Quantitative bias in Illumina TruSeq and a novel post amplification barcoding strategy for multiplexed DNA and small RNA deep sequencing

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

STAT3 Is the Master Regulator for the Forming of 3D Spheroids of 3T3-L1 Preadipocytes

To elucidate the currently unknown mechanisms responsible for the diverse biological aspects between two-dimensional (2D) and three-dimensional (3D) cultured 3T3-L1 preadipocytes, RNA-sequencing analyses were performed. During a 7-day culture period, 2D- and 3D-cultured 3T3-L1 cells were subjected to lipid staining by BODIPY, qPCR for adipogenesis related genes, including peroxisome proliferator-activated receptor γ (Pparγ), CCAAT/enhancer-binding protein alpha (Cebpa), Ap2 (fatty acid-binding protein 4; Fabp4), leptin, and AdipoQ (adiponectin), and RNA-sequencing analysis. Differentially expressed genes (DEGs) were detected by next-generation RNA sequencing (RNA-seq) and validated by a quantitative reverse transcription–polymerase chain reaction (qRT–PCR). Bioinformatic analyses were performed on DEGs using a Gene Ontology (GO) enrichment analysis and an Ingenuity Pathway Analysis (IPA). Significant spontaneous adipogenesis was observed in 3D 3T3-L1 spheroids, but not in 2D-cultured cells. The mRNA expression of Pparγ, Cebpa, and Ap2 among the five genes tested were significantly higher in 3D spheroids than in 2D-cultured cells, thus providing support for this conclusion. RNA analysis demonstrated that a total of 826 upregulated and 725 downregulated genes were identified as DEGs. GO enrichment analysis and IPA found 50 possible upstream regulators, and among these, 6 regulators—transforming growth factor β1 (TGFβ1), signal transducer and activator of transcription 3 (STAT3), interleukin 6 (IL6), angiotensinogen (AGT), FOS, and MYC—were, in fact, significantly upregulated. Further analyses of these regulators by causal networks of the top 14 predicted diseases and functions networks (IPA network score indicated more than 30), suggesting that STAT3 was the most critical upstream regulator. The findings presented herein suggest that STAT3 has a critical role in regulating the unique biological properties of 3D spheroids that are produced from 3T3-L1 preadipocytes.

A Small RNA-Seq Protocol with Less Bias and Improved Capture of 2'-O-Methyl RNAs

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNAs such as plant microRNAs (miRNAs) carry a 2'-O-methyl (2'-OMe) modification at their 3' terminal nucleotide. This modification adds another level of difficulty as it inhibits 3' adapter ligation. We previously demonstrated that modified versions of the "TruSeq (TS)" protocol have less bias and an improved detection of 2'-OMe RNAs. Here we describe in detail protocol "TS5," which showed the best overall performance. We also provide guidelines for bioinformatics analysis of the sequencing data.

Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: Wet lab procedure

Metagenomic high-throughput sequencing (mHTS) is a hypothesis-free, universal pathogen detection technique for determination of the DNA/RNA sequences in a variety of sample types and infectious syndromes. mHTS is still in its early stages of translating into clinical application. To support the development, implementation and standardization of mHTS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mHTS for viral diagnostics to share methodologies and experiences, and to develop application recommendations. This manuscript aims to provide practical recommendations for the wet lab procedures necessary for implementation of mHTS for virus diagnostics and to give recommendations for development and validation of laboratory methods, including mHTS quality assurance, control and quality assessment protocols.

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

A comparison between SOLiD 5500XLand Ion Torrent PGM-derived miRNA expression profiles in two breast cell lines

Next-generation sequencing (NGS) platforms allow the analysis of hundreds of millions of molecules in a single sequencing run, revolutionizing many research areas. NGS-based microRNA studies enable expression quantification in unprecedented scale without the limitations of closed-platforms. Yet, whereas a massive amount of data produced by these platforms is available, comparisons of quantification/discovery capabilities between platforms are still lacking. Here we compare two NGS-platforms: SOLiD and PGM, by evaluating their microRNA identification/quantification capabilities using two breast-derived cell-lines. A high expression correlation (R2 > 0.9) was achieved, encompassing 97% of the miRNAs, and the few discrepancies in miRNA counts were attributable to molecules that have very low expression. Quantification divergences indicative of artefactual representation were seen for 14 miRNAs (higher in SOLiD-reads) and another 10 miRNAs more abundant in PGM-data. An inspection of these revealed an increased and statistically significant count of uracyls and uracyl-stretches for PGM-enriched miRNAs, compared to SOLiD and to the miRBase. In parallel, adenines and adenine-stretches were enriched for SOLiDderived miRNA reads. We conclude that, whereas both platforms are overall consistent and can be used interchangeably for microRNA expression studies, particular sequence features appear to be indicative of specific platform bias, and their presence in microRNAs should be considered for database-analyses.

