Single-molecule direct RNA sequencing without cDNA synthesis

Metatranscriptomic data mining together with microfluidic card uncovered the potential pathogens and seasonal RNA viral ecology in a drinking water source

AIMS

Despite metatranscriptomics becoming an emerging tool for pathogen surveillance, very little is known about the feasibility of this approach for understanding the fate of human-derived pathogens in drinking water sources.

METHODS AND RESULTS

We conducted multiplexed microfluidic cards and metatranscriptomic sequencing of the drinking water source in a border city of North Korea in four seasons. Microfluidic card detected norovirus, hepatitis B virus (HBV), enterovirus, and Vibrio cholerae in the water. Phylogenetic analyses showed that environmental-derived sequences from norovirus GII.17, genotype C of HBV, and coxsackievirus A6 (CA6) were genetically related to the local clinical isolates. Meanwhile, metatranscriptomic assembly suggested that several bacterial pathogens, including Acinetobacter johnsonii and V. cholerae might be prevalent in the studied region. Metatranscriptomic analysis recovered 349 species-level groups with substantial viral diversity without detection of norovirus, HBV, and CA6. Seasonally distinct virus communities were also found. Specifically, 126, 73, 126, and 457 types of viruses were identified in spring, summer, autumn, and winter, respectively. The viromes were dominated by the Pisuviricota phylum, including members from Marnaviridae, Dicistroviridae, Luteoviridae, Potyviridae, Picornaviridae, Astroviridae, and Picobirnaviridae families. Further phylogenetic analyses of RNA (Ribonucleic Acid)-dependent RNA polymerase (RdRp) sequences showed a diverse set of picorna-like viruses associated with shellfish, of which several novel picorna-like viruses were also identified. Additionally, potential animal pathogens, including infectious bronchitis virus, Bat dicibavirus, Bat nodavirus, Bat picornavirus 2, infectious bursal disease virus, and Macrobrachium rosenbergii nodavirus were also identified.

CONCLUSIONS

Our data illustrate the divergence between microfluidic cards and metatranscriptomics, highlighting that the combination of both methods facilitates the source tracking of human viruses in challenging settings without sufficient clinical surveillance.

How do emerging long-read sequencing technologies function in transforming the plant pathology research landscape?

Long-read sequencing technologies are revolutionizing the sequencing and analysis of plant and pathogen genomes and transcriptomes, as well as contributing to emerging areas of interest in plant-pathogen interactions, disease management techniques, and the introduction of new plant varieties or cultivars. Long-read sequencing (LRS) technologies are progressively being implemented to study plants and pathogens of agricultural importance, which have substantial economic effects. The variability and complexity of the genome and transcriptome affect plant growth, development and pathogen responses. Overcoming the limitations of second-generation sequencing, LRS technology has significantly increased the length of a single contiguous read from a few hundred to millions of base pairs. Because of the longer read lengths, new analysis methods and tools have been developed for plant and pathogen genomics and transcriptomics. LRS technologies enable faster, more efficient, and high-throughput ultralong reads, allowing direct sequencing of genomes that would be impossible or difficult to investigate using short-read sequencing approaches. These benefits include genome assembly in repetitive areas, creating more comprehensive and exact genome determinations, assembling full-length transcripts, and detecting DNA and RNA alterations. Furthermore, these technologies allow for the identification of transcriptome diversity, significant structural variation analysis, and direct epigenetic mark detection in plant and pathogen genomic regions. LRS in plant pathology is found efficient for identifying and characterization of effectors in plants as well as known and unknown plant pathogens. In this review, we investigate how these technologies are transforming the landscape of determination and characterization of plant and pathogen genomes and transcriptomes efficiently and accurately. Moreover, we highlight potential areas of interest offered by LRS technologies for future study into plant-pathogen interactions, disease control strategies, and the development of new plant varieties or cultivars.

Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision

RNA-seq, including single cell RNA-seq (scRNA-seq), is plagued by insufficient sensitivity and lack of precision. As a result, the full potential of (sc)RNA-seq is limited. Major factors in this respect are the presence of global bias in most datasets, which affects detection and quantitation of RNA in a length-dependent fashion. In particular, scRNA-seq is affected by technical noise and a high rate of dropouts, where the vast majority of original transcripts is not converted into sequencing reads. We discuss these biases origins and implications, bioinformatics approaches to correct for them, and how biases can be exploited to infer characteristics of the sample preparation process, which in turn can be used to improve library preparation.

