Input RNA Research Articles

Abstract C148: Rapid blood-based test for ALK, RET and ROS1 mRNA fusions and somatic variants in NSCLC

Abstract Tissue based methods for the detection of ALK fusions include FISH and IHC. Patients with advanced non-small cell lung cancer (NSCLC) may not be good candidates for biopsies and in cases where tissue is obtained, it is not always sufficient for testing. Additionally, determination of the full range of tumor heterogeneity and any impact of molecular variants on therapeutic responses may not be fully captured by the current FISH and IHC tests being conducted for ALK. For these reasons, blood-based testing that uses PCR and NGS methods for detection of mRNA fusion transcripts and somatic variants in circulation are becoming more clinically relevant. Pre-analytic as well as primer design are critical parameters in the development of circulating RNA tests. We have approached the pre-analytic variables by assessing multiple potential sources of fusion RNAs in prospectively-collected plasma samples, including cell-free RNA (cfRNA) and exosomal RNA. Additionally, test development for ALK, RET and ROS1 (ARR) utilized fusion-partner agnostic primers, only requiring knowledge of the fusion kinase sequence. This test technology has previously been shown in FFPE-extracted mRNA specimens to have the unique capability to identify common fusions, including EML4-ALK variants 1 and 3a/b, as well as rare fusions and novel transcript variants. In this study we have extended the capability of this technology to plasma samples from donors previously diagnosed with NSCLC. Data generated during the development of this test involved extraction of RNA from cell lines and donor plasma, processing to cDNA, adaptor ligation and two-step anchored PCR with specificity for human ALK, RET and ROS1. Amplicons were sequenced on a MiSeq (v2 chemistry) and reads were mapped to the human genome and a fusion specific database in order to identify the specific fusion partner(s). Test turn-around time from RNA extraction to results averaged 72 hours. With this test system we evaluated known variant-positive cell lines for EML4-ALK, SLC34A2-ROS1 and CCDC6-RET, as well as remnant prospectively-collected plasma from NSCLC donors (females of less than 65 years of age, and wild-type for circulating EGFR sensitizing and KRAS somatic variants). All cell lines were positive for the respective fusions (lower limit of input RNA at 25ng) and negative in test cross-reactivity experiments (up to 250ng input RNA). The presence of the fusions in the cell lines were independently confirmed with variant-specific qPCR assays. We additionally tested cell-line spiked human donor samples and successfully demonstrated detection of cell-line derived ARR fusions and donor-derived wild-type ALK, RET & ROS1. All human donor samples passed QC measures based on control gene expression. Ongoing experiments are being conducted to further develop this test and evaluate its relevance for routine blood-based clinical laboratory testing using plasma from patients diagnosed with NSCLC. Citation Format: Hestia Mellert, Kristina Koch, Shannon Campbell, Gary Pestano. Rapid blood-based test for ALK, RET and ROS1 mRNA fusions and somatic variants in NSCLC. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C148.

Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.

BackgroundWhole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs).ResultsUsing published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson’s r = 0.92) and Ion Torrent Proton (Pearson’s r = 0.92). We used ROC, Matthew’s correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations.ConclusionsOur study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2270-1) contains supplementary material, which is available to authorized users.

Reference gene study for forensic body fluid identification

Reference genes are used in forensic body fluid identification studies to normalise data generated during gene expression experiments. The use of reference genes improves the reliability of qRT-PCR. In this study, 10 most common reference genes UCE, TEF, GAPDH, 18S rRNA, ACTB, B2M, B-Actin, OAZ1, RPS 29 and S15 widely used in forensic body fluid identification studies were selected from relevant literature and qPCR efficiency and sensitivity of all the reference genes was tested using SYBR Green detection. Stability was also assayed using samples stored at room temperature for 6 months using Taqman assay probes. All the markers except TEF displayed high sensitivity and were detected down to 25pg of RNA input. Stability study demonstrates that B2M, ACTB, RPS29, and UCE are ideal markers for normalization in forensic body fluid identification studies. The study confirms that reference genes should be selected only upon adequate validation of their suitability.

TARDIS, a targeted RNA directional sequencing method for rare RNA discovery.

