Identification of microRNAs from Amur grape (Vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics.

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Wang, Chen; Han, Jian; Liu, Chonghuai; Kibet, Korir Nicholas; Kayesh, Emrul; Shangguan, Lingfei; Li, Xiaoying; Fang, Jinggui

2012-03-29

MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved mi

Identification of microRNAs from Amur grape (vitis amurensis Rupr. by deep sequencing and analysis of microRNA variations with bioinformatics

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Wang Chen

2012-03-01

Full Text Available Abstract Background MicroRNA (miRNA is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr. is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. Results A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Conclusions Deep sequencing of short RNAs from Amur grape flowers and berries identified 72

Deep RNA sequencing of the skeletal muscle transcriptome in swimming fish.

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Arjan P Palstra

Full Text Available Deep RNA sequencing (RNA-seq was performed to provide an in-depth view of the transcriptome of red and white skeletal muscle of exercised and non-exercised rainbow trout (Oncorhynchus mykiss with the specific objective to identify expressed genes and quantify the transcriptomic effects of swimming-induced exercise. Pubertal autumn-spawning seawater-raised female rainbow trout were rested (n = 10 or swum (n = 10 for 1176 km at 0.75 body-lengths per second in a 6,000-L swim-flume under reproductive conditions for 40 days. Red and white muscle RNA of exercised and non-exercised fish (4 lanes was sequenced and resulted in 15-17 million reads per lane that, after de novo assembly, yielded 149,159 red and 118,572 white muscle contigs. Most contigs were annotated using an iterative homology search strategy against salmonid ESTs, the zebrafish Danio rerio genome and general Metazoan genes. When selecting for large contigs (>500 nucleotides, a number of novel rainbow trout gene sequences were identified in this study: 1,085 and 1,228 novel gene sequences for red and white muscle, respectively, which included a number of important molecules for skeletal muscle function. Transcriptomic analysis revealed that sustained swimming increased transcriptional activity in skeletal muscle and specifically an up-regulation of genes involved in muscle growth and developmental processes in white muscle. The unique collection of transcripts will contribute to our understanding of red and white muscle physiology, specifically during the long-term reproductive migration of salmonids.

Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata

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Yu Huaping

2010-07-01

Full Text Available Abstract Background MicroRNAs (miRNAs play a critical role in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as Arabidopsis and rice. Deep sequencing technologies have facilitated identification of species-specific or lowly expressed as well as conserved or highly expressed miRNAs in plants. Results In this research, we used Solexa sequencing to discover new microRNAs in trifoliate orange (Citrus trifoliata which is an important rootstock of citrus. A total of 13,106,753 reads representing 4,876,395 distinct sequences were obtained from a short RNA library generated from small RNA extracted from C. trifoliata flower and fruit tissues. Based on sequence similarity and hairpin structure prediction, we found that 156,639 reads representing 63 sequences from 42 highly conserved miRNA families, have perfect matches to known miRNAs. We also identified 10 novel miRNA candidates whose precursors were all potentially generated from citrus ESTs. In addition, five miRNA* sequences were also sequenced. These sequences had not been earlier described in other plant species and accumulation of the 10 novel miRNAs were confirmed by qRT-PCR analysis. Potential target genes were predicted for most conserved and novel miRNAs. Moreover, four target genes including one encoding IRX12 copper ion binding/oxidoreductase and three genes encoding NB-LRR disease resistance protein have been experimentally verified by detection of the miRNA-mediated mRNA cleavage in C. trifoliata. Conclusion Deep sequencing of short RNAs from C. trifoliata flowers and fruits identified 10 new potential miRNAs and 42 highly conserved miRNA families, indicating that specific miRNAs exist in C. trifoliata. These results show that regulatory miRNAs exist in agronomically important trifoliate orange

Deep sequencing of foot-and-mouth disease virus reveals RNA sequences involved in genome packaging.

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Logan, Grace; Newman, Joseph; Wright, Caroline F; Lasecka-Dykes, Lidia; Haydon, Daniel T; Cottam, Eleanor M; Tuthill, Tobias J

2017-10-18

Non-enveloped viruses protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. Packaging and capsid assembly in RNA viruses can involve interactions between capsid proteins and secondary structures in the viral genome as exemplified by the RNA bacteriophage MS2 and as proposed for other RNA viruses of plants, animals and human. In the picornavirus family of non-enveloped RNA viruses, the requirements for genome packaging remain poorly understood. Here we show a novel and simple approach to identify predicted RNA secondary structures involved in genome packaging in the picornavirus foot-and-mouth disease virus (FMDV). By interrogating deep sequencing data generated from both packaged and unpackaged populations of RNA we have determined multiple regions of the genome with constrained variation in the packaged population. Predicted secondary structures of these regions revealed stem loops with conservation of structure and a common motif at the loop. Disruption of these features resulted in attenuation of virus growth in cell culture due to a reduction in assembly of mature virions. This study provides evidence for the involvement of predicted RNA structures in picornavirus packaging and offers a readily transferable methodology for identifying packaging requirements in many other viruses. Importance In order to transmit their genetic material to a new host, non-enveloped viruses must protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. For many non-enveloped RNA viruses the requirements for this critical part of the viral life cycle remain poorly understood. We have identified RNA sequences involved in genome packaging of the picornavirus foot-and-mouth disease virus. This virus causes an economically devastating disease of livestock affecting both the developed and developing world. The experimental methods developed to carry out this work are novel, simple and transferable to the

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

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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

Deep-sequencing protocols influence the results obtained in small-RNA sequencing.

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Joern Toedling

Full Text Available Second-generation sequencing is a powerful method for identifying and quantifying small-RNA components of cells. However, little attention has been paid to the effects of the choice of sequencing platform and library preparation protocol on the results obtained. We present a thorough comparison of small-RNA sequencing libraries generated from the same embryonic stem cell lines, using different sequencing platforms, which represent the three major second-generation sequencing technologies, and protocols. We have analysed and compared the expression of microRNAs, as well as populations of small RNAs derived from repetitive elements. Despite the fact that different libraries display a good correlation between sequencing platforms, qualitative and quantitative variations in the results were found, depending on the protocol used. Thus, when comparing libraries from different biological samples, it is strongly recommended to use the same sequencing platform and protocol in order to ensure the biological relevance of the comparisons.

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

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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.

Deep sequencing of Salmonella RNA associated with heterologous Hfq proteins in vivo reveals small RNAs as a major target class and identifies RNA processing phenotypes.

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Sittka, Alexandra; Sharma, Cynthia M; Rolle, Katarzyna; Vogel, Jörg

2009-01-01

The bacterial Sm-like protein, Hfq, is a key factor for the stability and function of small non-coding RNAs (sRNAs) in Escherichia coli. Homologues of this protein have been predicted in many distantly related organisms yet their functional conservation as sRNA-binding proteins has not entirely been clear. To address this, we expressed in Salmonella the Hfq proteins of two eubacteria (Neisseria meningitides, Aquifex aeolicus) and an archaeon (Methanocaldococcus jannaschii), and analyzed the associated RNA by deep sequencing. This in vivo approach identified endogenous Salmonella sRNAs as a major target of the foreign Hfq proteins. New Salmonella sRNA species were also identified, and some of these accumulated specifically in the presence of a foreign Hfq protein. In addition, we observed specific RNA processing defects, e.g., suppression of precursor processing of SraH sRNA by Methanocaldococcus Hfq, or aberrant accumulation of extracytoplasmic target mRNAs of the Salmonella GcvB, MicA or RybB sRNAs. Taken together, our study provides evidence of a conserved inherent sRNA-binding property of Hfq, which may facilitate the lateral transmission of regulatory sRNAs among distantly related species. It also suggests that the expression of heterologous RNA-binding proteins combined with deep sequencing analysis of RNA ligands can be used as a molecular tool to dissect individual steps of RNA metabolism in vivo.

A comprehensive survey of 3′ animal miRNA modification events and a possible role for 3′ adenylation in modulating miRNA targeting effectiveness

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Burroughs, A. Maxwell; Ando, Yoshinari; de Hoon, Michiel J.L.; Tomaru, Yasuhiro; Nishibu, Takahiro; Ukekawa, Ryo; Funakoshi, Taku; Kurokawa, Tsutomu; Suzuki, Harukazu; Hayashizaki, Yoshihide; Daub, Carsten O.

2010-01-01

Animal microRNA sequences are subject to 3′ nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3′ adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a...

Transcriptome analysis of the model protozoan, Tetrahymena thermophila, using Deep RNA sequencing.

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Jie Xiong

Full Text Available BACKGROUND: The ciliated protozoan Tetrahymena thermophila is a well-studied single-celled eukaryote model organism for cellular and molecular biology. However, the lack of extensive T. thermophila cDNA libraries or a large expressed sequence tag (EST database limited the quality of the original genome annotation. METHODOLOGY/PRINCIPAL FINDINGS: This RNA-seq study describes the first deep sequencing analysis of the T. thermophila transcriptome during the three major stages of the life cycle: growth, starvation and conjugation. Uniquely mapped reads covered more than 96% of the 24,725 predicted gene models in the somatic genome. More than 1,000 new transcribed regions were identified. The great dynamic range of RNA-seq allowed detection of a nearly six order-of-magnitude range of measurable gene expression orchestrated by this cell. RNA-seq also allowed the first prediction of transcript untranslated regions (UTRs and an updated (larger size estimate of the T. thermophila transcriptome: 57 Mb, or about 55% of the somatic genome. Our study identified nearly 1,500 alternative splicing (AS events distributed over 5.2% of T. thermophila genes. This percentage represents a two order-of-magnitude increase over previous EST-based estimates in Tetrahymena. Evidence of stage-specific regulation of alternative splicing was also obtained. Finally, our study allowed us to completely confirm about 26.8% of the genes originally predicted by the gene finder, to correct coding sequence boundaries and intron-exon junctions for about a third, and to reassign microarray probes and correct earlier microarray data. CONCLUSIONS/SIGNIFICANCE: RNA-seq data significantly improve the genome annotation and provide a fully comprehensive view of the global transcriptome of T. thermophila. To our knowledge, 5.2% of T. thermophila genes with AS is the highest percentage of genes showing AS reported in a unicellular eukaryote. Tetrahymena thus becomes an excellent unicellular

Short RNA guides cleavage by eukaryotic RNase III.

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Bruno Lamontagne

Full Text Available In eukaryotes, short RNAs guide a variety of enzymatic activities that range from RNA editing to translation repression. It is hypothesized that pre-existing proteins evolved to bind and use guide RNA during evolution. However, the capacity of modern proteins to adopt new RNA guides has never been demonstrated. Here we show that Rnt1p, the yeast orthologue of the bacterial dsRNA-specific RNase III, can bind short RNA transcripts and use them as guides for sequence-specific cleavage. Target cleavage occurred at a constant distance from the Rnt1p binding site, leaving the guide RNA intact for subsequent cleavage. Our results indicate that RNase III may trigger sequence-specific RNA degradation independent of the RNAi machinery, and they open the road for a new generation of precise RNA silencing tools that do not trigger a dsRNA-mediated immune response.

microRNA expression profiling in fetal single ventricle malformation identified by deep sequencing.

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Yu, Zhang-Bin; Han, Shu-Ping; Bai, Yun-Fei; Zhu, Chun; Pan, Ya; Guo, Xi-Rong

2012-01-01

microRNAs (miRNAs) have emerged as key regulators in many biological processes, particularly cardiac growth and development, although the specific miRNA expression profile associated with this process remains to be elucidated. This study aimed to characterize the cellular microRNA profile involved in the development of congenital heart malformation, through the investigation of single ventricle (SV) defects. Comprehensive miRNA profiling in human fetal SV cardiac tissue was performed by deep sequencing. Differential expression of 48 miRNAs was revealed by sequencing by oligonucleotide ligation and detection (SOLiD) analysis. Of these, 38 were down-regulated and 10 were up-regulated in differentiated SV cardiac tissue, compared to control cardiac tissue. This was confirmed by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. Predicted target genes of the 48 differentially expressed miRNAs were analyzed by gene ontology and categorized according to cellular process, regulation of biological process and metabolic process. Pathway-Express analysis identified the WNT and mTOR signaling pathways as the most significant processes putatively affected by the differential expression of these miRNAs. The candidate genes involved in cardiac development were identified as potential targets for these differentially expressed microRNAs and the collaborative network of microRNAs and cardiac development related-mRNAs was constructed. These data provide the basis for future investigation of the mechanism of the occurrence and development of fetal SV malformations.

miRBase: annotating high confidence microRNAs using deep sequencing data.

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Kozomara, Ana; Griffiths-Jones, Sam

2014-01-01

We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

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Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Conserved generation of short products at piRNA loci

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Khorshid Mohsen

2011-01-01

Full Text Available Abstract Background The piRNA pathway operates in animal germ lines to ensure genome integrity through retrotransposon silencing. The Piwi protein-associated small RNAs (piRNAs guide Piwi proteins to retrotransposon transcripts, which are degraded and thereby post-transcriptionally silenced through a ping-pong amplification process. Cleavage of the retrotransposon transcript defines at the same time the 5' end of a secondary piRNA that will in turn guide a Piwi protein to a primary piRNA precursor, thereby amplifying primary piRNAs. Although several studies provided evidence that this mechanism is conserved among metazoa, how the process is initiated and what enzymatic activities are responsible for generating the primary and secondary piRNAs are not entirely clear. Results Here we analyzed small RNAs from three mammalian species, seeking to gain further insight into the mechanisms responsible for the piRNA amplification loop. We found that in all these species piRNA-directed targeting is accompanied by the generation of short sequences that have a very precisely defined length, 19 nucleotides, and a specific spatial relationship with the guide piRNAs. Conclusions This suggests that the processing of the 5' product of piRNA-guided cleavage occurs while the piRNA target is engaged by the Piwi protein. Although they are not stabilized through methylation of their 3' ends, the 19-mers are abundant not only in testes lysates but also in immunoprecipitates of Miwi and Mili proteins. They will enable more accurate identification of piRNA loci in deep sequencing data sets.

InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data.

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Konstantin Okonechnikov

Full Text Available Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology

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Yuri Kravatsky

2017-11-01

Full Text Available The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs, requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s. Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s. The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi targets in human immunodeficiency virus 1 (HIV-1 subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

MicroRNA discovery and analysis of pinewood nematode Bursaphelenchus xylophilus by deep sequencing.

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Qi-Xing Huang

Full Text Available BACKGROUND: MicroRNAs (miRNAs are considered to be very important in regulating the growth, development, behavior and stress response in animals and plants in post-transcriptional gene regulation. Pinewood nematode, Bursaphelenchus xylophilus, is an important invasive plant parasitic nematode in Asia. To have a comprehensive knowledge about miRNAs of the nematode is necessary for further in-depth study on roles of miRNAs in the ecological adaptation of the invasive species. METHODS AND FINDINGS: Five small RNA libraries were constructed and sequenced by Illumina/Solexa deep-sequencing technology. A total of 810 miRNA candidates (49 conserved and 761 novel were predicted by a computational pipeline, of which 57 miRNAs (20 conserved and 37 novel encoded by 53 miRNA precursors were identified by experimental methods. Ten novel miRNAs were considered to be species-specific miRNAs of B. xylophilus. Comparison of expression profiles of miRNAs in the five small RNA libraries showed that many miRNAs exhibited obviously different expression levels in the third-stage dispersal juvenile and at a cold-stressed status. Most of the miRNAs exhibited obviously down-regulated expression in the dispersal stage. But differences among the three geographic libraries were not prominent. A total of 979 genes were predicted to be targets of these authentic miRNAs. Among them, seven heat shock protein genes were targeted by 14 miRNAs, and six FMRFamide-like neuropeptides genes were targeted by 17 miRNAs. A real-time quantitative polymerase chain reaction was used to quantify the mRNA expression levels of target genes. CONCLUSIONS: Basing on the fact that a negative correlation existed between the expression profiles of miRNAs and the mRNA expression profiles of their target genes (hsp, flp by comparing those of the nematodes at a cold stressed status and a normal status, we suggested that miRNAs might participate in ecological adaptation and behavior regulation of the

Genome-wide analyses of long noncoding RNA expression profiles correlated with radioresistance in nasopharyngeal carcinoma via next-generation deep sequencing.

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Li, Guo; Liu, Yong; Liu, Chao; Su, Zhongwu; Ren, Shuling; Wang, Yunyun; Deng, Tengbo; Huang, Donghai; Tian, Yongquan; Qiu, Yuanzheng

2016-09-06

Radioresistance is one of the major factors limiting the therapeutic efficacy and prognosis of patients with nasopharyngeal carcinoma (NPC). Accumulating evidence has suggested that aberrant expression of long noncoding RNAs (lncRNAs) contributes to cancer progression. Therefore, here we identified lncRNAs associated with radioresistance in NPC. The differential expression profiles of lncRNAs associated with NPC radioresistance were constructed by next-generation deep sequencing by comparing radioresistant NPC cells with their parental cells. LncRNA-related mRNAs were predicted and analyzed using bioinformatics algorithms compared with the mRNA profiles related to radioresistance obtained in our previous study. Several lncRNAs and associated mRNAs were validated in established NPC radioresistant cell models and NPC tissues. By comparison between radioresistant CNE-2-Rs and parental CNE-2 cells by next-generation deep sequencing, a total of 781 known lncRNAs and 2054 novel lncRNAs were annotated. The top five upregulated and downregulated known/novel lncRNAs were detected using quantitative real-time reverse transcription-polymerase chain reaction, and 7/10 known lncRNAs and 3/10 novel lncRNAs were demonstrated to have significant differential expression trends that were the same as those predicted by deep sequencing. From the prediction process, 13 pairs of lncRNAs and their associated genes were acquired, and the prediction trends of three pairs were validated in both radioresistant CNE-2-Rs and 6-10B-Rs cell lines, including lncRNA n373932 and SLITRK5, n409627 and PRSS12, and n386034 and RIMKLB. LncRNA n373932 and its related SLITRK5 showed dramatic expression changes in post-irradiation radioresistant cells and a negative expression correlation in NPC tissues (R = -0.595, p < 0.05). Our study provides an overview of the expression profiles of radioresistant lncRNAs and potentially related mRNAs, which will facilitate future investigations into the

Deep sequencing uncovers commonality in small RNA profiles between transgene-induced and naturally occurring RNA silencing of chalcone synthase-A gene in petunia.

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Kasai, Megumi; Matsumura, Hideo; Yoshida, Kentaro; Terauchi, Ryohei; Taneda, Akito; Kanazawa, Akira

2013-01-30

Introduction of a transgene that transcribes RNA homologous to an endogenous gene in the plant genome can induce silencing of both genes, a phenomenon termed cosuppression. Cosuppression was first discovered in transgenic petunia plants transformed with the CHS-A gene encoding chalcone synthase, in which nonpigmented sectors in flowers or completely white flowers are produced. Some of the flower-color patterns observed in transgenic petunias having CHS-A cosuppression resemble those in existing nontransgenic varieties. Although the mechanism by which white sectors are generated in nontransgenic petunia is known to be due to RNA silencing of the CHS-A gene as in cosuppression, whether the same trigger(s) and/or pattern of RNA degradation are involved in these phenomena has not been known. Here, we addressed this question using deep-sequencing and bioinformatic analyses of small RNAs. We analyzed short interfering RNAs (siRNAs) produced in nonpigmented sectors of petal tissues in transgenic petunia plants that have CHS-A cosuppression and a nontransgenic petunia variety Red Star, that has naturally occurring CHS-A RNA silencing. In both silencing systems, 21-nt and 22-nt siRNAs were the most and the second-most abundant size classes, respectively. CHS-A siRNA production was confined to exon 2, indicating that RNA degradation through the RNA silencing pathway occurred in this exon. Common siRNAs were detected in cosuppression and naturally occurring RNA silencing, and their ranks based on the number of siRNAs in these plants were correlated with each other. Noticeably, highly abundant siRNAs were common in these systems. Phased siRNAs were detected in multiple phases at multiple sites, and some of the ends of the regions that produced phased siRNAs were conserved. The features of siRNA production found to be common to cosuppression and naturally occurring silencing of the CHS-A gene indicate mechanistic similarities between these silencing systems especially in the

A comprehensive survey of 3' animal miRNA modification events and a possible role for 3' adenylation in modulating miRNA targeting effectiveness.

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Burroughs, A Maxwell; Ando, Yoshinari; de Hoon, Michiel J L; Tomaru, Yasuhiro; Nishibu, Takahiro; Ukekawa, Ryo; Funakoshi, Taku; Kurokawa, Tsutomu; Suzuki, Harukazu; Hayashizaki, Yoshihide; Daub, Carsten O

2010-10-01

Animal microRNA sequences are subject to 3' nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3' adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1-EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3' addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3' adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake.

Population-genomic variation within RNA viruses of the Western honey bee, Apis mellifera, inferred from deep sequencing.

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Cornman, Robert Scott; Boncristiani, Humberto; Dainat, Benjamin; Chen, Yanping; vanEngelsdorp, Dennis; Weaver, Daniel; Evans, Jay D

2013-03-07

Deep sequencing of viruses isolated from infected hosts is an efficient way to measure population-genetic variation and can reveal patterns of dispersal and natural selection. In this study, we mined existing Illumina sequence reads to investigate single-nucleotide polymorphisms (SNPs) within two RNA viruses of the Western honey bee (Apis mellifera), deformed wing virus (DWV) and Israel acute paralysis virus (IAPV). All viral RNA was extracted from North American samples of honey bees or, in one case, the ectoparasitic mite Varroa destructor. Coverage depth was generally lower for IAPV than DWV, and marked gaps in coverage occurred in several narrow regions (selection. The Kakugo strain of DWV fell outside of all other DWV sequences at 100% bootstrap support. IAPV consensus sequences supported the existence of multiple clades as had been previously reported, and Fu and Li's D was closer to neutral expectation overall, although a sliding-window analysis identified a significantly positive D within the protease region, suggesting selection maintains diversity in that region. Within-sample mean diversity was comparable between the two viruses on average, although for both viruses there was substantial variation among samples in mean diversity at third codon positions and in the number of high-diversity sites. FST values were bimodal for DWV, likely reflecting neutral divergence in two low-diversity populations, whereas IAPV had several sites that were strong outliers with very low FST. This initial survey of genetic variation within honey bee RNA viruses suggests future directions for studies examining the underlying causes of population-genetic structure in these economically important pathogens.

Identification of microRNA-Like RNAs in the filamentous fungus Trichoderma reesei by solexa sequencing.

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Kang Kang

Full Text Available microRNAs (miRNAs are non-coding small RNAs (sRNAs capable of negatively regulating gene expression. Recently, microRNA-like small RNAs (milRNAs were discovered in several filamentous fungi but not yet in Trichoderma reesei, an industrial filamentous fungus that can secrete abundant hydrolases. To explore the presence of milRNA in T. reesei and evaluate their expression under induction of cellulose, two T. reesei sRNA libraries of cellulose induction (IN and non-induction (CON were generated and sequenced using Solexa sequencing technology. A total of 726 and 631 sRNAs were obtained from the IN and CON samples, respectively. Global expression analysis showed an extensively differential expression of sRNAs in T. reesei under the two conditions. Thirteen predicted milRNAs were identified in T. reesei based on the short hairpin structure analysis. The milRNA profiles obtained in deep sequencing were further validated by RT-qPCR assay. Computational analysis predicted a number of potential targets relating to many processes including regulation of enzyme expression. The presence and differential expression of T. reesei milRNAs imply that milRNA might play a role in T. reesei growth and cellulase induction. This work lays foundation for further functional study of fungal milRNAs and their industrial application.

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

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Juan, Li; Tong, Hong-li; Zhang, Pengjun; Guo, Guanghong; Wang, Zi; Wen, Xinyu; Dong, Zhennan; Tian, Ya-ping

2014-09-03

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

Expression profiles of mRNA and long noncoding RNA in the ovaries of letrozole-induced polycystic ovary syndrome rat model through deep sequencing.

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Fu, Lu-Lu; Xu, Ying; Li, Dan-Dan; Dai, Xiao-Wei; Xu, Xin; Zhang, Jing-Shun; Ming, Hao; Zhang, Xue-Ying; Zhang, Guo-Qing; Ma, Ya-Lan; Zheng, Lian-Wen

2018-05-30

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in reproductive-aged women. However, the exact pathophysiology of PCOS remains largely unclear. We performed deep sequencing to investigate the mRNA and long noncoding RNA (lncRNA) expression profiles in the ovarian tissues of letrozole-induced PCOS rat model and control rats. A total of 2147 mRNAs and 158 lncRNAs were differentially expressed between the PCOS models and control. Gene ontology analysis indicated that differentially expressed mRNAs were associated with biological adhesion, reproduction, and metabolic process. Pathway analysis results indicated that these aberrantly expressed mRNAs were related to several specific signaling pathways, including insulin resistance, steroid hormone biosynthesis, PPAR signaling pathway, cell adhesion molecules, autoimmune thyroid disease, and AMPK signaling pathway. The relative expression levels of mRNAs and lncRNAs were validated through qRT-PCR. LncRNA-miRNA-mRNA network was constructed to explore ceRNAs involved in the PCOS model and were also verified by qRTPCR experiment. These findings may provide insight into the pathogenesis of PCOS and clues to find key diagnostic and therapeutic roles of lncRNA in PCOS. Copyright © 2018 Elsevier B.V. All rights reserved.

Transcriptional Slippage and RNA Editing Increase the Diversity of Transcripts in Chloroplasts: Insight from Deep Sequencing of Vigna radiata Genome and Transcriptome.

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Ching-Ping Lin

Full Text Available We performed deep sequencing of the nuclear and organellar genomes of three mungbean genotypes: Vigna radiata ssp. sublobata TC1966, V. radiata var. radiata NM92 and the recombinant inbred line RIL59 derived from a cross between TC1966 and NM92. Moreover, we performed deep sequencing of the RIL59 transcriptome to investigate transcript variability. The mungbean chloroplast genome has a quadripartite structure including a pair of inverted repeats separated by two single copy regions. A total of 213 simple sequence repeats were identified in the chloroplast genomes of NM92 and RIL59; 78 single nucleotide variants and nine indels were discovered in comparing the chloroplast genomes of TC1966 and NM92. Analysis of the mungbean chloroplast transcriptome revealed mRNAs that were affected by transcriptional slippage and RNA editing. Transcriptional slippage frequency was positively correlated with the length of simple sequence repeats of the mungbean chloroplast genome (R2=0.9911. In total, 41 C-to-U editing sites were found in 23 chloroplast genes and in one intergenic spacer. No editing site that swapped U to C was found. A combination of bioinformatics and experimental methods revealed that the plastid-encoded RNA polymerase-transcribed genes psbF and ndhA are affected by transcriptional slippage in mungbean and in main lineages of land plants, including three dicots (Glycine max, Brassica rapa, and Nicotiana tabacum, two monocots (Oryza sativa and Zea mays, two gymnosperms (Pinus taeda and Ginkgo biloba and one moss (Physcomitrella patens. Transcript analysis of the rps2 gene showed that transcriptional slippage could affect transcripts at single sequence repeat regions with poly-A runs. It showed that transcriptional slippage together with incomplete RNA editing may cause sequence diversity of transcripts in chloroplasts of land plants.

A comprehensive survey of 3′ animal miRNA modification events and a possible role for 3′ adenylation in modulating miRNA targeting effectiveness

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Burroughs, A. Maxwell; Ando, Yoshinari; de Hoon, Michiel J.L.; Tomaru, Yasuhiro; Nishibu, Takahiro; Ukekawa, Ryo; Funakoshi, Taku; Kurokawa, Tsutomu; Suzuki, Harukazu; Hayashizaki, Yoshihide; Daub, Carsten O.

2010-01-01

Animal microRNA sequences are subject to 3′ nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3′ adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1–EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3′ addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3′ adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake. PMID:20719920

Nicotiana small RNA sequences support a host genome origin of cucumber mosaic virus satellite RNA.

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Kiran Zahid

2015-01-01

Full Text Available Satellite RNAs (satRNAs are small noncoding subviral RNA pathogens in plants that depend on helper viruses for replication and spread. Despite many decades of research, the origin of satRNAs remains unknown. In this study we show that a β-glucuronidase (GUS transgene fused with a Cucumber mosaic virus (CMV Y satellite RNA (Y-Sat sequence (35S-GUS:Sat was transcriptionally repressed in N. tabacum in comparison to a 35S-GUS transgene that did not contain the Y-Sat sequence. This repression was not due to DNA methylation at the 35S promoter, but was associated with specific DNA methylation at the Y-Sat sequence. Both northern blot hybridization and small RNA deep sequencing detected 24-nt siRNAs in wild-type Nicotiana plants with sequence homology to Y-Sat, suggesting that the N. tabacum genome contains Y-Sat-like sequences that give rise to 24-nt sRNAs capable of guiding RNA-directed DNA methylation (RdDM to the Y-Sat sequence in the 35S-GUS:Sat transgene. Consistent with this, Southern blot hybridization detected multiple DNA bands in Nicotiana plants that had sequence homology to Y-Sat, suggesting that Y-Sat-like sequences exist in the Nicotiana genome as repetitive DNA, a DNA feature associated with 24-nt sRNAs. Our results point to a host genome origin for CMV satRNAs, and suggest novel approach of using small RNA sequences for finding the origin of other satRNAs.

Simultaneous identification of DNA and RNA viruses present in pig faeces using process-controlled deep sequencing.

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Jana Sachsenröder

Full Text Available BACKGROUND: Animal faeces comprise a community of many different microorganisms including bacteria and viruses. Only scarce information is available about the diversity of viruses present in the faeces of pigs. Here we describe a protocol, which was optimized for the purification of the total fraction of viral particles from pig faeces. The genomes of the purified DNA and RNA viruses were simultaneously amplified by PCR and subjected to deep sequencing followed by bioinformatic analyses. The efficiency of the method was monitored using a process control consisting of three bacteriophages (T4, M13 and MS2 with different morphology and genome types. Defined amounts of the bacteriophages were added to the sample and their abundance was assessed by quantitative PCR during the preparation procedure. RESULTS: The procedure was applied to a pooled faecal sample of five pigs. From this sample, 69,613 sequence reads were generated. All of the added bacteriophages were identified by sequence analysis of the reads. In total, 7.7% of the reads showed significant sequence identities with published viral sequences. They mainly originated from bacteriophages (73.9% and mammalian viruses (23.9%; 0.8% of the sequences showed identities to plant viruses. The most abundant detected porcine viruses were kobuvirus, rotavirus C, astrovirus, enterovirus B, sapovirus and picobirnavirus. In addition, sequences with identities to the chimpanzee stool-associated circular ssDNA virus were identified. Whole genome analysis indicates that this virus, tentatively designated as pig stool-associated circular ssDNA virus (PigSCV, represents a novel pig virus. CONCLUSION: The established protocol enables the simultaneous detection of DNA and RNA viruses in pig faeces including the identification of so far unknown viruses. It may be applied in studies investigating aetiology, epidemiology and ecology of diseases. The implemented process control serves as quality control, ensures

Using small RNA (sRNA) deep sequencing to understand global virus distribution in plants

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Small RNAs (sRNAs), a class of regulatory RNAs, have been used to serve as the specificity determinants of suppressing gene expression in plants and animals. Next generation sequencing (NGS) uncovered the sRNA landscape in most organisms including their associated microbes. In the current study, w...

Small RNA Deep Sequencing and the Effects of microRNA408 on Root Gravitropic Bending in Arabidopsis

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Li, Huasheng; Lu, Jinying; Sun, Qiao; Chen, Yu; He, Dacheng; Liu, Min

2015-11-01

MicroRNA (miRNA) is a non-coding small RNA composed of 20 to 24 nucleotides that influences plant root development. This study analyzed the miRNA expression in Arabidopsis root tip cells using Illumina sequencing and real-time PCR before (sample 0) and 15 min after (sample 15) a 3-D clinostat rotational treatment was administered. After stimulation was performed, the expression levels of seven miRNA genes, including Arabidopsis miR160, miR161, miR394, miR402, miR403, miR408, and miR823, were significantly upregulated. Illumina sequencing results also revealed two novel miRNAsthat have not been previously reported, The target genes of these miRNAs included pentatricopeptide repeat-containing protein and diadenosine tetraphosphate hydrolase. An overexpression vector of Arabidopsis miR408 was constructed and transferred to Arabidopsis plant. The roots of plants over expressing miR408 exhibited a slower reorientation upon gravistimulation in comparison with those of wild-type. This result indicate that miR408 could play a role in root gravitropic response.

MicroRNAs in Amoebozoa: deep sequencing of the small RNA population in the social amoeba Dictyostelium discoideum reveals developmentally regulated microRNAs.

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Avesson, Lotta; Reimegård, Johan; Wagner, E Gerhart H; Söderbom, Fredrik

2012-10-01

The RNA interference machinery has served as a guardian of eukaryotic genomes since the divergence from prokaryotes. Although the basic components have a shared origin, silencing pathways directed by small RNAs have evolved in diverse directions in different eukaryotic lineages. Micro (mi)RNAs regulate protein-coding genes and play vital roles in plants and animals, but less is known about their functions in other organisms. Here, we report, for the first time, deep sequencing of small RNAs from the social amoeba Dictyostelium discoideum. RNA from growing single-cell amoebae as well as from two multicellular developmental stages was sequenced. Computational analyses combined with experimental data reveal the expression of miRNAs, several of them exhibiting distinct expression patterns during development. To our knowledge, this is the first report of miRNAs in the Amoebozoa supergroup. We also show that overexpressed miRNA precursors generate miRNAs and, in most cases, miRNA* sequences, whose biogenesis is dependent on the Dicer-like protein DrnB, further supporting the presence of miRNAs in D. discoideum. In addition, we find miRNAs processed from hairpin structures originating from an intron as well as from a class of repetitive elements. We believe that these repetitive elements are sources for newly evolved miRNAs.

Nuclear RNA sequencing of the mouse erythroid cell transcriptome.

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Jennifer A Mitchell

Full Text Available In addition to protein coding genes a substantial proportion of mammalian genomes are transcribed. However, most transcriptome studies investigate steady-state mRNA levels, ignoring a considerable fraction of the transcribed genome. In addition, steady-state mRNA levels are influenced by both transcriptional and posttranscriptional mechanisms, and thus do not provide a clear picture of transcriptional output. Here, using deep sequencing of nuclear RNAs (nucRNA-Seq in parallel with chromatin immunoprecipitation sequencing (ChIP-Seq of active RNA polymerase II, we compared the nuclear transcriptome of mouse anemic spleen erythroid cells with polymerase occupancy on a genome-wide scale. We demonstrate that unspliced transcripts quantified by nucRNA-seq correlate with primary transcript frequencies measured by RNA FISH, but differ from steady-state mRNA levels measured by poly(A-enriched RNA-seq. Highly expressed protein coding genes showed good correlation between RNAPII occupancy and transcriptional output; however, genome-wide we observed a poor correlation between transcriptional output and RNAPII association. This poor correlation is due to intergenic regions associated with RNAPII which correspond with transcription factor bound regulatory regions and a group of stable, nuclear-retained long non-coding transcripts. In conclusion, sequencing the nuclear transcriptome provides an opportunity to investigate the transcriptional landscape in a given cell type through quantification of unspliced primary transcripts and the identification of nuclear-retained long non-coding RNAs.

antaRNA: ant colony-based RNA sequence design.

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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.

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

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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/.

