosequencing (UDPS) to map the viral heterogeneity of a single patient over 9.6 years of chronic HCV genotype 4a infection. Informed error correction of the raw UDPS data was performed using a temporally matched clonal data set. The resultant data set reported the detection of low-frequency recombinants throughout the study period, implying that recombination is an active mechanism through which HCV can explore novel sequence space. The data indicate that polyvirus infection of hepatocytes has occurred but that the fitness quotients of recombinant daughter virions are too low for the daughter virions to compete against the parental genomes. The subpopulations of parental genomes contributing to the recombination events highlighted a dynamic virome where subpopulations of variants are in competition. In addition, we provide direct evidence that demonstrates the growth of subdominant populations to dominance in the absence of a detectable humoral response. Analysis of ultradeep pyrosequencing data sets derived from virus amplicons frequently relies on software tools that are not optimized for amplicon analysis, assume random incorporation of sequencing errors, and are focused on achieving higher specificity at the expense of sensitivity. Such analysis is further complicated by the presence of hypervariable regions. In this study, we made use of a temporally matched reference sequence data set to inform error correction algorithms. Using this methodology, we were able to (i) detect multiple instances of hepatitis C virus intrasubtype recombination at the E1/E2 junction (a phenomenon rarely reported in the literature) and (ii) interrogate the longitudinal quasispecies complexity of the virome. Parallel to the UDPS, isolation of IgG-bound virions was found to coincide with the collapse of specific viral subpopulations.

HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data

BackgroundCurrent-generation sequencing technologies are able to produce low-cost, high-throughput reads. However, the produced reads are imperfect and may contain various sequencing errors. Although many error correction methods have been developed in recent years, none explicitly targets homopolymer-length errors in the 454 sequencing reads.ResultsWe present HECTOR, a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data. In this algorithm, for the first time we have investigated a novel homopolymer spectrum based approach to handle homopolymer insertions or deletions, which are the dominant sequencing errors in 454 pyrosequencing reads. We have evaluated the performance of HECTOR, in terms of correction quality, runtime and parallel scalability, using both simulated and real pyrosequencing datasets. This performance has been further compared to that of Coral, a state-of-the-art error corrector which is based on multiple sequence alignment and Acacia, a recently published error corrector for amplicon pyrosequences. Our evaluations reveal that HECTOR demonstrates comparable correction quality to Coral, but runs 3.7× faster on average. In addition, HECTOR performs well even when the coverage of the dataset is low.ConclusionOur homopolymer spectrum based approach is theoretically capable of processing arbitrary-length homopolymer-length errors, with a linear time complexity. HECTOR employs a multi-threaded design based on a master-slave computing model. Our experimental results show that HECTOR is a practical 454 pyrosequencing read error corrector which is competitive in terms of both correction quality and speed. The source code and all simulated data are available at: http://hector454.sourceforge.net.

Pulsed blooms and persistent oil-degrading bacterial populations in the water column during and after the Deepwater Horizon blowout

One of the defining features of the Deepwater Horizon oil spill was the rapid formation and persistence of a hydrocarbon plume in deep water. Here we use 16S rRNA gene clone libraries and pyrosequencing of 16S rRNA gene fragments to outline the temporal dynamics of the bacterial community in the water column near the Macondo wellhead. Our timeline starts with the pre-spill (March 2010) status of the water column bacterial community, continues through the bacterial enrichments dominating the hydrocarbon plume after the blowout (DWH Oceanospirillales, Cycloclasticus, Colwellia in late May 2010), and leads towards post-spill bacterial communities with molecular signatures related to degradation of phytoplankton pulses (September and October 2010; July 2011) in the water column near the Macondo wellhead. We document a dramatic transition as the complex bacterial community before the oil spill was temporarily overwhelmed by a few specialized bacterial groups responding to the massive influx of hydrocarbons in May 2010. In September and October 2010, this bacterial bloom had been replaced by a diversified bacterial community which resembled its predecessor prior to the spill. Notably, the post-plume 16S rRNA gene clone libraries and pyrosequencing datasets illustrated the continued presence of oil-degrading bacteria in the water column near the Macondo wellhead which we posit to represent an inherent signature of hydrocarbon catabolic potential to the Gulf of Mexico. The pyroseqencing results detected and tracked minority bacterial populations that were not visible in the conventional 16S rRNA gene clone libraries and allowed us to identify natural reservoirs of the Deepwater Horizon Oceanospirillales within and outside of the Gulf of Mexico.

