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

Amplicon-based semiconductor sequencing of human exomes: performance evaluation and optimization strategies

The Ion Proton platform allows to perform whole exome sequencing (WES) at low cost, providing rapid turnaround time and great flexibility. Products for WES on Ion Proton system include the AmpliSeq Exome kit and the recently introduced HiQ sequencing chemistry. Here, we used gold standard variants from GIAB consortium to assess the performances in variants identification, characterize the erroneous calls and develop a filtering strategy to reduce false positives. The AmpliSeq Exome kit captures a large fraction of bases (>94 %) in human CDS, ClinVar genes and ACMG genes, but with 2,041 (7 %), 449 (13 %) and 11 (19 %) genes not fully represented, respectively. Overall, 515 protein coding genes contain hard-to-sequence regions, including 90 genes from ClinVar. Performance in variants detection was maximum at mean coverage >120×, while at 90× and 70× we measured a loss of variants of 3.2 and 4.5 %, respectively. WES using HiQ chemistry showed ~71/97.5 % sensitivity, ~37/2 % FDR and ~0.66/0.98 F1 score for indels and SNPs, respectively. The proposed low, medium or high-stringency filters reduced the amount of false positives by 10.2, 21.2 and 40.4 % for indels and 21.2, 41.9 and 68.2 % for SNP, respectively. Amplicon-based WES on Ion Proton platform using HiQ chemistry emerged as a competitive approach, with improved accuracy in variants identification. False-positive variants remain an issue for the Ion Torrent technology, but our filtering strategy can be applied to reduce erroneous variants.

Multicenter quality assessment of 16S ribosomal DNA-sequencing for microbiome analyses reveals high inter-center variability

The composition of human as well as animal microbiota has increasingly gained in interest since metabolites and structural components of endogenous microorganisms fundamentally influence all aspects of host physiology. Since many of the bacteria are still unculturable, molecular techniques such as high-throughput sequencing have dramatically increased our knowledge of microbial communities. The majority of microbiome studies published thus far are based on bacterial 16S ribosomal RNA (rRNA) gene sequencing, so that they can, at least in principle, be compared to determine the role of the microbiome composition for host metabolism and physiology, developmental processes, as well as different diseases. However, differences in DNA preparation and purification, 16S rDNA PCR amplification, sequencing procedures and platforms, as well as bioinformatic analysis and quality control measures may strongly affect the microbiome composition results obtained in different laboratories. To systematically evaluate the comparability of results and identify the most influential methodological factors affecting these differences, identical human stool sample replicates spiked with quantified marker bacteria, and their subsequent DNA sequences were analyzed by nine different centers in an external quality assessment (EQA). While high intra-center reproducibility was observed in repetitive tests, significant inter-center differences of reported microbiota composition were obtained. All steps of the complex analysis workflow significantly influenced microbiome profiles, but the magnitude of variation caused by PCR primers for 16S rDNA amplification was clearly the largest. In order to advance microbiome research to a more standardized and routine medical diagnostic procedure, it is essential to establish uniform standard operating procedures throughout laboratories and to initiate regular proficiency testing.

Next-generation sequencing (NGS) in the microbiological world: How to make the most of your money

The Sanger sequencing method produces relatively long DNA sequences of unmatched quality and has been considered for long time as the gold standard for sequencing DNA. Many improvements of the Sanger method that culminated with fluorescent dyes coupled with automated capillary electrophoresis enabled the sequencing of the first genomes. Nevertheless, using this technology to sequence whole genomes was costly, laborious and time consuming even for genomes that are relatively small in size. A major technological advance was the introduction of next-generation sequencing (NGS) pioneered by 454 Life Sciences in the early part of the 21th century. NGS allowed scientists to sequence thousands to millions of DNA molecules in a single machine run. Since then, new NGS technologies have emerged and existing NGS platforms have been improved, enabling the production of genome sequences at an unprecedented rate as well as broadening the spectrum of NGS applications. The current affordability of generating genomic information, especially with microbial samples, has resulted in a false sense of simplicity that belies the fact that many researchers still consider these technologies a black box. In this review, our objective is to identify and discuss four steps that we consider crucial to the success of any NGS-related project. These steps are: (1) the definition of the research objectives beyond sequencing and appropriate experimental planning, (2) library preparation, (3) sequencing and (4) data analysis. The goal of this review is to give an overview of the process, from sample to analysis, and discuss how to optimize your resources to achieve the most from your NGS-based research. Regardless of the evolution and improvement of the sequencing technologies, these four steps will remain relevant.

Circulating miRNA signatures of early pregnancy in cattle

Background

Low fertility remains a leading cause of poor productivity in dairy cattle. In this context, there is significant interest in developing novel tools for accurate early diagnosis of pregnancy. MicroRNAs (miRNAs) are short RNA molecules which are critically involved in regulating gene expression during both health and disease. MiRNAs have been shown to regulate ovarian function, uterine receptivity, embryonic development and placental function. Circulating miRNAs can provide useful biomarkers of tissue function and disease; importantly, differential miRNA profiles have been linked to pregnancy and preeclampsia in humans. This study sought to establish the potential of circulating miRNAs as biomarkers of early pregnancy in cattle.

Results

We applied Illumina small-RNA sequencing to profile miRNAs in plasma samples collected from eight non-pregnant heifers on Days 0, 8 and 16 of the oestrous cycle and 11 heifers on Days 16 and 24 of pregnancy. We sequenced a total of 46 samples and generated 9.2 million miRNA reads per sample. There were no differences in miRNA read abundance between any of the pregnant and non-pregnant time-points (FDR > 0.1). As a complementary approach, we analysed sample pools (3–4 samples/pool) corresponding to Days 0, 8 and 16 of the oestrous cycle and Day 24 of pregnancy (n = 3 pools/group) using Qiagen PCR arrays. A total of 16 miRNAs were differentially expressed (FDR < 0.1) in plasma between pregnant and non-pregnant animals. RT-qPCR validation using the same plasma samples confirmed that miR-26a was differentially upregulated on Day 16 pregnant relative to non-pregnant heifers (1.7-fold; P = 0.043), whereas miR-1249 tended to be upregulated in Day 16 pregnant heifers (1.6-fold; P = 0.081). Further validation in an independent group of heifers confirmed an increase in plasma miR-26a levels during early pregnancy, which was significant only on Day 24 (2.0-fold; P = 0.027).