RNA-seq and ChIP-seq as Complementary Approaches for Comprehension of Plant Transcriptional Regulatory Mechanism

The availability of data produced from various sequencing platforms offer the possibility to answer complex questions in plant research. However, drawbacks can arise when there are gaps in the information generated, and complementary platforms are essential to obtain more comprehensive data sets relating to specific biological process, such as responses to environmental perturbations in plant systems. The investigation of transcriptional regulation raises different challenges, particularly in associating differentially expressed transcription factors with their downstream responsive genes. In this paper, we discuss the integration of transcriptional factor studies through RNA sequencing (RNA-seq) and Chromatin Immunoprecipitation sequencing (ChIP-seq). We show how the data from ChIP-seq can strengthen information generated from RNA-seq in elucidating gene regulatory mechanisms. In particular, we discuss how integration of ChIP-seq and RNA-seq data can help to unravel transcriptional regulatory networks. This review discusses recent advances in methods for studying transcriptional regulation using these two methods. It also provides guidelines for making choices in selecting specific protocols in RNA-seq pipelines for genome-wide analysis to achieve more detailed characterization of specific transcription regulatory pathways via ChIP-seq.

Analysis of 3' End Modifications in microRNAs by High-Throughput Sequencing

MicroRNAs are ~22 nt small, non-coding RNAs that direct posttranscriptional silencing of gene expression to regulate animal development, physiology, and disease. An emerging mechanism that controls the biogenesis of microRNAs is the addition of non-templated nucleotides, predominantly uridine, to the 3' end of precursor-microRNAs, in a process that is commonly referred to as tailing. Here, we describe methods that enable the systematic characterization of tailing events in mature microRNAs and their precursors. We report protocols for untargeted and targeted cDNA library preparation procedures, as exemplified in the context of the model organism Drosophila melanogaster and focusing on precursor-microRNAs. We also refer to a dedicated computational framework for the subsequent analysis of untemplated nucleotide additions in cDNA libraries. The described methods for the systematic characterization of posttranscriptional modifications in gene regulatory small RNAs and their precursors will be instrumental in clarifying regulatory concepts that control posttranscriptional gene silencing.

High-throughput, Efficient, and Unbiased Capture of Small RNAs from Low-input Samples for Sequencing

MicroRNAs hold great promise as biomarkers of disease. However, there are few efficient and robust methods for measuring microRNAs from low input samples. Here, we develop a high-throughput sequencing protocol that efficiently captures small RNAs while minimizing inherent biases associated with library production. The protocol is based on early barcoding such that all downstream manipulations can be performed on a pool of many samples thereby reducing reagent usage and workload. We show that the optimization of adapter concentrations along with the addition of nucleotide modifications and random nucleotides increases the efficiency of small RNA capture. We further show, using unique molecular identifiers, that stochastic capture of low input RNA rather than PCR amplification influences the biased quantitation of intermediately and lowly expressed microRNAs. Our improved method allows the processing of tens to hundreds of samples simultaneously while retaining high efficiency quantitation of microRNAs in low input samples from tissues or bodily fluids.

Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application.

Preparation of highly multiplexed small RNA sequencing libraries

MicroRNAs (miRNAs) are ~22-nucleotide-long small non-coding RNAs that regulate the expression of protein-coding genes by base pairing to partially complementary target sites, preferentially located in the 3´ untranslated region (UTR) of target mRNAs. The expression and function of miRNAs have been extensively studied in human disease, as well as the possibility of using these molecules as biomarkers for prognostication and treatment guidance. To identify and validate miRNAs as biomarkers, their expression must be screened in large collections of patient samples. Here, we develop a scalable protocol for the rapid and economical preparation of a large number of small RNA sequencing libraries using dual indexing for multiplexing. Combined with the use of off-the-shelf reagents, more samples can be sequenced simultaneously on large-scale sequencing platforms at a considerably lower cost per sample. Sample preparation is simplified by pooling libraries prior to gel purification, which allows for the selection of a narrow size range while minimizing sample variation. A comparison with publicly available data from benchmarking of miRNA analysis platforms showed that this method captures absolute and differential expression as effectively as commercially available alternatives.

Determination of absolute expression profiles using multiplexed miRNA analysis

Accurate measurement of miRNA expression is critical to understanding their role in gene expression as well as their application as disease biomarkers. Correct identification of changes in miRNA expression rests on reliable normalization to account for biological and technological variance between samples. Ligo-miR is a multiplex assay designed to rapidly measure absolute miRNA copy numbers, thus reducing dependence on biological controls. It uses a simple 2-step ligation process to generate length coded products that can be quantified using a variety of DNA sizing methods. We demonstrate Ligo-miR's ability to quantify miRNA expression down to 20 copies per cell sensitivity, accurately discriminate between closely related miRNA, and reliably measure differential changes as small as 1.2-fold. Then, benchmarking studies were performed to show the high correlation between Ligo-miR, microarray, and TaqMan qRT-PCR. Finally, Ligo-miR was used to determine copy number profiles in a number of breast, esophageal, and pancreatic cell lines and to demonstrate the utility of copy number analysis for providing layered insight into expression profile changes.