High-throughput transcriptional analysis has unveiled a myriad of novel RNAs. However, technical constraints in RNA sequencing library preparation and platform performance hamper the identification of rare transcripts contained within the RNA repertoire. Herein we present targeted-RNA directional sequencing (TARDIS), a hybridization-based method that allows subsets of RNAs contained within the transcriptome to be interrogated independently of transcript length, function, the presence or absence of poly-A tracts, or the mechanism of biogenesis. TARDIS is a modular protocol that is subdivided into four main phases, including the generation of random DNA traps covering the region of interest, purification of input RNA material, DNA trap-based RNA capture, and finally RNA-sequencing library construction. Importantly, coupling RNA capture to strand-specific RNA sequencing enables robust identification and reconstruction of novel transcripts, the definition of sense and antisense RNA pairs and, by the concomitant analysis of long and natural small RNA pools, it allows the user to infer potential precursor-product relations. TARDIS takes ∼10 d to implement.

Identification of sensory hair-cell transcripts by thiouracil-tagging in zebrafish.

BackgroundSensory hair cells are exquisitely sensitive to mechanical stimuli and as such, are prone to damage and apoptosis during dissections or in vitro manipulations. Thiouracil (TU)-tagging is a noninvasive method to label cell type-specific transcripts in an intact organism, thereby meeting the challenge of how to analyze gene expression in hair cells without the need to sort cells. We adapted TU-tagging to zebrafish to identify novel transcripts expressed in the sensory hair cells of the developing acoustico-lateralis organs.MethodsWe created a transgenic line of zebrafish expressing the T.gondii uracil phospho-ribosyltransferase (UPRT) enzyme specifically in the hair cells of the inner ear and lateral line organ. RNA was labeled by exposing 3 days post-fertilization (dpf) UPRT transgenic larvae to 2.5 mM 4-thiouracil (4TU) for 15 hours. Following total RNA isolation, poly(A) mRNA enrichment, and purification of TU-tagged RNA, deep sequencing was performed on the input and TU-tagged RNA samples. ResultsAnalysis of the RNA sequencing data revealed the expression of 28 transcripts that were significantly enriched (adjusted p-value < 0.05) in the UPRT TU-tagged RNA relative to the input sample. Of the 25 TU-tagged transcripts with mammalian homologs, the expression of 18 had not been previously demonstrated in zebrafish hair cells. The hair cell-restricted expression for 17 of these transcripts was confirmed by whole mount mRNA in situ hybridization in 3 dpf larvae.ConclusionsThe hair cell-restricted pattern of expression of these genes offers insight into the biology of this receptor cell type and may serve as useful markers to study the development and function of sensory hair cells. In addition, our study demonstrates the utility of TU-tagging to study nascent transcripts in specific cell types that are relatively rare in the context of the whole zebrafish larvae.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2072-5) contains supplementary material, which is available to authorized users.

Whole transcriptome profiling reveals the RNA content of motor axons.

Most RNAs within polarized cells such as neurons are sorted subcellularly in a coordinated manner. Despite advances in the development of methods for profiling polyadenylated RNAs from small amounts of input RNA, techniques for profiling coding and non-coding RNAs simultaneously are not well established. Here, we optimized a transcriptome profiling method based on double-random priming and applied it to serially diluted total RNA down to 10 pg. Read counts of expressed genes were robustly correlated between replicates, indicating that the method is both reproducible and scalable. Our transcriptome profiling method detected both coding and long non-coding RNAs sized >300 bases. Compared to total RNAseq using a conventional approach our protocol detected 70% more genes due to reduced capture of ribosomal RNAs. We used our method to analyze the RNA composition of compartmentalized motoneurons. The somatodendritic compartment was enriched for transcripts with post-synaptic functions as well as for certain nuclear non-coding RNAs such as 7SK. In axons, transcripts related to translation were enriched including the cytoplasmic non-coding RNA 7SL. Our profiling method can be applied to a wide range of investigations including perturbations of subcellular transcriptomes in neurodegenerative diseases and investigations of microdissected tissue samples such as anatomically defined fiber tracts.

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

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

The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing.

RNA-seq by poly(A) selection is currently the most common protocol for whole transcriptome sequencing as it provides a broad, detailed, and accurate view of the RNA landscape. Unfortunately, the utility of poly(A) libraries is greatly limited when the input RNA is degraded, which is the norm for research tissues and clinical samples, especially when specimens are formalin-fixed. To facilitate the use of RNA sequencing beyond cell lines and in the clinical setting, we developed an exome-capture transcriptome protocol with greatly improved performance on degraded RNA. Capture transcriptome libraries enable measuring absolute and differential gene expression, calling genetic variants, and detecting gene fusions. Through validation against gold-standard poly(A) and Ribo-Zero libraries from intact RNA, we show that capture RNA-seq provides accurate and unbiased estimates of RNA abundance, uniform transcript coverage, and broad dynamic range. Unlike poly(A) selection and Ribo-Zero depletion, capture libraries retain these qualities regardless of RNA quality and provide excellent data from clinical specimens including formalin-fixed paraffin-embedded (FFPE) blocks. Systematic improvements across key applications of RNA-seq are shown on a cohort of prostate cancer patients and a set of clinical FFPE samples. Further, we demonstrate the utility of capture RNA-seq libraries in a patient with a highly malignant solitary fibrous tumor (SFT) enrolled in our clinical sequencing program called MI-ONCOSEQ. Capture transcriptome profiling from FFPE revealed two oncogenic fusions: the pathognomonic NAB2-STAT6 inversion and a therapeutically actionable BRAF fusion, which may drive this specific cancer's aggressive phenotype.

Abstract 4901: Comparison of gene expression platforms: RNA-Seq, Fluidigm, and Nanostring

Abstract Accurately measuring the expression of genes in formalin-fixed paraffin embedded (FFPE) tumor tissues has long been a struggle due to the inherent degradation of RNA isolated from these materials. Accurate quantification of gene expression levels in FFPE samples can enable the testing of biomarker hypotheses in the clinic and can potentially be used for patient stratification or selection in clinical trials. Platforms such as Fluidigm, Nanostring and microarrays are currently the high-throughput technologies utilized. Each of these platforms has different drawbacks and challenges such as lack of sensitivity, reproducibility or dynamic range when working with degraded FFPE samples. Currently, whole transcriptome RNA sequencing (RNA-Seq) is the only platform that offers a truly high-throughput, sensitive, and reproducible method to accurately quantify mRNA levels in RNA derived from FFPE samples. RNA-Seq, however has not yet been widely evaluated and adapted for use with degraded FFPE samples. Here we report the direct comparison of whole transcriptome RNA-Seq with two platforms that are currently compatible with FFPE derived RNA, Fluidigm and Nanostring, to determine the accuracy and feasibility of using this technology on degraded RNA. Utilizing a collection of matched fresh frozen (FF) and FFPE samples we analyzed gene expression using all three platforms to allow for a direct evaluation of each technology. By comparing the results to the matching FF sample, we were able to determine the accuracy and sensitivity of each platform when using degraded FFPE derived RNA. By titrating down the input of FFPE RNA into the RNA-Seq library prep we were also able to define the optimal input of FFPE RNA needed to accurately and reproducibly quantify gene expression. This work allows for a systematic comparison of different gene expression platforms for their use with degraded FFPE RNA. Citation Format: Erica B. Schleifman, Maipelo Motlhabi, Craig Cummings, Rin Nakamura, Linda Bosch, Rajesh Patel, An Do, Andrew Watson, Thomas Sandmann, Walter Darbonne, Ian McCaffery, Eric Peters, Rajiv Raja. Comparison of gene expression platforms: RNA-Seq, Fluidigm, and Nanostring. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4901. doi:10.1158/1538-7445.AM2015-4901

Abstract 4750: Transcriptome sequencing of the Reed-Sternberg cells of classical Hodgkin lymphoma