Conclusions

Through genome-wide analyses we have successfully profiled plasma miRNA populations associated with early pregnancy in cattle. We have identified miR-26a as a potential circulating biomarker of early pregnancy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2529-1) contains supplementary material, which is available to authorized users.

Assessment of the latest NGS enrichment capture methods in clinical context

Enrichment capture methods for NGS are widely used, however, they evolve rapidly and it is necessary to periodically measure their strengths and weaknesses before transfer to diagnostic services. We assessed two recently released custom DNA solution-capture enrichment methods for NGS, namely Illumina NRCCE and Agilent SureSelect(QXT), against a reference method NimbleGen SeqCap EZ Choice on a similar gene panel, sharing 678 kb and 110 genes. Two Illumina MiSeq runs of 12 samples each have been performed, for each of the three methods, using the same 24 patients (affected with sensorineural disorders). Technical outcomes have been computed and compared, including depth and evenness of coverage, enrichment in targeted regions, performance in GC-rich regions and ability to generate consistent variant datasets. While we show that the three methods resulted in suitable datasets for standard DNA variant discovery, we describe significant differences between the results for the above parameters. NimbleGen offered the best depth of coverage and evenness, while NRCCE showed the highest on target levels but high duplicate rates. SureSelect(QXT) showed an overall quality close to that of NimbleGen. The new methods exhibit reduced preparation time but behave differently. These findings will guide laboratories in their choice of library enrichment approach.

A survey of best practices for RNA-seq data analysis

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling

Background

In the last 5 years, the rapid pace of innovations and improvements in sequencing technologies has completely changed the landscape of metagenomic and metagenetic experiments. Therefore, it is critical to benchmark the various methodologies for interrogating the composition of microbial communities, so that we can assess their strengths and limitations. The most common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene and in the last 10 years the field has moved from sequencing a small number of amplicons and samples to more complex studies where thousands of samples and multiple different gene regions are interrogated.

Results

We assembled 2 synthetic communities with an even (EM) and uneven (UM) distribution of archaeal and bacterial strains and species, as metagenomic control material, to assess performance of different experimental strategies. The 2 synthetic communities were used in this study, to highlight the limitations and the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We describe an extensive survey based on synthetic communities using 3 experimental designs (fusion primers, universal tailed tag, ligated adaptors) across the 9 hypervariable 16S rDNA regions. We demonstrate that library preparation methodology can affect data interpretation due to different error and chimera rates generated during the procedure. The observed community composition was always biased, to a degree that depended on the platform, sequenced region and primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing is still quantitative, in that relative changes in abundance of taxa between samples can be recovered, despite these biases.

Conclusion

We have assessed a range of experimental conditions across several next generation sequencing platforms using the most up-to-date configurations. We propose that the choice of sequencing platform and experimental design needs to be taken into consideration in the early stage of a project by running a small trial consisting of several hypervariable regions to quantify the discriminatory power of each region. We also suggest that the use of a synthetic community as a positive control would be beneficial to identify the potential biases and procedural drawbacks that may lead to data misinterpretation. The results of this study will serve as a guideline for making decisions on which experimental condition and sequencing platform to consider to achieve the best microbial profiling.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2194-9) contains supplementary material, which is available to authorized users.

Real-world data in the molecular era-finding the reality in the real world

Real-world data (RWD) promises to provide a pivotal element to the understanding of personalized medicine. However, without true representation (or the reality) of the patient-disease biosystem and its molecular contributors, RWD may hamper rather than help this advancement. In this review article, we discuss RWD vs. clinical reality and the disconnects that exist currently (emphasizing molecular medicine), and methods of closing the gaps between RWD and reality.

Exome sequencing explained: a practical guide to its clinical application

Next-generation sequencing has catapulted healthcare into a revolutionary genomics era. One such technology, whole-exome sequencing, which targets the protein-coding regions of the genome, has proven success in identifying new causal mutations for diseases of previously unknown etiology. With a successful diagnostic rate approaching 25% for rare disease in recent studies, its clinical utility is becoming increasingly popular. However, the interpretation of whole-exome sequencing data requires expertise in genomic informatics and clinical medicine to ensure the accurate and safe reporting of findings back to the bedside. This is challenged by vast amounts of sequencing data harbouring approximately 25 000 variants per sequenced individual. Computational strategies and fastidious filtering frameworks are thus required to extricate candidate variants in a sea of common polymorphisms. Once prioritized, identified variants require intensive scrutiny at a biological level, and require judicious assessment alongside the clinical phenotype. In the final step, all evidence is collated and documented alongside pathogenicity guidelines to produce an exome report that returns to the clinic. This review provides a practical guide for clinicians and genomic informaticians on the clinical application of whole-exome sequencing. We address sequencing capture and methodology, quality control parameters at different stages of sequencing analysis and propose an exome data filtering strategy that includes primary filtering (for the removal of probable benign variants) and secondary filtering for the prioritization of remaining candidates.