Contribution of Next-Generation Sequencing to Aquatic and Fish Virology

The recent technological advances in nucleic acid sequencing, called next-generation sequencing (NGS), have revolutionized the field of genomics and have also influenced viral research. Aquatic viruses, and especially those infecting fish, have also greatly benefited from NGS technologies, which provide a huge amount of molecular information at a low cost in a relatively short period of time. Here, we review the use of the current high-throughput sequencing platforms with a special focus on the associated challenges (regarding sample preparation and bioinformatics) in their applications to the field of aquatic virology, especially for: (i) discovering novel viruses that may be associated with fish mortalities, (ii) elucidating the mechanisms of pathogenesis, and finally (iii) studying the molecular epidemiology of these pathogens.

Targeted genomic enrichment and sequencing of CyHV-3 from carp tissues confirms low nucleotide diversity and mixed genotype infections

Koi herpesvirus disease (KHVD) is an emerging disease that causes mass mortality in koi and common carp, Cyprinus carpio L. Its causative agent is Cyprinid herpesvirus 3 (CyHV-3), also known as koi herpesvirus (KHV). Although data on the pathogenesis of this deadly virus is relatively abundant in the literature, still little is known about its genomic diversity and about the molecular mechanisms that lead to such a high virulence. In this context, we developed a new strategy for sequencing full-length CyHV-3 genomes directly from infected fish tissues. Total genomic DNA extracted from carp gill tissue was specifically enriched with CyHV-3 sequences through hybridization to a set of nearly 2 million overlapping probes designed to cover the entire genome length, using KHV-J sequence (GenBank accession number AP008984) as reference. Applied to 7 CyHV-3 specimens from Poland and Indonesia, this targeted genomic enrichment enabled recovery of the full genomes with >99.9% reference coverage. The enrichment rate was directly correlated to the estimated number of viral copies contained in the DNA extracts used for library preparation, which varied between ∼5000 and ∼2×10⁷. The average sequencing depth was >200 for all samples, thus allowing the search for variants with high confidence. Sequence analyses highlighted a significant proportion of intra-specimen sequence heterogeneity, suggesting the presence of mixed infections in all investigated fish. They also showed that inter-specimen genetic diversity at the genome scale was very low (>99.95% of sequence identity). By enabling full genome comparisons directly from infected fish tissues, this new method will be valuable to trace outbreaks rapidly and at a reasonable cost, and in turn to understand the transmission routes of CyHV-3.

Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow

Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will encourage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions.

Where does transcription start? 5'-RACE adapted to next-generation sequencing

The variability and complexity of the transcription initiation process was examined by adapting RNA ligase-mediated rapid amplification of 5' cDNA ends (5'-RACE) to Next-Generation Sequencing (NGS). We oligo-labelled 5'-m(7)G-capped mRNA from two genes, the simple mono-exonic Beta-2-Adrenoceptor (ADRB2R)and the complex multi-exonic Glucocorticoid Receptor (GR, NR3C1), and detected a variability in TSS location that has received little attention up to now. Transcription was not initiated at a fixed TSS, but from loci of 4 to 10 adjacent nucleotides. Individual TSSs had frequencies from <0.001% to 38.5% of the total gene-specific 5' m(7)G-capped transcripts. ADRB2R used a single locus consisting of 4 adjacent TSSs. Unstimulated, the GR used a total of 358 TSSs distributed throughout 38 loci, that were principally in the 5' UTRs and were spliced using established donor and acceptor sites. Complete demethylation of the epigenetically sensitive GR promoter with 5-azacytidine induced one new locus and 127 TSSs, 12 of which were unique. We induced GR transcription with dexamethasone and Interferon-γ, adding one new locus and 185 additional TSSs distributed throughout the promoter region. In-vitro the TSS microvariability regulated mRNA translation efficiency and the relative abundance of the different GRN-terminal protein isoform levels.

Addressing Bias in Small RNA Library Preparation for Sequencing: A New Protocol Recovers MicroRNAs that Evade Capture by Current Methods

Recent advances in sequencing technology have helped unveil the unexpected complexity and diversity of small RNAs. A critical step in small RNA library preparation for sequencing is the ligation of adapter sequences to both the 5' and 3' ends of small RNAs. Studies have shown that adapter ligation introduces a significant but widely unappreciated bias in the results of high-throughput small RNA sequencing. We show that due to this bias the two widely used Illumina library preparation protocols produce strikingly different microRNA (miRNA) expression profiles in the same batch of cells. There are 102 highly expressed miRNAs that are >5-fold differentially detected and some miRNAs, such as miR-24-3p, are over 30-fold differentially detected. While some level of bias in library preparation is not surprising, the apparent massive differential bias between these two widely used adapter sets is not well appreciated. In an attempt to mitigate this bias, the new Bioo Scientific NEXTflex V2 protocol utilizes a pool of adapters with random nucleotides at the ligation boundary. We show that this protocol is able to detect robustly several miRNAs that evade capture by the Illumina-based methods. While these analyses do not indicate a definitive gold standard for small RNA library preparation, the results of the NEXTflex protocol do correlate best with RT-qPCR. As increasingly more laboratories seek to study small RNAs, researchers should be aware of the extent to which the results may differ with different protocols, and should make an informed decision about the protocol that best fits their study.

Efficient synthesis of stably adenylated DNA and RNA adapters for microRNA capture using T4 RNA ligase 1

MicroRNA profiling methods have become increasingly important due to the rapid rise of microRNA in both basic and translational sciences. A critical step in many microRNA profiling assays is adapter ligation using pre-adenylated adapters. While pre-adenylated adapters can be chemically or enzymatically prepared, enzymatic adenylation is preferred due to its ease and high yield. However, previously reported enzymatic methods either require tedious purification steps or use thermostable ligases that can generate side products during the subsequent ligation step. We have developed a highly efficient, template- and purification-free, adapter adenylation method using T4 RNA ligase 1. This method is capable of adenylating large amounts of adapter at ~100% efficiency and can efficiently adenylate both DNA and RNA bases. We find that the adenylation reaction speed can differ between DNA and RNA and between terminal nucleotides, leading to bias if reactions are not allowed to run to completion. We further find that the addition of high PEG levels can effectively suppress these differences.

A novel method to identify and isolate proliferative inflammatory atrophy (PIA) clusters and to extract high-quality PIA RNA

Epidemiological and histopathological studies have indicated that proliferative inflammatory atrophy (PIA) of the prostate is closely associated with the onset and development of prostate cancer (PCa). However, accurate isolation of PIA still remains a difficult matter, as well as high-quality RNA extraction from isolated PIA. These issues generated a lack of molecular evidence to support the mechanistic explanation proposed for the progression of PIA to PCa. Therefore, the isolation of PIA and the extraction of high-quality RNA from isolated PIA are of great importance to further demonstrate the correlation between PIA and the development of PCa at a molecular level. In this study, clinical samples from radical prostatectomy were stored in liquid nitrogen, PIA was identified by H&E staining of cryosections, PIA clusters were isolated by manual microdissection, total RNA was extracted from the PIA clusters by Trizol, and RNA quality was determined using the Agilent 2100 Bioanalyzer. Our results showed that PIA might be isolated by manual microdissection of cryosections stored in liquid nitrogen from clinical radical prostatectomy and used for extracting high-quality RNA (RIN > 7.5) by Trizol. Therefore, the present study established a valid method to discover molecular evidence in support of the correlation between PIA and the development of PCa.

Profiling the circulating miRNAs in mice exposed to gram-positive and gram-negative bacteria by Illumina small RNA deep sequencing

BACKGROUND

We profiled the expression of circulating microRNAs (miRNAs) in mice using Illumina small RNA deep sequencing in order to identify the miRNAs that may potentially be used as biomarkers to distinguish between gram-negative and gram-positive bacterial infections.

RESULTS

Recombinant-specific gram-negative pathogen Escherichia coli (Xen14) and gram-positive pathogen Staphylococcus aureus (Xen29) were used to induce bacterial infection in mice at a concentration of 1 × 10(8) bacteria/100 μL of phosphate buffered saline (PBS). Small RNA libraries generated from the serum of mice after exposure to PBS, Xen14, Xen29, and Xen14 + Xen29 via the routes of subcutaneous injection (I), cut wound (C), or under grafted skin (S) were analyzed using an Illumina HiSeq2000 Sequencer. Following exposure to gram-negative bacteria alone, no differentially expressed miRNA was found in the injection, cut, or skin graft models. Exposure to mixed bacteria induced a similar expression pattern of the circulating miRNAs to that induced by gram-positive bacterial infection. Upon gram-positive bacterial infection, 9 miRNAs (mir-193b-3p, mir-133a-1-3p, mir-133a-2-3p, mir-133a-1-5p, mir-133b-3p, mir-434-3p, mir-127-3p, mir-676-3p, mir-215-5p) showed upregulation greater than 4-fold with a p-value < 0.01. Among them, mir-193b-3p, mir-133a-1-3p, and mir-133a-2-3p presented the most common miRNA targets expressed in the mice exposed to gram-positive bacterial infection.

CONCLUSIONS

This study identified mir-193b-3p, mir-133a-1-3p, and mir-133a-2-3p as potential circulating miRNAs for gram-positive bacterial infections.

An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.

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.

All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing

BACKGROUND

DNA-based methods like PCR efficiently identify and quantify the taxon composition of complex biological materials, but are limited to detecting species targeted by the choice of the primer assay. We show here how untargeted deep sequencing of foodstuff total genomic DNA, followed by bioinformatic analysis of sequence reads, facilitates highly accurate identification of species from all kingdoms of life, at the same time enabling quantitative measurement of the main ingredients and detection of unanticipated food components.

RESULTS

Sequence data simulation and real-case Illumina sequencing of DNA from reference sausages composed of mammalian (pig, cow, horse, sheep) and avian (chicken, turkey) species are able to quantify material correctly at the 1% discrimination level via a read counting approach. An additional metagenomic step facilitates identification of traces from animal, plant and microbial DNA including unexpected species, which is prospectively important for the detection of allergens and pathogens.

CONCLUSIONS

Our data suggest that deep sequencing of total genomic DNA from samples of heterogeneous taxon composition promises to be a valuable screening tool for reference species identification and quantification in biosurveillance applications like food testing, potentially alleviating some of the problems in taxon representation and quantification associated with targeted PCR-based approaches.

Four methods of preparing mRNA 5' end libraries using the Illumina sequencing platform

Background

The 5′ untranslated regions of mRNA play an important role in their translation.

Results

Here, we describe the development of four methods of profiling mRNA 5′ ends using the Illumina sequencing platform; the first method utilizes SMART (Switching Mechanism At 5′ end of RNA Transcript) technology, while the second involves replacing the 5′ cap structure with RNA oligomers via ligation. The third and fourth methods are modifications of SMART, and involve enriching mRNA molecules with (nuclear transcripts) and without (mitochondrial transcripts) 5′ end cap structures, respectively. Libraries prepared using SMART technology gave more reproducible results, but the ligation method was advantageous in that it only sequenced mRNAs with a cap structure at the 5′ end.

Conclusions

These methods are suitable for global mapping of mRNA 5′ ends, both with and without cap structures, at a single molecule resolution. In addition, comparison of the present results obtained using different methods revealed the presence of abundant messenger RNAs without a cap structure.

Genome-wide identification of transcript start and end sites by transcript isoform sequencing

Hundreds of transcript isoforms with varying boundaries and alternative regulatory signals are transcribed from the genome, even in a genetically homogeneous population of cells. To study this transcriptional heterogeneity, we developed transcript isoform sequencing (TIF-seq), a method that allows the genome-wide profiling of full-length transcript isoforms defined by their exact 5' and 3' boundaries. TIF-seq entails the generation of full-length cDNA libraries, followed by their circularization and the sequencing of the junction fragments spanning the 5' and 3' transcript ends. By determining the respective co-occurrence of start and end sites of individual transcript molecules, TIF-seq can distinguish variations that conventional approaches for mapping single ends cannot, such as short abortive transcripts, bicistronic messages and overlapping transcripts that differ in lengths. The TIF-seq protocol we describe here can be applied to any eukaryotic organism (e.g., yeast, human), and it requires 6-10 d for generating TIF-seq libraries, 10 d for sequencing and 2-3 d for analysis.

Comprehensive evaluation and optimization of amplicon library preparation methods for high-throughput antibody sequencing

High-throughput sequencing (HTS) of antibody repertoire libraries has become a powerful tool in the field of systems immunology. However, numerous sources of bias in HTS workflows may affect the obtained antibody repertoire data. A crucial step in antibody library preparation is the addition of short platform-specific nucleotide adapter sequences. As of yet, the impact of the method of adapter addition on experimental library preparation and the resulting antibody repertoire HTS datasets has not been thoroughly investigated. Therefore, we compared three standard library preparation methods by performing Illumina HTS on antibody variable heavy genes from murine antibody-secreting cells. Clonal overlap and rank statistics demonstrated that the investigated methods produced equivalent HTS datasets. PCR-based methods were experimentally superior to ligation with respect to speed, efficiency, and practicality. Finally, using a two-step PCR based method we established a protocol for antibody repertoire library generation, beginning from inputs as low as 1 ng of total RNA. In summary, this study represents a major advance towards a standardized experimental framework for antibody HTS, thus opening up the potential for systems-based, cross-experiment meta-analyses of antibody repertoires.

Elimination of ligation dependent artifacts in T4 RNA ligase to achieve high efficiency and low bias microRNA capture

Adapter ligation is a critical first step in many microRNA analysis methods including microarray, qPCR, and sequencing. Previous studies have shown that ligation bias can have dramatic effects on both the fidelity of expression profiles and reproducibility across samples. We have developed a method for high efficiency and low bias microRNA capture by 3′ adapter ligation using T4 RNA ligase that does not require pooled adapters. Using a panel of 20 microRNA, we investigated the effects of ligase type, PEG concentration, ligase amount, adapter concentration, incubation time, incubation temperature, and adapter design on capture efficiency and bias. Of these factors, high PEG% was found to be critical in suppressing ligation bias. We obtained high average capture efficiency and low CV across the 20 microRNA panel, both in idealized buffer conditions (86%±10%) and total RNA spiking conditions (64%±17%). We demonstrate that this method is reliable across microRNA species that previous studies have had difficulty capturing and that our adapter design performs significantly better than the common adapter designs. Further, we demonstrate that the optimization methodology must be specifically designed for minimizing bias in order to obtain the ideal reaction parameters.

Feasibility of whole RNA sequencing from single-cell mRNA amplification

Single-cell sampling with RNA-seq analysis plays an important role in reference laboratory; cytogenomic diagnosis for specimens on glass-slides or rare cells in circulating blood for tumor and genetic diseases; measurement of sensitivity and specificity in tumor-tissue genomic analysis with mixed-cells; mechanism analysis of differentiation and proliferation of cancer stem cell for academic purpose. Our single- cell RNA-seq technique shows that fragments were 250-450 bp after fragmentation, amplification, and adapter addition. There were 11.6 million reads mapped in raw sequencing reads (19.6 million). The numbers of mapped genes, mapped transcripts, and mapped exons were 31,332, 41,210, and 85,786, respectively. All QC results demonstrated that RNA-seq techniques could be used for single-cell genomic performance. Analysis of the mapped genes showed that the number of genes mapped by RNA-seq (6767 genes) was much higher than that of differential display (288 libraries) among similar specimens which we have developed and published. The single-cell RNA-seq can detect gene splicing using different subtype TGF-beta analysis. The results from using Q-rtPCR tests demonstrated that sensitivity is 76% and specificity is 55% from single-cell RNA-seq technique with some gene expression missing (2/8 genes). However, it will be feasible to use RNA-seq techniques to contribute to genomic medicine at single-cell level.

ISEV position paper: extracellular vesicle RNA analysis and bioinformatics

Extracellular vesicles (EVs) are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA) has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV) held a workshop on "evRNA analysis and bioinformatics." Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.

Differential transcriptome analysis of glandular and filamentous trichomes in Artemisia annua

BACKGROUND

The medicinal plant Artemisia annua is covered with filamentous trichomes and glandular, artemisinin producing trichomes. A high artemisinin supply is needed at a reduced cost for treating malaria. Artemisinin production in bioreactors can be facilitated if a better insight is obtained in the biosynthesis of artemisinin and other metabolites. Therefore, metabolic activities of glandular and filamentous trichomes were investigated at the transcriptome level.

RESULTS

By laser pressure catapulting, glandular and filamentous trichomes as well as apical and sub-apical cells from glandular trichomes were collected and their transcriptome was sequenced using Illumina RNA-Seq. A de novo transcriptome was assembled (Trinity) and studied with a differential expression analysis (edgeR).A comparison of the transcriptome from glandular and filamentous trichomes shows that MEP, MVA, most terpene and lipid biosynthesis pathways are significantly upregulated in glandular trichomes. Conversely, some transcripts coding for specific sesquiterpenoid and triterpenoid enzymes such as 8-epi-cedrol synthase and an uncharacterized oxidosqualene cyclase were significantly upregulated in filamentous trichomes. All known artemisinin biosynthesis genes are upregulated in glandular trichomes and were detected in both the apical and sub-apical cells of the glandular trichomes. No significant differential expression could be observed between the apical and sub-apical cells.

CONCLUSIONS

Our results underscore the vast metabolic capacities of A. annua glandular trichomes but nonetheless point to the existence of specific terpene metabolic pathways in the filamentous trichomes. Candidate genes that might be involved in artemisinin biosynthesis are proposed based on their putative function and their differential expression level.

Keys for microRNA expression profiling of single rat hypothalamic nuclei and multiplex sequencing strategies

Integrative research has taken on the challenge of addressing questions in physiology by using novel knowledge and novel techniques. Recently, small and long non-coding RNAs have emerged as key regulators of gene expression, while next-generation sequencing technologies have revolutionized the characterization of genomes and gene expression. For a decade, it has been known that microRNAs (miRNAs) are RNAs of 18-24 bases that regulate gene expression in mammals. Here, we first describe the nature of miRNAs and the advantages of high-throughput sequencing technologies for establishing miRNA expression profiles. The hypothalamus harbours a dozen specialized areas or nuclei, the sampling of which is required to establish physiologically relevant miRNA expression profiles. MicroRNA expression profiling from single animals is also important for investigating potential genetic or epigenetic differences between individuals. Establishing a large number of miRNA expression profiles of individual hypothalamic nuclei of single rats at a cost compatible with laboratory finance can be achieved by using tagged cDNA libraries constructed from purified small RNAs and a multiplex sequencing strategy. We continue this report by surveying specificities of the different strategies that are used at present for constructing tagged cDNA libraries and provide a comparative analysis of miRNA expression profiles from hypothalamic arcuate nuclei of seven male Wistar rats.

Biases in small RNA deep sequencing data

High-throughput RNA sequencing (RNA-seq) is considered a powerful tool for novel gene discovery and fine-tuned transcriptional profiling. The digital nature of RNA-seq is also believed to simplify meta-analysis and to reduce background noise associated with hybridization-based approaches. The development of multiplex sequencing enables efficient and economic parallel analysis of gene expression. In addition, RNA-seq is of particular value when low RNA expression or modest changes between samples are monitored. However, recent data uncovered severe bias in the sequencing of small non-protein coding RNA (small RNA-seq or sRNA-seq), such that the expression levels of some RNAs appeared to be artificially enhanced and others diminished or even undetectable. The use of different adapters and barcodes during ligation as well as complex RNA structures and modifications drastically influence cDNA synthesis efficacies and exemplify sources of bias in deep sequencing. In addition, variable specific RNA G/C-content is associated with unequal polymerase chain reaction amplification efficiencies. Given the central importance of RNA-seq to molecular biology and personalized medicine, we review recent findings that challenge small non-protein coding RNA-seq data and suggest approaches and precautions to overcome or minimize bias.

Chemical fragmentation for massively parallel sequencing library preparation

Fragmentation is essential in most library preparation protocols for use with massively parallel sequencing systems. Complexes that generate hydroxyl radicals, such as iron-EDTA, can be used to introduce random DNA cleavage. Here we describe a chemical fragmentation method that can be incorporated into library preparation protocols for next-generation sequencing workflows. This protocol has been validated by whole genome, amplicon and exome sequencing. Chemical fragmentation is a cost-effective alternative to current fragmentation methods that has no observable sequence bias and requires no instrumentation.

Identification of extracellular miRNA in human cerebrospinal fluid by next-generation sequencing

There has been a growing interest in using next-generation sequencing (NGS) to profile extracellular small RNAs from the blood and cerebrospinal fluid (CSF) of patients with neurological diseases, CNS tumors, or traumatic brain injury for biomarker discovery. Small sample volumes and samples with low RNA abundance create challenges for downstream small RNA sequencing assays. Plasma, serum, and CSF contain low amounts of total RNA, of which small RNAs make up a fraction. The purpose of this study was to maximize RNA isolation from RNA-limited samples and apply these methods to profile the miRNA in human CSF by small RNA deep sequencing. We systematically tested RNA isolation efficiency using ten commercially available kits and compared their performance on human plasma samples. We used RiboGreen to quantify total RNA yield and custom TaqMan assays to determine the efficiency of small RNA isolation for each of the kits. We significantly increased the recovery of small RNA by repeating the aqueous extraction during the phenol-chloroform purification in the top performing kits. We subsequently used the methods with the highest small RNA yield to purify RNA from CSF and serum samples from the same individual. We then prepared small RNA sequencing libraries using Illumina's TruSeq sample preparation kit and sequenced the samples on the HiSeq 2000. Not surprisingly, we found that the miRNA expression profile of CSF is substantially different from that of serum. To our knowledge, this is the first time that the small RNA fraction from CSF has been profiled using next-generation sequencing.

Differences in microRNA detection levels are technology and sequence dependent

Identification and quantification of small RNAs are challenging because of their short length, high sequence similarities within microRNA (miRNA) families, and the existence of miRNA isoforms and O-methyl 3' modifications. In this study, the detection performance of three high-throughput commercial platforms, Agilent and Affymetrix microarrays and Illumina next-generation sequencing, was systematically and comprehensively compared. The ability to detect miRNAs was shown to depend strongly on the platform and on miRNA modifications and sequence. Using synthetic transcripts, including mature, precursor, and O-methyl-modified miRNAs spiked into human RNA, a large intensity variation in all spiked-in miRNAs and a reduced capacity in detecting O-methyl-modified miRNAs were observed between the tested platforms. In addition, endogenous human miRNA expression levels were assessed across the platforms. Detected miRNA expression levels were not consistent between platforms. Although biases in miRNA detection were previously described, here the end-point result, i.e., detection intensity, of these biases was investigated on multiple platforms in a controlled fashion. A detailed exploration of a large number of attributes, including base composition, sequence structure, and isoform miRNA attributes, suggests their impact on miRNA expression detection level. This study provides a basis for understanding the attributes that should be considered to adjust platform-dependent detection biases.

