Library preparation methods for next-generation sequencing: tone down the bias

Analyzing Immunoglobulin Repertoires

Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis.

Systematic comparison of small RNA library preparation protocols for next-generation sequencing

Background

Next-generation sequencing technologies have revolutionized the study of small RNAs (sRNAs) on a genome-wide scale. However, classical sRNA library preparation methods introduce serious bias, mainly during adapter ligation steps. Several types of sRNA including plant microRNAs (miRNA), piwi-interacting RNAs (piRNA) in insects, nematodes and mammals, and small interfering RNAs (siRNA) in insects and plants contain a 2’-O-methyl (2’-OMe) modification at their 3′ terminal nucleotide. This inhibits 3′ adapter ligation and makes library preparation particularly challenging. To reduce bias, the NEBNext kit (New England Biolabs) uses polyethylene glycol (PEG), the NEXTflex V2 kit (BIOO Scientific) uses both randomised adapters and PEG, and the novel SMARTer (Clontech) and CATS (Diagenode) kits avoid ligation altogether. Here we compared these methods with Illumina’s classical TruSeq protocol regarding the detection of normal and 2’ OMe RNAs. In addition, we modified the TruSeq and NEXTflex protocols to identify conditions that improve performance.

Results

Among the five kits tested with their respective standard protocols, the SMARTer and CATS kits had the lowest levels of bias but also had a strong formation of side products, and as a result performed relatively poorly with biological samples; NEXTflex detected the largest numbers of different miRNAs. The use of a novel type of randomised adapters called MidRand-Like (MRL) adapters and PEG improved the detection of 2’ OMe RNAs both in the TruSeq as well as in the NEXTflex protocol.

Conclusions

While it is commonly accepted that biases in sRNA library preparation protocols are mainly due to adapter ligation steps, the ligation-free protocols were not the best performing methods. Our modified versions of the TruSeq and NEXTflex protocols provide an improved tool for the study of 2’ OMe RNAs.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4491-6) contains supplementary material, which is available to authorized users.

In vivo microbiome and associated immune markers: New insights into the pathogenesis of vaginal dysbiosis

The microbiota fulfils a key role in the training and function of the immune system, which contributes to the symbiosis between the host and complex microbial communities. In this study, we characterized the interplay between vaginal bacteria and local immune mediators during dysbiosis in selected women of reproductive age who were grouped according to Nugent’s criteria. The abundance of Gardnerella vaginalis and Bifidobacterium breve was increased in the intermediate dysbiotic status, while the presence of a plethora of non-resident bacteria characterized the group with overt vaginosis. In response to these increases, the anti-inflammatory IL1ra and pro-inflammatory IL2 increased, while the embryo trophic factors FGFβ and GMCSF decreased compared to the healthy milieu. A specific pattern, including IL1α, IL1β, IL8, MIG, MIP1α and RANTES, distinguished the intermediate group from the vaginosis group, while IL5 and IL13, which are secreted by Th2 cells, were significantly associated with the perturbation of the commensals Lactobacilli, Gardnerella and Ureaplasma. Summarizing, we postulate that although the dysbiotic condition triggers a pro-inflammatory process, the presence of a steady state level of Th2 may influence clinical manifestations. These results raise clinically relevant questions regarding the use of vaginal immunological markers as efficacious tools to monitor microbial alterations.

Surveillance of Foodborne Pathogens: Towards Diagnostic Metagenomics of Fecal Samples

Diagnostic metagenomics is a rapidly evolving laboratory tool for culture-independent tracing of foodborne pathogens. The method has the potential to become a generic platform for detection of most pathogens and many sample types. Today, however, it is still at an early and experimental stage. Studies show that metagenomic methods, from sample storage and DNA extraction to library preparation and shotgun sequencing, have a great influence on data output. To construct protocols that extract the complete metagenome but with minimal bias is an ongoing challenge. Many different software strategies for data analysis are being developed, and several studies applying diagnostic metagenomics to human clinical samples have been published, detecting, and sometimes, typing bacterial infections. It is possible to obtain a draft genome of the pathogen and to develop methods that can theoretically be applied in real-time. Finally, diagnostic metagenomics can theoretically be better geared than conventional methods to detect co-infections. The present review focuses on the current state of test development, as well as practical implementation of diagnostic metagenomics to trace foodborne bacterial infections in fecal samples from animals and humans.

RNA-Seq and Expression Arrays: Selection Guidelines for Genome-Wide Expression Profiling

The development of genome-wide gene expression profiling technologies over the past two decades has produced great opportunity for researchers to explore the transcriptome and to better understand biological systems and their perturbation. In this chapter we provide an overview of microarray and massively parallel sequencing technologies and their application to gene expression analysis. We discuss factors that impact expression data generation and analysis that which should be considered in the application of these technology platforms. We further present the results of a simple illustration study to highlight performance similarities and differences in expression profiling of protein-coding mRNAs with each platform. Based on technical and analytical differences between the two platforms, reports in the literature comparing arrays and RNA-Seq for gene expression, and our own example study and experience, we provide recommendations for platform selection for gene expression studies.

Small sample sizes in high-throughput miRNA screens: A common pitfall for the identification of miRNA biomarkers

Since the discovery of microRNAs (miRNAs), circulating miRNAs have been proposed as biomarkers for disease. Consequently, many groups have tried to identify circulating miRNA biomarkers for various types of diseases including cardiovascular disease and cancer. However, the replicability of these experiments has been disappointingly low. In order to identify circulating miRNA candidate biomarkers, in general, first an unbiased high-throughput screen is performed in which a large number of miRNAs is detected and quantified in the circulation. Because these are costly experiments, many of such studies have been performed using a low number of study subjects (small sample size). Due to lack of power in small sample size experiments, true effects are often missed and many of the detected effects are wrong. Therefore, it is important to have a good estimate of the appropriate sample size for a miRNA high-throughput screen. In this review, we discuss the effects of small sample sizes in high-throughput screens for circulating miRNAs. Using data from a miRNA high-throughput experiment on isolated monocytes, we illustrate that the implementation of power calculations in a high-throughput miRNA discovery experiment will avoid unnecessarily large and expensive experiments, while still having enough power to be able to detect clinically important differences.