Identification of microRNAs and microRNA targets in Xenopus gastrulae: The role of miR-26 in the regulation of Smad1

MicroRNAs (miRNAs) are known to play diverse roles in the regulation of vertebrate development. To investigate miRNA-target mRNA relationships in embryonic development, we have carried out small-RNA sequencing to identify miRNAs expressed in the early gastrula of Xenopus laevis. We identify a total of 180 miRNAs, and we have identified the locations of the miRNA precursor sequences in the X. laevis genome. Of these miRNAs, 141 represent miRs previously identified in Xenopus tropicalis. Alignment to human miRNAs led to the identification of 39 miRNAs that have not previously been described for Xenopus. We have also used a biochemical approach to isolate mRNAs that are associated with the RNA-Induced Silencing Complex (RISC) in early gastrulae and thus candidate targets of miRNA-dependent regulation. Interrogation of this RISC-associated mRNA pool by RT-PCR indicates that a number of genes essential for early patterning and specification may be under regulation by miRNAs. Smad1 transcripts are associated with the RISC; target prediction algorithms identify a single miRNA-binding site for miR-26, which is common to the 3'UTRs of Smad1a and Smad1b. Disruption of the interaction between miR-26 and the Smad1 3'UTR via a Target Protector Morpholino Oligonucleotide (TPMO) leads to a 2-fold increase in Smad1 protein accumulation, moderate increases in the expression of BMP4/Smad1 target genes, and a reduction in organizer gene expression, as well as a partially ventralized phenotype in approximately 25% of embryos. Overexpression of miR-26 resulted in moderately decreased expression of Smad1-dependent genes and an expansion of the region expressing the Organizer gene not1. Our findings indicate that interactions between miR-26 and the Smad1 3'UTR modulate Smad1 function in the establishment of axial patterning; they also establish a foundation for the functional analysis of miRNAs and their regulatory interactions during gastrulation.

Detection of RNA nucleoside modifications with the uridine-specific ribonuclease MC1 from Momordica charantia

A codon-optimized recombinant ribonuclease, MC1 is characterized for its uridine-specific cleavage ability to map nucleoside modifications in RNA. The published MC1 amino acid sequence, as noted in a previous study, was used as a template to construct a synthetic gene with a natural codon bias favoring expression in Escherichia coli. Following optimization of various expression conditions, the active recombinant ribonuclease was successfully purified as a C-terminal His-tag fusion protein from E. coli [Rosetta 2(DE3)] cells. The isolated protein was tested for its ribonuclease activity against oligoribonucleotides and commercially available E. coli tRNA(Tyr I). Analysis of MC1 digestion products by ion-pairing reverse phase liquid-chromatography coupled with mass spectrometry (IP-RP-LC-MS) revealed enzymatic cleavage of RNA at the 5'-termini of uridine and pseudouridine, but cleavage was absent if the uridine was chemically modified or preceded by a nucleoside with a bulky modification. Furthermore, the utility of this enzyme to generate complementary digestion products to other common endonucleases, such as RNase T1, which enables the unambiguous mapping of modified residues in RNA is demonstrated.

Mini but mighty: microRNAs in the pathobiology of periodontal disease

MicroRNAs (miRNAs) are a family of small, noncoding RNA molecules that negatively regulate protein expression either by inhibiting initiation of the translation of mRNA or by inducing the degradation of mRNA molecules. Accumulating evidence suggests that miRNA-mediated repression of protein expression is of paramount importance in a broad range of physiologic and pathologic conditions. In particular, miRNA-induced dysregulation of molecular processes involved in inflammatory pathways has been shown to contribute to the development of chronic inflammatory diseases. In this review, first of all we provide an overview of miRNA biogenesis, the main mechanisms of action and the miRNA profiling tools currently available. Then, we summarize the available evidence supporting a specific role for miRNAs in the pathobiology of periodontitis. Based on a review of available data on the differential expression of miRNAs in gingival tissues in states of periodontal health and disease, we address specific roles for miRNAs in molecular and cellular pathways causally linked to periodontitis. Our review points to several lines of evidence suggesting the involvement of miRNAs in periodontal tissue homeostasis and pathology. Although the intricate regulatory networks affected by miRNA function are still incompletely mapped, further utilization of systems biology tools is expected to enhance our understanding of the pathobiology of periodontitis.

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

High-Throughput Ligand Discovery Reveals a Sitewise Gradient of Diversity in Broadly Evolved Hydrophilic Fibronectin Domains

Discovering new binding function via a combinatorial library in small protein scaffolds requires balance between appropriate mutations to introduce favorable intermolecular interactions while maintaining intramolecular integrity. Sitewise constraints exist in a non-spatial gradient from diverse to conserved in evolved antibody repertoires; yet non-antibody scaffolds generally do not implement this strategy in combinatorial libraries. Despite the fact that biased amino acid distributions, typically elevated in tyrosine, serine, and glycine, have gained wider use in synthetic scaffolds, these distributions are still predominantly applied uniformly to diversified sites. While select sites in fibronectin domains and DARPins have shown benefit from sitewise designs, they have not been deeply evaluated. Inspired by this disparity between diversity distributions in natural libraries and synthetic scaffold libraries, we hypothesized that binders resulting from discovery and evolution would exhibit a non-spatial, sitewise gradient of amino acid diversity. To identify sitewise diversities consistent with efficient evolution in the context of a hydrophilic fibronectin domain, >10⁵ binders to six targets were evolved and sequenced. Evolutionarily favorable amino acid distributions at 25 sites reveal Shannon entropies (range: 0.3–3.9; median: 2.1; standard deviation: 1.1) supporting the diversity gradient hypothesis. Sitewise constraints in evolved sequences are consistent with complementarity, stability, and consensus biases. Implementation of sitewise constrained diversity enables direct selection of nanomolar affinity binders validating an efficient strategy to balance inter- and intra-molecular interaction demands at each site.

Using mixtures of biological samples as process controls for RNA-sequencing experiments

Background

Genome-scale “-omics” measurements are challenging to benchmark due to the enormous variety of unique biological molecules involved. Mixtures of previously-characterized samples can be used to benchmark repeatability and reproducibility using component proportions as truth for the measurement. We describe and evaluate experiments characterizing the performance of RNA-sequencing (RNA-Seq) measurements, and discuss cases where mixtures can serve as effective process controls.

