A deep learning method for lincRNA detection using auto-encoder algorithm.

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly annotated lincRNA data, deep learning methods based on auto-encoder algorithm can exert their capability in knowledge learning in order to capture the useful features and the information correlation along DNA genome sequences for lincRNA detection. As our knowledge, this is the first application to adopt the deep learning techniques for identifying lincRNA transcription sequences.

Ariadne: a database search engine for identification and chemical analysis of RNA using tandem mass spectrometry data.

PubMed

Nakayama, Hiroshi; Akiyama, Misaki; Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-04-01

We present here a method to correlate tandem mass spectra of sample RNA nucleolytic fragments with an RNA nucleotide sequence in a DNA/RNA sequence database, thereby allowing tandem mass spectrometry (MS/MS)-based identification of RNA in biological samples. Ariadne, a unique web-based database search engine, identifies RNA by two probability-based evaluation steps of MS/MS data. In the first step, the software evaluates the matches between the masses of product ions generated by MS/MS of an RNase digest of sample RNA and those calculated from a candidate nucleotide sequence in a DNA/RNA sequence database, which then predicts the nucleotide sequences of these RNase fragments. In the second step, the candidate sequences are mapped for all RNA entries in the database, and each entry is scored for a function of occurrences of the candidate sequences to identify a particular RNA. Ariadne can also predict post-transcriptional modifications of RNA, such as methylation of nucleotide bases and/or ribose, by estimating mass shifts from the theoretical mass values. The method was validated with MS/MS data of RNase T1 digests of in vitro transcripts. It was applied successfully to identify an unknown RNA component in a tRNA mixture and to analyze post-transcriptional modification in yeast tRNA(Phe-1).

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

PubMed

Brown, Roger B; Madrid, Nathaniel J; Suzuki, Hideaki; Ness, Scott A

2017-01-01

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

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

PubMed Central

Li, Jun; Tibshirani, Robert

2015-01-01

We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ‘sequencing depths’. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ‘outliers’ in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. PMID:22127579

Evaluation of normalization methods in mammalian microRNA-Seq data

PubMed Central

Garmire, Lana Xia; Subramaniam, Shankar

2012-01-01

Simple total tag count normalization is inadequate for microRNA sequencing data generated from the next generation sequencing technology. However, so far systematic evaluation of normalization methods on microRNA sequencing data is lacking. We comprehensively evaluate seven commonly used normalization methods including global normalization, Lowess normalization, Trimmed Mean Method (TMM), quantile normalization, scaling normalization, variance stabilization, and invariant method. We assess these methods on two individual experimental data sets with the empirical statistical metrics of mean square error (MSE) and Kolmogorov-Smirnov (K-S) statistic. Additionally, we evaluate the methods with results from quantitative PCR validation. Our results consistently show that Lowess normalization and quantile normalization perform the best, whereas TMM, a method applied to the RNA-Sequencing normalization, performs the worst. The poor performance of TMM normalization is further evidenced by abnormal results from the test of differential expression (DE) of microRNA-Seq data. Comparing with the models used for DE, the choice of normalization method is the primary factor that affects the results of DE. In summary, Lowess normalization and quantile normalization are recommended for normalizing microRNA-Seq data, whereas the TMM method should be used with caution. PMID:22532701

Free energy minimization to predict RNA secondary structures and computational RNA design.

PubMed

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

SELEX-Based Screening of Exosome-Tropic RNA.

PubMed

Yamashita, Takuma; Shinotsuka, Haruka; Takahashi, Yuki; Kato, Kana; Nishikawa, Makiya; Takakura, Yoshinobu

2017-01-01

Cell-derived nanosized vesicles or exosomes are expected to become delivery carriers for functional RNAs, such as small interfering RNA (siRNA). A method to efficiently load functional RNAs into exosomes is required for the development of exosome-based delivery carriers of functional RNAs. However, there is no method to find exosome-tropic exogenous RNA sequences. In this study, we used a systematic evolution of ligands by exponential enrichment (SELEX) method to screen exosome-tropic RNAs that can be used to load functional RNAs into exosomes by conjugation. Pooled single stranded 80-base RNAs, each of which contains a randomized 40-base sequence, were transfected into B16-BL6 murine melanoma cells and exosomes were collected from the cells. RNAs extracted from the exosomes were subjected to next round of SELEX. Cloning and sequencing of RNAs in SELEX-screened RNA pools showed that 29 of 56 clones had a typical RNA sequence. The sequence found by SELEX was enriched in exosomes after transfection to B16-BL6 cells. The results show that the SELEX-based method can be used for screening of exosome-tropic RNAs.

Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods.

PubMed

Dal Molin, Alessandra; Baruzzo, Giacomo; Di Camillo, Barbara

2017-01-01

The sequencing of the transcriptomes of single-cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types and for the study of stochastic gene expression. In recent years, various tools for analyzing single-cell RNA-sequencing data have been proposed, many of them with the purpose of performing differentially expression analysis. In this work, we compare four different tools for single-cell RNA-sequencing differential expression, together with two popular methods originally developed for the analysis of bulk RNA-sequencing data, but largely applied to single-cell data. We discuss results obtained on two real and one synthetic dataset, along with considerations about the perspectives of single-cell differential expression analysis. In particular, we explore the methods performance in four different scenarios, mimicking different unimodal or bimodal distributions of the data, as characteristic of single-cell transcriptomics. We observed marked differences between the selected methods in terms of precision and recall, the number of detected differentially expressed genes and the overall performance. Globally, the results obtained in our study suggest that is difficult to identify a best performing tool and that efforts are needed to improve the methodologies for single-cell RNA-sequencing data analysis and gain better accuracy of results.

Predicting protein-binding RNA nucleotides with consideration of binding partners.

PubMed

Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in most performance measures. To the best of our knowledge, this is the first sequence-based prediction of protein-binding nucleotides in RNA which considers the binding partner of RNA. The new model will provide valuable information for designing biochemical experiments to find putative protein-binding sites in RNA with unknown structure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

Townsley, Brad T; Covington, Michael F; Ichihashi, Yasunori; Zumstein, Kristina; Sinha, Neelima R

2015-01-01

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.

Comprehensive discovery of noncoding RNAs in acute myeloid leukemia cell transcriptomes.

PubMed

Zhang, Jin; Griffith, Malachi; Miller, Christopher A; Griffith, Obi L; Spencer, David H; Walker, Jason R; Magrini, Vincent; McGrath, Sean D; Ly, Amy; Helton, Nichole M; Trissal, Maria; Link, Daniel C; Dang, Ha X; Larson, David E; Kulkarni, Shashikant; Cordes, Matthew G; Fronick, Catrina C; Fulton, Robert S; Klco, Jeffery M; Mardis, Elaine R; Ley, Timothy J; Wilson, Richard K; Maher, Christopher A

2017-11-01

To detect diverse and novel RNA species comprehensively, we compared deep small RNA and RNA sequencing (RNA-seq) methods applied to a primary acute myeloid leukemia (AML) sample. We were able to discover previously unannotated small RNAs using deep sequencing of a library method using broader insert size selection. We analyzed the long noncoding RNA (lncRNA) landscape in AML by comparing deep sequencing from multiple RNA-seq library construction methods for the sample that we studied and then integrating RNA-seq data from 179 AML cases. This identified lncRNAs that are completely novel, differentially expressed, and associated with specific AML subtypes. Our study revealed the complexity of the noncoding RNA transcriptome through a combined strategy of strand-specific small RNA and total RNA-seq. This dataset will serve as an invaluable resource for future RNA-based analyses. Copyright © 2017 ISEH – Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

The bench scientist's guide to RNA-Seq analysis

USDA-ARS?s Scientific Manuscript database

RNA sequencing (RNA-Seq) is emerging as a highly accurate method to quantify transcript abundance. However, analyses of the large data sets obtained by sequencing the entire transcriptome of organisms have generally been performed by bioinformatic specialists. Here we outline a methods strategy desi...

Simultaneous sequencing of coding and noncoding RNA reveals a human transcriptome dominated by a small number of highly expressed noncoding genes.

PubMed

Boivin, Vincent; Deschamps-Francoeur, Gabrielle; Couture, Sonia; Nottingham, Ryan M; Bouchard-Bourelle, Philia; Lambowitz, Alan M; Scott, Michelle S; Abou-Elela, Sherif

2018-07-01

Comparing the abundance of one RNA molecule to another is crucial for understanding cellular functions but most sequencing techniques can target only specific subsets of RNA. In this study, we used a new fragmented ribodepleted TGIRT sequencing method that uses a thermostable group II intron reverse transcriptase (TGIRT) to generate a portrait of the human transcriptome depicting the quantitative relationship of all classes of nonribosomal RNA longer than 60 nt. Comparison between different sequencing methods indicated that FRT is more accurate in ranking both mRNA and noncoding RNA than viral reverse transcriptase-based sequencing methods, even those that specifically target these species. Measurements of RNA abundance in different cell lines using this method correlate with biochemical estimates, confirming tRNA as the most abundant nonribosomal RNA biotype. However, the single most abundant transcript is 7SL RNA, a component of the signal recognition particle. S tructured n on c oding RNAs (sncRNAs) associated with the same biological process are expressed at similar levels, with the exception of RNAs with multiple functions like U1 snRNA. In general, sncRNAs forming RNPs are hundreds to thousands of times more abundant than their mRNA counterparts. Surprisingly, only 50 sncRNA genes produce half of the non-rRNA transcripts detected in two different cell lines. Together the results indicate that the human transcriptome is dominated by a small number of highly expressed sncRNAs specializing in functions related to translation and splicing. © 2018 Boivin et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

An Accurate Scalable Template-based Alignment Algorithm

PubMed Central

Gardner, David P.; Xu, Weijia; Miranker, Daniel P.; Ozer, Stuart; Cannone, Jamie J.; Gutell, Robin R.

2013-01-01

The rapid determination of nucleic acid sequences is increasing the number of sequences that are available. Inherent in a template or seed alignment is the culmination of structural and functional constraints that are selecting those mutations that are viable during the evolution of the RNA. While we might not understand these structural and functional, template-based alignment programs utilize the patterns of sequence conservation to encapsulate the characteristics of viable RNA sequences that are aligned properly. We have developed a program that utilizes the different dimensions of information in rCAD, a large RNA informatics resource, to establish a profile for each position in an alignment. The most significant include sequence identity and column composition in different phylogenetic taxa. We have compared our methods with a maximum of eight alternative alignment methods on different sets of 16S and 23S rRNA sequences with sequence percent identities ranging from 50% to 100%. The results showed that CRWAlign outperformed the other alignment methods in both speed and accuracy. A web-based alignment server is available at http://www.rna.ccbb.utexas.edu/SAE/2F/CRWAlign. PMID:24772376

Comparison of 16S rRNA sequencing with biochemical testing for species-level identification of clinical isolates of Neisseria spp.

PubMed

Mechergui, Arij; Achour, Wafa; Ben Hassen, Assia

2014-08-01

We aimed to compare accuracy of genus and species level identification of Neisseria spp. using biochemical testing and 16S rRNA sequence analysis. These methods were evaluated using 85 Neisseria spp. clinical isolates initially identified to the genus level by conventional biochemical tests and API NH system (Bio-Mérieux(®)). In 34 % (29/85), more than one possibility was given by 16S rRNA sequence analysis. In 6 % (5/85), one of the possibilities offered by 16S rRNA gene sequencing, agreed with the result given by biochemical testing. In 4 % (3/85), the same species was given by both methods. 16S rRNA gene sequencing results did not correlate well with biochemical tests.

Methods and compositions for controlling gene expression by RNA processing

DOEpatents

Doudna, Jennifer A.; Qi, Lei S.; Haurwitz, Rachel E.; Arkin, Adam P.

2017-08-29

The present disclosure provides nucleic acids encoding an RNA recognition sequence positioned proximal to an insertion site for the insertion of a sequence of interest; and host cells genetically modified with the nucleic acids. The present disclosure also provides methods of modifying the activity of a target RNA, and kits and compositions for carrying out the methods.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

PubMed

Polishchuk, Maya; Paz, Inbal; Yakhini, Zohar; Mandel-Gutfreund, Yael

2018-05-25

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptases

PubMed Central

Qin, Yidan; Yao, Jun; Wu, Douglas C.; Nottingham, Ryan M.; Mohr, Sabine; Hunicke-Smith, Scott; Lambowitz, Alan M.

2016-01-01

Next-generation RNA-sequencing (RNA-seq) has revolutionized transcriptome profiling, gene expression analysis, and RNA-based diagnostics. Here, we developed a new RNA-seq method that exploits thermostable group II intron reverse transcriptases (TGIRTs) and used it to profile human plasma RNAs. TGIRTs have higher thermostability, processivity, and fidelity than conventional reverse transcriptases, plus a novel template-switching activity that can efficiently attach RNA-seq adapters to target RNA sequences without RNA ligation. The new TGIRT-seq method enabled construction of RNA-seq libraries from <1 ng of plasma RNA in <5 h. TGIRT-seq of RNA in 1-mL plasma samples from a healthy individual revealed RNA fragments mapping to a diverse population of protein-coding gene and long ncRNAs, which are enriched in intron and antisense sequences, as well as nearly all known classes of small ncRNAs, some of which have never before been seen in plasma. Surprisingly, many of the small ncRNA species were present as full-length transcripts, suggesting that they are protected from plasma RNases in ribonucleoprotein (RNP) complexes and/or exosomes. This TGIRT-seq method is readily adaptable for profiling of whole-cell, exosomal, and miRNAs, and for related procedures, such as HITS-CLIP and ribosome profiling. PMID:26554030

DNA and RNA sequencing by nanoscale reading through programmable electrophoresis and nanoelectrode-gated tunneling and dielectric detection

DOEpatents

Lee, James W.; Thundat, Thomas G.

2005-06-14

An apparatus and method for performing nucleic acid (DNA and/or RNA) sequencing on a single molecule. The genetic sequence information is obtained by probing through a DNA or RNA molecule base by base at nanometer scale as though looking through a strip of movie film. This DNA sequencing nanotechnology has the theoretical capability of performing DNA sequencing at a maximal rate of about 1,000,000 bases per second. This enhanced performance is made possible by a series of innovations including: novel applications of a fine-tuned nanometer gap for passage of a single DNA or RNA molecule; thin layer microfluidics for sample loading and delivery; and programmable electric fields for precise control of DNA or RNA movement. Detection methods include nanoelectrode-gated tunneling current measurements, dielectric molecular characterization, and atomic force microscopy/electrostatic force microscopy (AFM/EFM) probing for nanoscale reading of the nucleic acid sequences.

Sequencing RNA by a combination of exonuclease digestion and uridine specific chemical cleavage using MALDI-TOF.

PubMed Central

Tolson, D A; Nicholson, N H

1998-01-01

The determination of DNA sequences by partial exonuclease digestion followed by Matrix-Assisted Laser Desorption Time of Flight Mass Spectrometry (MALDI-TOF) is a well established method. When the same procedure is applied to RNA, difficulties arise due to the small (1 Da) mass difference between the nucleotides U and C, which makes unambiguous assignment difficult using a MALDI-TOF instrument. Here we report our experiences with sequence specific endonucleases and chemical methods followed by MALDI-TOF to resolve these sequence ambiguities. We have found chemical methods superior to endonucleases both in terms of correct specificity and extent of sequence coverage. This methodology can be used in combination with exonuclease digestion to rapidly assign RNA sequences. PMID:9421498

Identification of extracellular miRNA in archived serum samples by next-generation sequencing from RNA extracted using multiple methods.

PubMed

Gautam, Aarti; Kumar, Raina; Dimitrov, George; Hoke, Allison; Hammamieh, Rasha; Jett, Marti

2016-10-01

miRNAs act as important regulators of gene expression by promoting mRNA degradation or by attenuating protein translation. Since miRNAs are stably expressed in bodily fluids, there is growing interest in profiling these miRNAs, as it is minimally invasive and cost-effective as a diagnostic matrix. A technical hurdle in studying miRNA dynamics is the ability to reliably extract miRNA as small sample volumes and low RNA abundance create challenges for extraction and downstream applications. The purpose of this study was to develop a pipeline for the recovery of miRNA using small volumes of archived serum samples. The RNA was extracted employing several widely utilized RNA isolation kits/methods with and without addition of a carrier. The small RNA library preparation was carried out using Illumina TruSeq small RNA kit and sequencing was carried out using Illumina platform. A fraction of five microliters of total RNA was used for library preparation as quantification is below the detection limit. We were able to profile miRNA levels in serum from all the methods tested. We found out that addition of nucleic acid based carrier molecules had higher numbers of processed reads but it did not enhance the mapping of any miRBase annotated sequences. However, some of the extraction procedures offer certain advantages: RNA extracted by TRIzol seemed to align to the miRBase best; extractions using TRIzol with carrier yielded higher miRNA-to-small RNA ratios. Nuclease free glycogen can be carrier of choice for miRNA sequencing. Our findings illustrate that miRNA extraction and quantification is influenced by the choice of methodologies. Addition of nucleic acid- based carrier molecules during extraction procedure is not a good choice when assaying miRNA using sequencing. The careful selection of an extraction method permits the archived serum samples to become valuable resources for high-throughput applications.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy

PubMed Central

Matkovich, Scot J.; Dorn, Gerald W.

2018-01-01

Summary MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicates purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses. PMID:25836573

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

PubMed

Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

Structator: fast index-based search for RNA sequence-structure patterns

PubMed Central

2011-01-01

Background The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs. Results We present a novel method and readily applicable software for time efficient matching of RNA sequence-structure patterns in sequence databases. Our approach is based on affix arrays, a recently introduced index data structure, preprocessed from the target database. Affix arrays support bidirectional pattern search, which is required for efficiently handling the structural constraints of the pattern. Structural patterns like stem-loops can be matched inside out, such that the loop region is matched first and then the pairing bases on the boundaries are matched consecutively. This allows to exploit base pairing information for search space reduction and leads to an expected running time that is sublinear in the size of the sequence database. The incorporation of a new chaining approach in the search of RNA sequence-structure patterns enables the description of molecules folding into complex secondary structures with multiple ordered patterns. The chaining approach removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our method runs up to two orders of magnitude faster than previous methods. Conclusions The presented method's sublinear expected running time makes it well suited for RNA sequence-structure pattern matching in large sequence databases. RNA molecules containing several stem-loop substructures can be described by multiple sequence-structure patterns and their matches are efficiently handled by a novel chaining method. Beyond our algorithmic contributions, we provide with Structator a complete and robust open-source software solution for index-based search of RNA sequence-structure patterns. The Structator software is available at http://www.zbh.uni-hamburg.de/Structator. PMID:21619640

Selective amplification and sequencing of cyclic phosphate-containing RNAs by the cP-RNA-seq method.

PubMed

Honda, Shozo; Morichika, Keisuke; Kirino, Yohei

2016-03-01

RNA digestions catalyzed by many ribonucleases generate RNA fragments that contain a 2',3'-cyclic phosphate (cP) at their 3' termini. However, standard RNA-seq methods are unable to accurately capture cP-containing RNAs because the cP inhibits the adapter ligation reaction. We recently developed a method named cP-RNA-seq that is able to selectively amplify and sequence cP-containing RNAs. Here we describe the cP-RNA-seq protocol in which the 3' termini of all RNAs, except those containing a cP, are cleaved through a periodate treatment after phosphatase treatment; hence, subsequent adapter ligation and cDNA amplification steps are exclusively applied to cP-containing RNAs. cP-RNA-seq takes ∼6 d, excluding the time required for sequencing and bioinformatics analyses, which are not covered in detail in this protocol. Biochemical validation of the existence of cP in the identified RNAs takes ∼3 d. Even though the cP-RNA-seq method was developed to identify angiogenin-generating 5'-tRNA halves as a proof of principle, the method should be applicable to global identification of cP-containing RNA repertoires in various transcriptomes.

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA-seq is typically performed in "bulk," and the data represent an average of gene expression patterns across thousands to millions of cells; this might obscure biologically relevant differences between cells. Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.

PubMed

Bauer, Markus; Klau, Gunnar W; Reinert, Knut

2007-07-27

The discovery of functional non-coding RNA sequences has led to an increasing interest in algorithms related to RNA analysis. Traditional sequence alignment algorithms, however, fail at computing reliable alignments of low-homology RNA sequences. The spatial conformation of RNA sequences largely determines their function, and therefore RNA alignment algorithms have to take structural information into account. We present a graph-based representation for sequence-structure alignments, which we model as an integer linear program (ILP). We sketch how we compute an optimal or near-optimal solution to the ILP using methods from combinatorial optimization, and present results on a recently published benchmark set for RNA alignments. The implementation of our algorithm yields better alignments in terms of two published scores than the other programs that we tested: This is especially the case with an increasing number of input sequences. Our program LARA is freely available for academic purposes from http://www.planet-lisa.net.

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

High-Throughput, Data-Rich Cellular RNA Device Engineering

PubMed Central

Townshend, Brent; Kennedy, Andrew B.; Xiang, Joy S.; Smolke, Christina D.

2015-01-01

Methods for rapidly assessing sequence-structure-function landscapes and developing conditional gene-regulatory devices are critical to our ability to manipulate and interface with biology. We describe a framework for engineering RNA devices from preexisting aptamers that exhibit ligand-responsive ribozyme tertiary interactions. Our methodology utilizes cell sorting, high-throughput sequencing, and statistical data analyses to enable parallel measurements of the activities of hundreds of thousands of sequences from RNA device libraries in the absence and presence of ligands. Our tertiary interaction RNA devices exhibit improved performance in terms of gene silencing, activation ratio, and ligand sensitivity as compared to optimized RNA devices that rely on secondary structure changes. We apply our method to building biosensors for diverse ligands and determine consensus sequences that enable ligand-responsive tertiary interactions. These methods advance our ability to develop broadly applicable genetic tools and to elucidate understanding of the underlying sequence-structure-function relationships that empower rational design of complex biomolecules. PMID:26258292

RNA-ID, a highly sensitive and robust method to identify cis-regulatory sequences using superfolder GFP and a fluorescence-based assay.

PubMed

Dean, Kimberly M; Grayhack, Elizabeth J

2012-12-01

We have developed a robust and sensitive method, called RNA-ID, to screen for cis-regulatory sequences in RNA using fluorescence-activated cell sorting (FACS) of yeast cells bearing a reporter in which expression of both superfolder green fluorescent protein (GFP) and yeast codon-optimized mCherry red fluorescent protein (RFP) is driven by the bidirectional GAL1,10 promoter. This method recapitulates previously reported progressive inhibition of translation mediated by increasing numbers of CGA codon pairs, and restoration of expression by introduction of a tRNA with an anticodon that base pairs exactly with the CGA codon. This method also reproduces effects of paromomycin and context on stop codon read-through. Five key features of this method contribute to its effectiveness as a selection for regulatory sequences: The system exhibits greater than a 250-fold dynamic range, a quantitative and dose-dependent response to known inhibitory sequences, exquisite resolution that allows nearly complete physical separation of distinct populations, and a reproducible signal between different cells transformed with the identical reporter, all of which are coupled with simple methods involving ligation-independent cloning, to create large libraries. Moreover, we provide evidence that there are sequences within a 9-nt library that cause reduced GFP fluorescence, suggesting that there are novel cis-regulatory sequences to be found even in this short sequence space. This method is widely applicable to the study of both RNA-mediated and codon-mediated effects on expression.

RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.

PubMed

Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-01-01

Protein-RNA interactions are central to essential cellular processes such as protein synthesis and regulation of gene expression and play roles in human infectious and genetic diseases. Reliable identification of protein-RNA interfaces is critical for understanding the structural bases and functional implications of such interactions and for developing effective approaches to rational drug design. Sequence-based computational methods offer a viable, cost-effective way to identify putative RNA-binding residues in RNA-binding proteins. Here we report two novel approaches: (i) HomPRIP, a sequence homology-based method for predicting RNA-binding sites in proteins; (ii) RNABindRPlus, a new method that combines predictions from HomPRIP with those from an optimized Support Vector Machine (SVM) classifier trained on a benchmark dataset of 198 RNA-binding proteins. Although highly reliable, HomPRIP cannot make predictions for the unaligned parts of query proteins and its coverage is limited by the availability of close sequence homologs of the query protein with experimentally determined RNA-binding sites. RNABindRPlus overcomes these limitations. We compared the performance of HomPRIP and RNABindRPlus with that of several state-of-the-art predictors on two test sets, RB44 and RB111. On a subset of proteins for which homologs with experimentally determined interfaces could be reliably identified, HomPRIP outperformed all other methods achieving an MCC of 0.63 on RB44 and 0.83 on RB111. RNABindRPlus was able to predict RNA-binding residues of all proteins in both test sets, achieving an MCC of 0.55 and 0.37, respectively, and outperforming all other methods, including those that make use of structure-derived features of proteins. More importantly, RNABindRPlus outperforms all other methods for any choice of tradeoff between precision and recall. An important advantage of both HomPRIP and RNABindRPlus is that they rely on readily available sequence and sequence-derived features of RNA-binding proteins. A webserver implementation of both methods is freely available at http://einstein.cs.iastate.edu/RNABindRPlus/.

Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

PubMed

Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

2016-09-07

Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative study of topological indices of macro/supramolecular RNA complex networks.

PubMed

Agüero-Chapín, Guillermín; Antunes, Agostinho; Ubeira, Florencio M; Chou, Kuo-Chen; González-Díaz, Humberto

2008-11-01

RNA function annotation is often based on alignment to a previously studied template. In contrast to the study of proteins, there are not many alignment-free methods to predict RNA functions if alignment fails. The use of topological indices (TIs) of RNA complex networks (CNs) to find quantitative structure-activity relationships (QSAR) may be an alternative to incorporate secondary structure or sequence-to-sequence similarity. Here, we introduce new QSAR-like techniques using RNA macromolecular CNs (mmCNs), where nodes are nucleotides, or RNA supramolecular CNs (smCNs), where nodes are RNA sequences. We studied a data set of 198 sequences including 18S-rRNAs (important phylogenetic molecular biomarkers). We constructed three types of RNA mmCNs: sequence-linear (SL), Cartesian-lattice (CL), and sequence-folding CNs (SF-CNs) and two smCNs: sequence-sequence disagreement CN (SSD) and sequence-sequence similarity (SSS-smCN). We reported the first comparative QSAR study with all these CIs and CNs, which includes: (i) spectral moments ( ( i )micro d ( w)) of SL-mmCNs (accuracy = 75.3%), (ii) electrostatic CIs (xi d ) of CL-mmCNs (>90%), (iii) thermodynamic parameters (Delta G, Delta H, Delta S, and T m) of SF-mmCNs (64.7%), (iv) disagreement-distribution moments ( M k ) of the SSD-smCN (79.3%), and (v) node centralities of the SSD-smCN (78.0%). Furthermore, we reported the experimental isolation of a new RNA sequence from Psidum guajava leaf tissue and its QSAR and BLAST prediction to illustrate the practical use of these methods. We also investigated the use of these CNs to explore rRNA diversity on bacteria, plants, and parasites from the Dactylogyrus genus. The HPL-mmCNs model was the best of all found. All the CNs and TIs, except SF-mmCNs, were introduced here by the first time for the QSAR study of RNA, which allowed a comparative study for RNA classification.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

PubMed

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads.

PubMed

Song, Li; Florea, Liliana

2015-01-01

Next-generation sequencing of cellular RNA (RNA-seq) is rapidly becoming the cornerstone of transcriptomic analysis. However, sequencing errors in the already short RNA-seq reads complicate bioinformatics analyses, in particular alignment and assembly. Error correction methods have been highly effective for whole-genome sequencing (WGS) reads, but are unsuitable for RNA-seq reads, owing to the variation in gene expression levels and alternative splicing. We developed a k-mer based method, Rcorrector, to correct random sequencing errors in Illumina RNA-seq reads. Rcorrector uses a De Bruijn graph to compactly represent all trusted k-mers in the input reads. Unlike WGS read correctors, which use a global threshold to determine trusted k-mers, Rcorrector computes a local threshold at every position in a read. Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from https://github.com/mourisl/Rcorrector/.

Continuous in vitro evolution of bacteriophage RNA polymerase promoters

NASA Technical Reports Server (NTRS)

Breaker, R. R.; Banerji, A.; Joyce, G. F.

1994-01-01

Rapid in vitro evolution of bacteriophage T7, T3, and SP6 RNA polymerase promoters was achieved by a method that allows continuous enrichment of DNAs that contain functional promoter elements. This method exploits the ability of a special class of nucleic acid molecules to replicate continuously in the presence of both a reverse transcriptase and a DNA-dependent RNA polymerase. Replication involves the synthesis of both RNA and cDNA intermediates. The cDNA strand contains an embedded promoter sequence, which becomes converted to a functional double-stranded promoter element, leading to the production of RNA transcripts. Synthetic cDNAs, including those that contain randomized promoter sequences, can be used to initiate the amplification cycle. However, only those cDNAs that contain functional promoter sequences are able to produce RNA transcripts. Furthermore, each RNA transcript encodes the RNA polymerase promoter sequence that was responsible for initiation of its own transcription. Thus, the population of amplifying molecules quickly becomes enriched for those templates that encode functional promoters. Optimal promoter sequences for phage T7, T3, and SP6 RNA polymerase were identified after a 2-h amplification reaction, initiated in each case with a pool of synthetic cDNAs encoding greater than 10(10) promoter sequence variants.

How Messenger RNA and Nascent Chain Sequences Regulate Translation Elongation.

PubMed

Choi, Junhong; Grosely, Rosslyn; Prabhakar, Arjun; Lapointe, Christopher P; Wang, Jinfan; Puglisi, Joseph D

2018-06-20

Translation elongation is a highly coordinated, multistep, multifactor process that ensures accurate and efficient addition of amino acids to a growing nascent-peptide chain encoded in the sequence of translated messenger RNA (mRNA). Although translation elongation is heavily regulated by external factors, there is clear evidence that mRNA and nascent-peptide sequences control elongation dynamics, determining both the sequence and structure of synthesized proteins. Advances in methods have driven experiments that revealed the basic mechanisms of elongation as well as the mechanisms of regulation by mRNA and nascent-peptide sequences. In this review, we highlight how mRNA and nascent-peptide elements manipulate the translation machinery to alter the dynamics and pathway of elongation.

Freiburg RNA tools: a central online resource for RNA-focused research and teaching.

PubMed

Raden, Martin; Ali, Syed M; Alkhnbashi, Omer S; Busch, Anke; Costa, Fabrizio; Davis, Jason A; Eggenhofer, Florian; Gelhausen, Rick; Georg, Jens; Heyne, Steffen; Hiller, Michael; Kundu, Kousik; Kleinkauf, Robert; Lott, Steffen C; Mohamed, Mostafa M; Mattheis, Alexander; Miladi, Milad; Richter, Andreas S; Will, Sebastian; Wolff, Joachim; Wright, Patrick R; Backofen, Rolf

2018-05-21

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

Diversity and community composition of methanogenic archaea in the rumen of Scottish upland sheep assessed by different methods.

PubMed

Snelling, Timothy J; Genç, Buğra; McKain, Nest; Watson, Mick; Waters, Sinéad M; Creevey, Christopher J; Wallace, R John

2014-01-01

Ruminal archaeomes of two mature sheep grazing in the Scottish uplands were analysed by different sequencing and analysis methods in order to compare the apparent archaeal communities. All methods revealed that the majority of methanogens belonged to the Methanobacteriales order containing the Methanobrevibacter, Methanosphaera and Methanobacteria genera. Sanger sequenced 1.3 kb 16S rRNA gene amplicons identified the main species of Methanobrevibacter present to be a SGMT Clade member Mbb. millerae (≥ 91% of OTUs); Methanosphaera comprised the remainder of the OTUs. The primers did not amplify ruminal Thermoplasmatales-related 16S rRNA genes. Illumina sequenced V6-V8 16S rRNA gene amplicons identified similar Methanobrevibacter spp. and Methanosphaera clades and also identified the Thermoplasmatales-related order as 13% of total archaea. Unusually, both methods concluded that Mbb. ruminantium and relatives from the same clade (RO) were almost absent. Sequences mapping to rumen 16S rRNA and mcrA gene references were extracted from Illumina metagenome data. Mapping of the metagenome data to 16S rRNA gene references produced taxonomic identification to Order level including 2-3% Thermoplasmatales, but was unable to discriminate to species level. Mapping of the metagenome data to mcrA gene references resolved 69% to unclassified Methanobacteriales. Only 30% of sequences were assigned to species level clades: of the sequences assigned to Methanobrevibacter, most mapped to SGMT (16%) and RO (10%) clades. The Sanger 16S amplicon and Illumina metagenome mcrA analyses showed similar species richness (Chao1 Index 19-35), while Illumina metagenome and amplicon 16S rRNA analysis gave lower richness estimates (10-18). The values of the Shannon Index were low in all methods, indicating low richness and uneven species distribution. Thus, although much information may be extracted from the other methods, Illumina amplicon sequencing of the V6-V8 16S rRNA gene would be the method of choice for studying rumen archaeal communities.

tRNAmodpred: a computational method for predicting posttranscriptional modifications in tRNAs

PubMed Central

Machnicka, Magdalena A.; Dunin-Horkawicz, Stanislaw; de Crécy-Lagard, Valerie; Bujnicki, Janusz M.

2016-01-01

tRNA molecules contain numerous chemically altered nucleosides, which are formed by enzymatic modification of the primary transcripts during the complex tRNA maturation process. Some of the modifications are introduced by single reactions, while other require complex series of reactions carried out by several different enzymes. The location and distribution of various types of modifications vary greatly between different tRNA molecules, organisms and organelles. We have developed a computational method tRNAmodpred, for predicting modifications in tRNA sequences. Briefly, our method takes as an input one or more unmodified tRNA sequences and a set of protein sequences corresponding to a proteome of a cell. Subsequently it identifies homologs of known tRNA modification enzymes in the proteome, predicts tRNA modification activities and maps them onto known pathways of RNA modification from the MODOMICS database. Thereby, theoretically possible modification pathways are identified, and products of these modification reactions are proposed for query tRNAs. This method allows for predicting modification patterns for newly sequenced genomes as well as for checking tentative modification status of tRNAs from one species treated with enzymes from another source, e.g. to predict the possible modifications of eukaryotic tRNAs expressed in bacteria. tRNAmodpred is freely available as web server at http://genesilico.pl/trnamodpred/. PMID:27016142

Integrated sequencing of exome and mRNA of large-sized single cells.

PubMed

Wang, Lily Yan; Guo, Jiajie; Cao, Wei; Zhang, Meng; He, Jiankui; Li, Zhoufang

2018-01-10

Current approaches of single cell DNA-RNA integrated sequencing are difficult to call SNPs, because a large amount of DNA and RNA is lost during DNA-RNA separation. Here, we performed simultaneous single-cell exome and transcriptome sequencing on individual mouse oocytes. Using microinjection, we kept the nuclei intact to avoid DNA loss, while retaining the cytoplasm inside the cell membrane, to maximize the amount of DNA and RNA captured from the single cell. We then conducted exome-sequencing on the isolated nuclei and mRNA-sequencing on the enucleated cytoplasm. For single oocytes, exome-seq can cover up to 92% of exome region with an average sequencing depth of 10+, while mRNA-sequencing reveals more than 10,000 expressed genes in enucleated cytoplasm, with similar performance for intact oocytes. This approach provides unprecedented opportunities to study DNA-RNA regulation, such as RNA editing at single nucleotide level in oocytes. In future, this method can also be applied to other large cells, including neurons, large dendritic cells and large tumour cells for integrated exome and transcriptome sequencing.

High-throughput amplification of mature microRNAs in uncharacterized animal models using polyadenylated RNA and stem-loop reverse transcription polymerase chain reaction.

PubMed

Biggar, Kyle K; Wu, Cheng-Wei; Storey, Kenneth B

2014-10-01

This study makes a significant advancement on a microRNA amplification technique previously used for expression analysis and sequencing in animal models without annotated mature microRNA sequences. As research progresses into the post-genomic era of microRNA prediction and analysis, the need for a rapid and cost-effective method for microRNA amplification is critical to facilitate wide-scale analysis of microRNA expression. To facilitate this requirement, we have reoptimized the design of amplification primers and introduced a polyadenylation step to allow amplification of all mature microRNAs from a single RNA sample. Importantly, this method retains the ability to sequence reverse transcription polymerase chain reaction (RT-PCR) products, validating microRNA-specific amplification. Copyright © 2014 Elsevier Inc. All rights reserved.

Fragmentation of whole-transcriptome RNA using E. coli RNase III.

PubMed

Ares, Manuel

2013-05-01

High-throughput sequencing (HTS) methods can provide short sequence reads for many millions of individual molecules in a sample, allowing the use of sequencing to measure the abundance of RNA molecules. To quantify the amount of a particular sequence in a sample of large RNAs (e.g., mRNAs), it is important to fragment the RNA into short pieces that can be ligated to oligonucleotides that allow polymerase chain reaction (PCR) amplification and sequencing. The most desired end structure of RNA for such ligation steps is a 5' phosphate and a 3' OH. Thus, enzymes that leave these groups after cleavage are of particular utility, avoiding the need to dephosphorylate the 3' end with phosphatases or phosphorylate the 5' end with kinase before proceeding. One such enzyme, RNase III, is widely available. Although it primarily cuts duplex RNA, this specificity is salt- and concentration-dependent, and many RNAs that lack strong extended duplexes are nonetheless susceptible to cleavage at many spots. RNA fragmentation by RNase III does not seem to grossly affect the distribution of RNA sequencing reads. Thus, it has become a standard method for creating nominally representative pools of transcriptome sequences with 5' phosphates and 3' OH for library construction. Three steps in preparing fragmented transcriptome RNA for sequencing library construction are described here: (1) fragmenting the RNA with RNase III to the extent that ~60-100-nucleotide fragments are created, (2) purifying the RNA from the RNase III reaction, and (3) analyzing the digestion products for their suitability in library production.

Classifying next-generation sequencing data using a zero-inflated Poisson model.

PubMed

Zhou, Yan; Wan, Xiang; Zhang, Baoxue; Tong, Tiejun

2018-04-15

With the development of high-throughput techniques, RNA-sequencing (RNA-seq) is becoming increasingly popular as an alternative for gene expression analysis, such as RNAs profiling and classification. Identifying which type of diseases a new patient belongs to with RNA-seq data has been recognized as a vital problem in medical research. As RNA-seq data are discrete, statistical methods developed for classifying microarray data cannot be readily applied for RNA-seq data classification. Witten proposed a Poisson linear discriminant analysis (PLDA) to classify the RNA-seq data in 2011. Note, however, that the count datasets are frequently characterized by excess zeros in real RNA-seq or microRNA sequence data (i.e. when the sequence depth is not enough or small RNAs with the length of 18-30 nucleotides). Therefore, it is desired to develop a new model to analyze RNA-seq data with an excess of zeros. In this paper, we propose a Zero-Inflated Poisson Logistic Discriminant Analysis (ZIPLDA) for RNA-seq data with an excess of zeros. The new method assumes that the data are from a mixture of two distributions: one is a point mass at zero, and the other follows a Poisson distribution. We then consider a logistic relation between the probability of observing zeros and the mean of the genes and the sequencing depth in the model. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. Two real datasets including a breast cancer RNA-seq dataset and a microRNA-seq dataset are also analyzed, and they coincide with the simulation results that our proposed method outperforms the existing competitors. The software is available at http://www.math.hkbu.edu.hk/∼tongt. xwan@comp.hkbu.edu.hk or tongt@hkbu.edu.hk. Supplementary data are available at Bioinformatics online.

RNA circularization reveals terminal sequence heterogeneity in a double-stranded RNA virus.

PubMed

Widmer, G

1993-03-01

Double-stranded RNA viruses (dsRNA), termed LRV1, have been found in several strains of the protozoan parasite Leishmania. With the aim of constructing a full-length cDNA copy of the viral genome, including its terminal sequences, a protocol based on PCR amplification across the 3'-5' junction of circularized RNA was developed. This method proved to be applicable to dsRNA. It provided a relatively simple alternative to one-sided PCR, without loss of specificity inherent in the use of generic primers. LRV1 terminal nucleotide sequences obtained by this method showed a considerable variation in length, particularly at the 5' end of the positive strand, as well as the potential for forming 3' overhangs. The opposite genomic end terminates in 0, 1, or 2 TCA trinucleotide repeats. These results are compared with terminal sequences derived from one-sided PCR experiments.

Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

PubMed Central

2010-01-01

Background In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA. Results Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection. Discussion The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction. PMID:20550657

Isothermal circular-strand-displacement polymerization of DNA and microRNA in digital microfluidic devices.

PubMed

Giuffrida, Maria Chiara; Zanoli, Laura Maria; D'Agata, Roberta; Finotti, Alessia; Gambari, Roberto; Spoto, Giuseppe

2015-02-01

Nucleic-acid amplification is a crucial step in nucleic-acid-sequence-detection assays. The use of digital microfluidic devices to miniaturize amplification techniques reduces the required sample volume and the analysis time and offers new possibilities for process automation and integration in a single device. The recently introduced droplet polymerase-chain-reaction (PCR) amplification methods require repeated cycles of two or three temperature-dependent steps during the amplification of the nucleic-acid target sequence. In contrast, low-temperature isothermal-amplification methods have no need for thermal cycling, thus requiring simplified microfluidic-device features. Here, the combined use of digital microfluidics and molecular-beacon (MB)-assisted isothermal circular-strand-displacement polymerization (ICSDP) to detect microRNA-210 sequences is described. MicroRNA-210 has been described as the most consistently and predominantly upregulated hypoxia-inducible factor. The nmol L(-1)-pmol L(-1) detection capabilities of the method were first tested by targeting single-stranded DNA sequences from the genetically modified Roundup Ready soybean. The ability of the droplet-ICSDP method to discriminate between full-matched, single-mismatched, and unrelated sequences was also investigated. The detection of a range of nmol L(-1)-pmol L(-1) microRNA-210 solutions compartmentalized in nanoliter-sized droplets was performed, establishing the ability of the method to detect as little as 10(-18) mol of microRNA target sequences compartmentalized in 20 nL droplets. The suitability of the method for biological samples was tested by detecting microRNA-210 from transfected K562 cells.

Selective amplification and sequencing of cyclic phosphate-containing RNAs by the cP-RNA-seq method

PubMed Central

Honda, Shozo; Morichika, Keisuke; Kirino, Yohei

2016-01-01

RNA digestions catalyzed by many ribonucleases generate RNA fragments containing a 2′,3′-cyclic phosphate (cP) at their 3′-termini. However, standard RNA-seq methods are unable to accurately capture cP-containing RNAs because the cP inhibits the adapter ligation reaction. We recently developed a method named “cP-RNA-seq” that is able to selectively amplify and sequence cP-containing RNAs. Here we describe the cP-RNA-seq protocol in which the 3′-termini of all RNAs, except those containing a cP, are cleaved through a periodate treatment after phosphatase treatment, hence subsequent adapter ligation and cDNA amplification steps are exclusively applied to cP-containing RNAs. cP-RNA-seq takes ~6 d, excluding the time required for sequencing and bioinformatics analyses, such downstream assays are not covered in detail in this protocol. Biochemical validation of the existence of cP in the identified RNAs takes ~3 d. Even though the cP-RNA-seq method was developed to identify angiogenin-generating 5′-tRNA halves as a proof of principle, the method should be applicable to global identification of cP-containing RNA repertoires in various transcriptomes. PMID:26866791

VaDiR: an integrated approach to Variant Detection in RNA.

PubMed

Neums, Lisa; Suenaga, Seiji; Beyerlein, Peter; Anders, Sara; Koestler, Devin; Mariani, Andrea; Chien, Jeremy

2018-02-01

Advances in next-generation DNA sequencing technologies are now enabling detailed characterization of sequence variations in cancer genomes. With whole-genome sequencing, variations in coding and non-coding sequences can be discovered. But the cost associated with it is currently limiting its general use in research. Whole-exome sequencing is used to characterize sequence variations in coding regions, but the cost associated with capture reagents and biases in capture rate limit its full use in research. Additional limitations include uncertainty in assigning the functional significance of the mutations when these mutations are observed in the non-coding region or in genes that are not expressed in cancer tissue. We investigated the feasibility of uncovering mutations from expressed genes using RNA sequencing datasets with a method called Variant Detection in RNA(VaDiR) that integrates 3 variant callers, namely: SNPiR, RVBoost, and MuTect2. The combination of all 3 methods, which we called Tier 1 variants, produced the highest precision with true positive mutations from RNA-seq that could be validated at the DNA level. We also found that the integration of Tier 1 variants with those called by MuTect2 and SNPiR produced the highest recall with acceptable precision. Finally, we observed a higher rate of mutation discovery in genes that are expressed at higher levels. Our method, VaDiR, provides a possibility of uncovering mutations from RNA sequencing datasets that could be useful in further functional analysis. In addition, our approach allows orthogonal validation of DNA-based mutation discovery by providing complementary sequence variation analysis from paired RNA/DNA sequencing datasets.

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

PubMed Central

Yan, Yong-Wei; Zou, Bin; Zhu, Ting; Hozzein, Wael N.

2017-01-01

RNA-seq-based SSU (small subunit) rRNA (ribosomal RNA) analysis has provided a better understanding of potentially active microbial community within environments. However, for RNA-seq library construction, high quantities of purified RNA are typically required. We propose a modified RNA-seq method for SSU rRNA-based microbial community analysis that depends on the direct ligation of a 5’ adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10–100 ng) and does not require a DNA removal step. The method was initially tested on three mock communities synthesized with enriched SSU rRNA of archaeal, bacterial and fungal isolates at different ratios, and was subsequently used for environmental samples of high or low biomass. For high-biomass salt-marsh sediments, enriched SSU rRNA and total nucleic acid-derived RNA-seq datasets revealed highly consistent community compositions for all of the SSU rRNA sequences, and as much as 46.4%-59.5% of 16S rRNA sequences were suitable for OTU (operational taxonomic unit)-based community and diversity analyses with complete coverage of V1-V2 regions. OTU-based community structures for the two datasets were also highly consistent with those determined by all of the 16S rRNA reads. For low-biomass samples, total nucleic acid-derived RNA-seq datasets were analyzed, and highly active bacterial taxa were also identified by the OTU-based method, notably including members of the previously underestimated genus Nitrospira and phylum Acidobacteria in tap water, members of the phylum Actinobacteria on a shower curtain, and members of the phylum Cyanobacteria on leaf surfaces. More than half of the bacterial 16S rRNA sequences covered the complete region of primer 8F, and non-coverage rates as high as 38.7% were obtained for phylum-unclassified sequences, providing many opportunities to identify novel bacterial taxa. This modified RNA-seq method will provide a better snapshot of diverse microbial communities, most notably by OTU-based analysis, even communities with low-biomass samples. PMID:29016661

An Optimized Transient Dual Luciferase Assay for Quantifying MicroRNA Directed Repression of Targeted Sequences

PubMed Central

Moyle, Richard L.; Carvalhais, Lilia C.; Pretorius, Lara-Simone; Nowak, Ekaterina; Subramaniam, Gayathery; Dalton-Morgan, Jessica; Schenk, Peer M.

2017-01-01

Studies investigating the action of small RNAs on computationally predicted target genes require some form of experimental validation. Classical molecular methods of validating microRNA action on target genes are laborious, while approaches that tag predicted target sequences to qualitative reporter genes encounter technical limitations. The aim of this study was to address the challenge of experimentally validating large numbers of computationally predicted microRNA-target transcript interactions using an optimized, quantitative, cost-effective, and scalable approach. The presented method combines transient expression via agroinfiltration of Nicotiana benthamiana leaves with a quantitative dual luciferase reporter system, where firefly luciferase is used to report the microRNA-target sequence interaction and Renilla luciferase is used as an internal standard to normalize expression between replicates. We report the appropriate concentration of N. benthamiana leaf extracts and dilution factor to apply in order to avoid inhibition of firefly LUC activity. Furthermore, the optimal ratio of microRNA precursor expression construct to reporter construct and duration of the incubation period post-agroinfiltration were determined. The optimized dual luciferase assay provides an efficient, repeatable and scalable method to validate and quantify microRNA action on predicted target sequences. The optimized assay was used to validate five predicted targets of rice microRNA miR529b, with as few as six technical replicates. The assay can be extended to assess other small RNA-target sequence interactions, including assessing the functionality of an artificial miRNA or an RNAi construct on a targeted sequence. PMID:28979287

Evaluating Quality of Aged Archival Formalin-Fixed Paraffin-Embedded Samples for RNA-Sequencing

EPA Science Inventory

Archival formalin-fixed paraffin-embedded (FFPE) samples offer a vast, untapped source of genomic data for biomarker discovery. However, the quality of FFPE samples is often highly variable, and conventional methods to assess RNA quality for RNA-sequencing (RNA-seq) are not infor...

Identification of Bacillus Probiotics Isolated from Soil Rhizosphere Using 16S rRNA, recA, rpoB Gene Sequencing and RAPD-PCR.

PubMed

Mohkam, Milad; Nezafat, Navid; Berenjian, Aydin; Mobasher, Mohammad Ali; Ghasemi, Younes

2016-03-01

Some Bacillus species, especially Bacillus subtilis and Bacillus pumilus groups, have highly similar 16S rRNA gene sequences, which are hard to identify based on 16S rDNA sequence analysis. To conquer this drawback, rpoB, recA sequence analysis along with randomly amplified polymorphic (RAPD) fingerprinting was examined as an alternative method for differentiating Bacillus species. The 16S rRNA, rpoB and recA genes were amplified via a polymerase chain reaction using their specific primers. The resulted PCR amplicons were sequenced, and phylogenetic analysis was employed by MEGA 6 software. Identification based on 16S rRNA gene sequencing was underpinned by rpoB and recA gene sequencing as well as RAPD-PCR technique. Subsequently, concatenation and phylogenetic analysis showed that extent of diversity and similarity were better obtained by rpoB and recA primers, which are also reinforced by RAPD-PCR methods. However, in one case, these approaches failed to identify one isolate, which in combination with the phenotypical method offsets this issue. Overall, RAPD fingerprinting, rpoB and recA along with concatenated genes sequence analysis discriminated closely related Bacillus species, which highlights the significance of the multigenic method in more precisely distinguishing Bacillus strains. This research emphasizes the benefit of RAPD fingerprinting, rpoB and recA sequence analysis superior to 16S rRNA gene sequence analysis for suitable and effective identification of Bacillus species as recommended for probiotic products.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1987-10-07

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1990-10-09

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Moyzis, Robert K.; Ratliff, Robert L.; Shera, E. Brooks; Stewart, Carleton C.

1990-01-01

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed.

Method for rapid base sequencing in DNA and RNA with two base labeling

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Posner, R.G.; Marrone, B.L.; Hammond, M.L.; Simpson, D.J.

1995-04-11

A method is described for rapid-base sequencing in DNA and RNA with two-base labeling and employing fluorescent detection of single molecules at two wavelengths. Bases modified to accept fluorescent labels are used to replicate a single DNA or RNA strand to be sequenced. The bases are then sequentially cleaved from the replicated strand, excited with a chosen spectrum of electromagnetic radiation, and the fluorescence from individual, tagged bases detected in the order of cleavage from the strand. 4 figures.

Method for rapid base sequencing in DNA and RNA with two base labeling

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Posner, Richard G.; Marrone, Babetta L.; Hammond, Mark L.; Simpson, Daniel J.

1995-01-01

Method for rapid-base sequencing in DNA and RNA with two-base labeling and employing fluorescent detection of single molecules at two wavelengths. Bases modified to accept fluorescent labels are used to replicate a single DNA or RNA strand to be sequenced. The bases are then sequentially cleaved from the replicated strand, excited with a chosen spectrum of electromagnetic radiation, and the fluorescence from individual, tagged bases detected in the order of cleavage from the strand.

The Role of 16S rRNA Gene Sequencing in Identification of Microorganisms Misidentified by Conventional Methods

PubMed Central

Petti, C. A.; Polage, C. R.; Schreckenberger, P.

2005-01-01

Traditional methods for microbial identification require the recognition of differences in morphology, growth, enzymatic activity, and metabolism to define genera and species. Full and partial 16S rRNA gene sequencing methods have emerged as useful tools for identifying phenotypically aberrant microorganisms. We report on three bacterial blood isolates from three different College of American Pathologists-certified laboratories that were referred to ARUP Laboratories for definitive identification. Because phenotypic identification suggested unusual organisms not typically associated with the submitted clinical diagnosis, consultation with the Medical Director was sought and further testing was performed including partial 16S rRNA gene sequencing. All three patients had endocarditis, and conventional methods identified isolates from patients A, B, and C as a Facklamia sp., Eubacterium tenue, and a Bifidobacterium sp. 16S rRNA gene sequencing identified the isolates as Enterococcus faecalis, Cardiobacterium valvarum, and Streptococcus mutans, respectively. We conclude that the initial identifications of these three isolates were erroneous, may have misled clinicians, and potentially impacted patient care. 16S rRNA gene sequencing is a more objective identification tool, unaffected by phenotypic variation or technologist bias, and has the potential to reduce laboratory errors. PMID:16333109

RNA-Seq for Bacterial Gene Expression.

PubMed

Poulsen, Line Dahl; Vinther, Jeppe

2018-06-01

RNA sequencing (RNA-seq) has become the preferred method for global quantification of bacterial gene expression. With the continued improvements in sequencing technology and data analysis tools, the most labor-intensive and expensive part of an RNA-seq experiment is the preparation of sequencing libraries, which is also essential for the quality of the data obtained. Here, we present a straightforward and inexpensive basic protocol for preparation of strand-specific RNA-seq libraries from bacterial RNA as well as a computational pipeline for the data analysis of sequencing reads. The protocol is based on the Illumina platform and allows easy multiplexing of samples and the removal of sequencing reads that are PCR duplicates. © 2018 by John Wiley & Sons, Inc. © 2018 John Wiley & Sons, Inc.

mirRICH, a simple method to enrich the small RNA fraction from over-dried RNA pellets.

PubMed

Choi, Cheolwon; Yoon, Seulgi; Moon, Hyesu; Bae, Yun-Ui; Kim, Chae-Bin; Diskul-Na-Ayudthaya, Penchatr; Ngu, Trinh Van; Munir, Javaria; Han, JaeWook; Park, Se Bin; Moon, Jong-Seok; Song, Sujung; Ryu, Seongho

2018-04-11

Techniques to isolate the small RNA fraction (<200nt) by column-based methods are commercially available. However, their use is limited because of the relatively high cost. We found that large RNA molecules, including mRNAs and rRNAs, are aggregated together in the presence of salts when RNA pellets are over-dried. Moreover, once RNA pellets are over-dried, large RNA molecules are barely soluble again during the elution process, whereas small RNA molecules (<100nt) can be eluted. We therefore modified the acid guanidinium thiocyanate-phenol-chloroform (AGPC)-based RNA extraction protocol by skipping the 70% ethanol washing step and over-drying the RNA pellet for 1 hour at room temperature. We named this novel small RNA isolation method "mirRICH." The quality of the small RNA sequences was validated by electrophoresis, next-generation sequencing, and quantitative PCR, and the findings support that our newly developed column-free method can successfully and efficiently isolate small RNAs from over-dried RNA pellets.

Targeted RNA-Sequencing with Competitive Multiplex-PCR Amplicon Libraries

PubMed Central

Blomquist, Thomas M.; Crawford, Erin L.; Lovett, Jennie L.; Yeo, Jiyoun; Stanoszek, Lauren M.; Levin, Albert; Li, Jia; Lu, Mei; Shi, Leming; Muldrew, Kenneth; Willey, James C.

2013-01-01

Whole transcriptome RNA-sequencing is a powerful tool, but is costly and yields complex data sets that limit its utility in molecular diagnostic testing. A targeted quantitative RNA-sequencing method that is reproducible and reduces the number of sequencing reads required to measure transcripts over the full range of expression would be better suited to diagnostic testing. Toward this goal, we developed a competitive multiplex PCR-based amplicon sequencing library preparation method that a) targets only the sequences of interest and b) controls for inter-target variation in PCR amplification during library preparation by measuring each transcript native template relative to a known number of synthetic competitive template internal standard copies. To determine the utility of this method, we intentionally selected PCR conditions that would cause transcript amplification products (amplicons) to converge toward equimolar concentrations (normalization) during library preparation. We then tested whether this approach would enable accurate and reproducible quantification of each transcript across multiple library preparations, and at the same time reduce (through normalization) total sequencing reads required for quantification of transcript targets across a large range of expression. We demonstrate excellent reproducibility (R2 = 0.997) with 97% accuracy to detect 2-fold change using External RNA Controls Consortium (ERCC) reference materials; high inter-day, inter-site and inter-library concordance (R2 = 0.97–0.99) using FDA Sequencing Quality Control (SEQC) reference materials; and cross-platform concordance with both TaqMan qPCR (R2 = 0.96) and whole transcriptome RNA-sequencing following “traditional” library preparation using Illumina NGS kits (R2 = 0.94). Using this method, sequencing reads required to accurately quantify more than 100 targeted transcripts expressed over a 107-fold range was reduced more than 10,000-fold, from 2.3×109 to 1.4×105 sequencing reads. These studies demonstrate that the competitive multiplex-PCR amplicon library preparation method presented here provides the quality control, reproducibility, and reduced sequencing reads necessary for development and implementation of targeted quantitative RNA-sequencing biomarkers in molecular diagnostic testing. PMID:24236095

Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

PubMed

Yehdego, Daniel T; Zhang, Boyu; Kodimala, Vikram K R; Johnson, Kyle L; Taufer, Michela; Leung, Ming-Ying

2013-05-01

Secondary structures of ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Experimental observations and computing limitations suggest that we can approach the secondary structure prediction problem for long RNA sequences by segmenting them into shorter chunks, predicting the secondary structures of each chunk individually using existing prediction programs, and then assembling the results to give the structure of the original sequence. The selection of cutting points is a crucial component of the segmenting step. Noting that stem-loops and pseudoknots always contain an inversion, i.e., a stretch of nucleotides followed closely by its inverse complementary sequence, we developed two cutting methods for segmenting long RNA sequences based on inversion excursions: the centered and optimized method. Each step of searching for inversions, chunking, and predictions can be performed in parallel. In this paper we use a MapReduce framework, i.e., Hadoop, to extensively explore meaningful inversion stem lengths and gap sizes for the segmentation and identify correlations between chunking methods and prediction accuracy. We show that for a set of long RNA sequences in the RFAM database, whose secondary structures are known to contain pseudoknots, our approach predicts secondary structures more accurately than methods that do not segment the sequence, when the latter predictions are possible computationally. We also show that, as sequences exceed certain lengths, some programs cannot computationally predict pseudoknots while our chunking methods can. Overall, our predicted structures still retain the accuracy level of the original prediction programs when compared with known experimental secondary structure.

Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes

PubMed Central

Shiroguchi, Katsuyuki; Jia, Tony Z.; Sims, Peter A.; Xie, X. Sunney

2012-01-01

RNA sequencing (RNA-Seq) is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable, even in the presence of multiple sequencing errors. This method allows counting with single-copy resolution despite sequence-dependent bias and PCR-amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of Escherichia coli with more accurate and reproducible quantification than conventional RNA-Seq. PMID:22232676

RISC RNA sequencing for context-specific identification of in vivo miR targets

PubMed Central

Matkovich, Scot J; Van Booven, Derek J; Eschenbacher, William H; Dorn, Gerald W

2010-01-01

Rationale MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo. Objective To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs). Methods and Results We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias, and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1,645 mRNAs consistently targeted to mouse cardiac RISCs. We employed this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing ‘seed’ sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts. Conclusions RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context, and is applicable to any tissue and any disease state. Summary MicroRNAs (miRs) are key regulators of mRNA translation in health and disease. While bioinformatic predictions suggest that a single miR may target hundreds of mRNAs, the number of experimentally verified targets of miRs is low. To enable comprehensive, unbiased examination of miR targets, we have performed deep RNA sequencing of cardiac transcriptomes in parallel with cardiac RNA-induced silencing complex (RISC)-associated RNAs (the RISCome), called RISC sequencing. We developed methods that did not require cross-linking of RNAs to RISCs or amplification of mRNA prior to sequencing, making it possible to rapidly perform RISC sequencing from intact tissue while avoiding amplification bias. Comparison of RISCome with transcriptome expression defined the degree of RISC enrichment for each mRNA. The majority of the mRNAs enriched in wild-type cardiac RISComes compared to transcriptomes were bioinformatically predicted to be targets of at least 1 of 139 cardiac-expressed miRs. Programming cardiomyocyte RISCs via transgenic overexpression in adult hearts of miR-133a or miR-499, two miRs that contain entirely different ‘seed’ sequences, elicited differing profiles of RISC-targeted mRNAs. Thus, RISC sequencing represents a highly sensitive method for general RISC profiling and individual miR target identification in biological context. PMID:21030712

INFO-RNA--a fast approach to inverse RNA folding.

PubMed

Busch, Anke; Backofen, Rolf

2006-08-01

The structure of RNA molecules is often crucial for their function. Therefore, secondary structure prediction has gained much interest. Here, we consider the inverse RNA folding problem, which means designing RNA sequences that fold into a given structure. We introduce a new algorithm for the inverse folding problem (INFO-RNA) that consists of two parts; a dynamic programming method for good initial sequences and a following improved stochastic local search that uses an effective neighbor selection method. During the initialization, we design a sequence that among all sequences adopts the given structure with the lowest possible energy. For the selection of neighbors during the search, we use a kind of look-ahead of one selection step applying an additional energy-based criterion. Afterwards, the pre-ordered neighbors are tested using the actual optimization criterion of minimizing the structure distance between the target structure and the mfe structure of the considered neighbor. We compared our algorithm to RNAinverse and RNA-SSD for artificial and biological test sets. Using INFO-RNA, we performed better than RNAinverse and in most cases, we gained better results than RNA-SSD, the probably best inverse RNA folding tool on the market. www.bioinf.uni-freiburg.de?Subpages/software.html.

A tale of two sequences: microRNA-target chimeric reads.

PubMed

Broughton, James P; Pasquinelli, Amy E

2016-04-04

In animals, a functional interaction between a microRNA (miRNA) and its target RNA requires only partial base pairing. The limited number of base pair interactions required for miRNA targeting provides miRNAs with broad regulatory potential and also makes target prediction challenging. Computational approaches to target prediction have focused on identifying miRNA target sites based on known sequence features that are important for canonical targeting and may miss non-canonical targets. Current state-of-the-art experimental approaches, such as CLIP-seq (cross-linking immunoprecipitation with sequencing), PAR-CLIP (photoactivatable-ribonucleoside-enhanced CLIP), and iCLIP (individual-nucleotide resolution CLIP), require inference of which miRNA is bound at each site. Recently, the development of methods to ligate miRNAs to their target RNAs during the preparation of sequencing libraries has provided a new tool for the identification of miRNA target sites. The chimeric, or hybrid, miRNA-target reads that are produced by these methods unambiguously identify the miRNA bound at a specific target site. The information provided by these chimeric reads has revealed extensive non-canonical interactions between miRNAs and their target mRNAs, and identified many novel interactions between miRNAs and noncoding RNAs.

Determining RNA quality for NextGen sequencing: some exceptions to the gold standard rule of 23S to 16S rRNA ratio

USDA-ARS?s Scientific Manuscript database

Using next-generation-sequencing technology to assess entire transcriptomes requires high quality starting RNA. Currently, RNA quality is routinely judged using automated microfluidic gel electrophoresis platforms and associated algorithms. Here we report that such automated methods generate false-n...

How to design a single-cell RNA-sequencing experiment: pitfalls, challenges and perspectives.

PubMed

Dal Molin, Alessandra; Di Camillo, Barbara

2018-01-31

The sequencing of the transcriptome of single cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types in heterogeneous cell populations or for the study of stochastic gene expression. In recent years, various experimental methods and computational tools for analysing single-cell RNA-sequencing data have been proposed. However, most of them are tailored to different experimental designs or biological questions, and in many cases, their performance has not been benchmarked yet, thus increasing the difficulty for a researcher to choose the optimal single-cell transcriptome sequencing (scRNA-seq) experiment and analysis workflow. In this review, we aim to provide an overview of the current available experimental and computational methods developed to handle single-cell RNA-sequencing data and, based on their peculiarities, we suggest possible analysis frameworks depending on specific experimental designs. Together, we propose an evaluation of challenges and open questions and future perspectives in the field. In particular, we go through the different steps of scRNA-seq experimental protocols such as cell isolation, messenger RNA capture, reverse transcription, amplification and use of quantitative standards such as spike-ins and Unique Molecular Identifiers (UMIs). We then analyse the current methodological challenges related to preprocessing, alignment, quantification, normalization, batch effect correction and methods to control for confounding effects. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Pseudomonas sp. strain CA5 (a selenite-reducing bacterium) 16S rRNA gene complete sequence. National Institute of Health, National Center for Biotechnology Information, GenBank sequence. Accession FJ422810.1.

USDA-ARS?s Scientific Manuscript database

This study used 1321 base pair 16S rRNA gene sequence methods to confirm the phylogenetic position of a soil isolate as a bacterium belonging to the genus Pesudomonas sp. Morphological, biochemical characteristics, and fatty acid profiles are consistent with the 16S rRNA gene sequence identification...

Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data.

PubMed

Li, Peipei; Piao, Yongjun; Shon, Ho Sun; Ryu, Keun Ho

2015-10-28

Recently, rapid improvements in technology and decrease in sequencing costs have made RNA-Seq a widely used technique to quantify gene expression levels. Various normalization approaches have been proposed, owing to the importance of normalization in the analysis of RNA-Seq data. A comparison of recently proposed normalization methods is required to generate suitable guidelines for the selection of the most appropriate approach for future experiments. In this paper, we compared eight non-abundance (RC, UQ, Med, TMM, DESeq, Q, RPKM, and ERPKM) and two abundance estimation normalization methods (RSEM and Sailfish). The experiments were based on real Illumina high-throughput RNA-Seq of 35- and 76-nucleotide sequences produced in the MAQC project and simulation reads. Reads were mapped with human genome obtained from UCSC Genome Browser Database. For precise evaluation, we investigated Spearman correlation between the normalization results from RNA-Seq and MAQC qRT-PCR values for 996 genes. Based on this work, we showed that out of the eight non-abundance estimation normalization methods, RC, UQ, Med, TMM, DESeq, and Q gave similar normalization results for all data sets. For RNA-Seq of a 35-nucleotide sequence, RPKM showed the highest correlation results, but for RNA-Seq of a 76-nucleotide sequence, least correlation was observed than the other methods. ERPKM did not improve results than RPKM. Between two abundance estimation normalization methods, for RNA-Seq of a 35-nucleotide sequence, higher correlation was obtained with Sailfish than that with RSEM, which was better than without using abundance estimation methods. However, for RNA-Seq of a 76-nucleotide sequence, the results achieved by RSEM were similar to without applying abundance estimation methods, and were much better than with Sailfish. Furthermore, we found that adding a poly-A tail increased alignment numbers, but did not improve normalization results. Spearman correlation analysis revealed that RC, UQ, Med, TMM, DESeq, and Q did not noticeably improve gene expression normalization, regardless of read length. Other normalization methods were more efficient when alignment accuracy was low; Sailfish with RPKM gave the best normalization results. When alignment accuracy was high, RC was sufficient for gene expression calculation. And we suggest ignoring poly-A tail during differential gene expression analysis.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

PubMed

Ziegenhain, Christoph; Vieth, Beate; Parekh, Swati; Reinius, Björn; Guillaumet-Adkins, Amy; Smets, Martha; Leonhardt, Heinrich; Heyn, Holger; Hellmann, Ines; Enard, Wolfgang

2017-02-16

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols. Copyright © 2017 Elsevier Inc. All rights reserved.

Probe-Directed Degradation (PDD) for Flexible Removal of Unwanted cDNA Sequences from RNA-Seq Libraries.

PubMed

Archer, Stuart K; Shirokikh, Nikolay E; Preiss, Thomas

2015-04-01

Most applications for RNA-seq require the depletion of abundant transcripts to gain greater coverage of the underlying transcriptome. The sequences to be targeted for depletion depend on application and species and in many cases may not be supported by commercial depletion kits. This unit describes a method for generating RNA-seq libraries that incorporates probe-directed degradation (PDD), which can deplete any unwanted sequence set, with the low-bias split-adapter method of library generation (although many other library generation methods are in principle compatible). The overall strategy is suitable for applications requiring customized sequence depletion or where faithful representation of fragment ends and lack of sequence bias is paramount. We provide guidelines to rapidly design specific probes against the target sequence, and a detailed protocol for library generation using the split-adapter method including several strategies for streamlining the technique and reducing adapter dimer content. Copyright © 2015 John Wiley & Sons, Inc.

CapZyme-Seq Comprehensively Defines Promoter-Sequence Determinants for RNA 5' Capping with NAD.

PubMed

Vvedenskaya, Irina O; Bird, Jeremy G; Zhang, Yuanchao; Zhang, Yu; Jiao, Xinfu; Barvík, Ivan; Krásný, Libor; Kiledjian, Megerditch; Taylor, Deanne M; Ebright, Richard H; Nickels, Bryce E

2018-05-03

Nucleoside-containing metabolites such as NAD + can be incorporated as 5' caps on RNA by serving as non-canonical initiating nucleotides (NCINs) for transcription initiation by RNA polymerase (RNAP). Here, we report CapZyme-seq, a high-throughput-sequencing method that employs NCIN-decapping enzymes NudC and Rai1 to detect and quantify NCIN-capped RNA. By combining CapZyme-seq with multiplexed transcriptomics, we determine efficiencies of NAD + capping by Escherichia coli RNAP for ∼16,000 promoter sequences. The results define preferred transcription start site (TSS) positions for NAD + capping and define a consensus promoter sequence for NAD + capping: HRRASWW (TSS underlined). By applying CapZyme-seq to E. coli total cellular RNA, we establish that sequence determinants for NCIN capping in vivo match the NAD + -capping consensus defined in vitro, and we identify and quantify NCIN-capped small RNAs (sRNAs). Our findings define the promoter-sequence determinants for NCIN capping with NAD + and provide a general method for analysis of NCIN capping in vitro and in vivo. Copyright © 2018 Elsevier Inc. All rights reserved.

RNAPattMatch: a web server for RNA sequence/structure motif detection based on pattern matching with flexible gaps

PubMed Central

Drory Retwitzer, Matan; Polishchuk, Maya; Churkin, Elena; Kifer, Ilona; Yakhini, Zohar; Barash, Danny

2015-01-01

Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational RNA pattern matching as an enhancement to sequence similarity. State-of-the-art programs differ by the flexibility of patterns allowed as queries and by their simplicity of use. In particular—no existing method is available as a user-friendly web server. A general program that searches for RNA sequence-structure patterns is RNA Structator. However, it is not available as a web server and does not provide the option to allow flexible gap pattern representation with an upper bound of the gap length being specified at any position in the sequence. Here, we introduce RNAPattMatch, a web-based application that is user friendly and makes sequence/structure RNA queries accessible to practitioners of various background and proficiency. It also extends RNA Structator and allows a more flexible variable gaps representation, in addition to analysis of results using energy minimization methods. RNAPattMatch service is available at http://www.cs.bgu.ac.il/rnapattmatch. A standalone version of the search tool is also available to download at the site. PMID:25940619

Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

Walia, Rasna R.; EL-Manzalawy, Yasser; Honavar, Vasant G.; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. PMID:27787829

Improved detection of CXCR4-using HIV by V3 genotyping: application of population-based and "deep" sequencing to plasma RNA and proviral DNA.

PubMed

Swenson, Luke C; Moores, Andrew; Low, Andrew J; Thielen, Alexander; Dong, Winnie; Woods, Conan; Jensen, Mark A; Wynhoven, Brian; Chan, Dennison; Glascock, Christopher; Harrigan, P Richard

2010-08-01

Tropism testing should rule out CXCR4-using HIV before treatment with CCR5 antagonists. Currently, the recombinant phenotypic Trofile assay (Monogram) is most widely utilized; however, genotypic tests may represent alternative methods. Independent triplicate amplifications of the HIV gp120 V3 region were made from either plasma HIV RNA or proviral DNA. These underwent standard, population-based sequencing with an ABI3730 (RNA n = 63; DNA n = 40), or "deep" sequencing with a Roche/454 Genome Sequencer-FLX (RNA n = 12; DNA n = 12). Position-specific scoring matrices (PSSMX4/R5) (-6.96 cutoff) and geno2pheno[coreceptor] (5% false-positive rate) inferred tropism from V3 sequence. These methods were then independently validated with a separate, blinded dataset (n = 278) of screening samples from the maraviroc MOTIVATE trials. Standard sequencing of HIV RNA with PSSM yielded 69% sensitivity and 91% specificity, relative to Trofile. The validation dataset gave 75% sensitivity and 83% specificity. Proviral DNA plus PSSM gave 77% sensitivity and 71% specificity. "Deep" sequencing of HIV RNA detected >2% inferred-CXCR4-using virus in 8/8 samples called non-R5 by Trofile, and <2% in 4/4 samples called R5. Triplicate analyses of V3 standard sequence data detect greater proportions of CXCR4-using samples than previously achieved. Sequencing proviral DNA and "deep" V3 sequencing may also be useful tools for assessing tropism.

Mapping of RNA accessible sites by extension of random oligonucleotide libraries with reverse transcriptase.

PubMed Central

Allawi, H T; Dong, F; Ip, H S; Neri, B P; Lyamichev, V I

2001-01-01

A rapid and simple method for determining accessible sites in RNA that is independent of the length of target RNA and does not require RNA labeling is described. In this method, target RNA is allowed to hybridize with sequence-randomized libraries of DNA oligonucleotides linked to a common tag sequence at their 5'-end. Annealed oligonucleotides are extended with reverse transcriptase and the extended products are then amplified by using PCR with a primer corresponding to the tag sequence and a second primer specific to the target RNA sequence. We used the combination of both the lengths of the RT-PCR products and the location of the binding site of the RNA-specific primer to determine which regions of the RNA molecules were RNA extendible sites, that is, sites available for oligonucleotide binding and extension. We then employed this reverse transcription with the random oligonucleotide libraries (RT-ROL) method to determine the accessible sites on four mRNA targets, human activated ras (ha-ras), human intercellular adhesion molecule-1 (ICAM-1), rabbit beta-globin, and human interferon-gamma (IFN-gamma). Our results were concordant with those of other researchers who had used RNase H cleavage or hybridization with arrays of oligonucleotides to identify accessible sites on some of these targets. Further, we found good correlation between sites when we compared the location of extendible sites identified by RT-ROL with hybridization sites of effective antisense oligonucleotides on ICAM-1 mRNA in antisense inhibition studies. Finally, we discuss the relationship between RNA extendible sites and RNA accessibility. PMID:11233988

Discovering Deeply Divergent RNA Viruses in Existing Metatranscriptome Data with Machine Learning

NASA Astrophysics Data System (ADS)

Rivers, A. R.

2016-02-01

Most sampling of RNA viruses and phages has been directed toward a narrow range of hosts and environments. Several marine metagenomic studies have examined the RNA viral fraction in aquatic samples and found a number of picornaviruses and uncharacterized sequences. The lack of homology to known protein families has limited the discovery of new RNA viruses. We developed a computational method for identifying RNA viruses that relies on information in the codon transition probabilities of viral sequences to train a classifier. This approach does not rely on homology, but it has higher information content than other reference-free methods such as tetranucleotide frequency. Training and validation with RefSeq data gave true positive and true negative rates of 99.6% and 99.5% on the highly imbalanced validation sets (0.2% viruses) that, like the metatranscriptomes themselves, contain mostly non-viral sequences. To further test the method, a validation dataset of putative RNA virus genomes were identified in metatransciptomes by the presence of RNA dependent RNA polymerase, an essential gene for RNA viruses. The classifier successfully identified 99.4% of those contigs as viral. This approach is currently being extended to screen all metatranscriptome data sequenced at the DOE Joint Genome Institute, presently 4.5 Gb of assembled data from 504 public projects representing a wide range of marine, aquatic and terrestrial environments.

Quantum Point Contact Single-Nucleotide Conductance for DNA and RNA Sequence Identification.

PubMed

Afsari, Sepideh; Korshoj, Lee E; Abel, Gary R; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-11-28

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve >99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.

Discriminative Prediction of A-To-I RNA Editing Events from DNA Sequence

PubMed Central

Sun, Jiangming; Singh, Pratibha; Bagge, Annika; Valtat, Bérengère; Vikman, Petter; Spégel, Peter; Mulder, Hindrik

2016-01-01

RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem. Using 41 nucleotide long DNA sequences, we show that novel A-to-I RNA editing events can be predicted from known A-to-I RNA editing events intra- and interspecies. The validity of the proposed method was verified in an independent experimental dataset. Using our approach, 203 202 putative A-to-I RNA editing events were predicted in the whole human genome. Out of these, 9% were previously reported. The remaining sites require further validation, e.g., by targeted deep sequencing. In conclusion, the approach described here is a useful tool to identify potential A-to-I RNA editing events without the requirement of extensive RNA sequencing. PMID:27764195

Sample sequencing of vascular plants demonstrates widespread conservation and divergence of microRNAs.

PubMed

Chávez Montes, Ricardo A; de Fátima Rosas-Cárdenas, Flor; De Paoli, Emanuele; Accerbi, Monica; Rymarquis, Linda A; Mahalingam, Gayathri; Marsch-Martínez, Nayelli; Meyers, Blake C; Green, Pamela J; de Folter, Stefan

2014-04-23

Small RNAs are pivotal regulators of gene expression that guide transcriptional and post-transcriptional silencing mechanisms in eukaryotes, including plants. Here we report a comprehensive atlas of sRNA and miRNA from 3 species of algae and 31 representative species across vascular plants, including non-model plants. We sequence and quantify sRNAs from 99 different tissues or treatments across species, resulting in a data set of over 132 million distinct sequences. Using miRBase mature sequences as a reference, we identify the miRNA sequences present in these libraries. We apply diverse profiling methods to examine critical sRNA and miRNA features, such as size distribution, tissue-specific regulation and sequence conservation between species, as well as to predict putative new miRNA sequences. We also develop database resources, computational analysis tools and a dedicated website, http://smallrna.udel.edu/. This study provides new insights on plant sRNAs and miRNAs, and a foundation for future studies.

Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns

PubMed Central

2013-01-01

Background It is well known that the search for homologous RNAs is more effective if both sequence and structure information is incorporated into the search. However, current tools for searching with RNA sequence-structure patterns cannot fully handle mutations occurring on both these levels or are simply not fast enough for searching large sequence databases because of the high computational costs of the underlying sequence-structure alignment problem. Results We present new fast index-based and online algorithms for approximate matching of RNA sequence-structure patterns supporting a full set of edit operations on single bases and base pairs. Our methods efficiently compute semi-global alignments of structural RNA patterns and substrings of the target sequence whose costs satisfy a user-defined sequence-structure edit distance threshold. For this purpose, we introduce a new computing scheme to optimally reuse the entries of the required dynamic programming matrices for all substrings and combine it with a technique for avoiding the alignment computation of non-matching substrings. Our new index-based methods exploit suffix arrays preprocessed from the target database and achieve running times that are sublinear in the size of the searched sequences. To support the description of RNA molecules that fold into complex secondary structures with multiple ordered sequence-structure patterns, we use fast algorithms for the local or global chaining of approximate sequence-structure pattern matches. The chaining step removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our improved online algorithm is faster than the best previous method by up to factor 45. Our best new index-based algorithm achieves a speedup of factor 560. Conclusions The presented methods achieve considerable speedups compared to the best previous method. This, together with the expected sublinear running time of the presented index-based algorithms, allows for the first time approximate matching of RNA sequence-structure patterns in large sequence databases. Beyond the algorithmic contributions, we provide with RaligNAtor a robust and well documented open-source software package implementing the algorithms presented in this manuscript. The RaligNAtor software is available at http://www.zbh.uni-hamburg.de/ralignator. PMID:23865810

Uncultivated Microbial Eukaryotic Diversity: A Method to Link ssu rRNA Gene Sequences with Morphology

PubMed Central

Hirst, Marissa B.; Kita, Kelley N.; Dawson, Scott C.

2011-01-01

Protists have traditionally been identified by cultivation and classified taxonomically based on their cellular morphologies and behavior. In the past decade, however, many novel protist taxa have been identified using cultivation independent ssu rRNA sequence surveys. New rRNA “phylotypes” from uncultivated eukaryotes have no connection to the wealth of prior morphological descriptions of protists. To link phylogenetically informative sequences with taxonomically informative morphological descriptions, we demonstrate several methods for combining whole cell rRNA-targeted fluorescent in situ hybridization (FISH) with cytoskeletal or organellar immunostaining. Either eukaryote or ciliate-specific ssu rRNA probes were combined with an anti-α-tubulin antibody or phalloidin, a common actin stain, to define cytoskeletal features of uncultivated protists in several environmental samples. The eukaryote ssu rRNA probe was also combined with Mitotracker® or a hydrogenosomal-specific anti-Hsp70 antibody to localize mitochondria and hydrogenosomes, respectively, in uncultivated protists from different environments. Using rRNA probes in combination with immunostaining, we linked ssu rRNA phylotypes with microtubule structure to describe flagellate and ciliate morphology in three diverse environments, and linked Naegleria spp. to their amoeboid morphology using actin staining in hay infusion samples. We also linked uncultivated ciliates to morphologically similar Colpoda-like ciliates using tubulin immunostaining with a ciliate-specific rRNA probe. Combining rRNA-targeted FISH with cytoskeletal immunostaining or stains targeting specific organelles provides a fast, efficient, high throughput method for linking genetic sequences with morphological features in uncultivated protists. When linked to phylotype, morphological descriptions of protists can both complement and vet the increasing number of sequences from uncultivated protists, including those of novel lineages, identified in diverse environments. PMID:22174774

CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates.

PubMed

Low, Joel Z B; Khang, Tsung Fei; Tammi, Martti T

2017-12-28

In current statistical methods for calling differentially expressed genes in RNA-Seq experiments, the assumption is that an adjusted observed gene count represents an unknown true gene count. This adjustment usually consists of a normalization step to account for heterogeneous sample library sizes, and then the resulting normalized gene counts are used as input for parametric or non-parametric differential gene expression tests. A distribution of true gene counts, each with a different probability, can result in the same observed gene count. Importantly, sequencing coverage information is currently not explicitly incorporated into any of the statistical models used for RNA-Seq analysis. We developed a fast Bayesian method which uses the sequencing coverage information determined from the concentration of an RNA sample to estimate the posterior distribution of a true gene count. Our method has better or comparable performance compared to NOISeq and GFOLD, according to the results from simulations and experiments with real unreplicated data. We incorporated a previously unused sequencing coverage parameter into a procedure for differential gene expression analysis with RNA-Seq data. Our results suggest that our method can be used to overcome analytical bottlenecks in experiments with limited number of replicates and low sequencing coverage. The method is implemented in CORNAS (Coverage-dependent RNA-Seq), and is available at https://github.com/joel-lzb/CORNAS .

GRIL-seq provides a method for identifying direct targets of bacterial small regulatory RNA by in vivo proximity ligation.

PubMed

Han, Kook; Tjaden, Brian; Lory, Stephen

2016-12-22

The first step in the post-transcriptional regulatory function of most bacterial small non-coding RNAs (sRNAs) is base pairing with partially complementary sequences of targeted transcripts. We present a simple method for identifying sRNA targets in vivo and defining processing sites of the regulated transcripts. The technique, referred to as global small non-coding RNA target identification by ligation and sequencing (GRIL-seq), is based on preferential ligation of sRNAs to the ends of base-paired targets in bacteria co-expressing T4 RNA ligase, followed by sequencing to identify the chimaeras. In addition to the RNA chaperone Hfq, the GRIL-seq method depends on the activity of the pyrophosphorylase RppH. Using PrrF1, an iron-regulated sRNA in Pseudomonas aeruginosa, we demonstrated that direct regulatory targets of this sRNA can readily be identified. Therefore, GRIL-seq represents a powerful tool not only for identifying direct targets of sRNAs in a variety of environments, but also for uncovering novel roles for sRNAs and their targets in complex regulatory networks.

Optimization of preservation and storage time of sponge tissues to obtain quality mRNA for next-generation sequencing.

PubMed

Riesgo, Ana; Pérez-Porro, Alicia R; Carmona, Susana; Leys, Sally P; Giribet, Gonzalo

2012-03-01

Transcriptome sequencing with next-generation sequencing technologies has the potential for addressing many long-standing questions about the biology of sponges. Transcriptome sequence quality depends on good cDNA libraries, which requires high-quality mRNA. Standard protocols for preserving and isolating mRNA often require optimization for unusual tissue types. Our aim was assessing the efficiency of two preservation modes, (i) flash freezing with liquid nitrogen (LN₂) and (ii) immersion in RNAlater, for the recovery of high-quality mRNA from sponge tissues. We also tested whether the long-term storage of samples at -80 °C affects the quantity and quality of mRNA. We extracted mRNA from nine sponge species and analysed the quantity and quality (A260/230 and A260/280 ratios) of mRNA according to preservation method, storage time, and taxonomy. The quantity and quality of mRNA depended significantly on the preservation method used (LN₂) outperforming RNAlater), the sponge species, and the interaction between them. When the preservation was analysed in combination with either storage time or species, the quantity and A260/230 ratio were both significantly higher for LN₂-preserved samples. Interestingly, individual comparisons for each preservation method over time indicated that both methods performed equally efficiently during the first month, but RNAlater lost efficiency in storage times longer than 2 months compared with flash-frozen samples. In summary, we find that for long-term preservation of samples, flash freezing is the preferred method. If LN₂ is not available, RNAlater can be used, but mRNA extraction during the first month of storage is advised. © 2011 Blackwell Publishing Ltd.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing.

PubMed

Li, Feng; Kaczor-Urbanowicz, Karolina Elżbieta; Sun, Jie; Majem, Blanca; Lo, Hsien-Chun; Kim, Yong; Koyano, Kikuye; Liu Rao, Shannon; Young Kang, So; Mi Kim, Su; Kim, Kyoung-Mee; Kim, Sung; Chia, David; Elashoff, David; Grogan, Tristan R; Xiao, Xinshu; Wong, David T W

2018-04-23

It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies. © 2018 American Association for Clinical Chemistry.

Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts

PubMed Central

Jukam, David; Teran, Nicole A; Risca, Viviana I; Smith, Owen K; Johnson, Whitney L; Skotheim, Jan M; Greenleaf, William James

2018-01-01

RNA is a critical component of chromatin in eukaryotes, both as a product of transcription, and as an essential constituent of ribonucleoprotein complexes that regulate both local and global chromatin states. Here, we present a proximity ligation and sequencing method called Chromatin-Associated RNA sequencing (ChAR-seq) that maps all RNA-to-DNA contacts across the genome. Using Drosophila cells, we show that ChAR-seq provides unbiased, de novo identification of targets of chromatin-bound RNAs including nascent transcripts, chromosome-specific dosage compensation ncRNAs, and genome-wide trans-associated RNAs involved in co-transcriptional RNA processing. PMID:29648534

Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.

PubMed

Macaulay, Iain C; Teng, Mabel J; Haerty, Wilfried; Kumar, Parveen; Ponting, Chris P; Voet, Thierry

2016-11-01

Parallel sequencing of a single cell's genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ∼3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.

BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data.

PubMed

Chae, Heejoon; Rhee, Sungmin; Nephew, Kenneth P; Kim, Sun

2015-01-15

It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA-mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise. The objective of this study was to modify our widely recognized Web server for the integrated mRNA-miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLAB-MMIA) to be compatible with high-throughput platforms, including next-generation sequencing (NGS) data (e.g. RNA-seq). We developed a new version called the BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high-performance publicly available server called MAHA. By using NGS data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages. First, sequencing data is more accurate than array-based methods for determining miRNA expression levels. Second, potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs. Third, because miRNA-mediated gene regulation is due to hybridization of an miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy. http://epigenomics.snu.ac.kr/biovlab_mmia_ngs/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Transcriptome Analysis at the Single-Cell Level Using SMART Technology.

PubMed

Fish, Rachel N; Bostick, Magnolia; Lehman, Alisa; Farmer, Andrew

2016-10-10

RNA sequencing (RNA-seq) is a powerful method for analyzing cell state, with minimal bias, and has broad applications within the biological sciences. However, transcriptome analysis of seemingly homogenous cell populations may in fact overlook significant heterogeneity that can be uncovered at the single-cell level. The ultra-low amount of RNA contained in a single cell requires extraordinarily sensitive and reproducible transcriptome analysis methods. As next-generation sequencing (NGS) technologies mature, transcriptome profiling by RNA-seq is increasingly being used to decipher the molecular signature of individual cells. This unit describes an ultra-sensitive and reproducible protocol to generate cDNA and sequencing libraries directly from single cells or RNA inputs ranging from 10 pg to 10 ng. Important considerations for working with minute RNA inputs are given. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

RNA-ID, a Powerful Tool for Identifying and Characterizing Regulatory Sequences.

PubMed

Brule, C E; Dean, K M; Grayhack, E J

2016-01-01

The identification and analysis of sequences that regulate gene expression is critical because regulated gene expression underlies biology. RNA-ID is an efficient and sensitive method to discover and investigate regulatory sequences in the yeast Saccharomyces cerevisiae, using fluorescence-based assays to detect green fluorescent protein (GFP) relative to a red fluorescent protein (RFP) control in individual cells. Putative regulatory sequences can be inserted either in-frame or upstream of a superfolder GFP fusion protein whose expression, like that of RFP, is driven by the bidirectional GAL1,10 promoter. In this chapter, we describe the methodology to identify and study cis-regulatory sequences in the RNA-ID system, explaining features and variations of the RNA-ID reporter, as well as some applications of this system. We describe in detail the methods to analyze a single regulatory sequence, from construction of a single GFP variant to assay of variants by flow cytometry, as well as modifications required to screen libraries of different strains simultaneously. We also describe subsequent analyses of regulatory sequences. © 2016 Elsevier Inc. All rights reserved.

Accurate RNA consensus sequencing for high-fidelity detection of transcriptional mutagenesis-induced epimutations.

PubMed

Reid-Bayliss, Kate S; Loeb, Lawrence A

2017-08-29

Transcriptional mutagenesis (TM) due to misincorporation during RNA transcription can result in mutant RNAs, or epimutations, that generate proteins with altered properties. TM has long been hypothesized to play a role in aging, cancer, and viral and bacterial evolution. However, inadequate methodologies have limited progress in elucidating a causal association. We present a high-throughput, highly accurate RNA sequencing method to measure epimutations with single-molecule sensitivity. Accurate RNA consensus sequencing (ARC-seq) uniquely combines RNA barcoding and generation of multiple cDNA copies per RNA molecule to eliminate errors introduced during cDNA synthesis, PCR, and sequencing. The stringency of ARC-seq can be scaled to accommodate the quality of input RNAs. We apply ARC-seq to directly assess transcriptome-wide epimutations resulting from RNA polymerase mutants and oxidative stress.

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

PubMed

Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

2018-03-09

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

The technology and biology of single-cell RNA sequencing.

PubMed

Kolodziejczyk, Aleksandra A; Kim, Jong Kyoung; Svensson, Valentine; Marioni, John C; Teichmann, Sarah A

2015-05-21

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis and Prediction of Exon Skipping Events from RNA-Seq with Sequence Information Using Rotation Forest.

PubMed

Du, Xiuquan; Hu, Changlin; Yao, Yu; Sun, Shiwei; Zhang, Yanping

2017-12-12

In bioinformatics, exon skipping (ES) event prediction is an essential part of alternative splicing (AS) event analysis. Although many methods have been developed to predict ES events, a solution has yet to be found. In this study, given the limitations of machine learning algorithms with RNA-Seq data or genome sequences, a new feature, called RS (RNA-seq and sequence) features, was constructed. These features include RNA-Seq features derived from the RNA-Seq data and sequence features derived from genome sequences. We propose a novel Rotation Forest classifier to predict ES events with the RS features (RotaF-RSES). To validate the efficacy of RotaF-RSES, a dataset from two human tissues was used, and RotaF-RSES achieved an accuracy of 98.4%, a specificity of 99.2%, a sensitivity of 94.1%, and an area under the curve (AUC) of 98.6%. When compared to the other available methods, the results indicate that RotaF-RSES is efficient and can predict ES events with RS features.

siRNA and innate immunity.

PubMed

Robbins, Marjorie; Judge, Adam; MacLachlan, Ian

2009-06-01

Canonical small interfering RNA (siRNA) duplexes are potent activators of the mammalian innate immune system. The induction of innate immunity by siRNA is dependent on siRNA structure and sequence, method of delivery, and cell type. Synthetic siRNA in delivery vehicles that facilitate cellular uptake can induce high levels of inflammatory cytokines and interferons after systemic administration in mammals and in primary human blood cell cultures. This activation is predominantly mediated by immune cells, normally via a Toll-like receptor (TLR) pathway. The siRNA sequence dependency of these pathways varies with the type and location of the TLR involved. Alternatively nonimmune cell activation may also occur, typically resulting from siRNA interaction with cytoplasmic RNA sensors such as RIG1. As immune activation by siRNA-based drugs represents an undesirable side effect due to the considerable toxicities associated with excessive cytokine release in humans, understanding and abrogating this activity will be a critical component in the development of safe and effective therapeutics. This review describes the intracellular mechanisms of innate immune activation by siRNA, the design of appropriate sequences and chemical modification approaches, and suitable experimental methods for studying their effects, with a view toward reducing siRNA-mediated off-target effects.

RNA-Seq Technology and Its Application in Fish Transcriptomics

PubMed Central

Ba, Yi; Zhuang, Qianfeng

2014-01-01

Abstract High-throughput sequencing technologies, also known as next-generation sequencing (NGS) technologies, have revolutionized the way that genomic research is advancing. In addition to the static genome, these state-of-art technologies have been recently exploited to analyze the dynamic transcriptome, and the resulting technology is termed RNA sequencing (RNA-seq). RNA-seq is free from many limitations of other transcriptomic approaches, such as microarray and tag-based sequencing method. Although RNA-seq has only been available for a short time, studies using this method have completely changed our perspective of the breadth and depth of eukaryotic transcriptomes. In terms of the transcriptomics of teleost fishes, both model and non-model species have benefited from the RNA-seq approach and have undergone tremendous advances in the past several years. RNA-seq has helped not only in mapping and annotating fish transcriptome but also in our understanding of many biological processes in fish, such as development, adaptive evolution, host immune response, and stress response. In this review, we first provide an overview of each step of RNA-seq from library construction to the bioinformatic analysis of the data. We then summarize and discuss the recent biological insights obtained from the RNA-seq studies in a variety of fish species. PMID:24380445

Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

PubMed

Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

2017-03-14

Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful features than nucleotide compositions in finding protein-binding regions in RNA sequences. But, a slight performance gain was obtained when using the sequence profiles along with nucleotide compositions. These are preliminary results of ongoing research, but demonstrate the potential of our approach as a powerful predictor of protein-binding regions in RNA. The program and supporting data are available at http://bclab.inha.ac.kr/RBPbinding .

Methods for processing high-throughput RNA sequencing data.

PubMed

Ares, Manuel

2014-11-03

High-throughput sequencing (HTS) methods for analyzing RNA populations (RNA-Seq) are gaining rapid application to many experimental situations. The steps in an RNA-Seq experiment require thought and planning, especially because the expense in time and materials is currently higher and the protocols are far less routine than those used for other high-throughput methods, such as microarrays. As always, good experimental design will make analysis and interpretation easier. Having a clear biological question, an idea about the best way to do the experiment, and an understanding of the number of replicates needed will make the entire process more satisfying. Whether the goal is capturing transcriptome complexity from a tissue or identifying small fragments of RNA cross-linked to a protein of interest, conversion of the RNA to cDNA followed by direct sequencing using the latest methods is a developing practice, with new technical modifications and applications appearing every day. Even more rapid are the development and improvement of methods for analysis of the very large amounts of data that arrive at the end of an RNA-Seq experiment, making considerations regarding reproducibility, validation, visualization, and interpretation increasingly important. This introduction is designed to review and emphasize a pathway of analysis from experimental design through data presentation that is likely to be successful, with the recognition that better methods are right around the corner. © 2014 Cold Spring Harbor Laboratory Press.

Multimodal RNA-seq using single-strand, double-strand, and CircLigase-based capture yields a refined and extended description of the C. elegans transcriptome.

PubMed

Lamm, Ayelet T; Stadler, Michael R; Zhang, Huibin; Gent, Jonathan I; Fire, Andrew Z

2011-02-01

We have used a combination of three high-throughput RNA capture and sequencing methods to refine and augment the transcriptome map of a well-studied genetic model, Caenorhabditis elegans. The three methods include a standard (non-directional) library preparation protocol relying on cDNA priming and foldback that has been used in several previous studies for transcriptome characterization in this species, and two directional protocols, one involving direct capture of single-stranded RNA fragments and one involving circular-template PCR (CircLigase). We find that each RNA-seq approach shows specific limitations and biases, with the application of multiple methods providing a more complete map than was obtained from any single method. Of particular note in the analysis were substantial advantages of CircLigase-based and ssRNA-based capture for defining sequences and structures of the precise 5' ends (which were lost using the double-strand cDNA capture method). Of the three methods, ssRNA capture was most effective in defining sequences to the poly(A) junction. Using data sets from a spectrum of C. elegans strains and stages and the UCSC Genome Browser, we provide a series of tools, which facilitate rapid visualization and assignment of gene structures.

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering

PubMed Central

Sul, Woo Jun; Cole, James R.; Jesus, Ederson da C.; Wang, Qiong; Farris, Ryan J.; Fish, Jordan A.; Tiedje, James M.

2011-01-01

High-throughput sequencing of 16S rRNA genes has increased our understanding of microbial community structure, but now even higher-throughput methods to the Illumina scale allow the creation of much larger datasets with more samples and orders-of-magnitude more sequences that swamp current analytic methods. We developed a method capable of handling these larger datasets on the basis of assignment of sequences into an existing taxonomy using a supervised learning approach (taxonomy-supervised analysis). We compared this method with a commonly used clustering approach based on sequence similarity (taxonomy-unsupervised analysis). We sampled 211 different bacterial communities from various habitats and obtained ∼1.3 million 16S rRNA sequences spanning the V4 hypervariable region by pyrosequencing. Both methodologies gave similar ecological conclusions in that β-diversity measures calculated by using these two types of matrices were significantly correlated to each other, as were the ordination configurations and hierarchical clustering dendrograms. In addition, our taxonomy-supervised analyses were also highly correlated with phylogenetic methods, such as UniFrac. The taxonomy-supervised analysis has the advantages that it is not limited by the exhaustive computation required for the alignment and clustering necessary for the taxonomy-unsupervised analysis, is more tolerant of sequencing errors, and allows comparisons when sequences are from different regions of the 16S rRNA gene. With the tremendous expansion in 16S rRNA data acquisition underway, the taxonomy-supervised approach offers the potential to provide more rapid and extensive community comparisons across habitats and samples. PMID:21873204

The complete mitochondrial genome of Lota lota (Gadiformes: Gadidae) from the Burqin River in China.

PubMed

Lu, Zhichuang; Zhang, Nan; Song, Na; Gao, Tianxiang

2016-05-01

In this study, the complete mitochondrial genome (mitogenome) sequence of Lota lota has been determined by long polymerase chain reaction and primer walking methods. The mitogenome is a circular molecule of 16,519 bp in length and contains 37 mitochondrial genes including 13 protein-coding genes, 2 ribosomal RNA (rRNA), 22 transfer RNA (tRNA) and a control region as other bony fishes. Within the control region, we identified the termination-associated sequence domain (TAS), the central conserved sequence block domains (CSB-F and CSB-D), and the conserved sequence block domains (CSB-1, CSB-2 and CSB-3).

ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

PubMed Central

Krestel, Ralf; Ohler, Uwe; Vingron, Martin; Marsico, Annalisa

2017-01-01

Abstract RNA-binding proteins (RBPs) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM’s model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image. PMID:28977546

Single-Molecule Electrical Random Resequencing of DNA and RNA

NASA Astrophysics Data System (ADS)

Ohshiro, Takahito; Matsubara, Kazuki; Tsutsui, Makusu; Furuhashi, Masayuki; Taniguchi, Masateru; Kawai, Tomoji

2012-07-01

Two paradigm shifts in DNA sequencing technologies--from bulk to single molecules and from optical to electrical detection--are expected to realize label-free, low-cost DNA sequencing that does not require PCR amplification. It will lead to development of high-throughput third-generation sequencing technologies for personalized medicine. Although nanopore devices have been proposed as third-generation DNA-sequencing devices, a significant milestone in these technologies has been attained by demonstrating a novel technique for resequencing DNA using electrical signals. Here we report single-molecule electrical resequencing of DNA and RNA using a hybrid method of identifying single-base molecules via tunneling currents and random sequencing. Our method reads sequences of nine types of DNA oligomers. The complete sequence of 5'-UGAGGUA-3' from the let-7 microRNA family was also identified by creating a composite of overlapping fragment sequences, which was randomly determined using tunneling current conducted by single-base molecules as they passed between a pair of nanoelectrodes.

Genome-Wide Analysis of A-to-I RNA Editing.

PubMed

Savva, Yiannis A; Laurent, Georges St; Reenan, Robert A

2016-01-01

Adenosine (A)-to-inosine (I) RNA editing is a fundamental posttranscriptional modification that ensures the deamination of A-to-I in double-stranded (ds) RNA molecules. Intriguingly, the A-to-I RNA editing system is particularly active in the nervous system of higher eukaryotes, altering a plethora of noncoding and coding sequences. Abnormal RNA editing is highly associated with many neurological phenotypes and neurodevelopmental disorders. However, the molecular mechanisms underlying RNA editing-mediated pathogenesis still remain enigmatic and have attracted increasing attention from researchers. Over the last decade, methods available to perform genome-wide transcriptome analysis, have evolved rapidly. Within the RNA editing field researchers have adopted next-generation sequencing technologies to identify RNA-editing sites within genomes and to elucidate the underlying process. However, technical challenges associated with editing site discovery have hindered efforts to uncover comprehensive editing site datasets, resulting in the general perception that the collections of annotated editing sites represent only a small minority of the total number of sites in a given organism, tissue, or cell type of interest. Additionally to doubts about sensitivity, existing RNA-editing site lists often contain high percentages of false positives, leading to uncertainty about their validity and usefulness in downstream studies. An accurate investigation of A-to-I editing requires properly validated datasets of editing sites with demonstrated and transparent levels of sensitivity and specificity. Here, we describe a high signal-to-noise method for RNA-editing site detection using single-molecule sequencing (SMS). With this method, authentic RNA-editing sites may be differentiated from artifacts. Machine learning approaches provide a procedure to improve upon and experimentally validate sequencing outcomes through use of computationally predicted, iterative feedback loops. Subsequent use of extensive Sanger sequencing validations can generate accurate editing site lists. This approach has broad application and accurate genome-wide editing analysis of various tissues from clinical specimens or various experimental organisms is now a possibility.

Library construction for next-generation sequencing: Overviews and challenges

PubMed Central

Head, Steven R.; Komori, H. Kiyomi; LaMere, Sarah A.; Whisenant, Thomas; Van Nieuwerburgh, Filip; Salomon, Daniel R.; Ordoukhanian, Phillip

2014-01-01

High-throughput sequencing, also known as next-generation sequencing (NGS), has revolutionized genomic research. In recent years, NGS technology has steadily improved, with costs dropping and the number and range of sequencing applications increasing exponentially. Here, we examine the critical role of sequencing library quality and consider important challenges when preparing NGS libraries from DNA and RNA sources. Factors such as the quantity and physical characteristics of the RNA or DNA source material as well as the desired application (i.e., genome sequencing, targeted sequencing, RNA-seq, ChIP-seq, RIP-seq, and methylation) are addressed in the context of preparing high quality sequencing libraries. In addition, the current methods for preparing NGS libraries from single cells are also discussed. PMID:24502796

RISC RNA sequencing for context-specific identification of in vivo microRNA targets.

PubMed

Matkovich, Scot J; Van Booven, Derek J; Eschenbacher, William H; Dorn, Gerald W

2011-01-07

MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo. To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs). We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1645 mRNAs consistently targeted to mouse cardiac RISCs. We used this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing "seed" sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts. RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context and is applicable to any tissue and any disease state.

An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile.

PubMed

Prakash, Celine; Haeseler, Arndt Von

2017-03-01

RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing coverage across a genomic feature has been a concern in RNA-seq and is attributed to biases for certain fragments in RNA-seq library preparation and sequencing. To investigate the expected coverage obtained from fragmentation, we develop a simple fragmentation model that is independent of bias from the experimental method and is not specific to the transcript sequence. Essentially, we enumerate all configurations for maximal placement of a given fragment length, F, on transcript length, T, to represent every possible fragmentation pattern, from which we compute the expected coverage profile across a transcript. We extend this model to incorporate general empirical attributes such as read length, fragment length distribution, and number of molecules of the transcript. We further introduce the fragment starting-point, fragment coverage, and read coverage profiles. We find that the expected profiles are not uniform and that factors such as fragment length to transcript length ratio, read length to fragment length ratio, fragment length distribution, and number of molecules influence the variability of coverage across a transcript. Finally, we explore a potential application of the model where, with simulations, we show that it is possible to correctly estimate the transcript copy number for any transcript in the RNA-seq experiment.

An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile

PubMed Central

Haeseler, Arndt Von

2017-01-01

Abstract RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing coverage across a genomic feature has been a concern in RNA-seq and is attributed to biases for certain fragments in RNA-seq library preparation and sequencing. To investigate the expected coverage obtained from fragmentation, we develop a simple fragmentation model that is independent of bias from the experimental method and is not specific to the transcript sequence. Essentially, we enumerate all configurations for maximal placement of a given fragment length, F, on transcript length, T, to represent every possible fragmentation pattern, from which we compute the expected coverage profile across a transcript. We extend this model to incorporate general empirical attributes such as read length, fragment length distribution, and number of molecules of the transcript. We further introduce the fragment starting-point, fragment coverage, and read coverage profiles. We find that the expected profiles are not uniform and that factors such as fragment length to transcript length ratio, read length to fragment length ratio, fragment length distribution, and number of molecules influence the variability of coverage across a transcript. Finally, we explore a potential application of the model where, with simulations, we show that it is possible to correctly estimate the transcript copy number for any transcript in the RNA-seq experiment. PMID:27661099

Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

RNA inverse folding using Monte Carlo tree search.

PubMed

Yang, Xiufeng; Yoshizoe, Kazuki; Taneda, Akito; Tsuda, Koji

2017-11-06

Artificially synthesized RNA molecules provide important ways for creating a variety of novel functional molecules. State-of-the-art RNA inverse folding algorithms can design simple and short RNA sequences of specific GC content, that fold into the target RNA structure. However, their performance is not satisfactory in complicated cases. We present a new inverse folding algorithm called MCTS-RNA, which uses Monte Carlo tree search (MCTS), a technique that has shown exceptional performance in Computer Go recently, to represent and discover the essential part of the sequence space. To obtain high accuracy, initial sequences generated by MCTS are further improved by a series of local updates. Our algorithm has an ability to control the GC content precisely and can deal with pseudoknot structures. Using common benchmark datasets for evaluation, MCTS-RNA showed a lot of promise as a standard method of RNA inverse folding. MCTS-RNA is available at https://github.com/tsudalab/MCTS-RNA .

RNA design using simulated SHAPE data.

PubMed

Lotfi, Mohadeseh; Zare-Mirakabad, Fatemeh; Montaseri, Soheila

2018-05-03

It has long been established that in addition to being involved in protein translation, RNA plays essential roles in numerous other cellular processes, including gene regulation and DNA replication. Such roles are known to be dictated by higher-order structures of RNA molecules. It is therefore of prime importance to find an RNA sequence that can fold to acquire a particular function that is desirable for use in pharmaceuticals and basic research. The challenge of finding an RNA sequence for a given structure is known as the RNA design problem. Although there are several algorithms to solve this problem, they mainly consider hard constraints, such as minimum free energy, to evaluate the predicted sequences. Recently, SHAPE data has emerged as a new soft constraint for RNA secondary structure prediction. To take advantage of this new experimental constraint, we report here a new method for accurate design of RNA sequences based on their secondary structures using SHAPE data as pseudo-free energy. We then compare our algorithm with four others: INFO-RNA, ERD, MODENA and RNAifold 2.0. Our algorithm precisely predicts 26 out of 29 new sequences for the structures extracted from the Rfam dataset, while the other four algorithms predict no more than 22 out of 29. The proposed algorithm is comparable to the above algorithms on RNA-SSD datasets, where they can predict up to 33 appropriate sequences for RNA secondary structures out of 34.

Quantitative Assessment of RNA-Protein Interactions with High Throughput Sequencing - RNA Affinity Profiling (HiTS-RAP)

PubMed Central

Ozer, Abdullah; Tome, Jacob M.; Friedman, Robin C.; Gheba, Dan; Schroth, Gary P.; Lis, John T.

2016-01-01

Because RNA-protein interactions play a central role in a wide-array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the High Throughput Sequencing-RNA Affinity Profiling (HiTS-RAP) assay, which couples sequencing on an Illumina GAIIx with the quantitative assessment of one or several proteins’ interactions with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of EGFP and NELF-E proteins with their corresponding canonical and mutant RNA aptamers. Here, we provide a detailed protocol for HiTS-RAP, which can be completed in about a month (8 days hands-on time) including the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, high-throughput sequencing and protein binding with GAIIx, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, RNA-MaP and RBNS. A successful HiTS-RAP experiment provides the sequence and binding curves for approximately 200 million RNAs in a single experiment. PMID:26182240

incaRNAfbinv: a web server for the fragment-based design of RNA sequences

PubMed Central

Drory Retwitzer, Matan; Reinharz, Vladimir; Ponty, Yann; Waldispühl, Jérôme; Barash, Danny

2016-01-01

Abstract In recent years, new methods for computational RNA design have been developed and applied to various problems in synthetic biology and nanotechnology. Lately, there is considerable interest in incorporating essential biological information when solving the inverse RNA folding problem. Correspondingly, RNAfbinv aims at including biologically meaningful constraints and is the only program to-date that performs a fragment-based design of RNA sequences. In doing so it allows the design of sequences that do not necessarily exactly fold into the target, as long as the overall coarse-grained tree graph shape is preserved. Augmented by the weighted sampling algorithm of incaRNAtion, our web server called incaRNAfbinv implements the method devised in RNAfbinv and offers an interactive environment for the inverse folding of RNA using a fragment-based design approach. It takes as input: a target RNA secondary structure; optional sequence and motif constraints; optional target minimum free energy, neutrality and GC content. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The two complementary methodologies RNAfbinv and incaRNAtion are merged together and fully implemented in our web server incaRNAfbinv, available at http://www.cs.bgu.ac.il/incaRNAfbinv. PMID:27185893

Generic Amplicon Deep Sequencing to Determine Ilarvirus Species Diversity in Australian Prunus

PubMed Central

Kinoti, Wycliff M.; Constable, Fiona E.; Nancarrow, Narelle; Plummer, Kim M.; Rodoni, Brendan

2017-01-01

The distribution of Ilarvirus species populations amongst 61 Australian Prunus trees was determined by next generation sequencing (NGS) of amplicons generated using a genus-based generic RT-PCR targeting a conserved region of the Ilarvirus RNA2 component that encodes the RNA dependent RNA polymerase (RdRp) gene. Presence of Ilarvirus sequences in each positive sample was further validated by Sanger sequencing of cloned amplicons of regions of each of RNA1, RNA2 and/or RNA3 that were generated by species specific PCRs and by metagenomic NGS. Prunus necrotic ringspot virus (PNRSV) was the most frequently detected Ilarvirus, occurring in 48 of the 61 Ilarvirus-positive trees and Prune dwarf virus (PDV) and Apple mosaic virus (ApMV) were detected in three trees and one tree, respectively. American plum line pattern virus (APLPV) was detected in three trees and represents the first report of APLPV detection in Australia. Two novel and distinct groups of Ilarvirus-like RNA2 amplicon sequences were also identified in several trees by the generic amplicon NGS approach. The high read depth from the amplicon NGS of the generic PCR products allowed the detection of distinct RNA2 RdRp sequence variant populations of PNRSV, PDV, ApMV, APLPV and the two novel Ilarvirus-like sequences. Mixed infections of ilarviruses were also detected in seven Prunus trees. Sanger sequencing of specific RNA1, RNA2, and/or RNA3 genome segments of each virus and total nucleic acid metagenomics NGS confirmed the presence of PNRSV, PDV, ApMV and APLPV detected by RNA2 generic amplicon NGS. However, the two novel groups of Ilarvirus-like RNA2 amplicon sequences detected by the generic amplicon NGS could not be associated to the presence of sequence from RNA1 or RNA3 genome segments or full Ilarvirus genomes, and their origin is unclear. This work highlights the sensitivity of genus-specific amplicon NGS in detection of virus sequences and their distinct populations in multiple samples, and the need for a standardized approach to accurately determine what constitutes an active, viable virus infection after detection by molecular based methods. PMID:28713347

Generic Amplicon Deep Sequencing to Determine Ilarvirus Species Diversity in Australian Prunus.

PubMed

Kinoti, Wycliff M; Constable, Fiona E; Nancarrow, Narelle; Plummer, Kim M; Rodoni, Brendan

2017-01-01

The distribution of Ilarvirus species populations amongst 61 Australian Prunus trees was determined by next generation sequencing (NGS) of amplicons generated using a genus-based generic RT-PCR targeting a conserved region of the Ilarvirus RNA2 component that encodes the RNA dependent RNA polymerase (RdRp) gene. Presence of Ilarvirus sequences in each positive sample was further validated by Sanger sequencing of cloned amplicons of regions of each of RNA1, RNA2 and/or RNA3 that were generated by species specific PCRs and by metagenomic NGS. Prunus necrotic ringspot virus (PNRSV) was the most frequently detected Ilarvirus , occurring in 48 of the 61 Ilarvirus -positive trees and Prune dwarf virus (PDV) and Apple mosaic virus (ApMV) were detected in three trees and one tree, respectively. American plum line pattern virus (APLPV) was detected in three trees and represents the first report of APLPV detection in Australia. Two novel and distinct groups of Ilarvirus -like RNA2 amplicon sequences were also identified in several trees by the generic amplicon NGS approach. The high read depth from the amplicon NGS of the generic PCR products allowed the detection of distinct RNA2 RdRp sequence variant populations of PNRSV, PDV, ApMV, APLPV and the two novel Ilarvirus -like sequences. Mixed infections of ilarviruses were also detected in seven Prunus trees. Sanger sequencing of specific RNA1, RNA2, and/or RNA3 genome segments of each virus and total nucleic acid metagenomics NGS confirmed the presence of PNRSV, PDV, ApMV and APLPV detected by RNA2 generic amplicon NGS. However, the two novel groups of Ilarvirus -like RNA2 amplicon sequences detected by the generic amplicon NGS could not be associated to the presence of sequence from RNA1 or RNA3 genome segments or full Ilarvirus genomes, and their origin is unclear. This work highlights the sensitivity of genus-specific amplicon NGS in detection of virus sequences and their distinct populations in multiple samples, and the need for a standardized approach to accurately determine what constitutes an active, viable virus infection after detection by molecular based methods.

Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

RNA catalysis and the origins of life

NASA Technical Reports Server (NTRS)

Orgel, Leslie E.

1986-01-01

The role of RNA catalysis in the origins of life is considered in connection with the discovery of riboszymes, which are RNA molecules that catalyze sequence-specific hydrolysis and transesterification reactions of RNA substrates. Due to this discovery, theories positing protein-free replication as preceding the appearance of the genetic code are more plausible. The scope of RNA catalysis in biology and chemistry is discussed, and it is noted that the development of methods to select (or predict) RNA sequences with preassigned catalytic functions would be a major contribution to the study of life's origins.

Single-Cell RNA-Sequencing in Glioma.

PubMed

Johnson, Eli; Dickerson, Katherine L; Connolly, Ian D; Hayden Gephart, Melanie

2018-04-10

In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas. Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas.

Computer-Aided Design of RNA Origami Structures.

PubMed

Sparvath, Steffen L; Geary, Cody W; Andersen, Ebbe S

2017-01-01

RNA nanostructures can be used as scaffolds to organize, combine, and control molecular functionalities, with great potential for applications in nanomedicine and synthetic biology. The single-stranded RNA origami method allows RNA nanostructures to be folded as they are transcribed by the RNA polymerase. RNA origami structures provide a stable framework that can be decorated with functional RNA elements such as riboswitches, ribozymes, interaction sites, and aptamers for binding small molecules or protein targets. The rich library of RNA structural and functional elements combined with the possibility to attach proteins through aptamer-based binding creates virtually limitless possibilities for constructing advanced RNA-based nanodevices.In this chapter we provide a detailed protocol for the single-stranded RNA origami design method using a simple 2-helix tall structure as an example. The first step involves 3D modeling of a double-crossover between two RNA double helices, followed by decoration with tertiary motifs. The second step deals with the construction of a 2D blueprint describing the secondary structure and sequence constraints that serves as the input for computer programs. In the third step, computer programs are used to design RNA sequences that are compatible with the structure, and the resulting outputs are evaluated and converted into DNA sequences to order.

Comprehensive analysis of RNA-protein interactions by high-throughput sequencing-RNA affinity profiling.

PubMed

Tome, Jacob M; Ozer, Abdullah; Pagano, John M; Gheba, Dan; Schroth, Gary P; Lis, John T

2014-06-01

RNA-protein interactions play critical roles in gene regulation, but methods to quantitatively analyze these interactions at a large scale are lacking. We have developed a high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay by adapting a high-throughput DNA sequencer to quantify the binding of fluorescently labeled protein to millions of RNAs anchored to sequenced cDNA templates. Using HiTS-RAP, we measured the affinity of mutagenized libraries of GFP-binding and NELF-E-binding aptamers to their respective targets and identified critical regions of interaction. Mutations additively affected the affinity of the NELF-E-binding aptamer, whose interaction depended mainly on a single-stranded RNA motif, but not that of the GFP aptamer, whose interaction depended primarily on secondary structure.

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex.

PubMed

Pollen, Alex A; Nowakowski, Tomasz J; Shuga, Joe; Wang, Xiaohui; Leyrat, Anne A; Lui, Jan H; Li, Nianzhen; Szpankowski, Lukasz; Fowler, Brian; Chen, Peilin; Ramalingam, Naveen; Sun, Gang; Thu, Myo; Norris, Michael; Lebofsky, Ronald; Toppani, Dominique; Kemp, Darnell W; Wong, Michael; Clerkson, Barry; Jones, Brittnee N; Wu, Shiquan; Knutsson, Lawrence; Alvarado, Beatriz; Wang, Jing; Weaver, Lesley S; May, Andrew P; Jones, Robert C; Unger, Marc A; Kriegstein, Arnold R; West, Jay A A

2014-10-01

Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.

Comparison of traditional phenotypic identification methods with partial 5' 16S rRNA gene sequencing for species-level identification of nonfermenting Gram-negative bacilli.

PubMed

Cloud, Joann L; Harmsen, Dag; Iwen, Peter C; Dunn, James J; Hall, Gerri; Lasala, Paul Rocco; Hoggan, Karen; Wilson, Deborah; Woods, Gail L; Mellmann, Alexander

2010-04-01

Correct identification of nonfermenting Gram-negative bacilli (NFB) is crucial for patient management. We compared phenotypic identifications of 96 clinical NFB isolates with identifications obtained by 5' 16S rRNA gene sequencing. Sequencing identified 88 isolates (91.7%) with >99% similarity to a sequence from the assigned species; 61.5% of sequencing results were concordant with phenotypic results, indicating the usability of sequencing to identify NFB.

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

PubMed Central

2018-01-01

Prediction of taxonomy for marker gene sequences such as 16S ribosomal RNA (rRNA) is a fundamental task in microbiology. Most experimentally observed sequences are diverged from reference sequences of authoritatively named organisms, creating a challenge for prediction methods. I assessed the accuracy of several algorithms using cross-validation by identity, a new benchmark strategy which explicitly models the variation in distances between query sequences and the closest entry in a reference database. When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%), all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA. Accuracy was found to fall rapidly with identity; for example, better methods were found to have V4 genus prediction accuracy of ∼100% at 100% identity but ∼50% at 97% identity. The relationship between identity and taxonomy was quantified as the probability that a rank is the lowest shared by a pair of sequences with a given pair-wise identity. With the V4 region, 95% identity was found to be a twilight zone where taxonomy is highly ambiguous because the probabilities that the lowest shared rank between pairs of sequences is genus, family, order or class are approximately equal. PMID:29682424

Comparative performance of high-density oligonucleotide sequencing and dideoxynucleotide sequencing of HIV type 1 pol from clinical samples.

PubMed

Günthard, H F; Wong, J K; Ignacio, C C; Havlir, D V; Richman, D D

1998-07-01

The performance of the high-density oligonucleotide array methodology (GeneChip) in detecting drug resistance mutations in HIV-1 pol was compared with that of automated dideoxynucleotide sequencing (ABI) of clinical samples, viral stocks, and plasmid-derived NL4-3 clones. Sequences from 29 clinical samples (plasma RNA, n = 17; lymph node RNA, n = 5; lymph node DNA, n = 7) from 12 patients, from 6 viral stock RNA samples, and from 13 NL4-3 clones were generated by both methods. Editing was done independently by a different investigator for each method before comparing the sequences. In addition, NL4-3 wild type (WT) and mutants were mixed in varying concentrations and sequenced by both methods. Overall, a concordance of 99.1% was found for a total of 30,865 bases compared. The comparison of clinical samples (plasma RNA and lymph node RNA and DNA) showed a slightly lower match of base calls, 98.8% for 19,831 nucleotides compared (protease region, 99.5%, n = 8272; RT region, 98.3%, n = 11,316), than for viral stocks and NL4-3 clones (protease region, 99.8%; RT region, 99.5%). Artificial mixing experiments showed a bias toward calling wild-type bases by GeneChip. Discordant base calls are most likely due to differential detection of mixtures. The concordance between GeneChip and ABI was high and appeared dependent on the nature of the templates (directly amplified versus cloned) and the complexity of mixes.

A highly efficient method for extracting next-generation sequencing quality RNA from adipose tissue of recalcitrant animal species.

PubMed

Sharma, Davinder; Golla, Naresh; Singh, Dheer; Onteru, Suneel K

2018-03-01

The next-generation sequencing (NGS) based RNA sequencing (RNA-Seq) and transcriptome profiling offers an opportunity to unveil complex biological processes. Successful RNA-Seq and transcriptome profiling requires a large amount of high-quality RNA. However, NGS-quality RNA isolation is extremely difficult from recalcitrant adipose tissue (AT) with high lipid content and low cell numbers. Further, the amount and biochemical composition of AT lipid varies depending upon the animal species which can pose different degree of resistance to RNA extraction. Currently available approaches may work effectively in one species but can be almost unproductive in another species. Herein, we report a two step protocol for the extraction of NGS quality RNA from AT across a broad range of animal species. © 2017 Wiley Periodicals, Inc.

An efficient and high fidelity method for amplification, cloning and sequencing of complete tospovirus genomic RNA segments

USDA-ARS?s Scientific Manuscript database

Amplification and sequencing of the complete M- and S-RNA segments of Tomato spotted wilt virus and Impatiens necrotic spot virus as a single fragment is useful for whole genome sequencing of tospoviruses co-infecting a single host plant. It avoids issues associated with overlapping amplicon-based ...

Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues

PubMed Central

Lee, Je Hyuk; Daugharthy, Evan R.; Scheiman, Jonathan; Kalhor, Reza; Ferrante, Thomas C.; Terry, Richard; Turczyk, Brian M.; Yang, Joyce L.; Lee, Ho Suk; Aach, John; Zhang, Kun; Church, George M.

2014-01-01

RNA sequencing measures the quantitative change in gene expression over the whole transcriptome, but it lacks spatial context. On the other hand, in situ hybridization provides the location of gene expression, but only for a small number of genes. Here we detail a protocol for genome-wide profiling of gene expression in situ in fixed cells and tissues, in which RNA is converted into cross-linked cDNA amplicons and sequenced manually on a confocal microscope. Unlike traditional RNA-seq our method enriches for context-specific transcripts over house-keeping and/or structural RNA, and it preserves the tissue architecture for RNA localization studies. Our protocol is written for researchers experienced in cell microscopy with minimal computing skills. Library construction and sequencing can be completed within 14 d, with image analysis requiring an additional 2 d. PMID:25675209

Research Techniques Made Simple: Single-Cell RNA Sequencing and its Applications in Dermatology.

PubMed

Wu, Xiaojun; Yang, Bin; Udo-Inyang, Imo; Ji, Suyun; Ozog, David; Zhou, Li; Mi, Qing-Sheng

2018-05-01

RNA sequencing is one of the most highly reliable and reproducible methods of assessing the cell transcriptome. As high-throughput RNA sequencing libraries at the single cell level have recently developed, single cell RNA sequencing has become more feasible and popular in biology research. Single cell RNA sequencing allows investigators to evaluate cell transcriptional profiles at the single cell level. It has become a very useful tool to perform investigations that could not be addressed by other methodologies, such as the assessment of cell-to-cell variation, the identification of rare populations, and the determination of heterogeneity within a cell population. So far, the single cell RNA sequencing technique has been widely applied to embryonic development, immune cell development, and human disease progress and treatment. Here, we describe the history of single cell technology development and its potential application in the field of dermatology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

ModeRNA: a tool for comparative modeling of RNA 3D structure

PubMed Central

Rother, Magdalena; Rother, Kristian; Puton, Tomasz; Bujnicki, Janusz M.

2011-01-01

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available. PMID:21300639

Comparison of various RNA extraction methods, cDNA preparation and isolation of calmodulin gene from a highly melanized isolate of apple leaf blotch fungus Marssonina coronaria.

PubMed

Chauhan, Arjun; Sharma, J N; Modgil, Manju; Siddappa, Sundaresha

2018-05-29

Marssonina coronaria causes apple blotch disease resulting in severe premature defoliation, and is distributed in many leading apple-growing areas in the world. Effective, reliable and high-quality RNA extraction is an indispensable procedure in any molecular biology study. No method currently exists for RNA extraction from M. coronaria that produces a high quantity of melanin-free RNA. Therefore, we evaluated eight RNA extraction methods including manual and commercial kits, to yield a sufficient quantity of high-quality and melanin-free RNA. Manual methods used here resulted in low quality and black colored RNA pellets showing the presence of melanin, despite all the modifications employed to original procedures. However, these methods when coupled with clean up resulted in melanin-free RNA. On the other hand, all commercial kits used were able to yield high-quality melanin-free RNA having variable yields. TRIzol™ Reagent + RNA Clean & Concentrator™-5 and Ambion-PureLink® RNA Mini Kit were found to be the best methods as the RNA extracted with these methods from 15 day old fungal culture grown on solid medium were free of melanin with good yield. RNA extracted by this improved methodology was applied for RT-PCR, subsequent PCR amplification, and isolation of calmodulin gene sequences from M. coronaria and infected apple leaf pieces. These methods are more time effective than traditional methods and take only an hour to complete. To our knowledge, this is the first report on the method of isolation of high-quality RNA for cDNA synthesis as well as isolation of the calmodulin gene sequence from this fungus. Copyright © 2018 Elsevier B.V. All rights reserved.

Mycobacterial RNA isolation optimized for non-coding RNA: high fidelity isolation of 5S rRNA from Mycobacterium bovis BCG reveals novel post-transcriptional processing and a complete spectrum of modified ribonucleosides.

PubMed

Hia, Fabian; Chionh, Yok Hian; Pang, Yan Ling Joy; DeMott, Michael S; McBee, Megan E; Dedon, Peter C

2015-03-11

A major challenge in the study of mycobacterial RNA biology is the lack of a comprehensive RNA isolation method that overcomes the unusual cell wall to faithfully yield the full spectrum of non-coding RNA (ncRNA) species. Here, we describe a simple and robust procedure optimized for the isolation of total ncRNA, including 5S, 16S and 23S ribosomal RNA (rRNA) and tRNA, from mycobacteria, using Mycobacterium bovis BCG to illustrate the method. Based on a combination of mechanical disruption and liquid and solid-phase technologies, the method produces all major species of ncRNA in high yield and with high integrity, enabling direct chemical and sequence analysis of the ncRNA species. The reproducibility of the method with BCG was evident in bioanalyzer electrophoretic analysis of isolated RNA, which revealed quantitatively significant differences in the ncRNA profiles of exponentially growing and non-replicating hypoxic bacilli. The method also overcame an historical inconsistency in 5S rRNA isolation, with direct sequencing revealing a novel post-transcriptional processing of 5S rRNA to its functional form and with chemical analysis revealing seven post-transcriptional ribonucleoside modifications in the 5S rRNA. This optimized RNA isolation procedure thus provides a means to more rigorously explore the biology of ncRNA species in mycobacteria. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Zipper plot: visualizing transcriptional activity of genomic regions.

PubMed

Avila Cobos, Francisco; Anckaert, Jasper; Volders, Pieter-Jan; Everaert, Celine; Rombaut, Dries; Vandesompele, Jo; De Preter, Katleen; Mestdagh, Pieter

2017-05-02

Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs. To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIP-sequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot. Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Using publicly available RNA-seq data, we found more than one hundred cases where junction reads connected protein-coding gene exons with a downstream mono-exonic lncRNA, revealing the need for a careful evaluation of lncRNA 5'-boundaries. Our method is implemented using the statistical programming language R and is freely available as a webtool.

rpoB Gene Sequencing for Identification of Corynebacterium Species

PubMed Central

Khamis, Atieh; Raoult, Didier; La Scola, Bernard

2004-01-01

The genus Corynebacterium is a heterogeneous group of species comprising human and animal pathogens and environmental bacteria. It is defined on the basis of several phenotypic characters and the results of DNA-DNA relatedness and, more recently, 16S rRNA gene sequencing. However, the 16S rRNA gene is not polymorphic enough to ensure reliable phylogenetic studies and needs to be completely sequenced for accurate identification. The almost complete rpoB sequences of 56 Corynebacterium species were determined by both PCR and genome walking methods. In all cases the percent similarities between different species were lower than those observed by 16S rRNA gene sequencing, even for those species with degrees of high similarity. Several clusters supported by high bootstrap values were identified. In order to propose a method for strain identification which does not require sequencing of the complete rpoB sequence (approximately 3,500 bp), we identified an area with a high degree of polymorphism, bordered by conserved sequences that can be used as universal primers for PCR amplification and sequencing. The sequence of this fragment (434 to 452 bp) allows accurate species identification and may be used in the future for routine sequence-based identification of Corynebacterium species. PMID:15364970

An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures

PubMed Central

Zandi, Kasra; Butler, Gregory; Kharma, Nawwaf

2016-01-01

Computational design of RNA sequences that fold into targeted secondary structures has many applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule is made of different types of secondary structure elements and an important RNA element named pseudoknot plays a key role in stabilizing the functional form of the molecule. However, due to the computational complexities associated with characterizing pseudoknotted RNA structures, most of the existing RNA sequence designer algorithms generally ignore this important structural element and therefore limit their applications. In this paper we present a new algorithm to design RNA sequences for pseudoknotted secondary structures. We use NUPACK as the folding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, and describe a new adaptive defect weighted sampling algorithm named Enzymer to design low ensemble defect RNA sequences for targeted secondary structures including pseudoknots. We used a biological data set of 201 pseudoknotted structures from the Pseudobase library to benchmark the performance of our algorithm. We compared the quality characteristics of the RNA sequences we designed by Enzymer with the results obtained from the state of the art MODENA and antaRNA. Our results show our method succeeds more frequently than MODENA and antaRNA do, and generates sequences that have lower ensemble defect, lower probability defect and higher thermostability. Finally by using Enzymer and by constraining the design to a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequences for a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download at https://bitbucket.org/casraz/enzymer. PMID:27499762

RoboOligo: software for mass spectrometry data to support manual and de novo sequencing of post-transcriptionally modified ribonucleic acids

PubMed Central

Sample, Paul J.; Gaston, Kirk W.; Alfonzo, Juan D.; Limbach, Patrick A.

2015-01-01

Ribosomal ribonucleic acid (RNA), transfer RNA and other biological or synthetic RNA polymers can contain nucleotides that have been modified by the addition of chemical groups. Traditional Sanger sequencing methods cannot establish the chemical nature and sequence of these modified-nucleotide containing oligomers. Mass spectrometry (MS) has become the conventional approach for determining the nucleotide composition, modification status and sequence of modified RNAs. Modified RNAs are analyzed by MS using collision-induced dissociation tandem mass spectrometry (CID MS/MS), which produces a complex dataset of oligomeric fragments that must be interpreted to identify and place modified nucleosides within the RNA sequence. Here we report the development of RoboOligo, an interactive software program for the robust analysis of data generated by CID MS/MS of RNA oligomers. There are three main functions of RoboOligo: (i) automated de novo sequencing via the local search paradigm. (ii) Manual sequencing with real-time spectrum labeling and cumulative intensity scoring. (iii) A hybrid approach, coined ‘variable sequencing’, which combines the user intuition of manual sequencing with the high-throughput sampling of automated de novo sequencing. PMID:25820423

Improve the prediction of RNA-binding residues using structural neighbours.

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.

The rRNA evolution and procaryotic phylogeny

NASA Technical Reports Server (NTRS)

Fox, G. E.

1986-01-01

Studies of ribosomal RNA primary structure allow reconstruction of phylogenetic trees for prokaryotic organisms. Such studies reveal major dichotomy among the bacteria that separates them into eubacteria and archaebacteria. Both groupings are further segmented into several major divisions. The results obtained from 5S rRNA sequences are essentially the same as those obtained with the 16S rRNA data. In the case of Gram negative bacteria the ribosomal RNA sequencing results can also be directly compared with hybridization studies and cytochrome c sequencing studies. There is again excellent agreement among the several methods. It seems likely then that the overall picture of microbial phylogeny that is emerging from the RNA sequence studies is a good approximation of the true history of these organisms. The RNA data allow examination of the evolutionary process in a semi-quantitative way. The secondary structures of these RNAs are largely established. As a result it is possible to recognize examples of local structural evolution. Evolutionary pathways accounting for these events can be proposed and their probability can be assessed.

Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

PubMed

Williams, Philip H; Eyles, Rod; Weiller, Georg

2012-01-01

MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

Miniprimer PCR, a New Lens for Viewing the Microbial World▿ †

PubMed Central

Isenbarger, Thomas A.; Finney, Michael; Ríos-Velázquez, Carlos; Handelsman, Jo; Ruvkun, Gary

2008-01-01

Molecular methods based on the 16S rRNA gene sequence are used widely in microbial ecology to reveal the diversity of microbial populations in environmental samples. Here we show that a new PCR method using an engineered polymerase and 10-nucleotide “miniprimers” expands the scope of detectable sequences beyond those detected by standard methods using longer primers and Taq polymerase. After testing the method in silico to identify divergent ribosomal genes in previously cloned environmental sequences, we applied the method to soil and microbial mat samples, which revealed novel 16S rRNA gene sequences that would not have been detected with standard primers. Deeply divergent sequences were discovered with high frequency and included representatives that define two new division-level taxa, designated CR1 and CR2, suggesting that miniprimer PCR may reveal new dimensions of microbial diversity. PMID:18083877

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

ERIC Educational Resources Information Center

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

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

PubMed Central

Griffith, Malachi; Walker, Jason R.; Spies, Nicholas C.; Ainscough, Benjamin J.; Griffith, Obi L.

2015-01-01

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. PMID:26248053

Development and Verification of an RNA Sequencing (RNA-Seq) Assay for the Detection of Gene Fusions in Tumors.

PubMed

Winters, Jennifer L; Davila, Jaime I; McDonald, Amber M; Nair, Asha A; Fadra, Numrah; Wehrs, Rebecca N; Thomas, Brittany C; Balcom, Jessica R; Jin, Long; Wu, Xianglin; Voss, Jesse S; Klee, Eric W; Oliver, Gavin R; Graham, Rondell P; Neff, Jadee L; Rumilla, Kandelaria M; Aypar, Umut; Kipp, Benjamin R; Jenkins, Robert B; Jen, Jin; Halling, Kevin C

2018-06-13

We assessed the performance characteristics of an RNA sequencing (RNA-Seq) assay designed to detect gene fusions in 571 genes to help manage patients with cancer. Polyadenylated RNA was converted to cDNA, which was then used to prepare next-generation sequencing libraries that were sequenced on an Illumina HiSeq 2500 instrument and analyzed with an in-house developed bioinformatic pipeline. The assay identified 38 of 41 gene fusions detected by another method, such as fluorescence in situ hybridization or RT-PCR, for a sensitivity of 93%. No false-positive gene fusions were identified in 15 normal tissue specimens and 10 tumor specimens that were negative for fusions by RNA sequencing or Mate Pair NGS (100% specificity). The assay also identified 22 fusions in 17 tumor specimens that had not been detected by other methods. Eighteen of the 22 fusions had not previously been described. Good intra-assay and interassay reproducibility was observed with complete concordance for the presence or absence of gene fusions in replicates. The analytical sensitivity of the assay was tested by diluting RNA isolated from gene fusion-positive cases with fusion-negative RNA. Gene fusions were generally detectable down to 12.5% dilutions for most fusions and as little as 3% for some fusions. This assay can help identify fusions in patients with cancer; these patients may in turn benefit from both US Food and Drug Administration-approved and investigational targeted therapies. Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

PubMed

Danaee, Padideh; Rouches, Mason; Wiley, Michelle; Deng, Dezhong; Huang, Liang; Hendrix, David

2018-05-09

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here, we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, 'bpRNA-1m', of over 100 000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar (≥90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.

ChIP-seq and RNA-seq methods to study circadian control of transcription in mammals

PubMed Central

Takahashi, Joseph S.; Kumar, Vivek; Nakashe, Prachi; Koike, Nobuya; Huang, Hung-Chung; Green, Carla B.; Kim, Tae-Kyung

2015-01-01

Genome-wide analyses have revolutionized our ability to study the transcriptional regulation of circadian rhythms. The advent of next-generation sequencing methods has facilitated the use of two such technologies, ChIP-seq and RNA-seq. In this chapter, we describe detailed methods and protocols for these two techniques, with emphasis on their usage in circadian rhythm experiments in the mouse liver, a major target organ of the circadian clock system. Critical factors for these methods are highlighted and issues arising with time series samples for ChIP-seq and RNA-seq are discussed. Finally detailed protocols for library preparation suitable for Illumina sequencing platforms are presented. PMID:25662462

[Influence of antisense RNA and sequences of viral transactivators traps on RNA synthesis of HTLV-1 virus].

PubMed

Borisenko, A S; Kotus, E V; Kaloshin, A A

2008-01-01

Significant number of scientific publications devoted to inhibition of viral replication by antisense RNA (asRNA) genes shows that this approach is useful for gene therapy of viral infections. To investigate the possibility of suppression of HTLV-1 virus reproduction by asRNA we constructed recombinant plasmids containing asRNA genes against U3 long terminal repeats region and X gene under the control of promoter of myeloproliferative sarcoma virus (MPSV) or without such promoter. Using stable calcium-phosphate transfection method with subsequent selection in the presence of G-418, RaHOS line-based cell clones carrying both asRNA genes and sequences able to bind HTLV-1 transactivator proteins (i.e. "traps" of viral transactivators, TVT) were obtained. Data from dot-hybridization analysis of viral RNA extracted from RaHOS cell clones showed that TVT sequences are able to suppress the viral RNA synthesis on 90% and asRNA against X gene synthesis--on 50%.

Fast, accurate and easy-to-pipeline methods for amplicon sequence processing

NASA Astrophysics Data System (ADS)

Antonielli, Livio; Sessitsch, Angela

2016-04-01

Next generation sequencing (NGS) technologies established since years as an essential resource in microbiology. While on the one hand metagenomic studies can benefit from the continuously increasing throughput of the Illumina (Solexa) technology, on the other hand the spreading of third generation sequencing technologies (PacBio, Oxford Nanopore) are getting whole genome sequencing beyond the assembly of fragmented draft genomes, making it now possible to finish bacterial genomes even without short read correction. Besides (meta)genomic analysis next-gen amplicon sequencing is still fundamental for microbial studies. Amplicon sequencing of the 16S rRNA gene and ITS (Internal Transcribed Spacer) remains a well-established widespread method for a multitude of different purposes concerning the identification and comparison of archaeal/bacterial (16S rRNA gene) and fungal (ITS) communities occurring in diverse environments. Numerous different pipelines have been developed in order to process NGS-derived amplicon sequences, among which Mothur, QIIME and USEARCH are the most well-known and cited ones. The entire process from initial raw sequence data through read error correction, paired-end read assembly, primer stripping, quality filtering, clustering, OTU taxonomic classification and BIOM table rarefaction as well as alternative "normalization" methods will be addressed. An effective and accurate strategy will be presented using the state-of-the-art bioinformatic tools and the example of a straightforward one-script pipeline for 16S rRNA gene or ITS MiSeq amplicon sequencing will be provided. Finally, instructions on how to automatically retrieve nucleotide sequences from NCBI and therefore apply the pipeline to targets other than 16S rRNA gene (Greengenes, SILVA) and ITS (UNITE) will be discussed.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells.

PubMed

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. © 2018 Han et al.; Published by Cold Spring Harbor Laboratory Press.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells

PubMed Central

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. PMID:29208629

SHAPE Selection (SHAPES) enrich for RNA structure signal in SHAPE sequencing-based probing data

PubMed Central

Poulsen, Line Dahl; Kielpinski, Lukasz Jan; Salama, Sofie R.; Krogh, Anders; Vinther, Jeppe

2015-01-01

Selective 2′ Hydroxyl Acylation analyzed by Primer Extension (SHAPE) is an accurate method for probing of RNA secondary structure. In existing SHAPE methods, the SHAPE probing signal is normalized to a no-reagent control to correct for the background caused by premature termination of the reverse transcriptase. Here, we introduce a SHAPE Selection (SHAPES) reagent, N-propanone isatoic anhydride (NPIA), which retains the ability of SHAPE reagents to accurately probe RNA structure, but also allows covalent coupling between the SHAPES reagent and a biotin molecule. We demonstrate that SHAPES-based selection of cDNA–RNA hybrids on streptavidin beads effectively removes the large majority of background signal present in SHAPE probing data and that sequencing-based SHAPES data contain the same amount of RNA structure data as regular sequencing-based SHAPE data obtained through normalization to a no-reagent control. Moreover, the selection efficiently enriches for probed RNAs, suggesting that the SHAPES strategy will be useful for applications with high-background and low-probing signal such as in vivo RNA structure probing. PMID:25805860

Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.

PubMed

Zou, Quan; Guo, Jiasheng; Ju, Ying; Wu, Meihong; Zeng, Xiangxiang; Hong, Zhiling

2015-11-01

tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A new predictor, tRNA-Predict, was designed. We obtained real and pseudo-tRNA sequences as training data sets using tRNAScan-SE and constructed three different tRNA feature sets. We then set up an ensemble classifier, LibMutil, to predict tRNAs from the training data. The positive data set of 623 tRNA sequences was obtained from tRNAdb 2009 and the negative data set was the false positive tRNAs predicted by tRNAscan-SE. Our in silico experiments revealed a prediction accuracy rate of 95.1 % for tRNA-Predict using 10-fold cross-validation. tRNA-Predict was developed to distinguish functional tRNAs from pseudo-tRNAs rather than to predict tRNAs from a genome-wide scan. However, tRNA-Predict can work with the output of tRNAscan-SE, which is a genome-wide scanning method, to improve the tRNAscan-SE annotation results. The tRNA-Predict web server is accessible at http://datamining.xmu.edu.cn/∼gjs/tRNA-Predict. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Droplet Microfluidic Device Fabrication and Use for Isothermal Amplification and Detection of MicroRNA.

PubMed

Giuffrida, Maria Chiara; D'Agata, Roberta; Spoto, Giuseppe

2017-01-01

Droplet microfluidics combined with the isothermal circular strand displacement polymerization (ICSDP) represents a powerful new technique to detect both single-stranded DNA and microRNA sequences. The method here described helps in overcoming some drawbacks of the lately introduced droplet polymerase chain reaction (PCR) amplification when implemented in microfluidic devices. The method also allows the detection of nanoliter droplets of nucleic acids sequences solutions, with a particular attention to microRNA sequences that are detected at the picomolar level. The integration of the ICSDP amplification protocol in droplet microfluidic devices reduces the time of analysis and the amount of sample required. In addition, there is also the possibility to design parallel analyses to be integrated in portable devices.

High-throughput and site-specific identification of 2'-O-methylation sites using ribose oxidation sequencing (RibOxi-seq).

PubMed

Zhu, Yinzhou; Pirnie, Stephan P; Carmichael, Gordon G

2017-08-01

Ribose methylation (2'- O -methylation, 2'- O Me) occurs at high frequencies in rRNAs and other small RNAs and is carried out using a shared mechanism across eukaryotes and archaea. As RNA modifications are important for ribosome maturation, and alterations in these modifications are associated with cellular defects and diseases, it is important to characterize the landscape of 2'- O -methylation. Here we report the development of a highly sensitive and accurate method for ribose methylation detection using next-generation sequencing. A key feature of this method is the generation of RNA fragments with random 3'-ends, followed by periodate oxidation of all molecules terminating in 2',3'-OH groups. This allows only RNAs harboring 2'-OMe groups at their 3'-ends to be sequenced. Although currently requiring microgram amounts of starting material, this method is robust for the analysis of rRNAs even at low sequencing depth. © 2017 Zhu et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Peregrine: A rapid and unbiased method to produce strand-specific RNA-Seq libraries from small quantities of starting material.

PubMed

Langevin, Stanley A; Bent, Zachary W; Solberg, Owen D; Curtis, Deanna J; Lane, Pamela D; Williams, Kelly P; Schoeniger, Joseph S; Sinha, Anupama; Lane, Todd W; Branda, Steven S

2013-04-01

Use of second generation sequencing (SGS) technologies for transcriptional profiling (RNA-Seq) has revolutionized transcriptomics, enabling measurement of RNA abundances with unprecedented specificity and sensitivity and the discovery of novel RNA species. Preparation of RNA-Seq libraries requires conversion of the RNA starting material into cDNA flanked by platform-specific adaptor sequences. Each of the published methods and commercial kits currently available for RNA-Seq library preparation suffers from at least one major drawback, including long processing times, large starting material requirements, uneven coverage, loss of strand information and high cost. We report the development of a new RNA-Seq library preparation technique that produces representative, strand-specific RNA-Seq libraries from small amounts of starting material in a fast, simple and cost-effective manner. Additionally, we have developed a new quantitative PCR-based assay for precisely determining the number of PCR cycles to perform for optimal enrichment of the final library, a key step in all SGS library preparation workflows.

Swellix: a computational tool to explore RNA conformational space.

PubMed

Sloat, Nathan; Liu, Jui-Wen; Schroeder, Susan J

2017-11-21

The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures. Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem.

Comparison between rpoB and 16S rRNA Gene Sequencing for Molecular Identification of 168 Clinical Isolates of Corynebacterium

PubMed Central

Khamis, Atieh; Raoult, Didier; La Scola, Bernard

2005-01-01

Higher proportions (91%) of 168 corynebacterial isolates were positively identified by partial rpoB gene determination than by that based on 16S rRNA gene sequences. This method is thus a simple, molecular-analysis-based method for identification of corynebacteria, but it should be used in conjunction with other tests for definitive identification. PMID:15815024

The nucleotide sequence of the putative transcription initiation site of a cloned ribosomal RNA gene of the mouse.

PubMed Central

Urano, Y; Kominami, R; Mishima, Y; Muramatsu, M

1980-01-01

Approximately one kilobase pairs surrounding and upstream the transcription initiation site of a cloned ribosomal DNA (rDNA) of the mouse were sequenced. The putative transcription initiation site was determined by two independent methods: one nuclease S1 protection and the other reverse transcriptase elongation mapping using isolated 45S ribosomal RNA precursor (45S RNA) and appropriate restriction fragments of rDNA. Both methods gave an identical result; 45S RNA had a structure starting from ACTCTTAG---. Characteristically, mouse rDNA had many T clusters (greater than or equal to 5) upstream the initiation site, the longest being 21 consecutive T's. A pentadecanucleotide, TGCCTCCCGAGTGCA, appeared twice within 260 nucleotides upstream the putative initiation site. No such characteristic sequences were found downstream this site. Little similarity was found in the upstream of the transcription initiation site between the mouse, Xenopus laevis and Saccharomyces cerevisiae rDNA. Images PMID:6162156

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

PubMed

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

From clinical sample to complete genome: Comparing methods for the extraction of HIV-1 RNA for high-throughput deep sequencing.

PubMed

Cornelissen, Marion; Gall, Astrid; Vink, Monique; Zorgdrager, Fokla; Binter, Špela; Edwards, Stephanie; Jurriaans, Suzanne; Bakker, Margreet; Ong, Swee Hoe; Gras, Luuk; van Sighem, Ard; Bezemer, Daniela; de Wolf, Frank; Reiss, Peter; Kellam, Paul; Berkhout, Ben; Fraser, Christophe; van der Kuyl, Antoinette C

2017-07-15

The BEEHIVE (Bridging the Evolution and Epidemiology of HIV in Europe) project aims to analyse nearly-complete viral genomes from >3000 HIV-1 infected Europeans using high-throughput deep sequencing techniques to investigate the virus genetic contribution to virulence. Following the development of a computational pipeline, including a new de novo assembler for RNA virus genomes, to generate larger contiguous sequences (contigs) from the abundance of short sequence reads that characterise the data, another area that determines genome sequencing success is the quality and quantity of the input RNA. A pilot experiment with 125 patient plasma samples was performed to investigate the optimal method for isolation of HIV-1 viral RNA for long amplicon genome sequencing. Manual isolation with the QIAamp Viral RNA Mini Kit (Qiagen) was superior over robotically extracted RNA using either the QIAcube robotic system, the mSample Preparation Systems RNA kit with automated extraction by the m2000sp system (Abbott Molecular), or the MagNA Pure 96 System in combination with the MagNA Pure 96 Instrument (Roche Diagnostics). We scored amplification of a set of four HIV-1 amplicons of ∼1.9, 3.6, 3.0 and 3.5kb, and subsequent recovery of near-complete viral genomes. Subsequently, 616 BEEHIVE patient samples were analysed to determine factors that influence successful amplification of the genome in four overlapping amplicons using the QIAamp Viral RNA Kit for viral RNA isolation. Both low plasma viral load and high sample age (stored before 1999) negatively influenced the amplification of viral amplicons >3kb. A plasma viral load of >100,000 copies/ml resulted in successful amplification of all four amplicons for 86% of the samples, this value dropped to only 46% for samples with viral loads of <20,000 copies/ml. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Sensitivity of BRCA1/2 testing in high-risk breast/ovarian/male breast cancer families: little contribution of comprehensive RNA/NGS panel testing.

PubMed

Byers, Helen; Wallis, Yvonne; van Veen, Elke M; Lalloo, Fiona; Reay, Kim; Smith, Philip; Wallace, Andrew J; Bowers, Naomi; Newman, William G; Evans, D Gareth

2016-11-01

The sensitivity of testing BRCA1 and BRCA2 remains unresolved as the frequency of deep intronic splicing variants has not been defined in high-risk familial breast/ovarian cancer families. This variant category is reported at significant frequency in other tumour predisposition genes, including NF1 and MSH2. We carried out comprehensive whole gene RNA analysis on 45 high-risk breast/ovary and male breast cancer families with no identified pathogenic variant on exonic sequencing and copy number analysis of BRCA1/2. In addition, we undertook variant screening of a 10-gene high/moderate risk breast/ovarian cancer panel by next-generation sequencing. DNA testing identified the causative variant in 50/56 (89%) breast/ovarian/male breast cancer families with Manchester scores of ≥50 with two variants being confirmed to affect splicing on RNA analysis. RNA sequencing of BRCA1/BRCA2 on 45 individuals from high-risk families identified no deep intronic variants and did not suggest loss of RNA expression as a cause of lost sensitivity. Panel testing in 42 samples identified a known RAD51D variant, a high-risk ATM variant in another breast ovary family and a truncating CHEK2 mutation. Current exonic sequencing and copy number analysis variant detection methods of BRCA1/2 have high sensitivity in high-risk breast/ovarian cancer families. Sequence analysis of RNA does not identify any variants undetected by current analysis of BRCA1/2. However, RNA analysis clarified the pathogenicity of variants of unknown significance detected by current methods. The low diagnostic uplift achieved through sequence analysis of the other known breast/ovarian cancer susceptibility genes indicates that further high-risk genes remain to be identified.

Redescriptions of three trachelocercid ciliates (Protista, Ciliophora, Karyorelictea), with notes on their phylogeny based on small subunit rRNA gene sequences.

PubMed

Yan, Ying; Xu, Yuan; Yi, Zhenzhen; Warren, Alan

2013-09-01

Three trachelocercid ciliates, Kovalevaia sulcata (Kovaleva, 1966) Foissner, 1997, Trachelocerca sagitta (Müller, 1786) Ehrenberg, 1840 and Trachelocerca ditis (Wright, 1982) Foissner, 1996, isolated from two coastal habitats at Qingdao, China, were investigated using live observation and silver impregnation methods. Data on their infraciliature and morphology are supplied. The small subunit rRNA (SSU rRNA) genes of K. sulcata and Trachelocerca sagitta were sequenced for the first time. Phylogenetic analyses based on SSU rRNA gene sequence data indicate that both organisms, and the previously sequenced Trachelocerca ditis, are located within the trachelocercid assemblage and that K. sulcata is sister to an unidentified taxon forming a clade that is basal to the core trachelocercids.

A Method that Will Captivate U.

PubMed

Martin, Sophie; Coller, Jeff

2015-09-03

In an age of next-generation sequencing, the ability to purify RNA transcripts has become a critical issue. In this issue, Duffy et al. (2015) improve on a pre-existing technique of RNA labeling and purification by 4-thiouridine tagging. By increasing the efficiency of RNA capture, this method will enhance the ability to study RNA dynamics, especially for transcripts normally inefficiently captured by previous methods. Copyright © 2015 Elsevier Inc. All rights reserved.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Nuclear counterparts of the cytoplasmic mitochondrial 12S rRNA gene: a problem of ancient DNA and molecular phylogenies.

PubMed

van der Kuyl, A C; Kuiken, C L; Dekker, J T; Perizonius, W R; Goudsmit, J

1995-06-01

Monkey mummy bones and teeth originating from the North Saqqara Baboon Galleries (Egypt), soft tissue from a mummified baboon in a museum collection, and nineteenth/twentieth-century skin fragments from mangabeys were used for DNA extraction and PCR amplification of part of the mitochondrial 12S rRNA gene. Sequences aligning with the 12S rRNA gene were recovered but were only distantly related to contemporary monkey mitochondrial 12S rRNA sequences. However, many of these sequences were identical or closely related to human nuclear DNA sequences resembling mitochondrial 12S rRNA (isolated from a cell line depleted in mitochondria) and therefore have to be considered contamination. Subsequently in a separate study we were able to recover genuine mitochondrial 12S rRNA sequences from many extant species of nonhuman Old World primates and sequences closely resembling the human nuclear integrations. Analysis of all sequences by the neighbor-joining (NJ) method indicated that mitochondrial DNA sequences and their nuclear counterparts can be divided into two distinct clusters. One cluster contained all temporary cytoplasmic mitochondrial DNA sequences and approximately half of the monkey nuclear mitochondriallike sequences. A second cluster contained most human nuclear sequences and the other half of monkey nuclear sequences with a separate branch leading to human and gorilla mitochondrial and nuclear sequences. Sequences recovered from ancient materials were equally divided between the two clusters. These results constitute a warning for when working with ancient DNA or performing phylogenetic analysis using mitochondrial DNA as a target sequence: Nuclear counterparts of mitochondrial genes may lead to faulty interpretation of results.

Determination of differential gene expression profiles in superficial and deeper zones of mature rat articular cartilage using RNA sequencing of laser microdissected tissue specimens.

PubMed

Mori, Yoshifumi; Chung, Ung-Il; Tanaka, Sakae; Saito, Taku

2014-01-01

Superficial zone (SFZ) cells, which are morphologically and functionally distinct from chondrocytes in deeper zones, play important roles in the maintenance of articular cartilage. Here, we established an easy and reliable method for performance of laser microdissection (LMD) on cryosections of mature rat articular cartilage using an adhesive membrane. We further examined gene expression profiles in the SFZ and the deeper zones of articular cartilage by performing RNA sequencing (RNA-seq). We validated sample collection methods, RNA amplification and the RNA-seq data using real-time RT-PCR. The combined data provide comprehensive information regarding genes specifically expressed in the SFZ or deeper zones, as well as a useful protocol for expression analysis of microsamples of hard tissues.

Optimizing exosomal RNA isolation for RNA-Seq analyses of archival sera specimens.

PubMed

Prendergast, Emily N; de Souza Fonseca, Marcos Abraão; Dezem, Felipe Segato; Lester, Jenny; Karlan, Beth Y; Noushmehr, Houtan; Lin, Xianzhi; Lawrenson, Kate

2018-01-01

Exosomes are endosome-derived membrane vesicles that contain proteins, lipids, and nucleic acids. The exosomal transcriptome mediates intercellular communication, and represents an understudied reservoir of novel biomarkers for human diseases. Next-generation sequencing enables complex quantitative characterization of exosomal RNAs from diverse sources. However, detailed protocols describing exosome purification for preparation of exosomal RNA-sequence (RNA-Seq) libraries are lacking. Here we compared methods for isolation of exosomes and extraction of exosomal RNA from human cell-free serum, as well as strategies for attaining equal representation of samples within pooled RNA-Seq libraries. We compared commercial precipitation with ultracentrifugation for exosome purification and confirmed the presence of exosomes via both transmission electron microscopy and immunoblotting. Exosomal RNA extraction was compared using four different RNA purification methods. We determined the minimal starting volume of serum required for exosome preparation and showed that high quality exosomal RNA can be isolated from sera stored for over a decade. Finally, RNA-Seq libraries were successfully prepared with exosomal RNAs extracted from human cell-free serum, cataloguing both coding and non-coding exosomal transcripts. This method provides researchers with strategic options to prepare RNA-Seq libraries and compare RNA-Seq data quantitatively from minimal volumes of fresh and archival human cell-free serum for disease biomarker discovery.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

PubMed

Xu, Weijia; Ozer, Stuart; Gutell, Robin R

2009-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA

PubMed Central

Xu, Weijia; Ozer, Stuart; Gutell, Robin R.

2010-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure. PMID:20502534

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

PubMed

Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

2015-08-01

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

Emergence of a replicating species from an in vitro RNA evolution reaction

NASA Technical Reports Server (NTRS)

Breaker, R. R.; Joyce, G. F.

1994-01-01

The technique of self-sustained sequence replication allows isothermal amplification of DNA and RNA molecules in vitro. This method relies on the activities of a reverse transcriptase and a DNA-dependent RNA polymerase to amplify specific nucleic acid sequences. We have modified this protocol to allow selective amplification of RNAs that catalyze a particular chemical reaction. During an in vitro RNA evolution experiment employing this modified system, a unique class of "selfish" RNAs emerged and replicated to the exclusion of the intended RNAs. Members of this class of selfish molecules, termed RNA Z, amplify efficiently despite their inability to catalyze the target chemical reaction. Their amplification requires the action of both reverse transcriptase and RNA polymerase and involves the synthesis of both DNA and RNA replication intermediates. The proposed amplification mechanism for RNA Z involves the formation of a DNA hairpin that functions as a template for transcription by RNA polymerase. This arrangement links the two strands of the DNA, resulting in the production of RNA transcripts that contain an embedded RNA polymerase promoter sequence.

Inverse PCR-based method for isolating novel SINEs from genome.

PubMed

Han, Yawei; Chen, Liping; Guan, Lihong; He, Shunping

2014-04-01

Short interspersed elements (SINEs) are moderately repetitive DNA sequences in eukaryotic genomes. Although eukaryotic genomes contain numerous SINEs copy, it is very difficult and laborious to isolate and identify them by the reported methods. In this study, the inverse PCR was successfully applied to isolate SINEs from Opsariichthys bidens genome in Eastern Asian Cyprinid. A group of SINEs derived from tRNA(Ala) molecular had been identified, which were named Opsar according to Opsariichthys. SINEs characteristics were exhibited in Opsar, which contained a tRNA(Ala)-derived region at the 5' end, a tRNA-unrelated region, and AT-rich region at the 3' end. The tRNA-derived region of Opsar shared 76 % sequence similarity with tRNA(Ala) gene. This result indicated that Opsar could derive from the inactive or pseudogene of tRNA(Ala). The reliability of method was tested by obtaining C-SINE, Ct-SINE, and M-SINEs from Ctenopharyngodon idellus, Megalobrama amblycephala, and Cyprinus carpio genomes. This method is simpler than the previously reported, which successfully omitted many steps, such as preparation of probes, construction of genomic libraries, and hybridization.

RNA-sequence data normalization through in silico prediction of reference genes: the bacterial response to DNA damage as case study.

PubMed

Berghoff, Bork A; Karlsson, Torgny; Källman, Thomas; Wagner, E Gerhart H; Grabherr, Manfred G

2017-01-01

Measuring how gene expression changes in the course of an experiment assesses how an organism responds on a molecular level. Sequencing of RNA molecules, and their subsequent quantification, aims to assess global gene expression changes on the RNA level (transcriptome). While advances in high-throughput RNA-sequencing (RNA-seq) technologies allow for inexpensive data generation, accurate post-processing and normalization across samples is required to eliminate any systematic noise introduced by the biochemical and/or technical processes. Existing methods thus either normalize on selected known reference genes that are invariant in expression across the experiment, assume that the majority of genes are invariant, or that the effects of up- and down-regulated genes cancel each other out during the normalization. Here, we present a novel method, moose 2 , which predicts invariant genes in silico through a dynamic programming (DP) scheme and applies a quadratic normalization based on this subset. The method allows for specifying a set of known or experimentally validated invariant genes, which guides the DP. We experimentally verified the predictions of this method in the bacterium Escherichia coli , and show how moose 2 is able to (i) estimate the expression value distances between RNA-seq samples, (ii) reduce the variation of expression values across all samples, and (iii) to subsequently reveal new functional groups of genes during the late stages of DNA damage. We further applied the method to three eukaryotic data sets, on which its performance compares favourably to other methods. The software is implemented in C++ and is publicly available from http://grabherr.github.io/moose2/. The proposed RNA-seq normalization method, moose 2 , is a valuable alternative to existing methods, with two major advantages: (i) in silico prediction of invariant genes provides a list of potential reference genes for downstream analyses, and (ii) non-linear artefacts in RNA-seq data are handled adequately to minimize variations between replicates.

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

Phylogenetic relationships of Malassezia species based on multilocus sequence analysis.

PubMed

Castellá, Gemma; Coutinho, Selene Dall' Acqua; Cabañes, F Javier

2014-01-01

Members of the genus Malassezia are lipophilic basidiomycetous yeasts, which are part of the normal cutaneous microbiota of humans and other warm-blooded animals. Currently, this genus consists of 14 species that have been characterized by phenetic and molecular methods. Although several molecular methods have been used to identify and/or differentiate Malassezia species, the sequencing of the rRNA genes and the chitin synthase-2 gene (CHS2) are the most widely employed. There is little information about the β-tubulin gene in the genus Malassezia, a gene has been used for the analysis of complex species groups. The aim of the present study was to sequence a fragment of the β-tubulin gene of Malassezia species and analyze their phylogenetic relationship using a multilocus sequence approach based on two rRNA genes (ITS including 5.8S rRNA and D1/D2 region of 26S rRNA) together with two protein encoding genes (CHS2 and β-tubulin). The phylogenetic study of the partial β-tubulin gene sequences indicated that this molecular marker can be used to assess diversity and identify new species. The multilocus sequence analysis of the four loci provides robust support to delineate species at the terminal nodes and could help to estimate divergence times for the origin and diversification of Malassezia species.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

PubMed

Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M

2016-04-20

RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Towards Long-Range RNA Structure Prediction in Eukaryotic Genes.

PubMed

Pervouchine, Dmitri D

2018-06-15

The ability to form an intramolecular structure plays a fundamental role in eukaryotic RNA biogenesis. Proximate regions in the primary transcripts fold into a local secondary structure, which is then hierarchically assembled into a tertiary structure that is stabilized by RNA-binding proteins and long-range intramolecular base pairings. While the local RNA structure can be predicted reasonably well for short sequences, long-range structure at the scale of eukaryotic genes remains problematic from the computational standpoint. The aim of this review is to list functional examples of long-range RNA structures, to summarize current comparative methods of structure prediction, and to highlight their advances and limitations in the context of long-range RNA structures. Most comparative methods implement the “first-align-then-fold” principle, i.e., they operate on multiple sequence alignments, while functional RNA structures often reside in non-conserved parts of the primary transcripts. The opposite “first-fold-then-align” approach is currently explored to a much lesser extent. Developing novel methods in both directions will improve the performance of comparative RNA structure analysis and help discover novel long-range structures, their higher-order organization, and RNA⁻RNA interactions across the transcriptome.

Thermodynamics of RNA structures by Wang–Landau sampling

PubMed Central

Lou, Feng; Clote, Peter

2010-01-01

Motivation: Thermodynamics-based dynamic programming RNA secondary structure algorithms have been of immense importance in molecular biology, where applications range from the detection of novel selenoproteins using expressed sequence tag (EST) data, to the determination of microRNA genes and their targets. Dynamic programming algorithms have been developed to compute the minimum free energy secondary structure and partition function of a given RNA sequence, the minimum free-energy and partition function for the hybridization of two RNA molecules, etc. However, the applicability of dynamic programming methods depends on disallowing certain types of interactions (pseudoknots, zig-zags, etc.), as their inclusion renders structure prediction an nondeterministic polynomial time (NP)-complete problem. Nevertheless, such interactions have been observed in X-ray structures. Results: A non-Boltzmannian Monte Carlo algorithm was designed by Wang and Landau to estimate the density of states for complex systems, such as the Ising model, that exhibit a phase transition. In this article, we apply the Wang-Landau (WL) method to compute the density of states for secondary structures of a given RNA sequence, and for hybridizations of two RNA sequences. Our method is shown to be much faster than existent software, such as RNAsubopt. From density of states, we compute the partition function over all secondary structures and over all pseudoknot-free hybridizations. The advantage of the WL method is that by adding a function to evaluate the free energy of arbitary pseudoknotted structures and of arbitrary hybridizations, we can estimate thermodynamic parameters for situations known to be NP-complete. This extension to pseudoknots will be made in the sequel to this article; in contrast, the current article describes the WL algorithm applied to pseudoknot-free secondary structures and hybridizations. Availability: The WL RNA hybridization web server is under construction at http://bioinformatics.bc.edu/clotelab/. Contact: clote@bc.edu PMID:20529917

Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms

PubMed Central

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts. PMID:23119097

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

PubMed

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

Sensitive and specific miRNA detection method using SplintR Ligase

PubMed Central

Jin, Jingmin; Vaud, Sophie; Zhelkovsky, Alexander M.; Posfai, Janos; McReynolds, Larry A.

2016-01-01

We describe a simple, specific and sensitive microRNA (miRNA) detection method that utilizes Chlorella virus DNA ligase (SplintR® Ligase). This two-step method involves ligation of adjacent DNA oligonucleotides hybridized to a miRNA followed by real-time quantitative PCR (qPCR). SplintR Ligase is 100X faster than either T4 DNA Ligase or T4 RNA Ligase 2 for RNA splinted DNA ligation. Only a 4–6 bp overlap between a DNA probe and miRNA was required for efficient ligation by SplintR Ligase. This property allows more flexibility in designing miRNA-specific ligation probes than methods that use reverse transcriptase for cDNA synthesis of miRNA. The qPCR SplintR ligation assay is sensitive; it can detect a few thousand molecules of miR-122. For miR-122 detection the SplintR qPCR assay, using a FAM labeled double quenched DNA probe, was at least 40× more sensitive than the TaqMan assay. The SplintR method, when coupled with NextGen sequencing, allowed multiplex detection of miRNAs from brain, kidney, testis and liver. The SplintR qPCR assay is specific; individual let-7 miRNAs that differ by one nucleotide are detected. The rapid kinetics and ability to ligate DNA probes hybridized to RNA with short complementary sequences makes SplintR Ligase a useful enzyme for miRNA detection. PMID:27154271

RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods

PubMed Central

Holik, Aliaksei Z.; Law, Charity W.; Liu, Ruijie; Wang, Zeya; Wang, Wenyi; Ahn, Jaeil; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.

2017-01-01

Abstract Carefully designed control experiments provide a gold standard for benchmarking different genomics research tools. A shortcoming of many gene expression control studies is that replication involves profiling the same reference RNA sample multiple times. This leads to low, pure technical noise that is atypical of regular studies. To achieve a more realistic noise structure, we generated a RNA-sequencing mixture experiment using two cell lines of the same cancer type. Variability was added by extracting RNA from independent cell cultures and degrading particular samples. The systematic gene expression changes induced by this design allowed benchmarking of different library preparation kits (standard poly-A versus total RNA with Ribozero depletion) and analysis pipelines. Data generated using the total RNA kit had more signal for introns and various RNA classes (ncRNA, snRNA, snoRNA) and less variability after degradation. For differential expression analysis, voom with quality weights marginally outperformed other popular methods, while for differential splicing, DEXSeq was simultaneously the most sensitive and the most inconsistent method. For sample deconvolution analysis, DeMix outperformed IsoPure convincingly. Our RNA-sequencing data set provides a valuable resource for benchmarking different protocols and data pre-processing workflows. The extra noise mimics routine lab experiments more closely, ensuring any conclusions are widely applicable. PMID:27899618

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.

PubMed

Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han

2017-03-01

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

visnormsc: A Graphical User Interface to Normalize Single-cell RNA Sequencing Data.

PubMed

Tang, Lijun; Zhou, Nan

2017-12-26

Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R. On the other hand, R programming ability is required, which prevents the biologists who lack the skills from learning to use it quickly. To make this method more user-friendly, we developed a graphical user interface, visnormsc, for normalization of single-cell RNA-seq data. It is implemented in Python and is freely available at https://github.com/solo7773/visnormsc . Although visnormsc is based on the existing method, it contributes to this field by offering a user-friendly alternative. The out-of-the-box and cross-platform features make visnormsc easy to learn and to use. It is expected to serve biologists by simplifying single-cell RNA-seq normalization.

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

PubMed Central

2017-01-01

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package. PMID:28100584

Mining, identification and function analysis of microRNAs and target genes in peanut (Arachis hypogaea L.).