Single molecule sequencing of the M13 virus genome without amplification

Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.

Gene-Based Pathogen Detection: Can We Use qPCR to Predict the Outcome of Diagnostic Metagenomics?

In microbial food safety, molecular methods such as quantitative PCR (qPCR) and next-generation sequencing (NGS) of bacterial isolates can potentially be replaced by diagnostic shotgun metagenomics. However, the methods for pre-analytical sample preparation are often optimized for qPCR, and do not necessarily perform equally well for qPCR and sequencing. The present study investigates, through screening of methods, whether qPCR can be used as an indicator for the optimization of sample preparation for NGS-based shotgun metagenomics with a diagnostic focus. This was used on human fecal samples spiked with 10³ or 10⁶ colony-forming units (CFU)/g Campylobacter jejuni, as well as porcine fecal samples spiked with 10³ or 10⁶ CFU/g Salmonella typhimurium. DNA was extracted from the samples using variations of two widely used kits. The following quality parameters were measured: DNA concentration, qPCR, DNA fragmentation during library preparation, amount of DNA available for sequencing, amount of sequencing data, distribution of data between samples in a batch, and data insert size; none showed any correlation with the target ratio of the spiking organism detected in sequencing data. Surprisingly, diagnostic metagenomics can have better detection sensitivity than qPCR for samples spiked with 10³ CFU/g C. jejuni. The study also showed that qPCR and sequencing results may be different due to inhibition in one of the methods. In conclusion, qPCR cannot uncritically be used as an indicator for the optimization of sample preparation for diagnostic metagenomics.

Parallel mapping with site-directed hydroxyl radicals and micrococcal nuclease reveals structural features of positioned nucleosomes in vivo

Micrococcal nuclease (MNase) has been widely used for analyses of nucleosome locations in many organisms. However, due to its sequence preference, the interpretations of the positions and occupancies of nucleosomes using MNase have remained controversial. Next-generation sequencing (NGS) has also been utilized for analyses of MNase-digests, but some technical biases are commonly present in the NGS experiments. Here, we established a gel-based method to map nucleosome positions in Saccharomyces cerevisiae, using isolated nuclei as the substrate for the histone H4 S47C-site-directed chemical cleavage in parallel with MNase digestion. The parallel mapping allowed us to compare the chemically and enzymatically cleaved sites by indirect end-labeling and primer extension mapping, and thus we could determine the nucleosome positions and the sizes of the nucleosome-free regions (or nucleosome-depleted regions) more accurately, as compared to nucleosome mapping by MNase alone. The analysis also revealed that the structural features of the nucleosomes flanked by the nucleosome-free region were different from those within regularly arrayed nucleosomes, showing that the structures and dynamics of individual nucleosomes strongly depend on their locations. Moreover, we demonstrated that the parallel mapping results were generally consistent with the previous genome-wide chemical mapping and MNase-Seq results. Thus, the gel-based parallel mapping will be useful for the analysis of a specific locus under various conditions.

Modified RNA-seq method for microbial community and diversity analysis using rRNA in different types of environmental samples

RNA-seq-based SSU (small subunit) rRNA (ribosomal RNA) analysis has provided a better understanding of potentially active microbial community within environments. However, for RNA-seq library construction, high quantities of purified RNA are typically required. We propose a modified RNA-seq method for SSU rRNA-based microbial community analysis that depends on the direct ligation of a 5’ adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10–100 ng) and does not require a DNA removal step. The method was initially tested on three mock communities synthesized with enriched SSU rRNA of archaeal, bacterial and fungal isolates at different ratios, and was subsequently used for environmental samples of high or low biomass. For high-biomass salt-marsh sediments, enriched SSU rRNA and total nucleic acid-derived RNA-seq datasets revealed highly consistent community compositions for all of the SSU rRNA sequences, and as much as 46.4%-59.5% of 16S rRNA sequences were suitable for OTU (operational taxonomic unit)-based community and diversity analyses with complete coverage of V1-V2 regions. OTU-based community structures for the two datasets were also highly consistent with those determined by all of the 16S rRNA reads. For low-biomass samples, total nucleic acid-derived RNA-seq datasets were analyzed, and highly active bacterial taxa were also identified by the OTU-based method, notably including members of the previously underestimated genus Nitrospira and phylum Acidobacteria in tap water, members of the phylum Actinobacteria on a shower curtain, and members of the phylum Cyanobacteria on leaf surfaces. More than half of the bacterial 16S rRNA sequences covered the complete region of primer 8F, and non-coverage rates as high as 38.7% were obtained for phylum-unclassified sequences, providing many opportunities to identify novel bacterial taxa. This modified RNA-seq method will provide a better snapshot of diverse microbial communities, most notably by OTU-based analysis, even communities with low-biomass samples.

Standardization procedure for plasma biomarker analysis in rat models of epileptogenesis: Focus on circulating microRNAs

The World Health Organization estimates that globally 2.4 million people are diagnosed with epilepsy each year. In nearly 30% of these cases, epilepsy cannot be properly controlled by antiepileptic drugs. More importantly, treatments to prevent or modify epileptogenesis do not exist. Therefore, novel therapies are urgently needed. In this respect, it is important to identify which patients will develop epilepsy and which individually tailored treatment is needed. However, currently, we have no tools to identify the patients at risk, and diagnosis of epileptogenesis remains as a major unmet medical need, which relates to lack of diagnostic biomarkers for epileptogenesis. As the epileptogenic process in humans is typically slow, the use of animal models is justified to speed up biomarker discovery. We aim to summarize recommendations for molecular biomarker research and propose a standardized procedure for biomarker discovery in rat models of epileptogenesis. The potential of many phylogenetically conserved circulating noncoding small RNAs, including microRNAs (miRNAs), as biomarkers has been explored in various brain diseases, including epilepsy. Recent studies show the feasibility of detecting miRNAs in blood in both experimental models and human epilepsy. However, the analysis of circulating miRNAs in rodent models is challenging, which relates both to the lack of standardized sampling protocols and to analysis of miRNAs. We will discuss the issues critical for preclinical plasma biomarker discovery, such as documentation, blood and brain tissue sampling and collection, plasma separation and storage, RNA extraction, quality control, and RNA detection. We propose a protocol for standardization of procedures for discovery of circulating miRNA biomarkers in rat models of epileptogenesis. Ultimately, we hope that the preclinical standardization will facilitate clinical biomarker discovery for epileptogenesis in man.

Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing

Phytoplankton is the basis for aquatic food webs and mirrors the water quality. Conventionally, phytoplankton analysis has been done using time consuming and partly subjective microscopic observations, but next generation sequencing (NGS) technologies provide promising potential for rapid automated examination of environmental samples. Because many phytoplankton species have tough cell walls, methods for cell lysis and DNA or RNA isolation need to be efficient to allow unbiased nucleic acid retrieval. Here, we analyzed how two phytoplankton preservation methods, three commercial DNA extraction kits and their improvements, three RNA extraction methods, and two data analysis procedures affected the results of the NGS analysis. A mock community was pooled from phytoplankton species with variation in nucleus size and cell wall hardness. Although the study showed potential for studying Lugol-preserved sample collections, it demonstrated critical challenges in the DNA-based phytoplankton analysis in overall. The 18S rRNA gene sequencing output was highly affected by the variation in the rRNA gene copy numbers per cell, while sample preservation and nucleic acid extraction methods formed another source of variation. At the top, sequence-specific variation in the data quality introduced unexpected bioinformatics bias when the sliding-window method was used for the quality trimming of the Ion Torrent data. While DNA-based analyses did not correlate with biomasses or cell numbers of the mock community, rRNA-based analyses were less affected by different RNA extraction procedures and had better match with the biomasses, dry weight and carbon contents, and are therefore recommended for quantitative phytoplankton analyses.

Guidance Statement On BRCA1/2 Tumor Testing in Ovarian Cancer Patients

The approval, in 2015, of the first poly (adenosine diphosphate-ribose) polymerase inhibitor (PARPi; olaparib, Lynparza) for platinum-sensitive relapsed high-grade ovarian cancer with either germline or somatic BRCA1/2 deleterious mutations is changing the way that BRCA1/2 testing services are offered to patients with ovarian cancer. Ovarian cancer patients are now being referred for BRCA1/2 genetic testing for treatment decisions, in addition to familial risk estimation, and irrespective of a family history of breast or ovarian cancer. Furthermore, testing of tumor samples to identify the estimated 3%-9% of patients with somatic BRCA1/2 mutations who, in addition to germline carriers, could benefit from PARPi therapy is also now being considered. This new testing paradigm poses some challenges, in particular the technical and analytical difficulties of analyzing chemically challenged DNA derived from formalin-fixed, paraffin-embedded specimens. The current manuscript reviews some of these challenges and technical recommendations to consider when undertaking BRCA1/2 testing in tumor tissue samples to detect both germline and somatic BRCA1/2 mutations. Also provided are considerations for incorporating genetic analysis of ovarian tumor samples into the patient pathway and ethical requirements.

Bioinformatic approaches to interrogating vitamin D receptor signaling

Bioinformatics applies unbiased approaches to develop statistically-robust insight into health and disease. At the global, or "20,000 foot" view bioinformatic analyses of vitamin D receptor (NR1I1/VDR) signaling can measure where the VDR gene or protein exerts a genome-wide significant impact on biology; VDR is significantly implicated in bone biology and immune systems, but not in cancer. With a more VDR-centric, or "2000 foot" view, bioinformatic approaches can interrogate events downstream of VDR activity. Integrative approaches can combine VDR ChIP-Seq in cell systems where significant volumes of publically available data are available. For example, VDR ChIP-Seq studies can be combined with genome-wide association studies to reveal significant associations to immune phenotypes. Similarly, VDR ChIP-Seq can be combined with data from Cancer Genome Atlas (TCGA) to infer the impact of VDR target genes in cancer progression. Therefore, bioinformatic approaches can reveal what aspects of VDR downstream networks are significantly related to disease or phenotype.

Enrichment of Viral Nucleic Acids by Solution Hybrid Selection with Genus Specific Oligonucleotides

Despite recent advances, our knowledge of potential and rare human pathogens is far from exhaustive. Current molecular diagnostic tools mainly rely on the specific amplification of marker sequences and may overlook infections caused by unknown and rare pathogens. Using high-throughput sequencing (HTS) can solve this problem; but, due to the extremely low fraction of pathogen genetic material in clinical samples, its application is only cost-effective in special, rather than routine, cases. In this study, we present a method for the semi-specific enrichment of viral conservative sequences in a HTS library by hybridization in solution with genus-specific degenerate biotinylated oligonucleotides. Nucleic acids of the test viruses (yellow fever virus and Japanese encephalitis virus) were enriched by solution hybrid selection using pan-flavivirus oligonucleotides. Moreover, enterovirus (family: Picornaviridae, genus: Enterovirus) sequences were successfully enriched using foot-and-mouth disease virus (family: Picornaviridae, genus: Aphthovirus) oligonucleotide. The enrichment factor relative to the background nucleic acid was about 1,000-fold. As hybridization has less stringent oligonucleotide match requirements than PCR, few oligonucleotides are sufficient to cover the potential sequence variation in the whole genus and may even enrich nucleic acids of viruses of other related genera. Efficient enrichment of viral sequences makes its use in diagnostics cost-efficient.

Review of Clinical Next-Generation Sequencing

CONTEXT

- Next-generation sequencing (NGS) is a technology being used by many laboratories to test for inherited disorders and tumor mutations. This technology is new for many practicing pathologists, who may not be familiar with the uses, methodology, and limitations of NGS.

OBJECTIVE

- To familiarize pathologists with several aspects of NGS, including current and expanding uses; methodology including wet bench aspects, bioinformatics, and interpretation; validation and proficiency; limitations; and issues related to the integration of NGS data into patient care.

DATA SOURCES

- The review is based on peer-reviewed literature and personal experience using NGS in a clinical setting at a major academic center.