Abstract Introduction: Most genomic studies of classical Hodgkin lymphoma (cHL) have been confined to cell lines due to the difficulty of isolating sparsely distributed Hodgkin and Reed-Sternberg (HRS) cells from reactive background tissue. One approach to evaluate primary cases has been to microdissect HRS cells from fresh-frozen tissue biopsies, which has been used for gene expression profiling and array comparative genomic hybridization to assess copy number alterations. However, laser capture microdissection is technically challenging, does not provide a pure tumor cell population, and yields very small amounts of degraded nucleic acids that may not be adequate for whole-transcriptome level RNA sequencing. Methods: We used a flow cytometric cell isolation method, which has enabled rapid isolation of thousands of viable HRS cells from primary cHL tumors (Fromm, et al., Am J Clin Pathol 126, 2006). Here we combined flow cytometry using CD64, CD95, CD30, CD5, CD20, CD15, CD40, and CD45, with the Arcturus PicoPure RNA Isolation kit to isolate high quality RNA from viable HRS cells and intratumor B cells from nine primary cases of CHL respectively. We applied the Clontech SMARTer Ultra Low Input RNA Kit followed by Kapa Library Preparation kit to generate what is to our knowledge the first full transcriptome RNA sequence data from primary cases of cHL. Four cell lines were sequenced using the same methodology. We performed differential expression and gene fusion analyses, and conducted a search for activated pathways. Results: We report the expression signature of purified primary HRS cells. PCA analysis showed that these segregate from HRS cell lines and primary B cells. We confirmed at the RNA level overexpression of relevant amplified genes for which inhibitors are available (AURKA and EZH2), and underexpression of transcripts encoded by genes previously found to be deleted (for example ATM). Pathway analysis revealed extensive downregulation of antigen presentation, consistent with our previous exome sequence analysis showing mutations in beta-2 microglobulin as the most common genetic alteration. Results of the mutational and transcriptional landscape of the HRS cells will be presented. Conclusions: Transcriptome-level analysis of flow-sorted HRS cells allows for expanded study of CHL pathogenesis, new target identification based on altered signaling pathways and potentially individualized approaches to CHL therapy. Citation Format: Jonathan Reichel, Joshua Brody, Olivier Elemento, Raul Rabadan, Ethel Cesarman. Transcriptome sequencing of the Reed-Sternberg cells of classical Hodgkin lymphoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4750. doi:10.1158/1538-7445.AM2015-4750

Differential Expression of microRNA in Cerebrospinal Fluid as a Potential Novel Biomarker for Alzheimer’s Disease

The need to find a better reflection of Alzheimer's disease (AD) pathophysiology led us to investigate differential expression of microRNA (miRNA) in cerebrospinal fluid (CSF) of AD patients compared to matched controls, using a genome-wide data-driven approach. From the Amsterdam Dementia Cohort, we selected 19 AD patients with CSF indicative of AD pathophysiology and 19 age and gender-matched controls without CSF evidence of AD (67 ± 6 years old, 20 [53%] female). We measured 754 miRNA in CSF using qRT-PCR (Taqman Array MicroRNA cards A and B, v3.0) according to the Megaplex Taqman protocol. Hierarchical cluster analysis was performed and groups were compared using Linear Models for Microarray Data, a modified t-test. We performed validation analysis using qRT-PCR single assays. 144 ± 66 miRNA could be detected using Megaplex array analysis (19% ). Mean Ct (average 32.4 ± 0.5) was correlated to age (r = 0.52, p = 0.001). Five miRNA were differentially expressed in CSF of AD patients. None of these could be replicated. After stratification by age, seven miRNA showed differential expression in late-onset AD, of which lower abundance of let-7a was replicated (log10RQ -1.46, p < 0.05). In early-onset AD, twelve miRNA were differentially expressed of which lower abundance of miRNA-532-3p remained borderline significant (log10RQ -1.27, p = 0.05). Although we could not consistently separate AD patients and controls in the whole group, we have found indications miRNA in CSF are able to reflect aging and perhaps also heterogeneity in AD. Further investigation requires optimizing RNA input, while maintaining strict age matching.

Pathogen transcriptional profile in nasopharyngeal aspirates of children with acute respiratory tract infection

BackgroundAcute respiratory tract infections (ARI) present a significant morbidity and pose a global health burden. Patients are frequently treated with antibiotics although ARI are most commonly caused by virus, strengthening the need for improved diagnostic methods. ObjectivesDetect viral and bacterial RNA in nasopharyngeal aspirates (NPA) from children aged 6–23 months with ARI using nCounter. Study designA custom-designed nCounter probeset containing viral and bacterial targets was tested in NPA of ARI patients. ResultsInitially, spiked control viral RNAs were detectable in ≥6.25ng input RNA, indicating absence of inhibitors in NPA. nCounter applied to a larger NPA sample (n=61) enabled the multiplex detection of different pathogens: RNA viruses Parainfluenza virus (PIV 1–3) and RSV A-B in 21%, Human metapneumovirus (hMPV) in 5%, Bocavirus (BoV), CoV, Influenza virus (IV) A in 3% and, Rhinovirus (RV) in 2% of samples, respectively. RSV A-B was confirmed by Real Time PCR (86.2–96.9% agreement). DNA virus (AV) was detected at RNA level, reflecting viral replication, in 10% of samples. Bacterial transcripts from Staphylococcus aureus, Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, Mycoplasma pneumoniae and Chlamydophila pneumoniae were detected in 77, 69, 26, 8, 3 and 2% of samples, respectively. ConclusionnCounter is robust and sensitive for the simultaneous detection of viral (both RNA and DNA) and bacterial transcripts in NPA with low RNA input (<10ng). This medium-throughput technique will increase our understanding of ARI pathogenesis and may provide an evidence-based approach for the targeted and rational use of antibiotics in pediatric ARI.

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

BackgroundRNA-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.ResultsDifferent 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.ConclusionData, 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.

BrAD-seq: Breath Adapter Directional sequencing: a streamlined, ultra-simple and fast library preparation protocol for strand specific mRNA library construction.

Next Generation Sequencing (NGS) is driving rapid advancement in biological understanding and RNA-sequencing (RNA-seq) has become an indispensable tool for biology and medicine. There is a growing need for access to these technologies although preparation of NGS libraries remains a bottleneck to wider adoption. Here we report a novel method for the production of strand specific RNA-seq libraries utilizing the terminal breathing of double-stranded cDNA to capture and incorporate a sequencing adapter. Breath Adapter Directional sequencing (BrAD-seq) reduces sample handling and requires far fewer enzymatic steps than most available methods to produce high quality strand-specific RNA-seq libraries. The method we present is optimized for 3-prime Digital Gene Expression (DGE) libraries and can easily extend to full transcript coverage shotgun (SHO) type strand-specific libraries and is modularized to accommodate a diversity of RNA and DNA input materials. BrAD-seq offers a highly streamlined and inexpensive option for RNA-seq libraries.

QmRLFS-finder: a model, web server and stand-alone tool for prediction and analysis of R-loop forming sequences.

The possible formation of three-stranded RNA and DNA hybrid structures (R-loops) in thousands of functionally important guanine-rich genic and inter-genic regions could suggest their involvement in transcriptional regulation and even development of diseases. Here, we introduce the first freely available R-loop prediction program called Quantitative Model of R-loop Forming Sequence (RLFS) finder (QmRLFS-finder), which predicts RLFSs in nucleic acid sequences based on experimentally supported structural models of RLFSs. QmRLFS-finder operates via a web server or a stand-alone command line tool. This tool identifies and visualizes RLFS coordinates from any natural or artificial DNA or RNA input sequences and creates standards-compliant output files for further annotation and analysis. QmRLFS-finder demonstrates highly accurate predictions of the detected RLFSs, proposing new perspective to further discoveries in R-loop biology, biotechnology and molecular therapy. QmRLFS-finder is freely available at http://rloop.bii.a-star.edu.sg/?pg=qmrlfs-finder.

Spermatozoa input concentrations and RNA isolation methods on RNA yield and quality in bull (Bos taurus)

Sperm RNA can be used to understand the past spermatogenic process, future successful fertilization, and embryo development. To study the sperm RNA composition and function, isolation of good quality RNA with sufficient quantity is essential. The objective of this study was to assess the influence of sperm input concentrations and RNA isolation methods on RNA yield and quality in bull sperm. The fresh semen samples from bulls (n=6) were snap-frozen in liquid nitrogen and stored at −80°C. The sperm RNA was isolated using membrane-based methods combined with TRIzol (RNeasy+TRIzol and PureLink+TRIzol) and conventional methods (TRIzol, Double TRIzol, and RNAzol RT). Based on fluorometric quantification, combined methods resulted in significantly (P<0.05) higher total RNA yields (800–900ng/30–40×106) as compared with other methods and yielded 20 to 30fg of RNA/spermatozoon. The quality of RNA isolated by membrane-based methods was superior to that isolated by conventional methods. The sperm RNA was observed to be intact as well as fragmented (50–2000bp). The study revealed that the membrane-based methods with a cocktail of lysis solution and an optimal input concentration of 30 to 40million sperm were optimal for maximum recovery of RNA from bull spermatozoa.

Analytical validation of a melanoma diagnostic gene signature using formalin-fixed paraffin-embedded melanocytic lesions.

These studies were to validate the analytical performance of a gene expression signature that differentiates melanoma and nevi, using RNA expression from 14 signature genes and nine normalization genes that generates a melanoma diagnostic score (MDS). Formalin-fixed paraffin-embedded melanocytic lesions were evaluated in these studies. The overall SD of the assay was determined to be 0.69 MDS units. Individual amplicons within the signature had an average amplification efficiency of 92% and a SD less than 0.5 CT. The MDS was reproducible across a 2000-fold dilution range of input RNA. Melanin, an inhibitor of PCR, does not interfere with the signature. These studies indicate this signature is robust and reproducible and is analytically validated on formalin-fixed paraffin-embedded melanocytic lesions.

Intramolecular circularization increases efficiency of RNA sequencing and enables CLIP-Seq of nuclear RNA from human cells.

RNA sequencing (RNA-Seq) is a powerful tool for analyzing the identity of cellular RNAs but is often limited by the amount of material available for analysis. In spite of extensive efforts employing existing protocols, we observed that it was not possible to obtain useful sequencing libraries from nuclear RNA derived from cultured human cells after crosslinking and immunoprecipitation (CLIP). Here, we report a method for obtaining strand-specific small RNA libraries for RNA sequencing that requires picograms of RNA. We employ an intramolecular circularization step that increases the efficiency of library preparation and avoids the need for intermolecular ligations of adaptor sequences. Other key features include random priming for full-length cDNA synthesis and gel-free library purification. Using our method, we generated CLIP-Seq libraries from nuclear RNA that had been UV-crosslinked and immunoprecipitated with anti-Argonaute 2 (Ago2) antibody. Computational protocols were developed to enable analysis of raw sequencing data and we observe substantial differences between recognition by Ago2 of RNA species in the nucleus relative to the cytoplasm. This RNA self-circularization approach to RNA sequencing (RC-Seq) allows data to be obtained using small amounts of input RNA that cannot be sequenced by standard methods.

Identification of suitable reference genes for gene expression studies using quantitative polymerase chain reaction in lung cancer in vitro.

The present study aimed to examine 10 housekeeping genes (HKGs), including 18s ribosomal RNA (18S), glyceraldehyde‑3‑phosphate dehydrogenase (GAPDH), ribosomal protein large P0 (RPLP0), β‑actin (ACTB), peptidylprolyl isomerase A (PPIA), phosphoglycerate kinase‑1 (PGK1), β‑2‑microglobulin (B2M), ribosomal protein LI3a (RPL13A), hypoxanthine phosphoribosyl transferase‑1 (HPRT1) and TATA box binding protein (TBP) in order to identify the most stable and suitable reference genes for use in expression studies in non‑small cell lung cancer. The mRNA expression encoding the panel of the 10 HKGs was determined using reverse transcription‑quantitative PCR (RT‑qPCR) in human lung cancer cell lines. Three software programs, BestKeeper, NormFinder and geNorm, were used to ascertain the most suitable reference genes to normalize the RNA input. The present study examined three lung cancer cell lines (A549, NCI‑H446 and NCI‑H460). The analysis of the experimental data using BestKeeper software revealed that all 10 HKGs were stable, with GADPH, followed by 18S being the most stable genes and PPIA and HPRT1 being the least stable genes. The NormFinder software results demonstrated that PPIA followed by ACTB were the most stable and B2M and RPLP0 were the least stable. The geNorm software results revealed that ACTB and PGK1, followed by PPIA were the most stable genes and B2M and RPLP0 were identified as the least stable genes. Due to discrepancies in the ranking orders of the reference genes obtained by different analyzing software programs, it was not possible to determine a single universal reference gene. The suitability of selected reference genes requires unconditional validation prior to each study. Based on the three analyzing programs, ACTB, PPIA and PGK1 were the most stable reference genes in lung cancer cell lines.

Sensitive and multiplexed on-chip microRNA profiling in oil-isolated hydrogel chambers.

Although microRNAs (miRNAs) have been shown to be excellent indicators of disease state, current profiling platforms are insufficient for clinical translation. Here, we demonstrate a versatile hydrogel-based microfluidic approach and novel amplification scheme for entirely on-chip, sensitive, and highly specific miRNA detection without the risk of sequence bias. A simulation-driven approach is used to engineer the hydrogel geometry and the gel-reaction environment is chemically optimized for robust detection performance. The assay provides 22.6 fM sensitivity over a three log range, demonstrates multiplexing across at least four targets, and requires just 10.3 ng of total RNA input in a 2 hour and 15 minutes assay.