PubMed

Zhang, Tingting; Hu, Shuhao; Yan, Caixia; Li, Chunjuan; Zhao, Xiaobo; Wan, Shubo; Shan, Shihua

2017-02-01

In the present investigation, a total of 60 conserved peanut (Arachis hypogaea L.) microRNA (miRNA) sequences, belonging to 16 families, were identified using bioinformatics methods. There were 392 target gene sequences, identified from 58 miRNAs with Target-align software and BLASTx analyses. Gene Ontology (GO) functional analysis suggested that these target genes were involved in mediating peanut growth and development, signal transduction and stress resistance. There were 55 miRNA sequences, verified employing a poly (A) tailing test, with a success rate of up to 91.67%. Twenty peanut target gene sequences were randomly selected, and the 5' rapid amplification of the cDNA ends (5'-RACE) method were used to validate the cleavage sites of these target genes. Of these, 14 (70%) peanut miRNA targets were verified by means of gel electrophoresis, cloning and sequencing. Furthermore, functional analysis and homologous sequence retrieval were conducted for target gene sequences, and 26 target genes were chosen as the objects for stress resistance experimental study. Real-time fluorescence quantitative PCR (qRT-PCR) technology was applied to measure the expression level of resistance-associated miRNAs and their target genes in peanut exposed to Aspergillus flavus (A. flavus) infection and drought stress, respectively. In consequence, 5 groups of miRNAs & targets were found accorded with the mode of miRNA negatively controlling the expression of target genes. This study, preliminarily determined the biological functions of some resistance-associated miRNAs and their target genes in peanut. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Ebbie: automated analysis and storage of small RNA cloning data using a dynamic web server

PubMed Central

Ebhardt, H Alexander; Wiese, Kay C; Unrau, Peter J

2006-01-01

Background DNA sequencing is used ubiquitously: from deciphering genomes[1] to determining the primary sequence of small RNAs (smRNAs) [2-5]. The cloning of smRNAs is currently the most conventional method to determine the actual sequence of these important regulators of gene expression. Typical smRNA cloning projects involve the sequencing of hundreds to thousands of smRNA clones that are delimited at their 5' and 3' ends by fixed sequence regions. These primers result from the biochemical protocol used to isolate and convert the smRNA into clonable PCR products. Recently we completed a smRNA cloning project involving tobacco plants, where analysis was required for ~700 smRNA sequences[6]. Finding no easily accessible research tool to enter and analyze smRNA sequences we developed Ebbie to assist us with our study. Results Ebbie is a semi-automated smRNA cloning data processing algorithm, which initially searches for any substring within a DNA sequencing text file, which is flanked by two constant strings. The substring, also termed smRNA or insert, is stored in a MySQL and BlastN database. These inserts are then compared using BlastN to locally installed databases allowing the rapid comparison of the insert to both the growing smRNA database and to other static sequence databases. Our laboratory used Ebbie to analyze scores of DNA sequencing data originating from an smRNA cloning project[6]. Through its built-in instant analysis of all inserts using BlastN, we were able to quickly identify 33 groups of smRNAs from ~700 database entries. This clustering allowed the easy identification of novel and highly expressed clusters of smRNAs. Ebbie is available under GNU GPL and currently implemented on Conclusion Ebbie was designed for medium sized smRNA cloning projects with about 1,000 database entries [6-8].Ebbie can be used for any type of sequence analysis where two constant primer regions flank a sequence of interest. The reliable storage of inserts, and their annotation in a MySQL database, BlastN[9] comparison of new inserts to dynamic and static databases make it a powerful new tool in any laboratory using DNA sequencing. Ebbie also prevents manual mistakes during the excision process and speeds up annotation and data-entry. Once the server is installed locally, its access can be restricted to protect sensitive new DNA sequencing data. Ebbie was primarily designed for smRNA cloning projects, but can be applied to a variety of RNA and DNA cloning projects[2,3,10,11]. PMID:16584563

Mapping posttranscriptional modifications in 5S ribosomal RNA by MALDI mass spectrometry.

PubMed

Kirpekar, F; Douthwaite, S; Roepstorff, P

2000-02-01

We present a method to screen RNA for posttranscriptional modifications based on Matrix Assisted Laser Desorption/Ionization mass spectrometry (MALDI-MS). After the RNA is digested to completion with a nucleotide-specific RNase, the fragments are analyzed by mass spectrometry. A comparison of the observed mass data with the data predicted from the gene sequence identifies fragments harboring modified nucleotides. Fragments larger than dinucleotides were valuable for the identification of posttranscriptional modifications. A more refined mapping of RNA modifications can be obtained by using two RNases in parallel combined with further fragmentation by Post Source Decay (PSD). This approach allows fast and sensitive screening of a purified RNA for posttranscriptional modification, and has been applied on 5S rRNA from two thermophilic microorganisms, the bacterium Bacillus stearothermophilus and the archaeon Sulfolobus acidocaldarius, as well as the halophile archaea Halobacterium halobium and Haloarcula marismortui. One S. acidocaldarius posttranscriptional modification was identified and was further characterized by PSD as a methylation of cytidine32. The modified C is located in a region that is clearly conserved with respect to both sequence and position in B. stearothermophilus and H. halobium and to some degree also in H. marismortui. However, no analogous modification was identified in the latter three organisms. We further find that the 5' end of H. halobium 5S rRNA is dephosphorylated, in contrast to the other 5S rRNA species investigated. The method additionally gives an immediate indication of whether the expected RNA sequence is in agreement with the observed fragment masses. Discrepancies with two of the published 5S rRNA sequences were identified and are reported here.

Mapping posttranscriptional modifications in 5S ribosomal RNA by MALDI mass spectrometry.

PubMed Central

Kirpekar, F; Douthwaite, S; Roepstorff, P

2000-01-01

We present a method to screen RNA for posttranscriptional modifications based on Matrix Assisted Laser Desorption/Ionization mass spectrometry (MALDI-MS). After the RNA is digested to completion with a nucleotide-specific RNase, the fragments are analyzed by mass spectrometry. A comparison of the observed mass data with the data predicted from the gene sequence identifies fragments harboring modified nucleotides. Fragments larger than dinucleotides were valuable for the identification of posttranscriptional modifications. A more refined mapping of RNA modifications can be obtained by using two RNases in parallel combined with further fragmentation by Post Source Decay (PSD). This approach allows fast and sensitive screening of a purified RNA for posttranscriptional modification, and has been applied on 5S rRNA from two thermophilic microorganisms, the bacterium Bacillus stearothermophilus and the archaeon Sulfolobus acidocaldarius, as well as the halophile archaea Halobacterium halobium and Haloarcula marismortui. One S. acidocaldarius posttranscriptional modification was identified and was further characterized by PSD as a methylation of cytidine32. The modified C is located in a region that is clearly conserved with respect to both sequence and position in B. stearothermophilus and H. halobium and to some degree also in H. marismortui. However, no analogous modification was identified in the latter three organisms. We further find that the 5' end of H. halobium 5S rRNA is dephosphorylated, in contrast to the other 5S rRNA species investigated. The method additionally gives an immediate indication of whether the expected RNA sequence is in agreement with the observed fragment masses. Discrepancies with two of the published 5S rRNA sequences were identified and are reported here. PMID:10688367

Screening for plant viruses by next generation sequencing using a modified double strand RNA extraction protocol with an internal amplification control.

PubMed

Kesanakurti, Prasad; Belton, Mark; Saeed, Hanaa; Rast, Heidi; Boyes, Ian; Rott, Michael

2016-10-01

The majority of plant viruses contain RNA genomes. Detection of viral RNA genomes in infected plant material by next generation sequencing (NGS) is possible through the extraction and sequencing of total RNA, total RNA devoid of ribosomal RNA, small RNA interference (RNAi) molecules, or double stranded RNA (dsRNA). Plants do not typically produce high molecular weight dsRNA, therefore the presence of dsRNA makes it an attractive target for plant virus diagnostics. The sensitivity of NGS as a diagnostic method demands an effective dsRNA protocol that is both representative of the sample and minimizes sample cross contamination. We have developed a modified dsRNA extraction protocol that is more efficient compared to traditional protocols, requiring reduced amounts of starting material, that is less prone to sample cross contamination. This was accomplished by using bead based homogenization of plant material in closed, disposable 50ml tubes. To assess the quality of extraction, we also developed an internal control by designing a real-time (quantitative) PCR (qPCR) assay that targets endornaviruses present in Phaseolus vulgaris cultivar Black Turtle Soup (BTS). Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

PubMed

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

RNA-SSPT: RNA Secondary Structure Prediction Tools

PubMed Central

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

PubMed Central

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-01-01

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy. PMID:25749473

Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

PubMed

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-03-04

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

[Phylogenetic analysis of closely related Leuconostoc citreum species based on partial housekeeping genes].

PubMed

Lv, Qiang; Chen, Ming; Xu, Haiyan; Song, Yuqin; Sun, Zhihong; Dan, Tong; Sun, Tiansong

2013-07-04

Using the 16S rRNA, dnaA, murC and pyrG gene sequences, we identified the phylogenetic relationship among closely related Leuconostoc citreum species. Seven Leu. citreum strains originally isolated from sourdough were characterized by PCR methods to amplify the dnaA, murC and pyrG gene sequences, which were determined to assess the suitability as phylogenetic markers. Then, we estimated the genetic distance and constructed the phylogenetic trees including 16S rRNA and above mentioned three housekeeping genes combining with published corresponding sequences. By comparing the phylogenetic trees, the topology of three housekeeping genes trees were consistent with that of 16S rRNA gene. The homology of closely related Leu. citreum species among dnaA, murC, pyrG and 16S rRNA gene sequences were different, ranged from75.5% to 97.2%, 50.2% to 99.7%, 65.0% to 99.8% and 98.5% 100%, respectively. The phylogenetic relationship of three housekeeping genes sequences were highly consistent with the results of 16S rRNA gene sequence, while the genetic distance of these housekeeping genes were extremely high than 16S rRNA gene. Consequently, the dnaA, murC and pyrG gene are suitable for classification and identification closely related Leu. citreum species.

PARTS: Probabilistic Alignment for RNA joinT Secondary structure prediction

PubMed Central

Harmanci, Arif Ozgun; Sharma, Gaurav; Mathews, David H.

2008-01-01

A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accomplished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed constraints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP) common secondary structures, sequence alignment and joint posterior probabilities of base pairing are obtained from the model via a dynamic programming algorithm called PARTS. The advantage of the more general structural alignment of PARTS is seen in secondary structure predictions for the RNase P family. For this family, the PARTS MAP predictions of secondary structures and alignment perform significantly better than prior methods that utilize a more restrictive structural alignment model. For the tRNA and 5S rRNA families, the richer structural alignment model of PARTS does not offer a benefit and the method therefore performs comparably with existing alternatives. For all RNA families studied, the posterior probability estimates obtained from PARTS offer an improvement over posterior probability estimates from a single sequence prediction. When considering the base pairings predicted over a threshold value of confidence, the combination of sensitivity and positive predictive value is superior for PARTS than for the single sequence prediction. PARTS source code is available for download under the GNU public license at http://rna.urmc.rochester.edu. PMID:18304945

Novel application of the MSSCP method in biodiversity studies.

PubMed

Tomczyk-Żak, Karolina; Kaczanowski, Szymon; Górecka, Magdalena; Zielenkiewicz, Urszula

2012-02-01

Analysis of 16S rRNA sequence diversity is widely performed for characterizing the biodiversity of microbial samples. The number of determined sequences has a considerable impact on complete results. Although the cost of mass sequencing is decreasing, it is often still too high for individual projects. We applied the multi-temperature single-strand conformational polymorphism (MSSCP) method to decrease the number of analysed sequences. This was a novel application of this method. As a control, the same sample was analysed using random sequencing. In this paper, we adapted the MSSCP technique for screening of unique sequences of the 16S rRNA gene library and bacterial strains isolated from biofilms growing on the walls of an ancient gold mine in Poland and determined whether the results obtained by both methods differed and whether random sequencing could be replaced by MSSCP. Although it was biased towards the detection of rare sequences in the samples, the qualitative results of MSSCP were not different than those of random sequencing. Unambiguous discrimination of unique clones and strains creates an opportunity to effectively estimate the biodiversity of natural communities, especially in populations which are numerous but species poor. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Methods for decoding Cas9 protospacer adjacent motif (PAM) sequences: A brief overview.

PubMed

Karvelis, Tautvydas; Gasiunas, Giedrius; Siksnys, Virginijus

2017-05-15

Recently the Cas9, an RNA guided DNA endonuclease, emerged as a powerful tool for targeted genome manipulations. Cas9 protein can be reprogrammed to cleave, bind or nick any DNA target by simply changing crRNA sequence, however a short nucleotide sequence, termed PAM, is required to initiate crRNA hybridization to the DNA target. PAM sequence is recognized by Cas9 protein and must be determined experimentally for each Cas9 variant. Exploration of Cas9 orthologs could offer a diversity of PAM sequences and novel biochemical properties that may be beneficial for genome editing applications. Here we briefly review and compare Cas9 PAM identification assays that can be adopted for other PAM-dependent CRISPR-Cas systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples.

PubMed

Reiman, Mario; Laan, Maris; Rull, Kristiina; Sõber, Siim

2017-08-01

RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set ( n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 3' untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. © FASEB.

Engineering of a DNA Polymerase for Direct m6 A Sequencing.

PubMed

Aschenbrenner, Joos; Werner, Stephan; Marchand, Virginie; Adam, Martina; Motorin, Yuri; Helm, Mark; Marx, Andreas

2018-01-08

Methods for the detection of RNA modifications are of fundamental importance for advancing epitranscriptomics. N 6 -methyladenosine (m 6 A) is the most abundant RNA modification in mammalian mRNA and is involved in the regulation of gene expression. Current detection techniques are laborious and rely on antibody-based enrichment of m 6 A-containing RNA prior to sequencing, since m 6 A modifications are generally "erased" during reverse transcription (RT). To overcome the drawbacks associated with indirect detection, we aimed to generate novel DNA polymerase variants for direct m 6 A sequencing. Therefore, we developed a screen to evolve an RT-active KlenTaq DNA polymerase variant that sets a mark for N 6 -methylation. We identified a mutant that exhibits increased misincorporation opposite m 6 A compared to unmodified A. Application of the generated DNA polymerase in next-generation sequencing allowed the identification of m 6 A sites directly from the sequencing data of untreated RNA samples. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana.

PubMed

Xiang, Shunian; Yan, Zhangming; Liu, Ke; Zhang, Yaou; Sun, Zhirong

2016-10-18

N 6 -Methyladenosine (m 6 A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m 6 A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m 6 A functions in plants. Therefore, computational prediction of mRNA m 6 A sites becomes emergently important. Here, we present a method to predict the m 6 A sites for A. thaliana mRNA sequence(s). To predict the m 6 A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m 6 A sites. The server also provides a comprehensive database of predicted transcriptome-wide m 6 A sites and curated m 6 A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m 6 A sites, which is freely accessible for public use at .

Replacement of RNA hairpins by in vitro selected tetranucleotides.

PubMed Central

Dichtl, B; Pan, T; DiRenzo, A B; Uhlenbeck, O C

1993-01-01

An in vitro selection method based on the autolytic cleavage of yeast tRNA(Phe) by Pb2+ was applied to obtain tRNA derivatives with the anticodon hairpin replaced by four single-stranded nucleotides. Based on the rates of the site-specific cleavage by Pb2+ and the presence of a specific UV-induced crosslink, certain tetranucleotide sequences allow proper folding of the rest of the tRNA molecule, whereas others do not. One such successful tetramer sequence was also used to replace the acceptor stem of yeast tRNA(Phe) and the anticodon hairpin of E.coli tRNA(Phe) without disrupting folding. These experiments suggest that certain tetramers may be able to replace structurally nonessential hairpins in any RNA. Images PMID:7680121

A Comprehensive Approach to Sequence-oriented IsomiR annotation (CASMIR): demonstration with IsomiR profiling in colorectal neoplasia.

PubMed

Wu, Chung Wah; Evans, Jared M; Huang, Shengbing; Mahoney, Douglas W; Dukek, Brian A; Taylor, William R; Yab, Tracy C; Smyrk, Thomas C; Jen, Jin; Kisiel, John B; Ahlquist, David A

2018-05-25

MicroRNA (miRNA) profiling is an important step in studying biological associations and identifying marker candidates. miRNA exists in isoforms, called isomiRs, which may exhibit distinct properties. With conventional profiling methods, limitations in assay and analysis platforms may compromise isomiR interrogation. We introduce a comprehensive approach to sequence-oriented isomiR annotation (CASMIR) to allow unbiased identification of global isomiRs from small RNA sequencing data. In this approach, small RNA reads are maintained as independent sequences instead of being summarized under miRNA names. IsomiR features are identified through step-wise local alignment against canonical forms and precursor sequences. Through customizing the reference database, CASMIR is applicable to isomiR annotation across species. To demonstrate its application, we investigated isomiR profiles in normal and neoplastic human colorectal epithelia. We also ran miRDeep2, a popular miRNA analysis algorithm to validate isomiRs annotated by CASMIR. With CASMIR, specific and biologically relevant isomiR patterns could be identified. We note that specific isomiRs are often more abundant than their canonical forms. We identify isomiRs that are commonly up-regulated in both colorectal cancer and advanced adenoma, and illustrate advantages in targeting isomiRs as potential biomarkers over canonical forms. Studying miRNAs at the isomiR level could reveal new insight into miRNA biology and inform assay design for specific isomiRs. CASMIR facilitates comprehensive annotation of isomiR features in small RNA sequencing data for isomiR profiling and differential expression analysis.

Modeling bias and variation in the stochastic processes of small RNA sequencing

PubMed Central

Etheridge, Alton; Sakhanenko, Nikita; Galas, David

2017-01-01

Abstract The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers has been hindered by high quantitative variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in sequence counts. This model implies a linear quadratic relation between the mean and variance of sequence counts. Using a large number of sequencing datasets, we demonstrate how one can use the generalized additive models for location, scale and shape (GAMLSS) distributional regression framework to calculate and apply empirical correction factors for ligase bias. Bias correction could remove more than 40% of the bias for miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition. Using synthetic mixes of known composition, we show that the GAMLSS approach can analyze differential expression with greater accuracy, higher sensitivity and specificity than six existing algorithms (DESeq2, edgeR, EBSeq, limma, DSS, voom) for the analysis of small RNA-seq data. PMID:28369495

Detection and characterization of Pasteuria 16S rRNA gene sequences from nematodes and soils.

PubMed

Duan, Y P; Castro, H F; Hewlett, T E; White, J H; Ogram, A V

2003-01-01

Various bacterial species in the genus Pasteuria have great potential as biocontrol agents against plant-parasitic nematodes, although study of this important genus is hampered by the current inability to cultivate Pasteuria species outside their host. To aid in the study of this genus, an extensive 16S rRNA gene sequence phylogeny was constructed and this information was used to develop cultivation-independent methods for detection of Pasteuria in soils and nematodes. Thirty new clones of Pasteuria 16S rRNA genes were obtained directly from nematodes and soil samples. These were sequenced and used to construct an extensive phylogeny of this genus. These sequences were divided into two deeply branching clades within the low-G + C, Gram-positive division; some sequences appear to represent novel species within the genus Pasteuria. In addition, a surprising degree of 16S rRNA gene sequence diversity was observed within what had previously been designated a single strain of Pasteuria penetrans (P-20). PCR primers specific to Pasteuria 16S rRNA for detection of Pasteuria in soils were also designed and evaluated. Detection limits for soil DNA were 100-10,000 Pasteuria endospores (g soil)(-1).

Early diagnosis of a Mexican variant of Papaya meleira virus (PMeV-Mx) by RT-PCR.

PubMed

Zamudio-Moreno, E; Ramirez-Prado, J H; Moreno-Valenzuela, O A; Lopez-Ochoa, L A

2015-02-06

Papaya meleira disease was identified in Brazil in the 1980s. The disease is caused by a double-stranded RNA virus known as Papaya meleira virus (PMeV), which has also been recently reported in Mexico. However, previously reported PMeV primers failed to diagnose the Mexican form of the disease. A genomic approach was used to identify sequences of the Mexican virus isolate, referred here to as PMeV-Mx, to develop a diagnostic method. A mini cDNA library was generated using total RNA from the latex of fruits; this RNA was also sequenced using the Illumina platform. Sequences corresponding to the previously reported 669-base pair sequence for PMeV from Brazil (PMeV-Br) were identified within the PMeV-Mx genome, exhibiting 79-92% identity with PMeV-Br. In addition, a new sequence of 1154-base pairs encoding a putative RNA-dependent RNA polymerase was identified in PMeV-Mx. Primers designed against this sequence detected both virus isolates, 2 amplicons of 173 and 491 base pairs from PMeV-Br and PMeV-Mx, and shared 100 and 98% identity, respectively. PMeV-Mx was found in the latex of fruits, in seedlings, and in the leaves, flowers, petioles, and seeds of mature plants. PMeV-Mx was more abundant in the latex of fruits than in the leaves. The limit of detection of the CB38/CB39 primer pair was 1 fg and 1 pg using total RNA extracted from the latex of fruits and from seedlings, respectively. A sensitive and early diagnosis protocol was developed; this method will enable the certification of seeds and seedlings prior to transplantation to the field.

High throughput sequencing analysis of RNA libraries reveals the influences of initial library and PCR methods on SELEX efficiency.

PubMed

Takahashi, Mayumi; Wu, Xiwei; Ho, Michelle; Chomchan, Pritsana; Rossi, John J; Burnett, John C; Zhou, Jiehua

2016-09-22

The systemic evolution of ligands by exponential enrichment (SELEX) technique is a powerful and effective aptamer-selection procedure. However, modifications to the process can dramatically improve selection efficiency and aptamer performance. For example, droplet digital PCR (ddPCR) has been recently incorporated into SELEX selection protocols to putatively reduce the propagation of byproducts and avoid selection bias that result from differences in PCR efficiency of sequences within the random library. However, a detailed, parallel comparison of the efficacy of conventional solution PCR versus the ddPCR modification in the RNA aptamer-selection process is needed to understand effects on overall SELEX performance. In the present study, we took advantage of powerful high throughput sequencing technology and bioinformatics analysis coupled with SELEX (HT-SELEX) to thoroughly investigate the effects of initial library and PCR methods in the RNA aptamer identification. Our analysis revealed that distinct "biased sequences" and nucleotide composition existed in the initial, unselected libraries purchased from two different manufacturers and that the fate of the "biased sequences" was target-dependent during selection. Our comparison of solution PCR- and ddPCR-driven HT-SELEX demonstrated that PCR method affected not only the nucleotide composition of the enriched sequences, but also the overall SELEX efficiency and aptamer efficacy.

Biosynthesis and genetic encoding of phosphothreonine through parallel selection and deep sequencing

PubMed Central

Huguenin-Dezot, Nicolas; Liang, Alexandria D.; Schmied, Wolfgang H.; Rogerson, Daniel T.; Chin, Jason W.

2017-01-01

The phosphorylation of threonine residues in proteins regulates diverse processes in eukaryotic cells, and thousands of threonine phosphorylations have been identified. An understanding of how threonine phosphorylation regulates biological function will be accelerated by general methods to bio-synthesize defined phospho-proteins. Here we address limitations in current methods for discovering aminoacyl-tRNA synthetase/tRNA pairs for incorporating non-natural amino acids into proteins, by combining parallel positive selections with deep sequencing and statistical analysis, to create a rapid approach for directly discovering aminoacyl-tRNA synthetase/tRNA pairs that selectively incorporate non-natural substrates. Our approach is scalable and enables the direct discovery of aminoacyl-tRNA synthetase/tRNA pairs with mutually orthogonal substrate specificity. We biosynthesize phosphothreonine in cells, and use our new selection approach to discover a phosphothreonyl-tRNA synthetase/tRNACUA pair. By combining these advances we create an entirely biosynthetic route to incorporating phosphothreonine in proteins and biosynthesize several phosphoproteins; enabling phosphoprotein structure determination and synthetic protein kinase activation. PMID:28553966

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment

PubMed Central

2013-01-01

Background Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. Results In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Conclusion Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA. PMID:24564200

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment.

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA.

Microbial diversity in an Armenian geothermal spring assessed by molecular and culture-based methods.

PubMed

Panosyan, Hovik; Birkeland, Nils-Kåre

2014-11-01

The phylogenetic diversity of the prokaryotic community thriving in the Arzakan hot spring in Armenia was studied using molecular and culture-based methods. A sequence analysis of 16S rRNA gene clone libraries demonstrated the presence of a diversity of microorganisms belonging to the Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Epsilonproteobacteria, Firmicutes, Bacteroidetes phyla, and Cyanobacteria. Proteobacteria was the dominant group, representing 52% of the bacterial clones. Denaturing gradient gel electrophoresis profiles of the bacterial 16S rRNA gene fragments also indicated the abundance of Proteobacteria, Bacteroidetes, and Cyanobacteria populations. Most of the sequences were most closely related to uncultivated microorganisms and shared less than 96% similarity with their closest matches in GenBank, indicating that this spring harbors a unique community of novel microbial species or genera. The majority of the sequences of an archaeal 16S rRNA gene library, generated from a methanogenic enrichment, were close relatives of members of the genus Methanoculleus. Aerobic endospore-forming bacteria mainly belonging to Bacillus and Geobacillus were detected only by culture-dependent methods. Three isolates were successfully obtained having 99, 96, and 96% 16S rRNA gene sequence similarities to Arcobacter sp., Methylocaldum sp., and Methanoculleus sp., respectively. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Specific binding of a HeLa cell nuclear protein to RNA sequences in the human immunodeficiency virus transactivating region.

PubMed Central

Gaynor, R; Soultanakis, E; Kuwabara, M; Garcia, J; Sigman, D S

1989-01-01

The transactivator protein, tat, encoded by the human immunodeficiency virus is a key regulator of viral transcription. Activation by the tat protein requires sequences downstream of the transcription initiation site called the transactivating region (TAR). RNA derived from the TAR is capable of forming a stable stem-loop structure and the maintenance of both the stem structure and the loop sequences located between +19 and +44 is required for complete in vivo activation by tat. Gel retardation assays with RNA from both wild-type and mutant TAR constructs generated in vitro with SP6 polymerase indicated specific binding of HeLa nuclear proteins to the TAR. To characterize this RNA-protein interaction, a method of chemical "imprinting" has been developed using photoactivated uranyl acetate as the nucleolytic agent. This reagent nicks RNA under physiological conditions at all four nucleotides in a reaction that is independent of sequence and secondary structure. Specific interaction of cellular proteins with TAR RNA could be detected by enhanced cleavages or imprints surrounding the loop region. Mutations that either disrupted stem base-pairing or extensively changed the primary sequence resulted in alterations in the cleavage pattern of the TAR RNA. Structural features of the TAR RNA stem-loop essential for tat activation are also required for specific binding of the HeLa cell nuclear protein. Images PMID:2544877

SimRNAweb: a web server for RNA 3D structure modeling with optional restraints.

PubMed

Magnus, Marcin; Boniecki, Michał J; Dawson, Wayne; Bujnicki, Janusz M

2016-07-08

RNA function in many biological processes depends on the formation of three-dimensional (3D) structures. However, RNA structure is difficult to determine experimentally, which has prompted the development of predictive computational methods. Here, we introduce a user-friendly online interface for modeling RNA 3D structures using SimRNA, a method that uses a coarse-grained representation of RNA molecules, utilizes the Monte Carlo method to sample the conformational space, and relies on a statistical potential to describe the interactions in the folding process. SimRNAweb makes SimRNA accessible to users who do not normally use high performance computational facilities or are unfamiliar with using the command line tools. The simplest input consists of an RNA sequence to fold RNA de novo. Alternatively, a user can provide a 3D structure in the PDB format, for instance a preliminary model built with some other technique, to jump-start the modeling close to the expected final outcome. The user can optionally provide secondary structure and distance restraints, and can freeze a part of the starting 3D structure. SimRNAweb can be used to model single RNA sequences and RNA-RNA complexes (up to 52 chains). The webserver is available at http://genesilico.pl/SimRNAweb. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multicolor microRNA FISH effectively differentiates tumor types

PubMed Central

Renwick, Neil; Cekan, Pavol; Masry, Paul A.; McGeary, Sean E.; Miller, Jason B.; Hafner, Markus; Li, Zhen; Mihailovic, Aleksandra; Morozov, Pavel; Brown, Miguel; Gogakos, Tasos; Mobin, Mehrpouya B.; Snorrason, Einar L.; Feilotter, Harriet E.; Zhang, Xiao; Perlis, Clifford S.; Wu, Hong; Suárez-Fariñas, Mayte; Feng, Huichen; Shuda, Masahiro; Moore, Patrick S.; Tron, Victor A.; Chang, Yuan; Tuschl, Thomas

2013-01-01

MicroRNAs (miRNAs) are excellent tumor biomarkers because of their cell-type specificity and abundance. However, many miRNA detection methods, such as real-time PCR, obliterate valuable visuospatial information in tissue samples. To enable miRNA visualization in formalin-fixed paraffin-embedded (FFPE) tissues, we developed multicolor miRNA FISH. As a proof of concept, we used this method to differentiate two skin tumors, basal cell carcinoma (BCC) and Merkel cell carcinoma (MCC), with overlapping histologic features but distinct cellular origins. Using sequencing-based miRNA profiling and discriminant analysis, we identified the tumor-specific miRNAs miR-205 and miR-375 in BCC and MCC, respectively. We addressed three major shortcomings in miRNA FISH, identifying optimal conditions for miRNA fixation and ribosomal RNA (rRNA) retention using model compounds and high-pressure liquid chromatography (HPLC) analyses, enhancing signal amplification and detection by increasing probe-hapten linker lengths, and improving probe specificity using shortened probes with minimal rRNA sequence complementarity. We validated our method on 4 BCC and 12 MCC tumors. Amplified miR-205 and miR-375 signals were normalized against directly detectable reference rRNA signals. Tumors were classified using predefined cutoff values, and all were correctly identified in blinded analysis. Our study establishes a reliable miRNA FISH technique for parallel visualization of differentially expressed miRNAs in FFPE tumor tissues. PMID:23728175

Fine-tuning structural RNA alignments in the twilight zone.

PubMed

Bremges, Andreas; Schirmer, Stefanie; Giegerich, Robert

2010-04-30

A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index.

Small RNA Library Preparation Method for Next-Generation Sequencing Using Chemical Modifications to Prevent Adapter Dimer Formation.

PubMed

Shore, Sabrina; Henderson, Jordana M; Lebedev, Alexandre; Salcedo, Michelle P; Zon, Gerald; McCaffrey, Anton P; Paul, Natasha; Hogrefe, Richard I

2016-01-01

For most sample types, the automation of RNA and DNA sample preparation workflows enables high throughput next-generation sequencing (NGS) library preparation. Greater adoption of small RNA (sRNA) sequencing has been hindered by high sample input requirements and inherent ligation side products formed during library preparation. These side products, known as adapter dimer, are very similar in size to the tagged library. Most sRNA library preparation strategies thus employ a gel purification step to isolate tagged library from adapter dimer contaminants. At very low sample inputs, adapter dimer side products dominate the reaction and limit the sensitivity of this technique. Here we address the need for improved specificity of sRNA library preparation workflows with a novel library preparation approach that uses modified adapters to suppress adapter dimer formation. This workflow allows for lower sample inputs and elimination of the gel purification step, which in turn allows for an automatable sRNA library preparation protocol.

Designing highly active siRNAs for therapeutic applications.

PubMed

Walton, S Patrick; Wu, Ming; Gredell, Joseph A; Chan, Christina

2010-12-01

The discovery of RNA interference (RNAi) generated considerable interest in developing short interfering RNAs (siRNAs) for understanding basic biology and as the active agents in a new variety of therapeutics. Early studies showed that selecting an active siRNA was not as straightforward as simply picking a sequence on the target mRNA and synthesizing the siRNA complementary to that sequence. As interest in applying RNAi has increased, the methods for identifying active siRNA sequences have evolved from focusing on the simplicity of synthesis and purification, to identifying preferred target sequences and secondary structures, to predicting the thermodynamic stability of the siRNA. As more specific details of the RNAi mechanism have been defined, these have been incorporated into more complex siRNA selection algorithms, increasing the reliability of selecting active siRNAs against a single target. Ultimately, design of the best siRNA therapeutics will require design of the siRNA itself, in addition to design of the vehicle and other components necessary for it to function in vivo. In this minireview, we summarize the evolution of siRNA selection techniques with a particular focus on one issue of current importance to the field, how best to identify those siRNA sequences likely to have high activity. Approaches to designing active siRNAs through chemical and structural modifications will also be highlighted. As the understanding of how to control the activity and specificity of siRNAs improves, the potential utility of siRNAs as human therapeutics will concomitantly grow. © 2010 The Authors Journal compilation © 2010 FEBS.

Evaluation of the impact of RNA preservation methods of spiders for de novo transcriptome assembly.

PubMed

Kono, Nobuaki; Nakamura, Hiroyuki; Ito, Yusuke; Tomita, Masaru; Arakawa, Kazuharu

2016-05-01

With advances in high-throughput sequencing technologies, de novo transcriptome sequencing and assembly has become a cost-effective method to obtain comprehensive genetic information of a species of interest, especially in nonmodel species with large genomes such as spiders. However, high-quality RNA is essential for successful sequencing, and sample preservation conditions require careful consideration for the effective storage of field-collected samples. To this end, we report a streamlined feasibility study of various storage conditions and their effects on de novo transcriptome assembly results. The storage parameters considered include temperatures ranging from room temperature to -80°C; preservatives, including ethanol, RNAlater, TRIzol and RNAlater-ICE; and sample submersion states. As a result, intact RNA was extracted and assembly was successful when samples were preserved at low temperatures regardless of the type of preservative used. The assemblies as well as the gene expression profiles were shown to be robust to RNA degradation, when 30 million 150-bp paired-end reads are obtained. The parameters for sample storage, RNA extraction, library preparation, sequencing and in silico assembly considered in this work provide a guideline for the study of field-collected samples of spiders. © 2015 John Wiley & Sons Ltd.

Phage-mediated Delivery of Targeted sRNA Constructs to Knock Down Gene Expression in E. coli.

PubMed

Bernheim, Aude G; Libis, Vincent K; Lindner, Ariel B; Wintermute, Edwin H

2016-03-20

RNA-mediated knockdowns are widely used to control gene expression. This versatile family of techniques makes use of short RNA (sRNA) that can be synthesized with any sequence and designed to complement any gene targeted for silencing. Because sRNA constructs can be introduced to many cell types directly or using a variety of vectors, gene expression can be repressed in living cells without laborious genetic modification. The most common RNA knockdown technology, RNA interference (RNAi), makes use of the endogenous RNA-induced silencing complex (RISC) to mediate sequence recognition and cleavage of the target mRNA. Applications of this technique are therefore limited to RISC-expressing organisms, primarily eukaryotes. Recently, a new generation of RNA biotechnologists have developed alternative mechanisms for controlling gene expression through RNA, and so made possible RNA-mediated gene knockdowns in bacteria. Here we describe a method for silencing gene expression in E. coli that functionally resembles RNAi. In this system a synthetic phagemid is designed to express sRNA, which may designed to target any sequence. The expression construct is delivered to a population of E. coli cells with non-lytic M13 phage, after which it is able to stably replicate as a plasmid. Antisense recognition and silencing of the target mRNA is mediated by the Hfq protein, endogenous to E. coli. This protocol includes methods for designing the antisense sRNA, constructing the phagemid vector, packaging the phagemid into M13 bacteriophage, preparing a live cell population for infection, and performing the infection itself. The fluorescent protein mKate2 and the antibiotic resistance gene chloramphenicol acetyltransferase (CAT) are targeted to generate representative data and to quantify knockdown effectiveness.

High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.

PubMed

Stegmayer, Georgina; Yones, Cristian; Kamenetzky, Laura; Milone, Diego H

2017-01-01

The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high class-imbalance classification problem. The classical way of approaching it has been training a binary classifier in a supervised manner, using well-known pre-miRNAs as positive class and artificially defining the negative class. However, although the selection of positive labeled examples is straightforward, it is very difficult to build a set of negative examples in order to obtain a good set of training samples for a supervised method. In this work, we propose a novel and effective way of approaching this problem using machine learning, without the definition of negative examples. The proposal is based on clustering unlabeled sequences of a genome together with well-known miRNA precursors for the organism under study, which allows for the quick identification of the best candidates to miRNA as those sequences clustered with known precursors. Furthermore, we propose a deep model to overcome the problem of having very few positive class labels. They are always maintained in the deep levels as positive class while less likely pre-miRNA sequences are filtered level after level. Our approach has been compared with other methods for pre-miRNAs prediction in several species, showing effective predictivity of novel miRNAs. Additionally, we will show that our approach has a lower training time and allows for a better graphical navegability and interpretation of the results. A web-demo interface to try deepSOM is available at http://fich.unl.edu.ar/sinc/web-demo/deepsom/.

RNA Crystallization

NASA Technical Reports Server (NTRS)

Golden, Barbara L.; Kundrot, Craig E.

2003-01-01

RNA molecules may be crystallized using variations of the methods developed for protein crystallography. As the technology has become available to syntheisize and purify RNA molecules in the quantities and with the quality that is required for crystallography, the field of RNA structure has exploded. The first consideration when crystallizing an RNA is the sequence, which may be varied in a rational way to enhance crystallizability or prevent formation of alternate structures. Once a sequence has been designed, the RNA may be synthesized chemically by solid-state synthesis, or it may be produced enzymatically using RNA polymerase and an appropriate DNA template. Purification of milligram quantities of RNA can be accomplished by HPLC or gel electrophoresis. As with proteins, crystallization of RNA is usually accomplished by vapor diffusion techniques. There are several considerations that are either unique to RNA crystallization or more important for RNA crystallization. Techniques for design, synthesis, purification, and crystallization of RNAs will be reviewed here.

Identification of characteristic oligonucleotides in the bacterial 16S ribosomal RNA sequence dataset

NASA Technical Reports Server (NTRS)

Zhang, Zhengdong; Willson, Richard C.; Fox, George E.

2002-01-01

MOTIVATION: The phylogenetic structure of the bacterial world has been intensively studied by comparing sequences of 16S ribosomal RNA (16S rRNA). This database of sequences is now widely used to design probes for the detection of specific bacteria or groups of bacteria one at a time. The success of such methods reflects the fact that there are local sequence segments that are highly characteristic of particular organisms or groups of organisms. It is not clear, however, the extent to which such signature sequences exist in the 16S rRNA dataset. A better understanding of the numbers and distribution of highly informative oligonucleotide sequences may facilitate the design of hybridization arrays that can characterize the phylogenetic position of an unknown organism or serve as the basis for the development of novel approaches for use in bacterial identification. RESULTS: A computer-based algorithm that characterizes the extent to which any individual oligonucleotide sequence in 16S rRNA is characteristic of any particular bacterial grouping was developed. A measure of signature quality, Q(s), was formulated and subsequently calculated for every individual oligonucleotide sequence in the size range of 5-11 nucleotides and for 15mers with reference to each cluster and subcluster in a 929 organism representative phylogenetic tree. Subsequently, the perfect signature sequences were compared to the full set of 7322 sequences to see how common false positives were. The work completed here establishes beyond any doubt that highly characteristic oligonucleotides exist in the bacterial 16S rRNA sequence dataset in large numbers. Over 16,000 15mers were identified that might be useful as signatures. Signature oligonucleotides are available for over 80% of the nodes in the representative tree.

Long-PCR based next generation sequencing of the whole mitochondrial genome of the peacock skate Pavoraja nitida (Elasmobranchii: Arhynchobatidae).

PubMed

Yang, Lei; Naylor, Gavin J P

2016-01-01

We determined the complete mitochondrial genome sequence (16,760 bp) of the peacock skate Pavoraja nitida using a long-PCR based next generation sequencing method. It has 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and 1 control region in the typical vertebrate arrangement. Primers, protocols, and procedures used to obtain this mitogenome are provided. We anticipate that this approach will facilitate rapid collection of mitogenome sequences for studies on phylogenetic relationships, population genetics, and conservation of cartilaginous fishes.

A robust and cost-effective approach to sequence and analyze complete genomes of small RNA viruses

USDA-ARS?s Scientific Manuscript database

Background: Next-generation sequencing (NGS) allows ultra-deep sequencing of nucleic acids. The use of sequence-independent amplification of viral nucleic acids without utilization of target-specific primers provides advantages over traditional sequencing methods and allows detection of unsuspected ...

Comprehensive comparative analysis of 5'-end RNA-sequencing methods.

PubMed

Adiconis, Xian; Haber, Adam L; Simmons, Sean K; Levy Moonshine, Ami; Ji, Zhe; Busby, Michele A; Shi, Xi; Jacques, Justin; Lancaster, Madeline A; Pan, Jen Q; Regev, Aviv; Levin, Joshua Z

2018-06-04

Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

Primer design for a prokaryotic differential display RT-PCR.

PubMed Central

Fislage, R; Berceanu, M; Humboldt, Y; Wendt, M; Oberender, H

1997-01-01

We have developed a primer set for a prokaryotic differential display of mRNA in the Enterobacteriaceae group. Each combination of ten 10mer and ten 11mer primers generates up to 85 bands from total Escherichia coli RNA, thus covering expressed sequences of a complete bacterial genome. Due to the lack of polyadenylation in prokaryotic RNA the type T11VN anchored oligonucleotides for the reverse transcriptase reaction had to be replaced with respect to the original method described by Liang and Pardee [ Science , 257, 967-971 (1992)]. Therefore, the sequences of both the 10mer and the new 11mer oligonucleotides were determined by a statistical evaluation of species-specific coding regions extracted from the EMBL database. The 11mer primers used for reverse transcription were selected for localization in the 3'-region of the bacterial RNA. The 10mer primers preferentially bind to the 5'-end of the RNA. None of the primers show homology to rRNA or other abundant small RNA species. Randomly sampled cDNA bands were checked for their bacterial origin either by re-amplification, cloning and sequencing or by re-amplification and direct sequencing with 10mer and 11mer primers after asymmetric PCR. PMID:9108168

Primer design for a prokaryotic differential display RT-PCR.

PubMed

Fislage, R; Berceanu, M; Humboldt, Y; Wendt, M; Oberender, H

1997-05-01

We have developed a primer set for a prokaryotic differential display of mRNA in the Enterobacteriaceae group. Each combination of ten 10mer and ten 11mer primers generates up to 85 bands from total Escherichia coli RNA, thus covering expressed sequences of a complete bacterial genome. Due to the lack of polyadenylation in prokaryotic RNA the type T11VN anchored oligonucleotides for the reverse transcriptase reaction had to be replaced with respect to the original method described by Liang and Pardee [ Science , 257, 967-971 (1992)]. Therefore, the sequences of both the 10mer and the new 11mer oligonucleotides were determined by a statistical evaluation of species-specific coding regions extracted from the EMBL database. The 11mer primers used for reverse transcription were selected for localization in the 3'-region of the bacterial RNA. The 10mer primers preferentially bind to the 5'-end of the RNA. None of the primers show homology to rRNA or other abundant small RNA species. Randomly sampled cDNA bands were checked for their bacterial origin either by re-amplification, cloning and sequencing or by re-amplification and direct sequencing with 10mer and 11mer primers after asymmetric PCR.

EMSAR: estimation of transcript abundance from RNA-seq data by mappability-based segmentation and reclustering.

PubMed

Lee, Soohyun; Seo, Chae Hwa; Alver, Burak Han; Lee, Sanghyuk; Park, Peter J

2015-09-03

RNA-seq has been widely used for genome-wide expression profiling. RNA-seq data typically consists of tens of millions of short sequenced reads from different transcripts. However, due to sequence similarity among genes and among isoforms, the source of a given read is often ambiguous. Existing approaches for estimating expression levels from RNA-seq reads tend to compromise between accuracy and computational cost. We introduce a new approach for quantifying transcript abundance from RNA-seq data. EMSAR (Estimation by Mappability-based Segmentation And Reclustering) groups reads according to the set of transcripts to which they are mapped and finds maximum likelihood estimates using a joint Poisson model for each optimal set of segments of transcripts. The method uses nearly all mapped reads, including those mapped to multiple genes. With an efficient transcriptome indexing based on modified suffix arrays, EMSAR minimizes the use of CPU time and memory while achieving accuracy comparable to the best existing methods. EMSAR is a method for quantifying transcripts from RNA-seq data with high accuracy and low computational cost. EMSAR is available at https://github.com/parklab/emsar.

GRIL-Seq, a method for identifying direct targets of bacterial small regulatory RNA by in vivo proximity ligation

PubMed Central

Han, Kook; Tjaden, Brian; Lory, Stephen

2017-01-01

The first step in the post-transcriptional regulatory function of most bacterial small non-coding RNAs (sRNAs) is base-pairing with partially complementary sequences of targeted transcripts. We present a simple method for identifying sRNA targets in vivo and defining processing sites of the regulated transcripts. The technique (referred to as GRIL-Seq) is based on preferential ligation of sRNAs to ends of base-paired targets in bacteria co-expressing T4 RNA ligase, followed by sequencing to identify the chimeras. In addition to the RNA chaperone Hfq, the GRIL-Seq method depends on the activity of the pyrophosphorylase RppH. Using PrrF1, an iron-regulated sRNA in Pseudomonas aeruginosa, we demonstrate that direct regulatory targets of this sRNA can be readily identified. Therefore, GRIL-Seq represents a powerful tool not only for identifying direct targets of sRNAs in a variety of environments, but can also result in uncovering novel roles for sRNAs and their targets in complex regulatory networks. PMID:28005055

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

PubMed

Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2012-05-10

RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM)-based representation (PSSMSeq) outperform those that use an amino acid identity based representation (IDSeq) or a smoothed PSSM (SmoPSSMSeq); (ii) Structure-based classifiers that use smoothed PSSM representation (SmoPSSMStr) outperform those that use PSSM (PSSMStr) as well as sequence identity based representation (IDStr). PSSMSeq classifiers, when tested on an independent test set of 44 proteins, achieve performance that is comparable to that of three state-of-the-art structure-based predictors (including those that exploit geometric features) in terms of Matthews Correlation Coefficient (MCC), although the structure-based methods achieve substantially higher Specificity (albeit at the expense of Sensitivity) compared to sequence-based methods. We also find that the expected performance of the classifiers on a residue level can be markedly different from that on a protein level. Our experiments show that the classifiers trained on three different non-redundant protein-RNA interface datasets achieve comparable cross-validation performance. However, we find that the results are significantly affected by differences in the distance threshold used to define interface residues. Our results demonstrate that protein-RNA interface residue predictors that use a PSSM-based encoding of sequence windows outperform classifiers that use other encodings of sequence windows. While structure-based methods that exploit geometric features can yield significant increases in the Specificity of protein-RNA interface residue predictions, such increases are offset by decreases in Sensitivity. These results underscore the importance of comparing alternative methods using rigorous statistical procedures, multiple performance measures, and datasets that are constructed based on several alternative definitions of interface residues and redundancy cutoffs as well as including evaluations on independent test sets into the comparisons.

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

PubMed Central

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

a Simple Symmetric Algorithm Using a Likeness with Introns Behavior in RNA Sequences

NASA Astrophysics Data System (ADS)

Regoli, Massimo

2009-02-01

The RNA-Crypto System (shortly RCS) is a symmetric key algorithm to cipher data. The idea for this new algorithm starts from the observation of nature. In particular from the observation of RNA behavior and some of its properties. The RNA sequences has some sections called Introns. Introns, derived from the term "intragenic regions", are non-coding sections of precursor mRNA (pre-mRNA) or other RNAs, that are removed (spliced out of the RNA) before the mature RNA is formed. Once the introns have been spliced out of a pre-mRNA, the resulting mRNA sequence is ready to be translated into a protein. The corresponding parts of a gene are known as introns as well. The nature and the role of Introns in the pre-mRNA is not clear and it is under ponderous researches by Biologists but, in our case, we will use the presence of Introns in the RNA-Crypto System output as a strong method to add chaotic non coding information and an unnecessary behaviour in the access to the secret key to code the messages. In the RNA-Crypto System algoritnm the introns are sections of the ciphered message with non-coding information as well as in the precursor mRNA.

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

PubMed

Li, Wenli; Turner, Amy; Aggarwal, Praful; Matter, Andrea; Storvick, Erin; Arnett, Donna K; Broeckel, Ulrich

2015-12-16

Whole 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). Using 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. Our 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.

Adenylylation of small RNA sequencing adapters using the TS2126 RNA ligase I.

PubMed

Lama, Lodoe; Ryan, Kevin

2016-01-01

Many high-throughput small RNA next-generation sequencing protocols use 5' preadenylylated DNA oligonucleotide adapters during cDNA library preparation. Preadenylylation of the DNA adapter's 5' end frees from ATP-dependence the ligation of the adapter to RNA collections, thereby avoiding ATP-dependent side reactions. However, preadenylylation of the DNA adapters can be costly and difficult. The currently available method for chemical adenylylation of DNA adapters is inefficient and uses techniques not typically practiced in laboratories profiling cellular RNA expression. An alternative enzymatic method using a commercial RNA ligase was recently introduced, but this enzyme works best as a stoichiometric adenylylating reagent rather than a catalyst and can therefore prove costly when several variant adapters are needed or during scale-up or high-throughput adenylylation procedures. Here, we describe a simple, scalable, and highly efficient method for the 5' adenylylation of DNA oligonucleotides using the thermostable RNA ligase 1 from bacteriophage TS2126. Adapters with 3' blocking groups are adenylylated at >95% yield at catalytic enzyme-to-adapter ratios and need not be gel purified before ligation to RNA acceptors. Experimental conditions are also reported that enable DNA adapters with free 3' ends to be 5' adenylylated at >90% efficiency. © 2015 Lama and Ryan; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

R-chie: a web server and R package for visualizing RNA secondary structures

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Zhu, Jing Yun A.; Meyer, Irmtraud M.

2012-01-01

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems. PMID:22434875

A simple method for construction of artificial microRNA vector in plant.

PubMed

Li, Yang; Li, Yang; Zhao, Sunping; Zhong, Sheng; Wang, Zhaohai; Ding, Bo; Li, Yangsheng

2014-10-01

Artificial microRNA (amiRNA) is a powerful tool for silencing genes in many plant species. Here we provide an easy method to construct amiRNA vectors that reinvents the Golden Gate cloning approach and features a novel system called top speed amiRNA construction (TAC). This speedy approach accomplishes one restriction-ligation step in only 5 min, allowing easy and high-throughput vector construction. Three primers were annealed to be a specific adaptor, then digested and ligated on our novel vector pTAC. Importantly, this method allows the recombined amiRNA constructs to maintain the precursor of osa-miR528 with exception of the desired amiRNA/amiRNA* sequences. Using this method, our results showed the expected decrease of targeted genes in Nicotiana benthamiana and Oryza sativa.

In Vitro Selection for Small-Molecule-Triggered Strand Displacement and Riboswitch Activity.

PubMed

Martini, Laura; Meyer, Adam J; Ellefson, Jared W; Milligan, John N; Forlin, Michele; Ellington, Andrew D; Mansy, Sheref S

2015-10-16

An in vitro selection method for ligand-responsive RNA sensors was developed that exploited strand displacement reactions. The RNA library was based on the thiamine pyrophosphate (TPP) riboswitch, and RNA sequences capable of hybridizing to a target duplex DNA in a TPP regulated manner were identified. After three rounds of selection, RNA molecules that mediated a strand exchange reaction upon TPP binding were enriched. The enriched sequences also showed riboswitch activity. Our results demonstrated that small-molecule-responsive nucleic acid sensors can be selected to control the activity of target nucleic acid circuitry.

Benchmarking of Methods for Genomic Taxonomy

DOE PAGES

Larsen, Mette V.; Cosentino, Salvatore; Lukjancenko, Oksana; ...

2014-02-26

One of the first issues that emerges when a prokaryotic organism of interest is encountered is the question of what it is—that is, which species it is. The 16S rRNA gene formed the basis of the first method for sequence-based taxonomy and has had a tremendous impact on the field of microbiology. Nevertheless, the method has been found to have a number of shortcomings. In this paper, we trained and benchmarked five methods for whole-genome sequence-based prokaryotic species identification on a common data set of complete genomes: (i) SpeciesFinder, which is based on the complete 16S rRNA gene; (ii) Reads2Typemore » that searches for species-specific 50-mers in either the 16S rRNA gene or the gyrB gene (for the Enterobacteraceae family); (iii) the ribosomal multilocus sequence typing (rMLST) method that samples up to 53 ribosomal genes; (iv) TaxonomyFinder, which is based on species-specific functional protein domain profiles; and finally (v) KmerFinder, which examines the number of cooccurring k-mers (substrings of k nucleotides in DNA sequence data). The performances of the methods were subsequently evaluated on three data sets of short sequence reads or draft genomes from public databases. In total, the evaluation sets constituted sequence data from more than 11,000 isolates covering 159 genera and 243 species. Our results indicate that methods that sample only chromosomal, core genes have difficulties in distinguishing closely related species which only recently diverged. Finally, the KmerFinder method had the overall highest accuracy and correctly identified from 93% to 97% of the isolates in the evaluations sets.« less

rpiCOOL: A tool for In Silico RNA-protein interaction detection using random forest.

PubMed

Akbaripour-Elahabad, Mohammad; Zahiri, Javad; Rafeh, Reza; Eslami, Morteza; Azari, Mahboobeh

2016-08-07

Understanding the principle of RNA-protein interactions (RPIs) is of critical importance to provide insights into post-transcriptional gene regulation and is useful to guide studies about many complex diseases. The limitations and difficulties associated with experimental determination of RPIs, call an urgent need to computational methods for RPI prediction. In this paper, we proposed a machine learning method to detect RNA-protein interactions based on sequence information. We used motif information and repetitive patterns, which have been extracted from experimentally validated RNA-protein interactions, in combination with sequence composition as descriptors to build a model to RPI prediction via a random forest classifier. About 20% of the "sequence motifs" and "nucleotide composition" features have been selected as the informative features with the feature selection methods. These results suggest that these two feature types contribute effectively in RPI detection. Results of 10-fold cross-validation experiments on three non-redundant benchmark datasets show a better performance of the proposed method in comparison with the current state-of-the-art methods in terms of various performance measures. In addition, the results revealed that the accuracy of the RPI prediction methods could vary considerably across different organisms. We have implemented the proposed method, namely rpiCOOL, as a stand-alone tool with a user friendly graphical user interface (GUI) that enables the researchers to predict RNA-protein interaction. The rpiCOOL is freely available at http://biocool.ir/rpicool.html for non-commercial uses. Copyright © 2016 Elsevier Ltd. All rights reserved.

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

PubMed Central

2014-01-01

Background Non-coding sequences such as microRNAs have important roles in disease processes. Computational microRNA target identification (CMTI) is becoming increasingly important since traditional experimental methods for target identification pose many difficulties. These methods are time-consuming, costly, and often need guidance from computational methods to narrow down candidate genes anyway. However, most CMTI methods are computationally demanding, since they need to handle not only several million query microRNA and reference RNA pairs, but also several million nucleotide comparisons within each given pair. Thus, the need to perform microRNA identification at such large scale has increased the demand for parallel computing. Methods Although most CMTI programs (e.g., the miRanda algorithm) are based on a modified Smith-Waterman (SW) algorithm, the existing parallel SW implementations (e.g., CUDASW++ 2.0/3.0, SWIPE) are unable to meet this demand in CMTI tasks. We present CUDA-miRanda, a fast microRNA target identification algorithm that takes advantage of massively parallel computing on Graphics Processing Units (GPU) using NVIDIA's Compute Unified Device Architecture (CUDA). CUDA-miRanda specifically focuses on the local alignment of short (i.e., ≤ 32 nucleotides) sequences against longer reference sequences (e.g., 20K nucleotides). Moreover, the proposed algorithm is able to report multiple alignments (up to 191 top scores) and the corresponding traceback sequences for any given (query sequence, reference sequence) pair. Results Speeds over 5.36 Giga Cell Updates Per Second (GCUPs) are achieved on a server with 4 NVIDIA Tesla M2090 GPUs. Compared to the original miRanda algorithm, which is evaluated on an Intel Xeon E5620@2.4 GHz CPU, the experimental results show up to 166 times performance gains in terms of execution time. In addition, we have verified that the exact same targets were predicted in both CUDA-miRanda and the original miRanda implementations through multiple test datasets. Conclusions We offer a GPU-based alternative to high performance compute (HPC) that can be developed locally at a relatively small cost. The community of GPU developers in the biomedical research community, particularly for genome analysis, is still growing. With increasing shared resources, this community will be able to advance CMTI in a very significant manner. Our source code is available at https://sourceforge.net/projects/cudamiranda/. PMID:25077821

Detection of viral sequences in archival spinal cords from fatal cases of poliomyelitis in 1951-1952.

PubMed

Rekand, Tiina; Male, Rune; Myking, Andreas O; Nygaard, Svein J T; Aarli, Johan A; Haarr, Lars; Langeland, Nina

2003-12-01

Poliovirus (PV) subjected to genetic characterization is often isolated from faecal carriage. Such virus is not necessarily identical to the virus causing paralytic disease since genetic modifications may occur during replication outside the nervous system. We have searched for poliovirus genomes in the 14 fatal cases occurring during the last epidemics in Norway in 1951-1952. A method was developed for isolation and analysis of poliovirus RNA from formalin-fixed and paraffin-embedded archival tissue. RNA was purified by incubation with Chelex-100 and heating followed by treatment with the proteinase K and chloroform extraction. Viral sequences were amplified by a reverse transcriptase-polymerase chain reaction (RT-PCR), the products subjected to TA cloning and sequenced. RNA from the beta-actin gene, as a control, was identified in 13 cases, while sequences specific for poliovirus were achieved in 11 cases. The sequences from the 2C region of poliovirus were rather conserved while those in the 5'-untranslated region were variable. The developed method should be suitable also for other genetic studies of old archival material.

Phylogenetic analysis of Fusobacterium prausnitzii based upon the 16S rRNA gene sequence and PCR confirmation.

PubMed

Wang, R F; Cao, W W; Cerniglia, C E

1996-01-01

In order to develop a PCR method to detect Fusobacterium prausnitzii in human feces and to clarify the phylogenetic position of this species, its 16S rRNA gene sequence was determined. The sequence described in this paper is different from the 16S rRNA gene sequence is specific for F. prausnitzii, and the results of this assay confirmed that F. prausnitzii is the most common species in human feces. However, a PCR assay based on the original GenBank sequence was negative when it was performed with two strains of F. prausnitzii obtained from the American Type Culture Collection. A phylogenetic tree based on the new 16S rRNA gene sequence was constructed. On this tree F. prausnitzii was not a member of the Fusobacterium group but was closer to some Eubacterium spp. and located between Clostridium "clusters III and IV" (M.D. Collins, P.A. Lawson, A. Willems, J.J. Cordoba, J. Fernandez-Garayzabal, P. Garcia, J. Cai, H. Hippe, and J.A.E. Farrow, Int. J. Syst. Bacteriol. 44:812-826, 1994).

Pseudouridines have context-dependent mutation and stop rates in high-throughput sequencing.