MicroRNA of the fifth-instar posterior silk gland of silkworm identified by Solexa sequencing

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Jisheng Li

2014-12-01

Full Text Available No special studies have been focused on the microRNA (miRNA in the fifth-instar posterior silk gland of Bombyx mori. Here, using next-generation sequencing, we acquired 93.2 million processed reads from 10 small RNA libraries. In this paper, we tried to thoroughly describe how our dataset generated from deep sequencing which was recently published in BMC genomics. Results showed that our findings are largely enriched silkworm miRNA depository and may benefit us to reveal the miRNA functions in the process of silk production.

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

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Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

MicroRNA identity and abundance in porcine skeletal muscles determined by deep sequencing

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Nielsen, M; Hansen, J H; Hedegaard, J

2010-01-01

levels of 212 annotated miRNA genes, thereby providing a thorough account of the miRNA transcriptome in porcine muscle tissue. The expression levels displayed a very large range, as reflected by the number of sequence reads, which varied from single counts for rare miRNAs to several million reads...

Deep RNA sequencing reveals dynamic regulation of myocardial noncoding RNAs in failing human heart and remodeling with mechanical circulatory support.

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Yang, Kai-Chien; Yamada, Kathryn A; Patel, Akshar Y; Topkara, Veli K; George, Isaac; Cheema, Faisal H; Ewald, Gregory A; Mann, Douglas L; Nerbonne, Jeanne M

2014-03-04

Microarrays have been used extensively to profile transcriptome remodeling in failing human heart, although the genomic coverage provided is limited and fails to provide a detailed picture of the myocardial transcriptome landscape. Here, we describe sequencing-based transcriptome profiling, providing comprehensive analysis of myocardial mRNA, microRNA (miRNA), and long noncoding RNA (lncRNA) expression in failing human heart before and after mechanical support with a left ventricular (LV) assist device (LVAD). Deep sequencing of RNA isolated from paired nonischemic (NICM; n=8) and ischemic (ICM; n=8) human failing LV samples collected before and after LVAD and from nonfailing human LV (n=8) was conducted. These analyses revealed high abundance of mRNA (37%) and lncRNA (71%) of mitochondrial origin. miRNASeq revealed 160 and 147 differentially expressed miRNAs in ICM and NICM, respectively, compared with nonfailing LV. Among these, only 2 (ICM) and 5 (NICM) miRNAs are normalized with LVAD. RNASeq detected 18 480, including 113 novel, lncRNAs in human LV. Among the 679 (ICM) and 570 (NICM) lncRNAs differentially expressed with heart failure, ≈10% are improved or normalized with LVAD. In addition, the expression signature of lncRNAs, but not miRNAs or mRNAs, distinguishes ICM from NICM. Further analysis suggests that cis-gene regulation represents a major mechanism of action of human cardiac lncRNAs. The myocardial transcriptome is dynamically regulated in advanced heart failure and after LVAD support. The expression profiles of lncRNAs, but not mRNAs or miRNAs, can discriminate failing hearts of different pathologies and are markedly altered in response to LVAD support. These results suggest an important role for lncRNAs in the pathogenesis of heart failure and in reverse remodeling observed with mechanical support.

Integrated mRNA and microRNA transcriptome sequencing characterizes sequence variants and mRNA–microRNA regulatory network in nasopharyngeal carcinoma model systems

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Carol Ying-Ying Szeto

2014-01-01

Full Text Available Nasopharyngeal carcinoma (NPC is a prevalent malignancy in Southeast Asia among the Chinese population. Aberrant regulation of transcripts has been implicated in many types of cancers including NPC. Herein, we characterized mRNA and miRNA transcriptomes by RNA sequencing (RNASeq of NPC model systems. Matched total mRNA and small RNA of undifferentiated Epstein–Barr virus (EBV-positive NPC xenograft X666 and its derived cell line C666, well-differentiated NPC cell line HK1, and the immortalized nasopharyngeal epithelial cell line NP460 were sequenced by Solexa technology. We found 2812 genes and 149 miRNAs (human and EBV to be differentially expressed in NP460, HK1, C666 and X666 with RNASeq; 533 miRNA–mRNA target pairs were inversely regulated in the three NPC cell lines compared to NP460. Integrated mRNA/miRNA expression profiling and pathway analysis show extracellular matrix organization, Beta-1 integrin cell surface interactions, and the PI3K/AKT, EGFR, ErbB, and Wnt pathways were potentially deregulated in NPC. Real-time quantitative PCR was performed on selected mRNA/miRNAs in order to validate their expression. Transcript sequence variants such as short insertions and deletions (INDEL, single nucleotide variant (SNV, and isomiRs were characterized in the NPC model systems. A novel TP53 transcript variant was identified in NP460, HK1, and C666. Detection of three previously reported novel EBV-encoded BART miRNAs and their isomiRs were also observed. Meta-analysis of a model system to a clinical system aids the choice of different cell lines in NPC studies. This comprehensive characterization of mRNA and miRNA transcriptomes in NPC cell lines and the xenograft provides insights on miRNA regulation of mRNA and valuable resources on transcript variation and regulation in NPC, which are potentially useful for mechanistic and preclinical studies.

Comparative analysis of transcriptomes in aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing

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Taketo Okada

2016-12-01

Full Text Available Ephedra plants are taxonomically classified as gymnosperms, and are medicinally important as the botanical origin of crude drugs and as bioresources that contain pharmacologically active chemicals. Here we show a comparative analysis of the transcriptomes of aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing by RNA-Seq. De novo assembly of short cDNA sequence reads generated 23,358, 13,373, and 28,579 contigs longer than 200 bases from aerial stems, roots, or both aerial stems and roots, respectively. The presumed functions encoded by these contig sequences were annotated by BLAST (blastx. Subsequently, these contigs were classified based on gene ontology slims, Enzyme Commission numbers, and the InterPro database. Furthermore, comparative gene expression analysis was performed between aerial stems and roots. These transcriptome analyses revealed differences and similarities between the transcriptomes of aerial stems and roots in E. sinica. Deep transcriptome sequencing of Ephedra should open the door to molecular biological studies based on the entire transcriptome, tissue- or organ-specific transcriptomes, or targeted genes of interest.

Phenotypic silencing of cytoplasmic genes using sequence-specific double-stranded short interfering RNA and its application in the reverse genetics of wild type negative-strand RNA viruses

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Barik Sailen

2001-12-01

Full Text Available Abstract Background Post-transcriptional gene silencing (PTGS by short interfering RNA has opened up new directions in the phenotypic mutation of cellular genes. However, its efficacy on non-nuclear genes and its effect on the interferon pathway remain unexplored. Since directed mutation of RNA genomes is not possible through conventional mutagenesis, we have tested sequence-specific 21-nucleotide long double-stranded RNAs (dsRNAs for their ability to silence cytoplasmic RNA genomes. Results Short dsRNAs were generated against specific mRNAs of respiratory syncytial virus, a nonsegmented negative-stranded RNA virus with a cytoplasmic life cycle. At nanomolar concentrations, the dsRNAs specifically abrogated expression of the corresponding viral proteins, and produced the expected mutant phenotype ex vivo. The dsRNAs did not induce an interferon response, and did not inhibit cellular gene expression. The ablation of the viral proteins correlated with the loss of the specific mRNAs. In contrast, viral genomic and antigenomic RNA, which are encapsidated, were not directly affected. Conclusions Synthetic inhibitory dsRNAs are effective in specific silencing of RNA genomes that are exclusively cytoplasmic and transcribed by RNA-dependent RNA polymerases. RNA-directed RNA gene silencing does not require cloning, expression, and mutagenesis of viral cDNA, and thus, will allow the generation of phenotypic null mutants of specific RNA viral genes under normal infection conditions and at any point in the infection cycle. This will, for the first time, permit functional genomic studies, attenuated infections, reverse genetic analysis, and studies of host-virus signaling pathways using a wild type RNA virus, unencumbered by any superinfecting virus.

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments.

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Hackenberg, Michael; Sturm, Martin; Langenberger, David; Falcón-Pérez, Juan Manuel; Aransay, Ana M

2009-07-01

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/.

Directional RNA deep sequencing sheds new light on the transcriptional response of Anabaena sp. strain PCC 7120 to combined-nitrogen deprivation

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Head Steven R

2011-06-01

Full Text Available Abstract Background Cyanobacteria are potential sources of renewable chemicals and biofuels and serve as model organisms for bacterial photosynthesis, nitrogen fixation, and responses to environmental changes. Anabaena (Nostoc sp. strain PCC 7120 (hereafter Anabaena is a multicellular filamentous cyanobacterium that can "fix" atmospheric nitrogen into ammonia when grown in the absence of a source of combined nitrogen. Because the nitrogenase enzyme is oxygen sensitive, Anabaena forms specialized cells called heterocysts that create a microoxic environment for nitrogen fixation. We have employed directional RNA-seq to map the Anabaena transcriptome during vegetative cell growth and in response to combined-nitrogen deprivation, which induces filaments to undergo heterocyst development. Our data provide an unprecedented view of transcriptional changes in Anabaena filaments during the induction of heterocyst development and transition to diazotrophic growth. Results Using the Illumina short read platform and a directional RNA-seq protocol, we obtained deep sequencing data for RNA extracted from filaments at 0, 6, 12, and 21 hours after the removal of combined nitrogen. The RNA-seq data provided information on transcript abundance and boundaries for the entire transcriptome. From these data, we detected novel antisense transcripts within the UTRs (untranslated regions and coding regions of key genes involved in heterocyst development, suggesting that antisense RNAs may be important regulators of the nitrogen response. In addition, many 5' UTRs were longer than anticipated, sometimes extending into upstream open reading frames (ORFs, and operons often showed complex structure and regulation. Finally, many genes that had not been previously identified as being involved in heterocyst development showed regulation, providing new candidates for future studies in this model organism. Conclusions Directional RNA-seq data were obtained that provide

High throughput 16S rRNA gene amplicon sequencing

DEFF Research Database (Denmark)

Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

Direct, rapid RNA sequence analysis

International Nuclear Information System (INIS)

Peattie, D.A.

1987-01-01

The original methods of RNA sequence analysis were based on enzymatic production and chromatographic separation of overlapping oligonucleotide fragments from within an RNA molecule followed by identification of the mononucleotides comprising the oligomer. Over the past decade the field of nucleic acid sequencing has changed dramatically, however, and RNA molecules now can be sequenced in a variety of more streamlined fashions. Most of the more recent advances in RNA sequencing have involved one-dimensional electrophoretic separation of 32 P-end-labeled oligoribonucleotides on polyacrylamide gels. In this chapter the author discusses two of these methods for determining the nucleotide sequences of RNA molecules rapidly: the chemical method and the enzymatic method. Both methods are direct and degradative, i.e., they rely on fragmatic and chemical approaches should be utilized. The single-strand-specific ribonucleases (A, T 1 , T 2 , and S 1 ) provide an efficient means to locate double-helical regions rapidly, and the chemical reactions provide a means to determine the RNA sequence within these regions. In addition, the chemical reactions allow one to assign interactions to specific atoms and to distinguish secondary interactions from tertiary ones. If the RNA molecule is small enough to be sequenced directly by the enzymatic or chemical method, the probing reactions can be done easily at the same time as sequencing reactions

sRNAnalyzer-a flexible and customizable small RNA sequencing data analysis pipeline.

Science.gov (United States)

Wu, Xiaogang; Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J; Wang, Kai

2017-12-01

Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline-sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

sRNAnalyzer—a flexible and customizable small RNA sequencing data analysis pipeline

Science.gov (United States)

Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J.

2017-01-01

Abstract Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline—sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/. PMID:29069500

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

Science.gov (United States)

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.

Identification of miRNAs and their target genes in developing soybean seeds by deep sequencing

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Chen Shou-Yi

2011-01-01

Full Text Available Abstract Background MicroRNAs (miRNAs regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in higher plants. miRNAs and related target genes have been widely studied in model plants such as Arabidopsis and rice; however, the number of identified miRNAs in soybean (Glycine max is limited, and global identification of the related miRNA targets has not been reported in previous research. Results In our study, a small RNA library and a degradome library were constructed from developing soybean seeds for deep sequencing. We identified 26 new miRNAs in soybean by bioinformatic analysis and further confirmed their expression by stem-loop RT-PCR. The miRNA star sequences of 38 known miRNAs and 8 new miRNAs were also discovered, providing additional evidence for the existence of miRNAs. Through degradome sequencing, 145 and 25 genes were identified as targets of annotated miRNAs and new miRNAs, respectively. GO analysis indicated that many of the identified miRNA targets may function in soybean seed development. Additionally, a soybean homolog of Arabidopsis SUPPRESSOR OF GENE SLIENCING 3 (AtSGS3 was detected as a target of the newly identified miRNA Soy_25, suggesting the presence of feedback control of miRNA biogenesis. Conclusions We have identified large numbers of miRNAs and their related target genes through deep sequencing of a small RNA library and a degradome library. Our study provides more information about the regulatory network of miRNAs in soybean and advances our understanding of miRNA functions during seed development.

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

Short Hairpin RNA (shRNA): Design, Delivery, and Assessment of Gene Knockdown

Science.gov (United States)

Moore, Chris B.; Guthrie, Elizabeth H.; Huang, Max Tze-Han; Taxman, Debra J.

2013-01-01

Shortly after the cellular mechanism of RNA interference (RNAi) was first described, scientists began using this powerful technique to study gene function. This included designing better methods for the successful delivery of small interfering RNAs (siRNAs) and short hairpin RNAs (shRNAs) into mammalian cells. While the simplest method for RNAi is the cytosolic delivery of siRNA oligonucleotides, this technique is limited to cells capable of transfection and is primarily utilized during transient in vitro studies. The introduction of shRNA into mammalian cells through infection with viral vectors allows for stable integration of shRNA and long-term knockdown of the targeted gene; however, several challenges exist with the implementation of this technology. Here we describe some well-tested protocols which should increase the chances of successful design, delivery, and assessment of gene knockdown by shRNA. We provide suggestions for designing shRNA targets and controls, a protocol for sequencing through the secondary structure of the shRNA hairpin structure, and protocols for packaging and delivery of shRNA lentiviral particles. Using real-time PCR and functional assays we demonstrate the successful knockdown of ASC, an inflammatory adaptor molecule. These studies demonstrate the practicality of including two shRNAs with different efficacies of knockdown to provide an additional level of control and to verify dose dependency of functional effects. Along with the methods described here, as new techniques and algorithms are designed in the future, shRNA is likely to include further promising application and continue to be a critical component of gene discovery. PMID:20387148

Sequence-specific RNA Photocleavage by Single-stranded DNA in Presence of Riboflavin

Science.gov (United States)

Zhao, Yongyun; Chen, Gangyi; Yuan, Yi; Li, Na; Dong, Juan; Huang, Xin; Cui, Xin; Tang, Zhuo

2015-10-01

Constant efforts have been made to develop new method to realize sequence-specific RNA degradation, which could cause inhibition of the expression of targeted gene. Herein, by using an unmodified short DNA oligonucleotide for sequence recognition and endogenic small molecue, vitamin B2 (riboflavin) as photosensitizer, we report a simple strategy to realize the sequence-specific photocleavage of targeted RNA. The DNA strand is complimentary to the target sequence to form DNA/RNA duplex containing a G•U wobble in the middle. The cleavage reaction goes through oxidative elimination mechanism at the nucleoside downstream of U of the G•U wobble in duplex to obtain unnatural RNA terminal, and the whole process is under tight control by using light as switch, which means the cleavage could be carried out according to specific spatial and temporal requirements. The biocompatibility of this method makes the DNA strand in combination with riboflavin a promising molecular tool for RNA manipulation.

Optimizing de novo common wheat transcriptome assembly using short-read RNA-Seq data

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Duan Jialei

2012-08-01

Full Text Available Abstract Background Rapid advances in next-generation sequencing methods have provided new opportunities for transcriptome sequencing (RNA-Seq. The unprecedented sequencing depth provided by RNA-Seq makes it a powerful and cost-efficient method for transcriptome study, and it has been widely used in model organisms and non-model organisms to identify and quantify RNA. For non-model organisms lacking well-defined genomes, de novo assembly is typically required for downstream RNA-Seq analyses, including SNP discovery and identification of genes differentially expressed by phenotypes. Although RNA-Seq has been successfully used to sequence many non-model organisms, the results of de novo assembly from short reads can still be improved by using recent bioinformatic developments. Results In this study, we used 212.6 million pair-end reads, which accounted for 16.2 Gb, to assemble the hexaploid wheat transcriptome. Two state-of-the-art assemblers, Trinity and Trans-ABySS, which use the single and multiple k-mer methods, respectively, were used, and the whole de novo assembly process was divided into the following four steps: pre-assembly, merging different samples, removal of redundancy and scaffolding. We documented every detail of these steps and how these steps influenced assembly performance to gain insight into transcriptome assembly from short reads. After optimization, the assembled transcripts were comparable to Sanger-derived ESTs in terms of both continuity and accuracy. We also provided considerable new wheat transcript data to the community. Conclusions It is feasible to assemble the hexaploid wheat transcriptome from short reads. Special attention should be paid to dealing with multiple samples to balance the spectrum of expression levels and redundancy. To obtain an accurate overview of RNA profiling, removal of redundancy may be crucial in de novo assembly.

DeepSimulator: a deep simulator for Nanopore sequencing

KAUST Repository

Li, Yu

2017-12-23

Motivation: Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals. Results: Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. Availability: The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

A short autocomplementary sequence plays an essential role in avian sarcoma-leukosis virus RNA dimerization.

Science.gov (United States)

Fossé, P; Motté, N; Roumier, A; Gabus, C; Muriaux, D; Darlix, J L; Paoletti, J

1996-12-24

Retroviral genomes consist of two identical RNA molecules joined noncovalently near their 5'-ends. Recently, two models have been proposed for RNA dimer formation on the basis of results obtained in vitro with human immunodeficiency virus type 1 RNA and Moloney murine leukemia virus RNA. It was first proposed that viral RNA dimerizes by forming an interstrand quadruple helix with purine tetrads. The second model postulates that RNA dimerization is initiated by a loop-loop interaction between the two RNA molecules. In order to better characterize the dimerization process of retroviral genomic RNA, we analyzed the in vitro dimerization of avian sarcoma-leukosis virus (ASLV) RNA using different transcripts. We determined the requirements for heterodimer formation, the thermal dissociation of RNA dimers, and the influence of antisense DNA oligonucleotides on dimer formation. Our results strongly suggest that purine tetrads are not involved in dimer formation. Data show that an autocomplementary sequence located upstream from the splice donor site and within a major packaging signal plays a crucial role in ASLV RNA dimer formation in vitro. This sequence is able to form a stem-loop structure, and phylogenetic analysis reveals that it is conserved in 28 different avian sarcoma and leukosis viruses. These results suggest that dimerization of ASLV RNA is initiated by a loop-loop interaction between two RNA molecules and provide an additional argument for the ubiquity of the dimerization process via loop-loop interaction.

miRDis: a Web tool for endogenous and exogenous microRNA discovery based on deep-sequencing data analysis.

Science.gov (United States)

Zhang, Hanyuan; Vieira Resende E Silva, Bruno; Cui, Juan

2018-05-01

Small RNA sequencing is the most widely used tool for microRNA (miRNA) discovery, and shows great potential for the efficient study of miRNA cross-species transport, i.e., by detecting the presence of exogenous miRNA sequences in the host species. Because of the increased appreciation of dietary miRNAs and their far-reaching implication in human health, research interests are currently growing with regard to exogenous miRNAs bioavailability, mechanisms of cross-species transport and miRNA function in cellular biological processes. In this article, we present microRNA Discovery (miRDis), a new small RNA sequencing data analysis pipeline for both endogenous and exogenous miRNA detection. Specifically, we developed and deployed a Web service that supports the annotation and expression profiling data of known host miRNAs and the detection of novel miRNAs, other noncoding RNAs, and the exogenous miRNAs from dietary species. As a proof-of-concept, we analyzed a set of human plasma sequencing data from a milk-feeding study where 225 human miRNAs were detected in the plasma samples and 44 show elevated expression after milk intake. By examining the bovine-specific sequences, data indicate that three bovine miRNAs (bta-miR-378, -181* and -150) are present in human plasma possibly because of the dietary uptake. Further evaluation based on different sets of public data demonstrates that miRDis outperforms other state-of-the-art tools in both detection and quantification of miRNA from either animal or plant sources. The miRDis Web server is available at: http://sbbi.unl.edu/miRDis/index.php.

Analysis of microRNA profile of Anopheles sinensis by deep sequencing and bioinformatic approaches.

Science.gov (United States)

Feng, Xinyu; Zhou, Xiaojian; Zhou, Shuisen; Wang, Jingwen; Hu, Wei

2018-03-12

microRNAs (miRNAs) are small non-coding RNAs widely identified in many mosquitoes. They are reported to play important roles in development, differentiation and innate immunity. However, miRNAs in Anopheles sinensis, one of the Chinese malaria mosquitoes, remain largely unknown. We investigated the global miRNA expression profile of An. sinensis using Illumina Hiseq 2000 sequencing. Meanwhile, we applied a bioinformatic approach to identify potential miRNAs in An. sinensis. The identified miRNA profiles were compared and analyzed by two approaches. The selected miRNAs from the sequencing result and the bioinformatic approach were confirmed with qRT-PCR. Moreover, target prediction, GO annotation and pathway analysis were carried out to understand the role of miRNAs in An. sinensis. We identified 49 conserved miRNAs and 12 novel miRNAs by next-generation high-throughput sequencing technology. In contrast, 43 miRNAs were predicted by the bioinformatic approach, of which two were assigned as novel. Comparative analysis of miRNA profiles by two approaches showed that 21 miRNAs were shared between them. Twelve novel miRNAs did not match any known miRNAs of any organism, indicating that they are possibly species-specific. Forty miRNAs were found in many mosquito species, indicating that these miRNAs are evolutionally conserved and may have critical roles in the process of life. Both the selected known and novel miRNAs (asi-miR-281, asi-miR-184, asi-miR-14, asi-miR-nov5, asi-miR-nov4, asi-miR-9383, and asi-miR-2a) could be detected by quantitative real-time PCR (qRT-PCR) in the sequenced sample, and the expression patterns of these miRNAs measured by qRT-PCR were in concordance with the original miRNA sequencing data. The predicted targets for the known and the novel miRNAs covered many important biological roles and pathways indicating the diversity of miRNA functions. We also found 21 conserved miRNAs and eight counterparts of target immune pathway genes in An. sinensis

Deep sequencing of subseafloor eukaryotic rRNA reveals active Fungi across marine subsurface provinces.

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William Orsi

Full Text Available The deep marine subsurface is a vast habitat for microbial life where cells may live on geologic timescales. Because DNA in sediments may be preserved on long timescales, ribosomal RNA (rRNA is suggested to be a proxy for the active fraction of a microbial community in the subsurface. During an investigation of eukaryotic 18S rRNA by amplicon pyrosequencing, unique profiles of Fungi were found across a range of marine subsurface provinces including ridge flanks, continental margins, and abyssal plains. Subseafloor fungal populations exhibit statistically significant correlations with total organic carbon (TOC, nitrate, sulfide, and dissolved inorganic carbon (DIC. These correlations are supported by terminal restriction length polymorphism (TRFLP analyses of fungal rRNA. Geochemical correlations with fungal pyrosequencing and TRFLP data from this geographically broad sample set suggests environmental selection of active Fungi in the marine subsurface. Within the same dataset, ancient rRNA signatures were recovered from plants and diatoms in marine sediments ranging from 0.03 to 2.7 million years old, suggesting that rRNA from some eukaryotic taxa may be much more stable than previously considered in the marine subsurface.

Quantitative phenotyping via deep barcode sequencing.

Science.gov (United States)

Smith, Andrew M; Heisler, Lawrence E; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J; Chee, Mark; Roth, Frederick P; Giaever, Guri; Nislow, Corey

2009-10-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or "Bar-seq," outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that approximately 20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene-environment interactions on a genome-wide scale.

On the optimal trimming of high-throughput mRNA sequence data

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Matthew D MacManes

2014-01-01

Full Text Available The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose Phred score < 2 or < 5, is optimal for most studies across a wide variety of metrics.

RNA deep sequencing reveals differential microRNA expression during development of sea urchin and sea star.

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Sabah Kadri

Full Text Available microRNAs (miRNAs are small (20-23 nt, non-coding single stranded RNA molecules that act as post-transcriptional regulators of mRNA gene expression. They have been implicated in regulation of developmental processes in diverse organisms. The echinoderms, Strongylocentrotus purpuratus (sea urchin and Patiria miniata (sea star are excellent model organisms for studying development with well-characterized transcriptional networks. However, to date, nothing is known about the role of miRNAs during development in these organisms, except that the genes that are involved in the miRNA biogenesis pathway are expressed during their developmental stages. In this paper, we used Illumina Genome Analyzer (Illumina, Inc. to sequence small RNA libraries in mixed stage population of embryos from one to three days after fertilization of sea urchin and sea star (total of 22,670,000 reads. Analysis of these data revealed the miRNA populations in these two species. We found that 47 and 38 known miRNAs are expressed in sea urchin and sea star, respectively, during early development (32 in common. We also found 13 potentially novel miRNAs in the sea urchin embryonic library. miRNA expression is generally conserved between the two species during development, but 7 miRNAs are highly expressed in only one species. We expect that our two datasets will be a valuable resource for everyone working in the field of developmental biology and the regulatory networks that affect it. The computational pipeline to analyze Illumina reads is available at http://www.benoslab.pitt.edu/services.html.

RNA Deep Sequencing Reveals Differential MicroRNA Expression during Development of Sea Urchin and Sea Star

Science.gov (United States)

Kadri, Sabah; Hinman, Veronica F.; Benos, Panayiotis V.

2011-01-01

microRNAs (miRNAs) are small (20–23 nt), non-coding single stranded RNA molecules that act as post-transcriptional regulators of mRNA gene expression. They have been implicated in regulation of developmental processes in diverse organisms. The echinoderms, Strongylocentrotus purpuratus (sea urchin) and Patiria miniata (sea star) are excellent model organisms for studying development with well-characterized transcriptional networks. However, to date, nothing is known about the role of miRNAs during development in these organisms, except that the genes that are involved in the miRNA biogenesis pathway are expressed during their developmental stages. In this paper, we used Illumina Genome Analyzer (Illumina, Inc.) to sequence small RNA libraries in mixed stage population of embryos from one to three days after fertilization of sea urchin and sea star (total of 22,670,000 reads). Analysis of these data revealed the miRNA populations in these two species. We found that 47 and 38 known miRNAs are expressed in sea urchin and sea star, respectively, during early development (32 in common). We also found 13 potentially novel miRNAs in the sea urchin embryonic library. miRNA expression is generally conserved between the two species during development, but 7 miRNAs are highly expressed in only one species. We expect that our two datasets will be a valuable resource for everyone working in the field of developmental biology and the regulatory networks that affect it. The computational pipeline to analyze Illumina reads is available at http://www.benoslab.pitt.edu/services.html. PMID:22216218

RNA polymerase II mediated transcription from the polymerase III promoters in short hairpin RNA expression vector

International Nuclear Information System (INIS)

Rumi, Mohammad; Ishihara, Shunji; Aziz, Monowar; Kazumori, Hideaki; Ishimura, Norihisa; Yuki, Takafumi; Kadota, Chikara; Kadowaki, Yasunori; Kinoshita, Yoshikazu

2006-01-01

RNA polymerase III promoters of human ribonuclease P RNA component H1, human U6, and mouse U6 small nuclear RNA genes are commonly used in short hairpin RNA (shRNA) expression vectors due their precise initiation and termination sites. During transient transfection of shRNA vectors, we observed that H1 or U6 promoters also express longer transcripts enough to express several reporter genes including firefly luciferase, green fluorescent protein EGFP, and red fluorescent protein JRed. Expression of such longer transcripts was augmented by upstream RNA polymerase II enhancers and completely inhibited by downstream polyA signal sequences. Moreover, the transcription of firefly luciferase from human H1 promoter was sensitive to RNA polymerase II inhibitor α-amanitin. Our findings suggest that commonly used polymerase III promoters in shRNA vectors are also prone to RNA polymerase II mediated transcription, which may have negative impacts on their targeted use

Characterization and Profiling of Liver microRNAs by RNA-sequencing in Cattle Divergently Selected for Residual Feed Intake

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Wijdan Al-Husseini

2016-10-01

Full Text Available MicroRNAs (miRNAs are short non-coding RNAs that post-transcriptionally regulate expression of mRNAs in many biological pathways. Liver plays an important role in the feed efficiency of animals and high and low efficient cattle demonstrated different gene expression profiles by microarray. Here we report comprehensive miRNAs profiles by next-gen deep sequencing in Angus cattle divergently selected for residual feed intake (RFI and identify miRNAs related to feed efficiency in beef cattle. Two microRNA libraries were constructed from pooled RNA extracted from livers of low and high RFI cattle, and sequenced by Illumina genome analyser. In total, 23,628,103 high quality short sequence reads were obtained and more than half of these reads were matched to the bovine genome (UMD 3.1. We identified 305 known bovine miRNAs. Bta-miR-143, bta-miR-30, bta-miR-122, bta-miR-378, and bta-let-7 were the top five most abundant miRNAs families expressed in liver, representing more than 63% of expressed miRNAs. We also identified 52 homologous miRNAs and 10 novel putative bovine-specific miRNAs, based on precursor sequence and the secondary structure and utilizing the miRBase (v. 21. We compared the miRNAs profile between high and low RFI animals and ranked the most differentially expressed bovine known miRNAs. Bovine miR-143 was the most abundant miRNA in the bovine liver and comprised 20% of total expressed mapped miRNAs. The most highly expressed miRNA in liver of mice and humans, miR-122, was the third most abundant in our cattle liver samples. We also identified 10 putative novel bovine-specific miRNA candidates. Differentially expressed miRNAs between high and low RFI cattle were identified with 18 miRNAs being up-regulated and 7 other miRNAs down-regulated in low RFI cattle. Our study has identified comprehensive miRNAs expressed in bovine liver. Some of the expressed miRNAs are novel in cattle. The differentially expressed miRNAs between high and low RFI

MicroRNA repertoire for functional genome research in tilapia identified by deep sequencing.

Science.gov (United States)

Yan, Biao; Wang, Zhen-Hua; Zhu, Chang-Dong; Guo, Jin-Tao; Zhao, Jin-Liang

2014-08-01

The Nile tilapia (Oreochromis niloticus; Cichlidae) is an economically important species in aquaculture and occupies a prominent position in the aquaculture industry. MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression involved in diverse biological and metabolic processes. To increase the repertoire of miRNAs characterized in tilapia, we used the Illumina/Solexa sequencing technology to sequence a small RNA library using pooled RNA sample isolated from the different developmental stages of tilapia. Bioinformatic analyses suggest that 197 conserved and 27 novel miRNAs are expressed in tilapia. Sequence alignments indicate that all tested miRNAs and miRNAs* are highly conserved across many species. In addition, we characterized the tissue expression patterns of five miRNAs using real-time quantitative PCR. We found that miR-1/206, miR-7/9, and miR-122 is abundantly expressed in muscle, brain, and liver, respectively, implying a potential role in the regulation of tissue differentiation or the maintenance of tissue identity. Overall, our results expand the number of tilapia miRNAs, and the discovery of miRNAs in tilapia genome contributes to a better understanding the role of miRNAs in regulating diverse biological processes.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data.

Science.gov (United States)

Luo, Guan-Zheng; Yang, Wei; Ma, Ying-Ke; Wang, Xiu-Jie

2014-02-01

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets. ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.

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

Science.gov (United States)

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.

Nucleotide sequence and genetic organization of barley stripe mosaic virus RNA gamma.

Science.gov (United States)

Gustafson, G; Hunter, B; Hanau, R; Armour, S L; Jackson, A O

1987-06-01

The complete nucleotide sequences of RNA gamma from the Type and ND18 strains of barley stripe mosaic virus (BSMV) have been determined. The sequences are 3164 (Type) and 2791 (ND18) nucleotides in length. Both sequences contain a 5'-noncoding region (87 or 88 nucleotides) which is followed by a long open reading frame (ORF1). A 42-nucleotide intercistronic region separates ORF1 from a second, shorter open reading frame (ORF2) located near the 3'-end of the RNA. There is a high degree of homology between the Type and ND18 strains in the nucleotide sequence of ORF1. However, the Type strain contains a 366 nucleotide direct tandem repeat within ORF1 which is absent in the ND18 strain. Consequently, the predicted translation product of Type RNA gamma ORF1 (mol wt 87,312) is significantly larger than that of ND18 RNA gamma ORF1 (mol wt 74,011). The amino acid sequence of the ORF1 polypeptide contains homologies with putative RNA polymerases from other RNA viruses, suggesting that this protein may function in replication of the BSMV genome. The nucleotide sequence of RNA gamma ORF2 is nearly identical in the Type and ND18 strains. ORF2 codes for a polypeptide with a predicted molecular weight of 17,209 (Type) or 17,074 (ND18) which is known to be translated from a subgenomic (sg) RNA. The initiation point of this sgRNA has been mapped to a location 27 nucleotides upstream of the ORF2 initiation codon in the intercistronic region between ORF1 and ORF2. The sgRNA is not coterminal with the 3'-end of the genomic RNA, but instead contains heterogeneous poly(A) termini up to 150 nucleotides long (J. Stanley, R. Hanau, and A. O. Jackson, 1984, Virology 139, 375-383). In the genomic RNA gamma, ORF2 is followed by a short poly(A) tract and a 238-nucleotide tRNA-like structure.

High-Resolution Analysis of Coronavirus Gene Expression by RNA Sequencing and Ribosome Profiling.

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Irigoyen, Nerea; Firth, Andrew E; Jones, Joshua D; Chung, Betty Y-W; Siddell, Stuart G; Brierley, Ian

2016-02-01

Members of the family Coronaviridae have the largest genomes of all RNA viruses, typically in the region of 30 kilobases. Several coronaviruses, such as Severe acute respiratory syndrome-related coronavirus (SARS-CoV) and Middle East respiratory syndrome-related coronavirus (MERS-CoV), are of medical importance, with high mortality rates and, in the case of SARS-CoV, significant pandemic potential. Other coronaviruses, such as Porcine epidemic diarrhea virus and Avian coronavirus, are important livestock pathogens. Ribosome profiling is a technique which exploits the capacity of the translating ribosome to protect around 30 nucleotides of mRNA from ribonuclease digestion. Ribosome-protected mRNA fragments are purified, subjected to deep sequencing and mapped back to the transcriptome to give a global "snap-shot" of translation. Parallel RNA sequencing allows normalization by transcript abundance. Here we apply ribosome profiling to cells infected with Murine coronavirus, mouse hepatitis virus, strain A59 (MHV-A59), a model coronavirus in the same genus as SARS-CoV and MERS-CoV. The data obtained allowed us to study the kinetics of virus transcription and translation with exquisite precision. We studied the timecourse of positive and negative-sense genomic and subgenomic viral RNA production and the relative translation efficiencies of the different virus ORFs. Virus mRNAs were not found to be translated more efficiently than host mRNAs; rather, virus translation dominates host translation at later time points due to high levels of virus transcripts. Triplet phasing of the profiling data allowed precise determination of translated reading frames and revealed several translated short open reading frames upstream of, or embedded within, known virus protein-coding regions. Ribosome pause sites were identified in the virus replicase polyprotein pp1a ORF and investigated experimentally. Contrary to expectations, ribosomes were not found to pause at the ribosomal

High-Resolution Analysis of Coronavirus Gene Expression by RNA Sequencing and Ribosome Profiling.