Results

We apply a linear model to total RNA mixture samples in RNA-seq experiments. This model provides a context for performance benchmarking. The parameters of the model fit to experimental results can be evaluated to assess bias and variability of the measurement of a mixture. A linear model describes the behavior of mixture expression measures and provides a context for performance benchmarking. Residuals from fitting the model to experimental data can be used as a metric for evaluating the effect that an individual step in an experimental process has on the linear response function and precision of the underlying measurement while identifying signals affected by interference from other sources. Effective benchmarking requires well-defined mixtures, which for RNA-Seq requires knowledge of the post-enrichment ‘target RNA’ content of the individual total RNA components. We demonstrate and evaluate an experimental method suitable for use in genome-scale process control and lay out a method utilizing spike-in controls to determine enriched RNA content of total RNA in samples.

Conclusions

Genome-scale process controls can be derived from mixtures. These controls relate prior knowledge of individual components to a complex mixture, allowing assessment of measurement performance. The target RNA fraction accounts for differential selection of RNA out of variable total RNA samples. Spike-in controls can be utilized to measure this relationship between target RNA content and input total RNA. Our mixture analysis method also enables estimation of the proportions of an unknown mixture, even when component-specific markers are not previously known, whenever pure components are measured alongside the mixture.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1912-7) contains supplementary material, which is available to authorized users.

Development and utilization of a custom PCR array workflow: analysis of gene expression in mycoplasma genitalium and guinea pig (Cavia porcellus)

Transcriptome analysis is a powerful tool for evaluating molecular pathways central to maturation of specific biological processes and disease states. Recently, PCR-based arrays have supplemented microarray and RNA-seq methodologies for studying changes in gene expression levels. PCR arrays are a more cost efficient alternative, however commercially available assemblies are generally limited to only a few more widely researched species (e.g., rat, human, and mouse). Consequently, the investigation of emerging or under-studied species is hindered until such assays are created. To address this need, we present data documenting the success of a developed workflow with enhanced potential to create and validate novel RT-PCR arrays for underrepresented species with whole or partial genome annotation. Utilizing this enhanced workflow, we have achieved a success rate of 80 % for first-round designs for over 400 primer pairs. Of these, ~160 distinct targets were sequence confirmed. Proof of concept studies using two unique arrays, one targeting the pathogenic bacterium Mycoplasma genitalium and the other specific for the guinea pig (Cavia porcellus), allowed us to identify significant (P < 0.05) changes in mRNA expression validated by subsequent qPCR. This flexible and adaptable platform provides a valuable and cost-effective alternative for gene expression analysis.

Fecal microbiota analysis: an overview of sample collection methods and sequencing strategies

Despite huge interest, there are still no universally accepted standards to conduct clinical studies in the field of gut microbiota analysis. Stool material is frequently used as a proxy of gut microbiota, but many different protocols can be used for collection and DNA extraction. Whereas 16S rRNA encoding gene amplification and sequencing has been widely used to study the composition of bacterial populations, it is now being challenged by the random, shotgun approach that brings far more information, although at a higher cost. In this review we give an overview of existing methods and important points to consider when conducting gut microbiota studies, with the objective to provide recommendations to those who would like to conduct such research.

Transcriptional analysis of phloem-associated cells of potato

Background

Numerous signal molecules, including proteins and mRNAs, are transported through the architecture of plants via the vascular system. As the connection between leaves and other organs, the petiole and stem are especially important in their transport function, which is carried out by the phloem and xylem, especially by the sieve elements in the phloem system. The phloem is an important conduit for transporting photosynthate and signal molecules like metabolites, proteins, small RNAs, and full-length mRNAs. Phloem sap has been used as an unadulterated source to profile phloem proteins and RNAs, but unfortunately, pure phloem sap cannot be obtained in most plant species.

Results

Here we make use of laser capture microdissection (LCM) and RNA-seq for an in-depth transcriptional profile of phloem-associated cells of both petioles and stems of potato. To expedite our analysis, we have taken advantage of the potato genome that has recently been fully sequenced and annotated. Out of the 27 k transcripts assembled that we identified, approximately 15 k were present in phloem-associated cells of petiole and stem with greater than ten reads. Among these genes, roughly 10 k are affected by photoperiod. Several RNAs from this day length-regulated group are also abundant in phloem cells of petioles and encode for proteins involved in signaling or transcriptional control. Approximately 22 % of the transcripts in phloem cells contained at least one binding motif for Pumilio, Nova, or polypyrimidine tract-binding proteins in their downstream sequences. Highlighting the predominance of binding processes identified in the gene ontology analysis of active genes from phloem cells, 78 % of the 464 RNA-binding proteins present in the potato genome were detected in our phloem transcriptome.

Conclusions

As a reasonable alternative when phloem sap collection is not possible, LCM can be used to isolate RNA from specific cell types, and along with RNA-seq, provides practical access to expression profiles of phloem tissue. The combination of these techniques provides a useful approach to the study of phloem and a comprehensive picture of the mechanisms associated with long-distance signaling. The data presented here provide valuable insights into potentially novel phloem-mobile mRNAs and phloem-associated RNA-binding proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1844-2) contains supplementary material, which is available to authorized users.

Current State of Circulating MicroRNAs as Cancer Biomarkers

BACKGROUND

Numerous studies have demonstrated the existence of stable regulatory RNAs, microRNAs (miRNAs), in the circulation and have shown that the spectrum of these extracellular miRNAs is affected by various pathologic conditions including cancers.

CONTENT

Circulating miRNAs have been the focus of numerous cancer biomarker discovery efforts over the past few years; however, a considerable number of these studies have yielded inconsistent and irreproducible findings. Here, we have summarized and compared the results of studies covering 8 different cancer types to address key questions, including the possibility of using circulating miRNA to detect cancers and what factors may affect miRNA signatures. Although identifying circulating miRNA signatures to detect specific types of early stage cancers can be challenging, study results suggest that it may be possible to use miRNAs to detect cancers in general.

SUMMARY

Circulating miRNA is a rich source for potential disease biomarkers; however, factors, both intrinsic and extrinsic, that may affect measurement of circulating miRNA have not been fully characterized. Better understanding of intra- and intercellular miRNA trafficking and the fundamental biology of cancer cell–derived lipid vesicles may facilitate the development of circulating miRNA-based biomarkers for cancer detection and classification.