PubMed

Zhou, Katherine I; Clark, Wesley C; Pan, David W; Eckwahl, Matthew J; Dai, Qing; Pan, Tao

2018-05-11

The abundant RNA modification pseudouridine (Ψ) has been mapped transcriptome-wide by chemically modifying pseudouridines with carbodiimide and detecting the resulting reverse transcription stops in high-throughput sequencing. However, these methods have limited sensitivity and specificity, in part due to the use of reverse transcription stops. We sought to use mutations rather than just stops in sequencing data to identify pseudouridine sites. Here, we identify reverse transcription conditions that allow read-through of carbodiimide-modified pseudouridine (CMC-Ψ), and we show that pseudouridines in carbodiimide-treated human ribosomal RNA have context-dependent mutation and stop rates in high-throughput sequencing libraries prepared under these conditions. Furthermore, accounting for the context-dependence of mutation and stop rates can enhance the detection of pseudouridine sites. Similar approaches could contribute to the sequencing-based detection of many RNA modifications.

Rapid amplification of 5' complementary DNA ends (5' RACE).

PubMed

2005-08-01

This method is used to extend partial cDNA clones by amplifying the 5' sequences of the corresponding mRNAs 1-3. The technique requires knowledge of only a small region of sequence within the partial cDNA clone. During PCR, the thermostable DNA polymerase is directed to the appropriate target RNA by a single primer derived from the region of known sequence; the second primer required for PCR is complementary to a general feature of the target-in the case of 5' RACE, to a homopolymeric tail added (via terminal transferase) to the 3' termini of cDNAs transcribed from a preparation of mRNA. This synthetic tail provides a primer-binding site upstream of the unknown 5' sequence of the target mRNA. The products of the amplification reaction are cloned into a plasmid vector for sequencing and subsequent manipulation.

Next-generation sequencing facilitates quantitative analysis of wild-type and Nrl−/− retinal transcriptomes

PubMed Central

Brooks, Matthew J.; Rajasimha, Harsha K.; Roger, Jerome E.

2011-01-01

Purpose Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. PMID:22162623

RNAstructure: software for RNA secondary structure prediction and analysis.

PubMed

Reuter, Jessica S; Mathews, David H

2010-03-15

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

Isothermal folding of a light-up bio-orthogonal RNA origami nanoribbon.

PubMed

Torelli, Emanuela; Kozyra, Jerzy Wieslaw; Gu, Jing-Ying; Stimming, Ulrich; Piantanida, Luca; Voïtchovsky, Kislon; Krasnogor, Natalio

2018-05-03

RNA presents intringuing roles in many cellular processes and its versatility underpins many different applications in synthetic biology. Nonetheless, RNA origami as a method for nanofabrication is not yet fully explored and the majority of RNA nanostructures are based on natural pre-folded RNA. Here we describe a biologically inert and uniquely addressable RNA origami scaffold that self-assembles into a nanoribbon by seven staple strands. An algorithm is applied to generate a synthetic De Bruijn scaffold sequence that is characterized by the lack of biologically active sites and repetitions larger than a predetermined design parameter. This RNA scaffold and the complementary staples fold in a physiologically compatible isothermal condition. In order to monitor the folding, we designed a new split Broccoli aptamer system. The aptamer is divided into two nonfunctional sequences each of which is integrated into the 5' or 3' end of two staple strands complementary to the RNA scaffold. Using fluorescence measurements and in-gel imaging, we demonstrate that once RNA origami assembly occurs, the split aptamer sequences are brought into close proximity forming the aptamer and turning on the fluorescence. This light-up 'bio-orthogonal' RNA origami provides a prototype that can have potential for in vivo origami applications.

Methods for determining the genetic affinity of microorganisms and viruses

NASA Technical Reports Server (NTRS)

Fox, George E. (Inventor); Willson, III, Richard C. (Inventor); Zhang, Zhengdong (Inventor)

2012-01-01

Selecting which sub-sequences in a database of nucleic acid such as 16S rRNA are highly characteristic of particular groupings of bacteria, microorganisms, fungi, etc. on a substantially phylogenetic tree. Also applicable to viruses comprising viral genomic RNA or DNA. A catalogue of highly characteristic sequences identified by this method is assembled to establish the genetic identity of an unknown organism. The characteristic sequences are used to design nucleic acid hybridization probes that include the characteristic sequence or its complement, or are derived from one or more characteristic sequences. A plurality of these characteristic sequences is used in hybridization to determine the phylogenetic tree position of the organism(s) in a sample. Those target organisms represented in the original sequence database and sufficient characteristic sequences can identify to the species or subspecies level. Oligonucleotide arrays of many probes are especially preferred. A hybridization signal can comprise fluorescence, chemiluminescence, or isotopic labeling, etc.; or sequences in a sample can be detected by direct means, e.g. mass spectrometry. The method's characteristic sequences can also be used to design specific PCR primers. The method uniquely identifies the phylogenetic affinity of an unknown organism without requiring prior knowledge of what is present in the sample. Even if the organism has not been previously encountered, the method still provides useful information about which phylogenetic tree bifurcation nodes encompass the organism.

Toward a General Approach for RNA-Templated Hierarchical Assembly of Split-Proteins

PubMed Central

Furman, Jennifer L.; Badran, Ahmed H.; Ajulo, Oluyomi; Porter, Jason R.; Stains, Cliff I.; Segal, David J.; Ghosh, Indraneel

2010-01-01

The ability to conditionally turn on a signal or induce a function in the presence of a user-defined RNA target has potential applications in medicine and synthetic biology. Although sequence-specific pumilio repeat proteins can target a limited set of ssRNA sequences, there are no general methods for targeting ssRNA with designed proteins. As a first step toward RNA recognition, we utilized the RNA binding domain of argonaute, implicated in RNA interference, for specifically targeting generic 2-nucleotide, 3' overhangs of any dsRNA. We tested the reassembly of a split-luciferase enzyme guided by argonaute-mediated recognition of newly generated nucleotide overhangs when ssRNA is targeted by a designed complementary guide sequence. This approach was successful when argonaute was utilized in conjunction with a pumilio repeat and expanded the scope of potential ssRNA targets. However, targeting any desired ssRNA remained elusive as two argonaute domains provided minimal reassembled split-luciferase. We next designed and tested a second hierarchical assembly, wherein ssDNA guides are appended to DNA hairpins that serve as a scaffold for high affinity zinc fingers attached to split-luciferase. In the presence of a ssRNA target containing adjacent sequences complementary to the guides, the hairpins are brought into proximity, allowing for zinc finger binding and concomitant reassembly of the fragmented luciferase. The scope of this new approach was validated by specifically targeting RNA encoding VEGF, hDM2, and HER2. These approaches provide potentially general design paradigms for the conditional reassembly of fragmented proteins in the presence of any desired ssRNA target. PMID:20681585

Isolation and identification of multidrug-resistant Staphylococcus haemolyticus from a laboratory-breeding mouse.

PubMed

Huang, Fengying; Meng, Qiuping; Tan, Guanghong; Huang, Yonghao; Wang, Hua; Mei, Wenli; Dai, Haofu

2011-06-01

To analysis and identify a bacterium strain isolated from laboratory breeding mouse far away from a hospital. Phenotype of the isolate was investigated by conventional microbiological methods, including Gram-staining, colony morphology, tests for haemolysis, catalase, coagulase, and antimicrobial susceptibility test. The mecA and 16S rRNA genes were amplified by the polymerase chain reaction (PCR) and sequenced. The base sequence of the PCR product was compared with known 16S rRNA gene sequences in the GenBank database by phylogenetic analysis and multiple sequence alignment. The isolate in this study was a gram positive, coagulase negative, and catalase positive coccus. The isolate was resistant to oxacillin, methicillin, penicillin, ampicillin, cefazolin, ciprofloxacin erythromycin, et al. PCR results indicated that the isolate was mecA gene positive and its 16S rRNA was 1 465 bp. Phylogenetic analysis of the resultant 16S rRNA indicated the isolate belonged to genus Saphylococcus, and multiple sequence alignment showed that the isolate was Saphylococcus haemolyticus with only one base difference from the corresponding 16S rRNA deposited in the GenBank. 16S rRNA gene sequencing is a suitable technique for non-specialist researchers. Laboratory animals are possible sources of lethal pathogens, and researchers must adapt protective measures when they manipulate animals. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

RNA editing: trypanosomes rewrite the genetic code.

PubMed

Stuart, K

1998-01-01

The understanding of how genetic information is stored and expressed has advanced considerably since the "central dogma" asserted that genetic information flows from the nucleotide sequence of DNA to that of messenger RNA (mRNA) which in turn specifies the amino acid sequence of a protein. It was found that genetic information can be stored as RNA (e.g. in RNA viruses) and can flow from RNA to DNA by reverse transcriptase enzyme activity. In addition, some genes contain introns, nucleotide sequences that are removed from their RNA (by RNA splicing) and thus are not represented in the resultant protein. Furthermore, alternative splicing was found to produce variant proteins from a single gene. More recently, the study of trypanosome parasites revealed an unexpected and indeed counter-intuitive genetic complexity. Genetic information for a single protein can be dispersed among several (DNA) genes in these organisms. One of these genes specifies an encrypted precursor mRNA that is converted to a functional mRNA by a process called RNA editing that inserts and deletes uridylate nucleotides. The sequence of the edited mRNA is specified by multiple small RNAs, named guide RNAs, (gRNAs) each of which is encoded in a separate gene. Thus, edited mRNA sequences are assembled from multiple genes by the transfer of information from one type of RNA to another. The existence of editing was surprising but has stimulated the discovery of other types of RNA editing. The Stuart laboratory has been exploring RNA editing in trypanosomes from the time of its discovery. They found dramatic differences between the mitochondrial gene sequences and those of the corresponding mRNAs, which indicated editing by the insertion and deletion of uridylates. Some editing was modest; simply eliminating shifts in sequence register of minimally extending the protein coding sequence. However, editing of many mRNAs was startingly extensive. The RNA sequence was essentially entirely remodeled with its sequence more the result of editing than the gene sequence. The identities of genes for such extensively edited RNA were not recognizable from the DNA sequence but they were readily identifiable from the edited mRNA sequence. Thus, despite the complex and extensive editing the resultant mRNA sequence is precise. Characterization of partially edited RNAs indicated that editing proceeds in the direction opposite to that used to specify the protein which reflects the use of the gRNAs. The numerous gRNAs that are used for editing are encoded in the DNA molecules whose role was previously a mystery. Using information gained in our earlier studies, the Stuart group developed an in vitro system that reproduces the fundamental process of editing in order to resolve the mechanism by which it occurs. They determined that editing entails a series of enzymatic steps rather than the mechanism used in RNA splicing. They also showed that chimeric gRNA-mRNA molecules are aberrant by-products of editing rather than intermediates in the process as had been proposed. Additional studies are exploring precisely how the number of added and deleted uridylates is specified by the gRNA. The Stuart laboratory showed that editing is performed by an aggregation of enzymes that catalyze the separate steps of editing. It also developed a method to purify this multimolecule complex that contains several, perhaps tens of, proteins. This will allow the study of its composition and the functions of its component parts. Indeed, the gene for one component has been identified and its detailed characterization begun. These studies are developing tools to explore related processes. An early finding in the lab was that the various mRNAs are differentially edited during the life cycle of the parasite. The pattern of this editing indicates that editing serves to regulate the alternation between two modes of energy generation. This regulation is coordinated with other events that are occurring during the life c

In silico analysis of 16S ribosomal RNA gene sequencing‐based methods for identification of medically important anaerobic bacteria

PubMed Central

Woo, Patrick C Y; Chung, Liliane M W; Teng, Jade L L; Tse, Herman; Pang, Sherby S Y; Lau, Veronica Y T; Wong, Vanessa W K; Kam, Kwok‐ling; Lau, Susanna K P; Yuen, Kwok‐Yung

2007-01-01

This study is the first study that provides useful guidelines to clinical microbiologists and technicians on the usefulness of full 16S rRNA sequencing, 5′‐end 527‐bp 16S rRNA sequencing and the existing MicroSeq full and 500 16S rDNA bacterial identification system (MicroSeq, Perkin‐Elmer Applied Biosystems Division, Foster City, California, USA) databases for the identification of all existing medically important anaerobic bacteria. Full and 527‐bp 16S rRNA sequencing are able to identify 52–63% of 130 Gram‐positive anaerobic rods, 72–73% of 86 Gram‐negative anaerobic rods and 78% of 23 anaerobic cocci. The existing MicroSeq databases are able to identify only 19–25% of 130 Gram‐positive anaerobic rods, 38% of 86 Gram‐negative anaerobic rods and 39% of 23 anaerobic cocci. These represent only 45–46% of those that should be confidently identified by full and 527‐bp 16S rRNA sequencing. To improve the usefulness of MicroSeq, bacterial species that should be confidently identified by full and/or 527‐bp 16S rRNA sequencing but not included in the existing MicroSeq databases should be included. PMID:17046845

Phylogenetic Analysis of Myobia musculi (Schranck, 1781) by Using the 18S Small Ribosomal Subunit Sequence

PubMed Central

Feldman, Sanford H; Ntenda, Abraham M

2011-01-01

We used high-fidelity PCR to amplify 2 overlapping regions of the ribosomal gene complex from the rodent fur mite Myobia musculi. The amplicons encompassed a large portion of the mite's ribosomal gene complex spanning 3128 nucleotides containing the entire 18S rRNA, internal transcribed spacer (ITS) 1, 5.8S rRNA, ITS2, and a portion of the 5′-end of the 28S rRNA. M. musculi’s 179-nucleotide 5.8S rRNA nucleotide sequence was not conserved, so this region was identified by conservation of rRNA secondary structure. Maximum likelihood and Bayesian inference phylogenetic analyses were performed by using multiple sequence alignment consisting of 1524 nucleotides of M. musculi 18S rRNA and homologous sequences from 42 prostigmatid mites and the tick Dermacentor andersoni. The phylograms produced by both methods were in agreement regarding terminal, secondary, and some tertiary phylogenetic relationships among mites. Bayesian inference discriminated most infraordinal relationships between Eleutherengona and Parasitengona mites in the suborder Anystina. Basal relationships between suborders Anystina and Eupodina historically determined by comparing differences in anatomic characteristics were less well-supported by our molecular analysis. Our results recapitulated similar 18S rRNA sequence analyses recently reported. Our study supports M. musculi as belonging to the suborder Anystina, infraorder Eleutherenona, and superfamily Cheyletoidea. PMID:22330574

A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments.

PubMed

Bansal, Vikas

2017-03-14

PCR amplification is an important step in the preparation of DNA sequencing libraries prior to high-throughput sequencing. PCR amplification introduces redundant reads in the sequence data and estimating the PCR duplication rate is important to assess the frequency of such reads. Existing computational methods do not distinguish PCR duplicates from "natural" read duplicates that represent independent DNA fragments and therefore, over-estimate the PCR duplication rate for DNA-seq and RNA-seq experiments. In this paper, we present a computational method to estimate the average PCR duplication rate of high-throughput sequence datasets that accounts for natural read duplicates by leveraging heterozygous variants in an individual genome. Analysis of simulated data and exome sequence data from the 1000 Genomes project demonstrated that our method can accurately estimate the PCR duplication rate on paired-end as well as single-end read datasets which contain a high proportion of natural read duplicates. Further, analysis of exome datasets prepared using the Nextera library preparation method indicated that 45-50% of read duplicates correspond to natural read duplicates likely due to fragmentation bias. Finally, analysis of RNA-seq datasets from individuals in the 1000 Genomes project demonstrated that 70-95% of read duplicates observed in such datasets correspond to natural duplicates sampled from genes with high expression and identified outlier samples with a 2-fold greater PCR duplication rate than other samples. The method described here is a useful tool for estimating the PCR duplication rate of high-throughput sequence datasets and for assessing the fraction of read duplicates that correspond to natural read duplicates. An implementation of the method is available at https://github.com/vibansal/PCRduplicates .

Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences | Center for Cancer Research

Cancer.gov

A graphical method is presented for displaying how binding proteins and other macromolecules interact with individual bases of nucleotide sequences. Characters representing the sequence are either oriented normally and placed above a line indicating favorable contact, or upside-down and placed below the line indicating unfavorable contact. The positive or negative height of

Human ribosomal RNA gene: nucleotide sequence of the transcription initiation region and comparison of three mammalian genes.

PubMed Central

Financsek, I; Mizumoto, K; Mishima, Y; Muramatsu, M

1982-01-01

The transcription initiation site of the human ribosomal RNA gene (rDNA) was located by using the single-strand specific nuclease protection method and by determining the first nucleotide of the in vitro capped 45S preribosomal RNA. The sequence of 1,211 nucleotides surrounding the initiation site was determined. The sequenced region was found to consist of 75% G and C and to contain a number of short direct and inverted repeats and palindromes. By comparison of the corresponding initiation regions of three mammalian species, several conserved sequences were found upstream and downstream from the transcription starting point. Two short A + T-rich sequences are present on human, mouse, and rat ribosomal RNA genes between the initiation site and 40 nucleotides upstream, and a C + T cluster is located at a position around -60. At and downstream from the initiation site, a common sequence, T-AG-C-T-G-A-C-A-C-G-C-T-G-T-C-C-T-CT-T, was found in the three genes from position -1 through +18. The strong conservation of these sequences suggests their functional significance in rDNA. The S1 nuclease protection experiments with cloned rDNA fragments indicated the presence in human 45S RNA of molecules several hundred nucleotides shorter than the supposed primary transcript. The first 19 nucleotides of these molecules appear identical--except for one mismatch--to the nucleotide sequence of the 5' end of a supposed early processing product of the mouse 45S RNA. Images PMID:6954460

Frnakenstein: multiple target inverse RNA folding.

PubMed

Lyngsø, Rune B; Anderson, James W J; Sizikova, Elena; Badugu, Amarendra; Hyland, Tomas; Hein, Jotun

2012-10-09

RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.

Frnakenstein: multiple target inverse RNA folding

PubMed Central

2012-01-01

Background RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. Results In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Conclusions Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein. PMID:23043260

StarScan: a web server for scanning small RNA targets from degradome sequencing data.

PubMed

Liu, Shun; Li, Jun-Hao; Wu, Jie; Zhou, Ke-Ren; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2015-07-01

Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites. In this study, an integrated web-based tool, StarScan (sRNA target Scan), was developed for scanning sRNA targets using degradome sequencing data from 20 species. Given a sRNA sequence from plants or animals, our web server performs an ultrafast and exhaustive search for potential sRNA-target interactions in annotated and unannotated genomic regions. The interactions between small RNAs and target transcripts were further evaluated using a novel tool, alignScore. A novel tool, degradomeBinomTest, was developed to quantify the abundance of degradome fragments located at the 9-11th nucleotide from the sRNA 5' end. This is the first web server for discovering potential sRNA-mediated RNA cleavage events in plants and animals, which affords mechanistic insights into the regulatory roles of sRNAs. The StarScan web server is available at http://mirlab.sysu.edu.cn/starscan/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

PubMed

Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

2017-01-21

RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA comparison tools, RNApdist and RNAdistance, showcased that RNA-TVcurve can efficiently capture subtle relationships among RNAs for mutation detection and non-coding RNA classification. All the relevant results were shown in an intuitive graphical manner, and can be freely downloaded from this server. RNA-TVcurve, along with test examples and detailed documents, are available at: http://ml.jlu.edu.cn/tvcurve/ .

A novel polydopamine-based chemiluminescence resonance energy transfer method for microRNA detection coupling duplex-specific nuclease-aided target recycling strategy.

PubMed

Wang, Qian; Yin, Bin-Cheng; Ye, Bang-Ce

2016-06-15

MicroRNAs (miRNAs), functioning as oncogenes or tumor suppressors, play significant regulatory roles in regulating gene expression and become as biomarkers for disease diagnostics and therapeutics. In this work, we have coupled a polydopamine (PDA) nanosphere-assisted chemiluminescence resonance energy transfer (CRET) platform and a duplex-specific nuclease (DSN)-assisted signal amplification strategy to develop a novel method for specific miRNA detection. With the assistance of hemin, luminol, and H2O2, the horseradish peroxidase (HRP)-mimicking G-rich sequence in the sensing probe produces chemiluminescence, which is quickly quenched by the CRET effect between PDA as energy acceptor and excited luminol as energy donor. The target miRNA triggers DSN to partially degrade the sensing probe in the DNA-miRNA heteroduplex to repeatedly release G-quadruplex formed by G-rich sequence from PDA for the production of chemiluminescence. The method allows quantitative detection of target miRNA in the range of 80 pM-50 nM with a detection limit of 49.6 pM. The method also shows excellent specificity to discriminate single-base differences, and can accurately quantify miRNA in biological samples, with good agreement with the result from a commercial miRNA detection kit. The procedure requires no organic dyes or labels, and is a simple and cost-effective method for miRNA detection for early clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of tissue sample processing methods for harvesting the viral metagenome and a snapshot of the RNA viral community in a turkey gut.

PubMed

Shah, Jigna D; Baller, Joshua; Zhang, Ying; Silverstein, Kevin; Xing, Zheng; Cardona, Carol J

2014-12-01

RNA viruses have been associated with enteritis in poultry and have been isolated from diseased birds. The same viral agents have also been detected in healthy flocks bringing into question their role in health and disease. In order to understand better eukaryotic viruses in the gut, this project focused on evaluating alternative methods to purify and concentrate viral particles, which do not involve the use of density gradients, for generating viral metagenome data. In this study, the sequence outcomes of three tissue processing methods have been evaluated and a data analysis pipeline has been established for RNA viruses from the gastrointestinal tract. In addition, with the use of the best method and increased sequencing depth, a glimpse of the RNA viral community in the gastrointestinal tract of a clinically normal 5-week old turkey is presented. The viruses from the Reoviridae and Astroviridae families together accounted for 76.3% of total viruses identified. The rarefaction curve at the species level further indicated that majority of the species diversity was included with the increased sequencing depth, implying that viruses from other viral families were present in very low abundance. Copyright © 2014 Elsevier B.V. All rights reserved.

Fine-tuning structural RNA alignments in the twilight zone

PubMed Central

2010-01-01

Background A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Results Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Conclusions Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index. PMID:20433706

CID-miRNA: A web server for prediction of novel miRNA precursors in human genome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tyagi, Sonika; Vaz, Candida; Gupta, Vipin

2008-08-08

microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filteringmore » systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at (http://mirna.jnu.ac.in/cidmirna/)« less

Using hidden Markov models and observed evolution to annotate viral genomes.

PubMed

McCauley, Stephen; Hein, Jotun

2006-06-01

ssRNA (single stranded) viral genomes are generally constrained in length and utilize overlapping reading frames to maximally exploit the coding potential within the genome length restrictions. This overlapping coding phenomenon leads to complex evolutionary constraints operating on the genome. In regions which code for more than one protein, silent mutations in one reading frame generally have a protein coding effect in another. To maximize coding flexibility in all reading frames, overlapping regions are often compositionally biased towards amino acids which are 6-fold degenerate with respect to the 64 codon alphabet. Previous methodologies have used this fact in an ad hoc manner to look for overlapping genes by motif matching. In this paper differentiated nucleotide compositional patterns in overlapping regions are incorporated into a probabilistic hidden Markov model (HMM) framework which is used to annotate ssRNA viral genomes. This work focuses on single sequence annotation and applies an HMM framework to ssRNA viral annotation. A description of how the HMM is parameterized, whilst annotating within a missing data framework is given. A Phylogenetic HMM (Phylo-HMM) extension, as applied to 14 aligned HIV2 sequences is also presented. This evolutionary extension serves as an illustration of the potential of the Phylo-HMM framework for ssRNA viral genomic annotation. The single sequence annotation procedure (SSA) is applied to 14 different strains of the HIV2 virus. Further results on alternative ssRNA viral genomes are presented to illustrate more generally the performance of the method. The results of the SSA method are encouraging however there is still room for improvement, and since there is overwhelming evidence to indicate that comparative methods can improve coding sequence (CDS) annotation, the SSA method is extended to a Phylo-HMM to incorporate evolutionary information. The Phylo-HMM extension is applied to the same set of 14 HIV2 sequences which are pre-aligned. The performance improvement that results from including the evolutionary information in the analysis is illustrated.

miR-ID: A novel, circularization-based platform for detection of microRNAs

PubMed Central

Kumar, Pavan; Johnston, Brian H.; Kazakov, Sergei A.

2011-01-01

MicroRNAs (miRNAs) are important regulators of gene expression and have great potential as biomarkers, prognostic indicators, and therapeutic targets. Determining the expression patterns of these molecules is essential for elucidating their biogenesis, regulation, relation to disease, and response to therapy. Although PCR-based assays are commonly used for expression profiling of miRNAs, the small size, sequence heterogeneity, and (in some cases) end modifications of miRNAs constrain the performance of existing PCR methods. Here we introduce miR-ID, a novel method that avoids these constraints while providing superior sensitivity and sequence specificity at a lower cost. It also has the unique ability to differentiate unmodified small RNAs from those carrying 2′-OMe groups at their 3′-ends while detecting both forms. miR-ID is comprised of the following steps: (1) circularization of the miRNA by a ligase; (2) reverse transcription of the circularized miRNA (RTC), producing tandem repeats of a DNA sequence complementary to the miRNA; and (3) qPCR amplification of segments of this multimeric cDNA using 5′-overlapping primers and a nonspecific dye such as SYBR Green. No chemically modified probes (e.g., TaqMan) or primers (e.g., LNA) are required. The circular RNA and multimeric cDNA templates provide unmatched flexibility in the positioning of primers, which may include straddling the boundaries between these repetitive miRNA sequences. miR-ID is based on new findings that are themselves of general interest, including reverse transcription of small RNA circles and the use of 5′-overlapping primers for detection of repetitive sequences by qPCR. PMID:21169480

Rapid Identification of Cell-Specific, Internalizing RNA Aptamers with Bioinformatics Analyses of a Cell-Based Aptamer Selection

PubMed Central

Thiel, William H.; Bair, Thomas; Peek, Andrew S.; Liu, Xiuying; Dassie, Justin; Stockdale, Katie R.; Behlke, Mark A.; Miller, Francis J.; Giangrande, Paloma H.

2012-01-01

Background The broad applicability of RNA aptamers as cell-specific delivery tools for therapeutic reagents depends on the ability to identify aptamer sequences that selectively access the cytoplasm of distinct cell types. Towards this end, we have developed a novel approach that combines a cell-based selection method (cell-internalization SELEX) with high-throughput sequencing (HTS) and bioinformatics analyses to rapidly identify cell-specific, internalization-competent RNA aptamers. Methodology/Principal Findings We demonstrate the utility of this approach by enriching for RNA aptamers capable of selective internalization into vascular smooth muscle cells (VSMCs). Several rounds of positive (VSMCs) and negative (endothelial cells; ECs) selection were performed to enrich for aptamer sequences that preferentially internalize into VSMCs. To identify candidate RNA aptamer sequences, HTS data from each round of selection were analyzed using bioinformatics methods: (1) metrics of selection enrichment; and (2) pairwise comparisons of sequence and structural similarity, termed edit and tree distance, respectively. Correlation analyses of experimentally validated aptamers or rounds revealed that the best cell-specific, internalizing aptamers are enriched as a result of the negative selection step performed against ECs. Conclusions and Significance We describe a novel approach that combines cell-internalization SELEX with HTS and bioinformatics analysis to identify cell-specific, cell-internalizing RNA aptamers. Our data highlight the importance of performing a pre-clear step against a non-target cell in order to select for cell-specific aptamers. We expect the extended use of this approach to enable the identification of aptamers to a multitude of different cell types, thereby facilitating the broad development of targeted cell therapies. PMID:22962591

A Simple Method for Amplifying RNA Targets (SMART)

PubMed Central

McCalla, Stephanie E.; Ong, Carmichael; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

We present a novel and simple method for amplifying RNA targets (named by its acronym, SMART), and for detection, using engineered amplification probes that overcome existing limitations of current RNA-based technologies. This system amplifies and detects optimal engineered ssDNA probes that hybridize to target RNA. The amplifiable probe-target RNA complex is captured on magnetic beads using a sequence-specific capture probe and is separated from unbound probe using a novel microfluidic technique. Hybridization sequences are not constrained as they are in conventional target-amplification reactions such as nucleic acid sequence amplification (NASBA). Our engineered ssDNA probe was amplified both off-chip and in a microchip reservoir at the end of the separation microchannel using isothermal NASBA. Optimal solution conditions for ssDNA amplification were investigated. Although KCl and MgCl2 are typically found in NASBA reactions, replacing 70 mmol/L of the 82 mmol/L total chloride ions with acetate resulted in optimal reaction conditions, particularly for low but clinically relevant probe concentrations (≤100 fmol/L). With the optimal probe design and solution conditions, we also successfully removed the initial heating step of NASBA, thus achieving a true isothermal reaction. The SMART assay using a synthetic model influenza DNA target sequence served as a fundamental demonstration of the efficacy of the capture and microfluidic separation system, thus bridging our system to a clinically relevant detection problem. PMID:22691910

LDAP: a web server for lncRNA-disease association prediction.

PubMed

Lan, Wei; Li, Min; Zhao, Kaijie; Liu, Jin; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2017-02-01

Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity. The web server is available at http://bioinformatics.csu.edu.cn/ldap jxwang@mail.csu.edu.cn. Supplementary data are available at Bioinformatics online.

Isolation and characterization of 5S rDNA sequences in catfishes genome (Heptapteridae and Pseudopimelodidae): perspectives for rDNA studies in fish by C0t method.

PubMed

Gouveia, Juceli Gonzalez; Wolf, Ivan Rodrigo; de Moraes-Manécolo, Vivian Patrícia Oliveira; Bardella, Vanessa Belline; Ferracin, Lara Munique; Giuliano-Caetano, Lucia; da Rosa, Renata; Dias, Ana Lúcia

2016-12-01

Sequences of 5S ribosomal RNA (rRNA) are extensively used in fish cytogenomic studies, once they have a flexible organization at the chromosomal level, showing inter- and intra-specific variation in number and position in karyotypes. Sequences from the genome of Imparfinis schubarti (Heptapteridae) were isolated, aiming to understand the organization of 5S rDNA families in the fish genome. The isolation of 5S rDNA from the genome of I. schubarti was carried out by reassociation kinetics (C 0 t) and PCR amplification. The obtained sequences were cloned for the construction of a micro-library. The obtained clones were sequenced and hybridized in I. schubarti and Microglanis cottoides (Pseudopimelodidae) for chromosome mapping. An analysis of the sequence alignments with other fish groups was accomplished. Both methods were effective when using 5S rDNA for hybridization in I. schubarti genome. However, the C 0 t method enabled the use of a complete 5S rRNA gene, which was also successful in the hybridization of M. cottoides. Nevertheless, this gene was obtained only partially by PCR. The hybridization results and sequence analyses showed that intact 5S regions are more appropriate for the probe operation, due to conserved structure and motifs. This study contributes to a better understanding of the organization of multigene families in catfish's genomes.

Identification of microRNAs differentially expressed involved in male flower development.

PubMed

Wang, Zhengjia; Huang, Jianqin; Sun, Zhichao; Zheng, Bingsong

2015-03-01

Hickory (Carya cathayensis Sarg.) is one of the most economically important woody trees in eastern China, but its long flowering phase delays yield. Our understanding of the regulatory roles of microRNAs (miRNAs) in male flower development in hickory remains poor. Using high-throughput sequencing technology, we have pyrosequenced two small RNA libraries from two male flower differentiation stages in hickory. Analysis of the sequencing data identified 114 conserved miRNAs that belonged to 23 miRNA families, five novel miRNAs including their corresponding miRNA*s, and 22 plausible miRNA candidates. Differential expression analysis revealed 12 miRNA sequences that were upregulated in the later (reproductive) stage of male flower development. Quantitative real-time PCR showed similar expression trends as that of the deep sequencing. Novel miRNAs and plausible miRNA candidates were predicted using bioinformatic analysis methods. The miRNAs newly identified in this study have increased the number of known miRNAs in hickory, and the identification of differentially expressed miRNAs will provide new avenues for studies into miRNAs involved in the process of male flower development in hickory and other related trees.

The complete nucleotide sequence and genome organization of a novel betaflexivirus infecting Citrullus lanatus.

PubMed

Xin, Min; Zhang, Peipei; Liu, Wenwen; Ren, Yingdang; Cao, Mengji; Wang, Xifeng

2017-10-01

The complete nucleotide sequence of a novel positive single-stranded (+ss) RNA virus, tentatively named watermelon virus A (WVA), was determined using a combination of three methods: RNA sequencing, small RNA sequencing, and Sanger sequencing. The full genome of WVA is comprised of 8,372 nucleotides (nt), excluding the poly (A) tail, and contains four open reading frames (ORFs). The largest ORF, ORF1 encodes a putative replication-associated polyprotein (RP) with three conserved domains. ORF2 and ORF4 encode a movement protein (MP) and coat protein (CP), respectively. The putative product encoded by ORF3, of an estimated molecular mass of 25 kDa, has no significant similarity with other proteins. Identity and phylogenetic analysis indicate that WVA is a new virus, closely related to members of the family Betaflexiviridae. However, the final taxonomic allocation of WVA within the family is yet to be determined.

Removing the needle from the haystack: Enrichment of Wolbachia endosymbiont transcripts from host nematode RNA by Cappable-seq™.

PubMed

Luck, Ashley N; Slatko, Barton E; Foster, Jeremy M

2017-01-01

Efficient transcriptomic sequencing of microbial mRNA derived from host-microbe associations is often compromised by the much lower relative abundance of microbial RNA in the mixed total RNA sample. One solution to this problem is to perform extensive sequencing until an acceptable level of transcriptome coverage is obtained. More cost-effective methods include use of prokaryotic and/or eukaryotic rRNA depletion strategies, sometimes in conjunction with depletion of polyadenylated eukaryotic mRNA. Here, we report use of Cappable-seq™ to specifically enrich, in a single step, Wolbachia endobacterial mRNA transcripts from total RNA prepared from the parasitic filarial nematode, Brugia malayi. The obligate Wolbachia endosymbiont is a proven drug target for many human filarial infections, yet the precise nature of its symbiosis with the nematode host is poorly understood. Insightful analysis of the expression levels of Wolbachia genes predicted to underpin the mutualistic association and of known drug target genes at different life cycle stages or in response to drug treatments is typically challenged by low transcriptomic coverage. Cappable-seq resulted in up to ~ 5-fold increase in the number of reads mapping to Wolbachia. On average, coverage of Wolbachia transcripts from B. malayi microfilariae was enriched ~40-fold by Cappable-seq. Additionally, this method has an additional benefit of selectively removing abundant prokaryotic ribosomal RNAs.The deeper microbial transcriptome sequencing afforded by Cappable-seq facilitates more detailed characterization of gene expression levels of pathogens and symbionts present in animal tissues.

Methods to enable the design of bioactive small molecules targeting RNA

PubMed Central

Disney, Matthew D.; Yildirim, Ilyas; Childs-Disney, Jessica L.

2014-01-01

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including Structure-Activity Relationships Through Sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome. PMID:24357181

Methods to enable the design of bioactive small molecules targeting RNA.

PubMed

Disney, Matthew D; Yildirim, Ilyas; Childs-Disney, Jessica L

2014-02-21

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Strategies for Improving siRNA-Induced Gene Silencing Efficiency

PubMed Central

Safari, Fatemeh; Rahmani Barouji, Solmaz; Tamaddon, Ali Mohammad

2017-01-01

Purpose: Human telomerase reverse transcriptase (hTERT) plays a crucial role in tumorigenesis and progression of cancers. Gene silencing of hTERT by short interfering RNA (siRNA) is considered as a promising strategy for cancer gene therapy. Various algorithms have been devised for designing a high efficient siRNA which is a significant issue in the clinical usage. Thereby, in the present study, the relation of siRNA designing criteria and the gene silencing efficiency was evaluated. Methods: The siRNA sequences were designed and characterized by using on line soft wares. Cationic co-polymer (polyethylene glycol-g-polyethylene imine (PEG-g-PEI)) was used for the construction of polyelectrolyte complexes (PECs) containing siRNAs. The cellular uptake of the PECs was evaluated. The gene silencing efficiency of different siRNA sequences was investigated and the effect of observing the rational designing on the functionality of siRNAs was assessed. Results: The size of PEG-g-PEI siRNA with N/P (Nitrogen/Phosphate) ratio of 2.5 was 114 ± 0.645 nm. The transfection efficiency of PECs was desirable (95.5% ± 2.4%.). The results of Real-Time PCR showed that main sequence (MS) reduced the hTERT expression up to 90% and control positive sequence (CPS) up to 63%. These findings demonstrated that the accessibility to the target site has priority than the other criteria such as sequence preferences and thermodynamic features. Conclusion: siRNA opens a hopeful window in cancer therapy which provides a convenient and tolerable therapeutic approach. Thereby, using the set of criteria and rational algorithms in the designing of siRNA remarkably affect the gene silencing efficiency. PMID:29399550

Strategies for Improving siRNA-Induced Gene Silencing Efficiency.

PubMed

Safari, Fatemeh; Rahmani Barouji, Solmaz; Tamaddon, Ali Mohammad

2017-12-01

Purpose: Human telomerase reverse transcriptase (hTERT) plays a crucial role in tumorigenesis and progression of cancers. Gene silencing of hTERT by short interfering RNA (siRNA) is considered as a promising strategy for cancer gene therapy. Various algorithms have been devised for designing a high efficient siRNA which is a significant issue in the clinical usage. Thereby, in the present study, the relation of siRNA designing criteria and the gene silencing efficiency was evaluated. Methods: The siRNA sequences were designed and characterized by using on line soft wares. Cationic co-polymer (polyethylene glycol-g-polyethylene imine (PEG-g-PEI)) was used for the construction of polyelectrolyte complexes (PECs) containing siRNAs. The cellular uptake of the PECs was evaluated. The gene silencing efficiency of different siRNA sequences was investigated and the effect of observing the rational designing on the functionality of siRNAs was assessed. Results: The size of PEG-g-PEI siRNA with N/P (Nitrogen/Phosphate) ratio of 2.5 was 114 ± 0.645 nm. The transfection efficiency of PECs was desirable (95.5% ± 2.4%.). The results of Real-Time PCR showed that main sequence (MS) reduced the hTERT expression up to 90% and control positive sequence (CPS) up to 63%. These findings demonstrated that the accessibility to the target site has priority than the other criteria such as sequence preferences and thermodynamic features. Conclusion: siRNA opens a hopeful window in cancer therapy which provides a convenient and tolerable therapeutic approach. Thereby, using the set of criteria and rational algorithms in the designing of siRNA remarkably affect the gene silencing efficiency.

The Extent of mRNA Editing Is Limited in Chicken Liver and Adipose, but Impacted by Tissular Context, Genotype, Age, and Feeding as Exemplified with a Conserved Edited Site in COG3.

PubMed

Roux, Pierre-François; Frésard, Laure; Boutin, Morgane; Leroux, Sophie; Klopp, Christophe; Djari, Anis; Esquerré, Diane; Martin, Pascal G P; Zerjal, Tatiana; Gourichon, David; Pitel, Frédérique; Lagarrigue, Sandrine

2015-12-04

RNA editing is a posttranscriptional process leading to differences between genomic DNA and transcript sequences, potentially enhancing transcriptome diversity. With recent advances in high-throughput sequencing, many efforts have been made to describe mRNA editing at the transcriptome scale, especially in mammals, yielding contradictory conclusions regarding the extent of this phenomenon. We show, by detailed description of the 25 studies focusing so far on mRNA editing at the whole-transcriptome scale, that systematic sequencing artifacts are considered in most studies whereas biological replication is often neglected and multi-alignment not properly evaluated, which ultimately impairs the legitimacy of results. We recently developed a rigorous strategy to identify mRNA editing using mRNA and genomic DNA sequencing, taking into account sequencing and mapping artifacts, and biological replicates. We applied this method to screen for mRNA editing in liver and white adipose tissue from eight chickens and confirm the small extent of mRNA recoding in this species. Among the 25 unique edited sites identified, three events were previously described in mammals, attesting that this phenomenon is conserved throughout evolution. Deeper investigations on five sites revealed the impact of tissular context, genotype, age, feeding conditions, and sex on mRNA editing levels. More specifically, this analysis highlighted that the editing level at the site located on COG3 was strongly regulated by four of these factors. By comprehensively characterizing the mRNA editing landscape in chickens, our results highlight how this phenomenon is limited and suggest regulation of editing levels by various genetic and environmental factors. Copyright © 2016 Roux et al.

The Extent of mRNA Editing Is Limited in Chicken Liver and Adipose, but Impacted by Tissular Context, Genotype, Age, and Feeding as Exemplified with a Conserved Edited Site in COG3

PubMed Central

Roux, Pierre-François; Frésard, Laure; Boutin, Morgane; Leroux, Sophie; Klopp, Christophe; Djari, Anis; Esquerré, Diane; Martin, Pascal GP; Zerjal, Tatiana; Gourichon, David; Pitel, Frédérique; Lagarrigue, Sandrine

2015-01-01

RNA editing is a posttranscriptional process leading to differences between genomic DNA and transcript sequences, potentially enhancing transcriptome diversity. With recent advances in high-throughput sequencing, many efforts have been made to describe mRNA editing at the transcriptome scale, especially in mammals, yielding contradictory conclusions regarding the extent of this phenomenon. We show, by detailed description of the 25 studies focusing so far on mRNA editing at the whole-transcriptome scale, that systematic sequencing artifacts are considered in most studies whereas biological replication is often neglected and multi-alignment not properly evaluated, which ultimately impairs the legitimacy of results. We recently developed a rigorous strategy to identify mRNA editing using mRNA and genomic DNA sequencing, taking into account sequencing and mapping artifacts, and biological replicates. We applied this method to screen for mRNA editing in liver and white adipose tissue from eight chickens and confirm the small extent of mRNA recoding in this species. Among the 25 unique edited sites identified, three events were previously described in mammals, attesting that this phenomenon is conserved throughout evolution. Deeper investigations on five sites revealed the impact of tissular context, genotype, age, feeding conditions, and sex on mRNA editing levels. More specifically, this analysis highlighted that the editing level at the site located on COG3 was strongly regulated by four of these factors. By comprehensively characterizing the mRNA editing landscape in chickens, our results highlight how this phenomenon is limited and suggest regulation of editing levels by various genetic and environmental factors. PMID:26637431

SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

PubMed

Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

2012-07-15

In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

Investigation of bacterial and archaeal communities: novel protocols using modern sequencing by Illumina MiSeq and traditional DGGE-cloning.

PubMed

Kraková, Lucia; Šoltys, Katarína; Budiš, Jaroslav; Grivalský, Tomáš; Ďuriš, František; Pangallo, Domenico; Szemes, Tomáš

2016-09-01

Different protocols based on Illumina high-throughput DNA sequencing and denaturing gradient gel electrophoresis (DGGE)-cloning were developed and applied for investigating hot spring related samples. The study was focused on three target genes: archaeal and bacterial 16S rRNA and mcrA of methanogenic microflora. Shorter read lengths of the currently most popular technology of sequencing by Illumina do not allow analysis of the complete 16S rRNA region, or of longer gene fragments, as was the case of Sanger sequencing. Here, we demonstrate that there is no need for special indexed or tailed primer sets dedicated to short variable regions of 16S rRNA since the presented approach allows the analysis of complete bacterial 16S rRNA amplicons (V1-V9) and longer archaeal 16S rRNA and mcrA sequences. Sample augmented with transposon is represented by a set of approximately 300 bp long fragments that can be easily sequenced by Illumina MiSeq. Furthermore, a low proportion of chimeric sequences was observed. DGGE-cloning based strategies were performed combining semi-nested PCR, DGGE and clone library construction. Comparing both investigation methods, a certain degree of complementarity was observed confirming that the DGGE-cloning approach is not obsolete. Novel protocols were created for several types of laboratories, utilizing the traditional DGGE technique or using the most modern Illumina sequencing.

Peregrine

PubMed Central

Langevin, Stanley A.; Bent, Zachary W.; Solberg, Owen D.; Curtis, Deanna J.; Lane, Pamela D.; Williams, Kelly P.; Schoeniger, Joseph S.; Sinha, Anupama; Lane, Todd W.; Branda, Steven S.

2013-01-01

Use of second generation sequencing (SGS) technologies for transcriptional profiling (RNA-Seq) has revolutionized transcriptomics, enabling measurement of RNA abundances with unprecedented specificity and sensitivity and the discovery of novel RNA species. Preparation of RNA-Seq libraries requires conversion of the RNA starting material into cDNA flanked by platform-specific adaptor sequences. Each of the published methods and commercial kits currently available for RNA-Seq library preparation suffers from at least one major drawback, including long processing times, large starting material requirements, uneven coverage, loss of strand information and high cost. We report the development of a new RNA-Seq library preparation technique that produces representative, strand-specific RNA-Seq libraries from small amounts of starting material in a fast, simple and cost-effective manner. Additionally, we have developed a new quantitative PCR-based assay for precisely determining the number of PCR cycles to perform for optimal enrichment of the final library, a key step in all SGS library preparation workflows. PMID:23558773

Dose-Response Analysis of RNA-Seq Profiles in Archival Formalin-Fixed Paraffin-Embedded (FFPE) Samples.

EPA Science Inventory

Use of archival resources has been limited to date by inconsistent methods for genomic profiling of degraded RNA from formalin-fixed paraffin-embedded (FFPE) samples. RNA-sequencing offers a promising way to address this problem. Here we evaluated transcriptomic dose responses us...

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2006-07-04

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2002-01-01

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

A population study of the minicircles in Trypanosoma cruzi: predicting guide RNAs in the absence of empirical RNA editing.

PubMed

Thomas, Sean; Martinez, L L Isadora Trejo; Westenberger, Scott J; Sturm, Nancy R

2007-05-24

The structurally complex network of minicircles and maxicircles comprising the mitochondrial DNA of kinetoplastids mirrors the complexity of the RNA editing process that is required for faithful expression of encrypted maxicircle genes. Although a few of the guide RNAs that direct this editing process have been discovered on maxicircles, guide RNAs are mostly found on the minicircles. The nuclear and maxicircle genomes have been sequenced and assembled for Trypanosoma cruzi, the causative agent of Chagas disease, however the complement of 1.4-kb minicircles, carrying four guide RNA genes per molecule in this parasite, has been less thoroughly characterised. Fifty-four CL Brener and 53 Esmeraldo strain minicircle sequence reads were extracted from T. cruzi whole genome shotgun sequencing data. With these sequences and all published T. cruzi minicircle sequences, 108 unique guide RNAs from all known T. cruzi minicircle sequences and two guide RNAs from the CL Brener maxicircle were predicted using a local alignment algorithm and mapped onto predicted or experimentally determined sequences of edited maxicircle open reading frames. For half of the sequences no statistically significant guide RNA could be assigned. Likely positions of these unidentified gRNAs in T. cruzi minicircle sequences are estimated using a simple Hidden Markov Model. With the local alignment predictions as a standard, the HMM had an ~85% chance of correctly identifying at least 20 nucleotides of guide RNA from a given minicircle sequence. Inter-minicircle recombination was documented. Variable regions contain species-specific areas of distinct nucleotide preference. Two maxicircle guide RNA genes were found. The identification of new minicircle sequences and the further characterization of all published minicircles are presented, including the first observation of recombination between minicircles. Extrapolation suggests a level of 4% recombinants in the population, supporting a relatively high recombination rate that may serve to minimize the persistence of gRNA pseudogenes. Characteristic nucleotide preferences observed within variable regions provide potential clues regarding the transcription and maturation of T. cruzi guide RNAs. Based on these preferences, a method of predicting T. cruzi guide RNAs using only primary minicircle sequence data was created.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

PubMed

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available. Copyright © 2016 Du et al.

aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

PubMed Central

Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

2016-01-01

Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

PubMed

He, Yan; Caporaso, J Gregory; Jiang, Xiao-Tao; Sheng, Hua-Fang; Huse, Susan M; Rideout, Jai Ram; Edgar, Robert C; Kopylova, Evguenia; Walters, William A; Knight, Rob; Zhou, Hong-Wei

2015-01-01

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Pawitan, Yudi; Rantalainen, Mattias

2018-02-27

RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16,562 isoform-pairs from 4,929 genes. Among those, 26% of the discovered patterns were significant (p<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. The effect of drop-out events, mean expression level, and properties of the expression distribution on the performances of ISOP were also investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoformlevel preference, commitment and heterogeneity in single-cell RNA-sequencing data. The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license. mattias.rantalainen@ki.se. Supplementary data are available at Bioinformatics online.

CLIP-related methodologies and their application to retrovirology.

PubMed

Bieniasz, Paul D; Kutluay, Sebla B

2018-05-02

Virtually every step of HIV-1 replication and numerous cellular antiviral defense mechanisms are regulated by the binding of a viral or cellular RNA-binding protein (RBP) to distinct sequence or structural elements on HIV-1 RNAs. Until recently, these protein-RNA interactions were studied largely by in vitro binding assays complemented with genetics approaches. However, these methods are highly limited in the identification of the relevant targets of RBPs in physiologically relevant settings. Development of crosslinking-immunoprecipitation sequencing (CLIP) methodology has revolutionized the analysis of protein-nucleic acid complexes. CLIP combines immunoprecipitation of covalently crosslinked protein-RNA complexes with high-throughput sequencing, providing a global account of RNA sequences bound by a RBP of interest in cells (or virions) at near-nucleotide resolution. Numerous variants of the CLIP protocol have recently been developed, some with major improvements over the original. Herein, we briefly review these methodologies and give examples of how CLIP has been successfully applied to retrovirology research.

Sequence Variation in the Small-Subunit rRNA Gene of Plasmodium malariae and Prevalence of Isolates with the Variant Sequence in Sichuan, China

PubMed Central

Liu, Qing; Zhu, Shenghua; Mizuno, Sahoko; Kimura, Masatsugu; Liu, Peina; Isomura, Shin; Wang, Xingzhen; Kawamoto, Fumihiko

1998-01-01

By two PCR-based diagnostic methods, Plasmodium malariae infections have been rediscovered at two foci in the Sichuan province of China, a region where no cases of P. malariae have been officially reported for the last 2 decades. In addition, a variant form of P. malariae which has a deletion of 19 bp and seven substitutions of base pairs in the target sequence of the small-subunit (SSU) rRNA gene was detected with high frequency. Alignment analysis of Plasmodium sp. SSU rRNA gene sequences revealed that the 5′ region of the variant sequence is identical to that of P. vivax or P. knowlesi and its 3′ region is identical to that of P. malariae. The same sequence variations were also found in P. malariae isolates collected along the Thai-Myanmar border, suggesting a wide distribution of this variant form from southern China to Southeast Asia. PMID:9774600

Genome-Wide Profiling of RNA–Protein Interactions Using CLIP-Seq

PubMed Central

Stork, Cheryl; Zheng, Sika

2017-01-01

UV crosslinking immunoprecipitation (CLIP) is an increasingly popular technique to study protein–RNA interactions in tissues and cells. Whole cells or tissues are ultraviolet irradiated to generate a covalent bond between RNA and proteins that are in close contact. After partial RNase digestion, antibodies specific to an RNA binding protein (RBP) or a protein–epitope tag is then used to immunoprecipitate the protein–RNA complexes. After stringent washing and gel separation the RBP–RNA complex is excised. The RBP is protease digested to allow purification of the bound RNA. Reverse transcription of the RNA followed by high-throughput sequencing of the cDNA library is now often used to identify protein bound RNA on a genome-wide scale. UV irradiation can result in cDNA truncations and/or mutations at the crosslink sites, which complicates the alignment of the sequencing library to the reference genome and the identification of the crosslinking sites. Meanwhile, one or more amino acids of a crosslinked RBP can remain attached to its bound RNA due to incomplete digestion of the protein. As a result, reverse transcriptase may not read through the crosslink sites, and produce cDNA ending at the crosslinked nucleotide. This is harnessed by one variant of CLIP methods to identify crosslinking sites at a nucleotide resolution. This method, individual nucleotide resolution CLIP (iCLIP) circularizes cDNA to capture the truncated cDNA and also increases the efficiency of ligating sequencing adapters to the library. Here, we describe the detailed procedure of iCLIP. PMID:26965263

Synthesis and biological activity of artificial mRNA prepared with novel phosphorylating reagents

PubMed Central

Nagata, Seigo; Hamasaki, Tomohiro; Uetake, Koichi; Masuda, Hirofumi; Takagaki, Kazuchika; Oka, Natsuhisa; Wada, Takeshi; Ohgi, Tadaaki; Yano, Junichi

2010-01-01

Though medicines that target mRNA are under active investigation, there has been little or no effort to develop mRNA itself as a medicine. Here, we report the synthesis of a 130-nt mRNA sequence encoding a 33-amino-acid peptide that includes the sequence of glucagon-like peptide-1, a peptide that stimulates glucose-dependent insulin secretion from the pancreas. The synthesis method used, which had previously been developed in our laboratory, was based on the use of 2-cyanoethoxymethyl as the 2′-hydroxy protecting group. We also developed novel, highly reactive phosphotriester pyrophosphorylating reagents to pyrophosphorylate the 5′-end of the 130-mer RNA in preparation for capping. We completed the synthesis of the artificial mRNA by the enzymatic addition of a 5′-cap and a 3′-poly(A) tail to the pyrophosphorylated 130-mer and showed that the resulting mRNA supported protein synthesis in a cell-free system and in whole cells. As far as we know, this is the first time that mRNA has been prepared from a chemically synthesized RNA sequence. As well as providing a research tool for the intracellular expression of peptides, the technology described here may be used for the production of mRNA for medical applications. PMID:20660478

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

miPrimer: an empirical-based qPCR primer design method for small noncoding microRNA

PubMed Central

Kang, Shih-Ting; Hsieh, Yi-Shan; Feng, Chi-Ting; Chen, Yu-Ting; Yang, Pok Eric; Chen, Wei-Ming

2018-01-01

MicroRNAs (miRNAs) are 18–25 nucleotides (nt) of highly conserved, noncoding RNAs involved in gene regulation. Because of miRNAs’ short length, the design of miRNA primers for PCR amplification remains a significant challenge. Adding to the challenge are miRNAs similar in sequence and miRNA family members that often only differ in sequences by 1 nt. Here, we describe a novel empirical-based method, miPrimer, which greatly reduces primer dimerization and increases primer specificity by factoring various intrinsic primer properties and employing four primer design strategies. The resulting primer pairs displayed an acceptable qPCR efficiency of between 90% and 110%. When tested on miRNA families, miPrimer-designed primers are capable of discriminating among members of miRNA families, as validated by qPCR assays using Quark Biosciences’ platform. Of the 120 miRNA primer pairs tested, 95.6% and 93.3% were successful in amplifying specifically non-family and family miRNA members, respectively, after only one design trial. In summary, miPrimer provides a cost-effective and valuable tool for designing miRNA primers. PMID:29208706

The conservation and function of RNA secondary structure in plants

PubMed Central

Vandivier, Lee E.; Anderson, Stephen J.; Foley, Shawn W.; Gregory, Brian D.

2016-01-01

RNA transcripts fold into secondary structures via intricate patterns of base pairing. These secondary structures impart catalytic, ligand binding, and scaffolding functions to a wide array of RNAs, forming a critical node of biological regulation. Among their many functions, RNA structural elements modulate epigenetic marks, alter mRNA stability and translation, regulate alternative splicing, transduce signals, and scaffold large macromolecular complexes. Thus, the study of RNA secondary structure is critical to understanding the function and regulation of RNA transcripts. Here, we review the origins, form, and function of RNA secondary structure, focusing on plants. We then provide an overview of methods for probing secondary structure, from physical methods such as X-ray crystallography and nuclear magnetic resonance imaging (NMR) to chemical and nuclease probing methods. Marriage with high-throughput sequencing has enabled these latter methods to scale across whole transcriptomes, yielding tremendous new insights into the form and function of RNA secondary structure. PMID:26865341

MINTmap: fast and exhaustive profiling of nuclear and mitochondrial tRNA fragments from short RNA-seq data

PubMed Central

Loher, Phillipe; Telonis, Aristeidis G.; Rigoutsos, Isidore

2017-01-01

Transfer RNA fragments (tRFs) are an established class of constitutive regulatory molecules that arise from precursor and mature tRNAs. RNA deep sequencing (RNA-seq) has greatly facilitated the study of tRFs. However, the repeat nature of the tRNA templates and the idiosyncrasies of tRNA sequences necessitate the development and use of methodologies that differ markedly from those used to analyze RNA-seq data when studying microRNAs (miRNAs) or messenger RNAs (mRNAs). Here we present MINTmap (for MItochondrial and Nuclear TRF mapping), a method and a software package that was developed specifically for the quick, deterministic and exhaustive identification of tRFs in short RNA-seq datasets. In addition to identifying them, MINTmap is able to unambiguously calculate and report both raw and normalized abundances for the discovered tRFs. Furthermore, to ensure specificity, MINTmap identifies the subset of discovered tRFs that could be originating outside of tRNA space and flags them as candidate false positives. Our comparative analysis shows that MINTmap exhibits superior sensitivity and specificity to other available methods while also being exceptionally fast. The MINTmap codes are available through https://github.com/TJU-CMC-Org/MINTmap/ under an open source GNU GPL v3.0 license. PMID:28220888

Comparative analysis of the small RNA transcriptomes of Pinus contorta and Oryza sativa

PubMed Central

Morin, Ryan D.; Aksay, Gozde; Dolgosheina, Elena; Ebhardt, H. Alexander; Magrini, Vincent; Mardis, Elaine R.; Sahinalp, S. Cenk; Unrau, Peter J.