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Nerea Irigoyen

2016-02-01

Full Text Available Members of the family Coronaviridae have the largest genomes of all RNA viruses, typically in the region of 30 kilobases. Several coronaviruses, such as Severe acute respiratory syndrome-related coronavirus (SARS-CoV and Middle East respiratory syndrome-related coronavirus (MERS-CoV, are of medical importance, with high mortality rates and, in the case of SARS-CoV, significant pandemic potential. Other coronaviruses, such as Porcine epidemic diarrhea virus and Avian coronavirus, are important livestock pathogens. Ribosome profiling is a technique which exploits the capacity of the translating ribosome to protect around 30 nucleotides of mRNA from ribonuclease digestion. Ribosome-protected mRNA fragments are purified, subjected to deep sequencing and mapped back to the transcriptome to give a global "snap-shot" of translation. Parallel RNA sequencing allows normalization by transcript abundance. Here we apply ribosome profiling to cells infected with Murine coronavirus, mouse hepatitis virus, strain A59 (MHV-A59, a model coronavirus in the same genus as SARS-CoV and MERS-CoV. The data obtained allowed us to study the kinetics of virus transcription and translation with exquisite precision. We studied the timecourse of positive and negative-sense genomic and subgenomic viral RNA production and the relative translation efficiencies of the different virus ORFs. Virus mRNAs were not found to be translated more efficiently than host mRNAs; rather, virus translation dominates host translation at later time points due to high levels of virus transcripts. Triplet phasing of the profiling data allowed precise determination of translated reading frames and revealed several translated short open reading frames upstream of, or embedded within, known virus protein-coding regions. Ribosome pause sites were identified in the virus replicase polyprotein pp1a ORF and investigated experimentally. Contrary to expectations, ribosomes were not found to pause at the

Deep sequencing of small RNAs identifies canonical and non-canonical miRNA and endogenous siRNAs in mammalian somatic tissues.

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Castellano, Leandro; Stebbing, Justin

2013-03-01

MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression. They are characterized by specific maturation processes defined by canonical and non-canonical biogenic pathways. Analysis of ∼0.5 billion sequences from mouse data sets derived from different tissues, developmental stages and cell types, partly characterized by either ablation or mutation of the main proteins belonging to miRNA processor complexes, reveals 66 high-confidence new genomic loci coding for miRNAs that could be processed in a canonical or non-canonical manner. A proportion of the newly discovered miRNAs comprises mirtrons, for which we define a new sub-class. Notably, some of these newly discovered miRNAs are generated from untranslated and open reading frames of coding genes, and we experimentally validate these. We also show that many annotated miRNAs do not present miRNA-like features, as they are neither processed by known processing complexes nor loaded on AGO2; this indicates that the current miRNA miRBase database list should be refined and re-defined. Accordingly, a group of them map on ribosomal RNA molecules, whereas others cannot undergo genuine miRNA biogenesis. Notably, a group of annotated miRNAs are Dgcr8 independent and DICER dependent endogenous small interfering RNAs that derive from a unique hairpin formed from a short interspersed nuclear element.

Short Interspersed Nuclear Element (SINE) Sequences in the Genome of the Human Pathogenic Fungus Aspergillus fumigatus Af293.

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Kanhayuwa, Lakkhana; Coutts, Robert H A

2016-01-01

Novel families of short interspersed nuclear element (SINE) sequences in the human pathogenic fungus Aspergillus fumigatus, clinical isolate Af293, were identified and categorised into tRNA-related and 5S rRNA-related SINEs. Eight predicted tRNA-related SINE families originating from different tRNAs, and nominated as AfuSINE2 sequences, contained target site duplications of short direct repeat sequences (4-14 bp) flanking the elements, an extended tRNA-unrelated region and typical features of RNA polymerase III promoter sequences. The elements ranged in size from 140-493 bp and were present in low copy number in the genome and five out of eight were actively transcribed. One putative tRNAArg-derived sequence, AfuSINE2-1a possessed a unique feature of repeated trinucleotide ACT residues at its 3'-terminus. This element was similar in sequence to the I-4_AO element found in A. oryzae and an I-1_AF long nuclear interspersed element-like sequence identified in A. fumigatus Af293. Families of 5S rRNA-related SINE sequences, nominated as AfuSINE3, were also identified and their 5'-5S rRNA-related regions show 50-65% and 60-75% similarity to respectively A. fumigatus 5S rRNAs and SINE3-1_AO found in A. oryzae. A. fumigatus Af293 contains five copies of AfuSINE3 sequences ranging in size from 259-343 bp and two out of five AfuSINE3 sequences were actively transcribed. Investigations on AfuSINE distribution in the fungal genome revealed that the elements are enriched in pericentromeric and subtelomeric regions and inserted within gene-rich regions. We also demonstrated that some, but not all, AfuSINE sequences are targeted by host RNA silencing mechanisms. Finally, we demonstrated that infection of the fungus with mycoviruses had no apparent effects on SINE activity.

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

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Philip H. Williams

2012-01-01

Full Text Available 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.

Next-generation small RNA sequencing for microRNAs profiling in the honey bee Apis mellifera.

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Chen, X; Yu, X; Cai, Y; Zheng, H; Yu, D; Liu, G; Zhou, Q; Hu, S; Hu, F

2010-12-01

MicroRNAs (miRNAs) are key regulators in various physiological and pathological processes via post-transcriptional regulation of gene expression. The honey bee (Apis mellifera) is a key model for highly social species, and its complex social behaviour can be interpreted theoretically as changes in gene regulation, in which miRNAs are thought to be involved. We used the SOLiD sequencing system to identify the repertoire of miRNAs in the honey bee by sequencing a mixed small RNA library from different developmental stages. We obtained a total of 36,796,459 raw sequences; of which 5,491,100 short sequences were fragments of mRNA and other noncoding RNAs (ncRNA), and 1,759,346 reads mapped to the known miRNAs. We predicted 267 novel honey bee miRNAs representing 380,182 short reads, including eight miRNAs of other insects in 14,107,583 genome-mapped sequences. We verified 50 of them using stem-loop reverse-transcription PCR (RT-PCR), in which 35 yielded PCR products. Cross-species analyses showed 81 novel miRNAs with homologues in other insects, suggesting that they were authentic miRNAs and have similar functions. The results of this study provide a basis for studies of the miRNA-modulating networks in development and some intriguing phenomena such as caste differentiation in A. mellifera. © 2010 The Authors. Insect Molecular Biology © 2010 The Royal Entomological Society.

ISVASE: identification of sequence variant associated with splicing event using RNA-seq data.

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Aljohi, Hasan Awad; Liu, Wanfei; Lin, Qiang; Yu, Jun; Hu, Songnian

2017-06-28

Exon recognition and splicing precisely and efficiently by spliceosome is the key to generate mature mRNAs. About one third or a half of disease-related mutations affect RNA splicing. Software PVAAS has been developed to identify variants associated with aberrant splicing by directly using RNA-seq data. However, it bases on the assumption that annotated splicing site is normal splicing, which is not true in fact. We develop the ISVASE, a tool for specifically identifying sequence variants associated with splicing events (SVASE) by using RNA-seq data. Comparing with PVAAS, our tool has several advantages, such as multi-pass stringent rule-dependent filters and statistical filters, only using split-reads, independent sequence variant identification in each part of splicing (junction), sequence variant detection for both of known and novel splicing event, additional exon-exon junction shift event detection if known splicing events provided, splicing signal evaluation, known DNA mutation and/or RNA editing data supported, higher precision and consistency, and short running time. Using a realistic RNA-seq dataset, we performed a case study to illustrate the functionality and effectiveness of our method. Moreover, the output of SVASEs can be used for downstream analysis such as splicing regulatory element study and sequence variant functional analysis. ISVASE is useful for researchers interested in sequence variants (DNA mutation and/or RNA editing) associated with splicing events. The package is freely available at https://sourceforge.net/projects/isvase/ .

RNA-Pareto: interactive analysis of Pareto-optimal RNA sequence-structure alignments.

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Schnattinger, Thomas; Schöning, Uwe; Marchfelder, Anita; Kestler, Hans A

2013-12-01

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting parameters. We now provide the interactive graphical software tool RNA-Pareto, which allows a direct inspection of all feasible results to the pairwise RNA sequence-structure alignment problem and greatly facilitates the exploration of the optimal solution set.

Reverse Transcription Errors and RNA-DNA Differences at Short Tandem Repeats.

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Fungtammasan, Arkarachai; Tomaszkiewicz, Marta; Campos-Sánchez, Rebeca; Eckert, Kristin A; DeGiorgio, Michael; Makova, Kateryna D

2016-10-01

Transcript variation has important implications for organismal function in health and disease. Most transcriptome studies focus on assessing variation in gene expression levels and isoform representation. Variation at the level of transcript sequence is caused by RNA editing and transcription errors, and leads to nongenetically encoded transcript variants, or RNA-DNA differences (RDDs). Such variation has been understudied, in part because its detection is obscured by reverse transcription (RT) and sequencing errors. It has only been evaluated for intertranscript base substitution differences. Here, we investigated transcript sequence variation for short tandem repeats (STRs). We developed the first maximum-likelihood estimator (MLE) to infer RT error and RDD rates, taking next generation sequencing error rates into account. Using the MLE, we empirically evaluated RT error and RDD rates for STRs in a large-scale DNA and RNA replicated sequencing experiment conducted in a primate species. The RT error rates increased exponentially with STR length and were biased toward expansions. The RDD rates were approximately 1 order of magnitude lower than the RT error rates. The RT error rates estimated with the MLE from a primate data set were concordant with those estimated with an independent method, barcoded RNA sequencing, from a Caenorhabditis elegans data set. Our results have important implications for medical genomics, as STR allelic variation is associated with >40 diseases. STR nonallelic transcript variation can also contribute to disease phenotype. The MLE and empirical rates presented here can be used to evaluate the probability of disease-associated transcripts arising due to RDD. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Short Interspersed Nuclear Element (SINE Sequences in the Genome of the Human Pathogenic Fungus Aspergillus fumigatus Af293.

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Lakkhana Kanhayuwa

Full Text Available Novel families of short interspersed nuclear element (SINE sequences in the human pathogenic fungus Aspergillus fumigatus, clinical isolate Af293, were identified and categorised into tRNA-related and 5S rRNA-related SINEs. Eight predicted tRNA-related SINE families originating from different tRNAs, and nominated as AfuSINE2 sequences, contained target site duplications of short direct repeat sequences (4-14 bp flanking the elements, an extended tRNA-unrelated region and typical features of RNA polymerase III promoter sequences. The elements ranged in size from 140-493 bp and were present in low copy number in the genome and five out of eight were actively transcribed. One putative tRNAArg-derived sequence, AfuSINE2-1a possessed a unique feature of repeated trinucleotide ACT residues at its 3'-terminus. This element was similar in sequence to the I-4_AO element found in A. oryzae and an I-1_AF long nuclear interspersed element-like sequence identified in A. fumigatus Af293. Families of 5S rRNA-related SINE sequences, nominated as AfuSINE3, were also identified and their 5'-5S rRNA-related regions show 50-65% and 60-75% similarity to respectively A. fumigatus 5S rRNAs and SINE3-1_AO found in A. oryzae. A. fumigatus Af293 contains five copies of AfuSINE3 sequences ranging in size from 259-343 bp and two out of five AfuSINE3 sequences were actively transcribed. Investigations on AfuSINE distribution in the fungal genome revealed that the elements are enriched in pericentromeric and subtelomeric regions and inserted within gene-rich regions. We also demonstrated that some, but not all, AfuSINE sequences are targeted by host RNA silencing mechanisms. Finally, we demonstrated that infection of the fungus with mycoviruses had no apparent effects on SINE activity.

Mapping vaccinia virus DNA replication origins at nucleotide level by deep sequencing.

Science.gov (United States)

Senkevich, Tatiana G; Bruno, Daniel; Martens, Craig; Porcella, Stephen F; Wolf, Yuri I; Moss, Bernard

2015-09-01

Poxviruses reproduce in the host cytoplasm and encode most or all of the enzymes and factors needed for expression and synthesis of their double-stranded DNA genomes. Nevertheless, the mode of poxvirus DNA replication and the nature and location of the replication origins remain unknown. A current but unsubstantiated model posits only leading strand synthesis starting at a nick near one covalently closed end of the genome and continuing around the other end to generate a concatemer that is subsequently resolved into unit genomes. The existence of specific origins has been questioned because any plasmid can replicate in cells infected by vaccinia virus (VACV), the prototype poxvirus. We applied directional deep sequencing of short single-stranded DNA fragments enriched for RNA-primed nascent strands isolated from the cytoplasm of VACV-infected cells to pinpoint replication origins. The origins were identified as the switching points of the fragment directions, which correspond to the transition from continuous to discontinuous DNA synthesis. Origins containing a prominent initiation point mapped to a sequence within the hairpin loop at one end of the VACV genome and to the same sequence within the concatemeric junction of replication intermediates. These findings support a model for poxvirus genome replication that involves leading and lagging strand synthesis and is consistent with the requirements for primase and ligase activities as well as earlier electron microscopic and biochemical studies implicating a replication origin at the end of the VACV genome.

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

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Kari A Dilley

Full Text Available Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV, and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV. Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR activation.

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

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Dilley, Kari A; Voorhies, Alexander A; Luthra, Priya; Puri, Vinita; Stockwell, Timothy B; Lorenzi, Hernan; Basler, Christopher F; Shabman, Reed S

2017-01-01

Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation.

CoverageAnalyzer (CAn: A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

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Ralf Hauenschild

2016-11-01

Full Text Available Combination of reverse transcription (RT and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq data, up to sophisticated modification analysis with significance-based modification candidate calling.

Analysis of 16S rRNA amplicon sequencing options on the Roche/454 next-generation titanium sequencing platform.

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Hideyuki Tamaki

Full Text Available BACKGROUND: 16S rRNA gene pyrosequencing approach has revolutionized studies in microbial ecology. While primer selection and short read length can affect the resulting microbial community profile, little is known about the influence of pyrosequencing methods on the sequencing throughput and the outcome of microbial community analyses. The aim of this study is to compare differences in output, ease, and cost among three different amplicon pyrosequencing methods for the Roche/454 Titanium platform METHODOLOGY/PRINCIPAL FINDINGS: The following three pyrosequencing methods for 16S rRNA genes were selected in this study: Method-1 (standard method is the recommended method for bi-directional sequencing using the LIB-A kit; Method-2 is a new option designed in this study for unidirectional sequencing with the LIB-A kit; and Method-3 uses the LIB-L kit for unidirectional sequencing. In our comparison among these three methods using 10 different environmental samples, Method-2 and Method-3 produced 1.5-1.6 times more useable reads than the standard method (Method-1, after quality-based trimming, and did not compromise the outcome of microbial community analyses. Specifically, Method-3 is the most cost-effective unidirectional amplicon sequencing method as it provided the most reads and required the least effort in consumables management. CONCLUSIONS: Our findings clearly demonstrated that alternative pyrosequencing methods for 16S rRNA genes could drastically affect sequencing output (e.g. number of reads before and after trimming but have little effect on the outcomes of microbial community analysis. This finding is important for both researchers and sequencing facilities utilizing 16S rRNA gene pyrosequencing for microbial ecological studies.

Deep sequencing of RNA from ancient maize kernels

DEFF Research Database (Denmark)

Fordyce, Sarah Louise; Avila Arcos, Maria del Carmen; Rasmussen, Morten

2013-01-01

The characterization of biomolecules from ancient samples can shed otherwise unobtainable insights into the past. Despite the fundamental role of transcriptomal change in evolution, the potential of ancient RNA remains unexploited - perhaps due to dogma associated with the fragility of RNA. We hy...... maize kernels. The results suggest that ancient seed transcriptomics may offer a powerful new tool with which to study plant domestication....

A Conserved Target Site in HIV-1 Gag RNA is Accessible to Inhibition by Both an HDV Ribozyme and a Short Hairpin RNA

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Robert J Scarborough

2014-01-01

Full Text Available Antisense-based molecules targeting HIV-1 RNA have the potential to be used as part of gene or drug therapy to treat HIV-1 infection. In this study, HIV-1 RNA was screened to identify more conserved and accessible target sites for ribozymes based on the hepatitis delta virus motif. Using a quantitative screen for effects on HIV-1 production, we identified a ribozyme targeting a highly conserved site in the Gag coding sequence with improved inhibitory potential compared to our previously described candidates targeting the overlapping Tat/Rev coding sequence. We also demonstrate that this target site is highly accessible to short hairpin directed RNA interference, suggesting that it may be available for the binding of antisense RNAs with different modes of action. We provide evidence that this target site is structurally conserved in diverse viral strains and that it is sufficiently different from the human transcriptome to limit off-target effects from antisense therapies. We also show that the modified hepatitis delta virus ribozyme is more sensitive to a mismatch in its target site compared to the short hairpin RNA. Overall, our results validate the potential of a new target site in HIV-1 RNA to be used for the development of antisense therapies.

Analysis of Pteridium ribosomal RNA sequences by rapid direct sequencing.

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Tan, M K

1991-08-01

A total of 864 bases from 5 regions interspersed in the 18S and 26S rRNA molecules from various clones of Pteridium covering the general geographical distribution of the genus was analysed using a rapid rRNA sequencing technique. No base difference has been detected amongst the three major lineages, two of which apparently separated before the breakup of the ancient supercontinent, Pangaea. These regions of the rRNA sequences have thus been conserved for at least 160 million years and are here compared with other eukaryotic, especially plant rRNAs.

CORE-SINEs: eukaryotic short interspersed retroposing elements with common sequence motifs.

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Gilbert, N; Labuda, D

1999-03-16

A 65-bp "core" sequence is dispersed in hundreds of thousands copies in the human genome. This sequence was found to constitute the central segment of a group of short interspersed elements (SINEs), referred to as mammalian-wide interspersed repeats, that proliferated before the radiation of placental mammals. Here, we propose that the core identifies an ancient tRNA-like SINE element, which survived in different lineages such as mammals, reptiles, birds, and fish, as well as mollusks, presumably for >550 million years. This element gave rise to a number of sequence families (CORE-SINEs), including mammalian-wide interspersed repeats, whose distinct 3' ends are shared with different families of long interspersed elements (LINEs). The evolutionary success of the generic CORE-SINE element can be related to the recruitment of the internal promoter from highly transcribed host RNA as well as to its capacity to adapt to changing retropositional opportunities by sequence exchange with actively amplifying LINEs. It reinforces the notion that the very existence of SINEs depends on the cohabitation with both LINEs and the host genome.

Short hairpin RNA interference therapy for ischemic heart disease

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Huang, Mei; Chan, Denise; Jia, Fangjun; Xie, Xiaoyan; Li, Zongjin; Hoyt, Grant; Robbins, Robert C.; Chen, Xiaoyuan; Giaccia, Amato; Wu, Joseph C.

2013-01-01

Background During hypoxia, upregulation of hypoxia inducible factor-1 alpha (HIF-1α) transcriptional factor can activate several downstream angiogenic genes. However, HIF-1α is naturally degraded by prolyl hydroxylase-2 (PHD2) protein. Here we hypothesize that short hairpin RNA (shRNA) interference therapy targeting PHD2 can be used for treatment of myocardial ischemia and this process can be followed noninvasively by molecular imaging. Methods and Results PHD2 was cloned from mouse embryonic stem (ES) cells by comparing the homolog gene in human and rat. The best candidate shRNA sequence for inhibiting PHD2 was inserted into the pSuper vector driven by the H1 promoter, followed by a separate hypoxia response element (HRE)-incorporated promoter driving a firefly luciferase (Fluc) reporter gene. This construct was used to transfect mouse C2C12 myoblast cell line for in vitro confirmation. Compared to the control short hairpin scramble (shScramble) as control, inhibition of PHD2 increased levels of HIF-1α protein and several downstream angiogenic genes by >30% (P<0.01). Afterwards, shRNA targeting PHD2 (shPHD2) plasmid was injected intramyocardially following ligation of left anterior descending (LAD) artery in mice. Animals were randomized into shPHD2 group (n=20) versus shScramble sequence as control (n=20). Bioluminescence imaging detected transgene expression for 4–5 weeks. Echocardiographic study showed the shPHD2 group had improved fractional shortening compared with the shScramble group at week 4 (33.7%±1.9% vs. 28.4%±2.8%; P<0.05). Postmortem analysis showed increased presence of small capillaries and venules in the infarcted zones by CD31 staining. Finally, Western blot anlaysis of explanted hearts also confirm that animals treated with shPHD2 had significantly higher levels of HIF-1α protein. Conclusions This is the first study to image the biological role of shRNA therapy for improving cardiac function. Inhibition of PHD2 by shRNA led to

High-throughput sequencing of RNA silencing-associated small RNAs in olive (Olea europaea L..

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Livia Donaire

Full Text Available 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.

Short sequence motifs, overrepresented in mammalian conservednon-coding sequences

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Minovitsky, Simon; Stegmaier, Philip; Kel, Alexander; Kondrashov,Alexey S.; Dubchak, Inna

2007-02-21

Background: A substantial fraction of non-coding DNAsequences of multicellular eukaryotes is under selective constraint. Inparticular, ~;5 percent of the human genome consists of conservednon-coding sequences (CNSs). CNSs differ from other genomic sequences intheir nucleotide composition and must play important functional roles,which mostly remain obscure.Results: We investigated relative abundancesof short sequence motifs in all human CNSs present in the human/mousewhole-genome alignments vs. three background sets of sequences: (i)weakly conserved or unconserved non-coding sequences (non-CNSs); (ii)near-promoter sequences (located between nucleotides -500 and -1500,relative to a start of transcription); and (iii) random sequences withthe same nucleotide composition as that of CNSs. When compared tonon-CNSs and near-promoter sequences, CNSs possess an excess of AT-richmotifs, often containing runs of identical nucleotides. In contrast, whencompared to random sequences, CNSs contain an excess of GC-rich motifswhich, however, lack CpG dinucleotides. Thus, abundance of short sequencemotifs in human CNSs, taken as a whole, is mostly determined by theiroverall compositional properties and not by overrepresentation of anyspecific short motifs. These properties are: (i) high AT-content of CNSs,(ii) a tendency, probably due to context-dependent mutation, of A's andT's to clump, (iii) presence of short GC-rich regions, and (iv) avoidanceof CpG contexts, due to their hypermutability. Only a small number ofshort motifs, overrepresented in all human CNSs are similar to bindingsites of transcription factors from the FOX family.Conclusion: Human CNSsas a whole appear to be too broad a class of sequences to possess strongfootprints of any short sequence-specific functions. Such footprintsshould be studied at the level of functional subclasses of CNSs, such asthose which flank genes with a particular pattern of expression. Overallproperties of CNSs are affected by

DeepSimulator: a deep simulator for Nanopore sequencing

KAUST Repository

Li, Yu; Han, Renmin; Bi, Chongwei; Li, Mo; Wang, Sheng; Gao, Xin

2017-01-01

or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments

Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

OpenAIRE

Manske, Magnus; Miotto, Olivo; Campino, Susana; Auburn, Sarah; Almagro-Garcia, Jacob; Maslen, Gareth; O?Brien, Jack; Djimde, Abdoulaye; Doumbo, Ogobara; Zongo, Issaka; Ouedraogo, Jean-Bosco; Michon, Pascal; Mueller, Ivo; Siba, Peter; Nzila, Alexis

2012-01-01

: Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. Here we describe methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality c...

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

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Nicholas J Schurch

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

Chimira: analysis of small RNA sequencing data and microRNA modifications.

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Vitsios, Dimitrios M; Enright, Anton J

2015-10-15

Chimira is a web-based system for microRNA (miRNA) analysis from small RNA-Seq data. Sequences are automatically cleaned, trimmed, size selected and mapped directly to miRNA hairpin sequences. This generates count-based miRNA expression data for subsequent statistical analysis. Moreover, it is capable of identifying epi-transcriptomic modifications in the input sequences. Supported modification types include multiple types of 3'-modifications (e.g. uridylation, adenylation), 5'-modifications and also internal modifications or variation (ADAR editing or single nucleotide polymorphisms). Besides cleaning and mapping of input sequences to miRNAs, Chimira provides a simple and intuitive set of tools for the analysis and interpretation of the results (see also Supplementary Material). These allow the visual study of the differential expression between two specific samples or sets of samples, the identification of the most highly expressed miRNAs within sample pairs (or sets of samples) and also the projection of the modification profile for specific miRNAs across all samples. Other tools have already been published in the past for various types of small RNA-Seq analysis, such as UEA workbench, seqBuster, MAGI, OASIS and CAP-miRSeq, CPSS for modifications identification. A comprehensive comparison of Chimira with each of these tools is provided in the Supplementary Material. Chimira outperforms all of these tools in total execution speed and aims to facilitate simple, fast and reliable analysis of small RNA-Seq data allowing also, for the first time, identification of global microRNA modification profiles in a simple intuitive interface. Chimira has been developed as a web application and it is accessible here: http://www.ebi.ac.uk/research/enright/software/chimira. aje@ebi.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Small RNA and transcriptome deep sequencing proffers insight into floral gene regulation in Rosa cultivars

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Kim Jungeun

2012-11-01

Full Text Available Abstract Background Roses (Rosa sp., which belong to the family Rosaceae, are the most economically important ornamental plants—making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars. Results We produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: ‘Vital’, ‘Maroussia’, and ‘Sympathy’ and Rosa rugosa Thunb. , respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO terms, Plant Ontology (PO terms, and MIPS Functional Catalogue (FunCat terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes. Conclusions In this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a

Size, Shape, and Sequence-Dependent Immunogenicity of RNA Nanoparticles

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Sijin Guo

2017-12-01

Full Text Available RNA molecules have emerged as promising therapeutics. Like all other drugs, the safety profile and immune response are important criteria for drug evaluation. However, the literature on RNA immunogenicity has been controversial. Here, we used the approach of RNA nanotechnology to demonstrate that the immune response of RNA nanoparticles is size, shape, and sequence dependent. RNA triangle, square, pentagon, and tetrahedron with same shape but different sizes, or same size but different shapes were used as models to investigate the immune response. The levels of pro-inflammatory cytokines induced by these RNA nanoarchitectures were assessed in macrophage-like cells and animals. It was found that RNA polygons without extension at the vertexes were immune inert. However, when single-stranded RNA with a specific sequence was extended from the vertexes of RNA polygons, strong immune responses were detected. These immunostimulations are sequence specific, because some other extended sequences induced little or no immune response. Additionally, larger-size RNA square induced stronger cytokine secretion. 3D RNA tetrahedron showed stronger immunostimulation than planar RNA triangle. These results suggest that the immunogenicity of RNA nanoparticles is tunable to produce either a minimal immune response that can serve as safe therapeutic vectors, or a strong immune response for cancer immunotherapy or vaccine adjuvants.

Efficient construction of an inverted minimal H1 promoter driven siRNA expression cassette: facilitation of promoter and siRNA sequence exchange.

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Hoorig Nassanian

2007-08-01

Full Text Available RNA interference (RNAi, mediated by small interfering RNA (siRNA, is an effective method used to silence gene expression at the post-transcriptional level. Upon introduction into target cells, siRNAs incorporate into the RNA-induced silencing complex (RISC. The antisense strand of the siRNA duplex then "guides" the RISC to the homologous mRNA, leading to target degradation and gene silencing. In recent years, various vector-based siRNA expression systems have been developed which utilize opposing polymerase III promoters to independently drive expression of the sense and antisense strands of the siRNA duplex from the same template.We show here the use of a ligase chain reaction (LCR to develop a new vector system called pInv-H1 in which a DNA sequence encoding a specific siRNA is placed between two inverted minimal human H1 promoters (approximately 100 bp each. Expression of functional siRNAs from this construct has led to efficient silencing of both reporter and endogenous genes. Furthermore, the inverted H1 promoter-siRNA expression cassette was used to generate a retrovirus vector capable of transducing and silencing expression of the targeted protein by>80% in target cells.The unique design of this construct allows for the efficient exchange of siRNA sequences by the directional cloning of short oligonucleotides via asymmetric restriction sites. This provides a convenient way to test the functionality of different siRNA sequences. Delivery of the siRNA cassette by retroviral transduction suggests that a single copy of the siRNA expression cassette efficiently knocks down gene expression at the protein level. We note that this vector system can potentially be used to generate a random siRNA library. The flexibility of the ligase chain reaction suggests that additional control elements can easily be introduced into this siRNA expression cassette.

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion.

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Zhao, Shanrong; Zhang, Ying; Gamini, Ramya; Zhang, Baohong; von Schack, David

2018-03-19

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

Deep sequencing of small RNA libraries from human prostate epithelial and stromal cells reveal distinct pattern of microRNAs primarily predicted to target growth factors.

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Singh, Savita; Zheng, Yun; Jagadeeswaran, Guru; Ebron, Jey Sabith; Sikand, Kavleen; Gupta, Sanjay; Sunker, Ramanjulu; Shukla, Girish C

2016-02-28

Complex epithelial and stromal cell interactions are required during the development and progression of prostate cancer. Regulatory small non-coding microRNAs (miRNAs) participate in the spatiotemporal regulation of messenger RNA (mRNA) and regulation of translation affecting a large number of genes involved in prostate carcinogenesis. In this study, through deep-sequencing of size fractionated small RNA libraries we profiled the miRNAs of prostate epithelial (PrEC) and stromal (PrSC) cells. Over 50 million reads were obtained for PrEC in which 860,468 were unique sequences. Similarly, nearly 76 million reads for PrSC were obtained in which over 1 million were unique reads. Expression of many miRNAs of broadly conserved and poorly conserved miRNA families were identified. Sixteen highly expressed miRNAs with significant change in expression in PrSC than PrEC were further analyzed in silico. ConsensusPathDB showed the target genes of these miRNAs were significantly involved in adherence junction, cell adhesion, EGRF, TGF-β and androgen signaling. Let-7 family of tumor-suppressor miRNAs expression was highly pervasive in both, PrEC and PrSC cells. In addition, we have also identified several miRNAs that are unique to PrEC or PrSC cells and their predicted putative targets are a group of transcription factors. This study provides perspective on the miRNA expression in PrEC and PrSC, and reveals a global trend in miRNA interactome. We conclude that the most abundant miRNAs are potential regulators of development and differentiation of the prostate gland by targeting a set of growth factors. Additionally, high level expression of the most members of let-7 family miRNAs suggests their role in the fine tuning of the growth and proliferation of prostate epithelial and stromal cells. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Rfam: annotating families of non-coding RNA sequences.

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Daub, Jennifer; Eberhardt, Ruth Y; Tate, John G; Burge, Sarah W

2015-01-01

The primary task of the Rfam database is to collate experimentally validated noncoding RNA (ncRNA) sequences from the published literature and facilitate the prediction and annotation of new homologues in novel nucleotide sequences. We group homologous ncRNA sequences into "families" and related families are further grouped into "clans." We collate and manually curate data cross-references for these families from other databases and external resources. Our Web site offers researchers a simple interface to Rfam and provides tools with which to annotate their own sequences using our covariance models (CMs), through our tools for searching, browsing, and downloading information on Rfam families. In this chapter, we will work through examples of annotating a query sequence, collating family information, and searching for data.

Deep whole-genome sequencing of 90 Han Chinese genomes.

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Lan, Tianming; Lin, Haoxiang; Zhu, Wenjuan; Laurent, Tellier Christian Asker Melchior; Yang, Mengcheng; Liu, Xin; Wang, Jun; Wang, Jian; Yang, Huanming; Xu, Xun; Guo, Xiaosen

2017-09-01

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000

Size, Shape, and Sequence-Dependent Immunogenicity of RNA Nanoparticles.

Science.gov (United States)

Guo, Sijin; Li, Hui; Ma, Mengshi; Fu, Jian; Dong, Yizhou; Guo, Peixuan

2017-12-15

RNA molecules have emerged as promising therapeutics. Like all other drugs, the safety profile and immune response are important criteria for drug evaluation. However, the literature on RNA immunogenicity has been controversial. Here, we used the approach of RNA nanotechnology to demonstrate that the immune response of RNA nanoparticles is size, shape, and sequence dependent. RNA triangle, square, pentagon, and tetrahedron with same shape but different sizes, or same size but different shapes were used as models to investigate the immune response. The levels of pro-inflammatory cytokines induced by these RNA nanoarchitectures were assessed in macrophage-like cells and animals. It was found that RNA polygons without extension at the vertexes were immune inert. However, when single-stranded RNA with a specific sequence was extended from the vertexes of RNA polygons, strong immune responses were detected. These immunostimulations are sequence specific, because some other extended sequences induced little or no immune response. Additionally, larger-size RNA square induced stronger cytokine secretion. 3D RNA tetrahedron showed stronger immunostimulation than planar RNA triangle. These results suggest that the immunogenicity of RNA nanoparticles is tunable to produce either a minimal immune response that can serve as safe therapeutic vectors, or a strong immune response for cancer immunotherapy or vaccine adjuvants. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Massively parallel sequencing, aCGH, and RNA-Seq technologies provide a comprehensive molecular diagnosis of Fanconi anemia.

Science.gov (United States)

Chandrasekharappa, Settara C; Lach, Francis P; Kimble, Danielle C; Kamat, Aparna; Teer, Jamie K; Donovan, Frank X; Flynn, Elizabeth; Sen, Shurjo K; Thongthip, Supawat; Sanborn, Erica; Smogorzewska, Agata; Auerbach, Arleen D; Ostrander, Elaine A

2013-05-30

Current methods for detecting mutations in Fanconi anemia (FA)-suspected patients are inefficient and often miss mutations. We have applied recent advances in DNA sequencing and genomic capture to the diagnosis of FA. Specifically, we used custom molecular inversion probes or TruSeq-enrichment oligos to capture and sequence FA and related genes, including introns, from 27 samples from the International Fanconi Anemia Registry at The Rockefeller University. DNA sequencing was complemented with custom array comparative genomic hybridization (aCGH) and RNA sequencing (RNA-seq) analysis. aCGH identified deletions/duplications in 4 different FA genes. RNA-seq analysis revealed lack of allele specific expression associated with a deletion and splicing defects caused by missense, synonymous, and deep-in-intron variants. The combination of TruSeq-targeted capture, aCGH, and RNA-seq enabled us to identify the complementation group and biallelic germline mutations in all 27 families: FANCA (7), FANCB (3), FANCC (3), FANCD1 (1), FANCD2 (3), FANCF (2), FANCG (2), FANCI (1), FANCJ (2), and FANCL (3). FANCC mutations are often the cause of FA in patients of Ashkenazi Jewish (AJ) ancestry, and we identified 2 novel FANCC mutations in 2 patients of AJ ancestry. We describe here a strategy for efficient molecular diagnosis of FA.

Ultra-deep sequencing of intra-host rabies virus populations during cross-species transmission.

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Monica K Borucki

2013-11-01

Full Text Available One of the hurdles to understanding the role of viral quasispecies in RNA virus cross-species transmission (CST events is the need to analyze a densely sampled outbreak using deep sequencing in order to measure the amount of mutation occurring on a small time scale. In 2009, the California Department of Public Health reported a dramatic increase (350 in the number of gray foxes infected with a rabies virus variant for which striped skunks serve as a reservoir host in Humboldt County. To better understand the evolution of rabies, deep-sequencing was applied to 40 unpassaged rabies virus samples from the Humboldt outbreak. For each sample, approximately 11 kb of the 12 kb genome was amplified and sequenced using the Illumina platform. Average coverage was 17,448 and this allowed characterization of the rabies virus population present in each sample at unprecedented depths. Phylogenetic analysis of the consensus sequence data demonstrated that samples clustered according to date (1995 vs. 2009 and geographic location (northern vs. southern. A single amino acid change in the G protein distinguished a subset of northern foxes from a haplotype present in both foxes and skunks, suggesting this mutation may have played a role in the observed increased transmission among foxes in this region. Deep-sequencing data indicated that many genetic changes associated with the CST event occurred prior to 2009 since several nonsynonymous mutations that were present in the consensus sequences of skunk and fox rabies samples obtained from 20032010 were present at the sub-consensus level (as rare variants in the viral population in skunk and fox samples from 1995. These results suggest that analysis of rare variants within a viral population may yield clues to ancestral genomes and identify rare variants that have the potential to be selected for if environment conditions change.