Meeting report: discussions and preliminary findings on extracellular RNA measurement methods from laboratories in the NIH Extracellular RNA Communication Consortium

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.

Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud

Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki.

Enzymological description of multitemplate PCR-Shrinking amplification bias by optimizing the polymerase-template ratio

Multitemplate polymerase chain reaction (PCR) is used for preparative and analytical applications in diagnostics and research. Classical PCR and qPCR are two basic setups with many possible experimental modifications. Classical PCR is a method of choice to obtain enough material for subsequent sophisticated applications such as construction of libraries for next-generation sequencing or high-throughput screening. Sequencing and Single Nucleotide Primer Extension (SNuPE) employ one-strand synthesis and represent a distinct variant of analytical DNA synthesis. In all these applications, maintaining the initial ratio of templates and avoiding underestimation of minority templates is desired. Here, we demonstrate that different templates can amplify independently at low template concentrations (typical in qPCR setups, in which the polymerase concentration is usually several orders of magnitude higher than the template concentration). However, rare templates can be diluted in an effort to keep DNA amplification in the exponential phase, or template concentration can be biased by differences in amplification efficiency. Moreover, amplification of templates present in low concentrations is more vulnerable to stochastic events that lead to proportional changes in the product ratio, as well as by incomplete amplification leading to chimera formation. These undesired effects can be compensated for by using highly processive polymerases with high and equal affinity to different primer-template complexes. Novel enhanced polymerases are desired. With increasing concentration of a primer-template of interest, the system becomes more deterministic. Nevertheless, marked deviation from independent exponential amplification occurs when the total template concentration starts to approach the polymerase concentration. The primer-template complexes compete for enzyme molecules, and the amount of products grows arithmetically-the system starts to obey Michaelis-Menten kinetics. Synthesis of rare products in a multitemplate mixture can run more easily under the detection limit in such conditions, although it would be unequivocally detectable in a single template assay. When fishing out rare template variants, the best processive polymerases should be used to decrease both amplification and detection limits. The possibility of stochastic events, should be taken into account to correctly interpret the obtained data.

Uncovering correlated variability in epigenomic datasets using the Karhunen-Loeve transform

BACKGROUND

Larger variation exists in epigenomes than in genomes, as a single genome shapes the identity of multiple cell types. With the advent of next-generation sequencing, one of the key problems in computational epigenomics is the poor understanding of correlations and quantitative differences between large scale data sets.

RESULTS

Here we bring to genomics a scenario of functional principal component analysis, a finite Karhunen-Loève transform, and explicitly decompose the variation in the coverage profiles of 27 chromatin mark ChIP-seq datasets at transcription start sites for H1, one of the most used human embryonic stem cell lines. Using this approach we identify positive correlations between H3K4me3 and H3K36me3, as well as between H3K9ac and H3K36me3, so far undetected by the most commonly used Pearson correlation between read enrichment coverages. We uncover highly negative correlations between H2A.Z, H3K4me3, and several histone acetylation marks, but these occur only between principal components of first and second order. We also demonstrate that levels of gene expression correlate significantly with scores of components of order higher than one, demonstrating that transcriptional regulation by histone marks escapes simple one-to-one relationships. This correlations were higher in significance and magnitude in protein coding genes than in non-coding RNAs.

CONCLUSIONS

In summary, we present a methodology to explore and uncover novel patterns of epigenomic variability and covariability in genomic data sets by using a functional eigenvalue decomposition of genomic data. R code is available at: http://github.com/pmb59/KLTepigenome.

Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis

Background

RNA-Seq provides remarkable power in the area of biomarkers discovery and disease characterization. Two crucial steps that affect RNA-Seq experiment results are Library Sample Preparation (LSP) and Bioinformatics Analysis (BA). This work describes an evaluation of the combined effect of LSP methods and BA tools in the detection of splice variants.

Results

Different LSPs (TruSeq unstranded/stranded, ScriptSeq, NuGEN) allowed the detection of a large common set of splice variants. However, each LSP also detected a small set of unique transcripts that are characterized by a low coverage and/or FPKM. This effect was particularly evident using the low input RNA NuGEN v2 protocol.

A benchmark dataset, in which synthetic reads as well as reads generated from standard (Illumina TruSeq 100) and low input (NuGEN) LSPs were spiked-in was used to evaluate the effect of LSP on the statistical detection of alternative splicing events (AltDE). Statistical detection of AltDE was done using as prototypes for splice variant-quantification Cuffdiff2 and RSEM-EBSeq. As prototype for exon-level analysis DEXSeq was used. Exon-level analysis performed slightly better than splice variant-quantification approaches, although at most only 50% of the spiked-in transcripts was detected. The performances of both splice variant-quantification and exon-level analysis improved when raising the number of input reads.

Conclusion

Data, derived from NuGEN v2, were not the ideal input for AltDE, especially when the exon-level approach was used. We observed that both splice variant-quantification and exon-level analysis performances were strongly dependent on the number of input reads. Moreover, the ribosomal RNA depletion protocol was less sensitive in detecting splicing variants, possibly due to the significant percentage of the reads mapping to non-coding transcripts.

Amplification-based method for microRNA detection

Over the last two decades, the study of miRNAs has attracted tremendous attention since they regulate gene expression post-transcriptionally and have been demonstrated to be dysregulated in many diseases. Detection methods with higher sensitivity, specificity and selectivity between precursors and mature microRNAs are urgently needed and widely studied. This review gave an overview of the amplification-based technologies including traditional methods, current modified methods and the cross-platforms of them combined with other techniques. Many progresses were found in the modified amplification-based microRNA detection methods, while traditional platforms could not be replaced until now. Several sample-specific normalizers had been validated, suggesting that the different normalizers should be established for different sample types and the combination of several normalizers might be more appropriate than a single universal normalizer. This systematic overview would be useful to provide comprehensive information for subsequent related studies and could reduce the un-necessary repetition in the future.

Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples

Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA libraries are needed for optimal results from next-generation sequencing. Environmental samples such as water may have low quality and quantities of DNA as well as contaminants that co-precipitate with DNA. The mechanical and enzymatic processes involved in extraction and library preparation may further damage the DNA. Gel size selection enables purification and recovery of DNA fragments of a defined size for sequencing applications. Nevertheless, this task is one of the most time-consuming steps in the DNA library preparation workflow. The protocol described here enables complete automation of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments. In this study, we describe a high-throughput approach to prepare high quality DNA libraries from freshwater samples that can be applied also to other environmental samples. We used an indirect approach to concentrate bacterial cells from environmental freshwater samples; DNA was extracted using a commercially available DNA extraction kit, and DNA libraries were prepared using a commercial transposon-based protocol. DNA fragments of 500 to 800 bp were gel size selected using Ranger Technology, an automated electrophoresis workstation. Sequencing of the size-selected DNA libraries demonstrated significant improvements to read length and quality of the sequencing reads.

Manipulating microRNAs for improved biomass and biofuels from plant feedstocks

Petroleum-based fuels are nonrenewable and unsustainable. Renewable sources of energy, such as lignocellulosic biofuels and plant metabolite-based drop-in fuels, can offset fossil fuel use and reverse environmental degradation through carbon sequestration. Despite these benefits, the lignocellulosic biofuels industry still faces many challenges, including the availability of economically viable crop plants. Cell wall recalcitrance is a major economic barrier for lignocellulosic biofuels production from biomass crops. Sustainability and biomass yield are two additional, yet interrelated, foci for biomass crop improvement. Many scientists are searching for solutions to these problems within biomass crop genomes. MicroRNAs (miRNAs) are involved in almost all biological and metabolic process in plants including plant development, cell wall biosynthesis and plant stress responses. Because of the broad functions of their targets (e.g. auxin response factors), the alteration of plant miRNA expression often results in pleiotropic effects. A specific miRNA usually regulates a biologically relevant bioenergy trait. For example, relatively low miR156 overexpression leads to a transgenic feedstock with enhanced biomass and decreased recalcitrance. miRNAs have been overexpressed in dedicated bioenergy feedstocks such as poplar and switchgrass yielding promising results for lignin reduction, increased plant biomass, the timing of flowering and response to harsh environments. In this review, we present the status of miRNA-related research in several major biofuel crops and relevant model plants. We critically assess published research and suggest next steps for miRNA manipulation in feedstocks for increased biomass and sustainability for biofuels and bioproducts.

Sequencing the functional antibody repertoire--diagnostic and therapeutic discovery

The development of high-throughput DNA sequencing technologies has enabled large-scale characterization of functional antibody repertoires, a new method of understanding protective and pathogenic immune responses. Important parameters to consider when sequencing antibody repertoires include the methodology, the B-cell population and clinical characteristics of the individuals analysed, and the bioinformatic analysis. Although focused sequencing of immunoglobulin heavy chains or complement determining regions can be utilized to monitor particular immune responses and B-cell malignancies, high-fidelity analysis of the full-length paired heavy and light chains expressed by individual B cells is critical for characterizing functional antibody repertoires. Bioinformatic identification of clonal antibody families and recombinant expression of representative members produces recombinant antibodies that can be used to identify the antigen targets of functional immune responses and to investigate the mechanisms of their protective or pathogenic functions. Integrated analysis of coexpressed functional genes provides the potential to further pinpoint the most important antibodies and clonal families generated during an immune response. Sequencing antibody repertoires is transforming our understanding of immune responses to autoimmunity, vaccination, infection and cancer. We anticipate that antibody repertoire sequencing will provide next-generation biomarkers, diagnostic tools and therapeutic antibodies for a spectrum of diseases, including rheumatic diseases.

Whole genome amplification induced bias in the detection of KRAS-mutated cell populations during colorectal carcinoma tissue testing

Whole genome amplification replicates the entire DNA content of a sample and can thus help to circumvent material limitations when insufficient DNA is available for planned genetic analyses. However, there are conflicting data in the literature whether whole genome amplification introduces bias or reflects precisely the spectrum of starting DNA. We analyzed the origins of discrepancies in KRAS (Kirsten rat sarcoma viral oncogene homolog gene) mutation detection in six of ten samples amplified using the GenomePlex® Tissue Whole Genome Amplification kit 5 (WGA5; Sigma-Aldrich, St. Louis, MO, USA) and KRAS StripAssay® (KRAS SA; ViennaLab Diagnostics, Vienna, Austria). We undertook reextraction, reamplification, retyping, authentication, reanalysis, and reinterpretation to determine whether the discrepancies originated during the preanalytical, analytical, and/or interpretative phase of genotyping. We conclude that a combination of glass slide/sample heterogeneity and biased amplification due to stochastic effects in the early phases of whole genome amplification (WGA) may have adversely affected the results obtained. Our findings are relevant for both forensic genetics testing and massively parallel sequencing using preamplification.

Assessing the accuracy of quantitative molecular microbial profiling

The application of high-throughput sequencing in profiling microbial communities is providing an unprecedented ability to investigate microbiomes. Such studies typically apply one of two methods: amplicon sequencing using PCR to target a conserved orthologous sequence (typically the 16S ribosomal RNA gene) or whole (meta)genome sequencing (WGS). Both methods have been used to catalog the microbial taxa present in a sample and quantify their respective abundances. However, a comparison of the inherent precision or bias of the different sequencing approaches has not been performed. We previously developed a metagenomic control material (MCM) to investigate error when performing different sequencing strategies. Amplicon sequencing using four different primer strategies and two 16S rRNA regions was examined (Roche 454 Junior) and compared to WGS (Illumina HiSeq). All sequencing methods generally performed comparably and in good agreement with organism specific digital PCR (dPCR); WGS notably demonstrated very high precision. Where discrepancies between relative abundances occurred they tended to differ by less than twofold. Our findings suggest that when alternative sequencing approaches are used for microbial molecular profiling they can perform with good reproducibility, but care should be taken when comparing small differences between distinct methods. This work provides a foundation for future work comparing relative differences between samples and the impact of extraction methods. We also highlight the value of control materials when conducting microbial profiling studies to benchmark methods and set appropriate thresholds.