CONCLUSIONS

- The clinical applications of NGS will increase as the technology, bioinformatics, and resources evolve to address the limitations and improve quality of results. The challenge for clinical laboratories is to ensure testing is clinically relevant, cost-effective, and can be integrated into clinical care.

Novel ribonuclease activity of cusativin from Cucumis sativus for mapping nucleoside modifications in RNA

A recombinant ribonuclease, cusativin, was characterized for its cytidine-specific cleavage ability of RNA to map chemical modifications. Following purification of native cusativin protein as described before (Rojo et al. Planta 194:328, 17), partial amino acid sequencing was carried out to identify the corresponding protein coding gene in cucumber genome. Cloning and heterologous expression of the identified gene in Escherichia coli resulted in successful production of active protein as a C-terminal His-tag fusion protein. The ribonuclease activity and cleavage specificity of the fusion protein were confirmed with a variety of tRNA isoacceptors and total tRNA. Characterization of cusativin digestion products by ion-pairing reverse-phase liquid chromatography coupled with mass spectrometry (IP-RP-LC-MS) analysis revealed cleavage of CpA, CpG, and CpU phosphodiester bonds at the 3'-terminus of cytidine under optimal digestion conditions. Ribose methylation or acetylation of cytosine inhibited RNA cleavage. The CpC phosphodiester bond was also resistant to cusativin-mediated RNA cleavage; a feature to our knowledge has not been reported for other nucleobase-specific ribonucleases. Here, we demonstrate the analytical utility of such a novel feature for obtaining high-sequence coverage and accurate mapping of modified residues in substrate RNAs. Graphical abstract Cytidine-specific novel ribonuclease activity of cusativin.

Early experience with formalin-fixed paraffin-embedded (FFPE) based commercial clinical genomic profiling of gliomas-robust and informative with caveats

BACKGROUND

Commercial targeted genomic profiling with next generation sequencing using formalin-fixed paraffin embedded (FFPE) tissue has recently entered into clinical use for diagnosis and for the guiding of therapy. However, there is limited independent data regarding the accuracy or robustness of commercial genomic profiling in gliomas.

METHODS

As part of patient care, FFPE samples of gliomas from 71 patients were submitted for targeted genomic profiling to one commonly used commercial vendor, Foundation Medicine. Genomic alterations were determined for the following grades or groups of gliomas; Grade I/II, Grade III, primary glioblastomas (GBMs), recurrent primary GBMs, and secondary GBMs. In addition, FFPE samples from the same patients were independently assessed with conventional methods such as immunohistochemistry (IHC), Quantitative real-time PCR (qRT-PCR), or Fluorescence in situ hybridization (FISH) for three genetic alterations: IDH1 mutations, EGFR amplification, and EGFRvIII expression.

RESULTS

A total of 100 altered genes were detected by the aforementioned targeted genomic profiling assay. The number of different genomic alterations was significantly different between the five groups of gliomas and consistent with the literature. CDKN2A/B, TP53, and TERT were the most common genomic alterations seen in primary GBMs, whereas IDH1, TP53, and PIK3CA were the most common in secondary GBMs. Targeted genomic profiling demonstrated 92.3%-100% concordance with conventional methods. The targeted genomic profiling report provided an average of 5.5 drugs, and listed an average of 8.4 clinical trials for the 71 glioma patients studied but only a third of the trials were appropriate for glioma patients.

CONCLUSIONS

In this limited comparison study, this commercial next generation sequencing based-targeted genomic profiling showed a high concordance rate with conventional methods for the 3 genetic alterations and identified mutations expected for the type of glioma. While it may not be feasible to exhaustively independently validate a commercial genomic profiling assay, examination of a few markers provides some reassurance of its robustness. While potential targeted drugs are recommended based on genetic alterations, to date most targeted therapies have failed in glioblasomas so the usefulness of such recommendations will increase with development of novel and efficacious drugs.

Integration of quantitated expression estimates from polyA-selected and rRNA-depleted RNA-seq libraries

BACKGROUND

The availability of fast alignment-free algorithms has greatly reduced the computational burden of RNA-seq processing, especially for relatively poorly assembled genomes. Using these approaches, previous RNA-seq datasets could potentially be processed and integrated with newly sequenced libraries. Confounding factors in such integration include sequencing depth and methods of RNA extraction and selection. Different selection methods (typically, either polyA-selection or rRNA-depletion) omit different RNAs, resulting in different fractions of the transcriptome being sequenced. In particular, rRNA-depleted libraries sample a broader fraction of the transcriptome than polyA-selected libraries. This study aimed to develop a systematic means of accounting for library type that allows data from these two methods to be compared.

RESULTS

The method was developed by comparing two RNA-seq datasets from ovine macrophages, identical except for RNA selection method. Gene-level expression estimates were obtained using a two-part process centred on the high-speed transcript quantification tool Kallisto. Firstly, a set of reference transcripts was defined that constitute a standardised RNA space, with expression from both datasets quantified against it. Secondly, a simple ratio-based correction was applied to the rRNA-depleted estimates. The outcome is an almost perfect correlation between gene expression estimates, independent of library type and across the full range of levels of expression.

CONCLUSION

A combination of reference transcriptome filtering and a ratio-based correction can create equivalent expression profiles from both polyA-selected and rRNA-depleted libraries. This approach will allow meta-analysis and integration of existing RNA-seq data into transcriptional atlas projects.