Identification of human microRNA-like sequences embedded within the protein-encoding genes of the human immunodeficiency virus.

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Bryan Holland

Full Text Available BACKGROUND: MicroRNAs (miRNAs are highly conserved, short (18-22 nts, non-coding RNA molecules that regulate gene expression by binding to the 3' untranslated regions (3'UTRs of mRNAs. While numerous cellular microRNAs have been associated with the progression of various diseases including cancer, miRNAs associated with retroviruses have not been well characterized. Herein we report identification of microRNA-like sequences in coding regions of several HIV-1 genomes. RESULTS: Based on our earlier proteomics and bioinformatics studies, we have identified 8 cellular miRNAs that are predicted to bind to the mRNAs of multiple proteins that are dysregulated during HIV-infection of CD4+ T-cells in vitro. In silico analysis of the full length and mature sequences of these 8 miRNAs and comparisons with all the genomic and subgenomic sequences of HIV-1 strains in global databases revealed that the first 18/18 sequences of the mature hsa-miR-195 sequence (including the short seed sequence, matched perfectly (100%, or with one nucleotide mismatch, within the envelope (env genes of five HIV-1 genomes from Africa. In addition, we have identified 4 other miRNA-like sequences (hsa-miR-30d, hsa-miR-30e, hsa-miR-374a and hsa-miR-424 within the env and the gag-pol encoding regions of several HIV-1 strains, albeit with reduced homology. Mapping of the miRNA-homologues of env within HIV-1 genomes localized these sequence to the functionally significant variable regions of the env glycoprotein gp120 designated V1, V2, V4 and V5. CONCLUSIONS: We conclude that microRNA-like sequences are embedded within the protein-encoding regions of several HIV-1 genomes. Given that the V1 to V5 regions of HIV-1 envelopes contain specific, well-characterized domains that are critical for immune responses, virus neutralization and disease progression, we propose that the newly discovered miRNA-like sequences within the HIV-1 genomes may have evolved to self-regulate survival of the

RNA deep sequencing reveals novel candidate genes and polymorphisms in boar testis and liver tissues with divergent androstenone levels.

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Asep Gunawan

Full Text Available Boar taint is an unpleasant smell and taste of pork meat derived from some entire male pigs. The main causes of boar taint are the two compounds androstenone (5α-androst-16-en-3-one and skatole (3-methylindole. It is crucial to understand the genetic mechanism of boar taint to select pigs for lower androstenone levels and thus reduce boar taint. The aim of the present study was to investigate transcriptome differences in boar testis and liver tissues with divergent androstenone levels using RNA deep sequencing (RNA-Seq. The total number of reads produced for each testis and liver sample ranged from 13,221,550 to 33,206,723 and 12,755,487 to 46,050,468, respectively. In testis samples 46 genes were differentially regulated whereas 25 genes showed differential expression in the liver. The fold change values ranged from -4.68 to 2.90 in testis samples and -2.86 to 3.89 in liver samples. Differentially regulated genes in high androstenone testis and liver samples were enriched in metabolic processes such as lipid metabolism, small molecule biochemistry and molecular transport. This study provides evidence for transcriptome profile and gene polymorphisms of boars with divergent androstenone level using RNA-Seq technology. Digital gene expression analysis identified candidate genes in flavin monooxygenease family, cytochrome P450 family and hydroxysteroid dehydrogenase family. Moreover, polymorphism and association analysis revealed mutation in IRG6, MX1, IFIT2, CYP7A1, FMO5 and KRT18 genes could be potential candidate markers for androstenone levels in boars. Further studies are required for proving the role of candidate genes to be used in genomic selection against boar taint in pig breeding programs.

High-throughput sequencing of small RNA transcriptome reveals salt stress regulated microRNAs in sugarcane.

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Mariana Carnavale Bottino

Full Text Available Salt stress is a primary cause of crop losses worldwide, and it has been the subject of intense investigation to unravel the complex mechanisms responsible for salinity tolerance. MicroRNA is implicated in many developmental processes and in responses to various abiotic stresses, playing pivotal roles in plant adaptation. Deep sequencing technology was chosen to determine the small RNA transcriptome of Saccharum sp cultivars grown on saline conditions. We constructed four small RNAs libraries prepared from plants grown on hydroponic culture submitted to 170 mM NaCl and harvested after 1 h, 6 hs and 24 hs. Each library was sequenced individually and together generated more than 50 million short reads. Ninety-eight conserved miRNAs and 33 miRNAs* were identified by bioinformatics. Several of the microRNA showed considerable differences of expression in the four libraries. To confirm the results of the bioinformatics-based analysis, we studied the expression of the 10 most abundant miRNAs and 1 miRNA* in plants treated with 170 mM NaCl and in plants with a severe treatment of 340 mM NaCl. The results showed that 11 selected miRNAs had higher expression in samples treated with severe salt treatment compared to the mild one. We also investigated the regulation of the same miRNAs in shoots of four cultivars grown on soil treated with 170 mM NaCl. Cultivars could be grouped according to miRNAs expression in response to salt stress. Furthermore, the majority of the predicted target genes had an inverse regulation with their correspondent microRNAs. The targets encode a wide range of proteins, including transcription factors, metabolic enzymes and genes involved in hormone signaling, probably assisting the plants to develop tolerance to salinity. Our work provides insights into the regulatory functions of miRNAs, thereby expanding our knowledge on potential salt-stressed regulated genes.

Screening for sequence-specific RNA-BPs by comprehensive UV crosslinking

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Le Meuth-Metzinger Valerie

2002-06-01

Full Text Available Abstract Background Specific cis-elements and the associated trans-acting factors have been implicated in the post-transcriptional regulation of gene expression. In the era of genome wide analyses identifying novel trans-acting factors and cis-regulatory elements is a step towards understanding coordinated gene expression. UV-crosslink analysis is a standard method used to identify RNA-binding proteins. Uridine is traditionally used to radiolabel substrate RNAs, however, proteins binding to cis-elments particularly uridine poor will be weakly or not detected. We evaluate here the possibility of using UV-crosslinking with RNA substrates radiolabeled with each of the four ribonucleotides as an approach for screening for novel sequence specific RNA-binding proteins. Results The radiolabeled RNA substrates were derived from the 3'UTRs of the cloned Eg and c-mos Xenopus laevis maternal mRNAs. Specific, but not identical, uv-crosslinking signals were obtained, some of which corresponded to already identified proteins. A signal for a novel 90 kDa protein was observed with the c-mos 3'UTR radiolabeled with both CTP and GTP but not with UTP. The binding site of the 90 kDa RNA-binding protein was localised to a 59-nucleotide portion of the c-mos 3'UTR. Conclusion That the 90 kDa signal was detected with RNAs radiolabeled with CTP or GTP but not UTP illustrates the advantage of radiolabeling all four nucleotides in a UV-crosslink based screen. This method can be used for both long and short RNAs and does not require knowledge of the cis-acting sequence. It should be amenable to high throughput screening for RNA binding proteins.

Oasis: online analysis of small RNA deep sequencing data.

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Capece, Vincenzo; Garcia Vizcaino, Julio C; Vidal, Ramon; Rahman, Raza-Ur; Pena Centeno, Tonatiuh; Shomroni, Orr; Suberviola, Irantzu; Fischer, Andre; Bonn, Stefan

2015-07-01

Oasis is a web application that allows for the fast and flexible online analysis of small-RNA-seq (sRNA-seq) data. It was designed for the end user in the lab, providing an easy-to-use web frontend including video tutorials, demo data and best practice step-by-step guidelines on how to analyze sRNA-seq data. Oasis' exclusive selling points are a differential expression module that allows for the multivariate analysis of samples, a classification module for robust biomarker detection and an advanced programming interface that supports the batch submission of jobs. Both modules include the analysis of novel miRNAs, miRNA targets and functional analyses including GO and pathway enrichment. Oasis generates downloadable interactive web reports for easy visualization, exploration and analysis of data on a local system. Finally, Oasis' modular workflow enables for the rapid (re-) analysis of data. Oasis is implemented in Python, R, Java, PHP, C++ and JavaScript. It is freely available at http://oasis.dzne.de. stefan.bonn@dzne.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Computational prediction of miRNA genes from small RNA sequencing data

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Wenjing eKang

2015-01-01

Full Text Available Next-generation sequencing now for the first time allows researchers to gauge 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. 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.

An introduction to deep learning on biological sequence data: examples and solutions.

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Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Recurrent chimeric RNAs enriched in human prostate cancer identified by deep sequencing

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Kannan, Kalpana; Wang, Liguo; Wang, Jianghua; Ittmann, Michael M.; Li, Wei; Yen, Laising

2011-01-01

Transcription-induced chimeric RNAs, possessing sequences from different genes, are expected to increase the proteomic diversity through chimeric proteins or altered regulation. Despite their importance, few studies have focused on chimeric RNAs especially regarding their presence/roles in human cancers. By deep sequencing the transcriptome of 20 human prostate cancer and 10 matched benign prostate tissues, we obtained 1.3 billion sequence reads, which led to the identification of 2,369 chimeric RNA candidates. Chimeric RNAs occurred in significantly higher frequency in cancer than in matched benign samples. Experimental investigation of a selected 46 set led to the confirmation of 32 chimeric RNAs, of which 27 were highly recurrent and previously undescribed in prostate cancer. Importantly, a subset of these chimeras was present in prostate cancer cell lines, but not detectable in primary human prostate epithelium cells, implying their associations with cancer. These chimeras contain discernable 5′ and 3′ splice sites at the RNA junction, indicating that their formation is mediated by splicing. Their presence is also largely independent of the expression of parental genes, suggesting that other factors are involved in their production and regulation. One chimera, TMEM79-SMG5, is highly differentially expressed in human cancer samples and therefore a potential biomarker. The prevalence of chimeric RNAs may allow the limited number of human genes to encode a substantially larger number of RNAs and proteins, forming an additional layer of cellular complexity. Together, our results suggest that chimeric RNAs are widespread, and increased chimeric RNA events could represent a unique class of molecular alteration in cancer. PMID:21571633

RNA sequencing: current and prospective uses in metabolic research.

Science.gov (United States)

Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay

2014-10-01

Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment. © 2014 Society for Endocrinology.

Deep Sequencing Analysis of miRNA Expression in Breast Muscle of Fast-Growing and Slow-Growing Broilers

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Hongjia Ouyang

2015-07-01

Full Text Available Growth performance is an important economic trait in chicken. MicroRNAs (miRNAs have been shown to play important roles in various biological processes, but their functions in chicken growth are not yet clear. To investigate the function of miRNAs in chicken growth, breast muscle tissues of the two-tail samples (highest and lowest body weight from Recessive White Rock (WRR and Xinghua Chickens (XH were performed on high throughput small RNA deep sequencing. In this study, a total of 921 miRNAs were identified, including 733 known mature miRNAs and 188 novel miRNAs. There were 200, 279, 257 and 297 differentially expressed miRNAs in the comparisons of WRRh vs. WRRl, WRRh vs. XHh, WRRl vs. XHl, and XHh vs. XHl group, respectively. A total of 22 highly differentially expressed miRNAs (fold change > 2 or < 0.5; p-value < 0.05; q-value < 0.01, which also have abundant expression (read counts > 1000 were found in our comparisons. As far as two analyses (WRRh vs. WRRl, and XHh vs. XHl are concerned, we found 80 common differentially expressed miRNAs, while 110 miRNAs were found in WRRh vs. XHh and WRRl vs. XHl. Furthermore, 26 common miRNAs were identified among all four comparisons. Four differentially expressed miRNAs (miR-223, miR-16, miR-205a and miR-222b-5p were validated by quantitative real-time RT-PCR (qRT-PCR. Regulatory networks of interactions among miRNAs and their targets were constructed using integrative miRNA target-prediction and network-analysis. Growth hormone receptor (GHR was confirmed as a target of miR-146b-3p by dual-luciferase assay and qPCR, indicating that miR-34c, miR-223, miR-146b-3p, miR-21 and miR-205a are key growth-related target genes in the network. These miRNAs are proposed as candidate miRNAs for future studies concerning miRNA-target function on regulation of chicken growth.

Nucleotide sequence of a human tRNA gene heterocluster

International Nuclear Information System (INIS)

Chang, Y.N.; Pirtle, I.L.; Pirtle, R.M.

1986-01-01

Leucine tRNA from bovine liver was used as a hybridization probe to screen a human gene library harbored in Charon-4A of bacteriophage lambda. The human DNA inserts from plaque-pure clones were characterized by restriction endonuclease mapping and Southern hybridization techniques, using both [3'- 32 P]-labeled bovine liver leucine tRNA and total tRNA as hybridization probes. An 8-kb Hind III fragment of one of these γ-clones was subcloned into the Hind III site of pBR322. Subsequent fine restriction mapping and DNA sequence analysis of this plasmid DNA indicated the presence of four tRNA genes within the 8-kb DNA fragment. A leucine tRNA gene with an anticodon of AAG and a proline tRNA gene with an anticodon of AGG are in a 1.6-kb subfragment. A threonine tRNA gene with an anticodon of UGU and an as yet unidentified tRNA gene are located in a 1.1-kb subfragment. These two different subfragments are separated by 2.8 kb. The coding regions of the three sequenced genes contain characteristic internal split promoter sequences and do not have intervening sequences. The 3'-flanking region of these three genes have typical RNA polymerase III termination sites of at least four consecutive T residues

Novel Approach to Analyzing MFE of Noncoding RNA Sequences.

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George, Tina P; Thomas, Tessamma

2016-01-01

Genomic studies have become noncoding RNA (ncRNA) centric after the study of different genomes provided enormous information on ncRNA over the past decades. The function of ncRNA is decided by its secondary structure, and across organisms, the secondary structure is more conserved than the sequence itself. In this study, the optimal secondary structure or the minimum free energy (MFE) structure of ncRNA was found based on the thermodynamic nearest neighbor model. MFE of over 2600 ncRNA sequences was analyzed in view of its signal properties. Mathematical models linking MFE to the signal properties were found for each of the four classes of ncRNA analyzed. MFE values computed with the proposed models were in concordance with those obtained with the standard web servers. A total of 95% of the sequences analyzed had deviation of MFE values within ±15% relative to those obtained from standard web servers.

Sequence analysis of RNase MRP RNA reveals its origination from eukaryotic RNase P RNA

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Zhu, Yanglong; Stribinskis, Vilius; Ramos, Kenneth S.; Li, Yong

2006-01-01

RNase MRP is a eukaryote-specific endoribonuclease that generates RNA primers for mitochondrial DNA replication and processes precursor rRNA. RNase P is a ubiquitous endoribonuclease that cleaves precursor tRNA transcripts to produce their mature 5′ termini. We found extensive sequence homology of catalytic domains and specificity domains between their RNA subunits in many organisms. In Candida glabrata, the internal loop of helix P3 is 100% conserved between MRP and P RNAs. The helix P8 of MRP RNA from microsporidia Encephalitozoon cuniculi is identical to that of P RNA. Sequence homology can be widely spread over the whole molecule of MRP RNA and P RNA, such as those from Dictyostelium discoideum. These conserved nucleotides between the MRP and P RNAs strongly support the hypothesis that the MRP RNA is derived from the P RNA molecule in early eukaryote evolution. PMID:16540690

Short-term Memory of Deep RNN

OpenAIRE

Gallicchio, Claudio

2018-01-01

The extension of deep learning towards temporal data processing is gaining an increasing research interest. In this paper we investigate the properties of state dynamics developed in successive levels of deep recurrent neural networks (RNNs) in terms of short-term memory abilities. Our results reveal interesting insights that shed light on the nature of layering as a factor of RNN design. Noticeably, higher layers in a hierarchically organized RNN architecture results to be inherently biased ...

mESAdb: microRNA expression and sequence analysis database.

Science.gov (United States)

Kaya, Koray D; Karakülah, Gökhan; Yakicier, Cengiz M; Acar, Aybar C; Konu, Ozlen

2011-01-01

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

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

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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.

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

Science.gov (United States)

Olson, Nathan D.; Lund, Steven P.; Zook, Justin M.; Rojas-Cornejo, Fabiola; Beck, Brian; Foy, Carole; Huggett, Jim; Whale, Alexandra S.; Sui, Zhiwei; Baoutina, Anna; Dobeson, Michael; Partis, Lina; Morrow, Jayne B.

2015-01-01

This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies. PMID:27077030

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

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Nathan D. Olson

2015-03-01

Full Text Available This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1 identity of biologically conserved position, (2 ratio of 16S rRNA gene copies featuring identified variants, and (3 the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies.

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

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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.

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

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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

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

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Wycliff M. Kinoti

2017-06-01

Full Text Available 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

Detection of Emerging Vaccine-Related Polioviruses by Deep Sequencing.

Science.gov (United States)

Sahoo, Malaya K; Holubar, Marisa; Huang, ChunHong; Mohamed-Hadley, Alisha; Liu, Yuanyuan; Waggoner, Jesse J; Troy, Stephanie B; Garcia-Garcia, Lourdes; Ferreyra-Reyes, Leticia; Maldonado, Yvonne; Pinsky, Benjamin A

2017-07-01

Oral poliovirus vaccine can mutate to regain neurovirulence. To date, evaluation of these mutations has been performed primarily on culture-enriched isolates by using conventional Sanger sequencing. We therefore developed a culture-independent, deep-sequencing method targeting the 5' untranslated region (UTR) and P1 genomic region to characterize vaccine-related poliovirus variants. Error analysis of the deep-sequencing method demonstrated reliable detection of poliovirus mutations at levels of vaccinated, asymptomatic children and their close contacts collected during a prospective cohort study in Veracruz, Mexico, revealed no vaccine-derived polioviruses. This was expected given that the longest duration between sequenced sample collection and the end of the most recent national immunization week was 66 days. However, we identified many low-level variants (Sabin serotypes, as well as vaccine-related viruses with multiple canonical mutations associated with phenotypic reversion present at high levels (>90%). These results suggest that monitoring emerging vaccine-related poliovirus variants by deep sequencing may aid in the poliovirus endgame and efforts to ensure global polio eradication. Copyright © 2017 Sahoo et al.

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

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Francesca Cordero

Full Text Available BACKGROUND: Massive Parallel Sequencing methods (MPS can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. PRIMARY FINDINGS: A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq show a very good specificity and sensitivity in the detection of differential expression. CONCLUSIONS: The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

Science.gov (United States)

Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Donatelli, Susanna; Calogero, Raffaele A

2012-01-01

Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq) show a very good specificity and sensitivity in the detection of differential expression. The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Reconstruction of ancestral RNA sequences under multiple structural constraints.

Science.gov (United States)

Tremblay-Savard, Olivier; Reinharz, Vladimir; Waldispühl, Jérôme

2016-11-11

Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. In this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families. We test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database. Our results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement .

DNA Replication Profiling Using Deep Sequencing.

Science.gov (United States)

Saayman, Xanita; Ramos-Pérez, Cristina; Brown, Grant W

2018-01-01

Profiling of DNA replication during progression through S phase allows a quantitative snap-shot of replication origin usage and DNA replication fork progression. We present a method for using deep sequencing data to profile DNA replication in S. cerevisiae.

Reconstruction of ancestral RNA sequences under multiple structural constraints

OpenAIRE

Tremblay-Savard, Olivier; Reinharz, Vladimir; Waldisp?hl, J?r?me

2016-01-01

Background Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. Methods In this paper, we introduce achARNement, a maximum parsimony approach that, given...

Import of desired nucleic acid sequences using addressing motif of mitochondrial ribosomal 5S-rRNA for fluorescent in vivo hybridization of mitochondrial DNA and RNA.

Science.gov (United States)

Zelenka, Jaroslav; Alán, Lukáš; Jabůrek, Martin; Ježek, Petr

2014-04-01

Based on the matrix-addressing sequence of mitochondrial ribosomal 5S-rRNA (termed MAM), which is naturally imported into mitochondria, we have constructed an import system for in vivo targeting of mitochondrial DNA (mtDNA) or mt-mRNA, in order to provide fluorescence hybridization of the desired sequences. Thus DNA oligonucleotides were constructed, containing the 5'-flanked T7 RNA polymerase promoter. After in vitro transcription and fluorescent labeling with Alexa Fluor(®) 488 or 647 dye, we obtained the fluorescent "L-ND5 probe" containing MAM and exemplar cargo, i.e., annealing sequence to a short portion of ND5 mRNA and to the light-strand mtDNA complementary to the heavy strand nd5 mt gene (5'-end 21 base pair sequence). For mitochondrial in vivo fluorescent hybridization, HepG2 cells were treated with dequalinium micelles, containing the fluorescent probes, bringing the probes proximally to the mitochondrial outer membrane and to the natural import system. A verification of import into the mitochondrial matrix of cultured HepG2 cells was provided by confocal microscopy colocalizations. Transfections using lipofectamine or probes without 5S-rRNA addressing MAM sequence or with MAM only were ineffective. Alternatively, the same DNA oligonucleotides with 5'-CACC overhang (substituting T7 promoter) were transcribed from the tetracycline-inducible pENTRH1/TO vector in human embryonic kidney T-REx®-293 cells, while mitochondrial matrix localization after import of the resulting unlabeled RNA was detected by PCR. The MAM-containing probe was then enriched by three-order of magnitude over the natural ND5 mRNA in the mitochondrial matrix. In conclusion, we present a proof-of-principle for mitochondrial in vivo hybridization and mitochondrial nucleic acid import.

Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons.

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Magdalena Guardiola

Full Text Available Marine sediments are home to one of the richest species pools on Earth, but logistics and a dearth of taxonomic work-force hinders the knowledge of their biodiversity. We characterized α- and β-diversity of deep-sea assemblages from submarine canyons in the western Mediterranean using an environmental DNA metabarcoding. We used a new primer set targeting a short eukaryotic 18S sequence (ca. 110 bp. We applied a protocol designed to obtain extractions enriched in extracellular DNA from replicated sediment corers. With this strategy we captured information from DNA (local or deposited from the water column that persists adsorbed to inorganic particles and buffered short-term spatial and temporal heterogeneity. We analysed replicated samples from 20 localities including 2 deep-sea canyons, 1 shallower canal, and two open slopes (depth range 100-2,250 m. We identified 1,629 MOTUs, among which the dominant groups were Metazoa (with representatives of 19 phyla, Alveolata, Stramenopiles, and Rhizaria. There was a marked small-scale heterogeneity as shown by differences in replicates within corers and within localities. The spatial variability between canyons was significant, as was the depth component in one of the canyons where it was tested. Likewise, the composition of the first layer (1 cm of sediment was significantly different from deeper layers. We found that qualitative (presence-absence and quantitative (relative number of reads data showed consistent trends of differentiation between samples and geographic areas. The subset of exclusively benthic MOTUs showed similar patterns of β-diversity and community structure as the whole dataset. Separate analyses of the main metazoan phyla (in number of MOTUs showed some differences in distribution attributable to different lifestyles. Our results highlight the differentiation that can be found even between geographically close assemblages, and sets the ground for future monitoring and conservation

Poly(A)-tag deep sequencing data processing to extract poly(A) sites.

Science.gov (United States)

Wu, Xiaohui; Ji, Guoli; Li, Qingshun Quinn

2015-01-01

Polyadenylation [poly(A)] is an essential posttranscriptional processing step in the maturation of eukaryotic mRNA. The advent of next-generation sequencing (NGS) technology has offered feasible means to generate large-scale data and new opportunities for intensive study of polyadenylation, particularly deep sequencing of the transcriptome targeting the junction of 3'-UTR and the poly(A) tail of the transcript. To take advantage of this unprecedented amount of data, we present an automated workflow to identify polyadenylation sites by integrating NGS data cleaning, processing, mapping, normalizing, and clustering. In this pipeline, a series of Perl scripts are seamlessly integrated to iteratively map the single- or paired-end sequences to the reference genome. After mapping, the poly(A) tags (PATs) at the same genome coordinate are grouped into one cleavage site, and the internal priming artifacts removed. Then the ambiguous region is introduced to parse the genome annotation for cleavage site clustering. Finally, cleavage sites within a close range of 24 nucleotides and from different samples can be clustered into poly(A) clusters. This procedure could be used to identify thousands of reliable poly(A) clusters from millions of NGS sequences in different tissues or treatments.

Next-generation sequencing library preparation method for identification of RNA viruses on the Ion Torrent Sequencing Platform.

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Chen, Guiqian; Qiu, Yuan; Zhuang, Qingye; Wang, Suchun; Wang, Tong; Chen, Jiming; Wang, Kaicheng

2018-05-09

Next generation sequencing (NGS) is a powerful tool for the characterization, discovery, and molecular identification of RNA viruses. There were multiple NGS library preparation methods published for strand-specific RNA-seq, but some methods are not suitable for identifying and characterizing RNA viruses. In this study, we report a NGS library preparation method to identify RNA viruses using the Ion Torrent PGM platform. The NGS sequencing adapters were directly inserted into the sequencing library through reverse transcription and polymerase chain reaction, without fragmentation and ligation of nucleic acids. The results show that this method is simple to perform, able to identify multiple species of RNA viruses in clinical samples.

RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

Science.gov (United States)

Pan, Xiaoyong; Shen, Hong-Bin

2017-02-28

RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

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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 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 Active Immune Defense with a Minimal CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) RNA and without the Cas6 Protein*

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Maier, Lisa-Katharina; Stachler, Aris-Edda; Saunders, Sita J.; Backofen, Rolf; Marchfelder, Anita

2015-01-01

The prokaryotic immune system CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated) is a defense system that protects prokaryotes against foreign DNA. The short CRISPR RNAs (crRNAs) are central components of this immune system. In CRISPR-Cas systems type I and III, crRNAs are generated by the endonuclease Cas6. We developed a Cas6b-independent crRNA maturation pathway for the Haloferax type I-B system in vivo that expresses a functional crRNA, which we termed independently generated crRNA (icrRNA). The icrRNA is effective in triggering degradation of an invader plasmid carrying the matching protospacer sequence. The Cas6b-independent maturation of the icrRNA allowed mutation of the repeat sequence without interfering with signals important for Cas6b processing. We generated 23 variants of the icrRNA and analyzed them for activity in the interference reaction. icrRNAs with deletions or mutations of the 3′ handle are still active in triggering an interference reaction. The complete 3′ handle could be removed without loss of activity. However, manipulations of the 5′ handle mostly led to loss of interference activity. Furthermore, we could show that in the presence of an icrRNA a strain without Cas6b (Δcas6b) is still active in interference. PMID:25512373

An active immune defense with a minimal CRISPR (clustered regularly interspaced short palindromic repeats) RNA and without the Cas6 protein.

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Maier, Lisa-Katharina; Stachler, Aris-Edda; Saunders, Sita J; Backofen, Rolf; Marchfelder, Anita

2015-02-13

The prokaryotic immune system CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated) is a defense system that protects prokaryotes against foreign DNA. The short CRISPR RNAs (crRNAs) are central components of this immune system. In CRISPR-Cas systems type I and III, crRNAs are generated by the endonuclease Cas6. We developed a Cas6b-independent crRNA maturation pathway for the Haloferax type I-B system in vivo that expresses a functional crRNA, which we termed independently generated crRNA (icrRNA). The icrRNA is effective in triggering degradation of an invader plasmid carrying the matching protospacer sequence. The Cas6b-independent maturation of the icrRNA allowed mutation of the repeat sequence without interfering with signals important for Cas6b processing. We generated 23 variants of the icrRNA and analyzed them for activity in the interference reaction. icrRNAs with deletions or mutations of the 3' handle are still active in triggering an interference reaction. The complete 3' handle could be removed without loss of activity. However, manipulations of the 5' handle mostly led to loss of interference activity. Furthermore, we could show that in the presence of an icrRNA a strain without Cas6b (Δcas6b) is still active in interference. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

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Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Mutation of miRNA target sequences during human evolution

DEFF Research Database (Denmark)

Gardner, Paul P; Vinther, Jeppe

2008-01-01

It has long-been hypothesized that changes in non-protein-coding genes and the regulatory sequences controlling expression could undergo positive selection. Here we identify 402 putative microRNA (miRNA) target sequences that have been mutated specifically in the human lineage and show that genes...... containing such deletions are more highly expressed than their mouse orthologs. Our findings indicate that some miRNA target mutations are fixed by positive selection and might have been involved in the evolution of human-specific traits....

Systematic Analysis of Long Noncoding RNAs in the Senescence-accelerated Mouse Prone 8 Brain Using RNA Sequencing

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Shuai Zhang

2016-01-01

Full Text Available Long noncoding RNAs (lncRNAs may play an important role in Alzheimer's disease (AD pathogenesis. However, despite considerable research in this area, the comprehensive and systematic understanding of lncRNAs in AD is still limited. The emergence of RNA sequencing provides a predictor and has incomparable advantage compared with other methods, including microarray. In this study, we identified lncRNAs in a 7-month-old mouse brain through deep RNA sequencing using the senescence-accelerated mouse prone 8 (SAMP8 and senescence-accelerated mouse resistant 1 (SAMR1 models. A total of 599,985,802 clean reads and 23,334 lncRNA transcripts were obtained. Then, we identified 97 significantly upregulated and 114 significantly downregulated lncRNA transcripts from all cases in SAMP8 mice relative to SAMR1 mice. Gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes analyses revealed that these significantly dysregulated lncRNAs were involved in regulating the development of AD from various angles, such as nerve growth factor term (GO: 1990089, mitogen-activated protein kinase signaling pathway, and AD pathway. Furthermore, the most probable AD-associated lncRNAs were predicted and listed in detail. Our study provided the systematic dissection of lncRNA profiling in SAMP8 mouse brain and accelerated the development of lncRNA biomarkers in AD. These attracting biomarkers could provide significant insights into AD therapy in the future.

SimFuse: A Novel Fusion Simulator for RNA Sequencing (RNA-Seq Data

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Yuxiang Tan

2015-01-01

Full Text Available The performance evaluation of fusion detection algorithms from high-throughput sequencing data crucially relies on the availability of data with known positive and negative cases of gene rearrangements. The use of simulated data circumvents some shortcomings of real data by generation of an unlimited number of true and false positive events, and the consequent robust estimation of accuracy measures, such as precision and recall. Although a few simulated fusion datasets from RNA Sequencing (RNA-Seq are available, they are of limited sample size. This makes it difficult to systematically evaluate the performance of RNA-Seq based fusion-detection algorithms. Here, we present SimFuse to address this problem. SimFuse utilizes real sequencing data as the fusions’ background to closely approximate the distribution of reads from a real sequencing library and uses a reference genome as the template from which to simulate fusions’ supporting reads. To assess the supporting read-specific performance, SimFuse generates multiple datasets with various numbers of fusion supporting reads. Compared to an extant simulated dataset, SimFuse gives users control over the supporting read features and the sample size of the simulated library, based on which the performance metrics needed for the validation and comparison of alternative fusion-detection algorithms can be rigorously estimated.

Transcriptome sequencing of the Microarray Quality Control (MAQC RNA reference samples using next generation sequencing

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Thierry-Mieg Danielle

2009-06-01

Full Text Available Abstract Background Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC reference RNA samples using Roche's 454 Genome Sequencer FLX. Results We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database. Conclusion Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.

Reconstruction of ancestral RNA sequences under multiple structural constraints

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Olivier Tremblay-Savard

2016-11-01

Full Text Available Abstract Background Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. Methods In this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families. Results We test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database. Conclusions Our results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement .

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

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Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

2014-03-05

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

Sequence-specific inhibition of microRNA-130a gene by CRISPR/Cas9 system in breast cancer cell line

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Ainina Abdollah, Nur; Das Kumitaa, Theva; Yusof Narazah, Mohd; Razak, Siti Razila Abdul

2017-05-01

MicroRNAs (miRNAs) are short stranded noncoding RNA that play important roles in apoptosis, cell survival, development and cell proliferation. However, gene expression control via small regulatory RNA, particularly miRNA in breast cancer is still less explored. Therefore, this project aims to develop an approach to target microRNA-130a using the Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 system in MCF7, breast cancer cell line. The 20 bp sequences target at stem loop, 3ʹ and 5ʹ end of miR130a were cloned into pSpCas9(BB)-2A-GFP (PX458) plasmid, and the positive clones were confirmed by sequencing. A total of 5 μg of PX458-miR130a was transfected to MCF7 using Lipofectamine® 3000 according to manufacturer’s protocol. The transfected cells were maintained in the incubator at 37 °C under humidified 5% CO2. After 48 hours, cells were harvested and total RNA was extracted using miRNeasy Mini Kit (Qiagen). cDNAs were synthesised specific to miR-130a using TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems). Then, qRT-PCR was carried out using TaqMan Universal Master Mix (Applied Biosystems) to quantify the knockdown level of mature miRNAs in the cells. Result showed that miR-130a-5p was significantly downregulated in MCF7 cell line. However, no significant changes were observed for sequences targeting miR-130a-3p and stem loop. Thus, this study showed that the expression of miR-130a-5p was successfully down-regulated using CRISPR silencing system. This technique may be useful to manipulate the level of miRNA in various cell types to answer clinical questions at the molecular level.

MATAM: reconstruction of phylogenetic marker genes from short sequencing reads in metagenomes.