Illuminating choices for library prep: a comparison of library preparation methods for whole genome sequencing of Cryptococcus neoformans using Illumina HiSeq

The industry of next-generation sequencing is constantly evolving, with novel library preparation methods and new sequencing machines being released by the major sequencing technology companies annually. The Illumina TruSeq v2 library preparation method was the most widely used kit and the market leader; however, it has now been discontinued, and in 2013 was replaced by the TruSeq Nano and TruSeq PCR-free methods, leaving a gap in knowledge regarding which is the most appropriate library preparation method to use. Here, we used isolates from the pathogenic fungi Cryptococcus neoformans var. grubii and sequenced them using the existing TruSeq DNA v2 kit (Illumina), along with two new kits: the TruSeq Nano DNA kit (Illumina) and the NEBNext Ultra DNA kit (New England Biolabs) to provide a comparison. Compared to the original TruSeq DNA v2 kit, both newer kits gave equivalent or better sequencing data, with increased coverage. When comparing the two newer kits, we found little difference in cost and workflow, with the NEBNext Ultra both slightly cheaper and faster than the TruSeq Nano. However, the quality of data generated using the TruSeq Nano DNA kit was superior due to higher coverage at regions of low GC content, and more SNPs identified. Researchers should therefore evaluate their resources and the type of application (and hence data quality) being considered when ultimately deciding on which library prep method to use.

GeneFriends: a human RNA-seq-based gene and transcript co-expression database

Co-expression networks have proven effective at assigning putative functions to genes based on the functional annotation of their co-expressed partners, in candidate gene prioritization studies and in improving our understanding of regulatory networks. The growing number of genome resequencing efforts and genome-wide association studies often identify loci containing novel genes and there is a need to infer their functions and interaction partners. To facilitate this we have expanded GeneFriends, an online database that allows users to identify co-expressed genes with one or more user-defined genes. This expansion entails an RNA-seq-based co-expression map that includes genes and transcripts that are not present in the microarray-based co-expression maps, including over 10 000 non-coding RNAs. The results users obtain from GeneFriends include a co-expression network as well as a summary of the functional enrichment among the co-expressed genes. Novel insights can be gathered from this database for different splice variants and ncRNAs, such as microRNAs and lincRNAs. Furthermore, our updated tool allows candidate transcripts to be linked to diseases and processes using a guilt-by-association approach. GeneFriends is freely available from http://www.GeneFriends.org and can be used to quickly identify and rank candidate targets relevant to the process or disease under study.

A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq

BACKGROUND

Next-Generation Sequencing (NGS) is revolutionizing molecular epidemiology by providing new approaches to undertake whole genome sequencing (WGS) in diagnostic settings for a variety of human and veterinary pathogens. Previous sequencing protocols have been subject to biases such as those encountered during PCR amplification and cell culture, or are restricted by the need for large quantities of starting material. We describe here a simple and robust methodology for the generation of whole genome sequences on the Illumina MiSeq. This protocol is specific for foot-and-mouth disease virus (FMDV) or other polyadenylated RNA viruses and circumvents both the use of PCR and the requirement for large amounts of initial template.

RESULTS

The protocol was successfully validated using five FMDV positive clinical samples from the 2001 epidemic in the United Kingdom, as well as a panel of representative viruses from all seven serotypes. In addition, this protocol was successfully used to recover 94% of an FMDV genome that had previously been identified as cell culture negative. Genome sequences from three other non-FMDV polyadenylated RNA viruses (EMCV, ERAV, VESV) were also obtained with minor protocol amendments. We calculated that a minimum coverage depth of 22 reads was required to produce an accurate consensus sequence for FMDV O. This was achieved in 5 FMDV/O/UKG isolates and the type O FMDV from the serotype panel with the exception of the 5' genomic termini and area immediately flanking the poly(C) region.

CONCLUSIONS

We have developed a universal WGS method for FMDV and other polyadenylated RNA viruses. This method works successfully from a limited quantity of starting material and eliminates the requirement for genome-specific PCR amplification. This protocol has the potential to generate consensus-level sequences within a routine high-throughput diagnostic environment.

MicroRNAs influence reproductive responses by females to male sex peptide in Drosophila melanogaster

Across taxa, female behavior and physiology change significantly following the receipt of ejaculate molecules during mating. For example, receipt of sex peptide (SP) in female Drosophila melanogaster significantly alters female receptivity, egg production, lifespan, hormone levels, immunity, sleep, and feeding patterns. These changes are underpinned by distinct tissue- and time-specific changes in diverse sets of mRNAs. However, little is yet known about the regulation of these gene expression changes, and hence the potential role of microRNAs (miRNAs), in female postmating responses. A preliminary screen of genomic responses in females to receipt of SP suggested that there were changes in the expression of several miRNAs. Here we tested directly whether females lacking four of the candidate miRNAs highlighted (miR-279, miR-317, miR-278, and miR-184) showed altered fecundity, receptivity, and lifespan responses to receipt of SP, when mated once or continually to SP null or control males. The results showed that miRNA-lacking females mated to SP null males exhibited altered receptivity, but not reproductive output, in comparison to controls. However, these effects interacted significantly with the genetic background of the miRNA-lacking females. No significant survival effects were observed in miRNA-lacking females housed continually with SP null or control males. However, continual exposure to control males that transferred SP resulted in significantly higher variation in miRNA-lacking female lifespan than did continual exposure to SP null males. The results provide the first insight into the effects and importance of miRNAs in regulating postmating responses in females.