2008-01-01

The diversity of microRNAs and small-interfering RNAs has been extensively explored within angiosperms by focusing on a few key organisms such as Oryza sativa and Arabidopsis thaliana. A deeper division of the plants is defined by the radiation of the angiosperms and gymnosperms, with the latter comprising the commercially important conifers. The conifers are expected to provide important information regarding the evolution of highly conserved small regulatory RNAs. Deep sequencing provides the means to characterize and quantitatively profile small RNAs in understudied organisms such as these. Pyrosequencing of small RNAs from O. sativa revealed, as expected, ∼21- and ∼24-nt RNAs. The former contained known microRNAs, and the latter largely comprised intergenic-derived sequences likely representing heterochromatin siRNAs. In contrast, sequences from Pinus contorta were dominated by 21-nt small RNAs. Using a novel sequence-based clustering algorithm, we identified sequences belonging to 18 highly conserved microRNA families in P. contorta as well as numerous clusters of conserved small RNAs of unknown function. Using multiple methods, including expressed sequence folding and machine learning algorithms, we found a further 53 candidate novel microRNA families, 51 appearing specific to the P. contorta library. In addition, alignment of small RNA sequences to the O. sativa genome revealed six perfectly conserved classes of small RNA that included chloroplast transcripts and specific types of genomic repeats. The conservation of microRNAs and other small RNAs between the conifers and the angiosperms indicates that important RNA silencing processes were highly developed in the earliest spermatophytes. Genomic mapping of all sequences to the O. sativa genome can be viewed at http://microrna.bcgsc.ca/cgi-bin/gbrowse/rice_build_3/. PMID:18323537

Evidence for Context-Dependent Complementarity of Non-Shine-Dalgarno Ribosome Binding Sites to Escherichia coli rRNA

PubMed Central

Barendt, Pamela A.; Shah, Najaf A.; Barendt, Gregory A.; Kothari, Parth A.; Sarkar, Casim A.

2013-01-01

While the ribosome has evolved to function in complex intracellular environments, these contexts do not easily allow for the study of its inherent capabilities. We have used a synthetic, well-defined, Escherichia coli (E. coli)-based translation system in conjunction with ribosome display, a powerful in vitro selection method, to identify ribosome binding sites (RBSs) that can promote the efficient translation of messenger RNAs (mRNAs) with a leader length representative of natural E. coli mRNAs. In previous work, we used a longer leader sequence and unexpectedly recovered highly efficient cytosine-rich sequences with complementarity to the 16S ribosomal RNA (rRNA) and similarity to eukaryotic RBSs. In the current study, Shine-Dalgarno (SD) sequences were prevalent but non-SD sequences were also heavily enriched and were dominated by novel guanine- and uracil-rich motifs which showed statistically significant complementarity to the 16S rRNA. Additionally, only SD motifs exhibited position-dependent decreases in sequence entropy, indicating that non-SD motifs likely operate by increasing the local concentration of ribosomes in the vicinity of the start codon, rather than by a position-dependent mechanism. These results further support the putative generality of mRNA-rRNA complementarity in facilitating mRNA translation, but also suggest that context (e.g., leader length and composition) dictates the specific subset of possible RBSs that are used for efficient translation of a given transcript. PMID:23427812

Sensitive detection of microRNA in complex biological samples by using two stages DSN-assisted target recycling signal amplification method.

PubMed

Zhang, Kai; Wang, Ke; Zhu, Xue; Xu, Fei; Xie, Minhao

2017-01-15

MicroRNA (miRNA) has become an important biomarker candidate for cancer diagnosis, prognosis, and therapy. In this study, we have developed a novel fluorescence method for sensitive and specific miRNA detection via duplex specific nuclease (DSN) signal amplification and demonstrated its practical application in biological samples. Malachite green (MG) was employed as a "label-free" signal transducer since fluorescence of MG could be enhanced by 100-fold when MG were binding to a G-quadruplex structure formed within the d(G 2 T) 13 G sequence. The proposed signal amplification strategy is an integrated "biological circuit" designed to initiate a cascade of enzymatic reactions in order to detect, amplify, and measure a specific miRNA sequence by using the isothermal cleavage property of a DSN. The circuit is composed of two molecular switches operating in series: the amplification reaction activated by a specific miRNA and the strand-displacement polymerization reaction designed to initiate molecular beacon-assisted amplification and signal transduction by using MG/G-quadruplex complex. The hsa-miR-141 (miR141) was chosen as a target miRNA because its level specifically abnormal in a wide range of common human cancers including breast, lung, colon, and prostate cancer. The proposed method allowed quantitative sequence-specific detection of miR141 (with a detection limit of 1.03pM) in a dynamic range from 1pM to 10μM, with an excellent ability to discriminate differences in miRNAs. Moreover, the detection assay was applied to quantify miR141 in cancerous cell lysates. On the basis of these findings, we believe that this proposed sensitive and specific assay has great potential as a miRNA quantification method for use in biomedical research and clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Whole genome analysis of CRISPR Cas9 sgRNA off-target homologies via an efficient computational algorithm.

PubMed

Zhou, Hong; Zhou, Michael; Li, Daisy; Manthey, Joseph; Lioutikova, Ekaterina; Wang, Hong; Zeng, Xiao

2017-11-17

The beauty and power of the genome editing mechanism, CRISPR Cas9 endonuclease system, lies in the fact that it is RNA-programmable such that Cas9 can be guided to any genomic loci complementary to a 20-nt RNA, single guide RNA (sgRNA), to cleave double stranded DNA, allowing the introduction of wanted mutations. Unfortunately, it has been reported repeatedly that the sgRNA can also guide Cas9 to off-target sites where the DNA sequence is homologous to sgRNA. Using human genome and Streptococcus pyogenes Cas9 (SpCas9) as an example, this article mathematically analyzed the probabilities of off-target homologies of sgRNAs and discovered that for large genome size such as human genome, potential off-target homologies are inevitable for sgRNA selection. A highly efficient computationl algorithm was developed for whole genome sgRNA design and off-target homology searches. By means of a dynamically constructed sequence-indexed database and a simplified sequence alignment method, this algorithm achieves very high efficiency while guaranteeing the identification of all existing potential off-target homologies. Via this algorithm, 1,876,775 sgRNAs were designed for the 19,153 human mRNA genes and only two sgRNAs were found to be free of off-target homology. By means of the novel and efficient sgRNA homology search algorithm introduced in this article, genome wide sgRNA design and off-target analysis were conducted and the results confirmed the mathematical analysis that for a sgRNA sequence, it is almost impossible to escape potential off-target homologies. Future innovations on the CRISPR Cas9 gene editing technology need to focus on how to eliminate the Cas9 off-target activity.

Tn5Prime, a Tn5 based 5' capture method for single cell RNA-seq.

PubMed

Cole, Charles; Byrne, Ashley; Beaudin, Anna E; Forsberg, E Camilla; Vollmers, Christopher

2018-06-01

RNA-sequencing (RNA-seq) is a powerful technique to investigate and quantify entire transcriptomes. Recent advances in the field have made it possible to explore the transcriptomes of single cells. However, most widely used RNA-seq protocols fail to provide crucial information regarding transcription start sites. Here we present a protocol, Tn5Prime, that takes advantage of the Tn5 transposase-based Smart-seq2 protocol to create RNA-seq libraries that capture the 5' end of transcripts. The Tn5Prime method dramatically streamlines the 5' capture process and is both cost effective and reliable. By applying Tn5Prime to bulk RNA and single cell samples, we were able to define transcription start sites as well as quantify transcriptomes at high accuracy and reproducibility. Additionally, similar to 3' end-based high-throughput methods like Drop-seq and 10× Genomics Chromium, the 5' capture Tn5Prime method allows the introduction of cellular identifiers during reverse transcription, simplifying the analysis of large numbers of single cells. In contrast to 3' end-based methods, Tn5Prime also enables the assembly of the variable 5' ends of the antibody sequences present in single B-cell data. Therefore, Tn5Prime presents a robust tool for both basic and applied research into the adaptive immune system and beyond.

Dose-Response Analysis of RNA-Seq Profiles in Archival ...

EPA Pesticide Factsheets

Use of archival resources has been limited to date by inconsistent methods for genomic profiling of degraded RNA from formalin-fixed paraffin-embedded (FFPE) samples. RNA-sequencing offers a promising way to address this problem. Here we evaluated transcriptomic dose responses using RNA-sequencing in paired FFPE and frozen (FROZ) samples from two archival studies in mice, one 20 years old. Experimental treatments included 3 different doses of di(2-ethylhexyl)phthalate or dichloroacetic acid for the recently archived and older studies, respectively. Total RNA was ribo-depleted and sequenced using the Illumina HiSeq platform. In the recently archived study, FFPE samples had 35% lower total counts compared to FROZ samples but high concordance in fold-change values of differentially expressed genes (DEGs) (r2 = 0.99), highly enriched pathways (90% overlap with FROZ), and benchmark dose estimates for preselected target genes (2% difference vs FROZ). In contrast, older FFPE samples had markedly lower total counts (3% of FROZ) and poor concordance in global DEGs and pathways. However, counts from FFPE and FROZ samples still positively correlated (r2 = 0.84 across all transcripts) and showed comparable dose responses for more highly expressed target genes. These findings highlight potential applications and issues in using RNA-sequencing data from FFPE samples. Recently archived FFPE samples were highly similar to FROZ samples in sequencing q

MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

PubMed Central

Zhou, Quan

2017-01-01

An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples. PMID:28350876

Computational modeling of RNA 3D structures, with the aid of experimental restraints

PubMed Central

Magnus, Marcin; Matelska, Dorota; Łach, Grzegorz; Chojnowski, Grzegorz; Boniecki, Michal J; Purta, Elzbieta; Dawson, Wayne; Dunin-Horkawicz, Stanislaw; Bujnicki, Janusz M

2014-01-01

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation (“Greek science” approach) or utilize information derived from known structures of other RNA molecules (“Babylonian science” approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately. PMID:24785264

Mapping RNA Structure In Vitro with SHAPE Chemistry and Next-Generation Sequencing (SHAPE-Seq).

PubMed

Watters, Kyle E; Lucks, Julius B

2016-01-01

Mapping RNA structure with selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry has proven to be a versatile method for characterizing RNA structure in a variety of contexts. SHAPE reagents covalently modify RNAs in a structure-dependent manner to create adducts at the 2'-OH group of the ribose backbone at nucleotides that are structurally flexible. The positions of these adducts are detected using reverse transcriptase (RT) primer extension, which stops one nucleotide before the modification, to create a pool of cDNAs whose lengths reflect the location of SHAPE modification. Quantification of the cDNA pools is used to estimate the "reactivity" of each nucleotide in an RNA molecule to the SHAPE reagent. High reactivities indicate nucleotides that are structurally flexible, while low reactivities indicate nucleotides that are inflexible. These SHAPE reactivities can then be used to infer RNA structures by restraining RNA structure prediction algorithms. Here, we provide a state-of-the-art protocol describing how to perform in vitro RNA structure probing with SHAPE chemistry using next-generation sequencing to quantify cDNA pools and estimate reactivities (SHAPE-Seq). The use of next-generation sequencing allows for higher throughput, more consistent data analysis, and multiplexing capabilities. The technique described herein, SHAPE-Seq v2.0, uses a universal reverse transcription priming site that is ligated to the RNA after SHAPE modification. The introduced priming site allows for the structural analysis of an RNA independent of its sequence.

Simplified Identification of mRNA or DNA in Whole Cells

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

A recently invented method of detecting a selected messenger ribonucleic acid (mRNA) or deoxyribonucleic acid (DNA) sequence offers two important advantages over prior such methods: it is simpler and can be implemented by means of compact equipment. The simplification and miniaturization achieved by this invention are such that this method is suitable for use outside laboratories, in field settings in which space and power supplies may be limited. The present method is based partly on hybridization of nucleic acid, which is a powerful technique for detection of specific complementary nucleic acid sequences and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes.

A Rapid Method for Engineering Recombinant Polioviruses or Other Enteroviruses.

PubMed

Bessaud, Maël; Pelletier, Isabelle; Blondel, Bruno; Delpeyroux, Francis

2016-01-01

The cloning of large enterovirus RNA sequences is labor-intensive because of the frequent instability in bacteria of plasmidic vectors containing the corresponding cDNAs. In order to circumvent this issue we have developed a PCR-based method that allows the generation of highly modified or chimeric full-length enterovirus genomes. This method relies on fusion PCR which enables the concatenation of several overlapping cDNA amplicons produced separately. A T7 promoter sequence added upstream the fusion PCR products allows its transcription into infectious genomic RNAs directly in transfected cells constitutively expressing the phage T7 RNA polymerase. This method permits the rapid recovery of modified viruses that can be subsequently amplified on adequate cell-lines.

RNActive® Technology: Generation and Testing of Stable and Immunogenic mRNA Vaccines.

PubMed

Rauch, Susanne; Lutz, Johannes; Kowalczyk, Aleksandra; Schlake, Thomas; Heidenreich, Regina

2017-01-01

Developing effective mRNA vaccines poses certain challenges concerning mRNA stability and ability to induce sufficient immune stimulation and requires a specific panel of techniques for production and testing. Here, we describe the production of stabilized mRNA with enhanced immunogenicity, generated using conventional nucleotides only, by introducing changes to the mRNA sequence and by complexation with the nucleotide-binding peptide protamine (RNActive® technology). Methods described here include the synthesis, purification, and protamine complexation of mRNA vaccines as well as a comprehensive panel of in vitro and in vivo methods for evaluation of vaccine quality and immunogenicity.

The power and promise of RNA-seq in ecology and evolution.

PubMed

Todd, Erica V; Black, Michael A; Gemmell, Neil J

2016-03-01

Reference is regularly made to the power of new genomic sequencing approaches. Using powerful technology, however, is not the same as having the necessary power to address a research question with statistical robustness. In the rush to adopt new and improved genomic research methods, limitations of technology and experimental design may be initially neglected. Here, we review these issues with regard to RNA sequencing (RNA-seq). RNA-seq adds large-scale transcriptomics to the toolkit of ecological and evolutionary biologists, enabling differential gene expression (DE) studies in nonmodel species without the need for prior genomic resources. High biological variance is typical of field-based gene expression studies and means that larger sample sizes are often needed to achieve the same degree of statistical power as clinical studies based on data from cell lines or inbred animal models. Sequencing costs have plummeted, yet RNA-seq studies still underutilize biological replication. Finite research budgets force a trade-off between sequencing effort and replication in RNA-seq experimental design. However, clear guidelines for negotiating this trade-off, while taking into account study-specific factors affecting power, are currently lacking. Study designs that prioritize sequencing depth over replication fail to capitalize on the power of RNA-seq technology for DE inference. Significant recent research effort has gone into developing statistical frameworks and software tools for power analysis and sample size calculation in the context of RNA-seq DE analysis. We synthesize progress in this area and derive an accessible rule-of-thumb guide for designing powerful RNA-seq experiments relevant in eco-evolutionary and clinical settings alike. © 2016 John Wiley & Sons Ltd.

Prediction of constitutive A-to-I editing sites from human transcriptomes in the absence of genomic sequences

PubMed Central

2013-01-01

Background Adenosine-to-inosine (A-to-I) RNA editing is recognized as a cellular mechanism for generating both RNA and protein diversity. Inosine base pairs with cytidine during reverse transcription and therefore appears as guanosine during sequencing of cDNA. Current approaches of RNA editing identification largely depend on the comparison between transcriptomes and genomic DNA (gDNA) sequencing datasets from the same individuals, and it has been challenging to identify editing candidates from transcriptomes in the absence of gDNA information. Results We have developed a new strategy to accurately predict constitutive RNA editing sites from publicly available human RNA-seq datasets in the absence of relevant genomic sequences. Our approach establishes new parameters to increase the ability to map mismatches and to minimize sequencing/mapping errors and unreported genome variations. We identified 695 novel constitutive A-to-I editing sites that appear in clusters (named “editing boxes”) in multiple samples and which exhibit spatial and dynamic regulation across human tissues. Some of these editing boxes are enriched in non-repetitive regions lacking inverted repeat structures and contain an extremely high conversion frequency of As to Is. We validated a number of editing boxes in multiple human cell lines and confirmed that ADAR1 is responsible for the observed promiscuous editing events in non-repetitive regions, further expanding our knowledge of the catalytic substrate of A-to-I RNA editing by ADAR enzymes. Conclusions The approach we present here provides a novel way of identifying A-to-I RNA editing events by analyzing only RNA-seq datasets. This method has allowed us to gain new insights into RNA editing and should also aid in the identification of more constitutive A-to-I editing sites from additional transcriptomes. PMID:23537002

Uncovering Small RNA-Mediated Responses to Cold Stress in a Wheat Thermosensitive Genic Male-Sterile Line by Deep Sequencing1[W][OA

PubMed Central

Tang, Zhonghui; Zhang, Liping; Xu, Chenguang; Yuan, Shaohua; Zhang, Fengting; Zheng, Yonglian; Zhao, Changping

2012-01-01

The male sterility of thermosensitive genic male sterile (TGMS) lines of wheat (Triticum aestivum) is strictly controlled by temperature. The early phase of anther development is especially susceptible to cold stress. MicroRNAs (miRNAs) play an important role in plant development and in responses to environmental stress. In this study, deep sequencing of small RNA (smRNA) libraries obtained from spike tissues of the TGMS line under cold and control conditions identified a total of 78 unique miRNA sequences from 30 families and trans-acting small interfering RNAs (tasiRNAs) derived from two TAS3 genes. To identify smRNA targets in the wheat TGMS line, we applied the degradome sequencing method, which globally and directly identifies the remnants of smRNA-directed target cleavage. We identified 26 targets of 16 miRNA families and three targets of tasiRNAs. Comparing smRNA sequencing data sets and TaqMan quantitative polymerase chain reaction results, we identified six miRNAs and one tasiRNA (tasiRNA-ARF [for Auxin-Responsive Factor]) as cold stress-responsive smRNAs in spike tissues of the TGMS line. We also determined the expression profiles of target genes that encode transcription factors in response to cold stress. Interestingly, the expression of cold stress-responsive smRNAs integrated in the auxin-signaling pathway and their target genes was largely noncorrelated. We investigated the tissue-specific expression of smRNAs using a tissue microarray approach. Our data indicated that miR167 and tasiRNA-ARF play roles in regulating the auxin-signaling pathway and possibly in the developmental response to cold stress. These data provide evidence that smRNA regulatory pathways are linked with male sterility in the TGMS line during cold stress. PMID:22508932

Thermostable group II intron reverse transcriptase fusion proteins and their use in cDNA synthesis and next-generation RNA sequencing.

PubMed

Mohr, Sabine; Ghanem, Eman; Smith, Whitney; Sheeter, Dennis; Qin, Yidan; King, Olga; Polioudakis, Damon; Iyer, Vishwanath R; Hunicke-Smith, Scott; Swamy, Sajani; Kuersten, Scott; Lambowitz, Alan M

2013-07-01

Mobile group II introns encode reverse transcriptases (RTs) that function in intron mobility ("retrohoming") by a process that requires reverse transcription of a highly structured, 2-2.5-kb intron RNA with high processivity and fidelity. Although the latter properties are potentially useful for applications in cDNA synthesis and next-generation RNA sequencing (RNA-seq), group II intron RTs have been difficult to purify free of the intron RNA, and their utility as research tools has not been investigated systematically. Here, we developed general methods for the high-level expression and purification of group II intron-encoded RTs as fusion proteins with a rigidly linked, noncleavable solubility tag, and we applied them to group II intron RTs from bacterial thermophiles. We thus obtained thermostable group II intron RT fusion proteins that have higher processivity, fidelity, and thermostability than retroviral RTs, synthesize cDNAs at temperatures up to 81°C, and have significant advantages for qRT-PCR, capillary electrophoresis for RNA-structure mapping, and next-generation RNA sequencing. Further, we find that group II intron RTs differ from the retroviral enzymes in template switching with minimal base-pairing to the 3' ends of new RNA templates, making it possible to efficiently and seamlessly link adaptors containing PCR-primer binding sites to cDNA ends without an RNA ligase step. This novel template-switching activity enables facile and less biased cloning of nonpolyadenylated RNAs, such as miRNAs or protein-bound RNA fragments. Our findings demonstrate novel biochemical activities and inherent advantages of group II intron RTs for research, biotechnological, and diagnostic methods, with potentially wide applications.

Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state

PubMed Central

Yates, Kathleen B.; Bi, Kevin; Darko, Samuel; Godec, Jernej; Gerdemann, Ulrike; Swadling, Leo; Douek, Daniel C.; Klenerman, Paul; Barnes, Eleanor J.; Sharpe, Arlene H.

2017-01-01

Abstract The T cell compartment must contain diversity in both T cell receptor (TCR) repertoire and cell state to provide effective immunity against pathogens. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current methods for TCR inference from scRNA-seq are limited in their sensitivity and require long sequencing reads, thus increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present TRAPeS, a publicly available tool that can efficiently extract TCR sequence information from short-read scRNA-seq libraries. We apply it to investigate heterogeneity in the CD8+ T cell response in humans and mice, and show that it is accurate and more sensitive than existing approaches. Coupling TRAPeS with transcriptome analysis of CD8+ T cells specific for a single epitope from Yellow Fever Virus (YFV), we show that the recently described ‘naive-like’ memory population have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype cells. This suggests that TCR usage is associated with the differentiation state of the CD8+ T cell response to YFV. PMID:28934479

PanFP: Pangenome-based functional profiles for microbial communities

DOE PAGES

Jun, Se -Ran; Hauser, Loren John; Schadt, Christopher Warren; ...

2015-09-26

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interestmore » for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.« less

PanFP: pangenome-based functional profiles for microbial communities.

PubMed

Jun, Se-Ran; Robeson, Michael S; Hauser, Loren J; Schadt, Christopher W; Gorin, Andrey A

2015-09-26

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost-effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. We present a computational method called pangenome-based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU's taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome's functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8-0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed-reference OTU picking strategies against specific reference sequence databases. We developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub ( https://github.com/srjun/PanFP ).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun, Se -Ran; Hauser, Loren John; Schadt, Christopher Warren

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interestmore » for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.« less

CORALINA: a universal method for the generation of gRNA libraries for CRISPR-based screening.

PubMed

Köferle, Anna; Worf, Karolina; Breunig, Christopher; Baumann, Valentin; Herrero, Javier; Wiesbeck, Maximilian; Hutter, Lukas H; Götz, Magdalena; Fuchs, Christiane; Beck, Stephan; Stricker, Stefan H

2016-11-14

The bacterial CRISPR system is fast becoming the most popular genetic and epigenetic engineering tool due to its universal applicability and adaptability. The desire to deploy CRISPR-based methods in a large variety of species and contexts has created an urgent need for the development of easy, time- and cost-effective methods enabling large-scale screening approaches. Here we describe CORALINA (comprehensive gRNA library generation through controlled nuclease activity), a method for the generation of comprehensive gRNA libraries for CRISPR-based screens. CORALINA gRNA libraries can be derived from any source of DNA without the need of complex oligonucleotide synthesis. We show the utility of CORALINA for human and mouse genomic DNA, its reproducibility in covering the most relevant genomic features including regulatory, coding and non-coding sequences and confirm the functionality of CORALINA generated gRNAs. The simplicity and cost-effectiveness make CORALINA suitable for any experimental system. The unprecedented sequence complexities obtainable with CORALINA libraries are a necessary pre-requisite for less biased large scale genomic and epigenomic screens.

Isolation of high-quality total RNA from rumen anaerobic bacteria and fungi, and subsequent detection of glycoside hydrolases.

PubMed

Wang, Pan; Qi, Meng; Barboza, Perry; Leigh, Mary Beth; Ungerfeld, Emilio; Selinger, L Brent; McAllister, Tim A; Forster, Robert J

2011-07-01

The rumen is one of the most powerful fibrolytic fermentation systems known. Gene expression analyses, such as reverse transcription PCR (RT-PCR), microarrays, and metatranscriptomics, are techniques that could significantly expand our understanding of this ecosystem. The ability to isolate and stabilize representative RNA samples is critical to obtaining reliable results with these procedures. In this study, we successfully isolated high-quality total RNA from the solid phase of ruminal contents by using an improved RNA extraction method. This method is based on liquid nitrogen grinding of whole ruminal solids without microbial detachment and acid guanidinium - phenol - chloroform extraction combined with column purification. Yields of total RNA were as high as 150 µg per g of fresh ruminal content. The typical large subunit/small subunit rRNA ratio ranged from 1.8 to 2.0 with an RNA integrity number (Agilent Technologies) greater than 8.5. By eliminating the detachment step, the resulting RNA was more representative of the complete ecosystem. Our improved method removed a major barrier limiting analysis of rumen microbial function from a gene expression perspective. The polyA-tailed eukaryotic mRNAs obtained have successfully been applied to next-generation sequencing, and metatranscriptomic analysis of the solid fraction of rumen contents revealed abundant sequences related to rumen fungi.

TRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structures.

PubMed

Wiebe, Nicholas J P; Meyer, Irmtraud M

2010-06-24

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment.

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma

PubMed Central

Wrzeszczynski, Kazimierz O.; Frank, Mayu O.; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A.; Moore Vogel, Julia L.; Bruce, Jeffrey N.; Lassman, Andrew B.; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V.; Zody, Michael C.; Jobanputra, Vaidehi; Royyuru, Ajay K.

2017-01-01

Objective: To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Methods: Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. Results: More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. Conclusions: The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. ClinicalTrials.gov identifier: NCT02725684. PMID:28740869

The complete mitochondrial genome of Papilio glaucus and its phylogenetic implications.

PubMed

Shen, Jinhui; Cong, Qian; Grishin, Nick V

2015-09-01

Due to the intriguing morphology, lifecycle, and diversity of butterflies and moths, Lepidoptera are emerging as model organisms for the study of genetics, evolution and speciation. The progress of these studies relies on decoding Lepidoptera genomes, both nuclear and mitochondrial. Here we describe a protocol to obtain mitogenomes from Next Generation Sequencing reads performed for whole-genome sequencing and report the complete mitogenome of Papilio (Pterourus) glaucus. The circular mitogenome is 15,306 bp in length and rich in A and T. It contains 13 protein-coding genes (PCGs), 22 transfer-RNA-coding genes (tRNA), and 2 ribosomal-RNA-coding genes (rRNA), with a gene order typical for mitogenomes of Lepidoptera. We performed phylogenetic analyses based on PCG and RNA-coding genes or protein sequences using Bayesian Inference and Maximum Likelihood methods. The phylogenetic trees consistently show that among species with available mitogenomes Papilio glaucus is the closest to Papilio (Agehana) maraho from Asia.

A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine.

PubMed

Jain, Dharm Skandh; Gupte, Sanket Rajan; Aduri, Raviprasad

2018-06-22

RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA. Here, we present a data-driven model for RPI prediction using a gradient boosting classifier. Amino acids and nucleotides are classified based on the high-resolution structural data of RNA protein complexes. The minimum structural unit consisting of five residues is used as the descriptor. Comparative analysis of existing methods shows the consistently higher performance of our method irrespective of the length of RNA present in the RPI. The method has been successfully applied to map RPI networks involving both long noncoding RNA as well as TERRA RNA. The method is also shown to successfully predict RNA and protein hubs present in RPI networks of four different organisms. The robustness of this method will provide a way for predicting RPI networks of yet unknown interactions for both long noncoding RNA and microRNA.

A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution.

PubMed

Reinharz, Vladimir; Ponty, Yann; Waldispühl, Jérôme

2013-07-01

The design of RNA sequences folding into predefined secondary structures is a milestone for many synthetic biology and gene therapy studies. Most of the current software uses similar local search strategies (i.e. a random seed is progressively adapted to acquire the desired folding properties) and more importantly do not allow the user to control explicitly the nucleotide distribution such as the GC-content in their sequences. However, the latter is an important criterion for large-scale applications as it could presumably be used to design sequences with better transcription rates and/or structural plasticity. In this article, we introduce IncaRNAtion, a novel algorithm to design RNA sequences folding into target secondary structures with a predefined nucleotide distribution. IncaRNAtion uses a global sampling approach and weighted sampling techniques. We show that our approach is fast (i.e. running time comparable or better than local search methods), seedless (we remove the bias of the seed in local search heuristics) and successfully generates high-quality sequences (i.e. thermodynamically stable) for any GC-content. To complete this study, we develop a hybrid method combining our global sampling approach with local search strategies. Remarkably, our glocal methodology overcomes both local and global approaches for sampling sequences with a specific GC-content and target structure. IncaRNAtion is available at csb.cs.mcgill.ca/incarnation/. Supplementary data are available at Bioinformatics online.

Tetrahymena australis (Protozoa, Ciliophora): A Well-Known But "Non-Existing" Taxon - Consideration of Its Identification, Definition and Systematic Position.

PubMed

Liu, Mingjian; Fan, Xinpeng; Gao, Feng; Gao, Shan; Yu, Yuhe; Warren, Alan; Huang, Jie

2016-11-01

A cryptic species of the Tetrahymena pyriformis complex, Tetrahymena australis, has been known for a long time but never properly diagnosed based on taxonomic methods. The species name is thus invalid according to the International Code of Zoological Nomenclature. Recently, a population isolated from a freshwater lake in Wuhan, China was investigated using live observations, silver staining methods and gene sequence data. This organism can be separated from other described species of the T. pyriformis complex by its relatively small body size, the number of somatic kineties and differences in sequences of two genes, namely the small subunit ribosomal RNA (SSU rRNA) and the mitochondrial cytochrome c oxidase subunit I (cox1). We compared the SSU rRNA gene sequences of all available Tetrahymena species to reveal the nucleotide differences within this genus. The sequence of the Wuhan population is identical to two sequences of a previously isolated strain of T. australis (ATCC #30831). Phylogenetic analyses indicate that these three sequences (X56167, M98015, KT334373) cluster with Tetrahymena shanghaiensis (EF070256) in a polytomy. However, sequence divergence of the cox1 gene between the Wuhan population and another strain of T. australis (ATCC #30271) is 1.4%, suggesting that these may represent different subspecies. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

A novel diagnostic method for malaria using loop-mediated isothermal amplification (LAMP) and MinION™ nanopore sequencer.

PubMed

Imai, Kazuo; Tarumoto, Norihito; Misawa, Kazuhisa; Runtuwene, Lucky Ronald; Sakai, Jun; Hayashida, Kyoko; Eshita, Yuki; Maeda, Ryuichiro; Tuda, Josef; Murakami, Takashi; Maesaki, Shigefumi; Suzuki, Yutaka; Yamagishi, Junya; Maeda, Takuya

2017-09-13

A simple and accurate molecular diagnostic method for malaria is urgently needed due to the limitations of conventional microscopic examination. In this study, we demonstrate a new diagnostic procedure for human malaria using loop mediated isothermal amplification (LAMP) and the MinION™ nanopore sequencer. We generated specific LAMP primers targeting the 18S-rRNA gene of all five human Plasmodium species including two P. ovale subspecies (P. falciparum, P. vivax, P. ovale wallikeri, P. ovale curtisi, P. knowlesi and P. malariae) and examined human blood samples collected from 63 malaria patients in Indonesia. Additionally, we performed amplicon sequencing of our LAMP products using MinION™ nanopore sequencer to identify each Plasmodium species. Our LAMP method allowed amplification of all targeted 18S-rRNA genes of the reference plasmids with detection limits of 10-100 copies per reaction. Among the 63 clinical samples, 54 and 55 samples were positive by nested PCR and our LAMP method, respectively. Identification of the Plasmodium species by LAMP amplicon sequencing analysis using the MinION™ was consistent with the reference plasmid sequences and the results of nested PCR. Our diagnostic method combined with LAMP and MinION™ could become a simple and accurate tool for the identification of human Plasmodium species, even in resource-limited situations.

Fingerprints of Modified RNA Bases from Deep Sequencing Profiles.

PubMed

Kietrys, Anna M; Velema, Willem A; Kool, Eric T

2017-11-29

Posttranscriptional modifications of RNA bases are not only found in many noncoding RNAs but have also recently been identified in coding (messenger) RNAs as well. They require complex and laborious methods to locate, and many still lack methods for localized detection. Here we test the ability of next-generation sequencing (NGS) to detect and distinguish between ten modified bases in synthetic RNAs. We compare ultradeep sequencing patterns of modified bases, including miscoding, insertions and deletions (indels), and truncations, to unmodified bases in the same contexts. The data show widely varied responses to modification, ranging from no response, to high levels of mutations, insertions, deletions, and truncations. The patterns are distinct for several of the modifications, and suggest the future use of ultradeep sequencing as a fingerprinting strategy for locating and identifying modifications in cellular RNAs.

Identification of Bacterial Populations in Drinking Water Using 16S rRNA-Based Sequence Analyses

EPA Science Inventory

Intracellular RNA is rapidly degraded in stressed cells and is more unstable outside of the cell than DNA. As a result, RNA-based methods have been suggested to study the active microbial fraction in environmental matrices. The aim of this study was to identify bacterial populati...

Linnorm: improved statistical analysis for single cell RNA-seq expression data

PubMed Central

Yip, Shun H.; Wang, Panwen; Kocher, Jean-Pierre A.; Sham, Pak Chung

2017-01-01

Abstract Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. PMID:28981748

SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing.

PubMed

Tsuchiya, Mariko; Amano, Kojiro; Abe, Masaya; Seki, Misato; Hase, Sumitaka; Sato, Kengo; Sakakibara, Yasubumi

2016-06-15

Deep sequencing of the transcripts of regulatory non-coding RNA generates footprints of post-transcriptional processes. After obtaining sequence reads, the short reads are mapped to a reference genome, and specific mapping patterns can be detected called read mapping profiles, which are distinct from random non-functional degradation patterns. These patterns reflect the maturation processes that lead to the production of shorter RNA sequences. Recent next-generation sequencing studies have revealed not only the typical maturation process of miRNAs but also the various processing mechanisms of small RNAs derived from tRNAs and snoRNAs. We developed an algorithm termed SHARAKU to align two read mapping profiles of next-generation sequencing outputs for non-coding RNAs. In contrast with previous work, SHARAKU incorporates the primary and secondary sequence structures into an alignment of read mapping profiles to allow for the detection of common processing patterns. Using a benchmark simulated dataset, SHARAKU exhibited superior performance to previous methods for correctly clustering the read mapping profiles with respect to 5'-end processing and 3'-end processing from degradation patterns and in detecting similar processing patterns in deriving the shorter RNAs. Further, using experimental data of small RNA sequencing for the common marmoset brain, SHARAKU succeeded in identifying the significant clusters of read mapping profiles for similar processing patterns of small derived RNA families expressed in the brain. The source code of our program SHARAKU is available at http://www.dna.bio.keio.ac.jp/sharaku/, and the simulated dataset used in this work is available at the same link. Accession code: The sequence data from the whole RNA transcripts in the hippocampus of the left brain used in this work is available from the DNA DataBank of Japan (DDBJ) Sequence Read Archive (DRA) under the accession number DRA004502. yasu@bio.keio.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A method for release and multiple strand amplification of small quantities of DNA from endospores of the fastidious bacterium Pasteuria penetrans.

PubMed

Mauchline, T H; Mohan, S; Davies, K G; Schaff, J E; Opperman, C H; Kerry, B R; Hirsch, P R

2010-05-01

To establish a reliable protocol to extract DNA from Pasteuria penetrans endospores for use as template in multiple strand amplification, thus providing sufficient material for genetic analyses. To develop a highly sensitive PCR-based diagnostic tool for P. penetrans. An optimized method to decontaminate endospores, release and purify DNA enabled multiple strand amplification. DNA purity was assessed by cloning and sequencing gyrB and 16S rRNA gene fragments obtained from PCR using generic primers. Samples indicated to be 100%P. penetrans by the gyrB assay were estimated at 46% using the 16S rRNA gene. No bias was detected on cloning and sequencing 12 housekeeping and sporulation gene fragments from amplified DNA. The detection limit by PCR with Pasteuria-specific 16S rRNA gene primers following multiple strand amplification of DNA extracted using the method was a single endospore. Generation of large quantities DNA will facilitate genomic sequencing of P. penetrans. Apparent differences in sample purity are explained by variations in 16S rRNA gene copy number in Eubacteria leading to exaggerated estimations of sample contamination. Detection of single endospores will facilitate investigations of P. penetrans molecular ecology. These methods will advance studies on P. penetrans and facilitate research on other obligate and fastidious micro-organisms where it is currently impractical to obtain DNA in sufficient quantity and quality.

Harnessing NGS and Big Data Optimally: Comparison of miRNA Prediction from Assembled versus Non-assembled Sequencing Data--The Case of the Grass Aegilops tauschii Complex Genome.

PubMed

Budak, Hikmet; Kantar, Melda

2015-07-01

MicroRNAs (miRNAs) are small, endogenous, non-coding RNA molecules that regulate gene expression at the post-transcriptional level. As high-throughput next generation sequencing (NGS) and Big Data rapidly accumulate for various species, efforts for in silico identification of miRNAs intensify. Surprisingly, the effect of the input genomics sequence on the robustness of miRNA prediction was not evaluated in detail to date. In the present study, we performed a homology-based miRNA and isomiRNA prediction of the 5D chromosome of bread wheat progenitor, Aegilops tauschii, using two distinct sequence data sets as input: (1) raw sequence reads obtained from 454-GS FLX Titanium sequencing platform and (2) an assembly constructed from these reads. We also compared this method with a number of available plant sequence datasets. We report here the identification of 62 and 22 miRNAs from raw reads and the assembly, respectively, of which 16 were predicted with high confidence from both datasets. While raw reads promoted sensitivity with the high number of miRNAs predicted, 55% (12 out of 22) of the assembly-based predictions were supported by previous observations, bringing specificity forward compared to the read-based predictions, of which only 37% were supported. Importantly, raw reads could identify several repeat-related miRNAs that could not be detected with the assembly. However, raw reads could not capture 6 miRNAs, for which the stem-loops could only be covered by the relatively longer sequences from the assembly. In summary, the comparison of miRNA datasets obtained by these two strategies revealed that utilization of raw reads, as well as assemblies for in silico prediction, have distinct advantages and disadvantages. Consideration of these important nuances can benefit future miRNA identification efforts in the current age of NGS and Big Data driven life sciences innovation.

Synthetic Spike-in Standards Improve Run-Specific Systematic Error Analysis for DNA and RNA Sequencing

PubMed Central

Zook, Justin M.; Samarov, Daniel; McDaniel, Jennifer; Sen, Shurjo K.; Salit, Marc

2012-01-01

While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a data set used to calculate association of SSEs with various features in the reads and sequence context. This data set is typically either from a part of the data set being “recalibrated” (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 Phred-scaled quality score units, and by as much as 13 units at CpG sites. In addition, since the spike-in data used for recalibration are independent of the genome being sequenced, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration. PMID:22859977

Discovery of DNA viruses in wild-caught mosquitoes using small RNA high throughput sequencing.

PubMed

Ma, Maijuan; Huang, Yong; Gong, Zhengda; Zhuang, Lu; Li, Cun; Yang, Hong; Tong, Yigang; Liu, Wei; Cao, Wuchun

2011-01-01

Mosquito-borne infectious diseases pose a severe threat to public health in many areas of the world. Current methods for pathogen detection and surveillance are usually dependent on prior knowledge of the etiologic agents involved. Hence, efficient approaches are required for screening wild mosquito populations to detect known and unknown pathogens. In this study, we explored the use of Next Generation Sequencing to identify viral agents in wild-caught mosquitoes. We extracted total RNA from different mosquito species from South China. Small 18-30 bp length RNA molecules were purified, reverse-transcribed into cDNA and sequenced using Illumina GAIIx instrumentation. Bioinformatic analyses to identify putative viral agents were conducted and the results confirmed by PCR. We identified a non-enveloped single-stranded DNA densovirus in the wild-caught Culex pipiens molestus mosquitoes. The majority of the viral transcripts (.>80% of the region) were covered by the small viral RNAs, with a few peaks of very high coverage obtained. The +/- strand sequence ratio of the small RNAs was approximately 7∶1, indicating that the molecules were mainly derived from the viral RNA transcripts. The small viral RNAs overlapped, enabling contig assembly of the viral genome sequence. We identified some small RNAs in the reverse repeat regions of the viral 5'- and 3' -untranslated regions where no transcripts were expected. Our results demonstrate for the first time that high throughput sequencing of small RNA is feasible for identifying viral agents in wild-caught mosquitoes. Our results show that it is possible to detect DNA viruses by sequencing the small RNAs obtained from insects, although the underlying mechanism of small viral RNA biogenesis is unclear. Our data and those of other researchers show that high throughput small RNA sequencing can be used for pathogen surveillance in wild mosquito vectors.

COME: a robust coding potential calculation tool for lncRNA identification and characterization based on multiple features.

PubMed

Hu, Long; Xu, Zhiyu; Hu, Boqin; Lu, Zhi John

2017-01-09

Recent genomic studies suggest that novel long non-coding RNAs (lncRNAs) are specifically expressed and far outnumber annotated lncRNA sequences. To identify and characterize novel lncRNAs in RNA sequencing data from new samples, we have developed COME, a coding potential calculation tool based on multiple features. It integrates multiple sequence-derived and experiment-based features using a decompose-compose method, which makes it more accurate and robust than other well-known tools. We also showed that COME was able to substantially improve the consistency of predication results from other coding potential calculators. Moreover, COME annotates and characterizes each predicted lncRNA transcript with multiple lines of supporting evidence, which are not provided by other tools. Remarkably, we found that one subgroup of lncRNAs classified by such supporting features (i.e. conserved local RNA secondary structure) was highly enriched in a well-validated database (lncRNAdb). We further found that the conserved structural domains on lncRNAs had better chance than other RNA regions to interact with RNA binding proteins, based on the recent eCLIP-seq data in human, indicating their potential regulatory roles. Overall, we present COME as an accurate, robust and multiple-feature supported method for the identification and characterization of novel lncRNAs. The software implementation is available at https://github.com/lulab/COME. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

High-throughput detection of RNA processing in bacteria.

PubMed

Gill, Erin E; Chan, Luisa S; Winsor, Geoffrey L; Dobson, Neil; Lo, Raymond; Ho Sui, Shannan J; Dhillon, Bhavjinder K; Taylor, Patrick K; Shrestha, Raunak; Spencer, Cory; Hancock, Robert E W; Unrau, Peter J; Brinkman, Fiona S L

2018-03-27

Understanding the RNA processing of an organism's transcriptome is an essential but challenging step in understanding its biology. Here we investigate with unprecedented detail the transcriptome of Pseudomonas aeruginosa PAO1, a medically important and innately multi-drug resistant bacterium. We systematically mapped RNA cleavage and dephosphorylation sites that result in 5'-monophosphate terminated RNA (pRNA) using monophosphate RNA-Seq (pRNA-Seq). Transcriptional start sites (TSS) were also mapped using differential RNA-Seq (dRNA-Seq) and both datasets were compared to conventional RNA-Seq performed in a variety of growth conditions. The pRNA-Seq library revealed known tRNA, rRNA and transfer-messenger RNA (tmRNA) processing sites, together with previously uncharacterized RNA cleavage events that were found disproportionately near the 5' ends of transcripts associated with basic bacterial functions such as oxidative phosphorylation and purine metabolism. The majority (97%) of the processed mRNAs were cleaved at precise codon positions within defined sequence motifs indicative of distinct endonucleolytic activities. The most abundant of these motifs corresponded closely to an E. coli RNase E site previously established in vitro. Using the dRNA-Seq library, we performed an operon analysis and predicted 3159 potential TSS. A correlation analysis uncovered 105 antiparallel pairs of TSS that were separated by 18 bp from each other and were centered on single palindromic TAT(A/T)ATA motifs (likely - 10 promoter elements), suggesting that, consistent with previous in vitro experimentation, these sites can initiate transcription bi-directionally and may thus provide a novel form of transcriptional regulation. TSS and RNA-Seq analysis allowed us to confirm expression of small non-coding RNAs (ncRNAs), many of which are differentially expressed in swarming and biofilm formation conditions. This study uses pRNA-Seq, a method that provides a genome-wide survey of RNA processing, to study the bacterium Pseudomonas aeruginosa and discover extensive transcript processing not previously appreciated. We have also gained novel insight into RNA maturation and turnover as well as a potential novel form of transcription regulation. NOTE: All sequence data has been submitted to the NCBI sequence read archive. Accession numbers are as follows: [NCBI sequence read archive: SRX156386, SRX157659, SRX157660, SRX157661, SRX157683 and SRX158075]. The sequence data is viewable using Jbrowse on www.pseudomonas.com .

Fluorescence Competition Assay Measurements of Free Energy Changes for RNA Pseudoknots†

PubMed Central

2009-01-01

RNA pseudoknots have important functions, and thermodynamic stability is a key to predicting pseudoknots in RNA sequences and to understanding their functions. Traditional methods, such as UV melting and differential scanning calorimetry, for measuring RNA thermodynamics are restricted to temperature ranges around the melting temperature for a pseudoknot. Here, we report RNA pseudoknot free energy changes at 37 °C measured by fluorescence competition assays. Sequence-dependent studies for the loop 1−stem 2 region reveal (1) the individual nearest-neighbor hydrogen bonding (INN-HB) model provides a reasonable estimate for the free energy change when a Watson−Crick base pair in stem 2 is changed, (2) the loop entropy can be estimated by a statistical polymer model, although some penalty for certain loop sequences is necessary, and (3) tertiary interactions can significantly stabilize pseudoknots and extending the length of stem 2 may alter tertiary interactions such that the INN-HB model does not predict the net effect of adding a base pair. The results can inform writing of algorithms for predicting and/or designing RNA secondary structures. PMID:19921809

Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping

NASA Astrophysics Data System (ADS)

Labib, Mahmoud; Mohamadi, Reza M.; Poudineh, Mahla; Ahmed, Sharif U.; Ivanov, Ivaylo; Huang, Ching-Lung; Moosavi, Maral; Sargent, Edward H.; Kelley, Shana O.

2018-05-01

Cell-to-cell variation in gene expression creates a need for techniques that can characterize expression at the level of individual cells. This is particularly true for rare circulating tumour cells, in which subtyping and drug resistance are of intense interest. Here we describe a method for cell analysis—single-cell mRNA cytometry—that enables the isolation of rare cells from whole blood as a function of target mRNA sequences. This approach uses two classes of magnetic particles that are labelled to selectively hybridize with different regions of the target mRNA. Hybridization leads to the formation of large magnetic clusters that remain localized within the cells of interest, thereby enabling the cells to be magnetically separated. Targeting specific intracellular mRNAs enablescirculating tumour cells to be distinguished from normal haematopoietic cells. No polymerase chain reaction amplification is required to determine RNA expression levels and genotype at the single-cell level, and minimal cell manipulation is required. To demonstrate this approach we use single-cell mRNA cytometry to detect clinically important sequences in prostate cancer specimens.

Discrimination of Bacillus anthracis from closely related microorganisms by analysis of 16S and 23S rRNA with oligonucleotide microchips

DOEpatents

Bavykin, Sergei G.; Mirzabekova, legal representative, Natalia V.; Mirzabekov, deceased, Andrei D.

2007-12-04

The present invention relates to methods and compositions for using nucleotide sequence variations of 16S and 23S rRNA within the B. cereus group to discriminate a highly infectious bacterium B. anthracis from closely related microorganisms. Sequence variations in the 16S and 23S rRNA of the B. cereus subgroup including B. anthracis are utilized to construct an array that can detect these sequence variations through selective hybridizations and discriminate B. cereus group that includes B. anthracis. Discrimination of single base differences in rRNA was achieved with a microchip during analysis of B. cereus group isolates from both single and in mixed samples, as well as identification of polymorphic sites. Successful use of a microchip to determine the appropriate subgroup classification using eight reference microorganisms from the B. cereus group as a study set, was demonstrated.

Validation of two ribosomal RNA removal methods for microbial metatranscriptomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Shaomei; Wurtzel, Omri; Singh, Kanwar

2010-10-01

The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion, as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integritymore » for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.« less

Potential applications of RNA interference-based therapeutics in the treatment of cardiovascular disease.

PubMed

Hassan, Ali

2006-06-01

RNA interference (RNAi) in eukaryotes is a recently identified phenomenon in which small double stranded RNA molecules called short interfering RNA (siRNA) interact with messenger RNA (mRNA) containing homologous sequences in a sequence-specific manner. Ultimately, this interaction results in degradation of the target mRNA. Because of the high sequence specificity of the RNAi process, and the apparently ubiquitous expression of the endogenous protein components necessary for RNAi, there appears to be little limitation to the genes that can be targeted for silencing by RNAi. Thus, RNAi has enormous potential, both as a research tool and as a mode of therapy. Several recent patents have described advances in RNAi technology that are likely to lead to new treatments for cardiovascular disease. These patents have described methods for increased delivery of siRNA to cardiovascular target tissues, chemical modifications of siRNA that improve their pharmacokinetic characteristics, and expression vectors capable of expressing RNAi effectors in situ. Though RNAi has only recently been demonstrated to occur in mammalian tissues, work has advanced rapidly in the development of RNAi-based therapeutics. Recently, therapeutic silencing of apoliporotein B, the ligand for the low density lipoprotein receptor, has been demonstrated in adult mice by systemic administration of chemically modified siRNA. This demonstrates the potential for RNAi-based therapeutics, and suggests that the future for RNAi in the treatment of cardiovascular disease is bright.

Analyses of the radiation of birnaviruses from diverse host phyla and of their evolutionary affinities with other double-stranded RNA and positive strand RNA viruses using robust structure-based multiple sequence alignments and advanced phylogenetic methods

PubMed Central

2013-01-01

Background Birnaviruses form a distinct family of double-stranded RNA viruses infecting animals as different as vertebrates, mollusks, insects and rotifers. With such a wide host range, they constitute a good model for studying the adaptation to the host. Additionally, several lines of evidence link birnaviruses to positive strand RNA viruses and suggest that phylogenetic analyses may provide clues about transition. Results We characterized the genome of a birnavirus from the rotifer Branchionus plicalitis. We used X-ray structures of RNA-dependent RNA polymerases and capsid proteins to obtain multiple structure alignments that allowed us to obtain reliable multiple sequence alignments and we employed “advanced” phylogenetic methods to study the evolutionary relationships between some positive strand and double-stranded RNA viruses. We showed that the rotifer birnavirus genome exhibited an organization remarkably similar to other birnaviruses. As this host was phylogenetically very distant from the other known species targeted by birnaviruses, we revisited the evolutionary pathways within the Birnaviridae family using phylogenetic reconstruction methods. We also applied a number of phylogenetic approaches based on structurally conserved domains/regions of the capsid and RNA-dependent RNA polymerase proteins to study the evolutionary relationships between birnaviruses, other double-stranded RNA viruses and positive strand RNA viruses. Conclusions We show that there is a good correlation between the phylogeny of the birnaviruses and that of their hosts at the phylum level using the RNA-dependent RNA polymerase (genomic segment B) on the one hand and a concatenation of the capsid protein, protease and ribonucleoprotein (genomic segment A) on the other hand. This correlation tends to vanish within phyla. The use of advanced phylogenetic methods and robust structure-based multiple sequence alignments allowed us to obtain a more accurate picture (in terms of probability of the tree topologies) of the evolutionary affinities between double-stranded RNA and positive strand RNA viruses. In particular, we were able to show that there exists a good statistical support for the claims that dsRNA viruses are not monophyletic and that viruses with permuted RdRps belong to a common evolution lineage as previously proposed by other groups. We also propose a tree topology with a good statistical support describing the evolutionary relationships between the Picornaviridae, Caliciviridae, Flaviviridae families and a group including the Alphatetraviridae, Nodaviridae, Permutotretraviridae, Birnaviridae, and Cystoviridae families. PMID:23865988

Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

PubMed Central

Zheng, Yun; Ji, Bo; Song, Renhua; Wang, Shengpeng; Li, Ting; Zhang, Xiaotuo; Chen, Kun; Li, Tianqing; Li, Jinyan

2016-01-01

Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3′-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles. PMID:27229138

Host-Associated Metagenomics: A Guide to Generating Infectious RNA Viromes

PubMed Central

Robert, Catherine; Pascalis, Hervé; Michelle, Caroline; Jardot, Priscilla; Charrel, Rémi; Raoult, Didier; Desnues, Christelle

2015-01-01

Background Metagenomic analyses have been widely used in the last decade to describe viral communities in various environments or to identify the etiology of human, animal, and plant pathologies. Here, we present a simple and standardized protocol that allows for the purification and sequencing of RNA viromes from complex biological samples with an important reduction of host DNA and RNA contaminants, while preserving the infectivity of viral particles. Principal Findings We evaluated different viral purification steps, random reverse transcriptions and sequence-independent amplifications of a pool of representative RNA viruses. Viruses remained infectious after the purification process. We then validated the protocol by sequencing the RNA virome of human body lice engorged in vitro with artificially contaminated human blood. The full genomes of the most abundant viruses absorbed by the lice during the blood meal were successfully sequenced. Interestingly, random amplifications differed in the genome coverage of segmented RNA viruses. Moreover, the majority of reads were taxonomically identified, and only 7–15% of all reads were classified as “unknown”, depending on the random amplification method. Conclusion The protocol reported here could easily be applied to generate RNA viral metagenomes from complex biological samples of different origins. Our protocol allows further virological characterizations of the described viral communities because it preserves the infectivity of viral particles and allows for the isolation of viruses. PMID:26431175

Improved systematic tRNA gene annotation allows new insights into the evolution of mitochondrial tRNA structures and into the mechanisms of mitochondrial genome rearrangements

PubMed Central

Jühling, Frank; Pütz, Joern; Bernt, Matthias; Donath, Alexander; Middendorf, Martin; Florentz, Catherine; Stadler, Peter F.

2012-01-01

Transfer RNAs (tRNAs) are present in all types of cells as well as in organelles. tRNAs of animal mitochondria show a low level of primary sequence conservation and exhibit ‘bizarre’ secondary structures, lacking complete domains of the common cloverleaf. Such sequences are hard to detect and hence frequently missed in computational analyses and mitochondrial genome annotation. Here, we introduce an automatic annotation procedure for mitochondrial tRNA genes in Metazoa based on sequence and structural information in manually curated covariance models. The method, applied to re-annotate 1876 available metazoan mitochondrial RefSeq genomes, allows to distinguish between remaining functional genes and degrading ‘pseudogenes’, even at early stages of divergence. The subsequent analysis of a comprehensive set of mitochondrial tRNA genes gives new insights into the evolution of structures of mitochondrial tRNA sequences as well as into the mechanisms of genome rearrangements. We find frequent losses of tRNA genes concentrated in basal Metazoa, frequent independent losses of individual parts of tRNA genes, particularly in Arthropoda, and wide-spread conserved overlaps of tRNAs in opposite reading direction. Direct evidence for several recent Tandem Duplication-Random Loss events is gained, demonstrating that this mechanism has an impact on the appearance of new mitochondrial gene orders. PMID:22139921

Partial gene sequences for the A subunit of methyl-coenzyme M reductase (mcrI) as a phylogenetic tool for the family Methanosarcinaceae

NASA Technical Reports Server (NTRS)

Springer, E.; Sachs, M. S.; Woese, C. R.; Boone, D. R.

1995-01-01

Representatives of the family Methanosarcinaceae were analyzed phylogenetically by comparing partial sequences of their methyl-coenzyme M reductase (mcrI) genes. A 490-bp fragment from the A subunit of the gene was selected, amplified by the PCR, cloned, and sequenced for each of 25 strains belonging to the Methanosarcinaceae. The sequences obtained were aligned with the corresponding portions of five previously published sequences, and all of the sequences were compared to determine phylogenetic distances by Fitch distance matrix methods. We prepared analogous trees based on 16S rRNA sequences; these trees corresponded closely to the mcrI trees, although the mcrI sequences of pairs of organisms had 3.01 +/- 0.541 times more changes than the respective pairs of 16S rRNA sequences, suggesting that the mcrI fragment evolved about three times more rapidly than the 16S rRNA gene. The qualitative similarity of the mcrI and 16S rRNA trees suggests that transfer of genetic information between dissimilar organisms has not significantly affected these sequences, although we found inconsistencies between some mcrI distances that we measured and and previously published DNA reassociation data. It is unlikely that multiple mcrI isogenes were present in the organisms that we examined, because we found no major discrepancies in multiple determinations of mcrI sequences from the same organism. Our primers for the PCR also match analogous sites in the previously published mcrII sequences, but all of the sequences that we obtained from members of the Methanosarcinaceae were more closely related to mcrI sequences than to mcrII sequences, suggesting that members of the Methanosarcinaceae do not have distinct mcrII genes.

Identification and profiling of novel microRNAs in the Brassica rapa genome based on small RNA deep sequencing

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are one of the functional non-coding small RNAs involved in the epigenetic control of the plant genome. Although plants contain both evolutionary conserved miRNAs and species-specific miRNAs within their genomes, computational methods often only identify evolutionary conserved miRNAs. The recent sequencing of the Brassica rapa genome enables us to identify miRNAs and their putative target genes. In this study, we sought to provide a more comprehensive prediction of B. rapa miRNAs based on high throughput small RNA deep sequencing. Results We sequenced small RNAs from five types of tissue: seedlings, roots, petioles, leaves, and flowers. By analyzing 2.75 million unique reads that mapped to the B. rapa genome, we identified 216 novel and 196 conserved miRNAs that were predicted to target approximately 20% of the genome’s protein coding genes. Quantitative analysis of miRNAs from the five types of tissue revealed that novel miRNAs were expressed in diverse tissues but their expression levels were lower than those of the conserved miRNAs. Comparative analysis of the miRNAs between the B. rapa and Arabidopsis thaliana genomes demonstrated that redundant copies of conserved miRNAs in the B. rapa genome may have been deleted after whole genome triplication. Novel miRNA members seemed to have spontaneously arisen from the B. rapa and A. thaliana genomes, suggesting the species-specific expansion of miRNAs. We have made this data publicly available in a miRNA database of B. rapa called BraMRs. The database allows the user to retrieve miRNA sequences, their expression profiles, and a description of their target genes from the five tissue types investigated here. Conclusions This is the first report to identify novel miRNAs from Brassica crops using genome-wide high throughput techniques. The combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome. The finding of numerous novel miRNAs, many with few target genes and low expression levels, suggests the rapid evolution of miRNA genes. The development of a miRNA database, BraMRs, enables us to integrate miRNA identification, target prediction, and functional annotation of target genes. BraMRs will represent a valuable public resource with which to study the epigenetic control of B. rapa and other closely related Brassica species. The database is available at the following link: http://bramrs.rna.kr [1]. PMID:23163954

Biochemical identification of Argonaute 2 as the sole protein required for RNA-induced silencing complex activity

PubMed Central

Rand, Tim A.; Ginalski, Krzysztof; Grishin, Nick V.; Wang, Xiaodong

2004-01-01

RNA interference is carried out by the small double-stranded RNA-induced silencing complex (RISC). The RISC-bound small RNA guides the RISC complex to identify and cleave mRNAs with complementary sequences. The proteins that make up the RISC complex and cleave mRNA have not been unequivocally defined. Here, we report the biochemical purification of RISC activity to homogeneity from Drosophila Schnieder 2 cell extracts. Argonaute 2 (Ago-2) is the sole protein component present in the purified, functional RISC. By using a bioinformatics method that combines sequence-profile analysis with predicted protein secondary structure, we found homology between the PIWI domain of Ago-2 and endonuclease V and identified potential active-site amino acid residues within the PIWI domain of Ago-2. PMID:15452342

Biochemical identification of Argonaute 2 as the sole protein required for RNA-induced silencing complex activity.