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Pericard, Pierre; Dufresne, Yoann; Couderc, Loïc; Blanquart, Samuel; Touzet, Hélène

2018-02-15

Advances in the sequencing of uncultured environmental samples, dubbed metagenomics, raise a growing need for accurate taxonomic assignment. Accurate identification of organisms present within a community is essential to understanding even the most elementary ecosystems. However, current high-throughput sequencing technologies generate short reads which partially cover full-length marker genes and this poses difficult bioinformatic challenges for taxonomy identification at high resolution. We designed MATAM, a software dedicated to the fast and accurate targeted assembly of short reads sequenced from a genomic marker of interest. The method implements a stepwise process based on construction and analysis of a read overlap graph. It is applied to the assembly of 16S rRNA markers and is validated on simulated, synthetic and genuine metagenomes. We show that MATAM outperforms other available methods in terms of low error rates and recovered fractions and is suitable to provide improved assemblies for precise taxonomic assignments. https://github.com/bonsai-team/matam. pierre.pericard@gmail.com or helene.touzet@univ-lille1.fr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

RNA-Mediated Gene Duplication and Retroposons: Retrogenes, LINEs, SINEs, and Sequence Specificity

Science.gov (United States)

2013-01-01

A substantial number of “retrogenes” that are derived from the mRNA of various intron-containing genes have been reported. A class of mammalian retroposons, long interspersed element-1 (LINE1, L1), has been shown to be involved in the reverse transcription of retrogenes (or processed pseudogenes) and non-autonomous short interspersed elements (SINEs). The 3′-end sequences of various SINEs originated from a corresponding LINE. As the 3′-untranslated regions of several LINEs are essential for retroposition, these LINEs presumably require “stringent” recognition of the 3′-end sequence of the RNA template. However, the 3′-ends of mammalian L1s do not exhibit any similarity to SINEs, except for the presence of 3′-poly(A) repeats. Since the 3′-poly(A) repeats of L1 and Alu SINE are critical for their retroposition, L1 probably recognizes the poly(A) repeats, thereby mobilizing not only Alu SINE but also cytosolic mRNA. Many flowering plants only harbor L1-clade LINEs and a significant number of SINEs with poly(A) repeats, but no homology to the LINEs. Moreover, processed pseudogenes have also been found in flowering plants. I propose that the ancestral L1-clade LINE in the common ancestor of green plants may have recognized a specific RNA template, with stringent recognition then becoming relaxed during the course of plant evolution. PMID:23984183

Deep RNA-Seq analysis reveals unexpected features of human prostate basal epithelial cells

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Dingxiao Zhang

2016-03-01

Full Text Available Prostate cancer is the second leading cause of cancer-related deaths among American men [1]. The prostate gland mainly contains basal and luminal cells, which are constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here, for the first time, we describe a whole-genome transcriptome analysis of human benign prostatic basal and luminal populations by using deep RNA sequencing (GSE67070 [2]. Combined with comprehensive molecular and biological characterizations, we show that the differential gene expression profiles account for their distinct functional phenotypes. Strikingly, in contrast to luminal cells, basal cells preferentially express gene categories associated with stem cells, neural and neuronal development, and RNA processing. Of clinical relevance, the treatment failed castration-resistant and anaplastic prostate cancers molecularly resemble a basal-like phenotype. We also identified genes associated with patient clinical outcome. Therefore, we provide a gene expression resource for understanding human prostate epithelial lineages, and link the cell-type specific gene signatures to subtypes of prostate cancer development. Keywords: Prostate epithelial cells, Basal cells, Luminal cells, RNA-seq

Characterisation of the human uterine microbiome in non-pregnant women through deep sequencing of the V1-2 region of the 16S rRNA gene

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Hans Verstraelen

2016-01-01

Full Text Available Background. It is widely assumed that the uterine cavity in non-pregnant women is physiologically sterile, also as a premise to the long-held view that human infants develop in a sterile uterine environment, though likely reflecting under-appraisal of the extent of the human bacterial metacommunity. In an exploratory study, we aimed to investigate the putative presence of a uterine microbiome in a selected series of non-pregnant women through deep sequencing of the V1-2 hypervariable region of the 16S ribosomal RNA (rRNA gene.Methods. Nineteen women with various reproductive conditions, including subfertility, scheduled for hysteroscopy and not showing uterine anomalies were recruited. Subjects were highly diverse with regard to demographic and medical history and included nulliparous and parous women. Endometrial tissue and mucus harvesting was performed by use of a transcervical device designed to obtain endometrial biopsy, while avoiding cervicovaginal contamination. Bacteria were targeted by use of a barcoded Illumina MiSeq paired-end sequencing method targeting the 16S rRNA gene V1-2 region, yielding an average of 41,194 reads per sample after quality filtering. Taxonomic annotation was pursued by comparison with sequences available through the Ribosomal Database Project and the NCBI database.Results. Out of 183 unique 16S rRNA gene amplicon sequences, 15 phylotypes were present in all samples. In some 90% of the women included, community architecture was fairly similar inasmuch B. xylanisolvens, B. thetaiotaomicron, B. fragilis and an undetermined Pelomonas taxon constituted over one third of the endometrial bacterial community. On the singular phylotype level, six women showed predominance of L. crispatus or L. iners in the presence of the Bacteroides core. Two endometrial communities were highly dissimilar, largely lacking the Bacteroides core, one dominated by L. crispatus and another consisting of a highly diverse community, including

Two RNAs or DNAs May Artificially Fuse Together at a Short Homologous Sequence (SHS) during Reverse Transcription or Polymerase Chain Reactions, and Thus Reporting an SHS-Containing Chimeric RNA Requires Extra Caution

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Xie, Bingkun; Yang, Wei; Ouyang, Yongchang; Chen, Lichan; Jiang, Hesheng; Liao, Yuying; Liao, D. Joshua

2016-01-01

Tens of thousands of chimeric RNAs have been reported. Most of them contain a short homologous sequence (SHS) at the joining site of the two partner genes but are not associated with a fusion gene. We hypothesize that many of these chimeras may be technical artifacts derived from SHS-caused mis-priming in reverse transcription (RT) or polymerase chain reactions (PCR). We cloned six chimeric complementary DNAs (cDNAs) formed by human mitochondrial (mt) 16S rRNA sequences at an SHS, which were similar to several expression sequence tags (ESTs).These chimeras, which could not be detected with cDNA protection assay, were likely formed because some regions of the 16S rRNA are reversely complementary to another region to form an SHS, which allows the downstream sequence to loop back and anneal at the SHS to prime the synthesis of its complementary strand, yielding a palindromic sequence that can form a hairpin-like structure.We identified a 16S rRNA that ended at the 4th nucleotide(nt) of the mt-tRNA-leu was dominant and thus should be the wild type. We also cloned a mouse Bcl2-Nek9 chimeric cDNA that contained a 5-nt unmatchable sequence between the two partners, contained two copies of the reverse primer in the same direction but did not contain the forward primer, making it unclear how this Bcl2-Nek9 was formed and amplified. Moreover, a cDNA was amplified because one primer has 4 nts matched to the template, suggesting that there may be many more artificial cDNAs than we have realized, because the nuclear and mt genomes have many more 4-nt than 5-nt or longer homologues. Altogether, the chimeric cDNAs we cloned are good examples suggesting that many cDNAs may be artifacts due to SHS-caused mis-priming and thus greater caution should be taken when new sequence is obtained from a technique involving DNA polymerization. PMID:27148738

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

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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.

A comprehensive evaluation of the sl1p pipeline for 16S rRNA gene sequencing analysis.

Science.gov (United States)

Whelan, Fiona J; Surette, Michael G

2017-08-14

Advances in next-generation sequencing technologies have allowed for detailed, molecular-based studies of microbial communities such as the human gut, soil, and ocean waters. Sequencing of the 16S rRNA gene, specific to prokaryotes, using universal PCR primers has become a common approach to studying the composition of these microbiota. However, the bioinformatic processing of the resulting millions of DNA sequences can be challenging, and a standardized protocol would aid in reproducible analyses. The short-read library 16S rRNA gene sequencing pipeline (sl1p, pronounced "slip") was designed with the purpose of mitigating this lack of reproducibility by combining pre-existing tools into a computational pipeline. This pipeline automates the processing of raw 16S rRNA gene sequencing data to create human-readable tables, graphs, and figures to make the collected data more readily accessible. Data generated from mock communities were compared using eight OTU clustering algorithms, two taxon assignment approaches, and three 16S rRNA gene reference databases. While all of these algorithms and options are available to sl1p users, through testing with human-associated mock communities, AbundantOTU+, the RDP Classifier, and the Greengenes 2011 reference database were chosen as sl1p's defaults based on their ability to best represent the known input communities. sl1p promotes reproducible research by providing a comprehensive log file, and reduces the computational knowledge needed by the user to process next-generation sequencing data. sl1p is freely available at https://bitbucket.org/fwhelan/sl1p .

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

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Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

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Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

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Manal Helal

Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing.

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Anvar, Seyed Yahya; Allard, Guy; Tseng, Elizabeth; Sheynkman, Gloria M; de Klerk, Eleonora; Vermaat, Martijn; Yin, Raymund H; Johansson, Hans E; Ariyurek, Yavuz; den Dunnen, Johan T; Turner, Stephen W; 't Hoen, Peter A C

2018-03-29

The multifaceted control of gene expression requires tight coordination of regulatory mechanisms at transcriptional and post-transcriptional level. Here, we studied the interdependence of transcription initiation, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing. In MCF-7 breast cancer cells, we find 2700 genes with interdependent alternative transcription initiation, splicing and polyadenylation events, both in proximal and distant parts of mRNA molecules, including examples of coupling between transcription start sites and polyadenylation sites. The analysis of three human primary tissues (brain, heart and liver) reveals similar patterns of interdependency between transcription initiation and mRNA processing events. We predict thousands of novel open reading frames from full-length mRNA sequences and obtained evidence for their translation by shotgun proteomics. The mapping database rescues 358 previously unassigned peptides and improves the assignment of others. By recognizing sample-specific amino-acid changes and novel splicing patterns, full-length mRNA sequencing improves proteogenomics analysis of MCF-7 cells. Our findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a basis to reveal largely unresolved mechanisms that coordinate transcription initiation and mRNA processing.

"Transcriptomics": molecular diagnosis of inborn errors of metabolism via RNA-sequencing.

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Kremer, Laura S; Wortmann, Saskia B; Prokisch, Holger

2018-01-25

Exome wide sequencing techniques have revolutionized molecular diagnostics in patients with suspected inborn errors of metabolism or neuromuscular disorders. However, the diagnostic yield of 25-60% still leaves a large fraction of individuals without a diagnosis. This indicates a causative role for non-exonic regulatory variants not covered by whole exome sequencing. Here we review how systematic RNA-sequencing analysis (RNA-seq, "transcriptomics") lead to a molecular diagnosis in 10-35% of patients in whom whole exome sequencing failed to do so. Importantly, RNA-sequencing based discoveries cannot only guide molecular diagnosis but might also unravel therapeutic intervention points such as antisense oligonucleotide treatment for splicing defects as recently reported for spinal muscular atrophy.

Short read sequence typing (SRST: multi-locus sequence types from short reads

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Inouye Michael

2012-07-01

Full Text Available Abstract Background Multi-locus sequence typing (MLST has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context. Results We present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles. Conclusions SRST is a novel

Re-inspection of small RNA sequence datasets reveals several novel human miRNA genes.

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Thomas Birkballe Hansen

Full Text Available BACKGROUND: miRNAs are key players in gene expression regulation. To fully understand the complex nature of cellular differentiation or initiation and progression of disease, it is important to assess the expression patterns of as many miRNAs as possible. Thereby, identifying novel miRNAs is an essential prerequisite to make possible a comprehensive and coherent understanding of cellular biology. METHODOLOGY/PRINCIPAL FINDINGS: Based on two extensive, but previously published, small RNA sequence datasets from human embryonic stem cells and human embroid bodies, respectively [1], we identified 112 novel miRNA-like structures and were able to validate miRNA processing in 12 out of 17 investigated cases. Several miRNA candidates were furthermore substantiated by including additional available small RNA datasets, thereby demonstrating the power of combining datasets to identify miRNAs that otherwise may be assigned as experimental noise. CONCLUSIONS/SIGNIFICANCE: Our analysis highlights that existing datasets are not yet exhaustedly studied and continuous re-analysis of the available data is important to uncover all features of small RNA sequencing.

A sensitive short read homology search tool for paired-end read sequencing data.

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Techa-Angkoon, Prapaporn; Sun, Yanni; Lei, Jikai

2017-10-16

Homology search is still a significant step in functional analysis for genomic data. Profile Hidden Markov Model-based homology search has been widely used in protein domain analysis in many different species. In particular, with the fast accumulation of transcriptomic data of non-model species and metagenomic data, profile homology search is widely adopted in integrated pipelines for functional analysis. While the state-of-the-art tool HMMER has achieved high sensitivity and accuracy in domain annotation, the sensitivity of HMMER on short reads declines rapidly. The low sensitivity on short read homology search can lead to inaccurate domain composition and abundance computation. Our experimental results showed that half of the reads were missed by HMMER for a RNA-Seq dataset. Thus, there is a need for better methods to improve the homology search performance for short reads. We introduce a profile homology search tool named Short-Pair that is designed for short paired-end reads. By using an approximate Bayesian approach employing distribution of fragment lengths and alignment scores, Short-Pair can retrieve the missing end and determine true domains. In particular, Short-Pair increases the accuracy in aligning short reads that are part of remote homologs. We applied Short-Pair to a RNA-Seq dataset and a metagenomic dataset and quantified its sensitivity and accuracy on homology search. The experimental results show that Short-Pair can achieve better overall performance than the state-of-the-art methodology of profile homology search. Short-Pair is best used for next-generation sequencing (NGS) data that lack reference genomes. It provides a complementary paired-end read homology search tool to HMMER. The source code is freely available at https://sourceforge.net/projects/short-pair/ .

An integrated computational validation approach for potential novel miRNA prediction

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Pooja Viswam

2017-12-01

Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

MicroRNA sequence motifs reveal asymmetry between the stem arms

DEFF Research Database (Denmark)

Gorodkin, Jan; Havgaard, Jakob Hull; Ensterö, M.

2006-01-01

The processing of micro RNAs (miRNAs) from their stemloop precursor have revealed asymmetry in the processing of the mature and its star sequence. Furthermore, the miRNA processing system between organism differ. To assess this at the sequence level we have investigated mature miRNAs in their gen......The processing of micro RNAs (miRNAs) from their stemloop precursor have revealed asymmetry in the processing of the mature and its star sequence. Furthermore, the miRNA processing system between organism differ. To assess this at the sequence level we have investigated mature mi...

Deep sequencing-based analysis of the anaerobic stimulon in Neisseria gonorrhoeae

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Clark Virginia L

2011-01-01

Full Text Available Abstract Background Maintenance of an anaerobic denitrification system in the obligate human pathogen, Neisseria gonorrhoeae, suggests that an anaerobic lifestyle may be important during the course of infection. Furthermore, mounting evidence suggests that reduction of host-produced nitric oxide has several immunomodulary effects on the host. However, at this point there have been no studies analyzing the complete gonococcal transcriptome response to anaerobiosis. Here we performed deep sequencing to compare the gonococcal transcriptomes of aerobically and anaerobically grown cells. Using the information derived from this sequencing, we discuss the implications of the robust transcriptional response to anaerobic growth. Results We determined that 198 chromosomal genes were differentially expressed (~10% of the genome in response to anaerobic conditions. We also observed a large induction of genes encoded within the cryptic plasmid, pJD1. Validation of RNA-seq data using translational-lacZ fusions or RT-PCR demonstrated the RNA-seq results to be very reproducible. Surprisingly, many genes of prophage origin were induced anaerobically, as well as several transcriptional regulators previously unknown to be involved in anaerobic growth. We also confirmed expression and regulation of a small RNA, likely a functional equivalent of fnrS in the Enterobacteriaceae family. We also determined that many genes found to be responsive to anaerobiosis have also been shown to be responsive to iron and/or oxidative stress. Conclusions Gonococci will be subject to many forms of environmental stress, including oxygen-limitation, during the course of infection. Here we determined that the anaerobic stimulon in gonococci was larger than previous studies would suggest. Many new targets for future research have been uncovered, and the results derived from this study may have helped to elucidate factors or mechanisms of virulence that may have otherwise been overlooked.

DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

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Tsuji, Junko; Weng, Zhiping

2016-01-01

With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were "ready-to-map" small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.

Evasion of short interfering RNA-directed antiviral silencing in Musa acuminata persistently infected with six distinct banana streak pararetroviruses.

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Rajeswaran, Rajendran; Seguin, Jonathan; Chabannes, Matthieu; Duroy, Pierre-Olivier; Laboureau, Nathalie; Farinelli, Laurent; Iskra-Caruana, Marie-Line; Pooggin, Mikhail M

2014-10-01

Vegetatively propagated crop plants often suffer from infections with persistent RNA and DNA viruses. Such viruses appear to evade the plant defenses that normally restrict viral replication and spread. The major antiviral defense mechanism is based on RNA silencing generating viral short interfering RNAs (siRNAs) that can potentially repress viral genes posttranscriptionally through RNA cleavage and transcriptionally through DNA cytosine methylation. Here we examined the RNA silencing machinery of banana plants persistently infected with six pararetroviruses after many years of vegetative propagation. Using deep sequencing, we reconstructed consensus master genomes of the viruses and characterized virus-derived and endogenous small RNAs. Consistent with the presence of endogenous siRNAs that can potentially establish and maintain DNA methylation, the banana genomic DNA was extensively methylated in both healthy and virus-infected plants. A novel class of abundant 20-nucleotide (nt) endogenous small RNAs with 5'-terminal guanosine was identified. In all virus-infected plants, 21- to 24-nt viral siRNAs accumulated at relatively high levels (up to 22% of the total small RNA population) and covered the entire circular viral DNA genomes in both orientations. The hotspots of 21-nt and 22-nt siRNAs occurred within open reading frame (ORF) I and II and the 5' portion of ORF III, while 24-nt siRNAs were more evenly distributed along the viral genome. Despite the presence of abundant viral siRNAs of different size classes, the viral DNA was largely free of cytosine methylation. Thus, the virus is able to evade siRNA-directed DNA methylation and thereby avoid transcriptional silencing. This evasion of silencing likely contributes to the persistence of pararetroviruses in banana plants. We report that DNA pararetroviruses in Musa acuminata banana plants are able to evade DNA cytosine methylation and transcriptional gene silencing, despite being targeted by the host silencing

Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.

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Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S

2012-01-01

RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

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Steffen C. Lott

2018-04-01

Full Text Available Bacterial small RNAs (sRNAs are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.

Genome-wide identification of soybean microRNA responsive to soybean cyst nematodes infection by deep sequencing.

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Tian, Bin; Wang, Shichen; Todd, Timothy C; Johnson, Charles D; Tang, Guiliang; Trick, Harold N

2017-08-02

The soybean cyst nematode (SCN), Heterodera glycines, is one of the most devastating diseases limiting soybean production worldwide. It is known that small RNAs, including microRNAs (miRNAs) and small interfering RNAs (siRNAs), play important roles in regulating plant growth and development, defense against pathogens, and responses to environmental changes. In order to understand the role of soybean miRNAs during SCN infection, we analyzed 24 small RNA libraries including three biological replicates from two soybean cultivars (SCN susceptible KS4607, and SCN HG Type 7 resistant KS4313N) that were grown under SCN-infested and -noninfested soil at two different time points (SCN feeding establishment and egg production). In total, 537 known and 70 putative novel miRNAs in soybean were identified from a total of 0.3 billion reads (average about 13.5 million reads for each sample) with the programs of Bowtie and miRDeep2 mapper. Differential expression analyses were carried out using edgeR to identify miRNAs involved in the soybean-SCN interaction. Comparative analysis of miRNA profiling indicated a total of 60 miRNAs belonging to 25 families that might be specifically related to cultivar responses to SCN. Quantitative RT-PCR validated similar miRNA interaction patterns as sequencing results. These findings suggest that miRNAs are likely to play key roles in soybean response to SCN. The present work could provide a framework for miRNA functional identification and the development of novel approaches for improving soybean SCN resistance in future studies.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

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Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Mechanisms controlling mRNA processing and translation : decoding the regulatory layers defining gene expression through RNA sequencing

NARCIS (Netherlands)

Klerk, Eleonora de

2015-01-01

The work described in this thesis focuses on the mechanisms that give rise to alternative mRNAs and their alternative translation into proteins. Each of the described studies has been based on a specific set of high-throughput RNA sequencing technologies. An overview of the available RNA sequencing

Organism-specific rRNA capture system for application in next-generation sequencing.

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Sai-Kam Li

Full Text Available RNA-sequencing is a powerful tool in studying RNomics. However, the highly abundance of ribosomal RNAs (rRNA and transfer RNA (tRNA have predominated in the sequencing reads, thereby hindering the study of lowly expressed genes. Therefore, rRNA depletion prior to sequencing is often performed in order to preserve the subtle alteration in gene expression especially those at relatively low expression levels. One of the commercially available methods is to use DNA or RNA probes to hybridize to the target RNAs. However, there is always a concern with the non-specific binding and unintended removal of messenger RNA (mRNA when the same set of probes is applied to different organisms. The degree of such unintended mRNA removal varies among organisms due to organism-specific genomic variation. We developed a computer-based method to design probes to deplete rRNA in an organism-specific manner. Based on the computation results, biotinylated-RNA-probes were produced by in vitro transcription and were used to perform rRNA depletion with subtractive hybridization. We demonstrated that the designed probes of 16S rRNAs and 23S rRNAs can efficiently remove rRNAs from Mycobacterium smegmatis. In comparison with a commercial subtractive hybridization-based rRNA removal kit, using organism-specific probes is better in preserving the RNA integrity and abundance. We believe the computer-based design approach can be used as a generic method in preparing RNA of any organisms for next-generation sequencing, particularly for the transcriptome analysis of microbes.

Mature clustered, regularly interspaced, short palindromic repeats RNA (crRNA) length is measured by a ruler mechanism anchored at the precursor processing site.

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Hatoum-Aslan, Asma; Maniv, Inbal; Marraffini, Luciano A

2011-12-27

Precise RNA processing is fundamental to all small RNA-mediated interference pathways. In prokaryotes, clustered, regularly interspaced, short palindromic repeats (CRISPR) loci encode small CRISPR RNAs (crRNAs) that protect against invasive genetic elements by antisense targeting. CRISPR loci are transcribed as a long precursor that is cleaved within repeat sequences by CRISPR-associated (Cas) proteins. In many organisms, this primary processing generates crRNA intermediates that are subject to additional nucleolytic trimming to render mature crRNAs of specific lengths. The molecular mechanisms underlying this maturation event remain poorly understood. Here, we defined the genetic requirements for crRNA primary processing and maturation in Staphylococcus epidermidis. We show that changes in the position of the primary processing site result in extended or diminished maturation to generate mature crRNAs of constant length. These results indicate that crRNA maturation occurs by a ruler mechanism anchored at the primary processing site. We also show that maturation is mediated by specific cas genes distinct from those genes involved in primary processing, showing that this event is directed by CRISPR/Cas loci.

A cost-effective method for Illumina small RNA-Seq library preparation using T4 RNA ligase 1 adenylated adapters

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Chen Yun-Ru

2012-09-01

Full Text Available Abstract Background Deep sequencing is a powerful tool for novel small RNA discovery. Illumina small RNA sequencing library preparation requires a pre-adenylated 3’ end adapter containing a 5’,5’-adenyl pyrophosphoryl moiety. In the absence of ATP, this adapter can be ligated to the 3’ hydroxyl group of small RNA, while RNA self-ligation and concatenation are repressed. Pre-adenylated adapters are one of the most essential and costly components required for library preparation, and few are commercially available. Results We demonstrate that DNA oligo with 5’ phosphate and 3’ amine groups can be enzymatically adenylated by T4 RNA ligase 1 to generate customized pre-adenylated adapters. We have constructed and sequenced a small RNA library for tomato (Solanum lycopersicum using the T4 RNA ligase 1 adenylated adapter. Conclusion We provide an efficient and low-cost method for small RNA sequencing library preparation, which takes two days to complete and costs around $20 per library. This protocol has been tested in several plant species for small RNA sequencing including sweet potato, pepper, watermelon, and cowpea, and could be readily applied to any RNA samples.

Predicting effects of noncoding variants with deep learning-based sequence model.

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Zhou, Jian; Troyanskaya, Olga G

2015-10-01

Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

Deep Ion Torrent sequencing identifies soil fungal community shifts after frequent prescribed fires in a southeastern US forest ecosystem.

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Brown, Shawn P; Callaham, Mac A; Oliver, Alena K; Jumpponen, Ari

2013-12-01

Prescribed burning is a common management tool to control fuel loads, ground vegetation, and facilitate desirable game species. We evaluated soil fungal community responses to long-term prescribed fire treatments in a loblolly pine forest on the Piedmont of Georgia and utilized deep Internal Transcribed Spacer Region 1 (ITS1) amplicon sequencing afforded by the recent Ion Torrent Personal Genome Machine (PGM). These deep sequence data (19,000 + reads per sample after subsampling) indicate that frequent fires (3-year fire interval) shift soil fungus communities, whereas infrequent fires (6-year fire interval) permit system resetting to a state similar to that without prescribed fire. Furthermore, in nonmetric multidimensional scaling analyses, primarily ectomycorrhizal taxa were correlated with axes associated with long fire intervals, whereas soil saprobes tended to be correlated with the frequent fire recurrence. We conclude that (1) multiplexed Ion Torrent PGM analyses allow deep cost effective sequencing of fungal communities but may suffer from short read lengths and inconsistent sequence quality adjacent to the sequencing adaptor; (2) frequent prescribed fires elicit a shift in soil fungal communities; and (3) such shifts do not occur when fire intervals are longer. Our results emphasize the general responsiveness of these forests to management, and the importance of fire return intervals in meeting management objectives. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Identification of microRNAs Involved in the Host Response to Enterovirus 71 Infection by a Deep Sequencing Approach

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Lunbiao Cui

2010-01-01

Full Text Available Role of microRNA (miRNA has been highlighted in pathogen-host interactions recently. To identify cellular miRNAs involved in the host response to enterovirus 71 (EV71 infection, we performed a comprehensive miRNA profiling in EV71-infected Hep2 cells through deep sequencing. 64 miRNAs were found whose expression levels changed for more than 2-fold in response to EV71 infection. Gene ontology analysis revealed that many of these mRNAs play roles in neurological process, immune response, and cell death pathways, which are known to be associated with the extreme virulence of EV71. To our knowledge, this is the first study on host miRNAs expression alteration response to EV71 infection. Our findings supported the hypothesis that certain miRNAs might be essential in the host-pathogen interactions.

Phylogenetic relationships of Salmonella based on rRNA sequences

DEFF Research Database (Denmark)

Christensen, H.; Nordentoft, Steen; Olsen, J.E.

1998-01-01

separated by 16S rRNA analysis and found to be closely related to the Escherichia coli and Shigella complex by both 16S and 23S rRNA analyses. The diphasic serotypes S. enterica subspp. I and VI were separated from the monophasic serotypes subspp. IIIa and IV, including S. bongori, by 23S rRNA sequence...

Tissue-specific RNA expression marks distant-acting developmental enhancers.

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Han Wu

2014-09-01

Full Text Available Short non-coding transcripts can be transcribed from distant-acting transcriptional enhancer loci, but the prevalence of such enhancer RNAs (eRNAs within the transcriptome, and the association of eRNA expression with tissue-specific enhancer activity in vivo remain poorly understood. Here, we investigated the expression dynamics of tissue-specific non-coding RNAs in embryonic mouse tissues via deep RNA sequencing. Overall, approximately 80% of validated in vivo enhancers show tissue-specific RNA expression that correlates with tissue-specific enhancer activity. Globally, we identified thousands of tissue-specifically transcribed non-coding regions (TSTRs displaying various genomic hallmarks of bona fide enhancers. In transgenic mouse reporter assays, over half of tested TSTRs functioned as enhancers with reproducible activity in the predicted tissue. Together, our results demonstrate that tissue-specific eRNA expression is a common feature of in vivo enhancers, as well as a major source of extragenic transcription, and that eRNA expression signatures can be used to predict tissue-specific enhancers independent of known epigenomic enhancer marks.

Unique small RNA signatures uncovered in the tammar wallaby genome

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Lindsay James

2012-10-01

Full Text Available Abstract Background Small RNAs have proven to be essential regulatory molecules encoded within eukaryotic genomes. These short RNAs participate in a diverse array of cellular processes including gene regulation, chromatin dynamics and genome defense. The tammar wallaby, a marsupial mammal, is a powerful comparative model for studying the evolution of regulatory networks. As part of the genome sequencing initiative for the tammar, we have explored the evolution of each of the major classes of mammalian small RNAs in an Australian marsupial for the first time, including the first genome-scale analysis of the newest class of small RNAs, centromere repeat associated short interacting RNAs (crasiRNAs. Results Using next generation sequencing, we have characterized the major classes of small RNAs, micro (mi RNAs, piwi interacting (pi RNAs, and the centromere repeat associated short interacting (crasi RNAs in the tammar. We examined each of these small RNA classes with respect to the newly assembled tammar wallaby genome for gene and repeat features, salient features that define their canonical sequences, and the constitution of both highly conserved and species-specific members. Using a combination of miRNA hairpin predictions and co-mapping with miRBase entries, we identified a highly conserved cluster of miRNA genes on the X chromosome in the tammar and a total of 94 other predicted miRNA producing genes. Mapping all miRNAs to the tammar genome and comparing target genes among tammar, mouse and human, we identified 163 conserved target genes. An additional nine genes were identified in tammar that do not have an orthologous miRNA target in human and likely represent novel miRNA-regulated genes in the tammar. A survey of the tammar gonadal piRNAs shows that these small RNAs are enriched in retroelements and carry members from both marsupial and tammar-specific repeat classes. Lastly, this study includes the first in-depth analyses of the newly

A Simple and Efficient RNA Extraction Method from Deep-Sea Hydrothermal Vent Chimney Structures.

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Muto, Hisashi; Takaki, Yoshihiro; Hirai, Miho; Mino, Sayaka; Sawayama, Shigeki; Takai, Ken; Nakagawa, Satoshi

2017-12-27

RNA-based microbiological analyses, e.g., transcriptome and reverse transcription-quantitative PCR, require a relatively large amount of high quality RNA. RNA-based analyses on microbial communities in deep-sea hydrothermal environments often encounter methodological difficulties with RNA extraction due to the presence of unique minerals in and the low biomass of samples. In the present study, we assessed RNA extraction methods for deep-sea vent chimneys that had complex mineral compositions. Mineral-RNA adsorption experiments were conducted using mock chimney minerals and Escherichia coli total RNA solution, and showed that detectable RNA significantly decreased possibly due to adsorption onto minerals. This decrease in RNA was prevented by the addition of sodium tripolyphosphate (STPP), deoxynucleotide triphosphates (dNTPs), salmon sperm DNA, and NaOH. The addition of STPP was also effective for RNA extraction from the mixture of E. coli cells and mock chimney minerals when TRIzol reagent and the RNeasy column were used, but not when the RNeasy PowerSoil total RNA kit was used. A combination of STPP, TRIzol reagent, the RNeasy column, and sonication resulted in the highest RNA yield from a natural chimney. This indirect extraction procedure is simple, rapid, inexpensive, and may be used for large-scale RNA extraction.

Multi-resistance strategy for viral diseases and short hairpin RNA verification method in pigs

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Jong-nam Oh

2018-04-01

Full Text Available Objective Foot and mouth disease (FMD and porcine reproductive and respiratory syndrome (PRRS are major diseases that interrupt porcine production. Because they are viral diseases, vaccinations are of only limited effectiveness in preventing outbreaks. To establish an alternative multi-resistant strategy against FMD virus (FMDV and PRRS virus (PRRSV, the present study introduced two genetic modification techniques to porcine cells. Methods First, cluster of differentiation 163 (CD163, the PRRSV viral receptor, was edited with the clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 technique. The CD163 gene sequences of edited cells and control cells differed. Second, short hairpin RNA (shRNAs were integrated into the cells. The shRNAs, targeting the 3D gene of FMDV and the open reading frame 7 (ORF7 gene of PRRSV, were transferred into fibroblasts. We also developed an in vitro shRNA verification method with a target gene expression vector. Results shRNA activity was confirmed in vitro with vectors that expressed the 3D and ORF7 genes in the cells. Cells containing shRNAs showed lower transcript levels than cells with only the expression vectors. The shRNAs were integrated into CD163-edited cells to combine the two techniques, and the viral genes were suppressed in these cells. Conclusion We established a multi-resistant strategy against viral diseases and an in vitro shRNA verification method.

Transcriptome sequences resolve deep relationships of the grape family.

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Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M; Gerrath, Jean; Zimmer, Elizabeth A; Fang, Xiao-Dong

2013-01-01

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

Complete Genome Sequence of a Double-Stranded RNA Virus from Avocado

OpenAIRE

Villanueva, Francisco; Sabanadzovic, Sead; Valverde, Rodrigo A.; Navas-Castillo, Jesús

2012-01-01

A number of avocado (Persea americana) cultivars are known to contain high-molecular-weight double-stranded RNA (dsRNA) molecules for which a viral nature has been suggested, although sequence data are not available. Here we report the cloning and complete sequencing of a 13.5-kbp dsRNA virus isolated from avocado and show that it corresponds to the genome of a new species of the genus Endornavirus (family Endornaviridae), tentatively named Persea americana endornavirus (PaEV).

Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

Science.gov (United States)

Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

2016-10-01

The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

Short hairpin RNA-mediated knockdown of protein expression in Entamoeba histolytica

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Singh Upinder

2009-02-01

Full Text Available Abstract Background Entamoeba histolytica is an intestinal protozoan parasite of humans. The genome has been sequenced, but the study of individual gene products has been hampered by the lack of the ability to generate gene knockouts. We chose to test the use of RNA interference to knock down gene expression in Entamoeba histolytica. Results An episomal vector-based system, using the E. histolytica U6 promoter to drive expression of 29-basepair short hairpin RNAs, was developed to target protein-encoding genes in E. histolytica. The short hairpin RNAs successfully knocked down protein levels of all three unrelated genes tested with this system: Igl, the intermediate subunit of the galactose- and N-acetyl-D-galactosamine-inhibitable lectin; the transcription factor URE3-BP; and the membrane binding protein EhC2A. Igl levels were reduced by 72%, URE3-BP by 89%, and EhC2A by 97%. Conclusion Use of the U6 promoter to drive expression of 29-basepair short hairpin RNAs is effective at knocking down protein expression for unrelated genes in Entamoeba histolytica, providing a useful tool for the study of this parasite.

Short hairpin RNA-mediated knockdown of protein expression in Entamoeba histolytica.

Science.gov (United States)

Linford, Alicia S; Moreno, Heriberto; Good, Katelyn R; Zhang, Hanbang; Singh, Upinder; Petri, William A

2009-02-17

Entamoeba histolytica is an intestinal protozoan parasite of humans. The genome has been sequenced, but the study of individual gene products has been hampered by the lack of the ability to generate gene knockouts. We chose to test the use of RNA interference to knock down gene expression in Entamoeba histolytica. An episomal vector-based system, using the E. histolytica U6 promoter to drive expression of 29-basepair short hairpin RNAs, was developed to target protein-encoding genes in E. histolytica. The short hairpin RNAs successfully knocked down protein levels of all three unrelated genes tested with this system: Igl, the intermediate subunit of the galactose- and N-acetyl-D-galactosamine-inhibitable lectin; the transcription factor URE3-BP; and the membrane binding protein EhC2A. Igl levels were reduced by 72%, URE3-BP by 89%, and EhC2A by 97%. Use of the U6 promoter to drive expression of 29-basepair short hairpin RNAs is effective at knocking down protein expression for unrelated genes in Entamoeba histolytica, providing a useful tool for the study of this parasite.

Nucleotide sequence and genetic organization of Hungarian grapevine chrome mosaic nepovirus RNA2.

Science.gov (United States)

Brault, V; Hibrand, L; Candresse, T; Le Gall, O; Dunez, J

1989-10-11

The complete nucleotide sequence of hungarian grapevine chrome mosaic nepovirus (GCMV) RNA2 has been determined. The RNA sequence is 4441 nucleotides in length, excluding the poly(A) tail. A polyprotein of 1324 amino acids with a calculated molecular weight of 146 kDa is encoded in a single long open reading frame extending from nucleotides 218 to 4190. This polyprotein is homologous with the protein encoded by the S strain of tomato black ring virus (TBRV) RNA2, the only other nepovirus sequenced so far. Direct sequencing of the viral coat protein and in vitro translation of transcripts derived from cDNA sequences demonstrate that, as for comoviruses, the coat protein is located at the carboxy terminus of the polyprotein. A model for the expression of GCMV RNA2 is presented.

TurboFold: Iterative probabilistic estimation of secondary structures for multiple RNA sequences

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Sharma Gaurav

2011-04-01

Full Text Available Abstract Background The prediction of secondary structure, i.e. the set of canonical base pairs between nucleotides, is a first step in developing an understanding of the function of an RNA sequence. The most accurate computational methods predict conserved structures for a set of homologous RNA sequences. These methods usually suffer from high computational complexity. In this paper, TurboFold, a novel and efficient method for secondary structure prediction for multiple RNA sequences, is presented. Results TurboFold takes, as input, a set of homologous RNA sequences and outputs estimates of the base pairing probabilities for each sequence. The base pairing probabilities for a sequence are estimated by combining intrinsic information, derived from the sequence itself via the nearest neighbor thermodynamic model, with extrinsic information, derived from the other sequences in the input set. For a given sequence, the extrinsic information is computed by using pairwise-sequence-alignment-based probabilities for co-incidence with each of the other sequences, along with estimated base pairing probabilities, from the previous iteration, for the other sequences. The extrinsic information is introduced as free energy modifications for base pairing in a partition function computation based on the nearest neighbor thermodynamic model. This process yields updated estimates of base pairing probability. The updated base pairing probabilities in turn are used to recompute extrinsic information, resulting in the overall iterative estimation procedure that defines TurboFold. TurboFold is benchmarked on a number of ncRNA datasets and compared against alternative secondary structure prediction methods. The iterative procedure in TurboFold is shown to improve estimates of base pairing probability with each iteration, though only small gains are obtained beyond three iterations. Secondary structures composed of base pairs with estimated probabilities higher than a

Complete Genome Sequence of a Double-Stranded RNA Virus from Avocado

Science.gov (United States)

Villanueva, Francisco; Sabanadzovic, Sead; Valverde, Rodrigo A.