Extended blood group molecular typing and next-generation sequencing

Several high-throughput multiplex blood group molecular typing platforms have been developed to predict blood group antigen phenotypes. These molecular systems support extended donor/patient matching by detecting commonly encountered blood group polymorphisms as well as rare alleles that determine the expression of blood group antigens. Extended molecular typing of a large number of blood donors by high-throughput platforms can increase the likelihood of identifying donor red blood cells that match those of recipients. This is especially important in the management of multiply-transfused patients who may have developed several alloantibodies. Nevertheless, current molecular techniques have limitations. For example, they detect only predefined genetic variants. In contrast, target enrichment next-generation sequencing (NGS) is an emerging technology that provides comprehensive sequence information, focusing on specified genomic regions. Target enrichment NGS is able to assess genetic variations that cannot be achieved by traditional Sanger sequencing or other genotyping platforms. Target enrichment NGS has been used to detect both known and de novo genetic polymorphisms, including single-nucleotide polymorphisms, indels (insertions/deletions), and structural variations. This review discusses the methodology, advantages, and limitations of the current blood group genotyping techniques and describes various target enrichment NGS approaches that can be used to develop an extended blood group genotyping assay system.

Biotic interactions and temporal dynamics of the human gastrointestinal microbiota

The human gastrointestinal (GI) microbiota is important to human health and imbalances or shifts in the gut microbial community have been linked to many diseases. Most studies of the GI microbiota only capture snapshots of this dynamic community at one or a few time points. Although this is valuable in terms of providing knowledge of community composition and variability between individuals, it does not provide the foundation for going beyond descriptive studies and toward truly predictive ecological models. In order to achieve this goal, we need longitudinal data of appropriate temporal and taxonomic resolution, so that established time series analysis tools for identifying and quantifying putative interactions among community members can be used. Here, we present new analyses of existing data to illustrate the potential usefulness of this approach. We discuss challenges related to sampling and data processing, as well as analytical approaches and considerations for future studies of the GI microbiota and other complex microbial systems.

Ten years of next-generation sequencing technology

Ten years ago next-generation sequencing (NGS) technologies appeared on the market. During the past decade, tremendous progress has been made in terms of speed, read length, and throughput, along with a sharp reduction in per-base cost. Together, these advances democratized NGS and paved the way for the development of a large number of novel NGS applications in basic science as well as in translational research areas such as clinical diagnostics, agrigenomics, and forensic science. Here we provide an overview of the evolution of NGS and discuss the most significant improvements in sequencing technologies and library preparation protocols. We also explore the current landscape of NGS applications and provide a perspective for future developments.

Das methodische Potenzial der neuen Sequenziertechnologien jenseits der Mutationssuche

In diesem Beitrag wird eine Reihe wichtiger Anwendungen der neuen Sequenziertechnologien bzw. des Next Generation Sequencing (NGS) vorgestellt. An ausgewählten Beispielen werden für jede Methode die Anwendungsmöglichkeiten in der humangenetischen Forschung dargestellt, jeweils das prinzipielle Vorgehen beschrieben und mögliche Quellen für ausführliche Arbeitsanweisungen vorgestellt. Die beschriebenen Techniken umfassen im Einzelnen: RNA-Sequenzierung mittels NGS („RNA-Seq“), Chromatinimmunpräzipitation in Kombination mit NGS („ChIP-Seq“), „ribosome profiling“, Immunpräzipitation methylierter DNA-Segmente in Kombination mit NGS („methylated DNA immunoprecipitation“ bzw. „MeDIP-Seq“) und die HiC-Technik, eine Weiterentwicklung der Chromosome-Conformation-Capture(3c)-Methode.

Analysis of plant microbe interactions in the era of next generation sequencing technologies

Next generation sequencing (NGS) technologies have impressively accelerated research in biological science during the last years by enabling the production of large volumes of sequence data to a drastically lower price per base, compared to traditional sequencing methods. The recent and ongoing developments in the field allow addressing research questions in plant-microbe biology that were not conceivable just a few years ago. The present review provides an overview of NGS technologies and their usefulness for the analysis of microorganisms that live in association with plants. Possible limitations of the different sequencing systems, in particular sources of errors and bias, are critically discussed and methods are disclosed that help to overcome these shortcomings. A focus will be on the application of NGS methods in metagenomic studies, including the analysis of microbial communities by amplicon sequencing, which can be considered as a targeted metagenomic approach. Different applications of NGS technologies are exemplified by selected research articles that address the biology of the plant associated microbiota to demonstrate the worth of the new methods.

Integrative RNA-seq and microarray data analysis reveals GC content and gene length biases in the psoriasis transcriptome

Gene expression profiling of psoriasis has driven research advances and may soon provide the basis for clinical applications. For expression profiling studies, RNA-seq is now a competitive technology, but RNA-seq results may differ from those obtained by microarray. We therefore compared findings obtained by RNA-seq with those from eight microarray studies of psoriasis. RNA-seq and microarray datasets identified similar numbers of differentially expressed genes (DEGs), with certain genes uniquely identified by each technology. Correspondence between platforms and the balance of increased to decreased DEGs was influenced by mRNA abundance, GC content, and gene length. Weakly expressed genes, genes with low GC content, and long genes were all biased toward decreased expression in psoriasis lesions. The strength of these trends differed among array datasets, most likely due to variations in RNA quality. Gene length bias was by far the strongest trend and was evident in all datasets regardless of the expression profiling technology. The effect was due to differences between lesional and uninvolved skin with respect to the genome-wide correlation between gene length and gene expression, which was consistently more negative in psoriasis lesions. These findings demonstrate the complementary nature of RNA-seq and microarray technology and show that integrative analysis of both data types can provide a richer view of the transcriptome than strict reliance on a single method alone. Our results also highlight factors affecting correspondence between technologies, and we have established that gene length is a major determinant of differential expression in psoriasis lesions.

Analysis considerations for utilizing RNA-Seq to characterize the brain transcriptome

RNA-Seq allows one to examine only gene expression as well as expression of noncoding RNAs, alternative splicing, and allele-specific expression. With this increased sensitivity and dynamic range, there are computational and statistical considerations that need to be contemplated, which are highly dependent on the biological question being asked. We highlight these to provide an overview of their importance and the impact they can have on downstream interpretation of the brain transcriptome.