Taxonomic relatedness shapes bacterial assembly in activated sludge of globally distributed wastewater treatment plants

Activated sludge (AS), which has been in use for 100 years, has been the most popular biological process in various wastewater treatment plants (WWTPs), in which bacteria plays central roles in pollutant removal. However, the potential relationship between bacteria taxa and the niches occupied by specific functional bacteria in AS are largely unknown. Here, correlation-based network analysis was applied to a 16S rRNA gene pyrosequencing dataset containing > 760 000 sequences of 50 AS samples from globally distributed full-scale WWTPs. The results showed that (i) bacterial assembly in AS was nonrandomly arranged by taxonomic relatedness and (ii) intra- and inter-phylum/class co-occurrence higher than expected by chance was induced by multiple deterministic processes, such as habitat filtering and competition. Moreover, based on bacterial occupancy, a prevalent core set of cosmopolitan functional bacteria (e.g. multiple nitrogen-cycling-related bacteria) was widely distributed in the AS of different WWTPs, showing strong ecological associations among them. Additionally, the AS network has statistical and structural characteristics similar to those of previously reported ecological networks, such as power-law connectivity distribution and nonrandomly connected properties. Overall, this work provides novel insights into the bacterial associations within AS and sheds light on the ecological rules guiding bacterial assembly in WWTPs.

Quality Score Based Identification and Correction of Pyrosequencing Errors

Massively-parallel DNA sequencing using the 454/pyrosequencing platform allows in-depth probing of diverse sequence populations, such as within an HIV-1 infected individual. Analysis of this sequence data, however, remains challenging due to the shorter read lengths relative to that obtained by Sanger sequencing as well as errors introduced during DNA template amplification and during pyrosequencing. The ability to distinguish real variation from pyrosequencing errors with high sensitivity and specificity is crucial to interpreting sequence data. We introduce a new algorithm, CorQ (Correction through Quality), which utilizes the inherent base quality in a sequence-specific context to correct for homopolymer and non-homopolymer insertion and deletion (indel) errors. CorQ also takes uneven read mapping into account for correcting pyrosequencing miscall errors and it identifies and corrects carry forward errors. We tested the ability of CorQ to correctly call SNPs on a set of pyrosequences derived from ten viral genomes from an HIV-1 infected individual, as well as on six simulated pyrosequencing datasets generated using non-zero error rates to emulate errors introduced by PCR. When combined with the AmpliconNoise error correction method developed to remove ambiguities in signal intensities, we attained a 97% reduction in indel errors, a 98% reduction in carry forward errors, and >97% specificity of SNP detection. When compared to four other error correction methods, AmpliconNoise+CorQ performed at equal or higher SNP identification specificity, but the sensitivity of SNP detection was consistently higher (>98%) than other methods tested. This combined procedure will therefore permit examination of complex genetic populations with improved accuracy.

Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data

Summary The nuclear ribosomal internal transcribed spacer (ITS) region is the primary choice for molecular identification of fungi. Its two highly variable spacers (ITS1 and ITS2) are usually species specific, whereas the intercalary 5.8S gene is highly conserved. For sequence clustering and blast searches, it is often advantageous to rely on either one of the variable spacers but not the conserved 5.8S gene. To identify and extract ITS1 and ITS2 from large taxonomic and environmental data sets is, however, often difficult, and many ITS sequences are incorrectly delimited in the public sequence databases. We introduce ITSx, a Perl‐based software tool to extract ITS1, 5.8S and ITS2 – as well as full‐length ITS sequences – from both Sanger and high‐throughput sequencing data sets. ITSx uses hidden Markov models computed from large alignments of a total of 20 groups of eukaryotes, including fungi, metazoans and plants, and the sequence extraction is based on the predicted positions of the ribosomal genes in the sequences. ITSx has a very high proportion of true‐positive extractions and a low proportion of false‐positive extractions. Additionally, process parallelization permits expedient analyses of very large data sets, such as a one million sequence amplicon pyrosequencing data set. ITSx is rich in features and written to be easily incorporated into automated sequence analysis pipelines. ITSx paves the way for more sensitive blast searches and sequence clustering operations for the ITS region in eukaryotes. The software also permits elimination of non‐ITS sequences from any data set. This is particularly useful for amplicon‐based next‐generation sequencing data sets, where insidious non‐target sequences are often found among the target sequences. Such non‐target sequences are difficult to find by other means and would contribute noise to diversity estimates if left in the data set.