2012-01-01

A number of avocado (Persea americana) cultivars are known to contain high-molecular-weight double-stranded RNA (dsRNA) molecules for which a viral nature has been suggested, although sequence data are not available. Here we report the cloning and complete sequencing of a 13.5-kbp dsRNA virus isolated from avocado and show that it corresponds to the genome of a new species of the genus Endornavirus (family Endornaviridae), tentatively named Persea americana endornavirus (PaEV). PMID:22205720

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

Science.gov (United States)

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.

Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

DEFF Research Database (Denmark)

Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

2009-01-01

Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....

Genome-wide characterization of microRNA in foxtail millet (Setaria italica).

Science.gov (United States)

Yi, Fei; Xie, Shaojun; Liu, Yuwei; Qi, Xin; Yu, Jingjuan

2013-12-13

MicroRNAs (miRNAs) are a class of short non-coding, endogenous RNAs that play key roles in many biological processes in both animals and plants. Although many miRNAs have been identified in a large number of organisms, the miRNAs in foxtail millet (Setaria italica) have, until now, been poorly understood. In this study, two replicate small RNA libraries from foxtail millet shoots were sequenced, and 40 million reads representing over 10 million unique sequences were generated. We identified 43 known miRNAs, 172 novel miRNAs and 2 mirtron precursor candidates in foxtail millet. Some miRNA*s of the known and novel miRNAs were detected as well. Further, eight novel miRNAs were validated by stem-loop RT-PCR. Potential targets of the foxtail millet miRNAs were predicted based on our strict criteria. Of the predicted target genes, 79% (351) had functional annotations in InterPro and GO analyses, indicating the targets of the miRNAs were involved in a wide range of regulatory functions and some specific biological processes. A total of 69 pairs of syntenic miRNA precursors that were conserved between foxtail millet and sorghum were found. Additionally, stem-loop RT-PCR was conducted to confirm the tissue-specific expression of some miRNAs in the four tissues identified by deep-sequencing. We predicted, for the first time, 215 miRNAs and 447 miRNA targets in foxtail millet at a genome-wide level. The precursors, expression levels, miRNA* sequences, target functions, conservation, and evolution of miRNAs we identified were investigated. Some of the novel foxtail millet miRNAs and miRNA targets were validated experimentally.

Small RNA sequence analysis of adenovirus VA RNA-derived miRNAs reveals an unexpected serotype-specific difference in structure and abundance.

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Wael Kamel

Full Text Available Human adenoviruses (HAds encode for one or two highly abundant virus-associated RNAs, designated VA RNAI and VA RNAII, which fold into stable hairpin structures resembling miRNA precursors. Here we show that the terminal stem of the VA RNAs originating from Ad4, Ad5, Ad11 and Ad37, all undergo Dicer dependent processing into virus-specific miRNAs (so-called mivaRNAs. We further show that the mivaRNA duplex is subjected to a highly asymmetric RISC loading with the 3'-strand from all VA RNAs being the favored strand, except for the Ad37 VA RNAII, where the 5'-mivaRNAII strand was preferentially assembled into RISC. Although the mivaRNA seed sequences are not fully conserved between the HAds a bioinformatics prediction approach suggests that a large fraction of the VA RNAII-, but not the VA RNAI-derived mivaRNAs still are able to target the same cellular genes. Using small RNA deep sequencing we demonstrate that the Dicer processing event in the terminal stem of the VA RNAs is not unique and generates 3'-mivaRNAs with a slight variation of the position of the 5' terminal nucleotide in the RISC loaded guide strand. Also, we show that all analyzed VA RNAs, except Ad37 VA RNAI and Ad5 VA RNAII, utilize an alternative upstream A start site in addition to the classical +1 G start site. Further, the 5'-mivaRNAs with an A start appears to be preferentially incorporated into RISC. Although the majority of mivaRNA research has been done using Ad5 as the model system our analysis demonstrates that the mivaRNAs expressed in Ad11- and Ad37-infected cells are the most abundant mivaRNAs associated with Ago2-containing RISC. Collectively, our results show an unexpected variability in Dicer processing of the VA RNAs and a serotype-specific loading of mivaRNAs into Ago2-based RISC.

Identification of Bacterial Small RNAs by RNA Sequencing

DEFF Research Database (Denmark)

Gómez Lozano, María; Marvig, Rasmus Lykke; Molin, Søren

2014-01-01

sequencing (RNA-seq) is described that involves the preparation and analysis of three different sequencing libraries. As a signifi cant number of unique sRNAs are identifi ed in each library, the libraries can be used either alone or in combination to increase the number of sRNAs identifi ed. The approach......Small regulatory RNAs (sRNAs) in bacteria are known to modulate gene expression and control a variety of processes including metabolic reactions, stress responses, and pathogenesis in response to environmental signals. A method to identify bacterial sRNAs on a genome-wide scale based on RNA...... may be applied to identify sRNAs in any bacterium under different growth and stress conditions....

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

Science.gov (United States)

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.

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

Science.gov (United States)

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

SAAS: Short Amino Acid Sequence - A Promising Protein Secondary Structure Prediction Method of Single Sequence

Directory of Open Access Journals (Sweden)

Zhou Yuan Wu

2013-07-01

Full Text Available In statistical methods of predicting protein secondary structure, many researchers focus on single amino acid frequencies in α-helices, β-sheets, and so on, or the impact near amino acids on an amino acid forming a secondary structure. But the paper considers a short sequence of amino acids (3, 4, 5 or 6 amino acids as integer, and statistics short sequence's probability forming secondary structure. Also, many researchers select low homologous sequences as statistical database. But this paper select whole PDB database. In this paper we propose a strategy to predict protein secondary structure using simple statistical method. Numerical computation shows that, short amino acids sequence as integer to statistics, which can easy see trend of short sequence forming secondary structure, and it will work well to select large statistical database (whole PDB database without considering homologous, and Q3 accuracy is ca. 74% using this paper proposed simple statistical method, but accuracy of others statistical methods is less than 70%.

Gene expression profiling of non-polyadenylated RNA-seq across species

Directory of Open Access Journals (Sweden)

Xiao-Ou Zhang

2014-12-01

Full Text Available Transcriptomes are dynamic and unique, with each cell type/tissue, developmental stage and species expressing a different repertoire of RNA transcripts. Most mRNAs and well-characterized long noncoding RNAs are shaped with a 5′ cap and 3′ poly(A tail, thus conventional transcriptome analyses typically start with the enrichment of poly(A+ RNAs by oligo(dT selection, followed by deep sequencing approaches. However, accumulated lines of evidence suggest that many RNA transcripts are processed by alternative mechanisms without 3′ poly(A tails and, therefore, fail to be enriched by oligo(dT purification and are absent following deep sequencing analyses. We have described an enrichment strategy to purify non-polyadenylated (poly(A−/ribo− RNAs from human total RNAs by removal of both poly(A+ RNA transcripts and ribosomal RNAs, which led to the identification of many novel RNA transcripts with non-canonical 3′ ends in human. Here, we describe the application of non-polyadenylated RNA-sequencing in rhesus monkey and mouse cell lines/tissue, and further profile the transcription of non-polyadenylated RNAs across species, providing new resources for non-polyadenylated RNA identification and comparison across species.

Transcriptome sequences resolve deep relationships of the grape family.

Directory of Open Access Journals (Sweden)

Jun Wen

Full Text Available Previous phylogenetic studies of the grape family (Vitaceae yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

The chemical structure of DNA sequence signals for RNA transcription

Science.gov (United States)

George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

An introduction to Deep learning on biological sequence data - Examples and solutions

DEFF Research Database (Denmark)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten

2017-01-01

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use....... Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively...

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

Science.gov (United States)

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.

Oasis 2: improved online analysis of small RNA-seq data.

Science.gov (United States)

Rahman, Raza-Ur; Gautam, Abhivyakti; Bethune, Jörn; Sattar, Abdul; Fiosins, Maksims; Magruder, Daniel Sumner; Capece, Vincenzo; Shomroni, Orr; Bonn, Stefan

2018-02-14

Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing. Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment. Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks

OpenAIRE

Yin, Zi; Chang, Keng-hao; Zhang, Ruofei

2017-01-01

Information extraction and user intention identification are central topics in modern query understanding and recommendation systems. In this paper, we propose DeepProbe, a generic information-directed interaction framework which is built around an attention-based sequence to sequence (seq2seq) recurrent neural network. DeepProbe can rephrase, evaluate, and even actively ask questions, leveraging the generative ability and likelihood estimation made possible by seq2seq models. DeepProbe makes...

Sequence characterization of 5S ribosomal RNA from eight gram positive procaryotes

Science.gov (United States)

Woese, C. R.; Luehrsen, K. R.; Pribula, C. D.; Fox, G. E.

1976-01-01

Complete nucleotide sequences are presented for 5S rRNA from Bacillus subtilis, B. firmus, B. pasteurii, B. brevis, Lactobacillus brevis, and Streptococcus faecalis, and 5S rRNA oligonucleotide catalogs and partial sequence data are given for B. cereus and Sporosarcina ureae. These data demonstrate a striking consistency of 5S rRNA primary and secondary structure within a given bacterial grouping. An exception is B. brevis, in which the 5S rRNA sequence varies significantly from that of other bacilli in the tuned helix and the procaryotic loop. The localization of these variations suggests that B. brevis occupies an ecological niche that selects such changes. It is noted that this organism produces antibiotics which affect ribosome function.

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

Science.gov (United States)

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.

Deep Sequencing Reveals the Complete Genome and Evidence for Transcriptional Activity of the First Virus-Like Sequences Identified in Aristotelia chilensis (Maqui Berry

Directory of Open Access Journals (Sweden)

Javier Villacreses

2015-04-01

Full Text Available Here, we report the genome sequence and evidence for transcriptional activity of a virus-like element in the native Chilean berry tree Aristotelia chilensis. We propose to name the endogenous sequence as Aristotelia chilensis Virus 1 (AcV1. High-throughput sequencing of the genome of this tree uncovered an endogenous viral element, with a size of 7122 bp, corresponding to the complete genome of AcV1. Its sequence contains three open reading frames (ORFs: ORFs 1 and 2 shares 66%–73% amino acid similarity with members of the Caulimoviridae virus family, especially the Petunia vein clearing virus (PVCV, Petuvirus genus. ORF1 encodes a movement protein (MP; ORF2 a Reverse Transcriptase (RT and a Ribonuclease H (RNase H domain; and ORF3 showed no amino acid sequence similarity with any other known virus proteins. Analogous to other known endogenous pararetrovirus sequences (EPRVs, AcV1 is integrated in the genome of Maqui Berry and showed low viral transcriptional activity, which was detected by deep sequencing technology (DNA and RNA-seq. Phylogenetic analysis of AcV1 and other pararetroviruses revealed a closer resemblance with Petuvirus. Overall, our data suggests that AcV1 could be a new member of Caulimoviridae family, genus Petuvirus, and the first evidence of this kind of virus in a fruit plant.

High-throughput sequencing and analysis of the gill tissue transcriptome from the deep-sea hydrothermal vent mussel Bathymodiolus azoricus

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Gomes Paula

2010-10-01

Full Text Available Abstract Background Bathymodiolus azoricus is a deep-sea hydrothermal vent mussel found in association with large faunal communities living in chemosynthetic environments at the bottom of the sea floor near the Azores Islands. Investigation of the exceptional physiological reactions that vent mussels have adopted in their habitat, including responses to environmental microbes, remains a difficult challenge for deep-sea biologists. In an attempt to reveal genes potentially involved in the deep-sea mussel innate immunity we carried out a high-throughput sequence analysis of freshly collected B. azoricus transcriptome using gills tissues as the primary source of immune transcripts given its strategic role in filtering the surrounding waterborne potentially infectious microorganisms. Additionally, a substantial EST data set was produced and from which a comprehensive collection of genes coding for putative proteins was organized in a dedicated database, "DeepSeaVent" the first deep-sea vent animal transcriptome database based on the 454 pyrosequencing technology. Results A normalized cDNA library from gills tissue was sequenced in a full 454 GS-FLX run, producing 778,996 sequencing reads. Assembly of the high quality reads resulted in 75,407 contigs of which 3,071 were singletons. A total of 39,425 transcripts were conceptually translated into amino-sequences of which 22,023 matched known proteins in the NCBI non-redundant protein database, 15,839 revealed conserved protein domains through InterPro functional classification and 9,584 were assigned with Gene Ontology terms. Queries conducted within the database enabled the identification of genes putatively involved in immune and inflammatory reactions which had not been previously evidenced in the vent mussel. Their physical counterpart was confirmed by semi-quantitative quantitative Reverse-Transcription-Polymerase Chain Reactions (RT-PCR and their RNA transcription level by quantitative PCR (q

Small molecule alteration of RNA sequence in cells and animals.

Science.gov (United States)

Guan, Lirui; Luo, Yiling; Ja, William W; Disney, Matthew D

2017-10-18

RNA regulation and maintenance are critical for proper cell function. Small molecules that specifically alter RNA sequence would be exceptionally useful as probes of RNA structure and function or as potential therapeutics. Here, we demonstrate a photochemical approach for altering the trinucleotide expanded repeat causative of myotonic muscular dystrophy type 1 (DM1), r(CUG) exp . The small molecule, 2H-4-Ru, binds to r(CUG) exp and converts guanosine residues to 8-oxo-7,8-dihydroguanosine upon photochemical irradiation. We demonstrate targeted modification upon irradiation in cell culture and in Drosophila larvae provided a diet containing 2H-4-Ru. Our results highlight a general chemical biology approach for altering RNA sequence in vivo by using small molecules and photochemistry. Furthermore, these studies show that addition of 8-oxo-G lesions into RNA 3' untranslated regions does not affect its steady state levels. Copyright © 2017 Elsevier Ltd. All rights reserved.

Common 5S rRNA variants are likely to be accepted in many sequence contexts

Science.gov (United States)

Zhang, Zhengdong; D'Souza, Lisa M.; Lee, Youn-Hyung; Fox, George E.

2003-01-01

Over evolutionary time RNA sequences which are successfully fixed in a population are selected from among those that satisfy the structural and chemical requirements imposed by the function of the RNA. These sequences together comprise the structure space of the RNA. In principle, a comprehensive understanding of RNA structure and function would make it possible to enumerate which specific RNA sequences belong to a particular structure space and which do not. We are using bacterial 5S rRNA as a model system to attempt to identify principles that can be used to predict which sequences do or do not belong to the 5S rRNA structure space. One promising idea is the very intuitive notion that frequently seen sequence changes in an aligned data set of naturally occurring 5S rRNAs would be widely accepted in many other 5S rRNA sequence contexts. To test this hypothesis, we first developed well-defined operational definitions for a Vibrio region of the 5S rRNA structure space and what is meant by a highly variable position. Fourteen sequence variants (10 point changes and 4 base-pair changes) were identified in this way, which, by the hypothesis, would be expected to incorporate successfully in any of the known sequences in the Vibrio region. All 14 of these changes were constructed and separately introduced into the Vibrio proteolyticus 5S rRNA sequence where they are not normally found. Each variant was evaluated for its ability to function as a valid 5S rRNA in an E. coli cellular context. It was found that 93% (13/14) of the variants tested are likely valid 5S rRNAs in this context. In addition, seven variants were constructed that, although present in the Vibrio region, did not meet the stringent criteria for a highly variable position. In this case, 86% (6/7) are likely valid. As a control we also examined seven variants that are seldom or never seen in the Vibrio region of 5S rRNA sequence space. In this case only two of seven were found to be potentially valid. The

Unprecedented high-resolution view of bacterial operon architecture revealed by RNA sequencing.

Science.gov (United States)

Conway, Tyrrell; Creecy, James P; Maddox, Scott M; Grissom, Joe E; Conkle, Trevor L; Shadid, Tyler M; Teramoto, Jun; San Miguel, Phillip; Shimada, Tomohiro; Ishihama, Akira; Mori, Hirotada; Wanner, Barry L

2014-07-08

We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3' transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5' ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread. Importance: We precisely mapped the 5' and 3' ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are

Identification and Removal of Contaminant Sequences From Ribosomal Gene Databases: Lessons From the Census of Deep Life.

Science.gov (United States)

Sheik, Cody S; Reese, Brandi Kiel; Twing, Katrina I; Sylvan, Jason B; Grim, Sharon L; Schrenk, Matthew O; Sogin, Mitchell L; Colwell, Frederick S

2018-01-01

Earth's subsurface environment is one of the largest, yet least studied, biomes on Earth, and many questions remain regarding what microorganisms are indigenous to the subsurface. Through the activity of the Census of Deep Life (CoDL) and the Deep Carbon Observatory, an open access 16S ribosomal RNA gene sequence database from diverse subsurface environments has been compiled. However, due to low quantities of biomass in the deep subsurface, the potential for incorporation of contaminants from reagents used during sample collection, processing, and/or sequencing is high. Thus, to understand the ecology of subsurface microorganisms (i.e., the distribution, richness, or survival), it is necessary to minimize, identify, and remove contaminant sequences that will skew the relative abundances of all taxa in the sample. In this meta-analysis, we identify putative contaminants associated with the CoDL dataset, recommend best practices for removing contaminants from samples, and propose a series of best practices for subsurface microbiology sampling. The most abundant putative contaminant genera observed, independent of evenness across samples, were Propionibacterium , Aquabacterium , Ralstonia , and Acinetobacter . While the top five most frequently observed genera were Pseudomonas , Propionibacterium , Acinetobacter , Ralstonia , and Sphingomonas . The majority of the most frequently observed genera (high evenness) were associated with reagent or potential human contamination. Additionally, in DNA extraction blanks, we observed potential archaeal contaminants, including methanogens, which have not been discussed in previous contamination studies. Such contaminants would directly affect the interpretation of subsurface molecular studies, as methanogenesis is an important subsurface biogeochemical process. Utilizing previously identified contaminant genera, we found that ∼27% of the total dataset were identified as contaminant sequences that likely originate from DNA

Carbon transformations in deep granitic groundwater by attached bacterial populations characterized with 16S-rRNA gene sequencing technique and scanning electron microscopy

International Nuclear Information System (INIS)

Ekendahl, S.; Arlinger, J.; Staahl, F.; Pedersen, K.

1993-10-01

This report presents molecular characterization of attached bacterial populations growing in slowly flowing (1-3 mm s -1 ) artesian groundwater from deep crystalline bed-rock of the Stripa research mine, south central Sweden. The assimilation rate of CO 2 and lactate, and the lactate respiration rates were also determined. The bacteria studied grew in anoxic, high pH, 9-10, and low redox artesian groundwater flowing up through tubings from two levels of a borehole designated V2, 812-820 m and 970-1240 m below ground. The major groups of bacteria were found. Signature bases placed them in the appropriate systematic groups. All belonged to the Proteobacterial groups beta and gamma. One group was found only at the 812-820 m level, where it constituted 63% of the sequenced clones, whereas the second group existed almost exclusively and constituted 85% of the sequenced clones at the 970-1240 m level. The third group was equally distributed between the levels. A few other bacteria were also found. None of the 16S-rRNA genes from the dominating bacteria resembled any of the other by more than 90% similarity, and none of them resembled anything in the database by more than 96%. Temperature did not seem to have any effect on species composition at the deeper level. SEM images showed rods appearing in microcolonies. The difference in population diversity between the two levels studied presumably reflect the different environments. The earlier proposed presence of sulphate reducing bacteria could no be confirmed

deepTools2: a next generation web server for deep-sequencing data analysis.

Science.gov (United States)

Ramírez, Fidel; Ryan, Devon P; Grüning, Björn; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S; Heyne, Steffen; Dündar, Friederike; Manke, Thomas

2016-07-08

We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Finding the most significant common sequence and structure motifs in a set of RNA sequences

DEFF Research Database (Denmark)

Gorodkin, Jan; Heyer, L.J.; Stormo, G.D.

1997-01-01

We present a computational scheme to locally align a collection of RNA sequences using sequence and structure constraints, In addition, the method searches for the resulting alignments with the most significant common motifs, among all possible collections, The first part utilizes a simplified...

Evaluating Methods for Isolating Total RNA and Predicting the Success of Sequencing Phylogenetically Diverse Plant Transcriptomes

Science.gov (United States)

Bruskiewich, Richard; Burris, Jason N.; Carrigan, Charlotte T.; Chase, Mark W.; Clarke, Neil D.; Covshoff, Sarah; dePamphilis, Claude W.; Edger, Patrick P.; Goh, Falicia; Graham, Sean; Greiner, Stephan; Hibberd, Julian M.; Jordon-Thaden, Ingrid; Kutchan, Toni M.; Leebens-Mack, James; Melkonian, Michael; Miles, Nicholas; Myburg, Henrietta; Patterson, Jordan; Pires, J. Chris; Ralph, Paula; Rolf, Megan; Sage, Rowan F.; Soltis, Douglas; Soltis, Pamela; Stevenson, Dennis; Stewart, C. Neal; Surek, Barbara; Thomsen, Christina J. M.; Villarreal, Juan Carlos; Wu, Xiaolei; Zhang, Yong; Deyholos, Michael K.; Wong, Gane Ka-Shu

2012-01-01

Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers. PMID:23185583

Nucleotide sequence of tomato ringspot virus RNA-2.

Science.gov (United States)

Rott, M E; Tremaine, J H; Rochon, D M

1991-07-01

The sequence of tomato ringspot virus (TomRSV) RNA-2 has been determined. It is 7273 nucleotides in length excluding the 3' poly(A) tail and contains a single long open reading frame (ORF) of 5646 nucleotides in the positive sense beginning at position 78 and terminating at position 5723. A second in-frame AUG at position 441 is in a more favourable context for initiation of translation and may act as a site for initiation of translation. The TomRSV RNA-2 3' noncoding region is 1550 nucleotides in length. The coat protein is located in the C-terminal region of the large polypeptide and shows significant but limited amino acid sequence similarity to the putative coat proteins of the nepoviruses tomato black ring (TBRV), Hungarian grapevine chrome mosaic (GCMV) and grapevine fanleaf (GFLV). Comparisons of the coding and non-coding regions of TomRSV RNA-2 and the RNA components of TBRV, GCMV, GFLV and the comovirus cowpea mosaic virus revealed significant similarity for over 300 amino acids between the coding region immediately to the N-terminal side of the putative coat proteins of TomRSV and GFLV; very little similarity could be detected among the non-coding regions of TomRSV and any of these viruses.

Unusual loop-sequence flexibility of the proximal RNA replication element in EMCV.

Directory of Open Access Journals (Sweden)

Jan Zoll

Full Text Available Picornaviruses contain stable RNA structures at the 5' and 3' ends of the RNA genome, OriL and OriR involved in viral RNA replication. The OriL RNA element found at the 5' end of the enterovirus genome folds into a cloverleaf-like configuration. In vivo SELEX experiments revealed that functioning of the poliovirus cloverleaf depends on a specific structure in this RNA element. Little is known about the OriL of cardioviruses. Here, we investigated structural aspects and requirements of the apical loop of proximal stem-loop SL-A of mengovirus, a strain of EMCV. Using NMR spectroscopy, we showed that the mengovirus SL-A apical loop consists of an octaloop. In vivo SELEX experiments demonstrated that a large number of random sequences are tolerated in the apical octaloop that support virus replication. Mutants in which the SL-A loop size and the length of the upper part of the stem were varied showed that both stem-length and stability of the octaloop are important determinants for viral RNA replication and virus reproduction. Together, these data show that stem-loop A plays an important role in virus replication. The high degree of sequence flexibility and the lack of selective pressure on the octaloop argue against a role in sequence specific RNA-protein or RNA-RNA interactions in which octaloop nucleotides are involved.

Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer

Science.gov (United States)

2017-09-01

AWARD NUMBER: W81XWH-14-1-0080 TITLE: Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer . PRINCIPAL INVESTIGATOR...TITLE AND SUBTITLE Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer . 5a. CONTRACT NUMBER 5b. GRANT NUMBER GRANT11489...institutional, NIH-funded study of genetic and epigenetic alterations of pre-invasive DCIS that did or did not progress to invasive breast cancer , with an

Complete sequence of RNA1 of grapevine Anatolian ringspot virus.

Science.gov (United States)

Digiaro, Michele; Nahdi, Sabrine; Elbeaino, Toufic

2012-10-01

The nucleotide sequence of RNA1 of grapevine Anatolian ringspot virus (GARSV), a nepovirus of subgroup B, was determined from cDNA clones. It is 7,288 nucleotides in length excluding the 3' terminal poly(A) tail and contains a large open reading frame (ORF), extending from nucleotides 272 to 7001, encoding a polypeptide of 2,243 amino acids with a predicted molecular mass of 250 kDa. The primary structure of the polyprotein, compared with that of other viral polyproteins, revealed the presence of all the characteristic domains of members of the order Picornavirales, i.e., the NTP-binding protein (1B(Hel)), the viral genome-linked protein (1C(VPg)), the proteinase (1D(Prot)), the RNA-dependent RNA polymerase (1E(Pol)), and of the protease cofactor (1A(Pro-cof)) shared by members of the subfamily Comovirinae within the family Secoviridae. The cleavage sites predicted within the polyprotein were found to be in agreement with those previously reported for nepoviruses of subgroup B, processing from 1A to 1E proteins of 67, 64, 3, 23 and 92 kDa, respectively. The RNA1-encoded polyprotein (p1) shared the highest amino acid sequence identity (66 %) with tomato black ring virus (TBRV) and beet ringspot virus (BRSV). The 5'- and 3'-noncoding regions (NCRs) of GARSV-RNA1 shared 89 % and 95 % nucleotide sequence identity respectively with the corresponding regions in RNA2. Phylogenetic analysis confirmed the close relationship of GARSV to members of subgroup B of the genus Nepovirus.

Small RNA pathways and diversity in model legumes: lessons from genomics.

Directory of Open Access Journals (Sweden)

Pilar eBustos-Sanmamed

2013-07-01

Full Text Available Small non coding RNAs (smRNA participate in the regulation of development, cell differentiation, adaptation to environmental constraints and defense responses in plants. They negatively regulate gene expression by degrading specific mRNA targets, repressing their translation or modifying chromatin conformation through homologous interaction with target loci. MicroRNAs (miRNA and short-interfering RNAs (siRNA are generated from long double stranded RNA (dsRNA that are cleaved into 20- to 24-nucleotide dsRNAs by RNase III proteins called DICERs (DCL. One strand of the duplex is then loaded onto effective complexes containing different ARGONAUTE (AGO proteins. In this review, we explored smRNA diversity in model legumes and compiled available data from miRBAse, the miRNA database, and from 22 reports of smRNA deep sequencing or miRNA identification genome-wide in Medicago truncatula, Glycine max and Lotus japonicus. In addition to conserved miRNAs present in other plant species, 229, 179 and 35 novel miRNA families were identified respectively in these 3 legumes, among which several seems legume-specific. New potential functions of several miRNAs in the legume-specific nodulation process are discussed. Furthermore, a new category of siRNA, the phased siRNAs, which seems to mainly regulate disease-resistance genes, was recently discovered in legumes. Despite that the genome sequence of model legumes are not yet fully completed, further analysis was performed by database mining of gene families and protein characteristics of DCLs and AGOs in these genomes. Although most components of the smRNA pathways are conserved, identifiable homologs of key smRNA players from non-legumes could not yet be detected in M. truncatula available genomic and expressed sequence databases. In addition, an important gene diversification was observed in the three legumes. Functional significance of these variant isoforms may reflect peculiarities of smRNA biogenesis in

High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

Science.gov (United States)

Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

2016-09-07

Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

The genome of flax (Linum usitatissimum) assembled de novo from short shotgun sequence reads.

Science.gov (United States)

Wang, Zhiwen; Hobson, Neil; Galindo, Leonardo; Zhu, Shilin; Shi, Daihu; McDill, Joshua; Yang, Linfeng; Hawkins, Simon; Neutelings, Godfrey; Datla, Raju; Lambert, Georgina; Galbraith, David W; Grassa, Christopher J; Geraldes, Armando; Cronk, Quentin C; Cullis, Christopher; Dash, Prasanta K; Kumar, Polumetla A; Cloutier, Sylvie; Sharpe, Andrew G; Wong, Gane K-S; Wang, Jun; Deyholos, Michael K

2012-11-01

Flax (Linum usitatissimum) is an ancient crop that is widely cultivated as a source of fiber, oil and medicinally relevant compounds. To accelerate crop improvement, we performed whole-genome shotgun sequencing of the nuclear genome of flax. Seven paired-end libraries ranging in size from 300 bp to 10 kb were sequenced using an Illumina genome analyzer. A de novo assembly, comprised exclusively of deep-coverage (approximately 94× raw, approximately 69× filtered) short-sequence reads (44-100 bp), produced a set of scaffolds with N(50) =694 kb, including contigs with N(50)=20.1 kb. The contig assembly contained 302 Mb of non-redundant sequence representing an estimated 81% genome coverage. Up to 96% of published flax ESTs aligned to the whole-genome shotgun scaffolds. However, comparisons with independently sequenced BACs and fosmids showed some mis-assembly of regions at the genome scale. A total of 43384 protein-coding genes were predicted in the whole-genome shotgun assembly, and up to 93% of published flax ESTs, and 86% of A. thaliana genes aligned to these predicted genes, indicating excellent coverage and accuracy at the gene level. Analysis of the synonymous substitution rates (K(s) ) observed within duplicate gene pairs was consistent with a recent (5-9 MYA) whole-genome duplication in flax. Within the predicted proteome, we observed enrichment of many conserved domains (Pfam-A) that may contribute to the unique properties of this crop, including agglutinin proteins. Together these results show that de novo assembly, based solely on whole-genome shotgun short-sequence reads, is an efficient means of obtaining nearly complete genome sequence information for some plant species. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.

Genetic diversity of archaea in deep-sea hydrothermal vent environments.

OpenAIRE

Takai, K; Horikoshi, K

1999-01-01

Molecular phylogenetic analysis of naturally occurring archaeal communities in deep-sea hydrothermal vent environments was carried out by PCR-mediated small subunit rRNA gene (SSU rDNA) sequencing. As determined through partial sequencing of rDNA clones amplified with archaea-specific primers, the archaeal populations in deep-sea hydrothermal vent environments showed a great genetic diversity, and most members of these populations appeared to be uncultivated and unidentified organisms. In the...

Comparison of variable region 3 sequences of human immunodeficiency virus type 1 from infected children with the RNA and DNA sequences of the virus populations of their mothers.

Science.gov (United States)

Scarlatti, G; Leitner, T; Halapi, E; Wahlberg, J; Marchisio, P; Clerici-Schoeller, M A; Wigzell, H; Fenyö, E M; Albert, J; Uhlén, M

1993-01-01

We have compared the variable region 3 sequences from 10 human immunodeficiency virus type 1 (HIV-1)-infected infants to virus sequences from the corresponding mothers. The sequences were derived from DNA of uncultured peripheral blood mononuclear cells (PBMC), DNA of cultured PBMC, and RNA from serum collected at or shortly after delivery. The infected infants, in contrast to the mothers, harbored homogeneous virus populations. Comparison of sequences from the children and clones derived from DNA of the corresponding mothers showed that the transmitted virus represented either a minor or a major virus population of the mother. In contrast to an earlier study, we found no evidence of selection of minor virus variants during transmission. Furthermore, the transmitted virus variant did not show any characteristic molecular features. In some cases the transmitted virus was more related to the virus RNA population of the mother and in other cases it was more related to the virus DNA population. This suggests that either cell-free or cell-associated virus may be transmitted. These data will help AIDS researchers to understand the mechanism of transmission and to plan strategies for prevention of transmission. PMID:8446584

High-Throughput Sequencing Based Methods of RNA Structure Investigation

DEFF Research Database (Denmark)

Kielpinski, Lukasz Jan

In this thesis we describe the development of four related methods for RNA structure probing that utilize massive parallel sequencing. Using them, we were able to gather structural data for multiple, long molecules simultaneously. First, we have established an easy to follow experimental...... and computational protocol for detecting the reverse transcription termination sites (RTTS-Seq). This protocol was subsequently applied to hydroxyl radical footprinting of three dimensional RNA structures to give a probing signal that correlates well with the RNA backbone solvent accessibility. Moreover, we applied...

An optimized lentiviral vector system for conditional RNAi and efficient cloning of microRNA embedded short hairpin RNA libraries.

Science.gov (United States)

Adams, Felix F; Heckl, Dirk; Hoffmann, Thomas; Talbot, Steven R; Kloos, Arnold; Thol, Felicitas; Heuser, Michael; Zuber, Johannes; Schambach, Axel; Schwarzer, Adrian

2017-09-01

RNA interference (RNAi) and CRISPR-Cas9-based screening systems have emerged as powerful and complementary tools to unravel genetic dependencies through systematic gain- and loss-of-function studies. In recent years, a series of technical advances helped to enhance the performance of virally delivered RNAi. For instance, the incorporation of short hairpin RNAs (shRNAs) into endogenous microRNA contexts (shRNAmiRs) allows the use of Tet-regulated promoters for synchronous onset of gene knockdown and precise interrogation of gene dosage effects. However, remaining challenges include lack of efficient cloning strategies, inconsistent knockdown potencies and leaky expression. Here, we present a simple, one-step cloning approach for rapid and efficient cloning of miR-30 shRNAmiR libraries. We combined a human miR-30 backbone retaining native flanking sequences with an optimized all-in-one lentiviral vector system for conditional RNAi to generate a versatile toolbox characterized by higher doxycycline sensitivity, reduced leakiness and enhanced titer. Furthermore, refinement of existing shRNA design rules resulted in substantially improved prediction of powerful shRNAs. Our approach was validated by accurate quantification of the knockdown potency of over 250 single shRNAmiRs. To facilitate access and use by the scientific community, an online tool was developed for the automated design of refined shRNA-coding oligonucleotides ready for cloning into our system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

Science.gov (United States)

Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

2018-03-01

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Sequencing of 16S rRNA gene for id ntification of Sta h lococcus ...

African Journals Online (AJOL)

Asdmin

2014-01-15

Jan 15, 2014 ... as the type strains of a species of genus Trichoderma based on phylogenetic tree analysis together with the 18S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases. The sequence was deposited in GenBank with the accession numbers.

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

Science.gov (United States)

Argyropoulos, Christos; Etheridge, Alton; Sakhanenko, Nikita; Galas, David

2017-06-20

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. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

RNA2 of grapevine fanleaf virus: sequence analysis and coat protein cistron location.