PubMed

Rand, Tim A; Ginalski, Krzysztof; Grishin, Nick V; Wang, Xiaodong

2004-10-05

RNA interference is carried out by the small double-stranded RNA-induced silencing complex (RISC). The RISC-bound small RNA guides the RISC complex to identify and cleave mRNAs with complementary sequences. The proteins that make up the RISC complex and cleave mRNA have not been unequivocally defined. Here, we report the biochemical purification of RISC activity to homogeneity from Drosophila Schnieder 2 cell extracts. Argonaute 2 (Ago-2) is the sole protein component present in the purified, functional RISC. By using a bioinformatics method that combines sequence-profile analysis with predicted protein secondary structure, we found homology between the PIWI domain of Ago-2 and endonuclease V and identified potential active-site amino acid residues within the PIWI domain of Ago-2.

RNA 3D Structure Modeling by Combination of Template-Based Method ModeRNA, Template-Free Folding with SimRNA, and Refinement with QRNAS.

PubMed

Piatkowski, Pawel; Kasprzak, Joanna M; Kumar, Deepak; Magnus, Marcin; Chojnowski, Grzegorz; Bujnicki, Janusz M

2016-01-01

RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/ . SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb . For model optimization we use QRNAS, available at http://genesilico.pl/qrnas .

Position-specific binding of FUS to nascent RNA regulates mRNA length

PubMed Central

Masuda, Akio; Takeda, Jun-ichi; Okuno, Tatsuya; Okamoto, Takaaki; Ohkawara, Bisei; Ito, Mikako; Ishigaki, Shinsuke; Sobue, Gen

2015-01-01

More than half of all human genes produce prematurely terminated polyadenylated short mRNAs. However, the underlying mechanisms remain largely elusive. CLIP-seq (cross-linking immunoprecipitation [CLIP] combined with deep sequencing) of FUS (fused in sarcoma) in neuronal cells showed that FUS is frequently clustered around an alternative polyadenylation (APA) site of nascent RNA. ChIP-seq (chromatin immunoprecipitation [ChIP] combined with deep sequencing) of RNA polymerase II (RNAP II) demonstrated that FUS stalls RNAP II and prematurely terminates transcription. When an APA site is located upstream of an FUS cluster, FUS enhances polyadenylation by recruiting CPSF160 and up-regulates the alternative short transcript. In contrast, when an APA site is located downstream from an FUS cluster, polyadenylation is not activated, and the RNAP II-suppressing effect of FUS leads to down-regulation of the alternative short transcript. CAGE-seq (cap analysis of gene expression [CAGE] combined with deep sequencing) and PolyA-seq (a strand-specific and quantitative method for high-throughput sequencing of 3' ends of polyadenylated transcripts) revealed that position-specific regulation of mRNA lengths by FUS is operational in two-thirds of transcripts in neuronal cells, with enrichment in genes involved in synaptic activities. PMID:25995189

Gel-seq: A Method for Simultaneous Sequencing Library Preparation of DNA and RNA Using Hydrogel Matrices.

PubMed

Hoople, Gordon D; Richards, Andrew; Wu, Yan; Pisano, Albert P; Zhang, Kun

2018-03-26

The ability to amplify and sequence either DNA or RNA from small starting samples has only been achieved in the last five years. Unfortunately, the standard protocols for generating genomic or transcriptomic libraries are incompatible and researchers must choose whether to sequence DNA or RNA for a particular sample. Gel-seq solves this problem by enabling researchers to simultaneously prepare libraries for both DNA and RNA starting with 100 - 1000 cells using a simple hydrogel device. This paper presents a detailed approach for the fabrication of the device as well as the biological protocol to generate paired libraries. We designed Gel-seq so that it could be easily implemented by other researchers; many genetics labs already have the necessary equipment to reproduce the Gel-seq device fabrication. Our protocol employs commonly-used kits for both whole-transcript amplification (WTA) and library preparation, which are also likely to be familiar to researchers already versed in generating genomic and transcriptomic libraries. Our approach allows researchers to bring to bear the power of both DNA and RNA sequencing on a single sample without splitting and with negligible added cost.

Rapid Sequencing of Complete env Genes from Primary HIV-1 Samples.

PubMed

Laird Smith, Melissa; Murrell, Ben; Eren, Kemal; Ignacio, Caroline; Landais, Elise; Weaver, Steven; Phung, Pham; Ludka, Colleen; Hepler, Lance; Caballero, Gemma; Pollner, Tristan; Guo, Yan; Richman, Douglas; Poignard, Pascal; Paxinos, Ellen E; Kosakovsky Pond, Sergei L; Smith, Davey M

2016-07-01

The ability to study rapidly evolving viral populations has been constrained by the read length of next-generation sequencing approaches and the sampling depth of single-genome amplification methods. Here, we develop and characterize a method using Pacific Biosciences' Single Molecule, Real-Time (SMRT®) sequencing technology to sequence multiple, intact full-length human immunodeficiency virus-1 env genes amplified from viral RNA populations circulating in blood, and provide computational tools for analyzing and visualizing these data.

History and current status of wheat miRNAs using next-generation sequencing and their roles in development and stress.

PubMed

Budak, Hikmet; Khan, Zaeema; Kantar, Melda

2015-05-01

As small molecules that aid in posttranscriptional silencing, microRNA (miRNA) discovery and characterization have vastly benefited from the recent development and widespread application of next-generation sequencing (NGS) technologies. Several miRNAs were identified through sequencing of constructed small RNA libraries, whereas others were predicted by in silico methods using the recently accumulating sequence data. NGS was a major breakthrough in efforts to sequence and dissect the genomes of plants, including bread wheat and its progenitors, which have large, repetitive and complex genomes. Availability of survey sequences of wheat whole genome and its individual chromosomes enabled researchers to predict and assess wheat miRNAs both in the subgenomic and whole genome levels. Moreover, small RNA construction and sequencing-based studies identified several putative development- and stress-related wheat miRNAs, revealing their differential expression patterns in specific developmental stages and/or in response to stress conditions. With the vast amount of wheat miRNAs identified in recent years, we are approaching to an overall knowledge on the wheat miRNA repertoire. In the following years, more comprehensive research in relation to miRNA conservation or divergence across wheat and its close relatives or progenitors should be performed. Results may serve valuable in understanding both the significant roles of species-specific miRNAs and also provide us information in relation to the dynamics between miRNAs and evolution in wheat. Furthermore, putative development- or stress-related miRNAs identified should be subjected to further functional analysis, which may be valuable in efforts to develop wheat with better resistance and/or yield. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

[Knockdown of STAT3 inhibits proliferation and migration of HepG2 hepatoma cells induced by IFN1].

PubMed

Li, Xiaofang; Wang, Yuqi; Yan, Ben; Fang, Peipei; Ma, Chao; Xu, Ning; Fu, Xiaoyan; Liang, Shujuan

2018-02-01

Objective To prepare lentiviruses expressing shRNA sequences targeting human signal transducer and activator of transcription 3 (STAT3) and detect the effect of STAT3 knockdown on type I interferon (IFN1)-induced proliferation and migration in HepG2 cells. Methods Four STAT3-targeting shRNA sequences (shRNA1-shRNA4) and one control sequence (Ctrl shRNA) were selected and cloned respectively into pLKO.1-sp6-pgk-GFP to construct shRNA-expressing vectors. Along with backbone psPAX2 and pMD2.G vectors, they were separately transfected into HEK293T cells to prepare lentiviruses. HepG2 cells were infected with the lentiviruses. Cytoplastic STAT3 level was detected by Western blotting to screen effective shRNA sequence(s) targeting STAT3. Proliferation and migration of HepG2 cells were analyzed by CCK-8 assay and Transwell TM migration and scratching assay, respectively. To detect the effect of IFN1 on cell proliferation and migration of HepG2 cells, the cells were treated with 2000 U/mL IFNα2b for indicated time and the activation of IFN-triggered STAT1 signal transduction was assayed by Western blotting. Results Two most effective STAT3-targeting shRNA sequences shRNA1 and shRNA2 were selected, and the expression of both STAT3 shRNA significantly decreased proliferation and migration of HepG2 cells. When treated with IFNα2b, 2000 U/mL of IFN1 showed more competent in attenuating growth and migration of HepG2 cells. Our data further proved that knockdown of STAT3 increased the phosphorylation of STAT1, and IFNα2b further enhanced the activation of STAT1 signaling in HepG2 cells. Conclusion Knockdown of STAT3 inhibits cell migration and growth, and rescues IFN response through up-regulating STAT1 signal transduction in HepG2 hepatoma cells.

Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine

NASA Astrophysics Data System (ADS)

Xing, Pengwei; Su, Ran; Guo, Fei; Wei, Leyi

2017-04-01

N6-methyladenosine (m6A) refers to methylation of the adenosine nucleotide acid at the nitrogen-6 position. It plays an important role in a series of biological processes, such as splicing events, mRNA exporting, nascent mRNA synthesis, nuclear translocation and translation process. Numerous experiments have been done to successfully characterize m6A sites within sequences since high-resolution mapping of m6A sites was established. However, as the explosive growth of genomic sequences, using experimental methods to identify m6A sites are time-consuming and expensive. Thus, it is highly desirable to develop fast and accurate computational identification methods. In this study, we propose a sequence-based predictor called RAM-NPPS for identifying m6A sites within RNA sequences, in which we present a novel feature representation algorithm based on multi-interval nucleotide pair position specificity, and use support vector machine classifier to construct the prediction model. Comparison results show that our proposed method outperforms the state-of-the-art predictors on three benchmark datasets across the three species, indicating the effectiveness and robustness of our method. Moreover, an online webserver implementing the proposed predictor has been established at http://server.malab.cn/RAM-NPPS/. It is anticipated to be a useful prediction tool to assist biologists to reveal the mechanisms of m6A site functions.

The complete mitochondrial genome of Conus tulipa (Neogastropoda: Conidae).

PubMed

Chen, Po-Wei; Hsiao, Sheng-Tai; Huang, Chih-Wei; Chen, Kao-Sung; Tseng, Chen-Te; Wu, Wen-Lung; Hwang, Deng-Fwu

2016-07-01

The complete mitogenome sequence of the cone snail Conus tulipa (Linnaeus, 1758) has been sequenced by next-generation sequencing method. The assembled mitogenome is 16,599 bp in length, including 13 protein-coding genes, 22 transfer RNA genes and 2 ribosomal RNA genes. The overall base composition of C. tulipa is 28.7% A, 15.2% C, 18.4% G and 37.7% T. It shows 81.1% identity to the cone snail C. consors, 78.5% to C. borgesi and 77.5% to C. textile. Using the 13 protein-coding genes and 2 ribosomal RNA genes of C. tulipa in this study, together with 18 other closely species, we constructed the species phylogenetic tree to verify the accuracy and utility of new determined mitogenome sequence. The complete mitogenome of the C. tulipa provides an essential and important DNA molecular data for further phylogeography and evolutionary analysis for cone snail phylogeny.

Computational Prediction of miRNA Genes from Small RNA Sequencing Data

PubMed Central

Kang, Wenjing; Friedländer, Marc R.

2015-01-01

Next-generation sequencing now for the first time allows researchers to gage the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. microRNAs (miRNAs) are 22 nucleotide small RNAs (sRNAs) that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq), which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here, we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field. PMID:25674563

A general method to eliminate laboratory induced recombinants during massive, parallel sequencing of cDNA library.

PubMed

Waugh, Caryll; Cromer, Deborah; Grimm, Andrew; Chopra, Abha; Mallal, Simon; Davenport, Miles; Mak, Johnson

2015-04-09

Massive, parallel sequencing is a potent tool for dissecting the regulation of biological processes by revealing the dynamics of the cellular RNA profile under different conditions. Similarly, massive, parallel sequencing can be used to reveal the complexity of viral quasispecies that are often found in the RNA virus infected host. However, the production of cDNA libraries for next-generation sequencing (NGS) necessitates the reverse transcription of RNA into cDNA and the amplification of the cDNA template using PCR, which may introduce artefact in the form of phantom nucleic acids species that can bias the composition and interpretation of original RNA profiles. Using HIV as a model we have characterised the major sources of error during the conversion of viral RNA to cDNA, namely excess RNA template and the RNaseH activity of the polymerase enzyme, reverse transcriptase. In addition we have analysed the effect of PCR cycle on detection of recombinants and assessed the contribution of transfection of highly similar plasmid DNA to the formation of recombinant species during the production of our control viruses. We have identified RNA template concentrations, RNaseH activity of reverse transcriptase, and PCR conditions as key parameters that must be carefully optimised to minimise chimeric artefacts. Using our optimised RT-PCR conditions, in combination with our modified PCR amplification procedure, we have developed a reliable technique for accurate determination of RNA species using NGS technology.

High throughput sequencing analysis of RNA libraries reveals the influences of initial library and PCR methods on SELEX efficiency

PubMed Central

Takahashi, Mayumi; Wu, Xiwei; Ho, Michelle; Chomchan, Pritsana; Rossi, John J.; Burnett, John C.; Zhou, Jiehua

2016-01-01

The systemic evolution of ligands by exponential enrichment (SELEX) technique is a powerful and effective aptamer-selection procedure. However, modifications to the process can dramatically improve selection efficiency and aptamer performance. For example, droplet digital PCR (ddPCR) has been recently incorporated into SELEX selection protocols to putatively reduce the propagation of byproducts and avoid selection bias that result from differences in PCR efficiency of sequences within the random library. However, a detailed, parallel comparison of the efficacy of conventional solution PCR versus the ddPCR modification in the RNA aptamer-selection process is needed to understand effects on overall SELEX performance. In the present study, we took advantage of powerful high throughput sequencing technology and bioinformatics analysis coupled with SELEX (HT-SELEX) to thoroughly investigate the effects of initial library and PCR methods in the RNA aptamer identification. Our analysis revealed that distinct “biased sequences” and nucleotide composition existed in the initial, unselected libraries purchased from two different manufacturers and that the fate of the “biased sequences” was target-dependent during selection. Our comparison of solution PCR- and ddPCR-driven HT-SELEX demonstrated that PCR method affected not only the nucleotide composition of the enriched sequences, but also the overall SELEX efficiency and aptamer efficacy. PMID:27652575

Improved design of hammerhead ribozyme for selective digestion of target RNA through recognition of site-specific adenosine-to-inosine RNA editing

PubMed Central

Fukuda, Masatora; Kurihara, Kei; Yamaguchi, Shota; Oyama, Yui; Deshimaru, Masanobu

2014-01-01

Adenosine-to-inosine (A-to-I) RNA editing is an endogenous regulatory mechanism involved in various biological processes. Site-specific, editing-state–dependent degradation of target RNA may be a powerful tool both for analyzing the mechanism of RNA editing and for regulating biological processes. Previously, we designed an artificial hammerhead ribozyme (HHR) for selective, site-specific RNA cleavage dependent on the A-to-I RNA editing state. In the present work, we developed an improved strategy for constructing a trans-acting HHR that specifically cleaves target editing sites in the adenosine but not the inosine state. Specificity for unedited sites was achieved by utilizing a sequence encoding the intrinsic cleavage specificity of a natural HHR. We used in vitro selection methods in an HHR library to select for an extended HHR containing a tertiary stabilization motif that facilitates HHR folding into an active conformation. By using this method, we successfully constructed highly active HHRs with unedited-specific cleavage. Moreover, using HHR cleavage followed by direct sequencing, we demonstrated that this ribozyme could cleave serotonin 2C receptor (HTR2C) mRNA extracted from mouse brain, depending on the site-specific editing state. This unedited-specific cleavage also enabled us to analyze the effect of editing state at the E and C sites on editing at other sites by using direct sequencing for the simultaneous quantification of the editing ratio at multiple sites. Our approach has the potential to elucidate the mechanism underlying the interdependencies of different editing states in substrate RNA with multiple editing sites. PMID:24448449

Estimating Bacterial Diversity for Ecological Studies: Methods, Metrics, and Assumptions

PubMed Central

Birtel, Julia; Walser, Jean-Claude; Pichon, Samuel; Bürgmann, Helmut; Matthews, Blake

2015-01-01

Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5). Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques. PMID:25915756

[Genetic diversity and phylogeny of rhizobia isolated from peanut (Arachis hypogaea)].

PubMed

Yang, Jiang-Ke; Xie, Fu-Li; Zhou, Jun-Chu

2002-12-01

Forty three rhizobium strains isolated from peanut (Arachis hypogaea) and 15 reference strains from other genus and species were analyzed by the method of 16S rRNA RFLP, 16S rRNA sequencing and 16S-23S IGS PCR RFLP. The results of the 16S rRNA RFLP shown that 43 strains tested were all ascribed to the genus of Bradyrhizobium phylogenetically. Strains tested were adjacent to the B. japonicum and far from B. elkanii 16S rRNA genotype. The genotypes generated by the 4 restriction endonucleases, Mbo I, Dde I, Hae III and Msp I, were same as the representatives of B. japonicum. The dendrogram generated by 16S rRNA sequence and Neighbor-joining method shown that peanut rhizobia clustered into the subcluster represented by B. japonicum and B. liaoningense, were more close to B. liaoningense genetically, and the sequence difference between them was less than 1%. High sequence similarity was also determined between B. liaoningense and B. japonicum. JZ1, representative strain of peanut rhizobia were systematically far from the B. elkanii, and the sequence divergence about 2%. The results from IGS RFLP analysis indicated that although they were phylogenetically close to B. japonicum and B. elkanii, peanut rhizobia forming an independent group at the similarity of 71% could be further divided into four subgroups, A, B, C and D. Subgroup A consisted of strains from different region, subgroup B was composed of strains from Wuchang, Qianjiang and Jingzhou, subgroup C was mainly composed of strains from Jingzhou and starins of subgroup D mainly from Neijiang. Reference strains from B. japonicum and B. elkanii were independently clustered into the subgroup E at the similarity of 71%. The geographical factor effect on genetic diversity of rhizobia was found.

CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing data.

PubMed

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-07-01

Small RNAs (sRNAs) are 20-25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci. To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.

The Human Microbiome and Understanding the 16S rRNA Gene in Translational Nursing Science.

PubMed

Ames, Nancy J; Ranucci, Alexandra; Moriyama, Brad; Wallen, Gwenyth R

As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and healthcare practitioners to analyze these microbial communities and their role in health and disease. 16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings. The objectives of this review are to (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung, and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science. Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists-individuals uniquely positioned to utilize these techniques in future studies in clinical settings.

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites.

PubMed

Betel, Doron; Koppal, Anjali; Agius, Phaedra; Sander, Chris; Leslie, Christina

2010-01-01

mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

A New Challenge for Compression Algorithms: Genetic Sequences.

ERIC Educational Resources Information Center

Grumbach, Stephane; Tahi, Fariza

1994-01-01

Analyzes the properties of genetic sequences that cause the failure of classical algorithms used for data compression. A lossless algorithm, which compresses the information contained in DNA and RNA sequences by detecting regularities such as palindromes, is presented. This algorithm combines substitutional and statistical methods and appears to…

N6-Methylation Assessment in Escherichia coli 23S rRNA Utilizing a Bulge Loop in an RNA-DNA Hybrid.

PubMed

Yoshioka, Kyoko; Kurita, Ryoji

2018-06-07

We propose a sequence-selective assay of N6-methyl-adenosine (m6A) in RNA without PCR or reverse transcription, by employing a hybridization assay with a DNA probe designed to form a bulge loop at the position of a target modified nucleotide. The m6A in the bulge in the RNA-DNA hybrid was assumed to be sufficiently mobile to be selectively recognized by an anti-m6A antibody with a high affinity. By employing a surface-plasmon-resonance measurement or using a microtiter-plate immunoassay method, a specific m6A in the Escherichia coli 23S rRNA sequence could be detected at the nanomolar level when synthesized and purified oligo-RNA fragments were used for measurement. We have successfully achieved the first selective detection of m6A 2030 specifically in 23S rRNA from real samples of E. coli total RNA by using our immunochemical approach.

The maize stripe virus major noncapsid protein messenger RNA transcripts contain heterogeneous leader sequences at their 5' termini.

PubMed

Huiet, L; Feldstein, P A; Tsai, J H; Falk, B W

1993-12-01

Primer extension analyses and a PCR-based cloning strategy were used to identify and characterize 5' nucleotide sequences on the maize stripe virus (MStV) RNA4 mRNA transcripts encoding the major noncapsid protein (NCP). Direct RNA sequence analysis by primer extension showed that the NCP mRNA transcripts had 10-15 nucleotides beyond the 5' terminus of the MStV RNA4 nucleotide sequence. MStV genomic RNAs isolated from ribonucleoprotein particles (RNPs) lacked the additional 5' nucleotides. cDNA clones representing the 5' region of the mRNA transcripts were constructed, and the nucleotide sequences of the 5' regions were determined for 16 clones. Each was found to have a distinct 10-15 nucleotide sequence immediately 5' of the MStV RNA4 sequence. Eleven of 16 clones had the correct MStV RNA4 5' nucleotide sequence, while five showed minor variations at or near the 5' most MStV RNA4 nucleotide. These characteristics show strong similarities to other viral mRNA transcripts which are synthesized by cap snatching.

Functional Analysis of RNA Interference-Related Soybean Pod Borer (Lepidoptera) Genes Based on Transcriptome Sequences.

PubMed

Meng, Fanli; Yang, Mingyu; Li, Yang; Li, Tianyu; Liu, Xinxin; Wang, Guoyue; Wang, Zhanchun; Jin, Xianhao; Li, Wenbin

2018-01-01

RNA interference (RNAi) is useful for controlling pests of agriculturally important crops. The soybean pod borer (SPB) is the most important soybean pest in Northeastern Asia. In an earlier study, we confirmed that the SPB could be controlled via transgenic plant-mediated RNAi. Here, the SPB transcriptome was sequenced to identify RNAi-related genes, and also to establish an RNAi-of-RNAi assay system for evaluating genes involved in the SPB systemic RNAi response. The core RNAi genes, as well as genes potentially involved in double-stranded RNA (dsRNA) uptake were identified based on SPB transcriptome sequences. A phylogenetic analysis and the characterization of these core components as well as dsRNA uptake related genes revealed that they contain conserved domains essential for the RNAi pathway. The results of the RNAi-of-RNAi assay involving Laccas e 2 (a critical cuticle pigmentation gene) as a marker showed that genes encoding the sid-like ( Sil1 ), scavenger receptor class C ( Src ), and scavenger receptor class B ( Srb3 and Srb4 ) proteins of the endocytic pathway were required for SPB cellular uptake of dsRNA. The SPB response was inferred to contain three functional small RNA pathways (i.e., miRNA, siRNA, and piRNA pathways). Additionally, the SPB systemic RNA response may rely on systemic RNA interference deficient transmembrane channel-mediated and receptor-mediated endocytic pathways. The results presented herein may be useful for developing RNAi-mediated methods to control SPB infestations in soybean.

Functional Analysis of RNA Interference-Related Soybean Pod Borer (Lepidoptera) Genes Based on Transcriptome Sequences

PubMed Central

Meng, Fanli; Yang, Mingyu; Li, Yang; Li, Tianyu; Liu, Xinxin; Wang, Guoyue; Wang, Zhanchun; Jin, Xianhao; Li, Wenbin

2018-01-01

RNA interference (RNAi) is useful for controlling pests of agriculturally important crops. The soybean pod borer (SPB) is the most important soybean pest in Northeastern Asia. In an earlier study, we confirmed that the SPB could be controlled via transgenic plant-mediated RNAi. Here, the SPB transcriptome was sequenced to identify RNAi-related genes, and also to establish an RNAi-of-RNAi assay system for evaluating genes involved in the SPB systemic RNAi response. The core RNAi genes, as well as genes potentially involved in double-stranded RNA (dsRNA) uptake were identified based on SPB transcriptome sequences. A phylogenetic analysis and the characterization of these core components as well as dsRNA uptake related genes revealed that they contain conserved domains essential for the RNAi pathway. The results of the RNAi-of-RNAi assay involving Laccase 2 (a critical cuticle pigmentation gene) as a marker showed that genes encoding the sid-like (Sil1), scavenger receptor class C (Src), and scavenger receptor class B (Srb3 and Srb4) proteins of the endocytic pathway were required for SPB cellular uptake of dsRNA. The SPB response was inferred to contain three functional small RNA pathways (i.e., miRNA, siRNA, and piRNA pathways). Additionally, the SPB systemic RNA response may rely on systemic RNA interference deficient transmembrane channel-mediated and receptor-mediated endocytic pathways. The results presented herein may be useful for developing RNAi-mediated methods to control SPB infestations in soybean. PMID:29773992

RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

PubMed Central

Cruz, José Almeida; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cao, Song; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Flores, Samuel Coulbourn; Huang, Lili; Lavender, Christopher A.; Lisi, Véronique; Major, François; Mikolajczak, Katarzyna; Patel, Dinshaw J.; Philips, Anna; Puton, Tomasz; Santalucia, John; Sijenyi, Fredrick; Hermann, Thomas; Rother, Kristian; Rother, Magdalena; Serganov, Alexander; Skorupski, Marcin; Soltysinski, Tomasz; Sripakdeevong, Parin; Tuszynska, Irina; Weeks, Kevin M.; Waldsich, Christina; Wildauer, Michael; Leontis, Neocles B.; Westhof, Eric

2012-01-01

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises. PMID:22361291

Comprehensive Analysis of Bacterial Flora in Postoperative Maxillary Cyst Fluid by 16S rRNA Gene and Culture Methods

PubMed Central

Sano, Naoto; Yamashita, Yoshio; Fukuda, Kazumasa; Taniguchi, Hatsumi; Goto, Masaaki; Miyamoto, Hiroshi

2012-01-01

Intracystic fluid was aseptically collected from 11 patients with postoperative maxillary cyst (POMC), and DNA was extracted from the POMC fluid. Bacterial species were identified by sequencing after cloning of approximately 580 bp of the 16S rRNA gene. Identification of pathogenic bacteria was also performed by culture methods. The phylogenetic identity was determined by sequencing 517–596 bp in each of the 1139 16S rRNA gene clones. A total of 1114 clones were classified while the remaining 25 clones were unclassified. A total of 103 bacterial species belonging to 42 genera were identified in POMC fluid samples by 16S rRNA gene analysis. Species of Prevotella (91%), Neisseria (73%), Fusobacterium (73%), Porphyromonas (73%), and Propionibacterium (73%) were found to be highly prevalent in all patients. Streptococcus mitis (64%), Fusobacterium nucleatum (55%), Propionibacterium acnes (55%), Staphylococcus capitis (55%), and Streptococcus salivarius (55%) were detected in more than 6 of the 11 patients. The results obtained by the culture method were different from those obtained by 16S rRNA gene analysis, but both approaches may be necessary for the identification of pathogens, especially of bacteria that are difficult to detect by culture methods, and the development of rational treatments for patients with POMC. PMID:22685668

The conserved CAAGAAAGA spacer sequence is an essential element for the formation of 3' termini of the sea urchin H3 histone mRNA by RNA processing.

PubMed Central

Georgiev, O; Birnstiel, M L

1985-01-01

Analysis of cDNA sequences obtained from the small nuclear RNA U7 has previously suggested specific contacts, by base pairing, between the conserved stem-loop structure and CAAGAAAGA sequence of the histone pre-mRNA and the 5'-terminal sequence of the U7 RNA during RNA processing. In order to test some aspects of the model we have created a series of linker scan, deletion and insertion mutants of the 3' terminus of a sea urchin H3 histone gene and have injected mutant DNAs or in vitro synthesized precursors into frog oocyte nuclei for interpretation. We find that, in addition to the stem-loop structure of the mRNA, the CAAGAAAGA spacer transcript within the histone pre-mRNA is required absolutely for RNA processing, as predicted from our model. Spacer sequences immediately downstream of the CAAGAAAGA motif are not complementary to U7 RNA. Nevertheless, they are necessary for obtaining a maximal rate of RNA processing, as is the ACCA sequence coding for the 3' terminus of the mature mRNA. An increase of distance between the mRNA palindrome and the CAAGAAAGA by as little as six nucleotides abolishes all processing. It may, therefore, be useful to regard both these sequence motifs as part of one and the same RNA processing signal with narrowly defined topologies. Interestingly, U7 RNA-dependent 3' processing of histone pre-mRNA can occur in RNA injection experiments only when the in vitro synthesized pre-mRNA contains sequence extensions well beyond the region of sequence complementarities to the U7 RNA. In addition to directing 3' processing the terminal mRNA sequences may have a role in histone mRNA stabilization in the cytoplasmic compartment. Images Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. PMID:2410259

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Linnorm: improved statistical analysis for single cell RNA-seq expression data.

PubMed

Yip, Shun H; Wang, Panwen; Kocher, Jean-Pierre A; Sham, Pak Chung; Wang, Junwen

2017-12-15

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Impact of Normalization Methods on RNA-Seq Data Analysis

PubMed Central

Zyprych-Walczak, J.; Szabelska, A.; Handschuh, L.; Górczak, K.; Klamecka, K.; Figlerowicz, M.; Siatkowski, I.

2015-01-01

High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational methods that can tackle the analysis and management of data. The data normalization is one of the most crucial steps of data processing and this process must be carefully considered as it has a profound effect on the results of the analysis. In this work, we focus on a comprehensive comparison of five normalization methods related to sequencing depth, widely used for transcriptome sequencing (RNA-seq) data, and their impact on the results of gene expression analysis. Based on this study, we suggest a universal workflow that can be applied for the selection of the optimal normalization procedure for any particular data set. The described workflow includes calculation of the bias and variance values for the control genes, sensitivity and specificity of the methods, and classification errors as well as generation of the diagnostic plots. Combining the above information facilitates the selection of the most appropriate normalization method for the studied data sets and determines which methods can be used interchangeably. PMID:26176014

antaRNA: ant colony-based RNA sequence design.

PubMed

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Nucleotide cleaving agents and method

DOEpatents

Que, Jr., Lawrence; Hanson, Richard S.; Schnaith, Leah M. T.

2000-01-01

The present invention provides a unique series of nucleotide cleaving agents and a method for cleaving a nucleotide sequence, whether single-stranded or double-stranded DNA or RNA, using and a cationic metal complex having at least one polydentate ligand to cleave the nucleotide sequence phosphate backbone to yield a hydroxyl end and a phosphate end.

Complete Deletion of the Fucose Operon in Haemophilus influenzae Is Associated with a Cluster in Multilocus Sequence Analysis-Based Phylogenetic Group II Related to Haemophilus haemolyticus: Implications for Identification and Typing

PubMed Central

de Gier, Camilla; Kirkham, Lea-Ann S.

2015-01-01

Nonhemolytic variants of Haemophilus haemolyticus are difficult to differentiate from Haemophilus influenzae despite a wide difference in pathogenic potential. A previous investigation characterized a challenging set of 60 clinical strains using multiple PCRs for marker genes and described strains that could not be unequivocally identified as either species. We have analyzed the same set of strains by multilocus sequence analysis (MLSA) and near-full-length 16S rRNA gene sequencing. MLSA unambiguously allocated all study strains to either of the two species, while identification by 16S rRNA sequence was inconclusive for three strains. Notably, the two methods yielded conflicting identifications for two strains. Most of the “fuzzy species” strains were identified as H. influenzae that had undergone complete deletion of the fucose operon. Such strains, which are untypeable by the H. influenzae multilocus sequence type (MLST) scheme, have sporadically been reported and predominantly belong to a single branch of H. influenzae MLSA phylogenetic group II. We also found evidence of interspecies recombination between H. influenzae and H. haemolyticus within the 16S rRNA genes. Establishing an accurate method for rapid and inexpensive identification of H. influenzae is important for disease surveillance and treatment. PMID:26378279

Analysis of alterative cleavage and polyadenylation by 3′ region extraction and deep sequencing

PubMed Central

Hoque, Mainul; Ji, Zhe; Zheng, Dinghai; Luo, Wenting; Li, Wencheng; You, Bei; Park, Ji Yeon; Yehia, Ghassan; Tian, Bin

2012-01-01

Alternative cleavage and polyadenylation (APA) leads to mRNA isoforms with different coding sequences (CDS) and/or 3′ untranslated regions (3′UTRs). Using 3′ Region Extraction And Deep Sequencing (3′READS), a method which addresses the internal priming and oligo(A) tail issues that commonly plague polyA site (pA) identification, we comprehensively mapped pAs in the mouse genome, thoroughly annotating 3′ ends of genes and revealing over five thousand pAs (~8% of total) flanked by A-rich sequences, which have hitherto been overlooked. About 79% of mRNA genes and 66% of long non-coding RNA (lncRNA) genes have APA; but these two gene types have distinct usage patterns for pAs in introns and upstream exons. Promoter-distal pAs become relatively more abundant during embryonic development and cell differentiation, a trend affecting pAs in both 3′-most exons and upstream regions. Upregulated isoforms generally have stronger pAs, suggesting global modulation of the 3′ end processing activity in development and differentiation. PMID:23241633

RNase-Resistant Virus-Like Particles Containing Long Chimeric RNA Sequences Produced by Two-Plasmid Coexpression System▿

PubMed Central

Wei, Yuxiang; Yang, Changmei; Wei, Baojun; Huang, Jie; Wang, Lunan; Meng, Shuang; Zhang, Rui; Li, Jinming

2008-01-01

RNase-resistant, noninfectious virus-like particles containing exogenous RNA sequences (armored RNA) are good candidates as RNA controls and standards in RNA virus detection. However, the length of RNA packaged in the virus-like particles with high efficiency is usually less than 500 bases. In this study, we describe a method for producing armored L-RNA. Armored L-RNA is a complex of MS2 bacteriophage coat protein and RNA produced in Escherichia coli by the induction of a two-plasmid coexpression system in which the coat protein and maturase are expressed from one plasmid and the target RNA sequence with modified MS2 stem-loop (pac site) is transcribed from another plasmid. A 3V armored L-RNA of 2,248 bases containing six gene fragments—hepatitis C virus, severe acute respiratory syndrome coronavirus (SARS-CoV1, SARS-CoV2, and SARS-CoV3), avian influenza virus matrix gene (M300), and H5N1 avian influenza virus (HA300)—was successfully expressed by the two-plasmid coexpression system and was demonstrated to have all of the characteristics of armored RNA. We evaluated the 3V armored L-RNA as a calibrator for multiple virus assays. We used the WHO International Standard for HCV RNA (NIBSC 96/790) to calibrate the chimeric armored L-RNA, which was diluted by 10-fold serial dilutions to obtain samples containing 106 to 102 copies. In conclusion, the approach we used for armored L-RNA preparation is practical and could reduce the labor and cost of quality control in multiplex RNA virus assays. Furthermore, we can assign the chimeric armored RNA with an international unit for quantitative detection. PMID:18305135

The complete genomic sequence of a tentative new polerovirus identified in barley in South Korea.

PubMed

Zhao, Fumei; Lim, Seungmo; Yoo, Ran Hee; Igori, Davaajargal; Kim, Sang-Min; Kwak, Do Yeon; Kim, Sun Lim; Lee, Bong Choon; Moon, Jae Sun

2016-07-01

The complete nucleotide sequence of a new barley polerovirus, tentatively named barley virus G (BVG), which was isolated in Gimje, South Korea, has been determined using an RNA sequencing technique combined with polymerase chain reaction methods. The viral genomic RNA of BVG is 5,620 nucleotides long and contains six typical open reading frames commonly observed in other poleroviruses. Sequence comparisons revealed that BVG is most closely related to maize yellow dwarf virus-RMV, with the highest amino acid identities being less than 90 % for all of the corresponding proteins. These results suggested that BVG is a member of a new species in the genus Polerovirus.

Rapid Sequencing of Complete env Genes from Primary HIV-1 Samples

PubMed Central

Eren, Kemal; Ignacio, Caroline; Landais, Elise; Weaver, Steven; Phung, Pham; Ludka, Colleen; Hepler, Lance; Caballero, Gemma; Pollner, Tristan; Guo, Yan; Richman, Douglas; Poignard, Pascal; Paxinos, Ellen E.; Kosakovsky Pond, Sergei L.

2016-01-01

Abstract The ability to study rapidly evolving viral populations has been constrained by the read length of next-generation sequencing approaches and the sampling depth of single-genome amplification methods. Here, we develop and characterize a method using Pacific Biosciences’ Single Molecule, Real-Time (SMRT®) sequencing technology to sequence multiple, intact full-length human immunodeficiency virus-1 env genes amplified from viral RNA populations circulating in blood, and provide computational tools for analyzing and visualizing these data. PMID:29492273

Analysis of the 3’ untranslated regions of α-tubulin and S-crystallin mRNA and the identification of CPEB in dark- and light-adapted octopus retinas

PubMed Central

Kelly, Shannan; Yamamoto, Hideki

2008-01-01

Purpose We previously reported the differential expression and translation of mRNA and protein in dark- and light-adapted octopus retinas, which may result from cytoplasmic polyadenylation element (CPE)–dependent mRNA masking and unmasking. Here we investigate the presence of CPEs in α-tubulin and S-crystallin mRNA and report the identification of cytoplasmic polyadenylation element binding protein (CPEB) in light- and dark-adapted octopus retinas. Methods 3’-RACE and sequencing were used to isolate and analyze the 3’-UTRs of α-tubulin and S-crystallin mRNA. Total retinal protein isolated from light- and dark-adapted octopus retinas was subjected to western blot analysis followed by CPEB antibody detection, PEP-171 inhibition of CPEB, and dephosphorylation of CPEB. Results The following CPE-like sequence was detected in the 3’-UTR of isolated long S-crystallin mRNA variants: UUUAACA. No CPE or CPE-like sequences were detected in the 3’-UTRs of α-tubulin mRNA or of the short S-crystallin mRNA variants. Western blot analysis detected CPEB as two putative bands migrating between 60-80 kDa, while a third band migrated below 30 kDa in dark- and light-adapted retinas. Conclusions The detection of CPEB and the identification of the putative CPE-like sequences in the S-crystallin 3’-UTR suggest that CPEB may be involved in the activation of masked S-crystallin mRNA, but not in the regulation of α-tubulin mRNA, resulting in increased S-crystallin protein synthesis in dark-adapted octopus retinas. PMID:18682811

TSSer: an automated method to identify transcription start sites in prokaryotic genomes from differential RNA sequencing data.

PubMed

Jorjani, Hadi; Zavolan, Mihaela

2014-04-01

Accurate identification of transcription start sites (TSSs) is an essential step in the analysis of transcription regulatory networks. In higher eukaryotes, the capped analysis of gene expression technology enabled comprehensive annotation of TSSs in genomes such as those of mice and humans. In bacteria, an equivalent approach, termed differential RNA sequencing (dRNA-seq), has recently been proposed, but the application of this approach to a large number of genomes is hindered by the paucity of computational analysis methods. With few exceptions, when the method has been used, annotation of TSSs has been largely done manually. In this work, we present a computational method called 'TSSer' that enables the automatic inference of TSSs from dRNA-seq data. The method rests on a probabilistic framework for identifying both genomic positions that are preferentially enriched in the dRNA-seq data as well as preferentially captured relative to neighboring genomic regions. Evaluating our approach for TSS calling on several publicly available datasets, we find that TSSer achieves high consistency with the curated lists of annotated TSSs, but identifies many additional TSSs. Therefore, TSSer can accelerate genome-wide identification of TSSs in bacterial genomes and can aid in further characterization of bacterial transcription regulatory networks. TSSer is freely available under GPL license at http://www.clipz.unibas.ch/TSSer/index.php

lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

PubMed

Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

2015-01-01

Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

Comparing K-mer based methods for improved classification of 16S sequences.

PubMed

Vinje, Hilde; Liland, Kristian Hovde; Almøy, Trygve; Snipen, Lars

2015-07-01

The need for precise and stable taxonomic classification is highly relevant in modern microbiology. Parallel to the explosion in the amount of sequence data accessible, there has also been a shift in focus for classification methods. Previously, alignment-based methods were the most applicable tools. Now, methods based on counting K-mers by sliding windows are the most interesting classification approach with respect to both speed and accuracy. Here, we present a systematic comparison on five different K-mer based classification methods for the 16S rRNA gene. The methods differ from each other both in data usage and modelling strategies. We have based our study on the commonly known and well-used naïve Bayes classifier from the RDP project, and four other methods were implemented and tested on two different data sets, on full-length sequences as well as fragments of typical read-length. The difference in classification error obtained by the methods seemed to be small, but they were stable and for both data sets tested. The Preprocessed nearest-neighbour (PLSNN) method performed best for full-length 16S rRNA sequences, significantly better than the naïve Bayes RDP method. On fragmented sequences the naïve Bayes Multinomial method performed best, significantly better than all other methods. For both data sets explored, and on both full-length and fragmented sequences, all the five methods reached an error-plateau. We conclude that no K-mer based method is universally best for classifying both full-length sequences and fragments (reads). All methods approach an error plateau indicating improved training data is needed to improve classification from here. Classification errors occur most frequent for genera with few sequences present. For improving the taxonomy and testing new classification methods, the need for a better and more universal and robust training data set is crucial.

The nucleotide sequence of the intergenic region between the 5.8S and 26S rRNA genes of the yeast ribosomal RNA operon. Possible implications for the interaction between 5.8S and 26S rRNA and the processing of the primary transcript.

PubMed Central

Veldman, G M; Klootwijk, J; van Heerikhuizen, H; Planta, R J

1981-01-01

We have determined the nucleotide sequence of part of a cloned yeast ribosomal RNA operon extending from the 5.8S RNA gene downstream into the 5' -terminal region of the 26S RNA gene. We mapped the pertinent processing sites, viz. the 5' end of 26S rRNA and the 3'ends of 5.8S rRNA and its immediate precursor, 7S RNA. At the 3' end of 7S RNA we find the sequence UCGUUU which is very similar to the type I consensus sequence UCAUUA/U present at the 3' ends of 17S, 5.8S and 26S rRNA as well as 18S precursor rRNA in yeast. At the 5' end of the 26S RNA gene we find a sequence of thirteen nucleotides which is homologous to the type II sequence present at the 5' termini of both the 17S and the 5.8S RNA gene. These findings further support the suggestion put forward earlier (G.M. Veldman et al. (1980) Nucl. Acids Res. 8, 2907-2920) that both consensus sequences are involved in the recognition of precursor rRNA by the processing nuclease(s). We discuss a model for the processing of yeast rRNA in which a processing enzyme sequentially recognizes several combinations of a type I and a type II consensus sequence. We also describe the existence of a significant base complementarity between sequences in the 5' -terminal region of 26S rRNA and the 3' -terminal region of 5.8S rRNA. We suggest that base pairing between these sequences contributes to the binding between 5.8S and 26S rRNA. Images PMID:7312619

Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

PubMed

Al-Khatib, Ra'ed M; Rashid, Nur'Aini Abdul; Abdullah, Rosni

2011-08-01

The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

Short Communication An efficient method for simultaneous extraction of high-quality RNA and DNA from various plant tissues.

PubMed

Oliveira, R R; Viana, A J C; Reátegui, A C E; Vincentz, M G A

2015-12-29

Determination of gene expression is an important tool to study biological processes and relies on the quality of the extracted RNA. Changes in gene expression profiles may be directly related to mutations in regulatory DNA sequences or alterations in DNA cytosine methylation, which is an epigenetic mark. Correlation of gene expression with DNA sequence or epigenetic mark polymorphism is often desirable; for this, a robust protocol to isolate high-quality RNA and DNA simultaneously from the same sample is required. Although commercial kits and protocols are available, they are mainly optimized for animal tissues and, in general, restricted to RNA or DNA extraction, not both. In the present study, we describe an efficient and accessible method to extract both RNA and DNA simultaneously from the same sample of various plant tissues, using small amounts of starting material. The protocol was efficient in the extraction of high-quality nucleic acids from several Arabidopsis thaliana tissues (e.g., leaf, inflorescence stem, flower, fruit, cotyledon, seedlings, root, and embryo) and from other tissues of non-model plants, such as Avicennia schaueriana (Acanthaceae), Theobroma cacao (Malvaceae), Paspalum notatum (Poaceae), and Sorghum bicolor (Poaceae). The obtained nucleic acids were used as templates for downstream analyses, such as mRNA sequencing, quantitative real time-polymerase chain reaction, bisulfite treatment, and others; the results were comparable to those obtained with commercial kits. We believe that this protocol could be applied to a broad range of plant species, help avoid technical and sampling biases, and facilitate several RNA- and DNA-dependent analyses.

Beta-Poisson model for single-cell RNA-seq data analyses.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High-Throughput Sequencing of RNA Silencing-Associated Small RNAs in Olive (Olea europaea L.)

PubMed Central

Donaire, Livia; Pedrola, Laia; de la Rosa, Raúl; Llave, César

2011-01-01

Small RNAs (sRNAs) of 20 to 25 nucleotides (nt) in length maintain genome integrity and control gene expression in a multitude of developmental and physiological processes. Despite RNA silencing has been primarily studied in model plants, the advent of high-throughput sequencing technologies has enabled profiling of the sRNA component of more than 40 plant species. Here, we used deep sequencing and molecular methods to report the first inventory of sRNAs in olive (Olea europaea L.). sRNA libraries prepared from juvenile and adult shoots revealed that the 24-nt class dominates the sRNA transcriptome and atypically accumulates to levels never seen in other plant species, suggesting an active role of heterochromatin silencing in the maintenance and integrity of its large genome. A total of 18 known miRNA families were identified in the libraries. Also, 5 other sRNAs derived from potential hairpin-like precursors remain as plausible miRNA candidates. RNA blots confirmed miRNA expression and suggested tissue- and/or developmental-specific expression patterns. Target mRNAs of conserved miRNAs were computationally predicted among the olive cDNA collection and experimentally validated through endonucleolytic cleavage assays. Finally, we use expression data to uncover genetic components of the miR156, miR172 and miR390/TAS3-derived trans-acting small interfering RNA (tasiRNA) regulatory nodes, suggesting that these interactive networks controlling developmental transitions are fully operational in olive. PMID:22140484

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Principles for Predicting RNA Secondary Structure Design Difficulty.

PubMed

Anderson-Lee, Jeff; Fisker, Eli; Kosaraju, Vineet; Wu, Michelle; Kong, Justin; Lee, Jeehyung; Lee, Minjae; Zada, Mathew; Treuille, Adrien; Das, Rhiju

2016-02-27

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Construction Strategy for an Internal Amplification Control for Real-Time Diagnostic Assays Using Nucleic Acid Sequence-Based Amplification: Development and Clinical Application

PubMed Central

Rodríguez-Lázaro, David; D'Agostino, Martin; Pla, Maria; Cook, Nigel

2004-01-01

An important analytical control in molecular amplification-based methods is an internal amplification control (IAC), which should be included in each reaction mixture. An IAC is a nontarget nucleic acid sequence which is coamplified simultaneously with the target sequence. With negative results for the target nucleic acid, the absence of an IAC signal indicates that amplification has failed. A general strategy for the construction of an IAC for inclusion in molecular beacon-based real-time nucleic acid sequence-based amplification (NASBA) assays is presented. Construction proceeds in two phases. In the first phase, a double-stranded DNA molecule that contains nontarget sequences flanked by target sequences complementary to the NASBA primers is produced. At the 5′ end of this DNA molecule is a T7 RNA polymerase binding sequence. In the second phase of construction, RNA transcripts are produced from the DNA by T7 RNA polymerase. This RNA is the IAC; it is amplified by the target NASBA primers and is detected by a molecular beacon probe complementary to the internal nontarget sequences. As a practical example, an IAC for use in an assay for the detection of Mycobacterium avium subsp. paratuberculosis is described, its incorporation and optimization within the assay are detailed, and its application to spiked and natural clinical samples is shown to illustrate the correct interpretation of the diagnostic results. PMID:15583319

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

PubMed

Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

2010-01-01

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

An efficient and sensitive method for preparing cDNA libraries from scarce biological samples

PubMed Central

Sterling, Catherine H.; Veksler-Lublinsky, Isana; Ambros, Victor

2015-01-01

The preparation and high-throughput sequencing of cDNA libraries from samples of small RNA is a powerful tool to quantify known small RNAs (such as microRNAs) and to discover novel RNA species. Interest in identifying the small RNA repertoire present in tissues and in biofluids has grown substantially with the findings that small RNAs can serve as indicators of biological conditions and disease states. Here we describe a novel and straightforward method to clone cDNA libraries from small quantities of input RNA. This method permits the generation of cDNA libraries from sub-picogram quantities of RNA robustly, efficiently and reproducibly. We demonstrate that the method provides a significant improvement in sensitivity compared to previous cloning methods while maintaining reproducible identification of diverse small RNA species. This method should have widespread applications in a variety of contexts, including biomarker discovery from scarce samples of human tissue or body fluids. PMID:25056322

Primer and platform effects on 16S rRNA tag sequencing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tremblay, Julien; Singh, Kanwar; Fern, Alison

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as wellmore » as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. In conclusion, beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.« less

Primer and platform effects on 16S rRNA tag sequencing

DOE PAGES

Tremblay, Julien; Singh, Kanwar; Fern, Alison; ...

2015-08-04

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as wellmore » as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. In conclusion, beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.« less

Secondary structural entropy in RNA switch (Riboswitch) identification.

PubMed

Manzourolajdad, Amirhossein; Arnold, Jonathan

2015-04-28

RNA regulatory elements play a significant role in gene regulation. Riboswitches, a widespread group of regulatory RNAs, are vital components of many bacterial genomes. These regulatory elements generally function by forming a ligand-induced alternative fold that controls access to ribosome binding sites or other regulatory sites in RNA. Riboswitch-mediated mechanisms are ubiquitous across bacterial genomes. A typical class of riboswitch has its own unique structural and biological complexity, making de novo riboswitch identification a formidable task. Traditionally, riboswitches have been identified through comparative genomics based on sequence and structural homology. The limitations of structural-homology-based approaches, coupled with the assumption that there is a great diversity of undiscovered riboswitches, suggests the need for alternative methods for riboswitch identification, possibly based on features intrinsic to their structure. As of yet, no such reliable method has been proposed. We used structural entropy of riboswitch sequences as a measure of their secondary structural dynamics. Entropy values of a diverse set of riboswitches were compared to that of their mutants, their dinucleotide shuffles, and their reverse complement sequences under different stochastic context-free grammar folding models. Significance of our results was evaluated by comparison to other approaches, such as the base-pairing entropy and energy landscapes dynamics. Classifiers based on structural entropy optimized via sequence and structural features were devised as riboswitch identifiers and tested on Bacillus subtilis, Escherichia coli, and Synechococcus elongatus as an exploration of structural entropy based approaches. The unusually long untranslated region of the cotH in Bacillus subtilis, as well as upstream regions of certain genes, such as the sucC genes were associated with significant structural entropy values in genome-wide examinations. Various tests show that there is in fact a relationship between higher structural entropy and the potential for the RNA sequence to have alternative structures, within the limitations of our methodology. This relationship, though modest, is consistent across various tests. Understanding the behavior of structural entropy as a fairly new feature for RNA conformational dynamics, however, may require extensive exploratory investigation both across RNA sequences and folding models.

SPAR: small RNA-seq portal for analysis of sequencing experiments.

PubMed

Kuksa, Pavel P; Amlie-Wolf, Alexandre; Katanic, Živadin; Valladares, Otto; Wang, Li-San; Leung, Yuk Yee

2018-05-04

The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data. SPAR is freely available at https://www.lisanwanglab.org/SPAR.

Microbial community profiling of fresh basil and pitfalls in taxonomic assignment of enterobacterial pathogenic species based upon 16S rRNA amplicon sequencing.

PubMed

Ceuppens, Siele; De Coninck, Dieter; Bottledoorn, Nadine; Van Nieuwerburgh, Filip; Uyttendaele, Mieke

2017-09-18

Application of 16S rRNA (gene) amplicon sequencing on food samples is increasingly applied for assessing microbial diversity but may as unintended advantage also enable simultaneous detection of any human pathogens without a priori definition. In the present study high-throughput next-generation sequencing (NGS) of the V1-V2-V3 regions of the 16S rRNA gene was applied to identify the bacteria present on fresh basil leaves. However, results were strongly impacted by variations in the bioinformatics analysis pipelines (MEGAN, SILVAngs, QIIME and MG-RAST), including the database choice (Greengenes, RDP and M5RNA) and the annotation algorithm (best hit, representative hit and lowest common ancestor). The use of pipelines with default parameters will lead to discrepancies. The estimate of microbial diversity of fresh basil using 16S rRNA (gene) amplicon sequencing is thus indicative but subject to biases. Salmonella enterica was detected at low frequencies, between 0.1% and 0.4% of bacterial sequences, corresponding with 37 to 166 reads. However, this result was dependent upon the pipeline used: Salmonella was detected by MEGAN, SILVAngs and MG-RAST, but not by QIIME. Confirmation of Salmonella sequences by real-time PCR was unsuccessful. It was shown that taxonomic resolution obtained from the short (500bp) sequence reads of the 16S rRNA gene containing the hypervariable regions V1-V3 cannot allow distinction of Salmonella with closely related enterobacterial species. In conclusion 16S amplicon sequencing, getting the status of standard method in microbial ecology studies of foods, needs expertise on both bioinformatics and microbiology for analysis of results. It is a powerful tool to estimate bacterial diversity but amenable to biases. Limitations concerning taxonomic resolution for some bacterial species or its inability to detect sub-dominant (pathogenic) species should be acknowledged in order to avoid overinterpretation of results. Copyright © 2017 Elsevier B.V. All rights reserved.

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing.

PubMed

Jäger, Marten; Ott, Claus-Eric; Grünhagen, Johannes; Hecht, Jochen; Schell, Hanna; Mundlos, Stefan; Duda, Georg N; Robinson, Peter N; Lienau, Jasmin

2011-03-24

The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism.

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing

PubMed Central

2011-01-01

Background The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Results Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Conclusions Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism. PMID:21435219

Quantification of Functionalised Gold Nanoparticle-Targeted Knockdown of Gene Expression in HeLa Cells

PubMed Central

Jiwaji, Meesbah; Sandison, Mairi E.; Reboud, Julien; Stevenson, Ross; Daly, Rónán; Barkess, Gráinne; Faulds, Karen; Kolch, Walter; Graham, Duncan; Girolami, Mark A.; Cooper, Jonathan M.; Pitt, Andrew R.

2014-01-01

Introduction Gene therapy continues to grow as an important area of research, primarily because of its potential in the treatment of disease. One significant area where there is a need for better understanding is in improving the efficiency of oligonucleotide delivery to the cell and indeed, following delivery, the characterization of the effects on the cell. Methods In this report, we compare different transfection reagents as delivery vehicles for gold nanoparticles functionalized with DNA oligonucleotides, and quantify their relative transfection efficiencies. The inhibitory properties of small interfering RNA (siRNA), single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA) sequences targeted to human metallothionein hMT-IIa are also quantified in HeLa cells. Techniques used in this study include fluorescence and confocal microscopy, qPCR and Western analysis. Findings We show that the use of transfection reagents does significantly increase nanoparticle transfection efficiencies. Furthermore, siRNA, ssRNA and ssDNA sequences all have comparable inhibitory properties to ssDNA sequences immobilized onto gold nanoparticles. We also show that functionalized gold nanoparticles can co-localize with autophagosomes and illustrate other factors that can affect data collection and interpretation when performing studies with functionalized nanoparticles. Conclusions The desired outcome for biological knockdown studies is the efficient reduction of a specific target; which we demonstrate by using ssDNA inhibitory sequences targeted to human metallothionein IIa gene transcripts that result in the knockdown of both the mRNA transcript and the target protein. PMID:24926959

Fluorescence turn-on detection of target sequence DNA based on silicon nanodot-mediated quenching.