Transcriptional control and transcriptomic analysis of lipid metabolism in skin barrier formation and atopic dermatitis (AD)

Introduction: Atopic dermatitis (AD) is a multifactorial ailment associated with barrier breach and intense systemic inflammation. Several studies over the years have shown the complex interplay of a large number of factors in governing the progression and outcome of AD. In addition to the diverse types of AD resulting due to variation in the intrinsic mechanisms giving rise to AD such as single nucleotide polymorphisms (SNPs), epigenetic alterations or transcriptional changes, extrinsic factors such as age, ancestry, ethnicity, immunological background of the subject, the interactions of the subject with environmental stimuli and existing microbiome in the periphery surrounding the subject account for further heterogeneity in the clinical manifestations of the disease. Areas covered: Here we have selectively discussed transcriptional regulation of genes associated with skin lipid metabolism in the context of AD. Transcriptional control and transcriptomic changes are just one face of this multifaceted disease known to affect humans and a detailed study concerning those will enable us to develop targeted therapies to deal with the disease. Expert opinion: Large-scale integration of different omics approaches (genomics, epigenomics, transcriptomics, lipidomics, proteomics, metabolomics, effect of exposome) will help identify the potential candidate gene(s) associated with the development of various endotypes of AD.

Biomarkers of Infection: Are They Useful in the ICU?

Biomarkers are increasingly used in patients with serious infections in the critical care setting to complement clinical judgment and interpretation of other diagnostic and prognostic tests. The main purposes of such blood markers are (1) to improve infection diagnosis (i.e., differentiation between bacterial vs. viral vs. fungal vs. noninfectious), (2) to help in the early risk stratification and thus provide prognostic information regarding the risk for mortality and other adverse outcomes, and (3) to optimize antibiotic tailoring to individual needs of patients ("antibiotic stewardship").Especially in critically ill patients, in whom sepsis is a major cause of morbidity and mortality, rapid diagnosis is desirable to start timely and specific treatment.Besides some biomarkers, such as procalcitonin, which is well established and has shown positive effects in regard to utilization of antimicrobials and clinical outcomes, there is a growing number of novel markers from different pathophysiological pathways, where the final proof of an added value to clinical judgment and ultimately clinical benefit to patients is still lacking.Without a doubt, the addition of blood biomarkers to clinical medicine has had a strong impact on the way we care for patients today. Recent trials show that as an adjunct to other clinical and laboratory parameters these markers provide important information about risks for bacterial infection and resolution of infection. Moreover, biomarkers can help to optimize management of patients with serious illness in the intensive care unit, thereby offering more individualized treatment courses with overall improvements in clinical outcomes.

Reading canonical and modified nucleobases in 16S ribosomal RNA using nanopore native RNA sequencing

The ribosome small subunit is expressed in all living cells. It performs numerous essential functions during translation, including formation of the initiation complex and proofreading of base-pairs between mRNA codons and tRNA anticodons. The core constituent of the small ribosomal subunit is a ~1.5 kb RNA strand in prokaryotes (16S rRNA) and a homologous ~1.8 kb RNA strand in eukaryotes (18S rRNA). Traditional sequencing-by-synthesis (SBS) of rRNA genes or rRNA cDNA copies has achieved wide use as a ‘molecular chronometer’ for phylogenetic studies, and as a tool for identifying infectious organisms in the clinic. However, epigenetic modifications on rRNA are erased by SBS methods. Here we describe direct MinION nanopore sequencing of individual, full-length 16S rRNA absent reverse transcription or amplification. As little as 5 picograms (~10 attomole) of purified E. coli 16S rRNA was detected in 4.5 micrograms of total human RNA. Nanopore ionic current traces that deviated from canonical patterns revealed conserved E. coli 16S rRNA 7-methylguanosine and pseudouridine modifications, and a 7-methylguanosine modification that confers aminoglycoside resistance to some pathological E. coli strains.

Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level

Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS), and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple ‘omics’ in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial ‘dark matter.’ In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented.

Detecting PKD1 variants in polycystic kidney disease patients by single-molecule long-read sequencing

A genetic diagnosis of autosomal-dominant polycystic kidney disease (ADPKD) is challenging due to allelic heterogeneity, high GC content, and homology of the PKD1 gene with six pseudogenes. Short-read next-generation sequencing approaches, such as whole-genome sequencing and whole-exome sequencing, often fail at reliably characterizing complex regions such as PKD1. However, long-read single-molecule sequencing has been shown to be an alternative strategy that could overcome PKD1 complexities and discriminate between homologous regions of PKD1 and its pseudogenes. In this study, we present the increased power of resolution for complex regions using long-read sequencing to characterize a cohort of 19 patients with ADPKD. Our approach provided high sensitivity in identifying PKD1 pathogenic variants, diagnosing 94.7% of the patients. We show that reliable screening of ADPKD patients in a single test without interference of PKD1 homologous sequences, commonly introduced by residual amplification of PKD1 pseudogenes, by direct long-read sequencing is now possible. This strategy can be implemented in diagnostics and is highly suitable to sequence and resolve complex genomic regions that are of clinical relevance.

Modeling Enzyme Processivity Reveals that RNA-Seq Libraries Are Biased in Characteristic and Correctable Ways

Experimental procedures for preparing RNA-seq and single-cell (sc) RNA-seq libraries are based on assumptions regarding their underlying enzymatic reactions. Here, we show that the fairness of these assumptions varies within libraries: coverage by sequencing reads along and between transcripts exhibits characteristic, protocol-dependent biases. To understand the mechanistic basis of this bias, we present an integrated modeling framework that infers the relationship between enzyme reactions during library preparation and the characteristic coverage patterns observed for different protocols. Analysis of new and existing (sc)RNA-seq data from six different library preparation protocols reveals that polymerase processivity is the mechanistic origin of coverage biases. We apply our framework to demonstrate that lowering incubation temperature increases processivity, yield, and (sc)RNA-seq sensitivity in all protocols. We also provide correction factors based on our model for increasing accuracy of transcript quantification in existing samples prepared at standard temperatures. In total, our findings improve our ability to accurately reflect in vivo transcript abundances in (sc)RNA-seq libraries.

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Characterization of global RNA-seq biases specific to library preparation protocols

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Mathematical framework to reverse engineer enzyme reactions that cause bias

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Insights from reverse engineering allow optimization of RNA-seq protocols

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Lowered incubation temperatures during library preparation improve sensitivity

Cell type-specific gene expression profiling in brain tissue: comparison between TRAP, LCM and RNA-seq

The brain is an organ that consists of various cell types. As our knowledge of the structure and function of the brain progresses, cell type-specific research is gaining importance. Together with advances in sequencing technology and bioinformatics, cell type-specific transcriptome studies are providing important insights into brain cell function. In this review, we discuss 3 different cell type-specific transcriptome analyses i.e., Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP)/RiboTag, and single cell RNA-Seq, that are widely used in the field of neuroscience.

Evolutionary Insights into RNA trans-Splicing in Vertebrates

Pre-RNA splicing is an essential step in generating mature mRNA. RNA trans-splicing combines two separate pre-mRNA molecules to form a chimeric non-co-linear RNA, which may exert a function distinct from its original molecules. Trans-spliced RNAs may encode novel proteins or serve as noncoding or regulatory RNAs. These novel RNAs not only increase the complexity of the proteome but also provide new regulatory mechanisms for gene expression. An increasing amount of evidence indicates that trans-splicing occurs frequently in both physiological and pathological processes. In addition, mRNA reprogramming based on trans-splicing has been successfully applied in RNA-based therapies for human genetic diseases. Nevertheless, clarifying the extent and evolution of trans-splicing in vertebrates and developing detection methods for trans-splicing remain challenging. In this review, we summarize previous research, highlight recent advances in trans-splicing, and discuss possible splicing mechanisms and functions from an evolutionary viewpoint.

CANEapp: a user-friendly application for automated next generation transcriptomic data analysis

BACKGROUND

Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers.

RESULTS

To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app .

CONCLUSIONS

We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups.

Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome

The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.

Single Nucleotide Polymorphism Identification in Polyploids: A Review, Example, and Recommendations

Understanding the relationship between genotype and phenotype is a major biological question and being able to predict phenotypes based on molecular genotypes is integral to molecular breeding. Whole-genome duplications have shaped the history of all flowering plants and present challenges to elucidating the relationship between genotype and phenotype, especially in neopolyploid species. Although single nucleotide polymorphisms (SNPs) have become popular tools for genetic mapping, discovery and application of SNPs in polyploids has been difficult. Here, we summarize common experimental approaches to SNP calling, highlighting recent polyploid successes. To examine the impact of software choice on these analyses, we called SNPs among five peanut genotypes using different alignment programs (BWA-mem and Bowtie 2) and variant callers (SAMtools, GATK, and Freebayes). Alignments produced by Bowtie 2 and BWA-mem and analyzed in SAMtools shared 24.5% concordant SNPs, and SAMtools, GATK, and Freebayes shared 1.4% concordant SNPs. A subsequent analysis of simulated Brassica napus chromosome 1A and 1C genotypes demonstrated that, of the three software programs, SAMtools performed with the highest sensitivity and specificity on Bowtie 2 alignments. These results, however, are likely to vary among species, and we therefore propose a series of best practices for SNP calling in polyploids.

Hypothesis: Artifacts, Including Spurious Chimeric RNAs with a Short Homologous Sequence, Caused by Consecutive Reverse Transcriptions and Endogenous Random Primers

Recent RNA-sequencing technology and associated bioinformatics have led to identification of tens of thousands of putative human chimeric RNAs, i.e. RNAs containing sequences from two different genes, most of which are derived from neighboring genes on the same chromosome. In this essay, we redefine "two neighboring genes" as those producing individual transcripts, and point out two known mechanisms for chimeric RNA formation, i.e. transcription from a fusion gene or trans-splicing of two RNAs. By our definition, most putative RNA chimeras derived from canonically-defined neighboring genes may either be technical artifacts or be cis-splicing products of 5'- or 3'-extended RNA of either partner that is redefined herein as an unannotated gene, whereas trans-splicing events are rare in human cells. Therefore, most authentic chimeric RNAs result from fusion genes, about 1,000 of which have been identified hitherto. We propose a hypothesis of "consecutive reverse transcriptions (RTs)", i.e. another RT reaction following the previous one, for how most spurious chimeric RNAs, especially those containing a short homologous sequence, may be generated during RT, especially in RNA-sequencing wherein RNAs are fragmented. We also point out that RNA samples contain numerous RNA and DNA shreds that can serve as endogenous random primers for RT and ensuing polymerase chain reactions (PCR), creating artifacts in RT-PCR.

We can't all be supermodels: the value of comparative transcriptomics to the study of non-model insects

Insects are the most diverse group of organisms on the planet. Variation in gene expression lies at the heart of this biodiversity and recent advances in sequencing technology have spawned a revolution in researchers' ability to survey tissue-specific transcriptional complexity across a wide range of insect taxa. Increasingly, studies are using a comparative approach (across species, sexes and life stages) that examines the transcriptional basis of phenotypic diversity within an evolutionary context. In the present review, we summarize much of this research, focusing in particular on three critical aspects of insect biology: morphological development and plasticity; physiological response to the environment; and sexual dimorphism. A common feature that is emerging from these investigations concerns the dynamic nature of transcriptome evolution as indicated by rapid changes in the overall pattern of gene expression, the differential expression of numerous genes with unknown function, and the incorporation of novel, lineage-specific genes into the transcriptional profile.

Improved annotation of 3' untranslated regions and complex loci by combination of strand-specific direct RNA sequencing, RNA-Seq and ESTs

The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3′ untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3′ polyadenylation sites to within +/− 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3′ UTR re-annotation (including extension of one 3′ UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data.

Quantitative polyadenylation site mapping with single-molecule direct RNA sequencing

The known regulatory role of 3' untranslated regions (3'UTRs) and poly(A) tails in RNA localization, stability, and translation, and polyadenylation regulation defects leading to human diseases such as oculopharyngeal muscular dystrophy, thalassemias, thrombophilia, and IPEX syndrome underline the need to fully characterize genome-wide polyadenylation states and mechanisms across normal physiological and disease states. This chapter outlines the quantitative polyadenylation site mapping and analysis strategies developed with the single-molecule direct RNA sequencing technology.

RNA-Seq technology and its application in fish transcriptomics

High-throughput sequencing technologies, also known as next-generation sequencing (NGS) technologies, have revolutionized the way that genomic research is advancing. In addition to the static genome, these state-of-art technologies have been recently exploited to analyze the dynamic transcriptome, and the resulting technology is termed RNA sequencing (RNA-seq). RNA-seq is free from many limitations of other transcriptomic approaches, such as microarray and tag-based sequencing method. Although RNA-seq has only been available for a short time, studies using this method have completely changed our perspective of the breadth and depth of eukaryotic transcriptomes. In terms of the transcriptomics of teleost fishes, both model and non-model species have benefited from the RNA-seq approach and have undergone tremendous advances in the past several years. RNA-seq has helped not only in mapping and annotating fish transcriptome but also in our understanding of many biological processes in fish, such as development, adaptive evolution, host immune response, and stress response. In this review, we first provide an overview of each step of RNA-seq from library construction to the bioinformatic analysis of the data. We then summarize and discuss the recent biological insights obtained from the RNA-seq studies in a variety of fish species.

Applications and challenges of next-generation sequencing in Brassica species

Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.

Methodological limitations in determining astrocytic gene expression

Traditionally, astrocytic mRNA and protein expression are studied by in situ hybridization (ISH) and immunohistochemically. This led to the concept that astrocytes lack aralar, a component of the malate-aspartate-shuttle. At least similar aralar mRNA and protein expression in astrocytes and neurons isolated by fluorescence-assisted cell sorting (FACS) reversed this opinion. Demonstration of expression of other astrocytic genes may also be erroneous. Literature data based on morphological methods were therefore compared with mRNA expression in cells obtained by recently developed methods for determination of cell-specific gene expression. All Na,K-ATPase-α subunits were demonstrated by immunohistochemistry (IHC), but there are problems with the cotransporter NKCC1. Glutamate and GABA transporter gene expression was well determined immunohistochemically. The same applies to expression of many genes of glucose metabolism, whereas a single study based on findings in bacterial artificial chromosome (BAC) transgenic animals showed very low astrocytic expression of hexokinase. Gene expression of the equilibrative nucleoside transporters ENT1 and ENT2 was recognized by ISH, but ENT3 was not. The same applies to the concentrative transporters CNT2 and CNT3. All were clearly expressed in FACS-isolated cells, followed by biochemical analysis. ENT3 was enriched in astrocytes. Expression of many nucleoside transporter genes were shown by microarray analysis, whereas other important genes were not. Results in cultured astrocytes resembled those obtained by FACS. These findings call for reappraisal of cellular nucleoside transporter expression. FACS cell yield is small. Further development of cell separation methods to render methods more easily available and less animal and cost consuming and parallel studies of astrocytic mRNA and protein expression by ISH/IHC and other methods are necessary, but new methods also need to be thoroughly checked.

Deciphering the single-cell omic: innovative application for translational medicine

Traditional technologies to investigate system biology are limited by the detection of parameters resulting from the averages of large populations of cells, missing cells produced in small numbers, and attempting to uniform the heterogeneity. The advent of proteomics and genomics at a single-cell level has set the basis for an outstanding improvement in analytical technology and data acquisition. It has been well demonstrated that cellular heterogeneity is closely related to numerous stochastic transcriptional events leading to variations in patterns of expression among single genetically identical cells. The new-generation technology of single-cell analysis is able to better characterize a cell's population, identifying and differentiating outlier cells, in order to provide both a single-cell experiment and a corresponding bulk measurement, through the identification, quantification and characterization of all system biology aspects (genomics, transcriptomics, proteomics, metabolomics, degradomics and fluxomics). The movement of omics into single-cell analysis represents a significant and outstanding shift.

Strand-specific libraries for high throughput RNA sequencing (RNA-Seq) prepared without poly(A) selection

BACKGROUND

High throughput DNA sequencing technology has enabled quantification of all the RNAs in a cell or tissue, a method widely known as RNA sequencing (RNA-Seq). However, non-coding RNAs such as rRNA are highly abundant and can consume >70% of sequencing reads. A common approach is to extract only polyadenylated mRNA; however, such approaches are blind to RNAs with short or no poly(A) tails, leading to an incomplete view of the transcriptome. Another challenge of preparing RNA-Seq libraries is to preserve the strand information of the RNAs.

DESIGN

Here, we describe a procedure for preparing RNA-Seq libraries from 1 to 4 μg total RNA without poly(A) selection. Our method combines the deoxyuridine triphosphate (dUTP)/uracil-DNA glycosylase (UDG) strategy to achieve strand specificity with AMPure XP magnetic beads to perform size selection. Together, these steps eliminate gel purification, allowing a library to be made in less than two days. We barcode each library during the final PCR amplification step, allowing several samples to be sequenced in a single lane without sacrificing read length. Libraries prepared using this protocol are compatible with Illumina GAII, GAIIx and HiSeq 2000 platforms.

DISCUSSION

The RNA-Seq protocol described here yields strand-specific transcriptome libraries without poly(A) selection, which provide approximately 90% mappable sequences. Typically, more than 85% of mapped reads correspond to protein-coding genes and only 6% derive from non-coding RNAs. The protocol has been used to measure RNA transcript identity and abundance in tissues from flies, mice, rats, chickens, and frogs, demonstrating its general applicability.

Promising new assays and technologies for the diagnosis and management of infectious diseases

In the first decade of the 21st century, we have seen the completion of the human genome project and marked progress in the human microbiome project. The vast amount of data generated from these efforts combined with advances in molecular and biomedical technologies have led to the development of a multitude of assays and technologies that may be useful in the diagnosis and management of infectious diseases. Here, we identify several new assays and technologies that have recently come into clinical use or have potential for clinical use in the near future. The scope of this review is broad and includes topics such as the serum marker procalcitonin, gene expression profiling, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and nucleic acid aptamers. Principles that underlie each assay or technology, their clinical applications, and potential strengths and limitations are addressed.

Genomic sequencing in cancer

Genomic sequencing has provided critical insights into the etiology of both simple and complex diseases. The enormous reductions in cost for whole genome sequencing have allowed this technology to gain increasing use. Whole genome analysis has impacted research of complex diseases including cancer by allowing the systematic analysis of entire genomes in a single experiment, thereby facilitating the discovery of somatic and germline mutations, and identification of the insertions, deletions, and structural rearrangements, including translocations and inversions, in novel disease genes. Whole-genome sequencing can be used to provide the most comprehensive characterization of the cancer genome, the complexity of which we are only beginning to understand. Hence in this review, we focus on whole-genome sequencing in cancer.

Methods, Challenges and Potentials of Single Cell RNA-seq

RNA-sequencing (RNA-seq) has become the tool of choice for transcriptomics. Several recent studies demonstrate its successful adaption to single cell analysis. This allows new biological insights into cell differentiation, cell-to-cell variation and gene regulation, and how these aspects depend on each other. Here, I review the current single cell RNA-seq (scRNA-seq) efforts and discuss experimental protocols, challenges and potentials.

Application of metatranscriptomics to soil environments

The activities of soil microbial communities are of critical importance to terrestrial ecosystem functioning. The mechanisms that determine the interactions between soil microorganisms, their environment and neighbouring organisms, however, are poorly understood. Due to advances in sequencing technologies, an increasing number of metagenomics studies are being conducted on samples from diverse environments including soils. This information has not only increased our awareness of the functional potential of soil microbial communities, but also constitutes powerful reference material for soil metatranscriptomics studies. Metatranscriptomics provides a snapshot of transcriptional profiles that correspond to discrete populations within a microbial community at the time of sampling. This information can indicate the potential activities of complex microbial communities and the mechanisms that regulate them. Here we summarise the technical challenges for metatranscriptomics applied to soil environments and discuss approaches for gaining biologically meaningful insight into these datasets.

Going beyond five bases in DNA sequencing

DNA sequencing has provided a wealth of information about biological systems, but thus far has focused on the four canonical bases, and 5-methylcytosine through comparison of the genomic DNA sequence to a transformed four-base sequence obtained after treatment with bisulfite. However, numerous other chemical modifications to the nucleotides are known to control fundamental life functions, influence virulence of pathogens, and are associated with many diseases. These modifications cannot be accessed with traditional sequencing methods. In this opinion, we highlight several emerging single-molecule sequencing techniques that have the potential to directly detect many types of DNA modifications as an integral part of the sequencing protocol.