Science.gov (United States)

Serghini, M A; Fuchs, M; Pinck, M; Reinbolt, J; Walter, B; Pinck, L

1990-07-01

The nucleotide sequence of the genomic RNA2 (3774 nucleotides) of grapevine fanleaf virus strain F13 was determined from overlapping cDNA clones and its genetic organization was deduced. Two rapid and efficient methods were used for cDNA cloning of the 5' region of RNA2. The complete sequence contained only one long open reading frame of 3555 nucleotides (1184 codons, 131K product). The analysis of the N-terminal sequence of purified coat protein (CP) and identification of its C-terminal residue have allowed the CP cistron to be precisely positioned within the polyprotein. The CP produced by proteolytic cleavage at the Arg/Gly site between residues 680 and 681 contains 504 amino acids (Mr 56019) and has hydrophobic properties. The Arg/Gly cleavage site deduced by N-terminal amino acid sequence analysis is the first for a nepovirus coat protein and for plant viruses expressing their genomic RNAs by polyprotein synthesis. Comparison of GFLV RNA2 with M RNA of cowpea mosaic comovirus and with RNA2 of two closely related nepoviruses, tomato black ring virus and Hungarian grapevine chrome mosaic virus, showed strong similarities among the 3' non-coding regions but less similarity among the 5' end non-coding sequences than reported among other nepovirus RNAs.

Comparison of Boolean analysis and standard phylogenetic methods using artificially evolved and natural mt-tRNA sequences from great apes.

Science.gov (United States)

Ari, Eszter; Ittzés, Péter; Podani, János; Thi, Quynh Chi Le; Jakó, Eena

2012-04-01

Boolean analysis (or BOOL-AN; Jakó et al., 2009. BOOL-AN: A method for comparative sequence analysis and phylogenetic reconstruction. Mol. Phylogenet. Evol. 52, 887-97.), a recently developed method for sequence comparison uses the Iterative Canonical Form of Boolean functions. It considers sequence information in a way entirely different from standard phylogenetic methods (i.e. Maximum Parsimony, Maximum-Likelihood, Neighbor-Joining, and Bayesian analysis). The performance and reliability of Boolean analysis were tested and compared with the standard phylogenetic methods, using artificially evolved - simulated - nucleotide sequences and the 22 mitochondrial tRNA genes of the great apes. At the outset, we assumed that the phylogeny of Hominidae is generally well established, and the guide tree of artificial sequence evolution can also be used as a benchmark. These offer a possibility to compare and test the performance of different phylogenetic methods. Trees were reconstructed by each method from 2500 simulated sequences and 22 mitochondrial tRNA sequences. We also introduced a special re-sampling method for Boolean analysis on permuted sequence sites, the P-BOOL-AN procedure. Considering the reliability values (branch support values of consensus trees and Robinson-Foulds distances) we used for simulated sequence trees produced by different phylogenetic methods, BOOL-AN appeared as the most reliable method. Although the mitochondrial tRNA sequences of great apes are relatively short (59-75 bases long) and the ratio of their constant characters is about 75%, BOOL-AN, P-BOOL-AN and the Bayesian approach produced the same tree-topology as the established phylogeny, while the outcomes of Maximum Parsimony, Maximum-Likelihood and Neighbor-Joining methods were equivocal. We conclude that Boolean analysis is a promising alternative to existing methods of sequence comparison for phylogenetic reconstruction and congruence analysis. Copyright © 2012 Elsevier Inc. All

Unravelling the complexity of microRNA-mediated gene regulation in black pepper (Piper nigrum L.) using high-throughput small RNA profiling.

Science.gov (United States)

Asha, Srinivasan; Sreekumar, Sweda; Soniya, E V

2016-01-01

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

Deep Sequence Analysis of AgoshRNA Processing Reveals 3' A Addition and Trimming

NARCIS (Netherlands)

Harwig, Alex; Herrera-Carrillo, Elena; Jongejan, Aldo; van Kampen, Antonius Hubertus; Berkhout, Ben

2015-01-01

The RNA interference (RNAi) pathway, in which microprocessor and Dicer collaborate to process microRNAs (miRNA), was recently expanded by the description of alternative processing routes. In one of these noncanonical pathways, Dicer action is replaced by the Argonaute2 (Ago2) slicer function. It was

The RNA world, automatic sequences and oncogenetics

Energy Technology Data Exchange (ETDEWEB)

Tahir Shah, K

1993-04-01

We construct a model of the RNA world in terms of naturally evolving nucleotide sequences assuming only Crick-Watson base pairing and self-cleaving/splicing capability. These sequences have the following properties. (1) They are recognizable by an automation (or automata). That is, to each k-sequence, there exist a k-automation which accepts, recognizes or generates the k-sequence. These are known as automatic sequences. Fibonacci and Morse-Thue sequences are the most natural outcome of pre-biotic chemical conditions. (2) Infinite (resp. large) sequences are self-similar (resp. nearly self-similar) under certain rewrite rules and consequently give rise to fractal (resp.fractal-like) structures. Computationally, such sequences can also be generated by their corresponding deterministic parallel re-write system, known as a DOL system. The self-similar sequences are fixed points of their respective rewrite rules. Some of these automatic sequences have the capability that they can read or ``accept`` other sequences while others can detect errors and trigger error-correcting mechanisms. They can be enlarged and have block and/or palindrome structure. Linear recurring sequences such as Fibonacci sequence are simply Feed-back Shift Registers, a well know model of information processing machines. We show that a mutation of any rewrite rule can cause a combinatorial explosion of error and relates this to oncogenetical behavior. On the other hand, a mutation of sequences that are not rewrite rules, leads to normal evolutionary change. Known experimental results support our hypothesis. (author). Refs.

The RNA world, automatic sequences and oncogenetics

International Nuclear Information System (INIS)

Tahir Shah, K.

1993-04-01

We construct a model of the RNA world in terms of naturally evolving nucleotide sequences assuming only Crick-Watson base pairing and self-cleaving/splicing capability. These sequences have the following properties. 1) They are recognizable by an automation (or automata). That is, to each k-sequence, there exist a k-automation which accepts, recognizes or generates the k-sequence. These are known as automatic sequences. Fibonacci and Morse-Thue sequences are the most natural outcome of pre-biotic chemical conditions. 2) Infinite (resp. large) sequences are self-similar (resp. nearly self-similar) under certain rewrite rules and consequently give rise to fractal (resp.fractal-like) structures. Computationally, such sequences can also be generated by their corresponding deterministic parallel re-write system, known as a DOL system. The self-similar sequences are fixed points of their respective rewrite rules. Some of these automatic sequences have the capability that they can read or 'accept' other sequences while others can detect errors and trigger error-correcting mechanisms. They can be enlarged and have block and/or palindrome structure. Linear recurring sequences such as Fibonacci sequence are simply Feed-back Shift Registers, a well know model of information processing machines. We show that a mutation of any rewrite rule can cause a combinatorial explosion of error and relates this to oncogenetical behavior. On the other hand, a mutation of sequences that are not rewrite rules, leads to normal evolutionary change. Known experimental results support our hypothesis. (author). Refs

LookSeq: A browser-based viewer for deep sequencing data

OpenAIRE

Manske, Heinrich Magnus; Kwiatkowski, Dominic P.

2009-01-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an ov...

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

Energy Technology Data Exchange (ETDEWEB)

Shi, CY; Yang, H; Wei, CL; Yu, O; Zhang, ZZ; Sun, J; Wan, XC

2011-01-01

Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from poly (A){sup +} RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

Directory of Open Access Journals (Sweden)

Chen Qi

2011-02-01

Full Text Available Abstract Background Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Results Using high-throughput Illumina RNA-seq, the transcriptome from poly (A+ RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs. Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010. Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were

A validated pipeline for detection of SNVs and short InDels from RNA Sequencing

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Nitin Mandloi

2017-12-01

In this study, we have developed a pipeline to detect germline variants from RNA-seq data. The pipeline steps include: pre-processing, alignment, GATK best practices for RNA-seq and variant filtering. The pre-processing step includes base and adapter trimming and removal of contamination reads from rRNA, tRNA, mitochondrial DNA and repeat regions. The read alignment of the pre-processed reads is performed using STAR/HiSAT. After this we used GATK best practices for the RNA-seq dataset to call germline variants. We benchmarked our pipeline on NA12878 RNA-seq data downloaded from SRA (SRR1258218. After variant calling, the quality passed variants were compared against the gold standard variants provided by GIAB consortium. Of the total ~3.6 million high quality variants reported as gold standard variants for this sample (considering whole genome, our pipeline identified ~58,104 variants to be expressed in RNA-seq. Our pipeline achieved more than 99% of sensitivity in detection of germline variants.

Sequence analysis of L RNA of Lassa virus

International Nuclear Information System (INIS)

Vieth, Simon; Torda, Andrew E.; Asper, Marcel; Schmitz, Herbert; Guenther, Stephan

2004-01-01

The L RNA of three Lassa virus strains originating from Nigeria, Ghana/Ivory Coast, and Sierra Leone was sequenced and the data subjected to structure predictions and phylogenetic analyses. The L gene products had 2218-2221 residues, diverged by 18% at the amino acid level, and contained several conserved regions. Only one region of 504 residues (positions 1043-1546) could be assigned a function, namely that of an RNA polymerase. Secondary structure predictions suggest that this domain is very similar to RNA-dependent RNA polymerases of known structure encoded by plus-strand RNA viruses, permitting a model to be built. Outside the polymerase region, there is little structural data, except for regions of strong alpha-helical content and probably a coiled-coil domain at the N terminus. No evidence for reassortment or recombination during Lassa virus evolution was found. The secondary structure-assisted alignment of the RNA polymerase region permitted a reliable reconstruction of the phylogeny of all negative-strand RNA viruses, indicating that Arenaviridae are most closely related to Nairoviruses. In conclusion, the data provide a basis for structural and functional characterization of the Lassa virus L protein and reveal new insights into the phylogeny of negative-strand RNA viruses

Evaluation of microRNA alignment techniques

Science.gov (United States)

Kaspi, Antony; El-Osta, Assam

2016-01-01

Genomic alignment of small RNA (smRNA) sequences such as microRNAs poses considerable challenges due to their short length (∼21 nucleotides [nt]) as well as the large size and complexity of plant and animal genomes. While several tools have been developed for high-throughput mapping of longer mRNA-seq reads (>30 nt), there are few that are specifically designed for mapping of smRNA reads including microRNAs. The accuracy of these mappers has not been systematically determined in the case of smRNA-seq. In addition, it is unknown whether these aligners accurately map smRNA reads containing sequence errors and polymorphisms. By using simulated read sets, we determine the alignment sensitivity and accuracy of 16 short-read mappers and quantify their robustness to mismatches, indels, and nontemplated nucleotide additions. These were explored in the context of a plant genome (Oryza sativa, ∼500 Mbp) and a mammalian genome (Homo sapiens, ∼3.1 Gbp). Analysis of simulated and real smRNA-seq data demonstrates that mapper selection impacts differential expression results and interpretation. These results will inform on best practice for smRNA mapping and enable more accurate smRNA detection and quantification of expression and RNA editing. PMID:27284164

Combined DECS Analysis and Next-Generation Sequencing Enable Efficient Detection of Novel Plant RNA Viruses

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Hironobu Yanagisawa

2016-03-01

Full Text Available The presence of high molecular weight double-stranded RNA (dsRNA within plant cells is an indicator of infection with RNA viruses as these possess genomic or replicative dsRNA. DECS (dsRNA isolation, exhaustive amplification, cloning, and sequencing analysis has been shown to be capable of detecting unknown viruses. We postulated that a combination of DECS analysis and next-generation sequencing (NGS would improve detection efficiency and usability of the technique. Here, we describe a model case in which we efficiently detected the presumed genome sequence of Blueberry shoestring virus (BSSV, a member of the genus Sobemovirus, which has not so far been reported. dsRNAs were isolated from BSSV-infected blueberry plants using the dsRNA-binding protein, reverse-transcribed, amplified, and sequenced using NGS. A contig of 4,020 nucleotides (nt that shared similarities with sequences from other Sobemovirus species was obtained as a candidate of the BSSV genomic sequence. Reverse transcription (RT-PCR primer sets based on sequences from this contig enabled the detection of BSSV in all BSSV-infected plants tested but not in healthy controls. A recombinant protein encoded by the putative coat protein gene was bound by the BSSV-antibody, indicating that the candidate sequence was that of BSSV itself. Our results suggest that a combination of DECS analysis and NGS, designated here as “DECS-C,” is a powerful method for detecting novel plant viruses.

deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data.

Science.gov (United States)

Zheng, Ling-Ling; Li, Jun-Hao; Wu, Jie; Sun, Wen-Ju; Liu, Shun; Wang, Ze-Lin; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2016-01-04

Small non-coding RNAs (e.g. miRNAs) and long non-coding RNAs (e.g. lincRNAs and circRNAs) are emerging as key regulators of various cellular processes. However, only a very small fraction of these enigmatic RNAs have been well functionally characterized. In this study, we describe deepBase v2.0 (http://biocenter.sysu.edu.cn/deepBase/), an updated platform, to decode evolution, expression patterns and functions of diverse ncRNAs across 19 species. deepBase v2.0 has been updated to provide the most comprehensive collection of ncRNA-derived small RNAs generated from 588 sRNA-Seq datasets. Moreover, we developed a pipeline named lncSeeker to identify 176 680 high-confidence lncRNAs from 14 species. Temporal and spatial expression patterns of various ncRNAs were profiled. We identified approximately 24 280 primate-specific, 5193 rodent-specific lncRNAs, and 55 highly conserved lncRNA orthologs between human and zebrafish. We annotated 14 867 human circRNAs, 1260 of which are orthologous to mouse circRNAs. By combining expression profiles and functional genomic annotations, we developed lncFunction web-server to predict the function of lncRNAs based on protein-lncRNA co-expression networks. This study is expected to provide considerable resources to facilitate future experimental studies and to uncover ncRNA functions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Preparation of highly multiplexed small RNA sequencing libraries.

Science.gov (United States)

Persson, Helena; Søkilde, Rolf; Pirona, Anna Chiara; Rovira, Carlos

2017-08-01

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

Repertoire of bovine miRNA and miRNA-like small regulatory RNAs expressed upon viral infection.

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Evgeny A Glazov

Full Text Available MicroRNA (miRNA and other types of small regulatory RNAs play a crucial role in the regulation of gene expression in eukaryotes. Several distinct classes of small regulatory RNAs have been discovered in recent years. To extend the repertoire of small RNAs characterized in mammals and to examine relationship between host miRNA expression and viral infection we used Illumina's ultrahigh throughput sequencing approach. We sequenced three small RNA libraries prepared from cell line derived from the adult bovine kidney under normal conditions and upon infection of the cell line with Bovine herpesvirus 1. We used a bioinformatics approach to distinguish authentic mature miRNA sequences from other classes of small RNAs and short RNA fragments represented in the sequencing data. Using this approach we detected 219 out of 356 known bovine miRNAs and 115 respective miRNA* sequences. In addition we identified five new bovine orthologs of known mammalian miRNAs and discovered 268 new cow miRNAs many of which are not identifiable in other mammalian genomes and thus might be specific to the ruminant lineage. In addition we found seven new bovine mirtron candidates. We also discovered 10 small nucleolar RNA (snoRNA loci that give rise to small RNA with possible miRNA-like function. Results presented in this study extend our knowledge of the biology and evolution of small regulatory RNAs in mammals and illuminate mechanisms of small RNA biogenesis and function. New miRNA sequences and the original sequencing data have been submitted to miRNA repository (miRBase and NCBI GEO archive respectively. We envisage that these resources will facilitate functional annotation of the bovine genome and promote further functional and comparative genomics studies of small regulatory RNA in mammals.

Relationship between mRNA secondary structure and sequence variability in Chloroplast genes: possible life history implications.

Science.gov (United States)

Krishnan, Neeraja M; Seligmann, Hervé; Rao, Basuthkar J

2008-01-28

Synonymous sites are freer to vary because of redundancy in genetic code. Messenger RNA secondary structure restricts this freedom, as revealed by previous findings in mitochondrial genes that mutations at third codon position nucleotides in helices are more selected against than those in loops. This motivated us to explore the constraints imposed by mRNA secondary structure on evolutionary variability at all codon positions in general, in chloroplast systems. We found that the evolutionary variability and intrinsic secondary structure stability of these sequences share an inverse relationship. Simulations of most likely single nucleotide evolution in Psilotum nudum and Nephroselmis olivacea mRNAs, indicate that helix-forming propensities of mutated mRNAs are greater than those of the natural mRNAs for short sequences and vice-versa for long sequences. Moreover, helix-forming propensity estimated by the percentage of total mRNA in helices increases gradually with mRNA length, saturating beyond 1000 nucleotides. Protection levels of functionally important sites vary across plants and proteins: r-strategists minimize mutation costs in large genes; K-strategists do the opposite. Mrna length presumably predisposes shorter mRNAs to evolve under different constraints than longer mRNAs. The positive correlation between secondary structure protection and functional importance of sites suggests that some sites might be conserved due to packing-protection constraints at the nucleic acid level in addition to protein level constraints. Consequently, nucleic acid secondary structure a priori biases mutations. The converse (exposure of conserved sites) apparently occurs in a smaller number of cases, indicating a different evolutionary adaptive strategy in these plants. The differences between the protection levels of functionally important sites for r- and K-strategists reflect their respective molecular adaptive strategies. These converge with increasing domestication levels of

Deep amplicon sequencing reveals mixed phytoplasma infection within single grapevine plants

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Contaldo, Nicoletta; Makarova, Olga

2011-01-01

The diversity of phytoplasmas within single plants has not yet been fully investigated. In this project, deep amplicon sequencing was used to generate 50,926 phytoplasma sequences from 11 phytoplasma-infected grapevine samples from a PCR amplicon in the 5' end of the 16S region. After clustering ...

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

Science.gov (United States)

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

Single-Cell RNA Sequencing of Glioblastoma Cells.

Science.gov (United States)

Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G

2018-01-01

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

Uniform, optimal signal processing of mapped deep-sequencing data.

Science.gov (United States)

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

A simple method for the parallel deep sequencing of full influenza A genomes

DEFF Research Database (Denmark)

Kampmann, Marie-Louise; Fordyce, Sarah Louise; Avila Arcos, Maria del Carmen

2011-01-01

Given the major threat of influenza A to human and animal health, and its ability to evolve rapidly through mutation and reassortment, tools that enable its timely characterization are necessary to help monitor its evolution and spread. For this purpose, deep sequencing can be a very valuable tool....... This study reports a comprehensive method that enables deep sequencing of the complete genomes of influenza A subtypes using the Illumina Genome Analyzer IIx (GAIIx). By using this method, the complete genomes of nine viruses were sequenced in parallel, representing the 2009 pandemic H1N1 virus, H5N1 virus...

Profiling the nucleobase and structure selectivity of anticancer drugs and other DNA alkylating agents by RNA sequencing.

Science.gov (United States)

Gillingham, Dennis; Sauter, Basilius

2018-05-06

Drugs that covalently modify DNA are components of most chemotherapy regimens, often serving as first-line treatments. Classically the chemical reactivity of DNA alkylators has been determined in vitro with short oligonucleotides. Here we use next generation RNA sequencing to report on the chemoselectivity of alkylating agents. We develop the method with the well-known clinically used DNA modifiying drugs streptozotocin and temozolomide, and then apply the technique to profile RNA modification with uncharacterized alkylation reactions such as with powerful electrophiles like trimethylsilyldiazomethane. The multiplexed and massively parallel format of NGS offers analyses of chemical reactivity in nucleic acids to be accomplished in less time with greater statistical power. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Sara Kangaspeska

Full Text Available 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.

Highly divergent 16S rRNA sequences in ribosomal operons of Scytonema hyalinum (Cyanobacteria.

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Jeffrey R Johansen

Full Text Available A highly divergent 16S rRNA gene was found in one of the five ribosomal operons present in a species complex currently circumscribed as Scytonema hyalinum (Nostocales, Cyanobacteria using clone libraries. If 16S rRNA sequence macroheterogeneity among ribosomal operons due to insertions, deletions or truncation is excluded, the sequence heterogeneity observed in S. hyalinum was the highest observed in any prokaryotic species thus far (7.3-9.0%. The secondary structure of the 16S rRNA molecules encoded by the two divergent operons was nearly identical, indicating possible functionality. The 23S rRNA gene was examined for a few strains in this complex, and it was also found to be highly divergent from the gene in Type 2 operons (8.7%, and likewise had nearly identical secondary structure between the Type 1 and Type 2 operons. Furthermore, the 16S-23S ITS showed marked differences consistent between operons among numerous strains. Both operons have promoter sequences that satisfy consensus requirements for functional prokaryotic transcription initiation. Horizontal gene transfer from another unknown heterocytous cyanobacterium is considered the most likely explanation for the origin of this molecule, but does not explain the ultimate origin of this sequence, which is very divergent from all 16S rRNA sequences found thus far in cyanobacteria. The divergent sequence is highly conserved among numerous strains of S. hyalinum, suggesting adaptive advantage and selective constraint of the divergent sequence.

Appendix: a solution hybridization assay to detect radioactive globin messenger RNA nucleotide sequences

Energy Technology Data Exchange (ETDEWEB)

Ross, J

1976-09-15

In view of the sensitivity and specificity of the solution hybridization assay for unlabeled globin mRNA a similar technique has been devised to detect radioactive globin mRNA sequences with unlabeled globin cDNA. Several properties of the hybridization reaction are presented since RNA kinetic experiments reported recently depend on the validity of this assay. Data on hybridization analysis of (/sup 3/H)RNA from mouse fetal liver or erythroleukemia cell cytoplasm are presented. These data indicate that the excess cDNA solution assay for radioactive globin mRNA detection is specific for globin mRNA sequences. It can be performed rapidly and is highly reproducible from experiment. It is at least 500-fold less sensitive than the assay for unlabeled globin mRNA, due to the RNAase backgrounds of 0.05 to 0.15 %. However, this limitation has not affected kinetic experiments with non-dividing fetal liver erythroid cells, which synthesize relatively large quantities of globin mRNA.

Cloning and sequencing of full-length cDNAs of RNA1 and RNA2 of a Tomato black ring virus isolate from Poland.

Science.gov (United States)

Jończyk, M; Le Gall, O; Pałucha, A; Borodynko, N; Pospieszny, H

2004-04-01

Full-length cDNA clones corresponding to the RNA1 and RNA2 of the Polish isolate MJ of Tomato black ring virus (TBRV, genus Nepovirus) were obtained using a direct recombination strategy in yeast, and their complete nucleotide sequences were established. RNA1 is 7358 nucleotides and RNA2 is 4633 nucleotides in length, excluding the poly(A) tails. Both RNAs contain a single open reading frame encoding polyproteins of 254 kDa and 149 kDa for RNA1 and RNA2 respectively. Putative cleavage sites were identified, and the relationships between TBRV and related nepoviruses were studied by sequence comparison.

Short circuit in deep brain stimulation.

Science.gov (United States)

Samura, Kazuhiro; Miyagi, Yasushi; Okamoto, Tsuyoshi; Hayami, Takehito; Kishimoto, Junji; Katano, Mitsuo; Kamikaseda, Kazufumi

2012-11-01

The authors undertook this study to investigate the incidence, cause, and clinical influence of short circuits in patients treated with deep brain stimulation (DBS). After the incidental identification of a short circuit during routine follow-up, the authors initiated a policy at their institution of routinely evaluating both therapeutic impedance and system impendence at every outpatient DBS follow-up visit, irrespective of the presence of symptoms suggesting possible system malfunction. This study represents a report of their findings after 1 year of this policy. Implanted DBS leads exhibiting short circuits were identified in 7 patients (8.9% of the patients seen for outpatient follow-up examinations during the 12-month study period). The mean duration from DBS lead implantation to the discovery of the short circuit was 64.7 months. The symptoms revealing short circuits included the wearing off of therapeutic effect, apraxia of eyelid opening, or dysarthria in 6 patients with Parkinson disease (PD), and dystonia deterioration in 1 patient with generalized dystonia. All DBS leads with short circuits had been anchored to the cranium using titanium miniplates. Altering electrode settings resulted in clinical improvement in the 2 PD cases in which patients had specific symptoms of short circuits (2.5%) but not in the other 4 cases. The patient with dystonia underwent repositioning and replacement of a lead because the previous lead was located too anteriorly, but did not experience symptom improvement. In contrast to the sudden loss of clinical efficacy of DBS caused by an open circuit, short circuits may arise due to a gradual decrease in impedance, causing the insidious development of neurological symptoms via limited or extended potential fields as well as shortened battery longevity. The incidence of short circuits in DBS may be higher than previously thought, especially in cases in which DBS leads are anchored with miniplates. The circuit impedance of DBS

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

Science.gov (United States)

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

Thousands of primer-free, high-quality, full-length SSU rRNA sequences from all domains of life

DEFF Research Database (Denmark)

Karst, Soeren M; Dueholm, Morten S; McIlroy, Simon J

2016-01-01

Ribosomal RNA (rRNA) genes are the consensus marker for determination of microbial diversity on the planet, invaluable in studies of evolution and, for the past decade, high-throughput sequencing of variable regions of ribosomal RNA genes has become the backbone of most microbial ecology studies...... (SSU) rRNA genes and synthetic long read sequencing by molecular tagging, to generate primer-free, full-length SSU rRNA gene sequences from all domains of life, with a median raw error rate of 0.17%. We generated thousands of full-length SSU rRNA sequences from five well-studied ecosystems (soil, human...... gut, fresh water, anaerobic digestion, and activated sludge) and obtained sequences covering all domains of life and the majority of all described phyla. Interestingly, 30% of all bacterial operational taxonomic units were novel, compared to the SILVA database (less than 97% similarity...

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Science.gov (United States)

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Deep RNA sequencing reveals hidden features and dynamics of early gene transcription in Paramecium bursaria chlorella virus 1.

Directory of Open Access Journals (Sweden)

Guillaume Blanc

Full Text Available Paramecium bursaria chlorella virus 1 (PBCV-1 is the prototype of the genus Chlorovirus (family Phycodnaviridae that infects the unicellular, eukaryotic green alga Chlorella variabilis NC64A. The 331-kb PBCV-1 genome contains 416 major open reading frames. A mRNA-seq approach was used to analyze PBCV-1 transcriptomes at 6 progressive times during the first hour of infection. The alignment of 17 million reads to the PBCV-1 genome allowed the construction of single-base transcriptome maps. Significant transcription was detected for a subset of 50 viral genes as soon as 7 min after infection. By 20 min post infection (p.i., transcripts were detected for most PBCV-1 genes and transcript levels continued to increase globally up to 60 min p.i., at which time 41% or the poly (A+-containing RNAs in the infected cells mapped to the PBCV-1 genome. For some viral genes, the number of transcripts in the latter time points (20 to 60 min p.i. was much higher than that of the most highly expressed host genes. RNA-seq data revealed putative polyadenylation signal sequences in PBCV-1 genes that were identical to the polyadenylation signal AAUAAA of green algae. Several transcripts have an RNA fragment excised. However, the frequency of excision and the resulting putative shortened protein products suggest that most of these excision events have no functional role but are probably the result of the activity of misled splicesomes.

Phytophthora have distinct endogenous small RNA populations that include short interfering and microRNAs.

Directory of Open Access Journals (Sweden)

Noah Fahlgren

Full Text Available In eukaryotes, RNA silencing pathways utilize 20-30-nucleotide small RNAs to regulate gene expression, specify and maintain chromatin structure, and repress viruses and mobile genetic elements. RNA silencing was likely present in the common ancestor of modern eukaryotes, but most research has focused on plant and animal RNA silencing systems. Phytophthora species belong to a phylogenetically distinct group of economically important plant pathogens that cause billions of dollars in yield losses annually as well as ecologically devastating outbreaks. We analyzed the small RNA-generating components of the genomes of P. infestans, P. sojae and P. ramorum using bioinformatics, genetic, phylogenetic and high-throughput sequencing-based methods. Each species produces two distinct populations of small RNAs that are predominantly 21- or 25-nucleotides long. The 25-nucleotide small RNAs were primarily derived from loci encoding transposable elements and we propose that these small RNAs define a pathway of short-interfering RNAs that silence repetitive genetic elements. The 21-nucleotide small RNAs were primarily derived from inverted repeats, including a novel microRNA family that is conserved among the three species, and several gene families, including Crinkler effectors and type III fibronectins. The Phytophthora microRNA is predicted to target a family of amino acid/auxin permeases, and we propose that 21-nucleotide small RNAs function at the post-transcriptional level. The functional significance of microRNA-guided regulation of amino acid/auxin permeases and the association of 21-nucleotide small RNAs with Crinkler effectors remains unclear, but this work provides a framework for testing the role of small RNAs in Phytophthora biology and pathogenesis in future work.

Phytophthora have distinct endogenous small RNA populations that include short interfering and microRNAs.

Science.gov (United States)

Fahlgren, Noah; Bollmann, Stephanie R; Kasschau, Kristin D; Cuperus, Josh T; Press, Caroline M; Sullivan, Christopher M; Chapman, Elisabeth J; Hoyer, J Steen; Gilbert, Kerrigan B; Grünwald, Niklaus J; Carrington, James C

2013-01-01

In eukaryotes, RNA silencing pathways utilize 20-30-nucleotide small RNAs to regulate gene expression, specify and maintain chromatin structure, and repress viruses and mobile genetic elements. RNA silencing was likely present in the common ancestor of modern eukaryotes, but most research has focused on plant and animal RNA silencing systems. Phytophthora species belong to a phylogenetically distinct group of economically important plant pathogens that cause billions of dollars in yield losses annually as well as ecologically devastating outbreaks. We analyzed the small RNA-generating components of the genomes of P. infestans, P. sojae and P. ramorum using bioinformatics, genetic, phylogenetic and high-throughput sequencing-based methods. Each species produces two distinct populations of small RNAs that are predominantly 21- or 25-nucleotides long. The 25-nucleotide small RNAs were primarily derived from loci encoding transposable elements and we propose that these small RNAs define a pathway of short-interfering RNAs that silence repetitive genetic elements. The 21-nucleotide small RNAs were primarily derived from inverted repeats, including a novel microRNA family that is conserved among the three species, and several gene families, including Crinkler effectors and type III fibronectins. The Phytophthora microRNA is predicted to target a family of amino acid/auxin permeases, and we propose that 21-nucleotide small RNAs function at the post-transcriptional level. The functional significance of microRNA-guided regulation of amino acid/auxin permeases and the association of 21-nucleotide small RNAs with Crinkler effectors remains unclear, but this work provides a framework for testing the role of small RNAs in Phytophthora biology and pathogenesis in future work.

Phytophthora Have Distinct Endogenous Small RNA Populations That Include Short Interfering and microRNAs

Science.gov (United States)

Fahlgren, Noah; Bollmann, Stephanie R.; Kasschau, Kristin D.; Cuperus, Josh T.; Press, Caroline M.; Sullivan, Christopher M.; Chapman, Elisabeth J.; Hoyer, J. Steen; Gilbert, Kerrigan B.; Grünwald, Niklaus J.; Carrington, James C.

2013-01-01

In eukaryotes, RNA silencing pathways utilize 20-30-nucleotide small RNAs to regulate gene expression, specify and maintain chromatin structure, and repress viruses and mobile genetic elements. RNA silencing was likely present in the common ancestor of modern eukaryotes, but most research has focused on plant and animal RNA silencing systems. Phytophthora species belong to a phylogenetically distinct group of economically important plant pathogens that cause billions of dollars in yield losses annually as well as ecologically devastating outbreaks. We analyzed the small RNA-generating components of the genomes of P. infestans, P. sojae and P. ramorum using bioinformatics, genetic, phylogenetic and high-throughput sequencing-based methods. Each species produces two distinct populations of small RNAs that are predominantly 21- or 25-nucleotides long. The 25-nucleotide small RNAs were primarily derived from loci encoding transposable elements and we propose that these small RNAs define a pathway of short-interfering RNAs that silence repetitive genetic elements. The 21-nucleotide small RNAs were primarily derived from inverted repeats, including a novel microRNA family that is conserved among the three species, and several gene families, including Crinkler effectors and type III fibronectins. The Phytophthora microRNA is predicted to target a family of amino acid/auxin permeases, and we propose that 21-nucleotide small RNAs function at the post-transcriptional level. The functional significance of microRNA-guided regulation of amino acid/auxin permeases and the association of 21-nucleotide small RNAs with Crinkler effectors remains unclear, but this work provides a framework for testing the role of small RNAs in Phytophthora biology and pathogenesis in future work. PMID:24204767

Deep-sequencing to resolve complex diversity of apicomplexan parasites in platypuses and echidnas: Proof of principle for wildlife disease investigation.

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Šlapeta, Jan; Saverimuttu, Stefan; Vogelnest, Larry; Sangster, Cheryl; Hulst, Frances; Rose, Karrie; Thompson, Paul; Whittington, Richard

2017-11-01

The short-beaked echidna (Tachyglossus aculeatus) and the platypus (Ornithorhynchus anatinus) are iconic egg-laying monotremes (Mammalia: Monotremata) from Australasia. The aim of this study was to demonstrate the utility of diversity profiles in disease investigations of monotremes. Using small subunit (18S) rDNA amplicon deep-sequencing we demonstrated the presence of apicomplexan parasites and confirmed by direct and cloned amplicon gene sequencing Theileria ornithorhynchi, Theileria tachyglossi, Eimeria echidnae and Cryptosporidium fayeri. Using a combination of samples from healthy and diseased animals, we show a close evolutionary relationship between species of coccidia (Eimeria) and piroplasms (Theileria) from the echidna and platypus. The presence of E. echidnae was demonstrated in faeces and tissues affected by disseminated coccidiosis. Moreover, the presence of E. echidnae DNA in the blood of echidnas was associated with atoxoplasma-like stages in white blood cells, suggesting Hepatozoon tachyglossi blood stages are disseminated E. echidnae stages. These next-generation DNA sequencing technologies are suited to material and organisms that have not been previously characterised and for which the material is scarce. The deep sequencing approach supports traditional diagnostic methods, including microscopy, clinical pathology and histopathology, to better define the status quo. This approach is particularly suitable for wildlife disease investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

RNA-DNA sequence differences spell genetic code ambiguities

DEFF Research Database (Denmark)

Bentin, Thomas; Nielsen, Michael L

2013-01-01

A recent paper in Science by Li et al. 2011(1) reports widespread sequence differences in the human transcriptome between RNAs and their encoding genes termed RNA-DNA differences (RDDs). The findings could add a new layer of complexity to gene expression but the study has been criticized. ...

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons

Science.gov (United States)

Haas, Brian J.; Gevers, Dirk; Earl, Ashlee M.; Feldgarden, Mike; Ward, Doyle V.; Giannoukos, Georgia; Ciulla, Dawn; Tabbaa, Diana; Highlander, Sarah K.; Sodergren, Erica; Methé, Barbara; DeSantis, Todd Z.; Petrosino, Joseph F.; Knight, Rob; Birren, Bruce W.

2011-01-01

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys. PMID:21212162

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

Science.gov (United States)

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.

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

Science.gov (United States)

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 RNA in 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

Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

Science.gov (United States)

Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

2017-03-01

Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

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Manske, Magnus; Miotto, Olivo; Campino, Susana; Auburn, Sarah; Almagro-Garcia, Jacob; Maslen, Gareth; O’Brien, Jack; Djimde, Abdoulaye; Doumbo, Ogobara; Zongo, Issaka; Ouedraogo, Jean-Bosco; Michon, Pascal; Mueller, Ivo; Siba, Peter; Nzila, Alexis; Borrmann, Steffen; Kiara, Steven M.; Marsh, Kevin; Jiang, Hongying; Su, Xin-Zhuan; Amaratunga, Chanaki; Fairhurst, Rick; Socheat, Duong; Nosten, Francois; Imwong, Mallika; White, Nicholas J.; Sanders, Mandy; Anastasi, Elisa; Alcock, Dan; Drury, Eleanor; Oyola, Samuel; Quail, Michael A.; Turner, Daniel J.; Rubio, Valentin Ruano; Jyothi, Dushyanth; Amenga-Etego, Lucas; Hubbart, Christina; Jeffreys, Anna; Rowlands, Kate; Sutherland, Colin; Roper, Cally; Mangano, Valentina; Modiano, David; Tan, John C.; Ferdig, Michael T.; Amambua-Ngwa, Alfred; Conway, David J.; Takala-Harrison, Shannon; Plowe, Christopher V.; Rayner, Julian C.; Rockett, Kirk A.; Clark, Taane G.; Newbold, Chris I.; Berriman, Matthew; MacInnis, Bronwyn; Kwiatkowski, Dominic P.