PubMed

Zhang, Yanan; Ning, Xinping; Mao, Guobin; Ji, Xinghu; He, Zhike

2018-05-01

We have developed a new enzyme-free method for target sequence DNA detection based on the dynamic quenching of fluorescent silicon nanodots (SiNDs) toward Cy5-tagged DNA probe. Fascinatingly, the water-soluble SiNDs can quench the fluorescence of cyanine (Cy5) in Cy5-tagged DNA probe in homogeneous solution, and the fluorescence of Cy5-tagged DNA probe can be restored in the presence of target sequence DNA (the synthetic target miRNA-27a). Based on this phenomenon, a SiND-featured fluorescent sensor has been constructed for "turn-on" detection of the synthetic target miRNA-27a for the first time. This newly developed approach possesses the merits of low cost, simple design, and convenient operation since no enzymatic reaction, toxic reagents, or separation procedures are involved. The established method achieves a detection limit of 0.16 nM, and the relative standard deviation of this method is 9% (1 nM, n = 5). The linear range is 0.5-20 nM, and the recoveries in spiked human fluids are in the range of 90-122%. This protocol provides a new tactic in the development of the nonenzymic miRNA biosensors and opens a promising avenue for early diagnosis of miRNA-associated disease. Graphical abstract The SiND-based fluorescent sensor for detection of S-miR-27a.

RNA motif search with data-driven element ordering.

PubMed

Rampášek, Ladislav; Jimenez, Randi M; Lupták, Andrej; Vinař, Tomáš; Brejová, Broňa

2016-05-18

In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms. We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools. We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http://compbio.fmph.uniba.sk/rnarobo .

Species-specific identification of Dekkera/Brettanomyces yeasts by fluorescently labeled DNA probes targeting the 26S rRNA.

PubMed

Röder, Christoph; König, Helmut; Fröhlich, Jürgen

2007-09-01

Sequencing of the complete 26S rRNA genes of all Dekkera/Brettanomyces species colonizing different beverages revealed the potential for a specific primer and probe design to support diagnostic PCR approaches and FISH. By analysis of the complete 26S rRNA genes of all five currently known Dekkera/Brettanomyces species (Dekkera bruxellensis, D. anomala, Brettanomyces custersianus, B. nanus and B. naardenensis), several regions with high nucleotide sequence variability yet distinct from the D1/D2 domains were identified. FISH species-specific probes targeting the 26S rRNA gene's most variable regions were designed. Accessibility of probe targets for hybridization was facilitated by the construction of partially complementary 'side'-labeled probes, based on secondary structure models of the rRNA sequences. The specificity and routine applicability of the FISH-based method for yeast identification were tested by analyzing different wine isolates. Investigation of the prevalence of Dekkera/Brettanomyces yeasts in the German viticultural regions Wonnegau, Nierstein and Bingen (Rhinehesse, Rhineland-Palatinate) resulted in the isolation of 37 D. bruxellensis strains from 291 wine samples.

Consistent global structures of complex RNA states through multidimensional chemical mapping

PubMed Central

Cheng, Clarence Yu; Chou, Fang-Chieh; Kladwang, Wipapat; Tian, Siqi; Cordero, Pablo; Das, Rhiju

2015-01-01

Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis. Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions. We report that integrating a new method called MOHCA-seq (Multiplexed •OH Cleavage Analysis with paired-end sequencing) with mutate-and-map secondary structure inference guides Rosetta 3D modeling to consistent 1-nm accuracy for intricately folded ncRNAs with lengths up to 188 nucleotides, including a blind RNA-puzzle challenge, the lariat-capping ribozyme. This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon. MCM offers a sequencing-based route to uncovering ncRNA 3D structure, applicable to functionally important but potentially heterogeneous states. DOI: http://dx.doi.org/10.7554/eLife.07600.001 PMID:26035425

Comparing viral metagenomics methods using a highly multiplexed human viral pathogens reagent

PubMed Central

Li, Linlin; Deng, Xutao; Mee, Edward T.; Collot-Teixeira, Sophie; Anderson, Rob; Schepelmann, Silke; Minor, Philip D.; Delwart, Eric

2014-01-01

Unbiased metagenomic sequencing holds significant potential as a diagnostic tool for the simultaneous detection of any previously genetically described viral nucleic acids in clinical samples. Viral genome sequences can also inform on likely phenotypes including drug susceptibility or neutralization serotypes. In this study, different variables of the laboratory methods often used to generate viral metagenomics libraries on the efficiency of viral detection and virus genome coverage were compared. A biological reagent consisting of 25 different human RNA and DNA viral pathogens was used to estimate the effect of filtration and nuclease digestion, DNA/RNA extraction methods, pre-amplification and the use of different library preparation kits on the detection of viral nucleic acids. Filtration and nuclease treatment led to slight decreases in the percentage of viral sequence reads and number of viruses detected. For nucleic acid extractions silica spin columns improved viral sequence recovery relative to magnetic beads and Trizol extraction. Pre-amplification using random RT-PCR while generating more viral sequence reads resulted in detection of fewer viruses, more overlapping sequences, and lower genome coverage. The ScriptSeq library preparation method retrieved more viruses and a greater fraction of their genomes than the TruSeq and Nextera methods. Viral metagenomics sequencing was able to simultaneously detect up to 22 different viruses in the biological reagent analyzed including all those detected by qPCR. Further optimization will be required for the detection of viruses in biologically more complex samples such as tissues, blood, or feces. PMID:25497414

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.

PubMed

Logan, Grace; Freimanis, Graham L; King, David J; Valdazo-González, Begoña; Bachanek-Bankowska, Katarzyna; Sanderson, Nicholas D; Knowles, Nick J; King, Donald P; Cottam, Eleanor M

2014-09-30

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. 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. 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.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase.

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Finding specific RNA motifs: Function in a zeptomole world?

PubMed Central

KNIGHT, ROB; YARUS, MICHAEL

2003-01-01

We have developed a new method for estimating the abundance of any modular (piecewise) RNA motif within a longer random region. We have used this method to estimate the size of the active motifs available to modern SELEX experiments (picomoles of unique sequences) and to a plausible RNA World (zeptomoles of unique sequences: 1 zmole = 602 sequences). Unexpectedly, activities such as specific isoleucine binding are almost certainly present in zeptomoles of molecules, and even ribozymes such as self-cleavage motifs may appear (depending on assumptions about the minimal structures). The number of specified nucleotides is not the only important determinant of a motif’s rarity: The number of modules into which it is divided, and the details of this division, are also crucial. We propose three maxims for easily isolated motifs: the Maxim of Minimization, the Maxim of Multiplicity, and the Maxim of the Median. These maxims together state that selected motifs should be small and composed of as many separate, equally sized modules as possible. For evenly divided motifs with four modules, the largest accessible activity in picomole scale (1–1000 pmole) pools of length 100 is about 34 nucleotides; while for zeptomole scale (1–1000 zmole) pools it is about 20 specific nucleotides (50% probability of occurrence). This latter figure includes some ribozymes and aptamers. Consequently, an RNA metabolism apparently could have begun with only zeptomoles of RNA molecules. PMID:12554865

New support vector machine-based method for microRNA target prediction.

PubMed

Li, L; Gao, Q; Mao, X; Cao, Y

2014-06-09

MicroRNA (miRNA) plays important roles in cell differentiation, proliferation, growth, mobility, and apoptosis. An accurate list of precise target genes is necessary in order to fully understand the importance of miRNAs in animal development and disease. Several computational methods have been proposed for miRNA target-gene identification. However, these methods still have limitations with respect to their sensitivity and accuracy. Thus, we developed a new miRNA target-prediction method based on the support vector machine (SVM) model. The model supplies information of two binding sites (primary and secondary) for a radial basis function kernel as a similarity measure for SVM features. The information is categorized based on structural, thermodynamic, and sequence conservation. Using high-confidence datasets selected from public miRNA target databases, we obtained a human miRNA target SVM classifier model with high performance and provided an efficient tool for human miRNA target gene identification. Experiments have shown that our method is a reliable tool for miRNA target-gene prediction, and a successful application of an SVM classifier. Compared with other methods, the method proposed here improves the sensitivity and accuracy of miRNA prediction. Its performance can be further improved by providing more training examples.

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

PubMed

Li, Guang-Qing; Liu, Zi; Shen, Hong-Bin; Yu, Dong-Jun

2016-10-01

As one of the most ubiquitous post-transcriptional modifications of RNA, N 6 -methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons

PubMed Central

Krishnaswami, Suguna Rani; Grindberg, Rashel V; Novotny, Mark; Venepally, Pratap; Lacar, Benjamin; Bhutani, Kunal; Linker, Sara B; Pham, Son; Erwin, Jennifer A; Miller, Jeremy A; Hodge, Rebecca; McCarthy, James K; Kelder, Martin; McCorrison, Jamison; Aevermann, Brian D; Fuertes, Francisco Diez; Scheuermann, Richard H; Lee, Jun; Lein, Ed S; Schork, Nicholas; McConnell, Michael J; Gage, Fred H; Lasken, Roger S

2016-01-01

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing. PMID:26890679

Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.

PubMed

Liu, Xuejun; Shi, Xinxin; Chen, Chunlin; Zhang, Li

2015-10-16

The high-throughput sequencing technology, RNA-Seq, has been widely used to quantify gene and isoform expression in the study of transcriptome in recent years. Accurate expression measurement from the millions or billions of short generated reads is obstructed by difficulties. One is ambiguous mapping of reads to reference transcriptome caused by alternative splicing. This increases the uncertainty in estimating isoform expression. The other is non-uniformity of read distribution along the reference transcriptome due to positional, sequencing, mappability and other undiscovered sources of biases. This violates the uniform assumption of read distribution for many expression calculation approaches, such as the direct RPKM calculation and Poisson-based models. Many methods have been proposed to address these difficulties. Some approaches employ latent variable models to discover the underlying pattern of read sequencing. However, most of these methods make bias correction based on surrounding sequence contents and share the bias models by all genes. They therefore cannot estimate gene- and isoform-specific biases as revealed by recent studies. We propose a latent variable model, NLDMseq, to estimate gene and isoform expression. Our method adopts latent variables to model the unknown isoforms, from which reads originate, and the underlying percentage of multiple spliced variants. The isoform- and exon-specific read sequencing biases are modeled to account for the non-uniformity of read distribution, and are identified by utilizing the replicate information of multiple lanes of a single library run. We employ simulation and real data to verify the performance of our method in terms of accuracy in the calculation of gene and isoform expression. Results show that NLDMseq obtains competitive gene and isoform expression compared to popular alternatives. Finally, the proposed method is applied to the detection of differential expression (DE) to show its usefulness in the downstream analysis. The proposed NLDMseq method provides an approach to accurately estimate gene and isoform expression from RNA-Seq data by modeling the isoform- and exon-specific read sequencing biases. It makes use of a latent variable model to discover the hidden pattern of read sequencing. We have shown that it works well in both simulations and real datasets, and has competitive performance compared to popular methods. The method has been implemented as a freely available software which can be found at https://github.com/PUGEA/NLDMseq.

SearchSmallRNA: a graphical interface tool for the assemblage of viral genomes using small RNA libraries data

PubMed Central

2014-01-01

Background Next-generation parallel sequencing (NGS) allows the identification of viral pathogens by sequencing the small RNAs of infected hosts. Thus, viral genomes may be assembled from host immune response products without prior virus enrichment, amplification or purification. However, mapping of the vast information obtained presents a bioinformatics challenge. Methods In order to by pass the need of line command and basic bioinformatics knowledge, we develop a mapping software with a graphical interface to the assemblage of viral genomes from small RNA dataset obtained by NGS. SearchSmallRNA was developed in JAVA language version 7 using NetBeans IDE 7.1 software. The program also allows the analysis of the viral small interfering RNAs (vsRNAs) profile; providing an overview of the size distribution and other features of the vsRNAs produced in infected cells. Results The program performs comparisons between each read sequenced present in a library and a chosen reference genome. Reads showing Hamming distances smaller or equal to an allowed mismatched will be selected as positives and used to the assemblage of a long nucleotide genome sequence. In order to validate the software, distinct analysis using NGS dataset obtained from HIV and two plant viruses were used to reconstruct viral whole genomes. Conclusions SearchSmallRNA program was able to reconstructed viral genomes using NGS of small RNA dataset with high degree of reliability so it will be a valuable tool for viruses sequencing and discovery. It is accessible and free to all research communities and has the advantage to have an easy-to-use graphical interface. Availability and implementation SearchSmallRNA was written in Java and is freely available at http://www.microbiologia.ufrj.br/ssrna/. PMID:24607237

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing

PubMed Central

Salehi, Abdolreza; Rivera, Rocío Melissa

2018-01-01

RNA editing increases the diversity of the transcriptome and proteome. Adenosine-to-inosine (A-to-I) editing is the predominant type of RNA editing in mammals and it is catalyzed by the adenosine deaminases acting on RNA (ADARs) family. Here, we used a largescale computational analysis of transcriptomic data from brain, heart, colon, lung, spleen, kidney, testes, skeletal muscle and liver, from three adult animals in order to identify RNA editing sites in bovine. We developed a computational pipeline and used a rigorous strategy to identify novel editing sites from RNA-Seq data in the absence of corresponding DNA sequence information. Our methods take into account sequencing errors, mapping bias, as well as biological replication to reduce the probability of obtaining a false-positive result. We conducted a detailed characterization of sequence and structural features related to novel candidate sites and found 1,600 novel canonical A-to-I editing sites in the nine bovine tissues analyzed. Results show that these sites 1) occur frequently in clusters and short interspersed nuclear elements (SINE) repeats, 2) have a preference for guanines depletion/enrichment in the flanking 5′/3′ nucleotide, 3) occur less often in coding sequences than other regions of the genome, and 4) have low evolutionary conservation. Further, we found that a positive correlation exists between expression of ADAR family members and tissue-specific RNA editing. Most of the genes with predicted A-to-I editing in each tissue were significantly enriched in biological terms relevant to the function of the corresponding tissue. Lastly, the results highlight the importance of the RNA editome in nervous system regulation. The present study extends the list of RNA editing sites in bovine and provides pipelines that may be used to investigate the editome in other organisms. PMID:29470549

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.

The tmRNA website

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudson, Corey M.; Williams, Kelly P.

We report that the transfer-messenger RNA (tmRNA) and its partner protein SmpB act together in resolving problems arising when translating bacterial ribosomes reach the end of mRNA with no stop codon. Their genes have been found in nearly all bacterial genomes and in some organelles. The tmRNA Website serves tmRNA sequences, alignments and feature annotations, and has recently moved to http: //bioinformatics.sandia.gov/tmrna/. New features include software used to find the sequences, an update raising the number of unique tmRNA sequences from 492 to 1716, and a database of SmpB sequences which are served along with the tmRNA sequence from themore » same organism.« less

The tmRNA website

DOE PAGES

Hudson, Corey M.; Williams, Kelly P.

2014-11-05

We report that the transfer-messenger RNA (tmRNA) and its partner protein SmpB act together in resolving problems arising when translating bacterial ribosomes reach the end of mRNA with no stop codon. Their genes have been found in nearly all bacterial genomes and in some organelles. The tmRNA Website serves tmRNA sequences, alignments and feature annotations, and has recently moved to http: //bioinformatics.sandia.gov/tmrna/. New features include software used to find the sequences, an update raising the number of unique tmRNA sequences from 492 to 1716, and a database of SmpB sequences which are served along with the tmRNA sequence from themore » same organism.« less

SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.

PubMed

Wang, Tianyu; Nabavi, Sheida

2018-04-24

Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote the development of new methods for identifying differentially expressed (DE) genes. In this study, we proposed a new method, SigEMD, that combines a data imputation approach, a logistic regression model and a nonparametric method based on the Earth Mover's Distance, to precisely and efficiently identify DE genes in scRNAseq data. The regression model and data imputation are used to reduce the impact of large amounts of zero counts, and the nonparametric method is used to improve the sensitivity of detecting DE genes from multimodal scRNAseq data. By additionally employing gene interaction network information to adjust the final states of DE genes, we further reduce the false positives of calling DE genes. We used simulated datasets and real datasets to evaluate the detection accuracy of the proposed method and to compare its performance with those of other differential expression analysis methods. Results indicate that the proposed method has an overall powerful performance in terms of precision in detection, sensitivity, and specificity. Copyright © 2018 Elsevier Inc. All rights reserved.

iRNA-2methyl: Identify RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier.

PubMed

Qiu, Wang-Ren; Jiang, Shi-Yu; Sun, Bi-Qian; Xiao, Xuan; Cheng, Xiang; Chou, Kuo-Chen

2017-01-01

Being a kind of post-transcriptional modification (PTCM) in RNA, the 2'-Omethylation modification occurs in the processes of life development and disease formation as well. Accordingly, from the angles of both basic research and drug development, we are facing a challenging problem: given an uncharacterized RNA sequence formed by many nucleotides of A (adenine), C (cytosine), G (guanine), and U (uracil), which one can be of 2-O'-methylation modification, and which one cannot? Unfortunately, so far no computational method whatsoever has been developed to address such a problem. To fill this empty area, we propose a predictor called iRNA-2methyl. It is formed by incorporating a series of sequence-coupled factors into the general PseKNC (pseudo nucleotide composition), followed by fusing 12 basic random forest classifier into four ensemble predictors, with each aimed to identify the cases of A, C, G, and U along the RNA sequence concerned, respectively. Rigorous jackknife cross-validations have indicated that the success rates are very high (>93%). For the convenience of most experimental scientists, a user-friendly web-server for iRNA-2methyl has been established at http://www.jci-bioinfo.cn/iRNA-2methyl, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. The proposed predictor iRNA-2methyl will become a very useful bioinformatics tool for medicinal chemistry, helping to design effective drugs against the diseases related to the 2'-Omethylation modification. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Ribosomal RNA sequence suggest microsporidia are extremely ancient eukaryotes

NASA Technical Reports Server (NTRS)

Vossbrinck, C. R.; Maddox, J. V.; Friedman, S.; Debrunner-Vossbrinck, B. A.; Woese, C. R.

1987-01-01

A comparative sequence analysis of the 18S small subunit ribosomal RNA (rRNA) of the microsporidium Vairimorpha necatrix is presented. The results show that this rRNA sequence is more unlike those of other eukaryotes than any known eukaryote rRNA sequence. It is concluded that the lineage leading to microsporidia branched very early from that leading to other eukaryotes.

A Universal Next-Generation Sequencing Protocol To Generate Noninfectious Barcoded cDNA Libraries from High-Containment RNA Viruses

PubMed Central

Moser, Lindsey A.; Ramirez-Carvajal, Lisbeth; Puri, Vinita; Pauszek, Steven J.; Matthews, Krystal; Dilley, Kari A.; Mullan, Clancy; McGraw, Jennifer; Khayat, Michael; Beeri, Karen; Yee, Anthony; Dugan, Vivien; Heise, Mark T.; Frieman, Matthew B.; Rodriguez, Luis L.; Bernard, Kristen A.; Wentworth, David E.

2016-01-01

ABSTRACT Several biosafety level 3 and/or 4 (BSL-3/4) pathogens are high-consequence, single-stranded RNA viruses, and their genomes, when introduced into permissive cells, are infectious. Moreover, many of these viruses are select agents (SAs), and their genomes are also considered SAs. For this reason, cDNAs and/or their derivatives must be tested to ensure the absence of infectious virus and/or viral RNA before transfer out of the BSL-3/4 and/or SA laboratory. This tremendously limits the capacity to conduct viral genomic research, particularly the application of next-generation sequencing (NGS). Here, we present a sequence-independent method to rapidly amplify viral genomic RNA while simultaneously abolishing both viral and genomic RNA infectivity across multiple single-stranded positive-sense RNA (ssRNA+) virus families. The process generates barcoded DNA amplicons that range in length from 300 to 1,000 bp, which cannot be used to rescue a virus and are stable to transport at room temperature. Our barcoding approach allows for up to 288 barcoded samples to be pooled into a single library and run across various NGS platforms without potential reconstitution of the viral genome. Our data demonstrate that this approach provides full-length genomic sequence information not only from high-titer virion preparations but it can also recover specific viral sequence from samples with limited starting material in the background of cellular RNA, and it can be used to identify pathogens from unknown samples. In summary, we describe a rapid, universal standard operating procedure that generates high-quality NGS libraries free of infectious virus and infectious viral RNA. IMPORTANCE This report establishes and validates a standard operating procedure (SOP) for select agents (SAs) and other biosafety level 3 and/or 4 (BSL-3/4) RNA viruses to rapidly generate noninfectious, barcoded cDNA amenable for next-generation sequencing (NGS). This eliminates the burden of testing all processed samples derived from high-consequence pathogens prior to transfer from high-containment laboratories to lower-containment facilities for sequencing. Our established protocol can be scaled up for high-throughput sequencing of hundreds of samples simultaneously, which can dramatically reduce the cost and effort required for NGS library construction. NGS data from this SOP can provide complete genome coverage from viral stocks and can also detect virus-specific reads from limited starting material. Our data suggest that the procedure can be implemented and easily validated by institutional biosafety committees across research laboratories. PMID:27822536

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

PubMed

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-08-01

RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.

Equally parsimonious pathways through an RNA sequence space are not equally likely

NASA Technical Reports Server (NTRS)

Lee, Y. H.; DSouza, L. M.; Fox, G. E.

1997-01-01

An experimental system for determining the potential ability of sequences resembling 5S ribosomal RNA (rRNA) to perform as functional 5S rRNAs in vivo in the Escherichia coli cellular environment was devised previously. Presumably, the only 5S rRNA sequences that would have been fixed by ancestral populations are ones that were functionally valid, and hence the actual historical paths taken through RNA sequence space during 5S rRNA evolution would have most likely utilized valid sequences. Herein, we examine the potential validity of all sequence intermediates along alternative equally parsimonious trajectories through RNA sequence space which connect two pairs of sequences that had previously been shown to behave as valid 5S rRNAs in E. coli. The first trajectory requires a total of four changes. The 14 sequence intermediates provide 24 apparently equally parsimonious paths by which the transition could occur. The second trajectory involves three changes, six intermediate sequences, and six potentially equally parsimonious paths. In total, only eight of the 20 sequence intermediates were found to be clearly invalid. As a consequence of the position of these invalid intermediates in the sequence space, seven of the 30 possible paths consisted of exclusively valid sequences. In several cases, the apparent validity/invalidity of the intermediate sequences could not be anticipated on the basis of current knowledge of the 5S rRNA structure. This suggests that the interdependencies in RNA sequence space may be more complex than currently appreciated. If ancestral sequences predicted by parsimony are to be regarded as actual historical sequences, then the present results would suggest that they should also satisfy a validity requirement and that, in at least limited cases, this conjecture can be tested experimentally.

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

NASA Astrophysics Data System (ADS)

Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Microfluidic single-cell whole-transcriptome sequencing.

PubMed

Streets, Aaron M; Zhang, Xiannian; Cao, Chen; Pang, Yuhong; Wu, Xinglong; Xiong, Liang; Yang, Lu; Fu, Yusi; Zhao, Liang; Tang, Fuchou; Huang, Yanyi

2014-05-13

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.

An enzyme free electrochemical biosensor for sensitive detection of miRNA with a high discrimination factor by coupling the strand displacement reaction and catalytic hairpin assembly recycling.

PubMed

Yao, Juan; Zhang, Zhang; Deng, Zhenghua; Wang, Youqiang; Guo, Yongcan

2017-10-23

An isothermal, enzyme free, ultra-specific and ultra-sensitive protocol for electrochemical detection of miRNAs is proposed based on the toehold-mediated strand displacement reaction (SDR) and non-enzymatic catalytic hairpin reaction (CHA) recycling. The SDR was first triggered only in the presence of target miRNA and this process also affects other miRNA interferences having similar target sequences, thus guaranteeing a high discrimination factor and could be used in rare content miRNA detection with various amounts of interferences having similar target sequences. The output protector strand then triggered enzyme free CHA amplification and generates plenty of hairpin self-assembly products. This process in turn influences SDR equilibrium to move to the right and generates large amounts of protector output to ensure analysis sensitivity. Compared with traditional CHA, our proposed method greatly improved the signal to noise ratio and shows excellent performance in rare miRNA detection with miRNA analogue interference. Under the optimal experimental conditions and using square wave voltammetry, the established biosensor could detect target miRNA-21 down to 30 fM (S/N = 3) with a dynamic range from 100 fM to 2 nM, and discriminate rare target miRNA-21 from mismatched miRNA with high selectivity. This method holds great promise in miRNA detection from human cancer cell lines and would be a versatile and powerful tool for clinical molecular diagnostics.

TAM: a method for enrichment and depletion analysis of a microRNA category in a list of microRNAs.

PubMed

Lu, Ming; Shi, Bing; Wang, Juan; Cao, Qun; Cui, Qinghua

2010-08-09

MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing). For the above purpose, this study presents a method and develops a tool (TAM) for annotations of meaningful human miRNAs categories. We first integrated miRNAs into various meaningful categories according to prior knowledge, such as miRNA family, miRNA cluster, miRNA function, miRNA associated diseases, and tissue specificity. Using TAM, given lists of miRNAs can be rapidly annotated and summarized according to the integrated miRNA categorical data. Moreover, given a list of miRNAs, TAM can be used to predict novel related miRNAs. Finally, we confirmed the usefulness and reliability of TAM by applying it to deregulated miRNAs in acute myocardial infarction (AMI) from two independent experiments. TAM can efficiently identify meaningful categories for given miRNAs. In addition, TAM can be used to identify novel miRNA biomarkers. TAM tool, source codes, and miRNA category data are freely available at http://cmbi.bjmu.edu.cn/tam.

RnaSeqSampleSize: real data based sample size estimation for RNA sequencing.

PubMed

Zhao, Shilin; Li, Chung-I; Guo, Yan; Sheng, Quanhu; Shyr, Yu

2018-05-30

One of the most important and often neglected components of a successful RNA sequencing (RNA-Seq) experiment is sample size estimation. A few negative binomial model-based methods have been developed to estimate sample size based on the parameters of a single gene. However, thousands of genes are quantified and tested for differential expression simultaneously in RNA-Seq experiments. Thus, additional issues should be carefully addressed, including the false discovery rate for multiple statistic tests, widely distributed read counts and dispersions for different genes. To solve these issues, we developed a sample size and power estimation method named RnaSeqSampleSize, based on the distributions of gene average read counts and dispersions estimated from real RNA-seq data. Datasets from previous, similar experiments such as the Cancer Genome Atlas (TCGA) can be used as a point of reference. Read counts and their dispersions were estimated from the reference's distribution; using that information, we estimated and summarized the power and sample size. RnaSeqSampleSize is implemented in R language and can be installed from Bioconductor website. A user friendly web graphic interface is provided at http://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/ . RnaSeqSampleSize provides a convenient and powerful way for power and sample size estimation for an RNAseq experiment. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

Integrating De Novo Transcriptome Assembly and Cloning to Obtain Chicken Ovocleidin-17 Full-Length cDNA

PubMed Central

Ning, ZhongHua; Hincke, Maxwell T.; Yang, Ning; Hou, ZhuoCheng

2014-01-01

Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not ‘finished’. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences. PMID:24676480

Integrating de novo transcriptome assembly and cloning to obtain chicken Ovocleidin-17 full-length cDNA.

PubMed

Zhang, Quan; Liu, Long; Zhu, Feng; Ning, ZhongHua; Hincke, Maxwell T; Yang, Ning; Hou, ZhuoCheng

2014-01-01

Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not 'finished'. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences.

Computational biology of RNA interactions.

PubMed

Dieterich, Christoph; Stadler, Peter F

2013-01-01

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments. Copyright © 2012 John Wiley & Sons, Ltd.

The Human Microbiome and Understanding the 16S rRNA Gene in Translational Nursing Science

PubMed Central

Ames, Nancy J.; Ranucci, Alexandra; Moriyama, Brad; Wallen, Gwenyth R.

2017-01-01

Background As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and health care practitioners to analyze these microbial communities and their role in health and disease.16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings. Objectives The objectives of this review are to: (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science. Discussion Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists—individuals uniquely positioned to utilize these techniques in future studies in clinical settings. PMID:28252578

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing

PubMed Central

Tourlousse, Dieter M.; Yoshiike, Satowa; Ohashi, Akiko; Matsukura, Satoko; Noda, Naohiro

2017-01-01

Abstract High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible identity to known nucleotide sequences, permitting unambiguous identification of spike-in sequences in 16S-seq read data from any microbiome sample. Using defined mock communities and environmental microbiota, we characterized the performance of the spike-in standards and demonstrated their utility for evaluating data quality on a per-sample basis. Further, we showed that staggered spike-in mixtures added at the point of DNA extraction enable concurrent estimation of absolute microbial abundances suitable for comparative analysis. Results also underscored that template-specific Illumina sequencing artifacts may lead to biases in the perceived abundance of certain taxa. Taken together, the spike-in standards represent a novel bioanalytical tool that can substantially improve 16S-seq-based microbiome studies by enabling comprehensive quality control along with absolute quantification. PMID:27980100

Distributed biotin–streptavidin transcription roadblocks for mapping cotranscriptional RNA folding

PubMed Central

Strobel, Eric J.; Nedialkov, Yuri; Artsimovitch, Irina

2017-01-01

Abstract RNA folding during transcription directs an order of folding that can determine RNA structure and function. However, the experimental study of cotranscriptional RNA folding has been limited by the lack of easily approachable methods that can interrogate nascent RNA structure at nucleotide resolution. To address this, we previously developed cotranscriptional selective 2΄-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) to simultaneously probe all intermediate RNA transcripts during transcription by stalling elongation complexes at catalytically dead EcoRIE111Q roadblocks. While effective, the distribution of elongation complexes using EcoRIE111Q requires laborious PCR using many different oligonucleotides for each sequence analyzed. Here, we improve the broad applicability of cotranscriptional SHAPE-Seq by developing a sequence-independent biotin–streptavidin (SAv) roadblocking strategy that simplifies the preparation of roadblocking DNA templates. We first determine the properties of biotin–SAv roadblocks. We then show that randomly distributed biotin–SAv roadblocks can be used in cotranscriptional SHAPE-Seq experiments to identify the same RNA structural transitions related to a riboswitch decision-making process that we previously identified using EcoRIE111Q. Lastly, we find that EcoRIE111Q maps nascent RNA structure to specific transcript lengths more precisely than biotin–SAv and propose guidelines to leverage the complementary strengths of each transcription roadblock in cotranscriptional SHAPE-Seq. PMID:28398514

Distributed biotin-streptavidin transcription roadblocks for mapping cotranscriptional RNA folding.

PubMed

Strobel, Eric J; Watters, Kyle E; Nedialkov, Yuri; Artsimovitch, Irina; Lucks, Julius B

2017-07-07

RNA folding during transcription directs an order of folding that can determine RNA structure and function. However, the experimental study of cotranscriptional RNA folding has been limited by the lack of easily approachable methods that can interrogate nascent RNA structure at nucleotide resolution. To address this, we previously developed cotranscriptional selective 2΄-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) to simultaneously probe all intermediate RNA transcripts during transcription by stalling elongation complexes at catalytically dead EcoRIE111Q roadblocks. While effective, the distribution of elongation complexes using EcoRIE111Q requires laborious PCR using many different oligonucleotides for each sequence analyzed. Here, we improve the broad applicability of cotranscriptional SHAPE-Seq by developing a sequence-independent biotin-streptavidin (SAv) roadblocking strategy that simplifies the preparation of roadblocking DNA templates. We first determine the properties of biotin-SAv roadblocks. We then show that randomly distributed biotin-SAv roadblocks can be used in cotranscriptional SHAPE-Seq experiments to identify the same RNA structural transitions related to a riboswitch decision-making process that we previously identified using EcoRIE111Q. Lastly, we find that EcoRIE111Q maps nascent RNA structure to specific transcript lengths more precisely than biotin-SAv and propose guidelines to leverage the complementary strengths of each transcription roadblock in cotranscriptional SHAPE-Seq. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Design and cloning strategies for constructing shRNA expression vectors

PubMed Central

McIntyre, Glen J; Fanning, Gregory C

2006-01-01

Background Short hairpin RNA (shRNA) encoded within an expression vector has proven an effective means of harnessing the RNA interference (RNAi) pathway in mammalian cells. A survey of the literature revealed that shRNA vector construction can be hindered by high mutation rates and the ensuing sequencing is often problematic. Current options for constructing shRNA vectors include the use of annealed complementary oligonucleotides (74 % of surveyed studies), a PCR approach using hairpin containing primers (22 %) and primer extension of hairpin templates (4 %). Results We considered primer extension the most attractive method in terms of cost. However, in initial experiments we encountered a mutation frequency of 50 % compared to a reported 20 – 40 % for other strategies. By modifying the technique to be an isothermal reaction using the DNA polymerase Phi29, we reduced the error rate to 10 %, making primer extension the most efficient and cost-effective approach tested. We also found that inclusion of a restriction site in the loop could be exploited for confirming construct integrity by automated sequencing, while maintaining intended gene suppression. Conclusion In this study we detail simple improvements for constructing and sequencing shRNA that overcome current limitations. We also compare the advantages of our solutions against proposed alternatives. Our technical modifications will be of tangible benefit to researchers looking for a more efficient and reliable shRNA construction process. PMID:16396676

Metagenomics uncovers gaps in amplicon-based detection of microbial diversity

DOE PAGES

Eloe-Fadrosh, Emiley A.; Ivanova, Natalia N.; Woyke, Tanja; ...

2016-02-01

Our view of microbial diversity has expanded greatly over the past 40 years, primarily through the wide application of PCR-based surveys of the small-subunit ribosomal RNA (SSU rRNA) gene. Yet significant gaps in knowledge remain due to well-recognized limitations of this method. Here in this paper, we systematically survey primer fidelity in SSU rRNA gene sequences recovered from over 6,000 assembled metagenomes sampled globally. Our findings show that approximately 10% of environmental microbial sequences might be missed from classical PCR-based SSU rRNA gene surveys, mostly members of the Candidate Phyla Radiation (CPR) and as yet uncharacterized Archaea. In conclusion, thesemore » results underscore the extent of uncharacterized microbial diversity and provide fruitful avenues for describing additional phylogenetic lineages.« less

Bio—Cryptography: A Possible Coding Role for RNA Redundancy

NASA Astrophysics Data System (ADS)

Regoli, M.

2009-03-01

The RNA-Crypto System (shortly RCS) is a symmetric key algorithm to cipher data. The idea for this new algorithm starts from the observation of nature. In particular from the observation of RNA behavior and some of its properties. The RNA sequences have some sections called Introns. Introns, derived from the term "intragenic regions," are non-coding sections of precursor mRNA (pre-mRNA) or other RNAs, that are removed (spliced out of the RNA) before the mature RNA is formed. Once the introns have been spliced out of a pre-mRNA, the resulting mRNA sequence is ready to be translated into a protein. The corresponding parts of a gene are known as introns as well. The nature and the role of Introns in the pre-mRNA is not clear and it is under ponderous researches by biologists but, in our case, we will use the presence of Introns in the RNA-Crypto System output as a strong method to add chaotic non coding information and an unnecessary behavior in the access to the secret key to code the messages. In the RNA-Crypto System algorithm the introns are sections of the ciphered message with non-coding information as well as in the precursor mRNA.

Investigation of RNA Synthesis Using 5-Bromouridine Labelling and Immunoprecipitation.

PubMed

Kofoed, Rikke H; Betzer, Cristine; Lykke-Andersen, Søren; Molska, Ewa; Jensen, Poul H

2018-05-03

When steady state RNA levels are compared between two conditions, it is not possible to distinguish whether changes are caused by alterations in production or degradation of RNA. This protocol describes a method for measurement of RNA production, using 5-Bromouridine labelling of RNA followed by immunoprecipitation, which enables investigation of RNA synthesized within a short timeframe (e.g., 1 h). The advantage of 5-Bromouridine-labelling and immunoprecipitation over the use of toxic transcriptional inhibitors, such as α-amanitin and actinomycin D, is that there are no or very low effects on cell viability during short-term use. However, because 5-Bromouridine-immunoprecipitation only captures RNA produced within the short labelling time, slowly produced as well as rapidly degraded RNA can be difficult to measure by this method. The 5-Bromouridine-labelled RNA captured by 5-Bromouridine-immunoprecipitation can be analyzed by reverse transcription, quantitative polymerase chain reaction, and next generation sequencing. All types of RNA can be investigated, and the method is not limited to measuring mRNA as is presented in this example.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

PubMed

Rivas, Elena; Lang, Raymond; Eddy, Sean R

2012-02-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more

PubMed Central

Rivas, Elena; Lang, Raymond; Eddy, Sean R.

2012-01-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases. PMID:22194308

Random Amplification and Pyrosequencing for Identification of Novel Viral Genome Sequences

PubMed Central

Hang, Jun; Forshey, Brett M.; Kochel, Tadeusz J.; Li, Tao; Solórzano, Víctor Fiestas; Halsey, Eric S.; Kuschner, Robert A.

2012-01-01

ssRNA viruses have high levels of genomic divergence, which can lead to difficulty in genomic characterization of new viruses using traditional PCR amplification and sequencing methods. In this study, random reverse transcription, anchored random PCR amplification, and high-throughput pyrosequencing were used to identify orthobunyavirus sequences from total RNA extracted from viral cultures of acute febrile illness specimens. Draft genome sequence for the orthobunyavirus L segment was assembled and sequentially extended using de novo assembly contigs from pyrosequencing reads and orthobunyavirus sequences in GenBank as guidance. Accuracy and continuous coverage were achieved by mapping all reads to the L segment draft sequence. Subsequently, RT-PCR and Sanger sequencing were used to complete the genome sequence. The complete L segment was found to be 6936 bases in length, encoding a 2248-aa putative RNA polymerase. The identified L segment was distinct from previously published South American orthobunyaviruses, sharing 63% and 54% identity at the nucleotide and amino acid level, respectively, with the complete Oropouche virus L segment and 73% and 81% identity at the nucleotide and amino acid level, respectively, with a partial Caraparu virus L segment. The result demonstrated the effectiveness of a sequence-independent amplification and next-generation sequencing approach for obtaining complete viral genomes from total nucleic acid extracts and its use in pathogen discovery. PMID:22468136

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing

PubMed Central

2012-01-01

Background RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Results Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. Conclusions This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates. PMID:22985019

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing.

PubMed

Robles, José A; Qureshi, Sumaira E; Stephen, Stuart J; Wilson, Susan R; Burden, Conrad J; Taylor, Jennifer M

2012-09-17

RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates.

Digital transcriptome profiling using selective hexamer priming for cDNA synthesis.

PubMed

Armour, Christopher D; Castle, John C; Chen, Ronghua; Babak, Tomas; Loerch, Patrick; Jackson, Stuart; Shah, Jyoti K; Dey, John; Rohl, Carol A; Johnson, Jason M; Raymond, Christopher K

2009-09-01

We developed a procedure for the preparation of whole transcriptome cDNA libraries depleted of ribosomal RNA from only 1 microg of total RNA. The method relies on a collection of short, computationally selected oligonucleotides, called 'not-so-random' (NSR) primers, to obtain full-length, strand-specific representation of nonribosomal RNA transcripts. In this study we validated the technique by profiling human whole brain and universal human reference RNA using ultra-high-throughput sequencing.

An RNA motif that binds ATP

NASA Technical Reports Server (NTRS)

Sassanfar, M.; Szostak, J. W.

1993-01-01

RNAs that contain specific high-affinity binding sites for small molecule ligands immobilized on a solid support are present at a frequency of roughly one in 10(10)-10(11) in pools of random sequence RNA molecules. Here we describe a new in vitro selection procedure designed to ensure the isolation of RNAs that bind the ligand of interest in solution as well as on a solid support. We have used this method to isolate a remarkably small RNA motif that binds ATP, a substrate in numerous biological reactions and the universal biological high-energy intermediate. The selected ATP-binding RNAs contain a consensus sequence, embedded in a common secondary structure. The binding properties of ATP analogues and modified RNAs show that the binding interaction is characterized by a large number of close contacts between the ATP and RNA, and by a change in the conformation of the RNA.

Protein-RNA specificity by high-throughput principal component analysis of NMR spectra.

PubMed

Collins, Katherine M; Oregioni, Alain; Robertson, Laura E; Kelly, Geoff; Ramos, Andres

2015-03-31

Defining the RNA target selectivity of the proteins regulating mRNA metabolism is a key issue in RNA biology. Here we present a novel use of principal component analysis (PCA) to extract the RNA sequence preference of RNA binding proteins. We show that PCA can be used to compare the changes in the nuclear magnetic resonance (NMR) spectrum of a protein upon binding a set of quasi-degenerate RNAs and define the nucleobase specificity. We couple this application of PCA to an automated NMR spectra recording and processing protocol and obtain an unbiased and high-throughput NMR method for the analysis of nucleobase preference in protein-RNA interactions. We test the method on the RNA binding domains of three important regulators of RNA metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clostridium sphenoides Chronic Osteomyelitis Diagnosed Via Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry, Conflicting With 16S rRNA Sequencing but Confirmed by Whole Genome Sequencing.

PubMed

Perkins, Matthew J; Snesrud, Erik; McGann, Patrick; Duplessis, Christopher A

2017-01-01

We report a case of successful treatment of chronic osteomyelitis (emanating from contaminated soil exposure) caused by Clostridium sphenoides, an organism infrequently identified as a cause of human infection and more saliently osteomyelitis (only 1 reported case in the literature). Additional impetus for reporting this case resides in the insights gained regarding pathogen identification exploiting sophisticated molecular platforms coupled to traditional microbial culture-based methods. The fastidious nature of cultivating anaerobic organisms required initial attempts at 16S rRNA sequencing to identify a Clostridium species (Clostridium celerecrescens). However, on exploiting matrix-assisted laser desorption ionization time of flight (MALDI TOF) technology, C. sphenoides was identified, and confirmed on whole genome sequencing. The discrepancies noted in the varying platforms require vigilance to seek complementary testing for conflicting results. Although highly accurate, the MALDI TOF and 16S rRNA sequencing platforms are not immune to false identification particularly in differentiating closely related organisms. More germane, whole genome sequencing should be entertained when conflicting results are obtained from MALDI TOF and 16S rRNA sequencing. Precise species and/or strain level identification can be clinically relevant as antimicrobial sensitivity profiles may be discrepant between closely related species influencing clinical outcomes. Thus, it is incumbent on us to strive to acquire the correct species characterization when resources allow to dictate optimal treatment. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.

[Phylogeny of protostome moulting animals (Ecdysozoa) inferred from 18 and 28S rRNA gene sequences].

PubMed

Petrov, N B; Vladychenskaia, N S

2005-01-01

Reliability of reconstruction of phylogenetic relationships within a group of protostome moulting animals was evaluated by means of comparison of 18 and 28S rRNA gene sequences sets both taken separately and combined. Reliability of reconstructions was evaluated by values of the bootstrap support of major phylogenetic tree nodes and by degree of congruence of phylogenetic trees inferred by various methods. By both criteria, phylogenetic trees reconstructed from the combined 18 and 28S rRNA gene sequences were better than those inferred from 18 and 28S sequences taken separately. Results obtained are consistent with phylogenetic hypothesis separating protostome animals into two major clades, moulting Ecdysozoa (Priapulida + Kinorhyncha, Nematoda + Nematomorpha, Onychophora + Tardigrada, Myriapoda + Chelicerata, Crustacea + Hexapoda) and unmoulting Lophotrochozoa (Plathelminthes, Nemertini, Annelida, Mollusca, Echiura, Sipuncula). Clade Cephalorhyncha does not include nematomorphs (Nematomorpha). Conclusion was taken that it is necessary to use combined 18 and 28S data in phylogenetic studies.

Biotechnological applications of mobile group II introns and their reverse transcriptases: gene targeting, RNA-seq, and non-coding RNA analysis.

PubMed

Enyeart, Peter J; Mohr, Georg; Ellington, Andrew D; Lambowitz, Alan M

2014-01-13

Mobile group II introns are bacterial retrotransposons that combine the activities of an autocatalytic intron RNA (a ribozyme) and an intron-encoded reverse transcriptase to insert site-specifically into DNA. They recognize DNA target sites largely by base pairing of sequences within the intron RNA and achieve high DNA target specificity by using the ribozyme active site to couple correct base pairing to RNA-catalyzed intron integration. Algorithms have been developed to program the DNA target site specificity of several mobile group II introns, allowing them to be made into 'targetrons.' Targetrons function for gene targeting in a wide variety of bacteria and typically integrate at efficiencies high enough to be screened easily by colony PCR, without the need for selectable markers. Targetrons have found wide application in microbiological research, enabling gene targeting and genetic engineering of bacteria that had been intractable to other methods. Recently, a thermostable targetron has been developed for use in bacterial thermophiles, and new methods have been developed for using targetrons to position recombinase recognition sites, enabling large-scale genome-editing operations, such as deletions, inversions, insertions, and 'cut-and-pastes' (that is, translocation of large DNA segments), in a wide range of bacteria at high efficiency. Using targetrons in eukaryotes presents challenges due to the difficulties of nuclear localization and sub-optimal magnesium concentrations, although supplementation with magnesium can increase integration efficiency, and directed evolution is being employed to overcome these barriers. Finally, spurred by new methods for expressing group II intron reverse transcriptases that yield large amounts of highly active protein, thermostable group II intron reverse transcriptases from bacterial thermophiles are being used as research tools for a variety of applications, including qRT-PCR and next-generation RNA sequencing (RNA-seq). The high processivity and fidelity of group II intron reverse transcriptases along with their novel template-switching activity, which can directly link RNA-seq adaptor sequences to cDNAs during reverse transcription, open new approaches for RNA-seq and the identification and profiling of non-coding RNAs, with potentially wide applications in research and biotechnology.

Inventory of high-abundance mRNAs in skeletal muscle of normal men.

PubMed

Welle, S; Bhatt, K; Thornton, C A

1999-05-01

G42875rial analysis of gene expression (SAGE) method was used to generate a catalog of 53,875 short (14 base) expressed sequence tags from polyadenylated RNA obtained from vastus lateralis muscle of healthy young men. Over 12,000 unique tags were detected. The frequency of occurrence of each tag reflects the relative abundance of the corresponding mRNA. The mRNA species that were detected 10 or more times, each comprising >/=0.02% of the mRNA population, accounted for 64% of the mRNA mass but <10% of the total number of mRNA species detected. Almost all of the abundant tags matched mRNA or EST sequences cataloged in GenBank. Mitochondrial transcripts accounted for approximately 20% of the polyadenylated RNA. Transcripts encoding proteins of the myofibrils were the most abundant nuclear-encoded mRNAs. Transcripts encoding ribosomal proteins, and those encoding proteins involved in energy metabolism, also were very abundant. The database can be used as a reference for investigations of alterations in gene expression associated with conditions that influence muscle function, such as muscular dystrophies, aging, and exercise.

A PCR detection method for rapid identification of Melissococcus pluton in honeybee larvae.

PubMed

Govan, V A; Brözel, V; Allsopp, M H; Davison, S

1998-05-01

Melissococcus pluton is the causative agent of European foulbrood, a disease of honeybee larvae. This bacterium is particularly difficult to isolate because of its stringent growth requirements and competition from other bacteria. PCR was used selectively to amplify specific rRNA gene sequences of M. pluton from pure culture, from crude cell lysates, and directly from infected bee larvae. The PCR primers were designed from M. pluton 16S rRNA sequence data. The PCR products were visualized by agarose gel electrophoresis and confirmed as originating from M. pluton by sequencing in both directions. Detection was highly specific, and the probes did not hybridize with DNA from other bacterial species tested. This method enabled the rapid and specific detection and identification of M. pluton from pure cultures and infected bee larvae.

A PCR Detection Method for Rapid Identification of Melissococcus pluton in Honeybee Larvae

PubMed Central

Govan, V. A.; Brözel, V.; Allsopp, M. H.; Davison, S.

1998-01-01

Melissococcus pluton is the causative agent of European foulbrood, a disease of honeybee larvae. This bacterium is particularly difficult to isolate because of its stringent growth requirements and competition from other bacteria. PCR was used selectively to amplify specific rRNA gene sequences of M. pluton from pure culture, from crude cell lysates, and directly from infected bee larvae. The PCR primers were designed from M. pluton 16S rRNA sequence data. The PCR products were visualized by agarose gel electrophoresis and confirmed as originating from M. pluton by sequencing in both directions. Detection was highly specific, and the probes did not hybridize with DNA from other bacterial species tested. This method enabled the rapid and specific detection and identification of M. pluton from pure cultures and infected bee larvae. PMID:9572987

Ensemble-based classification approach for micro-RNA mining applied on diverse metagenomic sequences.

PubMed

ElGokhy, Sherin M; ElHefnawi, Mahmoud; Shoukry, Amin

2014-05-06

MicroRNAs (miRNAs) are endogenous ∼22 nt RNAs that are identified in many species as powerful regulators of gene expressions. Experimental identification of miRNAs is still slow since miRNAs are difficult to isolate by cloning due to their low expression, low stability, tissue specificity and the high cost of the cloning procedure. Thus, computational identification of miRNAs from genomic sequences provide a valuable complement to cloning. Different approaches for identification of miRNAs have been proposed based on homology, thermodynamic parameters, and cross-species comparisons. The present paper focuses on the integration of miRNA classifiers in a meta-classifier and the identification of miRNAs from metagenomic sequences collected from different environments. An ensemble of classifiers is proposed for miRNA hairpin prediction based on four well-known classifiers (Triplet SVM, Mipred, Virgo and EumiR), with non-identical features, and which have been trained on different data. Their decisions are combined using a single hidden layer neural network to increase the accuracy of the predictions. Our ensemble classifier achieved 89.3% accuracy, 82.2% f-measure, 74% sensitivity, 97% specificity, 92.5% precision and 88.2% negative predictive value when tested on real miRNA and pseudo sequence data. The area under the receiver operating characteristic curve of our classifier is 0.9 which represents a high performance index.The proposed classifier yields a significant performance improvement relative to Triplet-SVM, Virgo and EumiR and a minor refinement over MiPred.The developed ensemble classifier is used for miRNA prediction in mine drainage, groundwater and marine metagenomic sequences downloaded from the NCBI sequence reed archive. By consulting the miRBase repository, 179 miRNAs have been identified as highly probable miRNAs. Our new approach could thus be used for mining metagenomic sequences and finding new and homologous miRNAs. The paper investigates a computational tool for miRNA prediction in genomic or metagenomic data. It has been applied on three metagenomic samples from different environments (mine drainage, groundwater and marine metagenomic sequences). The prediction results provide a set of extremely potential miRNA hairpins for cloning prediction methods. Among the ensemble prediction obtained results there are pre-miRNA candidates that have been validated using miRbase while they have not been recognized by some of the base classifiers.

Identification of key factors regulating self-renewal and differentiation in EML hematopoietic precursor cells by RNA-sequencing analysis.

PubMed

Zong, Shan; Deng, Shuyun; Chen, Kenian; Wu, Jia Qian

2014-11-11

Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

PubMed Central

Chen, Kenian; Wu, Jia Qian

2014-01-01

Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo. PMID:25407807

Tree decomposition based fast search of RNA structures including pseudoknots in genomes.

PubMed

Song, Yinglei; Liu, Chunmei; Malmberg, Russell; Pan, Fangfang; Cai, Liming

2005-01-01

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.

Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)

PubMed Central

2013-01-01

Background The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. Results We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Conclusions Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools. PMID:24209455

Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki).

PubMed

Sturgill, David; Malone, John H; Sun, Xia; Smith, Harold E; Rabinow, Leonard; Samson, Marie-Laure; Oliver, Brian

2013-11-09

The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools.

RNA processing in Neurospora crassa mitochondria: use of transfer RNA sequences as signals.

PubMed Central

Breitenberger, C A; Browning, K S; Alzner-DeWeerd, B; RajBhandary, U L

1985-01-01

We have used RNA gel transfer hybridization, S1 nuclease mapping and primer extension to analyze transcripts derived from several genes in Neurospora crassa mitochondria. The transcripts studied include those for cytochrome oxidase subunit III, 17S rRNA and an unidentified open reading frame. In all three cases, initial transcripts are long, include tRNA sequences, and are subsequently processed to generate the mature RNAs. We find that endpoints of the most abundant transcripts generally coincide with those of tRNA sequences. We therefore conclude that tRNA sequences in long transcripts act as primary signals for RNA processing in N. crassa mitochondria. The situation is somewhat analogous to that observed in mammalian mitochondrial systems. The difference, however, is that in mammalian mitochondria, noncoding spacers between tRNA, rRNA and protein genes are very short and in many cases non-existent, allowing no room for intergenic RNA processing signals whereas, in N. crassa mtDNA, intergenic non-coding sequences are usually several hundred nucleotides long and contain highly conserved GC-rich palindromic sequences. Since these GC-rich palindromic sequences are retained in the processed mature RNAs, we conclude that they do not serve as signals for RNA processing. Images Fig. 2. Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. PMID:2990893

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

PubMed Central

Di, Yanming; Schafer, Daniel W.; Wilhelm, Larry J.; Fox, Samuel E.; Sullivan, Christopher M.; Curzon, Aron D.; Carrington, James C.; Mockler, Todd C.; Chang, Jeff H.

2011-01-01

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts. PMID:21998647

Pre-Mrna Introns as a Model for Cryptographic Algorithm:. Theory and Experiments

NASA Astrophysics Data System (ADS)

Regoli, Massimo

2010-01-01

The RNA-Crypto System (shortly RCS) is a symmetric key algorithm to cipher data. The idea for this new algorithm starts from the observation of nature. In particular from the observation of RNA behavior and some of its properties. In particular the RNA sequences have some sections called Introns. Introns, derived from the term "intragenic regions", are non-coding sections of precursor mRNA (pre-mRNA) or other RNAs, that are removed (spliced out of the RNA) before the mature RNA is formed. Once the introns have been spliced out of a pre-mRNA, the resulting mRNA sequence is ready to be translated into a protein. The corresponding parts of a gene are known as introns as well. The nature and the role of Introns in the pre-mRNA is not clear and it is under ponderous researches by Biologists but, in our case, we will use the presence of Introns in the RNA-Crypto System output as a strong method to add chaotic non coding information and an unnecessary behaviour in the access to the secret key to code the messages. In the RNA-Crypto System algorithm the introns are sections of the ciphered message with non-coding information as well as in the precursor mRNA.

Novel Molecular Method for Identification of Streptococcus pneumoniae Applicable to Clinical Microbiology and 16S rRNA Sequence-Based Microbiome Studies

PubMed Central

Scholz, Christian F. P.; Poulsen, Knud

2012-01-01

The close phylogenetic relationship of the important pathogen Streptococcus pneumoniae and several species of commensal streptococci, particularly Streptococcus mitis and Streptococcus pseudopneumoniae, and the recently demonstrated sharing of genes and phenotypic traits previously considered specific for S. pneumoniae hamper the exact identification of S. pneumoniae. Based on sequence analysis of 16S rRNA genes of a collection of 634 streptococcal strains, identified by multilocus sequence analysis, we detected a cytosine at position 203 present in all 440 strains of S. pneumoniae but replaced by an adenosine residue in all strains representing other species of mitis group streptococci. The S. pneumoniae-specific sequence signature could be demonstrated by sequence analysis or indirectly by restriction endonuclease digestion of a PCR amplicon covering the site. The S. pneumoniae-specific signature offers an inexpensive means for validation of the identity of clinical isolates and should be used as an integrated marker in the annotation procedure employed in 16S rRNA-based molecular studies of complex human microbiotas. This may avoid frequent misidentifications such as those we demonstrate to have occurred in previous reports and in reference sequence databases. PMID:22442329

RNAcentral: A comprehensive database of non-coding RNA sequences

DOE PAGES

Williams, Kelly Porter; Lau, Britney Yan

2016-10-28

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similaritymore » searches as well as genome browsing functionality.« less

RNAcentral: A comprehensive database of non-coding RNA sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Kelly Porter; Lau, Britney Yan

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similaritymore » searches as well as genome browsing functionality.« less

Short-term application of dexamethasone on stem cells derived from human gingiva reduces the expression of RUNX2 and β-catenin.

PubMed

Kim, Bo-Bae; Kim, Minji; Park, Yun-Hee; Ko, Youngkyung; Park, Jun-Beom

2017-06-01

Objective Next-generation sequencing was performed to evaluate the effects of short-term application of dexamethasone on human gingiva-derived mesenchymal stem cells. Methods Human gingiva-derived stem cells were treated with a final concentration of 10 -7  M dexamethasone and the same concentration of vehicle control. This was followed by mRNA sequencing and data analysis, gene ontology and pathway analysis, quantitative real-time polymerase chain reaction of mRNA, and western blot analysis of RUNX2 and β-catenin. Results In total, 26,364 mRNAs were differentially expressed. Comparison of the results of dexamethasone versus control at 2 hours revealed that 7 mRNAs were upregulated and 25 mRNAs were downregulated. The application of dexamethasone reduced the expression of RUNX2 and β-catenin in human gingiva-derived mesenchymal stem cells. Conclusion The effects of dexamethasone on stem cells were evaluated with mRNA sequencing, and validation of the expression was performed with qualitative real-time polymerase chain reaction and western blot analysis. The results of this study can provide new insights into the role of mRNA sequencing in maxillofacial areas.

Studying the evolutionary relationships and phylogenetic trees of 21 groups of tRNA sequences based on complex networks.

PubMed

Wei, Fangping; Chen, Bowen

2012-03-01

To find out the evolutionary relationships among different tRNA sequences of 21 amino acids, 22 networks are constructed. One is constructed from whole tRNAs, and the other 21 networks are constructed from the tRNAs which carry the same amino acids. A new method is proposed such that the alignment scores of any two amino acids groups are determined by the average degree and the average clustering coefficient of their networks. The anticodon feature of isolated tRNA and the phylogenetic trees of 21 group networks are discussed. We find that some isolated tRNA sequences in 21 networks still connect with other tRNAs outside their group, which reflects the fact that those tRNAs might evolve by intercrossing among these 21 groups. We also find that most anticodons among the same cluster are only one base different in the same sites when S ≥ 70, and they stay in the same rank in the ladder of evolutionary relationships. Those observations seem to agree on that some tRNAs might mutate from the same ancestor sequences based on point mutation mechanisms.