Comparison of Analysis Tools for miRNA High Throughput Sequencing Using Nerve Crush as a Model

Recent advances in sample preparation and analysis for next generation sequencing have made it possible to profile and discover new miRNAs in a high throughput manner. In the case of neurological disease and injury, these types of experiments have been more limited. Possibly because tissues such as the brain and spinal cord are inaccessible for direct sampling in living patients, and indirect sampling of blood and cerebrospinal fluid are affected by low amounts of RNA. We used a mouse model to examine changes in miRNA expression in response to acute nerve crush. We assayed miRNA from both muscle tissue and blood plasma. We examined how the depth of coverage (the number of mapped reads) changed the number of detectable miRNAs in each sample type. We also found that samples with very low starting amounts of RNA (mouse plasma) made high depth of mature miRNA coverage more difficult to obtain. Each tissue must be assessed independently for the depth of coverage required to adequately power detection of differential expression, weighed against the cost of sequencing that sample to the adequate depth. We explored the changes in total mapped reads and differential expression results generated by three different software packages: miRDeep2, miRNAKey, and miRExpress and two different analysis packages, DESeq and EdgeR. We also examine the accuracy of using miRDeep2 to predict novel miRNAs and subsequently detect them in the samples using qRT-PCR.

Genotyping 1000 yeast strains by next-generation sequencing

Background

The throughput of next-generation sequencing machines has increased dramatically over the last few years; yet the cost and time for library preparation have not changed proportionally, thus representing the main bottleneck for sequencing large numbers of samples. Here we present an economical, high-throughput library preparation method for the Illumina platform, comprising a 96-well based method for DNA isolation for yeast cells, a low-cost DNA shearing alternative, and adapter ligation using heat inactivation of enzymes instead of bead cleanups.

Results

Up to 384 whole-genome libraries can be prepared from yeast cells in one week using this method, for less than 15 euros per sample. We demonstrate the robustness of this protocol by sequencing over 1000 yeast genomes at ~30x coverage. The sequence information from 768 yeast segregants derived from two divergent S. cerevisiae strains was used to generate a meiotic recombination map at unprecedented resolution. Comparisons to other datasets indicate a high conservation of recombination at a chromosome-wide scale, but differences at the local scale. Additionally, we detected a high degree of aneuploidy (3.6%) by examining the sequencing coverage in these segregants. Differences in allele frequency allowed us to attribute instances of aneuploidy to gains of chromosomes during meiosis or mitosis, both of which showed a strong tendency to missegregate specific chromosomes.

Conclusions

Here we present a high throughput workflow to sequence genomes of large number of yeast strains at a low price. We have used this workflow to obtain recombination and aneuploidy data from hundreds of segregants, which can serve as a foundation for future studies of linkage, recombination, and chromosomal aberrations in yeast and higher eukaryotes.

Small RNA expression profiling by high-throughput sequencing: implications of enzymatic manipulation

Eukaryotic regulatory small RNAs (sRNAs) play significant roles in many fundamental cellular processes. As such, they have emerged as useful biomarkers for diseases and cell differentiation states. sRNA-based biomarkers outperform traditional messenger RNA-based biomarkers by testing fewer targets with greater accuracy and providing earlier detection for disease states. Therefore, expression profiling of sRNAs is fundamentally important to further advance the understanding of biological processes, as well as diagnosis and treatment of diseases. High-throughput sequencing (HTS) is a powerful approach for both sRNA discovery and expression profiling. Here, we discuss the general considerations for sRNA-based HTS profiling methods from RNA preparation to sequencing library construction, with a focus on the causes of systematic error. By examining the enzymatic manipulation steps of sRNA expression profiling, this paper aims to demystify current HTS-based sRNA profiling approaches and to aid researchers in the informed design and interpretation of profiling experiments.

Extent, causes, and consequences of small RNA expression variation in human adipose tissue

Small RNAs are functional molecules that modulate mRNA transcripts and have been implicated in the aetiology of several common diseases. However, little is known about the extent of their variability within the human population. Here, we characterise the extent, causes, and effects of naturally occurring variation in expression and sequence of small RNAs from adipose tissue in relation to genotype, gene expression, and metabolic traits in the MuTHER reference cohort. We profiled the expression of 15 to 30 base pair RNA molecules in subcutaneous adipose tissue from 131 individuals using high-throughput sequencing, and quantified levels of 591 microRNAs and small nucleolar RNAs. We identified three genetic variants and three RNA editing events. Highly expressed small RNAs are more conserved within mammals than average, as are those with highly variable expression. We identified 14 genetic loci significantly associated with nearby small RNA expression levels, seven of which also regulate an mRNA transcript level in the same region. In addition, these loci are enriched for variants significant in genome-wide association studies for body mass index. Contrary to expectation, we found no evidence for negative correlation between expression level of a microRNA and its target mRNAs. Trunk fat mass, body mass index, and fasting insulin were associated with more than twenty small RNA expression levels each, while fasting glucose had no significant associations. This study highlights the similar genetic complexity and shared genetic control of small RNA and mRNA transcripts, and gives a quantitative picture of small RNA expression variation in the human population.