Optimized Method for Robust Transcriptome Profiling of Minute Tissues Using Laser Capture Microdissection and Low-Input RNA-Seq

Obtaining high quality RNA from complex biological tissues, such as the brain, is needed for establishing high-fidelity cell-type specific transcriptomes. Although combining genetic labeling techniques with laser capture microdissection (LCM) is generally sufficient, concerns over RNA degradation and limited yields call into question results of many sequencing studies. Here we set out to address both of these issues by: (1) developing a fluorescence-assisted LCM protocol that yields high quality RNA from fresh-frozen tissues; and (2) determining a suitable RNA-Seq library generation method for limited amounts of RNA (1–5 ng total RNA). The latter focused on comparing commercially available kits able to produce libraries of sufficient concentration and complexity while limiting PCR amplification biases. We find that high quality RNA (RNA integrity number, RIN, >9) of sufficient concentration can be isolated from laser-captured material from thinly-sectioned tissues when digestion time and temperature are minimized. Furthermore, we found that library generation approaches that retain ribosomal RNA (rRNA) through cDNA library generation required fewer cycles of PCR, minimizing bias in the resulting libraries. Lastly, end stage depletion of rRNA prior to sequencing enriches for target RNAs, thereby increasing read depth and level of gene detection while decreasing sequencing costs. Here we describe our protocol for generating robust RNA-Seq libraries from laser-captured tissue and demonstrate that with this method, we obtain samples with RNA quality superior to the current standard in the LCM field, and show that low-input RNA-Seq kits that minimize PCR bias produce high fidelity sequencing metrics with less variability compared to current practices.

Characterization of porcine simple sequence repeat variation on a population scale with genome resequencing data

Simple sequence repeats (SSRs) are used as polymorphic molecular markers in many species. They contribute very important functional variations in a range of complex traits; however, little is known about the variation of most SSRs in pig populations. Here, using genome resequencing data, we identified ~0.63 million polymorphic SSR loci from more than 100 individuals. Through intensive analysis of this dataset, we found that the SSR motif composition, motif length, total length of alleles and distribution of alleles all contribute to SSR variability. Furthermore, we found that CG-containing SSRs displayed significantly lower polymorphism and higher cross-species conservation. With a rigorous filter procedure, we provided a catalogue of 16,527 high-quality polymorphic SSRs, which displayed reliable results for the analysis of phylogenetic relationships and provided valuable summary statistics for 30 individuals equally selected from eight local Chinese pig breeds, six commercial lean pig breeds and Chinese wild boars. In addition, from the high-quality polymorphic SSR catalogue, we identified four loci with potential loss-of-function alleles. Overall, these analyses provide a valuable catalogue of polymorphic SSRs to the existing pig genetic variation database, and we believe this catalogue could be used for future genome-wide genetic analysis.

Industrial Relevance of Chromosomal Copy Number Variation in Saccharomyces Yeasts

Chromosomal copy number variation (CCNV) plays a key role in evolution and health of eukaryotes. The unicellular yeast Saccharomyces cerevisiae is an important model for studying the generation, physiological impact, and evolutionary significance of CCNV. Fundamental studies of this yeast have contributed to an extensive set of methods for analyzing and introducing CCNV. Moreover, these studies provided insight into the balance between negative and positive impacts of CCNV in evolutionary contexts. A growing body of evidence indicates that CCNV not only frequently occurs in industrial strains of Saccharomyces yeasts but also is a key contributor to the diversity of industrially relevant traits. This notion is further supported by the frequent involvement of CCNV in industrially relevant traits acquired during evolutionary engineering. This review describes recent developments in genome sequencing and genome editing techniques and discusses how these offer opportunities to unravel contributions of CCNV in industrial Saccharomyces strains as well as to rationally engineer yeast chromosomal copy numbers and karyotypes.

Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.

Seafood Identification in Multispecies Products: Assessment of 16SrRNA, cytb, and COI Universal Primers' Efficiency as a Preliminary Analytical Step for Setting up Metabarcoding Next-Generation Sequencing Techniques

Few studies applying NGS have been conducted in the food inspection field, particularly on multispecies seafood products. A preliminary study screening the performance and the potential application in NGS analysis of 14 "universal primers" amplifying 16SrRNA, cytb, and COI genes in fish and cephalopods was performed. Species used in surimi preparation were chosen as target. An in silico analysis was conducted to test primers' coverage capacity by assessing mismatches (number and position) with the target sequences. The 9 pairs showing the best coverage capacity were tested in PCR on DNA samples of 53 collected species to assess their amplification performance (amplification rate and amplicon concentration). The results confirm that primers designed for the 16SrRNA gene amplification are the most suitable for NGS analysis also for identification of multispecies seafood products. In particular, the primer pair of Chapela et al. (2002) is the best candidate.

Changes in circulating microRNA levels can be identified as early as day 8 of pregnancy in cattle

Poor reproductive performance remains a major issue in the dairy industry, with low conception rates having a significant impact on milk production through extended calving intervals. A major limiting factor is the lack of reliable methods for early pregnancy diagnosis. Identification of animals within a herd that fail to conceive within 3 weeks after insemination would allow early re-insemination and shorten calving intervals. In a previous study, we found an increase in plasma miR-26a levels in Day 16-pregnant relative to non-pregnant heifers, however changes in miRNA levels that early during pregnancy were very small which likely prevented the identification of robust biomarkers. In this study, we extended our analyses to a wider interval during pregnancy (Days 8 to 60, n = 11 heifers) with the rationale that this may facilitate the identification of additional early pregnancy miRNA biomarkers. Using small RNA sequencing we identified a total of 77 miRNAs that were differentially expressed on Day 60 relative to Day 0 of pregnancy. We selected 14 miRNAs for validation by RT-qPCR and confirmed significant differences in the expression of let-7f, let-7c, miR-30c, miR-101, miR-26a, miR-205 and miR-143 between Days 0 and 60. RT-qPCR profiling throughout Days 0, 8, 16 and 60 of pregnancy showed a distinct increase in circulating levels of miR-26a (3.1-fold, P = 0.046) as early as Day 8 of pregnancy. In summary, in contrast to earlier stages of pregnancy (≤ Day 24), marked differences in the levels of multiple miRNAs can be detected in circulation by Day 60 in cattle. Retrospective analyses showed miR-26a levels to be increased in circulation as early as Day 8, sooner than previously reported in any species, suggesting a biological role for this miRNA in the very early events of pregnancy.

Biases in the SMART-DNA library preparation method associated with genomic poly dA/dT sequences

Avoiding biases in next generation sequencing (NGS) library preparation is crucial for obtaining reliable sequencing data. Recently, a new library preparation method has been introduced which has eliminated the need for the ligation step. This method, termed SMART (switching mechanism at the 5' end of the RNA transcript), is based on template switching reverse transcription. To date, there has been no systematic analysis of the additional biases introduced by this method. We analysed the genomic distribution of sequenced reads prepared from genomic DNA using the SMART methodology and found a strong bias toward long (≥12bp) poly dA/dT containing genomic loci. This bias is unique to the SMART-based library preparation and does not appear when libraries are prepared with conventional ligation based methods. Although this bias is obvious only when performing paired end sequencing, it affects single end sequenced samples as well. Our analysis demonstrates that sequenced reads originating from SMART-DNA libraries are heavily skewed toward genomic poly dA/dT tracts. This bias needs to be considered when deciding to use SMART based technology for library preparation.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches.

The fungal composition of natural biofinishes on oil-treated wood

BACKGROUND

Biofinished wood is considered to be a decorative and protective material for outdoor constructions, showing advantages compared to traditional treated wood in terms of sustainability and self-repair. Natural dark wood staining fungi are essential to biofinish formation on wood. Although all sorts of outdoor situated timber are subjected to fungal staining, the homogenous dark staining called biofinish has only been detected on specific vegetable oil-treated substrates. Revealing the fungal composition of various natural biofinishes on wood is a first step to understand and control biofinish formation for industrial application.

RESULTS

A culture-based survey of fungi in natural biofinishes on oil-treated wood samples showed the common wood stain fungus Aureobasidium and the recently described genus Superstratomyces to be predominant constituents. A culture-independent approach, based on amplification of the internal transcribed spacer regions, cloning and Sanger sequencing, resulted in clone libraries of two types of biofinishes. Aureobasidium was present in both biofinish types, but was only predominant in biofinishes on pine sapwood treated with raw linseed oil. Most cloned sequences of the other biofinish type (pine sapwood treated with olive oil) could not be identified. In addition, a more in-depth overview of the fungal composition of biofinishes was obtained with Illumina amplicon sequencing that targeted the internal transcribed spacer region 1. All investigated samples, that varied in wood species, (oil) treatments and exposure times, contained Aureobasidium and this genus was predominant in the biofinishes on pine sapwood treated with raw linseed oil. Lapidomyces was the predominant genus in most of the other biofinishes and present in all other samples. Surprisingly, Superstratomyces, which was predominantly detected by the cultivation-based approach, could not be found with the Illumina sequencing approach, while Lapidomyces was not detected in the culture-based approach.

CONCLUSIONS

Overall, the culture-based approach and two culture-independent methods that were used in this study revealed that natural biofinishes were composed of multiple fungal genera always containing the common wood staining mould Aureobasidium. Besides Aureobasidium, the use of other fungal genera for the production of biofinished wood has to be considered.

Virome Assembly and Annotation: A Surprise in the Namib Desert

Sequencing, assembly, and annotation of environmental virome samples is challenging. Methodological biases and differences in species abundance result in fragmentary read coverage; sequence reconstruction is further complicated by the mosaic nature of viral genomes. In this paper, we focus on biocomputational aspects of virome analysis, emphasizing latent pitfalls in sequence annotation. Using simulated viromes that mimic environmental data challenges we assessed the performance of five assemblers (CLC-Workbench, IDBA-UD, SPAdes, RayMeta, ABySS). Individual analyses of relevant scaffold length fractions revealed shortcomings of some programs in reconstruction of viral genomes with excessive read coverage (IDBA-UD, RayMeta), and in accurate assembly of scaffolds ≥50 kb (SPAdes, RayMeta, ABySS). The CLC-Workbench assembler performed best in terms of genome recovery (including highly covered genomes) and correct reconstruction of large scaffolds; and was used to assemble a virome from a copper rich site in the Namib Desert. We found that scaffold network analysis and cluster-specific read reassembly improved reconstruction of sequences with excessive read coverage, and that strict data filtering for non-viral sequences prior to downstream analyses was essential. In this study we describe novel viral genomes identified in the Namib Desert copper site virome. Taxonomic affiliations of diverse proteins in the dataset and phylogenetic analyses of circovirus-like proteins indicated links to the marine habitat. Considering additional evidence from this dataset we hypothesize that viruses may have been carried from the Atlantic Ocean into the Namib Desert by fog and wind, highlighting the impact of the extended environment on an investigated niche in metagenome studies.

Improved genome sequencing using an engineered transposase

Background

Next-generation sequencing (NGS) has transformed genomic research by reducing turnaround time and cost. However, no major breakthrough has been made in the upstream library preparation methods until the transposase-based Nextera method was invented. Nextera combines DNA fragmentation and barcoding in a single tube reaction and therefore enables a very fast workflow to sequencing-ready DNA libraries within a couple of hours. When compared to the traditional ligation-based methods, transposed-based Nextera has a slight insertion bias.

Results

Here we present the discovery of a mutant transposase (Tn5-059) with a lowered GC insertion bias through protein engineering. We demonstrate Tn5-059 reduces AT dropout and increases uniformity of genome coverage in both bacterial genomes and human genome. We also observe higher library diversity generated by Tn5-059 when compared to Nextera v2 for human exomes, which leads to less sequencing and lower cost per genome. In addition, when used for human exomes, Tn5-059 delivers consistent library insert size over a range of input DNA, allowing up to a tenfold variance from the 50 ng input recommendation.

Conclusions

Enhanced DNA input tolerance of Tn5-059 can translate to flexibility and robustness of workflow. DNA input tolerance together with superior uniformity of coverage and lower AT dropouts extend the applications of transposase based library preps. We discuss possible mechanisms of improvements in Tn5-059, and potential advantages of using the new mutant in varieties of applications including microbiome sequencing and chromatin profiling.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-016-0326-1) contains supplementary material, which is available to authorized users.

A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis

Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.

Ultrasensitive single-genome sequencing: accurate, targeted, next generation sequencing of HIV-1 RNA

BACKGROUND

Although next generation sequencing (NGS) offers the potential for studying virus populations in unprecedented depth, PCR error, amplification bias and recombination during library construction have limited its use to population sequencing and measurements of unlinked allele frequencies. Here we report a method, termed ultrasensitive Single-Genome Sequencing (uSGS), for NGS library construction and analysis that eliminates PCR errors and recombinants, and generates single-genome sequences of the same quality as the "gold-standard" of HIV-1 single-genome sequencing assay but with more than 100-fold greater depth.

RESULTS

Primer ID tagged cDNA was synthesized from mixtures of cloned BH10 wild-type and mutant HIV-1 transcripts containing ten drug resistance mutations. First, the resultant cDNA was divided and NGS libraries were generated in parallel using two methods: uSGS and a method applying long PCR primers to attach the NGS adaptors (LP-PCR-1). Second, cDNA was divided and NGS libraries were generated in parallel comparing 3 methods: uSGS and 2 methods adapted from more recent reports using variations of the long PCR primers to attach the adaptors (LP-PCR-2 and LP-PCR-3). Consistently, the uSGS method amplified a greater proportion of cDNAs, averaging 30% compared to 13% for LP-PCR-1, 21% for LP-PCR-2 and 14% for LP-PCR-3. Most importantly, when the uSGS sequences were binned according to their primer IDs, 94% of the bins did not contain PCR recombinant sequences versus only 55, 75 and 65% for LP-PCR-1, 2 and 3, respectively. Finally, when uSGS was applied to plasma samples from HIV-1 infected donors, both frequent and rare variants were detected in each sample and neighbor-joining trees revealed clusters of genomes driven by the linkage of these mutations, showing the lack of PCR recombinants in the datasets.

CONCLUSIONS

The uSGS assay can be used for accurate detection of rare variants and for identifying linkage of rare alleles associated with HIV-1 drug resistance. In addition, the method allows accurate in-depth analyses of the complex genetic relationships of viral populations in vivo.

In Silico Proficiency Testing for Clinical Next-Generation Sequencing

Quality assurance for clinical next-generation sequencing (NGS)-based assays is difficult given the complex methods and the range of sequence variants such assays can detect. As the number and range of mutations detected by clinical NGS assays has increased, it is difficult to apply standard analyte-specific proficiency testing (PT). Most current proficiency testing challenges for NGS are methods-based PT surveys that use DNA from reference samples engineered to harbor specific mutations that test both sequence generation and bioinformatics analysis. These methods-based PTs are limited by the number and types of mutations that can be physically introduced into a single DNA sample. In silico proficiency testing, which evaluates only the bioinformatics component of NGS assays, is a recently introduced PT method that allows for evaluation of numerous mutations spanning a range of variant classes. In silico PT data sets can be generated from simulated or actual sequencing data and are used to test alignment through variant detection and annotation steps. In silico PT has several advantages over the use of physical samples, including greater flexibility in tested variants, the ability to design laboratory-specific challenges, and lower costs. Herein, we review the use of in silico PT as an alternative to traditional methods-based PT as it is evolving in oncology applications and discuss how the approach is applicable more broadly.

Evaluation of library preparation methods for Illumina next generation sequencing of small amounts of DNA from foodborne parasites

Illumina library preparation methods for ultra-low input amounts were compared using genomic DNA from two foodborne parasites (Angiostrongylus cantonensis and Cyclospora cayetanensis) as examples. The Ovation Ultralow method resulted in libraries with the highest concentration and produced quality sequencing data, even when the input DNA was in the picogram range.

dupRadar: a Bioconductor package for the assessment of PCR artifacts in RNA-Seq data

BACKGROUND

PCR clonal artefacts originating from NGS library preparation can affect both genomic as well as RNA-Seq applications when protocols are pushed to their limits. In RNA-Seq however the artifactual reads are not easy to tell apart from normal read duplication due to natural over-sequencing of highly expressed genes. Especially when working with little input material or single cells assessing the fraction of duplicate reads is an important quality control step for NGS data sets. Up to now there are only tools to calculate the global duplication rates that do not take into account the effect of gene expression levels which leaves them of limited use for RNA-Seq data.

RESULTS

Here we present the tool dupRadar, which provides an easy means to distinguish the fraction of reads originating in natural duplication due to high expression from the fraction induced by artefacts. dupRadar assesses the fraction of duplicate reads per gene dependent on the expression level. Apart from the Bioconductor package dupRadar we provide shell scripts for easy integration into processing pipelines.

CONCLUSIONS

The Bioconductor package dupRadar offers straight-forward methods to assess RNA-Seq datasets for quality issues with PCR duplicates. It is aimed towards simple integration into standard analysis pipelines as a default QC metric that is especially useful for low-input and single cell RNA-Seq data sets.

Clinical potential of oligonucleotide-based therapeutics in the respiratory system

The discovery of an ever-expanding plethora of coding and non-coding RNAs with nodal and causal roles in the regulation of lung physiology and disease is reinvigorating interest in the clinical utility of the oligonucleotide therapeutic class. This is strongly supported through recent advances in nucleic acids chemistry, synthetic oligonucleotide delivery and viral gene therapy that have succeeded in bringing to market at least three nucleic acid-based drugs. As a consequence, multiple new candidates such as RNA interference modulators, antisense, and splice switching compounds are now progressing through clinical evaluation. Here, manipulation of RNA for the treatment of lung disease is explored, with emphasis on robust pharmacological evidence aligned to the five pillars of drug development: exposure to the appropriate tissue, binding to the desired molecular target, evidence of the expected mode of action, activity in the relevant patient population and commercially viable value proposition.

Quantifying the 'escapers' among RNA species

tRNAs are fundamental components of translation and emerging evidence places them more centrally in various other cellular processes. However, rather than being uniformly conserved, tRNA abundance is instead highly variable and adaptable. The amount of tRNA genes greatly differs among species. Moreover, even within the same genome, tRNA abundance shapes the proteome in a tissue- and cell-specific manner and is dynamically regulated in response to stress. Here, we review approaches for identification and quantification of tRNAs and their functional integrity. We discuss the resolution of each method and highlight new approaches with cell-wide resolution based on deep-sequencing technologies.

Clinical Next Generation Sequencing Outperforms Standard Microbiological Culture for Characterizing Polymicrobial Samples

BACKGROUND

Humans suffer from infections caused by single species or more complex polymicrobial communities. Identification of infectious bacteria commonly employs microbiological culture, which depends upon the in vitro propagation and isolation of viable organisms. In contrast, detection of bacterial DNA using next generation sequencing (NGS) allows culture-independent microbial profiling, potentially providing important new insights into the microbiota in clinical specimens.

METHODS

NGS 16S rRNA gene sequencing (NGS16S) was compared with culture using (a) synthetic polymicrobial samples for which the identity and abundance of organisms present were precisely defined and (b) primary clinical specimens.

RESULTS

Complex mixtures of at least 20 organisms were well resolved by NGS16S with excellent reproducibility. In mixed bacterial suspensions (10⁷ total genomes), we observed linear detection of a target organism over a 4-log concentration range (500-3 × 10⁶ genomes). NGS16S analysis more accurately recapitulated the known composition of synthetic samples than standard microbiological culture using nonselective media, which distorted the relative abundance of organisms and frequently failed to identify low-abundance pathogens. However, extended quantitative culture using selective media for each of the component species recovered the expected organisms at the proper abundance, validating NGS16S results. In an analysis of sputa from cystic fibrosis patients, NGS16S identified more clinically relevant pathogens than standard culture.

CONCLUSIONS

Biases in standard, nonselective microbiological culture lead to a distorted characterization of polymicrobial mixtures. NGS16S demonstrates enhanced reproducibility, quantification, and classification accuracy compared with standard culture, providing a more comprehensive, accurate, and culture-free analysis of clinical specimens.

Next-Generation Sequencing and Genome Editing in Plant Virology

Next-generation sequencing (NGS) has been applied to plant virology since 2009. NGS provides highly efficient, rapid, low cost DNA, or RNA high-throughput sequencing of the genomes of plant viruses and viroids and of the specific small RNAs generated during the infection process. These small RNAs, which cover frequently the whole genome of the infectious agent, are 21-24 nt long and are known as vsRNAs for viruses and vd-sRNAs for viroids. NGS has been used in a number of studies in plant virology including, but not limited to, discovery of novel viruses and viroids as well as detection and identification of those pathogens already known, analysis of genome diversity and evolution, and study of pathogen epidemiology. The genome engineering editing method, clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system has been successfully used recently to engineer resistance to DNA geminiviruses (family, Geminiviridae) by targeting different viral genome sequences in infected Nicotiana benthamiana or Arabidopsis plants. The DNA viruses targeted include tomato yellow leaf curl virus and merremia mosaic virus (begomovirus); beet curly top virus and beet severe curly top virus (curtovirus); and bean yellow dwarf virus (mastrevirus). The technique has also been used against the RNA viruses zucchini yellow mosaic virus, papaya ringspot virus and turnip mosaic virus (potyvirus) and cucumber vein yellowing virus (ipomovirus, family, Potyviridae) by targeting the translation initiation genes eIF4E in cucumber or Arabidopsis plants. From these recent advances of major importance, it is expected that NGS and CRISPR-Cas technologies will play a significant role in the very near future in advancing the field of plant virology and connecting it with other related fields of biology.

Whole Genome Sequencing of Enterovirus species C Isolates by High-Throughput Sequencing: Development of Generic Primers

Enteroviruses are among the most common viruses infecting humans and can cause diverse clinical syndromes ranging from minor febrile illness to severe and potentially fatal diseases. Enterovirus species C (EV-C) consists of more than 20 types, among which the three serotypes of polioviruses, the etiological agents of poliomyelitis, are included. Biodiversity and evolution of EV-C genomes are shaped by frequent recombination events. Therefore, identification and characterization of circulating EV-C strains require the sequencing of different genomic regions. A simple method was developed to quickly sequence the entire genome of EV-C isolates. Four overlapping fragments were produced separately by RT-PCR performed with generic primers. The four amplicons were then pooled and purified prior to being sequenced by a high-throughput technique. The method was assessed on a panel of EV-Cs belonging to a wide-range of types. It can be used to determine full-length genome sequences through de novo assembly of thousands of reads. It was also able to discriminate reads from closely related viruses in mixtures. By decreasing the workload compared to classical Sanger-based techniques, this method will serve as a precious tool for sequencing large panels of EV-Cs isolated in cell cultures during environmental surveillance or from patients, including vaccine-derived polioviruses.

Detection and quantitative estimation of spurious double stranded DNA formation during reverse transcription in bacteria using tagRNA-seq

Standard RNA-seq has a well know tendency to generate "ghost" antisense reads due to formation of spurious second strand cDNA in the sequencing process. We recently reported on a novel variant of RNA-seq coined "tagRNA-seq" introduced for the purpose of distinguishing primary from processed transcripts in bacteria. Incidentally, the additional information provided by the tags is also very suitable for detection of true anti-sense RNA transcripts and quantification of spurious antisense signals in a sample. We briefly explain how to perform such a detection and illustrate on previously published datasets.

A Novel Strategy for Exploitation of Host RNase E Activity by a Marine Cyanophage

Previous studies have shown that infection of Prochlorococcus MED4 by the cyanophage P-SSP7 leads to increased transcript levels of host endoribonuclease (RNase) E. However, it has remained enigmatic whether this is part of a host defense mechanism to degrade phage messenger RNA (mRNA) or whether this single-strand RNA-specific RNase is utilized by the phage. Here we describe a hitherto unknown means through which this cyanophage increases expression of RNase E during phage infection and concomitantly protects its own RNA from degradation. We identified two functionally different RNase E mRNA variants, one of which is significantly induced during phage infection. This transcript lacks the 5' UTR, is considerably more stable than the other transcript, and is likely responsible for increased RNase E protein levels during infection. Furthermore, selective enrichment and in vivo analysis of double-stranded RNA (dsRNA) during infection revealed that phage antisense RNAs (asRNAs) sequester complementary mRNAs to form dsRNAs, such that the phage protein-coding transcriptome is nearly completely covered by asRNAs. In contrast, the host protein-coding transcriptome is only partially covered by asRNAs. These data suggest that P-SSP7 orchestrates degradation of host RNA by increasing RNase E expression while masking its own transcriptome from RNase E degradation in dsRNA complexes. We propose that this combination of strategies contributes significantly to phage progeny production.