2013-01-01

Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. 1,2 Here we describe methods for large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short term culture. Analysis of 86,158 exonic SNPs that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome. PMID:22722859

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

Science.gov (United States)

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...

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

Science.gov (United States)

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.

RNA inverse folding using Monte Carlo tree search.

Science.gov (United States)

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-Seq analysis of D. radiodurans find non coding RNAs expressed in response to radiation stress

International Nuclear Information System (INIS)

Gadewal, Nikhil; Mukhopadhyaya, Rita

2015-01-01

In bacteria discovery of functional RNA molecules that are not translated into protein, noncoding RNAs, became possible with advent of Next Generation Sequencing technology. Bacterial non coding RNAs are typically 50-300 nucleotides long and work as internal signals controlling various levels of gene expression. Deep sequencing of total cellular RNA captures all coding and noncoding transcripts with their differential levels of expression in the transcriptome. It provides a powerful approach to study bacterial gene expression and mechanisms of gene regulation. We subjected the 3 h transcriptome of Deinococcus radiodurans R1 cells post exposure to 6 KGy gamma radiation to 100 x 2 cycles of deep sequencing on the Illumina HiSeq 2000 to look for ncRNA transcripts. Bioinformatics pipeline for analysis and interpretation of RNA Seq data was done in house using Softwares available in public domains. Our sequence data aligned with 21 putative ncRNAs expressed in the intergenic regions of annotated genome of D radiodurans. Verification of 2 ncRNA candidates and 3 transcription factor genes by Real Time PCR confirmed presence of these transcripts in the 3 h transcriptome sequenced by us. Any relationship between ncRNAs and control of radiation induced gene expression in D radiodurans can be proved only after specific gene knock outs in future. (author)

16S ribosomal RNA sequence analysis for determination of phylogenetic relationship among methylotrophs.

Science.gov (United States)

Tsuji, K; Tsien, H C; Hanson, R S; DePalma, S R; Scholtz, R; LaRoche, S

1990-01-01

16S ribosomal RNAs (rRNA) of 12 methylotrophic bacteria have been almost completely sequenced to establish their phylogenetic relationships. Methylotrophs that are physiologically related are phylogenetically diverse and are scattered among the purple eubacteria (class Proteobacteria). Group I methylotrophs can be classified in the beta- and the gamma-subdivisions and group II methylotrophs in the alpha-subdivision of the purple eubacteria, respectively. Pink-pigmented facultative and non-pigmented obligate group II methylotrophs form two distinctly separate branches within the alpha-subdivision. The secondary structures of the 16S rRNA sequences of 'Methylocystis parvus' strain OBBP, 'Methylosinus trichosporium' strain OB3b, 'Methylosporovibrio methanica' strain 81Z and Hyphomicrobium sp. strain DM2 are similar, and these non-pigmented obligate group II methylotrophs form one tight cluster in the alpha-subdivision. The pink-pigmented facultative methylotrophs, Methylobacterium extorquens strain AM1, Methylobacterium sp. strain DM4 and Methylobacterium organophilum strain XX form another cluster within the alpha-subdivision. Although similar in phenotypic characteristics, Methylobacterium organophilum strain XX and Methylobacterium extorquens strain AM1 are clearly distinguishable by their 16S rRNA sequences. The group I methylotrophs, Methylophilus methylotrophus strain AS1 and methylotrophic species DM11, which do not utilize methane, are similar in 16S rRNA sequence to bacteria in the beta-subdivision. The methane-utilizing, obligate group I methanotrophs, Methylococcus capsulatus strain BATH and Methylomonas methanica, are placed in the gamma-subdivision. The results demonstrate that it is possible to distinguish and classify the methylotrophic bacteria using 16S rRNA sequence analysis.

Targeted assembly of short sequence reads.

Directory of Open Access Journals (Sweden)

René L Warren

Full Text Available As next-generation sequence (NGS production continues to increase, analysis is becoming a significant bottleneck. However, in situations where information is required only for specific sequence variants, it is not necessary to assemble or align whole genome data sets in their entirety. Rather, NGS data sets can be mined for the presence of sequence variants of interest by localized assembly, which is a faster, easier, and more accurate approach. We present TASR, a streamlined assembler that interrogates very large NGS data sets for the presence of specific variants by only considering reads within the sequence space of input target sequences provided by the user. The NGS data set is searched for reads with an exact match to all possible short words within the target sequence, and these reads are then assembled stringently to generate a consensus of the target and flanking sequence. Typically, variants of a particular locus are provided as different target sequences, and the presence of the variant in the data set being interrogated is revealed by a successful assembly outcome. However, TASR can also be used to find unknown sequences that flank a given target. We demonstrate that TASR has utility in finding or confirming genomic mutations, polymorphisms, fusions and integration events. Targeted assembly is a powerful method for interrogating large data sets for the presence of sequence variants of interest. TASR is a fast, flexible and easy to use tool for targeted assembly.

Small RNA sequencing reveals metastasis-related microRNAs in lung adenocarcinoma

DEFF Research Database (Denmark)

Daugaard, Iben; Venø, Morten T.; Yan, Yan

2017-01-01

The majority of lung cancer deaths are caused by metastatic disease. MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression and miRNA dysregulation can contribute to metastatic progression. Here, small RNA sequencing was used to profile the miRNA and piwi-interacting RNA (piRNA......) transcriptomes in relation to lung cancer metastasis. RNA-seq was performed using RNA extracted from formalin-fixed paraffin embedded (FFPE) lung adenocarcinomas (LAC) and brain metastases from 8 patients, and LACs from 8 patients without detectable metastatic disease. Impact on miRNA and piRNA transcriptomes...... was subtle with 9 miRNAs and 8 piRNAs demonstrating differential expression between metastasizing and non-metastasizing LACs. For piRNAs, decreased expression of piR-57125 was the most significantly associated with distant metastasis. Validation by RT-qPCR in a LAC cohort comprising 52 patients confirmed...

Error Analysis of Deep Sequencing of Phage Libraries: Peptides Censored in Sequencing

Directory of Open Access Journals (Sweden)

Wadim L. Matochko

2013-01-01

Full Text Available Next-generation sequencing techniques empower selection of ligands from phage-display libraries because they can detect low abundant clones and quantify changes in the copy numbers of clones without excessive selection rounds. Identification of errors in deep sequencing data is the most critical step in this process because these techniques have error rates >1%. Mechanisms that yield errors in Illumina and other techniques have been proposed, but no reports to date describe error analysis in phage libraries. Our paper focuses on error analysis of 7-mer peptide libraries sequenced by Illumina method. Low theoretical complexity of this phage library, as compared to complexity of long genetic reads and genomes, allowed us to describe this library using convenient linear vector and operator framework. We describe a phage library as N×1 frequency vector n=ni, where ni is the copy number of the ith sequence and N is the theoretical diversity, that is, the total number of all possible sequences. Any manipulation to the library is an operator acting on n. Selection, amplification, or sequencing could be described as a product of a N×N matrix and a stochastic sampling operator (Sa. The latter is a random diagonal matrix that describes sampling of a library. In this paper, we focus on the properties of Sa and use them to define the sequencing operator (Seq. Sequencing without any bias and errors is Seq=Sa IN, where IN is a N×N unity matrix. Any bias in sequencing changes IN to a nonunity matrix. We identified a diagonal censorship matrix (CEN, which describes elimination or statistically significant downsampling, of specific reads during the sequencing process.

A DNA sequence obtained by replacement of the dopamine RNA aptamer bases is not an aptamer.

Science.gov (United States)

Álvarez-Martos, Isabel; Ferapontova, Elena E

2017-08-05

A unique specificity of the aptamer-ligand biorecognition and binding facilitates bioanalysis and biosensor development, contributing to discrimination of structurally related molecules, such as dopamine and other catecholamine neurotransmitters. The aptamer sequence capable of specific binding of dopamine is a 57 nucleotides long RNA sequence reported in 1997 (Biochemistry, 1997, 36, 9726). Later, it was suggested that the DNA homologue of the RNA aptamer retains the specificity of dopamine binding (Biochem. Biophys. Res. Commun., 2009, 388, 732). Here, we show that the DNA sequence obtained by the replacement of the RNA aptamer bases for their DNA analogues is not able of specific biorecognition of dopamine, in contrast to the original RNA aptamer sequence. This DNA sequence binds dopamine and structurally related catecholamine neurotransmitters non-specifically, as any DNA sequence, and, thus, is not an aptamer and cannot be used neither for in vivo nor in situ analysis of dopamine in the presence of structurally related neurotransmitters. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic diversity of archaea in deep-sea hydrothermal vent environments.

Science.gov (United States)

Takai, K; Horikoshi, K

1999-08-01

Molecular phylogenetic analysis of naturally occurring archaeal communities in deep-sea hydrothermal vent environments was carried out by PCR-mediated small subunit rRNA gene (SSU rDNA) sequencing. As determined through partial sequencing of rDNA clones amplified with archaea-specific primers, the archaeal populations in deep-sea hydrothermal vent environments showed a great genetic diversity, and most members of these populations appeared to be uncultivated and unidentified organisms. In the phylogenetic analysis, a number of rDNA sequences obtained from deep-sea hydrothermal vents were placed in deep lineages of the crenarchaeotic phylum prior to the divergence of cultivated thermophilic members of the crenarchaeota or between thermophilic members of the euryarchaeota and members of the methanogen-halophile clade. Whole cell in situ hybridization analysis suggested that some microorganisms of novel phylotypes predicted by molecular phylogenetic analysis were likely present in deep-sea hydrothermal vent environments. These findings expand our view of the genetic diversity of archaea in deep-sea hydrothermal vent environments and of the phylogenetic organization of archaea.

Genetic selection and DNA sequences of 4.5S RNA homologs

DEFF Research Database (Denmark)

Brown, S; Thon, G; Tolentino, E

1989-01-01

A general strategy for cloning the functional homologs of an Escherichia coli gene was used to clone homologs of 4.5S RNA from other bacteria. The genes encoding these homologs were selected by their ability to complement a deletion of the gene for 4.5S RNA. DNA sequences of the regions encoding...

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

Science.gov (United States)

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Malachi Griffith

2015-08-01

Full Text Available 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.

The role of upstream sequences in selecting the reading frame on tmRNA

Directory of Open Access Journals (Sweden)

Dewey Jonathan D

2008-06-01

Full Text Available Abstract Background tmRNA acts first as a tRNA and then as an mRNA to rescue stalled ribosomes in eubacteria. Two unanswered questions about tmRNA function remain: how does tmRNA, lacking an anticodon, bypass the decoding machinery and enter the ribosome? Secondly, how does the ribosome choose the proper codon to resume translation on tmRNA? According to the -1 triplet hypothesis, the answer to both questions lies in the unique properties of the three nucleotides upstream of the first tmRNA codon. These nucleotides assume an A-form conformation that mimics the codon-anticodon interaction, leading to recognition by the decoding center and choice of the reading frame. The -1 triplet hypothesis is important because it is the most credible model in which direct binding and recognition by the ribosome sets the reading frame on tmRNA. Results Conformational analysis predicts that 18 triplets cannot form the correct structure to function as the -1 triplet of tmRNA. We tested the tmRNA activity of all possible -1 triplet mutants using a genetic assay in Escherichia coli. While many mutants displayed reduced activity, our findings do not match the predictions of this model. Additional mutagenesis identified sequences further upstream that are required for tmRNA function. An immunoblot assay for translation of the tmRNA tag revealed that certain mutations in U85, A86, and the -1 triplet sequence result in improper selection of the first codon and translation in the wrong frame (-1 or +1 in vivo. Conclusion Our findings disprove the -1 triplet hypothesis. The -1 triplet is not required for accommodation of tmRNA into the ribosome, although it plays a minor role in frame selection. Our results strongly disfavor direct ribosomal recognition of the upstream sequence, instead supporting a model in which the binding of a separate ligand to A86 is primarily responsible for frame selection.

Microbial community profiling of fresh basil and pitfalls in taxonomic assignment of enterobacterial pathogenic species based upon 16S rRNA amplicon sequencing.

Science.gov (United States)

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

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

Science.gov (United States)

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.

The nucleotide sequence of satellite RNA in grapevine fanleaf virus, strain F13.

Science.gov (United States)

Fuchs, M; Pinck, M; Serghini, M A; Ravelonandro, M; Walter, B; Pinck, L

1989-04-01

The nucleotide sequence of cDNA copies of grapevine fanleaf virus (strain F13) satellite RNA has been determined. The primary structure obtained was 1114 nucleotides in length, excluding the poly(A) tail, and contained only one long open reading frame encoding a 341 residue, highly hydrophilic polypeptide of Mr37275. The coding sequence was bordered by a leader of 14 nucleotides and a 3'-terminal non-coding region of 74 nucleotides. No homology has been found with small satellite RNAs associated with other nepoviruses. Two limited homologies of eight nucleotides have been detected between the satellite RNA in grapevine fanleaf virus and those in tomato black ring virus, and a consensus sequence U.G/UGAAAAU/AU/AU/A at the 5' end of nepovirus RNAs is reported. A less extended consensus exists in this region in comovirus and picornavirus RNA.

Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping

Science.gov (United States)

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.

The complete mitochondrial genome of the deep-sea sponge Poecillastra laminaris (Astrophorida, Vulcanellidae).

Science.gov (United States)

Zeng, Cong; Thomas, Leighton J; Kelly, Michelle; Gardner, Jonathan P A

2016-05-01

The complete mitochondrial genome of a New Zealand specimen of the deep-sea sponge Poecillastra laminaris (Sollas, 1886) (Astrophorida, Vulcanellidae), from the Colville Ridge, New Zealand, was sequenced using the 454 Life Science pyrosequencing system. To identify homologous mitochondrial sequences, the 454 reads were mapped to the complete mitochondrial genome sequence of Geodia neptuni (GeneBank No. NC_006990). The P. laminaris genome is 18,413 bp in length and includes 14 protein-coding genes, 24 transfer RNA genes and 2 ribosomal RNA genes. Gene order resembled that of other demosponges. The base composition of the genome is A (29.1%), T (35.2%), C (14.0%) and G (21.7%). This is the second published mitogenome for a sponge of the order Astrophorida and will be useful in future phylogenetic analysis of deep-sea sponges.

Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing

OpenAIRE

Wang, Bin; Guo, Guangwu; Wang, Chao; Lin, Ying; Wang, Xiaoning; Zhao, Mouming; Guo, Yong; He, Minghui; Zhang, Yong; Pan, Li

2010-01-01

Aspergillus oryzae, an important filamentous fungus used in food fermentation and the enzyme industry, has been shown through genome sequencing and various other tools to have prominent features in its genomic composition. However, the functional complexity of the A. oryzae transcriptome has not yet been fully elucidated. Here, we applied direct high-throughput paired-end RNA-sequencing (RNA-Seq) to the transcriptome of A. oryzae under four different culture conditions. With the high resoluti...

Unifying cancer and normal RNA sequencing data from different sources

Science.gov (United States)

Wang, Qingguo; Armenia, Joshua; Zhang, Chao; Penson, Alexander V.; Reznik, Ed; Zhang, Liguo; Minet, Thais; Ochoa, Angelica; Gross, Benjamin E.; Iacobuzio-Donahue, Christine A.; Betel, Doron; Taylor, Barry S.; Gao, Jianjiong; Schultz, Nikolaus

2018-01-01

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data, such as the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA). While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources remains challenging, due to differences in sample and data processing. Here, we developed a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment, gene expression quantification, and batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from GTEx and TCGA and successfully corrected for study-specific biases, enabling comparative analysis between TCGA and GTEx. The normalized datasets are available for download on figshare. PMID:29664468

Computational sequence analysis of predicted long dsRNA transcriptomes of major crops reveals sequence complementarity with human genes.

Science.gov (United States)

Jensen, Peter D; Zhang, Yuanji; Wiggins, B Elizabeth; Petrick, Jay S; Zhu, Jin; Kerstetter, Randall A; Heck, Gregory R; Ivashuta, Sergey I

2013-01-01

Long double-stranded RNAs (long dsRNAs) are precursors for the effector molecules of sequence-specific RNA-based gene silencing in eukaryotes. Plant cells can contain numerous endogenous long dsRNAs. This study demonstrates that such endogenous long dsRNAs in plants have sequence complementarity to human genes. Many of these complementary long dsRNAs have perfect sequence complementarity of at least 21 nucleotides to human genes; enough complementarity to potentially trigger gene silencing in targeted human cells if delivered in functional form. However, the number and diversity of long dsRNA molecules in plant tissue from crops such as lettuce, tomato, corn, soy and rice with complementarity to human genes that have a long history of safe consumption supports a conclusion that long dsRNAs do not present a significant dietary risk.

The nucleotide sequence of 5S ribosomal RNA from Micrococcus lysodeikticus.

Science.gov (United States)

Hori, H; Osawa, S; Murao, K; Ishikura, H

1980-01-01

The nucleotide sequence of ribosomal 5S RNA from Micrococcus lysodeikticus is pGUUACGGCGGCUAUAGCGUGGGGGAAACGCCCGGCCGUAUAUCGAACCCGGAAGCUAAGCCCCAUAGCGCCGAUGGUUACUGUAACCGGGAGGUUGUGGGAGAGUAGGUCGCCGCCGUGAOH. When compared to other 5S RNAs, the sequence homology is greatest with Thermus aquaticus, and these two 5S RNAs reveal several features intermediate between those of typical gram-positive bacteria and gram-negative bacteria. PMID:6780979

Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues.

Science.gov (United States)

Chakraborty, Sandeep; Britton, Monica; Martínez-García, P J; Dandekar, Abhaya M

2016-03-01

Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling.

Discovery of Bovine Digital Dermatitis-Associated Treponema spp. in the Dairy Herd Environment by a Targeted Deep-Sequencing Approach

DEFF Research Database (Denmark)

Schou, Kirstine Klitgaard; Weiss Nielsen, Martin; Ingerslev, Hans-Christian

2014-01-01

The bacteria associated with the infectious claw disease bovine digital dermatitis (DD) are spirochetes of the genus Treponema; however, their environmental reservoir remains unknown. To our knowledge, the current study is the first report of the discovery and phylogenetic characterization of r...... of this disease among cows within a herd as well as between herds. To address the issue of DD infection reservoirs, we searched for evidence of DD-associated treponemes in fresh feces, in slurry, and in hoof lesions by deep sequencing of the V3 and V4 hypervariable regions of the 16S rRNA gene coupled...... with identification at the operational-taxonomic-unit level. Using treponeme-specific primers in this high-throughput approach, we identified small amounts of DNA (on average 0.6% of the total amount of sequence reads) from DD-associated treponemes in 43 of 64 samples from slurry and cow feces collected from six...

Deep sequencing shows microRNA involvement in bovine mammary gland adaptation to diets supplemented with linseed oil or safflower oil.

Science.gov (United States)

Li, Ran; Beaudoin, Frédéric; Ammah, Adolf A; Bissonnette, Nathalie; Benchaar, Chaouki; Zhao, Xin; Lei, Chuzhao; Ibeagha-Awemu, Eveline M

2015-10-30

Bovine milk fat composition is responsive to dietary manipulation providing an avenue to modify the content of fatty acids and especially some specific unsaturated fatty acid (USFA) isomers of benefit to human health. MicroRNAs (miRNAs) regulate gene expression but their specific roles in bovine mammary gland lipogenesis are unclear. The objective of this study was to determine the expression pattern of miRNAs following mammary gland adaptation to dietary supplementation with 5 % linseed or safflower oil using next generation RNA-sequencing. Twenty-four Canadian Holstein dairy cows (twelve per treatment) in mid lactation were fed a control diet (total mixed ration of corn:grass silages) for 28 days followed by a treatment period (control diet supplemented with 5 % linseed or safflower oil) of 28 days. Milk samples were collected weekly for fat and individual fatty acid determination. RNA from mammary gland biopsies harvested on day-14 (control period) and on days +7 and +28 (treatment period) from six randomly selected cows per treatment was subjected to small RNA sequencing. Milk fat percentage decreased significantly (P safflower oil treatments, respectively. Seven miRNAs including six up-regulated (bta-miR-199c, miR-199a-3p, miR-98, miR-378, miR-148b and miR-21-5p) and one down-regulated (bta-miR-200a) were found to be regulated (P < 0.05) by both treatments, and thus considered core differentially expressed (DE) miRNAs. The gene targets of core DE miRNAs have functions related to gene expression and general cellular metabolism (P < 0.05) and are enriched in four pathways of lipid metabolism (3-phosphoinositide biosynthesis, 3-phosphoinositide degradation, D-myo-inisitol-5-phosphate metabolism and the superpathway of inositol phosphate compounds). Our results suggest that DE miRNAs in this study might be important regulators of bovine mammary lipogenesis and metabolism. The novel miRNAs identified in this study will further enrich the bovine miRNome repertoire

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9.

Science.gov (United States)

Sternberg, Samuel H; Redding, Sy; Jinek, Martin; Greene, Eric C; Doudna, Jennifer A

2014-03-06

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9

Science.gov (United States)

Sternberg, Samuel H.; Redding, Sy; Jinek, Martin; Greene, Eric C.; Doudna, Jennifer A.

2014-03-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

ITSoneDB: a comprehensive collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences.

Science.gov (United States)

Santamaria, Monica; Fosso, Bruno; Licciulli, Flavio; Balech, Bachir; Larini, Ilaria; Grillo, Giorgio; De Caro, Giorgio; Liuni, Sabino; Pesole, Graziano

2018-01-04

A holistic understanding of environmental communities is the new challenge of metagenomics. Accordingly, the amplicon-based or metabarcoding approach, largely applied to investigate bacterial microbiomes, is moving to the eukaryotic world too. Indeed, the analysis of metabarcoding data may provide a comprehensive assessment of both bacterial and eukaryotic composition in a variety of environments, including human body. In this respect, whereas hypervariable regions of the 16S rRNA are the de facto standard barcode for bacteria, the Internal Transcribed Spacer 1 (ITS1) of ribosomal RNA gene cluster has shown a high potential in discriminating eukaryotes at deep taxonomic levels. As metabarcoding data analysis rely on the availability of a well-curated barcode reference resource, a comprehensive collection of ITS1 sequences supplied with robust taxonomies, is highly needed. To address this issue, we created ITSoneDB (available at http://itsonedb.cloud.ba.infn.it/) which in its current version hosts 985 240 ITS1 sequences spanning over 134 000 eukaryotic species. Each ITS1 is mapped on the NCBI reference taxonomy with its start and end positions precisely annotated. ITSoneDB has been developed in agreement to the FAIR guidelines by enabling the users to query and download its content through a simple web-interface and access relevant metadata by cross-linking to European Nucleotide Archive. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A short TE gradient-echo sequence using asymmetric sampling

International Nuclear Information System (INIS)

Fujita, Norihiko; Harada, Kohshi; Sakurai, Kosuke; Nakanishi, Katsuyuki; Kim, Shyogen; Kozuka, Takahiro

1990-01-01

We have developed a gradient-echo pulse sequence with a short TE less than 4 msec using a data set of asymmetric off-center sampling with a broad bandwidth. The use of such a short TE significantly reduces T 2 * dephasing effect even in a two-dimensional mode, and by collecting an off-center echo, motion-induced phase dispersion is also considerably decreased. High immunity of this sequence to these dephasing effects permits clear visualization of anatomical details near the skull base where large local field inhomogeneities and rapid blood flow such as in the internal carotid artery are present. (author)

Complete genome sequence of the aerobic, heterotroph Marinithermus hydrothermalis type strain (T1T) from a deep-sea hydrothermal vent chimney

Energy Technology Data Exchange (ETDEWEB)

Copeland, A [U.S. Department of Energy, Joint Genome Institute; Gu, Wei [U.S. Department of Energy, Joint Genome Institute; Yasawong, Montri [HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany; Lapidus, Alla L. [U.S. Department of Energy, Joint Genome Institute; Lucas, Susan [U.S. Department of Energy, Joint Genome Institute; Deshpande, Shweta [U.S. Department of Energy, Joint Genome Institute; Pagani, Ioanna [U.S. Department of Energy, Joint Genome Institute; Tapia, Roxanne [Los Alamos National Laboratory (LANL); Cheng, Jan-Fang [U.S. Department of Energy, Joint Genome Institute; Goodwin, Lynne A. [Los Alamos National Laboratory (LANL); Pitluck, Sam [U.S. Department of Energy, Joint Genome Institute; Liolios, Konstantinos [U.S. Department of Energy, Joint Genome Institute; Ivanova, N [U.S. Department of Energy, Joint Genome Institute; Mavromatis, K [U.S. Department of Energy, Joint Genome Institute; Mikhailova, Natalia [U.S. Department of Energy, Joint Genome Institute; Pati, Amrita [U.S. Department of Energy, Joint Genome Institute; Chen, Amy [U.S. Department of Energy, Joint Genome Institute; Palaniappan, Krishna [U.S. Department of Energy, Joint Genome Institute; Land, Miriam L [ORNL; Pan, Chongle [ORNL; Brambilla, Evelyne-Marie [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Rohde, Manfred [HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany; Tindall, Brian [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Sikorski, Johannes [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Goker, Markus [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Detter, J. Chris [U.S. Department of Energy, Joint Genome Institute; Bristow, James [U.S. Department of Energy, Joint Genome Institute; Eisen, Jonathan [U.S. Department of Energy, Joint Genome Institute; Markowitz, Victor [U.S. Department of Energy, Joint Genome Institute; Hugenholtz, Philip [U.S. Department of Energy, Joint Genome Institute; Kyrpides, Nikos C [U.S. Department of Energy, Joint Genome Institute; Klenk, Hans-Peter [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Woyke, Tanja [U.S. Department of Energy, Joint Genome Institute

2012-01-01

Marinithermus hydrothermalis Sako et al. 2003 is the type species of the monotypic genus Marinithermus. M. hydrothermalis T1 T was the first isolate within the phylum ThermusDeinococcus to exhibit optimal growth under a salinity equivalent to that of sea water and to have an absolute requirement for NaCl for growth. M. hydrothermalis T1 T is of interest because it may provide a new insight into the ecological significance of the aerobic, thermophilic decomposers in the circulation of organic compounds in deep-sea hydrothermal vent ecosystems. This is the first completed genome sequence of a member of the genus Marinithermus and the seventh sequence from the family Thermaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,269,167 bp long genome with its 2,251 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Complete genome sequence of the aerobic, heterotroph Marinithermus hydrothermalis type strain (T1(T)) from a deep-sea hydrothermal vent chimney.

Science.gov (United States)

Copeland, Alex; Gu, Wei; Yasawong, Montri; Lapidus, Alla; Lucas, Susan; Deshpande, Shweta; Pagani, Ioanna; Tapia, Roxanne; Cheng, Jan-Fang; Goodwin, Lynne A; Pitluck, Sam; Liolios, Konstantinos; Ivanova, Natalia; Mavromatis, Konstantinos; Mikhailova, Natalia; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Pan, Chongle; Brambilla, Evelyne-Marie; Rohde, Manfred; Tindall, Brian J; Sikorski, Johannes; Göker, Markus; Detter, John C; Bristow, James; Eisen, Jonathan A; Markowitz, Victor; Hugenholtz, Philip; Kyrpides, Nikos C; Klenk, Hans-Peter; Woyke, Tanja

2012-03-19

Marinithermus hydrothermalis Sako et al. 2003 is the type species of the monotypic genus Marinithermus. M. hydrothermalis T1(T) was the first isolate within the phylum "Thermus-Deinococcus" to exhibit optimal growth under a salinity equivalent to that of sea water and to have an absolute requirement for NaCl for growth. M. hydrothermalis T1(T) is of interest because it may provide a new insight into the ecological significance of the aerobic, thermophilic decomposers in the circulation of organic compounds in deep-sea hydrothermal vent ecosystems. This is the first completed genome sequence of a member of the genus Marinithermus and the seventh sequence from the family Thermaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,269,167 bp long genome with its 2,251 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

Science.gov (United States)

Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

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

Science.gov (United States)

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.

Sequence-specific inhibition of Dicer measured with a force-based microarray for RNA ligands.

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Limmer, Katja; Aschenbrenner, Daniela; Gaub, Hermann E

2013-04-01

Malfunction of protein translation causes many severe diseases, and suitable correction strategies may become the basis of effective therapies. One major regulatory element of protein translation is the nuclease Dicer that cuts double-stranded RNA independently of the sequence into pieces of 19-22 base pairs starting the RNA interference pathway and activating miRNAs. Inhibiting Dicer is not desirable owing to its multifunctional influence on the cell's gene regulation. Blocking specific RNA sequences by small-molecule binding, however, is a promising approach to affect the cell's condition in a controlled manner. A label-free assay for the screening of site-specific interference of small molecules with Dicer activity is thus needed. We used the Molecular Force Assay (MFA), recently developed in our lab, to measure the activity of Dicer. As a model system, we used an RNA sequence that forms an aptamer-binding site for paromomycin, a 615-dalton aminoglycoside. We show that Dicer activity is modulated as a function of concentration and incubation time: the addition of paromomycin leads to a decrease of Dicer activity according to the amount of ligand. The measured dissociation constant of paromomycin to its aptamer was found to agree well with literature values. The parallel format of the MFA allows a large-scale search and analysis for ligands for any RNA sequence.

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

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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).

Bacterial diversity and biogeography in deep-sea sediments of the South Atlantic Ocean

DEFF Research Database (Denmark)

Schauer, Regina; Bienhold, Christina; Ramette, Alban

2010-01-01

in 1051 sequences. Phylotypes affiliated with Gammaproteobacteria, Deltaproteobacteria and Acidobacteria were present in all three basins. The distribution of these shared phylotypes seemed to be influenced neither by the Walvis Ridge nor by different deep water masses, suggesting a high dispersal......Microbial biogeographic patterns in the deep sea depend on the ability of microorganisms to disperse. One possible limitation to microbial dispersal may be the Walvis Ridge that separates the Antarctic Lower Circumpolar Deep Water from the North Atlantic Deep Water. We examined bacterial...... communities in three basins of the eastern South Atlantic Ocean to determine diversity and biogeography of bacterial communities in deep-sea surface sediments. The analysis of 16S ribosomal RNA (rRNA) gene clone libraries in each basin revealed a high diversity, representing 521 phylotypes with 98% identity...

Deep sequencing methods for protein engineering and design.

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Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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Robert C. Edgar

2018-04-01

Full Text Available 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.

A novel RNA sequencing data analysis method for cell line authentication.

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Erik Fasterius

Full Text Available We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

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Ehsaneddin Asgari

Full Text Available We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec to refer to biological sequences in general with protein-vectors (ProtVec for proteins (amino-acid sequences and gene-vectors (GeneVec for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups. Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

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Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

Complete genome sequence of a tomato infecting tomato mottle mosaic virus in New York

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Complete genome sequence of an emerging isolate of tomato mottle mosaic virus (ToMMV) infecting experimental nicotianan benthamiana plants in up-state New York was obtained using small RNA deep sequencing. ToMMV_NY-13 shared 99% sequence identity to ToMMV isolates from Mexico and Florida. Broader d...

Pairwise local structural alignment of RNA sequences with sequence similarity less than 40%

DEFF Research Database (Denmark)

Havgaard, Jakob Hull; Lyngsø, Rune B.; Stormo, Gary D.

2005-01-01

detect two genes with low sequence similarity, where the genes are part of a larger genomic region. Results: Here we present such an approach for pairwise local alignment which is based on FILDALIGN and the Sankoff algorithm for simultaneous structural alignment of multiple sequences. We include...... the ability to conduct mutual scans of two sequences of arbitrary length while searching for common local structural motifs of some maximum length. This drastically reduces the complexity of the algorithm. The scoring scheme includes structural parameters corresponding to those available for free energy....... The structure prediction performance for a family is typically around 0.7 using Matthews correlation coefficient. In case (2), the algorithm is successful at locating RNA families with an average sensitivity of 0.8 and a positive predictive value of 0.9 using a BLAST-like hit selection scheme. Availability...

De novo assembly of human genomes with massively parallel short read sequencing

DEFF Research Database (Denmark)

Li, Ruiqiang; Zhu, Hongmei; Ruan, Jue

2010-01-01

genomes from short read sequences. We successfully assembled both the Asian and African human genome sequences, achieving an N50 contig size of 7.4 and 5.9 kilobases (kb) and scaffold of 446.3 and 61.9 kb, respectively. The development of this de novo short read assembly method creates new opportunities...... for building reference sequences and carrying out accurate analyses of unexplored genomes in a cost-effective way....

LookSeq: a browser-based viewer for deep sequencing data.

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Manske, Heinrich Magnus; Kwiatkowski, Dominic P

2009-11-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an overview of a genomic region to fine details such as heterogeneity within the sample. A specific problem, particularly if the sample is heterogeneous, is how to depict information about structural variation. LookSeq provides a simple graphical representation of paired sequence reads that is more revealing about potential insertions and deletions than are conventional methods.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

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Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

An integrated expression atlas of miRNAs and their promoters in human and mouse

DEFF Research Database (Denmark)

de Rie, Derek; Abugessaisa, Imad; Alam, Tanvir

2017-01-01

MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libr...

Combined sequencing of mRNA and DNA from human embryonic stem cells

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Florian Mertes

2016-06-01

Full Text Available Combined transcriptome and whole genome sequencing of the same ultra-low input sample down to single cells is a rapidly evolving approach for the analysis of rare cells. Besides stem cells, rare cells originating from tissues like tumor or biopsies, circulating tumor cells and cells from early embryonic development are under investigation. Herein we describe a universal method applicable for the analysis of minute amounts of sample material (150 to 200 cells derived from sub-colony structures from human embryonic stem cells. The protocol comprises the combined isolation and separate amplification of poly(A mRNA and whole genome DNA followed by next generation sequencing. Here we present a detailed description of the method developed and an overview of the results obtained for RNA and whole genome sequencing of human embryonic stem cells, sequencing data is available in the Gene Expression Omnibus (GEO database under accession number GSE69471.

Discovery and profiling of novel and conserved microRNAs during flower development in Carya cathayensis via deep sequencing.

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Wang, Zheng Jia; Huang, Jian Qin; Huang, You Jun; Li, Zheng; Zheng, Bing Song

2012-08-01

Hickory (Carya cathayensis Sarg.) is an economically important woody plant in China, but its long juvenile phase delays yield. MicroRNAs (miRNAs) are critical regulators of genes and important for normal plant development and physiology, including flower development. We used Solexa technology to sequence two small RNA libraries from two floral differentiation stages in hickory to identify miRNAs related to flower development. We identified 39 conserved miRNA sequences from 114 loci belonging to 23 families as well as two novel and ten potential novel miRNAs belonging to nine families. Moreover, 35 conserved miRNA*s and two novel miRNA*s were detected. Twenty miRNA sequences from 49 loci belonging to 11 families were differentially expressed; all were up-regulated at the later stage of flower development in hickory. Quantitative real-time PCR of 12 conserved miRNA sequences, five novel miRNA families, and two novel miRNA*s validated that all were expressed during hickory flower development, and the expression patterns were similar to those detected with Solexa sequencing. Finally, a total of 146 targets of the novel and conserved miRNAs were predicted. This study identified a diverse set of miRNAs that were closely related to hickory flower development and that could help in plant floral induction.

Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture