Chromatin Immunoprecipitation (ChIP) Protocol for Low-abundance Embryonic Samples.

PubMed

Rehimi, Rizwan; Bartusel, Michaela; Solinas, Francesca; Altmüller, Janine; Rada-Iglesias, Alvaro

2017-08-29

Chromatin immunoprecipitation (ChIP) is a widely-used technique for mapping the localization of post-translationally modified histones, histone variants, transcription factors, or chromatin-modifying enzymes at a given locus or on a genome-wide scale. The combination of ChIP assays with next-generation sequencing (i.e., ChIP-Seq) is a powerful approach to globally uncover gene regulatory networks and to improve the functional annotation of genomes, especially of non-coding regulatory sequences. ChIP protocols normally require large amounts of cellular material, thus precluding the applicability of this method to investigating rare cell types or small tissue biopsies. In order to make the ChIP assay compatible with the amount of biological material that can typically be obtained in vivo during early vertebrate embryogenesis, we describe here a simplified ChIP protocol in which the number of steps required to complete the assay were reduced to minimize sample loss. This ChIP protocol has been successfully used to investigate different histone modifications in various embryonic chicken and adult mouse tissues using low to medium cell numbers (5 x 10 4 - 5 x 10 5 cells). Importantly, this protocol is compatible with ChIP-seq technology using standard library preparation methods, thus providing global epigenomic maps in highly relevant embryonic tissues.

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

PubMed

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

2018-04-16

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

The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision.

PubMed

Perreault, Andrea A; Venters, Bryan J

2016-12-23

Chromatin immunoprecipitation (ChIP) is an indispensable tool in the fields of epigenetics and gene regulation that isolates specific protein-DNA interactions. ChIP coupled to high throughput sequencing (ChIP-seq) is commonly used to determine the genomic location of proteins that interact with chromatin. However, ChIP-seq is hampered by relatively low mapping resolution of several hundred base pairs and high background signal. The ChIP-exo method is a refined version of ChIP-seq that substantially improves upon both resolution and noise. The key distinction of the ChIP-exo methodology is the incorporation of lambda exonuclease digestion in the library preparation workflow to effectively footprint the left and right 5' DNA borders of the protein-DNA crosslink site. The ChIP-exo libraries are then subjected to high throughput sequencing. The resulting data can be leveraged to provide unique and ultra-high resolution insights into the functional organization of the genome. Here, we describe the ChIP-exo method that we have optimized and streamlined for mammalian systems and next-generation sequencing-by-synthesis platform.

Genome-wide analysis of replication timing by next-generation sequencing with E/L Repli-seq.

PubMed

Marchal, Claire; Sasaki, Takayo; Vera, Daniel; Wilson, Korey; Sima, Jiao; Rivera-Mulia, Juan Carlos; Trevilla-García, Claudia; Nogues, Coralin; Nafie, Ebtesam; Gilbert, David M

2018-05-01

This protocol is an extension to: Nat. Protoc. 6, 870-895 (2014); doi:10.1038/nprot.2011.328; published online 02 June 2011Cycling cells duplicate their DNA content during S phase, following a defined program called replication timing (RT). Early- and late-replicating regions differ in terms of mutation rates, transcriptional activity, chromatin marks and subnuclear position. Moreover, RT is regulated during development and is altered in diseases. Here, we describe E/L Repli-seq, an extension of our Repli-chip protocol. E/L Repli-seq is a rapid, robust and relatively inexpensive protocol for analyzing RT by next-generation sequencing (NGS), allowing genome-wide assessment of how cellular processes are linked to RT. Briefly, cells are pulse-labeled with BrdU, and early and late S-phase fractions are sorted by flow cytometry. Labeled nascent DNA is immunoprecipitated from both fractions and sequenced. Data processing leads to a single bedGraph file containing the ratio of nascent DNA from early versus late S-phase fractions. The results are comparable to those of Repli-chip, with the additional benefits of genome-wide sequence information and an increased dynamic range. We also provide computational pipelines for downstream analyses, for parsing phased genomes using single-nucleotide polymorphisms (SNPs) to analyze RT allelic asynchrony, and for direct comparison to Repli-chip data. This protocol can be performed in up to 3 d before sequencing, and requires basic cellular and molecular biology skills, as well as a basic understanding of Unix and R.

Limitations and possibilities of low cell number ChIP-seq

PubMed Central

2012-01-01

Background Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq) offers high resolution, genome-wide analysis of DNA-protein interactions. However, current standard methods require abundant starting material in the range of 1–20 million cells per immunoprecipitation, and remain a bottleneck to the acquisition of biologically relevant epigenetic data. Using a ChIP-seq protocol optimised for low cell numbers (down to 100,000 cells / IP), we examined the performance of the ChIP-seq technique on a series of decreasing cell numbers. Results We present an enhanced native ChIP-seq method tailored to low cell numbers that represents a 200-fold reduction in input requirements over existing protocols. The protocol was tested over a range of starting cell numbers covering three orders of magnitude, enabling determination of the lower limit of the technique. At low input cell numbers, increased levels of unmapped and duplicate reads reduce the number of unique reads generated, and can drive up sequencing costs and affect sensitivity if ChIP is attempted from too few cells. Conclusions The optimised method presented here considerably reduces the input requirements for performing native ChIP-seq. It extends the applicability of the technique to isolated primary cells and rare cell populations (e.g. biobank samples, stem cells), and in many cases will alleviate the need for cell culture and any associated alteration of epigenetic marks. However, this study highlights a challenge inherent to ChIP-seq from low cell numbers: as cell input numbers fall, levels of unmapped sequence reads and PCR-generated duplicate reads rise. We discuss a number of solutions to overcome the effects of reducing cell number that may aid further improvements to ChIP performance. PMID:23171294

Expression Profiling Smackdown: Human Transcriptome Array HTA 2.0 vs. RNA-Seq

PubMed Central

Palermo, Meghann; Driscoll, Heather; Tighe, Scott; Dragon, Julie; Bond, Jeff; Shukla, Arti; Vangala, Mahesh; Vincent, James; Hunter, Tim

2014-01-01

The advent of both microarray and massively parallel sequencing have revolutionized high-throughput analysis of the human transcriptome. Due to limitations in microarray technology, detecting and quantifying coding transcript isoforms, in addition to non-coding transcripts, has been challenging. As a result, RNA-Seq has been the preferred method for characterizing the full human transcriptome, until now. A new high-resolution array from Affymetrix, GeneChip Human Transcriptome Array 2.0 (HTA 2.0), has been designed to interrogate all transcript isoforms in the human transcriptome with >6 million probes targeting coding transcripts, exon-exon splice junctions, and non-coding transcripts. Here we compare expression results from GeneChip HTA 2.0 and RNA-Seq data using identical RNA extractions from three samples each of healthy human mesothelial cells in culture, LP9-C1, and healthy mesothelial cells treated with asbestos, LP9-A1. For GeneChip HTA 2.0 sample preparation, we chose to compare two target preparation methods, NuGEN Ovation Pico WTA V2 with the Encore Biotin Module versus Affymetrix's GeneChip WT PLUS with the WT Terminal Labeling Kit, on identical RNA extractions from both untreated and treated samples. These same RNA extractions were used for the RNA-Seq library preparation. All analyses were performed in Partek Genomics Suite 6.6. Expression profiles for control and asbestos-treated mesothelial cells prepared with NuGEN versus Affymetrix target preparation methods (GeneChip HTA 2.0) are compared to each other as well as to RNA-Seq results.

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

Chromatin analyses of Zymoseptoria tritici: Methods for chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq).

PubMed

Soyer, Jessica L; Möller, Mareike; Schotanus, Klaas; Connolly, Lanelle R; Galazka, Jonathan M; Freitag, Michael; Stukenbrock, Eva H

2015-06-01

The presence or absence of specific transcription factors, chromatin remodeling machineries, chromatin modification enzymes, post-translational histone modifications and histone variants all play crucial roles in the regulation of pathogenicity genes. Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) provides an important tool to study genome-wide protein-DNA interactions to help understand gene regulation in the context of native chromatin. ChIP-seq is a convenient in vivo technique to identify, map and characterize occupancy of specific DNA fragments with proteins against which specific antibodies exist or which can be epitope-tagged in vivo. We optimized existing ChIP protocols for use in the wheat pathogen Zymoseptoria tritici and closely related sister species. Here, we provide a detailed method, underscoring which aspects of the technique are organism-specific. Library preparation for Illumina sequencing is described, as this is currently the most widely used ChIP-seq method. One approach for the analysis and visualization of representative sequence is described; improved tools for these analyses are constantly being developed. Using ChIP-seq with antibodies against H3K4me2, which is considered a mark for euchromatin or H3K9me3 and H3K27me3, which are considered marks for heterochromatin, the overall distribution of euchromatin and heterochromatin in the genome of Z. tritici can be determined. Our ChIP-seq protocol was also successfully applied to Z. tritici strains with high levels of melanization or aberrant colony morphology, and to different species of the genus (Z. ardabiliae and Z. pseudotritici), suggesting that our technique is robust. The methods described here provide a powerful framework to study new aspects of chromatin biology and gene regulation in this prominent wheat pathogen. Copyright © 2015 Elsevier Inc. All rights reserved.

A comparative study of ChIP-seq sequencing library preparation methods.

PubMed

Sundaram, Arvind Y M; Hughes, Timothy; Biondi, Shea; Bolduc, Nathalie; Bowman, Sarah K; Camilli, Andrew; Chew, Yap C; Couture, Catherine; Farmer, Andrew; Jerome, John P; Lazinski, David W; McUsic, Andrew; Peng, Xu; Shazand, Kamran; Xu, Feng; Lyle, Robert; Gilfillan, Gregor D

2016-10-21

ChIP-seq is the primary technique used to investigate genome-wide protein-DNA interactions. As part of this procedure, immunoprecipitated DNA must undergo "library preparation" to enable subsequent high-throughput sequencing. To facilitate the analysis of biopsy samples and rare cell populations, there has been a recent proliferation of methods allowing sequencing library preparation from low-input DNA amounts. However, little information exists on the relative merits, performance, comparability and biases inherent to these procedures. Notably, recently developed single-cell ChIP procedures employing microfluidics must also employ library preparation reagents to allow downstream sequencing. In this study, seven methods designed for low-input DNA/ChIP-seq sample preparation (Accel-NGS® 2S, Bowman-method, HTML-PCR, SeqPlex™, DNA SMART™, TELP and ThruPLEX®) were performed on five replicates of 1 ng and 0.1 ng input H3K4me3 ChIP material, and compared to a "gold standard" reference PCR-free dataset. The performance of each method was examined for the prevalence of unmappable reads, amplification-derived duplicate reads, reproducibility, and for the sensitivity and specificity of peak calling. We identified consistent high performance in a subset of the tested reagents, which should aid researchers in choosing the most appropriate reagents for their studies. Furthermore, we expect this work to drive future advances by identifying and encouraging use of the most promising methods and reagents. The results may also aid judgements on how comparable are existing datasets that have been prepared with different sample library preparation reagents.

Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis, and Open Problems.

PubMed

Wei, Yingying; Wu, George; Ji, Hongkai

2013-05-01

Mapping genome-wide binding sites of all transcription factors (TFs) in all biological contexts is a critical step toward understanding gene regulation. The state-of-the-art technologies for mapping transcription factor binding sites (TFBSs) couple chromatin immunoprecipitation (ChIP) with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip). These technologies have limitations: they are low-throughput with respect to surveying many TFs. Recent advances in genome-wide chromatin profiling, including development of technologies such as DNase-seq, FAIRE-seq and ChIP-seq for histone modifications, make it possible to predict in vivo TFBSs by analyzing chromatin features at computationally determined DNA motif sites. This promising new approach may allow researchers to monitor the genome-wide binding sites of many TFs simultaneously. In this article, we discuss various experimental design and data analysis issues that arise when applying this approach. Through a systematic analysis of the data from the Encyclopedia Of DNA Elements (ENCODE) project, we compare the predictive power of individual and combinations of chromatin marks using supervised and unsupervised learning methods, and evaluate the value of integrating information from public ChIP and gene expression data. We also highlight the challenges and opportunities for developing novel analytical methods, such as resolving the one-motif-multiple-TF ambiguity and distinguishing functional and non-functional TF binding targets from the predicted binding sites. The online version of this article (doi:10.1007/s12561-012-9066-5) contains supplementary material, which is available to authorized users.

iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data.

PubMed

Yang, Chia-Chun; Andrews, Erik H; Chen, Min-Hsuan; Wang, Wan-Yu; Chen, Jeremy J W; Gerstein, Mark; Liu, Chun-Chi; Cheng, Chao

2016-08-12

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP's output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired. To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server ( http://syslab3.nchu.edu.tw/iTAR/ ) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF. The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the characteristic binding profiles and the density plot of normalized regulatory scores. The iTAR web server is a useful tool in identifying TF target genes from ChIP-seq/ChIP-chip data and discovering biological insights.

Quick genome sequencing of “Candidatus Liberibacter” strains by use of Enrichment-Enlargement-Next generation sequencing (EEN)

USDA-ARS?s Scientific Manuscript database

Members of “Candidatus Liberibacter” are associated with several important plant diseases such as citrus Huanglongbing (HLB) and potato zebra chip (ZC) disease. Inability to culture and low titers in infected hosts have been major obstacles for research on these bacteria. The use of whole genome seq...

Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

PubMed

Mendoza-Parra, Marco-Antonio; Saravaki, Vincent; Cholley, Pierre-Etienne; Blum, Matthias; Billoré, Benjamin; Gronemeyer, Hinrich

2016-01-01

We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from 'AAA' to 'DDD') to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody.  We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBC ( www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label "ChIP-seq grade".

Genome wide approaches to identify protein-DNA interactions.

PubMed

Ma, Tao; Ye, Zhenqing; Wang, Liguo

2018-05-29

Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome-wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Quasispecies Analyses of the HIV-1 Near-full-length Genome With Illumina MiSeq

PubMed Central

Ode, Hirotaka; Matsuda, Masakazu; Matsuoka, Kazuhiro; Hachiya, Atsuko; Hattori, Junko; Kito, Yumiko; Yokomaku, Yoshiyuki; Iwatani, Yasumasa; Sugiura, Wataru

2015-01-01

Human immunodeficiency virus type-1 (HIV-1) exhibits high between-host genetic diversity and within-host heterogeneity, recognized as quasispecies. Because HIV-1 quasispecies fluctuate in terms of multiple factors, such as antiretroviral exposure and host immunity, analyzing the HIV-1 genome is critical for selecting effective antiretroviral therapy and understanding within-host viral coevolution mechanisms. Here, to obtain HIV-1 genome sequence information that includes minority variants, we sought to develop a method for evaluating quasispecies throughout the HIV-1 near-full-length genome using the Illumina MiSeq benchtop deep sequencer. To ensure the reliability of minority mutation detection, we applied an analysis method of sequence read mapping onto a consensus sequence derived from de novo assembly followed by iterative mapping and subsequent unique error correction. Deep sequencing analyses of aHIV-1 clone showed that the analysis method reduced erroneous base prevalence below 1% in each sequence position and discarded only < 1% of all collected nucleotides, maximizing the usage of the collected genome sequences. Further, we designed primer sets to amplify the HIV-1 near-full-length genome from clinical plasma samples. Deep sequencing of 92 samples in combination with the primer sets and our analysis method provided sufficient coverage to identify >1%-frequency sequences throughout the genome. When we evaluated sequences of pol genes from 18 treatment-naïve patients' samples, the deep sequencing results were in agreement with Sanger sequencing and identified numerous additional minority mutations. The results suggest that our deep sequencing method would be suitable for identifying within-host viral population dynamics throughout the genome. PMID:26617593

Multiplexed ChIP-Seq Using Direct Nucleosome Barcoding: A Tool for High-Throughput Chromatin Analysis.

PubMed

Chabbert, Christophe D; Adjalley, Sophie H; Steinmetz, Lars M; Pelechano, Vicent

2018-01-01

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) or microarray hybridization (ChIP-on-chip) are standard methods for the study of transcription factor binding sites and histone chemical modifications. However, these approaches only allow profiling of a single factor or protein modification at a time.In this chapter, we present Bar-ChIP, a higher throughput version of ChIP-Seq that relies on the direct ligation of molecular barcodes to chromatin fragments. Bar-ChIP enables the concurrent profiling of multiple DNA-protein interactions and is therefore amenable to experimental scale-up, without the need for any robotic instrumentation.

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

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition

PubMed Central

Yuan, Chih-Chi; Craske, Madeleine Lisa; Labhart, Paul; Guler, Gulfem D.; Arnott, David; Maile, Tobias M.; Busby, Jennifer; Henry, Chisato; Kelly, Theresa K.; Tindell, Charles A.; Jhunjhunwala, Suchit; Zhao, Feng; Hatton, Charlie; Bryant, Barbara M.

2016-01-01

Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) has been instrumental in inferring the roles of histone post-translational modifications in the regulation of transcription, chromatin compaction and other cellular processes that require modulation of chromatin structure. However, analysis of ChIP-seq data is challenging when the manipulation of a chromatin-modifying enzyme significantly affects global levels of histone post-translational modifications. For example, small molecule inhibition of the methyltransferase EZH2 reduces global levels of histone H3 lysine 27 trimethylation (H3K27me3). However, standard ChIP-seq normalization and analysis methods fail to detect a decrease upon EZH2 inhibitor treatment. We overcome this challenge by employing an alternative normalization approach that is based on the addition of Drosophila melanogaster chromatin and a D. melanogaster-specific antibody into standard ChIP reactions. Specifically, the use of an antibody that exclusively recognizes the D. melanogaster histone variant H2Av enables precipitation of D. melanogaster chromatin as a minor fraction of the total ChIP DNA. The D. melanogaster ChIP-seq tags are used to normalize the human ChIP-seq data from DMSO and EZH2 inhibitor-treated samples. Employing this strategy, a substantial reduction in H3K27me3 signal is now observed in ChIP-seq data from EZH2 inhibitor treated samples. PMID:27875550

An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition.

PubMed

Egan, Brian; Yuan, Chih-Chi; Craske, Madeleine Lisa; Labhart, Paul; Guler, Gulfem D; Arnott, David; Maile, Tobias M; Busby, Jennifer; Henry, Chisato; Kelly, Theresa K; Tindell, Charles A; Jhunjhunwala, Suchit; Zhao, Feng; Hatton, Charlie; Bryant, Barbara M; Classon, Marie; Trojer, Patrick

2016-01-01

Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) has been instrumental in inferring the roles of histone post-translational modifications in the regulation of transcription, chromatin compaction and other cellular processes that require modulation of chromatin structure. However, analysis of ChIP-seq data is challenging when the manipulation of a chromatin-modifying enzyme significantly affects global levels of histone post-translational modifications. For example, small molecule inhibition of the methyltransferase EZH2 reduces global levels of histone H3 lysine 27 trimethylation (H3K27me3). However, standard ChIP-seq normalization and analysis methods fail to detect a decrease upon EZH2 inhibitor treatment. We overcome this challenge by employing an alternative normalization approach that is based on the addition of Drosophila melanogaster chromatin and a D. melanogaster-specific antibody into standard ChIP reactions. Specifically, the use of an antibody that exclusively recognizes the D. melanogaster histone variant H2Av enables precipitation of D. melanogaster chromatin as a minor fraction of the total ChIP DNA. The D. melanogaster ChIP-seq tags are used to normalize the human ChIP-seq data from DMSO and EZH2 inhibitor-treated samples. Employing this strategy, a substantial reduction in H3K27me3 signal is now observed in ChIP-seq data from EZH2 inhibitor treated samples.

Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data.

PubMed

Chung, Dongjun; Kuan, Pei Fen; Li, Bo; Sanalkumar, Rajendran; Liang, Kun; Bresnick, Emery H; Dewey, Colin; Keleş, Sündüz

2011-07-01

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.

A simple and novel method for RNA-seq library preparation of single cell cDNA analysis by hyperactive Tn5 transposase.

PubMed

Brouilette, Scott; Kuersten, Scott; Mein, Charles; Bozek, Monika; Terry, Anna; Dias, Kerith-Rae; Bhaw-Rosun, Leena; Shintani, Yasunori; Coppen, Steven; Ikebe, Chiho; Sawhney, Vinit; Campbell, Niall; Kaneko, Masahiro; Tano, Nobuko; Ishida, Hidekazu; Suzuki, Ken; Yashiro, Kenta

2012-10-01

Deep sequencing of single cell-derived cDNAs offers novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-seq analysis requires multiple steps with consequent sample loss and stochastic variation at each step significantly affecting output. Thus, a simpler and better protocol is desirable. The recently developed hyperactive Tn5-mediated library preparation, which brings high quality libraries, is likely one of the solutions. Here, we tested the applicability of hyperactive Tn5-mediated library preparation to deep sequencing of single cell cDNA, optimized the protocol, and compared it with the conventional method based on sonication. This new technique does not require any expensive or special equipment, which secures wider availability. A library was constructed from only 100 ng of cDNA, which enables the saving of precious specimens. Only a few steps of robust enzymatic reaction resulted in saved time, enabling more specimens to be prepared at once, and with a more reproducible size distribution among the different specimens. The obtained RNA-seq results were comparable to the conventional method. Thus, this Tn5-mediated preparation is applicable for anyone who aims to carry out deep sequencing for single cell cDNAs. Copyright © 2012 Wiley Periodicals, Inc.

ChIP-Seq Analysis for Identifying Genome-Wide Histone Modifications Associated with Stress-Responsive Genes in Plants.

PubMed

Li, Guosheng; Jagadeeswaran, Guru; Mort, Andrew; Sunkar, Ramanjulu

2017-01-01

Histone modifications represent the crux of epigenetic gene regulation essential for most biological processes including abiotic stress responses in plants. Thus, identification of histone modifications at the genome-scale can provide clues for how some genes are 'turned-on' while some others are "turned-off" in response to stress. This chapter details a step-by-step protocol for identifying genome-wide histone modifications associated with stress-responsive gene regulation using chromatin immunoprecipitation (ChIP) followed by sequencing of the DNA (ChIP-seq).

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

PubMed

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.

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

PubMed Central

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

2012-01-01

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

Normalization, bias correction, and peak calling for ChIP-seq

PubMed Central

Diaz, Aaron; Park, Kiyoub; Lim, Daniel A.; Song, Jun S.

2012-01-01

Next-generation sequencing is rapidly transforming our ability to profile the transcriptional, genetic, and epigenetic states of a cell. In particular, sequencing DNA from the immunoprecipitation of protein-DNA complexes (ChIP-seq) and methylated DNA (MeDIP-seq) can reveal the locations of protein binding sites and epigenetic modifications. These approaches contain numerous biases which may significantly influence the interpretation of the resulting data. Rigorous computational methods for detecting and removing such biases are still lacking. Also, multi-sample normalization still remains an important open problem. This theoretical paper systematically characterizes the biases and properties of ChIP-seq data by comparing 62 separate publicly available datasets, using rigorous statistical models and signal processing techniques. Statistical methods for separating ChIP-seq signal from background noise, as well as correcting enrichment test statistics for sequence-dependent and sonication biases, are presented. Our method effectively separates reads into signal and background components prior to normalization, improving the signal-to-noise ratio. Moreover, most peak callers currently use a generic null model which suffers from low specificity at the sensitivity level requisite for detecting subtle, but true, ChIP enrichment. The proposed method of determining a cell type-specific null model, which accounts for cell type-specific biases, is shown to be capable of achieving a lower false discovery rate at a given significance threshold than current methods. PMID:22499706

Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

PubMed Central

Siepel, Adam; Lis, John T.

2012-01-01

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

FUNDAMENTALS OF VITAMIN D HORMONE-REGULATED GENE EXPRESSION

PubMed Central

Pike, J. Wesley; Meyer, Mark B.

2014-01-01

Initial research focused upon several known genetic targets provided early insight into the mechanism of action of the vitamin D hormone (1,25-dihydroxyvitamin D3 (1,25(OH)2D3)). Recently, however, a series of technical advances involving the coupling of chromatin immunoprecipitation (ChIP) to unbiased methodologies that initially involved tiled DNA microarrays (ChIP-chip analysis) and now Next Generation DNA Sequencing techniques (ChIP-Seq analysis) has opened new avenues of research into the mechanisms through which 1,25(OH)2D3 regulates gene expression. In this review, we summarize briefly the results of this early work and then focus on more recent studies in which ChIP-chip and ChIP-seq analyses have been used to explore the mechanisms of 1,25(OH)2D3 action on a genome-wide scale providing specific target genes as examples. The results of this work have advanced our understanding of the mechanisms involved at both genetic and epigenetic levels and have revealed a series of new principles through which the vitamin D hormone functions to control the expression of genes. PMID:24239506

Use of sequence-independent-single-primer-amplification (SISPA) for whole genome sequencing using illumina MiSeq platform for avian influenza virus, Newcastle disease virus, and infectious bronchitis virus

USDA-ARS?s Scientific Manuscript database

Over the past decade, Next Generation Sequencing (NGS) technologies, also called deep sequencing, have continued to evolve, increasing capacity and lower the cost necessary for large genome sequencing projects. The one of the advantage of NGS platforms is the possibility to sequence the samples with...

Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T Cell Receptors in High-risk MYCN-not-amplified Human Neuroblastoma | Office of Cancer Genomics

Cancer.gov

Purpose: High-risk neuroblastoma is an aggressive disease. DNA sequencing studies have revealed a paucity of actionable genomic alterations and a low mutation burden, posing challenges to develop effective novel therapies. We used RNA sequencing (RNA-seq) to investigate the biology of this disease including a focus on tumor-infiltrating lymphocytes (TILs). Experimental Design: We performed deep RNA-seq on pre-treatment diagnostic tumors from 129 high-risk and 21 low- or intermediate-risk patients with neuroblastomas.

Reporting Differences Between Spacecraft Sequence Files

NASA Technical Reports Server (NTRS)

Khanampompan, Teerapat; Gladden, Roy E.; Fisher, Forest W.

2010-01-01

A suite of computer programs, called seq diff suite, reports differences between the products of other computer programs involved in the generation of sequences of commands for spacecraft. These products consist of files of several types: replacement sequence of events (RSOE), DSN keyword file [DKF (wherein DSN signifies Deep Space Network)], spacecraft activities sequence file (SASF), spacecraft sequence file (SSF), and station allocation file (SAF). These products can include line numbers, request identifications, and other pieces of information that are not relevant when generating command sequence products, though these fields can result in the appearance of many changes to the files, particularly when using the UNIX diff command to inspect file differences. The outputs of prior software tools for reporting differences between such products include differences in these non-relevant pieces of information. In contrast, seq diff suite removes the fields containing the irrelevant pieces of information before processing to extract differences, so that only relevant differences are reported. Thus, seq diff suite is especially useful for reporting changes between successive versions of the various products and in particular flagging difference in fields relevant to the sequence command generation and review process.

Full genome virus detection in fecal samples using sensitive nucleic acid preparation, deep sequencing, and a novel iterative sequence classification algorithm.

PubMed

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis.

Full Genome Virus Detection in Fecal Samples Using Sensitive Nucleic Acid Preparation, Deep Sequencing, and a Novel Iterative Sequence Classification Algorithm

PubMed Central

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J.; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis. PMID:24695106

Optimal use of tandem biotin and V5 tags in ChIP assays

PubMed Central

Kolodziej, Katarzyna E; Pourfarzad, Farzin; de Boer, Ernie; Krpic, Sanja; Grosveld, Frank; Strouboulis, John

2009-01-01

Background Chromatin immunoprecipitation (ChIP) assays coupled to genome arrays (Chip-on-chip) or massive parallel sequencing (ChIP-seq) lead to the genome wide identification of binding sites of chromatin associated proteins. However, the highly variable quality of antibodies and the availability of epitopes in crosslinked chromatin can compromise genomic ChIP outcomes. Epitope tags have often been used as more reliable alternatives. In addition, we have employed protein in vivo biotinylation tagging as a very high affinity alternative to antibodies. In this paper we describe the optimization of biotinylation tagging for ChIP and its coupling to a known epitope tag in providing a reliable and efficient alternative to antibodies. Results Using the biotin tagged erythroid transcription factor GATA-1 as example, we describe several optimization steps for the application of the high affinity biotin streptavidin system in ChIP. We find that the omission of SDS during sonication, the use of fish skin gelatin as blocking agent and choice of streptavidin beads can lead to significantly improved ChIP enrichments and lower background compared to antibodies. We also show that the V5 epitope tag performs equally well under the conditions worked out for streptavidin ChIP and that it may suffer less from the effects of formaldehyde crosslinking. Conclusion The combined use of the very high affinity biotin tag with the less sensitive to crosslinking V5 tag provides for a flexible ChIP platform with potential implications in ChIP sequencing outcomes. PMID:19196479

Transcriptomic sequencing reveals a set of unique genes activated by butyrate-induced histone modification

USDA-ARS?s Scientific Manuscript database

Butyrate is a nutritional element with strong epigenetic regulatory activity as an inhibitor of histone deacetylases (HDACs). Based on the analysis of differentially expressed genes induced by butyrate in the bovine epithelial cell using deep RNA-sequencing technology (RNA-seq), a set of unique gen...

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

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

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

Evidence for a persistent microbial seed bank throughout the global ocean

PubMed Central

Gibbons, Sean M.; Caporaso, J. Gregory; Pirrung, Meg; Field, Dawn; Knight, Rob; Gilbert, Jack A.

2013-01-01

Do bacterial taxa demonstrate clear endemism, like macroorganisms, or can one site’s bacterial community recapture the total phylogenetic diversity of the world’s oceans? Here we compare a deep bacterial community characterization from one site in the English Channel (L4-DeepSeq) with 356 datasets from the International Census of Marine Microbes (ICoMM) taken from around the globe (ranging from marine pelagic and sediment samples to sponge-associated environments). At the L4-DeepSeq site, increasing sequencing depth uncovers greater phylogenetic overlap with the global ICoMM data. This site contained 31.7–66.2% of operational taxonomic units identified in a given ICoMM biome. Extrapolation of this overlap suggests that 1.93 × 1011 sequences from the L4 site would capture all ICoMM bacterial phylogenetic diversity. Current technology trends suggest this limit may be attainable within 3 y. These results strongly suggest the marine biosphere maintains a previously undetected, persistent microbial seed bank. PMID:23487761

Parallel factor ChIP provides essential internal control for quantitative differential ChIP-seq.

PubMed

Guertin, Michael J; Cullen, Amy E; Markowetz, Florian; Holding, Andrew N

2018-04-17

A key challenge in quantitative ChIP combined with high-throughput sequencing (ChIP-seq) is the normalization of data in the presence of genome-wide changes in occupancy. Analysis-based normalization methods were developed for transcriptomic data and these are dependent on the underlying assumption that total transcription does not change between conditions. For genome-wide changes in transcription factor (TF) binding, these assumptions do not hold true. The challenges in normalization are confounded by experimental variability during sample preparation, processing and recovery. We present a novel normalization strategy utilizing an internal standard of unchanged peaks for reference. Our method can be readily applied to monitor genome-wide changes by ChIP-seq that are otherwise lost or misrepresented through analytical normalization. We compare our approach to normalization by total read depth and two alternative methods that utilize external experimental controls to study TF binding. We successfully resolve the key challenges in quantitative ChIP-seq analysis and demonstrate its application by monitoring the loss of Estrogen Receptor-alpha (ER) binding upon fulvestrant treatment, ER binding in response to estrodiol, ER mediated change in H4K12 acetylation and profiling ER binding in patient-derived xenographs. This is supported by an adaptable pipeline to normalize and quantify differential TF binding genome-wide and generate metrics for differential binding at individual sites.

ChimerDB 3.0: an enhanced database for fusion genes from cancer transcriptome and literature data mining.

PubMed

Lee, Myunggyo; Lee, Kyubum; Yu, Namhee; Jang, Insu; Choi, Ikjung; Kim, Pora; Jang, Ye Eun; Kim, Byounggun; Kim, Sunkyu; Lee, Byungwook; Kang, Jaewoo; Lee, Sanghyuk

2017-01-04

Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

HSA: a heuristic splice alignment tool.

PubMed

Bu, Jingde; Chi, Xuebin; Jin, Zhong

2013-01-01

RNA-Seq methodology is a revolutionary transcriptomics sequencing technology, which is the representative of Next generation Sequencing (NGS). With the high throughput sequencing of RNA-Seq, we can acquire much more information like differential expression and novel splice variants from deep sequence analysis and data mining. But the short read length brings a great challenge to alignment, especially when the reads span two or more exons. A two steps heuristic splice alignment tool is generated in this investigation. First, map raw reads to reference with unspliced aligner--BWA; second, split initial unmapped reads into three equal short reads (seeds), align each seed to the reference, filter hits, search possible split position of read and extend hits to a complete match. Compare with other splice alignment tools like SOAPsplice and Tophat2, HSA has a better performance in call rate and efficiency, but its results do not as accurate as the other software to some extent. HSA is an effective spliced aligner of RNA-Seq reads mapping, which is available at https://github.com/vlcc/HSA.

Chromatin immunoprecipitation (ChIP) method for non-model fruit flies (Diptera: Tephritidae) and evidence of histone modifications.

PubMed

Nagalingam, Kumaran; Lorenc, Michał T; Manoli, Sahana; Cameron, Stephen L; Clarke, Anthony R; Dudley, Kevin J

2018-01-01

Interactions between DNA and proteins located in the cell nucleus play an important role in controlling physiological processes by specifying, augmenting and regulating context-specific transcription events. Chromatin immunoprecipitation (ChIP) is a widely used methodology to study DNA-protein interactions and has been successfully used in various cell types for over three decades. More recently, by combining ChIP with genomic screening technologies and Next Generation Sequencing (e.g. ChIP-seq), it has become possible to profile DNA-protein interactions (including covalent histone modifications) across entire genomes. However, the applicability of ChIP-chip and ChIP-seq has rarely been extended to non-model species because of a number of technical challenges. Here we report a method that can be used to identify genome wide covalent histone modifications in a group of non-model fruit fly species (Diptera: Tephritidae). The method was developed by testing and refining protocols that have been used in model organisms, including Drosophila melanogaster. We demonstrate that this method is suitable for a group of economically important pest fruit fly species, viz., Bactrocera dorsalis, Ceratitis capitata, Zeugodacus cucurbitae and Bactrocera tryoni. We also report an example ChIP-seq dataset for B. tryoni, providing evidence for histone modifications in the genome of a tephritid fruit fly for the first time. Since tephritids are major agricultural pests globally, this methodology will be a valuable resource to study taxa-specific evolutionary questions and to assist with pest management. It also provides a basis for researchers working with other non-model species to undertake genome wide DNA-protein interaction studies.

Sequence Capture versus Restriction Site Associated DNA Sequencing for Shallow Systematics.

PubMed

Harvey, Michael G; Smith, Brian Tilston; Glenn, Travis C; Faircloth, Brant C; Brumfield, Robb T

2016-09-01

Sequence capture and restriction site associated DNA sequencing (RAD-Seq) are two genomic enrichment strategies for applying next-generation sequencing technologies to systematics studies. At shallow timescales, such as within species, RAD-Seq has been widely adopted among researchers, although there has been little discussion of the potential limitations and benefits of RAD-Seq and sequence capture. We discuss a series of issues that may impact the utility of sequence capture and RAD-Seq data for shallow systematics in non-model species. We review prior studies that used both methods, and investigate differences between the methods by re-analyzing existing RAD-Seq and sequence capture data sets from a Neotropical bird (Xenops minutus). We suggest that the strengths of RAD-Seq data sets for shallow systematics are the wide dispersion of markers across the genome, the relative ease and cost of laboratory work, the deep coverage and read overlap at recovered loci, and the high overall information that results. Sequence capture's benefits include flexibility and repeatability in the genomic regions targeted, success using low-quality samples, more straightforward read orthology assessment, and higher per-locus information content. The utility of a method in systematics, however, rests not only on its performance within a study, but on the comparability of data sets and inferences with those of prior work. In RAD-Seq data sets, comparability is compromised by low overlap of orthologous markers across species and the sensitivity of genetic diversity in a data set to an interaction between the level of natural heterozygosity in the samples examined and the parameters used for orthology assessment. In contrast, sequence capture of conserved genomic regions permits interrogation of the same loci across divergent species, which is preferable for maintaining comparability among data sets and studies for the purpose of drawing general conclusions about the impact of historical processes across biotas. We argue that sequence capture should be given greater attention as a method of obtaining data for studies in shallow systematics and comparative phylogeography. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

PubMed Central

Down, Thomas A.; Rakyan, Vardhman K.; Turner, Daniel J.; Flicek, Paul; Li, Heng; Kulesha, Eugene; Gräf, Stefan; Johnson, Nathan; Herrero, Javier; Tomazou, Eleni M.; Thorne, Natalie P.; Bäckdahl, Liselotte; Herberth, Marlis; Howe, Kevin L.; Jackson, David K.; Miretti, Marcos M.; Marioni, John C.; Birney, Ewan; Hubbard, Tim J. P.; Durbin, Richard; Tavaré, Simon; Beck, Stephan

2009-01-01

DNA methylation is an indispensible epigenetic modification of mammalian genomes. Consequently there is great interest in strategies for genome-wide/whole-genome DNA methylation analysis, and immunoprecipitation-based methods have proven to be a powerful option. Such methods are rapidly shifting the bottleneck from data generation to data analysis, necessitating the development of better analytical tools. Until now, a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling has been the inability to estimate absolute methylation levels. Here we report the development of a novel cross-platform algorithm – Bayesian Tool for Methylation Analysis (Batman) – for analyzing Methylated DNA Immunoprecipitation (MeDIP) profiles generated using arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). The latter is an approach we have developed to elucidate the first high-resolution whole-genome DNA methylation profile (DNA methylome) of any mammalian genome. MeDIP-seq/MeDIP-chip combined with Batman represent robust, quantitative, and cost-effective functional genomic strategies for elucidating the function of DNA methylation. PMID:18612301

FANSe2: a robust and cost-efficient alignment tool for quantitative next-generation sequencing applications.

PubMed

Xiao, Chuan-Le; Mai, Zhi-Biao; Lian, Xin-Lei; Zhong, Jia-Yong; Jin, Jing-Jie; He, Qing-Yu; Zhang, Gong

2014-01-01

Correct and bias-free interpretation of the deep sequencing data is inevitably dependent on the complete mapping of all mappable reads to the reference sequence, especially for quantitative RNA-seq applications. Seed-based algorithms are generally slow but robust, while Burrows-Wheeler Transform (BWT) based algorithms are fast but less robust. To have both advantages, we developed an algorithm FANSe2 with iterative mapping strategy based on the statistics of real-world sequencing error distribution to substantially accelerate the mapping without compromising the accuracy. Its sensitivity and accuracy are higher than the BWT-based algorithms in the tests using both prokaryotic and eukaryotic sequencing datasets. The gene identification results of FANSe2 is experimentally validated, while the previous algorithms have false positives and false negatives. FANSe2 showed remarkably better consistency to the microarray than most other algorithms in terms of gene expression quantifications. We implemented a scalable and almost maintenance-free parallelization method that can utilize the computational power of multiple office computers, a novel feature not present in any other mainstream algorithm. With three normal office computers, we demonstrated that FANSe2 mapped an RNA-seq dataset generated from an entire Illunima HiSeq 2000 flowcell (8 lanes, 608 M reads) to masked human genome within 4.1 hours with higher sensitivity than Bowtie/Bowtie2. FANSe2 thus provides robust accuracy, full indel sensitivity, fast speed, versatile compatibility and economical computational utilization, making it a useful and practical tool for deep sequencing applications. FANSe2 is freely available at http://bioinformatics.jnu.edu.cn/software/fanse2/.

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

PubMed

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.

Single-Cell Sequencing for Drug Discovery and Drug Development.

PubMed

Wu, Hongjin; Wang, Charles; Wu, Shixiu

2017-01-01

Next-generation sequencing (NGS), particularly single-cell sequencing, has revolutionized the scale and scope of genomic and biomedical research. Recent technological advances in NGS and singlecell studies have made the deep whole-genome (DNA-seq), whole epigenome and whole-transcriptome sequencing (RNA-seq) at single-cell level feasible. NGS at the single-cell level expands our view of genome, epigenome and transcriptome and allows the genome, epigenome and transcriptome of any organism to be explored without a priori assumptions and with unprecedented throughput. And it does so with single-nucleotide resolution. NGS is also a very powerful tool for drug discovery and drug development. In this review, we describe the current state of single-cell sequencing techniques, which can provide a new, more powerful and precise approach for analyzing effects of drugs on treated cells and tissues. Our review discusses single-cell whole genome/exome sequencing (scWGS/scWES), single-cell transcriptome sequencing (scRNA-seq), single-cell bisulfite sequencing (scBS), and multiple omics of single-cell sequencing. We also highlight the advantages and challenges of each of these approaches. Finally, we describe, elaborate and speculate the potential applications of single-cell sequencing for drug discovery and drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Genome-wide ChIP-seq mapping and analysis of butyrate-induced H3K9 and H3K27 acetylation and epigenomic landscape alteration in bovine cells

USDA-ARS?s Scientific Manuscript database

Utilizing next-generation sequencing technology, combined with ChIP (Chromatin Immunoprecipitation) technology, we analyzed histone modification (acetylation) induced by butyrate and the large-scale mapping of the epigenomic landscape of normal histone H3 and acetylated histone H3K9 and H3K27. To d...

Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing

PubMed Central

Varela, Ignacio; Fisher, Rosalie; McGranahan, Nicholas; Matthews, Nicholas; Santos, Claudio R; Martinez, Pierre; Phillimore, Benjamin; Begum, Sharmin; Rabinowitz, Adam; Spencer-Dene, Bradley; Gulati, Sakshi; Bates, Paul A; Stamp, Gordon; Pickering, Lisa; Gore, Martin; Nicol, David L; Hazell, Steven; Futreal, P Andrew; Stewart, Aengus; Swanton, Charles

2015-01-01

Clear cell renal carcinomas (ccRCCs) can display intratumor heterogeneity (ITH). We applied multiregion exome sequencing (M-seq) to resolve the genetic architecture and evolutionary histories of ten ccRCCs. Ultra-deep sequencing identified ITH in all cases. We found that 73–75% of identified ccRCC driver aberrations were subclonal, confounding estimates of driver mutation prevalence. ITH increased with the number of biopsies analyzed, without evidence of saturation in most tumors. Chromosome 3p loss and VHL aberrations were the only ubiquitous events. The proportion of C>T transitions at CpG sites increased during tumor progression. M-seq permits the temporal resolution of ccRCC evolution and refines mutational signatures occurring during tumor development. PMID:24487277

SeqReporter: automating next-generation sequencing result interpretation and reporting workflow in a clinical laboratory.

PubMed

Roy, Somak; Durso, Mary Beth; Wald, Abigail; Nikiforov, Yuri E; Nikiforova, Marina N

2014-01-01

A wide repertoire of bioinformatics applications exist for next-generation sequencing data analysis; however, certain requirements of the clinical molecular laboratory limit their use: i) comprehensive report generation, ii) compatibility with existing laboratory information systems and computer operating system, iii) knowledgebase development, iv) quality management, and v) data security. SeqReporter is a web-based application developed using ASP.NET framework version 4.0. The client-side was designed using HTML5, CSS3, and Javascript. The server-side processing (VB.NET) relied on interaction with a customized SQL server 2008 R2 database. Overall, 104 cases (1062 variant calls) were analyzed by SeqReporter. Each variant call was classified into one of five report levels: i) known clinical significance, ii) uncertain clinical significance, iii) pending pathologists' review, iv) synonymous and deep intronic, and v) platform and panel-specific sequence errors. SeqReporter correctly annotated and classified 99.9% (859 of 860) of sequence variants, including 68.7% synonymous single-nucleotide variants, 28.3% nonsynonymous single-nucleotide variants, 1.7% insertions, and 1.3% deletions. One variant of potential clinical significance was re-classified after pathologist review. Laboratory information system-compatible clinical reports were generated automatically. SeqReporter also facilitated quality management activities. SeqReporter is an example of a customized and well-designed informatics solution to optimize and automate the downstream analysis of clinical next-generation sequencing data. We propose it as a model that may envisage the development of a comprehensive clinical informatics solution. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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

PubMed

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.

TEA: the epigenome platform for Arabidopsis methylome study.

PubMed

Su, Sheng-Yao; Chen, Shu-Hwa; Lu, I-Hsuan; Chiang, Yih-Shien; Wang, Yu-Bin; Chen, Pao-Yang; Lin, Chung-Yen

2016-12-22

Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw .

The LAM-PCR Method to Sequence LV Integration Sites.

PubMed

Wang, Wei; Bartholomae, Cynthia C; Gabriel, Richard; Deichmann, Annette; Schmidt, Manfred

2016-01-01

Integrating viral gene transfer vectors are commonly used gene delivery tools in clinical gene therapy trials providing stable integration and continuous gene expression of the transgene in the treated host cell. However, integration of the reverse-transcribed vector DNA into the host genome is a potentially mutagenic event that may directly contribute to unwanted side effects. A comprehensive and accurate analysis of the integration site (IS) repertoire is indispensable to study clonality in transduced cells obtained from patients undergoing gene therapy and to identify potential in vivo selection of affected cell clones. To date, next-generation sequencing (NGS) of vector-genome junctions allows sophisticated studies on the integration repertoire in vitro and in vivo. We have explored the use of the Illumina MiSeq Personal Sequencer platform to sequence vector ISs amplified by non-restrictive linear amplification-mediated PCR (nrLAM-PCR) and LAM-PCR. MiSeq-based high-quality IS sequence retrieval is accomplished by the introduction of a double-barcode strategy that substantially minimizes the frequency of IS sequence collisions compared to the conventionally used single-barcode protocol. Here, we present an updated protocol of (nr)LAM-PCR for the analysis of lentiviral IS using a double-barcode system and followed by deep sequencing using the MiSeq device.

Using RNA-seq and targeted nucleases to identify mechanisms of drug resistance in acute myeloid leukemia.

PubMed

Rathe, Susan K; Moriarity, Branden S; Stoltenberg, Christopher B; Kurata, Morito; Aumann, Natalie K; Rahrmann, Eric P; Bailey, Natashay J; Melrose, Ellen G; Beckmann, Dominic A; Liska, Chase R; Largaespada, David A

2014-08-13

The evolution from microarrays to transcriptome deep-sequencing (RNA-seq) and from RNA interference to gene knockouts using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and Transcription Activator-Like Effector Nucleases (TALENs) has provided a new experimental partnership for identifying and quantifying the effects of gene changes on drug resistance. Here we describe the results from deep-sequencing of RNA derived from two cytarabine (Ara-C) resistance acute myeloid leukemia (AML) cell lines, and present CRISPR and TALEN based methods for accomplishing complete gene knockout (KO) in AML cells. We found protein modifying loss-of-function mutations in Dck in both Ara-C resistant cell lines. CRISPR and TALEN-based KO of Dck dramatically increased the IC₅₀ of Ara-C and introduction of a DCK overexpression vector into Dck KO clones resulted in a significant increase in Ara-C sensitivity. This effort demonstrates the power of using transcriptome analysis and CRISPR/TALEN-based KOs to identify and verify genes associated with drug resistance.

GWIPS-viz: development of a ribo-seq genome browser

PubMed Central

Michel, Audrey M.; Fox, Gearoid; M. Kiran, Anmol; De Bo, Christof; O’Connor, Patrick B. F.; Heaphy, Stephen M.; Mullan, James P. A.; Donohue, Claire A.; Higgins, Desmond G.; Baranov, Pavel V.

2014-01-01

We describe the development of GWIPS-viz (http://gwips.ucc.ie), an online genome browser for viewing ribosome profiling data. Ribosome profiling (ribo-seq) is a recently developed technique that provides genome-wide information on protein synthesis (GWIPS) in vivo. It is based on the deep sequencing of ribosome-protected messenger RNA (mRNA) fragments, which allows the ribosome density along all mRNA transcripts present in the cell to be quantified. Since its inception, ribo-seq has been carried out in a number of eukaryotic and prokaryotic organisms. Owing to the increasing interest in ribo-seq, there is a pertinent demand for a dedicated ribo-seq genome browser. GWIPS-viz is based on The University of California Santa Cruz (UCSC) Genome Browser. Ribo-seq tracks, coupled with mRNA-seq tracks, are currently available for several genomes: human, mouse, zebrafish, nematode, yeast, bacteria (Escherichia coli K12, Bacillus subtilis), human cytomegalovirus and bacteriophage lambda. Our objective is to continue incorporating published ribo-seq data sets so that the wider community can readily view ribosome profiling information from multiple studies without the need to carry out computational processing. PMID:24185699

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

PubMed

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.

Analysis of ChIP-seq Data in R/Bioconductor.

PubMed

de Santiago, Ines; Carroll, Thomas

2018-01-01

The development of novel high-throughput sequencing methods for ChIP (chromatin immunoprecipitation) has provided a very powerful tool to study gene regulation in multiple conditions at unprecedented resolution and scale. Proactive quality-control and appropriate data analysis techniques are of critical importance to extract the most meaningful results from the data. Over the last years, an array of R/Bioconductor tools has been developed allowing researchers to process and analyze ChIP-seq data. This chapter provides an overview of the methods available to analyze ChIP-seq data based primarily on software packages from the open-source Bioconductor project. Protocols described in this chapter cover basic steps including data alignment, peak calling, quality control and data visualization, as well as more complex methods such as the identification of differentially bound regions and functional analyses to annotate regulatory regions. The steps in the data analysis process were demonstrated on publicly available data sets and will serve as a demonstration of the computational procedures routinely used for the analysis of ChIP-seq data in R/Bioconductor, from which readers can construct their own analysis pipelines.

Misconceptions on Missing Data in RAD-seq Phylogenetics with a Deep-scale Example from Flowering Plants.

PubMed

Eaton, Deren A R; Spriggs, Elizabeth L; Park, Brian; Donoghue, Michael J

2017-05-01

Restriction-site associated DNA (RAD) sequencing and related methods rely on the conservation of enzyme recognition sites to isolate homologous DNA fragments for sequencing, with the consequence that mutations disrupting these sites lead to missing information. There is thus a clear expectation for how missing data should be distributed, with fewer loci recovered between more distantly related samples. This observation has led to a related expectation: that RAD-seq data are insufficiently informative for resolving deeper scale phylogenetic relationships. Here we investigate the relationship between missing information among samples at the tips of a tree and information at edges within it. We re-analyze and review the distribution of missing data across ten RAD-seq data sets and carry out simulations to determine expected patterns of missing information. We also present new empirical results for the angiosperm clade Viburnum (Adoxaceae, with a crown age >50 Ma) for which we examine phylogenetic information at different depths in the tree and with varied sequencing effort. The total number of loci, the proportion that are shared, and phylogenetic informativeness varied dramatically across the examined RAD-seq data sets. Insufficient or uneven sequencing coverage accounted for similar proportions of missing data as dropout from mutation-disruption. Simulations reveal that mutation-disruption, which results in phylogenetically distributed missing data, can be distinguished from the more stochastic patterns of missing data caused by low sequencing coverage. In Viburnum, doubling sequencing coverage nearly doubled the number of parsimony informative sites, and increased by >10X the number of loci with data shared across >40 taxa. Our analysis leads to a set of practical recommendations for maximizing phylogenetic information in RAD-seq studies. [hierarchical redundancy; phylogenetic informativeness; quartet informativeness; Restriction-site associated DNA (RAD) sequencing; sequencing coverage; Viburnum.]. © The authors 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Characteristics of microbial community functional structure of a biological coking wastewater treatment system.

PubMed

Joshi, Dev Raj; Zhang, Yu; Zhang, Hong; Gao, Yingxin; Yang, Min

2018-01-01

Nitrogenous heterocyclic compounds are key pollutants in coking wastewater; however, the functional potential of microbial communities for biodegradation of such contaminants during biological treatment is still elusive. Herein, a high throughput functional gene array (GeoChip 5.0) in combination with Illumina HiSeq2500 sequencing was used to compare and characterize the microbial community functional structure in a long run (500days) bench scale bioreactor treating coking wastewater, with a control system treating synthetic wastewater. Despite the inhibitory toxic pollutants, GeoChip 5.0 detected almost all key functional gene (average 61,940 genes) categories in the coking wastewater sludge. With higher abundance, aromatic ring cleavage dioxygenase genes including multi ring1,2diox; one ring2,3diox; catechol represented significant functional potential for degradation of aromatic pollutants which was further confirmed by Illumina HiSeq2500 analysis results. Response ratio analysis revealed that three nitrogenous compound degrading genes- nbzA (nitro-aromatics), tdnB (aniline), and scnABC (thiocyanate) were unique for coking wastewater treatment, which might be strong cause to increase ammonia level during the aerobic process. Additionally, HiSeq2500 elucidated carbozole and isoquinoline degradation genes in the system. These findings expanded our understanding on functional potential of microbial communities to remove organic nitrogenous pollutants; hence it will be useful in optimization strategies for biological treatment of coking wastewater. Copyright © 2017. Published by Elsevier B.V.

Long Non-Coding RNA and Alternative Splicing Modulations in Parkinson's Leukocytes Identified by RNA Sequencing

PubMed Central

Soreq, Lilach; Guffanti, Alessandro; Salomonis, Nathan; Simchovitz, Alon; Israel, Zvi; Bergman, Hagai; Soreq, Hermona

2014-01-01

The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinson's disease (PD) patients' leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5′-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases. PMID:24651478

A non-parametric peak calling algorithm for DamID-Seq.

PubMed

Li, Renhua; Hempel, Leonie U; Jiang, Tingbo

2015-01-01

Protein-DNA interactions play a significant role in gene regulation and expression. In order to identify transcription factor binding sites (TFBS) of double sex (DSX)-an important transcription factor in sex determination, we applied the DNA adenine methylation identification (DamID) technology to the fat body tissue of Drosophila, followed by deep sequencing (DamID-Seq). One feature of DamID-Seq data is that induced adenine methylation signals are not assured to be symmetrically distributed at TFBS, which renders the existing peak calling algorithms for ChIP-Seq, including SPP and MACS, inappropriate for DamID-Seq data. This challenged us to develop a new algorithm for peak calling. A challenge in peaking calling based on sequence data is estimating the averaged behavior of background signals. We applied a bootstrap resampling method to short sequence reads in the control (Dam only). After data quality check and mapping reads to a reference genome, the peaking calling procedure compromises the following steps: 1) reads resampling; 2) reads scaling (normalization) and computing signal-to-noise fold changes; 3) filtering; 4) Calling peaks based on a statistically significant threshold. This is a non-parametric method for peak calling (NPPC). We also used irreproducible discovery rate (IDR) analysis, as well as ChIP-Seq data to compare the peaks called by the NPPC. We identified approximately 6,000 peaks for DSX, which point to 1,225 genes related to the fat body tissue difference between female and male Drosophila. Statistical evidence from IDR analysis indicated that these peaks are reproducible across biological replicates. In addition, these peaks are comparable to those identified by use of ChIP-Seq on S2 cells, in terms of peak number, location, and peaks width.

RNA-Seq analysis to capture the transcriptome landscape of a single cell

PubMed Central

Tang, Fuchou; Barbacioru, Catalin; Nordman, Ellen; Xu, Nanlan; Bashkirov, Vladimir I; Lao, Kaiqin; Surani, M. Azim

2013-01-01

We describe here a protocol for digital transcriptome analysis in a single mouse blastomere using a deep sequencing approach. An individual blastomere was first isolated and put into lysate buffer by mouth pipette. Reverse transcription was then performed directly on the whole cell lysate. After this, the free primers were removed by Exonuclease I and a poly(A) tail was added to the 3′ end of the first-strand cDNA by Terminal Deoxynucleotidyl Transferase. Then the single cell cDNAs were amplified by 20 plus 9 cycles of PCR. Then 100-200 ng of these amplified cDNAs were used to construct a sequencing library. The sequencing library can be used for deep sequencing using the SOLiD system. Compared with the cDNA microarray technique, our assay can capture up to 75% more genes expressed in early embryos. The protocol can generate deep sequencing libraries within 6 days for 16 single cell samples. PMID:20203668

Breaking the 1000-gene barrier for Mimivirus using ultra-deep genome and transcriptome sequencing.

PubMed

Legendre, Matthieu; Santini, Sébastien; Rico, Alain; Abergel, Chantal; Claverie, Jean-Michel

2011-03-04

Mimivirus, a giant dsDNA virus infecting Acanthamoeba, is the prototype of the mimiviridae family, the latest addition to the family of the nucleocytoplasmic large DNA viruses (NCLDVs). Its 1.2 Mb-genome was initially predicted to encode 917 genes. A subsequent RNA-Seq analysis precisely mapped many transcript boundaries and identified 75 new genes. We now report a much deeper analysis using the SOLiD™ technology combining RNA-Seq of the Mimivirus transcriptome during the infectious cycle (202.4 Million reads), and a complete genome re-sequencing (45.3 Million reads). This study corrected the genome sequence and identified several single nucleotide polymorphisms. Our results also provided clear evidence of previously overlooked transcription units, including an important RNA polymerase subunit distantly related to Euryarchea homologues. The total Mimivirus gene count is now 1018, 11% greater than the original annotation. This study highlights the huge progress brought about by ultra-deep sequencing for the comprehensive annotation of virus genomes, opening the door to a complete one-nucleotide resolution level description of their transcriptional activity, and to the realistic modeling of the viral genome expression at the ultimate molecular level. This work also illustrates the need to go beyond bioinformatics-only approaches for the annotation of short protein and non-coding genes in viral genomes.

Complex and dynamic landscape of RNA polyadenylation revealed by PAS-Seq

PubMed Central

Shepard, Peter J.; Choi, Eun-A; Lu, Jente; Flanagan, Lisa A.; Hertel, Klemens J.; Shi, Yongsheng

2011-01-01

Alternative polyadenylation (APA) of mRNAs has emerged as an important mechanism for post-transcriptional gene regulation in higher eukaryotes. Although microarrays have recently been used to characterize APA globally, they have a number of serious limitations that prevents comprehensive and highly quantitative analysis. To better characterize APA and its regulation, we have developed a deep sequencing-based method called Poly(A) Site Sequencing (PAS-Seq) for quantitatively profiling RNA polyadenylation at the transcriptome level. PAS-Seq not only accurately and comprehensively identifies poly(A) junctions in mRNAs and noncoding RNAs, but also provides quantitative information on the relative abundance of polyadenylated RNAs. PAS-Seq analyses of human and mouse transcriptomes showed that 40%–50% of all expressed genes produce alternatively polyadenylated mRNAs. Furthermore, our study detected evolutionarily conserved polyadenylation of histone mRNAs and revealed novel features of mitochondrial RNA polyadenylation. Finally, PAS-Seq analyses of mouse embryonic stem (ES) cells, neural stem/progenitor (NSP) cells, and neurons not only identified more poly(A) sites than what was found in the entire mouse EST database, but also detected significant changes in the global APA profile that lead to lengthening of 3′ untranslated regions (UTR) in many mRNAs during stem cell differentiation. Together, our PAS-Seq analyses revealed a complex landscape of RNA polyadenylation in mammalian cells and the dynamic regulation of APA during stem cell differentiation. PMID:21343387

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma.

PubMed

Wrzeszczynski, Kazimierz O; Frank, Mayu O; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A; Moore Vogel, Julia L; Bruce, Jeffrey N; Lassman, Andrew B; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V; Zody, Michael C; Jobanputra, Vaidehi; Royyuru, Ajay K; Darnell, Robert B

2017-08-01

To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. NCT02725684.

Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome.

PubMed

Bush, Stephen J; Muriuki, Charity; McCulloch, Mary E B; Farquhar, Iseabail L; Clark, Emily L; Hume, David A

2018-04-24

mRNA-like long non-coding RNAs (lncRNAs) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. Thus, in many cases lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNAs, we compared de novo assembled lncRNAs derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNAs assembled in cattle and human. We then combined the novel lncRNAs with the sheep transcriptional atlas to identify co-regulated sets of protein-coding and non-coding loci. Few lncRNAs could be reproducibly assembled from a single dataset, even with deep sequencing of the same tissues from multiple animals. Furthermore, there was little sequence overlap between lncRNAs that were assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNAs to identify a consensus set of ruminant lncRNAs and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. In sheep, 20 to 30% of lncRNAs were located close to protein-coding genes with which they are strongly co-expressed, which is consistent with the evolutionary origin of some ncRNAs in enhancer sequences. Nevertheless, most of the lncRNAs are not co-expressed with neighbouring protein-coding genes. Alongside substantially expanding the ruminant lncRNA repertoire, the outcomes of our analysis demonstrate that stochastic sampling can be partly overcome by combining RNA-seq datasets from related species. This has practical implications for the future discovery of lncRNAs in other species.

Picking ChIP-seq peak detectors for analyzing chromatin modification experiments

PubMed Central

Micsinai, Mariann; Parisi, Fabio; Strino, Francesco; Asp, Patrik; Dynlacht, Brian D.; Kluger, Yuval

2012-01-01

Numerous algorithms have been developed to analyze ChIP-Seq data. However, the complexity of analyzing diverse patterns of ChIP-Seq signals, especially for epigenetic marks, still calls for the development of new algorithms and objective comparisons of existing methods. We developed Qeseq, an algorithm to detect regions of increased ChIP read density relative to background. Qeseq employs critical novel elements, such as iterative recalibration and neighbor joining of reads to identify enriched regions of any length. To objectively assess its performance relative to other 14 ChIP-Seq peak finders, we designed a novel protocol based on Validation Discriminant Analysis (VDA) to optimally select validation sites and generated two validation datasets, which are the most comprehensive to date for algorithmic benchmarking of key epigenetic marks. In addition, we systematically explored a total of 315 diverse parameter configurations from these algorithms and found that typically optimal parameters in one dataset do not generalize to other datasets. Nevertheless, default parameters show the most stable performance, suggesting that they should be used. This study also provides a reproducible and generalizable methodology for unbiased comparative analysis of high-throughput sequencing tools that can facilitate future algorithmic development. PMID:22307239

Picking ChIP-seq peak detectors for analyzing chromatin modification experiments.

PubMed

Micsinai, Mariann; Parisi, Fabio; Strino, Francesco; Asp, Patrik; Dynlacht, Brian D; Kluger, Yuval

2012-05-01

Numerous algorithms have been developed to analyze ChIP-Seq data. However, the complexity of analyzing diverse patterns of ChIP-Seq signals, especially for epigenetic marks, still calls for the development of new algorithms and objective comparisons of existing methods. We developed Qeseq, an algorithm to detect regions of increased ChIP read density relative to background. Qeseq employs critical novel elements, such as iterative recalibration and neighbor joining of reads to identify enriched regions of any length. To objectively assess its performance relative to other 14 ChIP-Seq peak finders, we designed a novel protocol based on Validation Discriminant Analysis (VDA) to optimally select validation sites and generated two validation datasets, which are the most comprehensive to date for algorithmic benchmarking of key epigenetic marks. In addition, we systematically explored a total of 315 diverse parameter configurations from these algorithms and found that typically optimal parameters in one dataset do not generalize to other datasets. Nevertheless, default parameters show the most stable performance, suggesting that they should be used. This study also provides a reproducible and generalizable methodology for unbiased comparative analysis of high-throughput sequencing tools that can facilitate future algorithmic development.

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

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

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

Impact of sequencing depth in ChIP-seq experiments

PubMed Central

Jung, Youngsook L.; Luquette, Lovelace J.; Ho, Joshua W.K.; Ferrari, Francesco; Tolstorukov, Michael; Minoda, Aki; Issner, Robbyn; Epstein, Charles B.; Karpen, Gary H.; Kuroda, Mitzi I.; Park, Peter J.

2014-01-01

In a chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiment, an important consideration in experimental design is the minimum number of sequenced reads required to obtain statistically significant results. We present an extensive evaluation of the impact of sequencing depth on identification of enriched regions for key histone modifications (H3K4me3, H3K36me3, H3K27me3 and H3K9me2/me3) using deep-sequenced datasets in human and fly. We propose to define sufficient sequencing depth as the number of reads at which detected enrichment regions increase <1% for an additional million reads. Although the required depth depends on the nature of the mark and the state of the cell in each experiment, we observe that sufficient depth is often reached at <20 million reads for fly. For human, there are no clear saturation points for the examined datasets, but our analysis suggests 40–50 million reads as a practical minimum for most marks. We also devise a mathematical model to estimate the sufficient depth and total genomic coverage of a mark. Lastly, we find that the five algorithms tested do not agree well for broad enrichment profiles, especially at lower depths. Our findings suggest that sufficient sequencing depth and an appropriate peak-calling algorithm are essential for ensuring robustness of conclusions derived from ChIP-seq data. PMID:24598259

Utility of next-generation RNA-sequencing in identifying chimeric transcription involving human endogenous retroviruses.

PubMed

Sokol, Martin; Jessen, Karen Margrethe; Pedersen, Finn Skou

2016-01-01

Several studies have shown that human endogenous retroviruses and endogenous retrovirus-like repeats (here collectively HERVs) impose direct regulation on human genes through enhancer and promoter motifs present in their long terminal repeats (LTRs). Although chimeric transcription in which novel gene isoforms containing retroviral and human sequence are transcribed from viral promoters are commonly associated with disease, regulation by HERVs is beneficial in other settings; for example, in human testis chimeric isoforms of TP63 induced by an ERV9 LTR protect the male germ line upon DNA damage by inducing apoptosis, whereas in the human globin locus the γ- and β-globin switch during normal hematopoiesis is mediated by complex interactions of an ERV9 LTR and surrounding human sequence. The advent of deep sequencing or next-generation sequencing (NGS) has revolutionized the way researchers solve important scientific questions and develop novel hypotheses in relation to human genome regulation. We recently applied next-generation paired-end RNA-sequencing (RNA-seq) together with chromatin immunoprecipitation with sequencing (ChIP-seq) to examine ERV9 chimeric transcription in human reference cell lines from Encyclopedia of DNA Elements (ENCODE). This led to the discovery of advanced regulation mechanisms by ERV9s and other HERVs across numerous human loci including transcription of large gene-unannotated genomic regions, as well as cooperative regulation by multiple HERVs and non-LTR repeats such as Alu elements. In this article, well-established examples of human gene regulation by HERVs are reviewed followed by a description of paired-end RNA-seq, and its application in identifying chimeric transcription genome-widely. Based on integrative analyses of RNA-seq and ChIP-seq, data we then present novel examples of regulation by ERV9s of tumor suppressor genes CADM2 and SEMA3A, as well as transcription of an unannotated region. Taken together, this article highlights the high suitability of contemporary sequencing methods in future analyses of human biology in relation to evolutionary acquired retroviruses in the human genome. © 2016 APMIS. Published by John Wiley & Sons Ltd.

In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data

NASA Astrophysics Data System (ADS)

Cai, Lei; Yuan, Wei; Zhang, Zhou; He, Lin; Chou, Kuo-Chen

2016-11-01

Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy. Combining different callers does increase reliability of candidates, but narrows the list down to very limited range of tumor read depth and variant allele frequency. Calling SNV on UDT-Seq data, which were of much higher read-depth, discovered additional true-positive variations, despite an even more tremendous growth in false positive predictions. Our findings not only provide valuable benchmark for state-of-the-art SNV calling methods, but also shed light on the access to more accurate SNV identification in the future.

Is this the right normalization? A diagnostic tool for ChIP-seq normalization.

PubMed

Angelini, Claudia; Heller, Ruth; Volkinshtein, Rita; Yekutieli, Daniel

2015-05-09

Chip-seq experiments are becoming a standard approach for genome-wide profiling protein-DNA interactions, such as detecting transcription factor binding sites, histone modification marks and RNA Polymerase II occupancy. However, when comparing a ChIP sample versus a control sample, such as Input DNA, normalization procedures have to be applied in order to remove experimental source of biases. Despite the substantial impact that the choice of the normalization method can have on the results of a ChIP-seq data analysis, their assessment is not fully explored in the literature. In particular, there are no diagnostic tools that show whether the applied normalization is indeed appropriate for the data being analyzed. In this work we propose a novel diagnostic tool to examine the appropriateness of the estimated normalization procedure. By plotting the empirical densities of log relative risks in bins of equal read count, along with the estimated normalization constant, after logarithmic transformation, the researcher is able to assess the appropriateness of the estimated normalization constant. We use the diagnostic plot to evaluate the appropriateness of the estimates obtained by CisGenome, NCIS and CCAT on several real data examples. Moreover, we show the impact that the choice of the normalization constant can have on standard tools for peak calling such as MACS or SICER. Finally, we propose a novel procedure for controlling the FDR using sample swapping. This procedure makes use of the estimated normalization constant in order to gain power over the naive choice of constant (used in MACS and SICER), which is the ratio of the total number of reads in the ChIP and Input samples. Linear normalization approaches aim to estimate a scale factor, r, to adjust for different sequencing depths when comparing ChIP versus Input samples. The estimated scaling factor can easily be incorporated in many peak caller algorithms to improve the accuracy of the peak identification. The diagnostic plot proposed in this paper can be used to assess how adequate ChIP/Input normalization constants are, and thus it allows the user to choose the most adequate estimate for the analysis.

Simultaneous and complete genome sequencing of influenza A and B with high coverage by Illumina MiSeq Platform.

PubMed

Rutvisuttinunt, Wiriya; Chinnawirotpisan, Piyawan; Simasathien, Sriluck; Shrestha, Sanjaya K; Yoon, In-Kyu; Klungthong, Chonticha; Fernandez, Stefan

2013-11-01

Active global surveillance and characterization of influenza viruses are essential for better preparation against possible pandemic events. Obtaining comprehensive information about the influenza genome can improve our understanding of the evolution of influenza viruses and emergence of new strains, and improve the accuracy when designing preventive vaccines. This study investigated the use of deep sequencing by the next-generation sequencing (NGS) Illumina MiSeq Platform to obtain complete genome sequence information from influenza virus isolates. The influenza virus isolates were cultured from 6 respiratory acute clinical specimens collected in Thailand and Nepal. DNA libraries obtained from each viral isolate were mixed and all were sequenced simultaneously. Total information of 2.6 Gbases was obtained from a 455±14 K/mm2 density with 95.76% (8,571,655/8,950,724 clusters) of the clusters passing quality control (QC) filters. Approximately 93.7% of all sequences from Read1 and 83.5% from Read2 contained high quality sequences that were ≥Q30, a base calling QC score standard. Alignments analysis identified three seasonal influenza A H3N2 strains, one 2009 pandemic influenza A H1N1 strain and two influenza B strains. The nearly entire genomes of all six virus isolates yielded equal or greater than 600-fold sequence coverage depth. MiSeq Platform identified seasonal influenza A H3N2, 2009 pandemic influenza A H1N1and influenza B in the DNA library mixtures efficiently. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Deep sequencing with intronic capture enables identification of an APC exon 10 inversion in a patient with polyposis.

PubMed

Shirts, Brian H; Salipante, Stephen J; Casadei, Silvia; Ryan, Shawnia; Martin, Judith; Jacobson, Angela; Vlaskin, Tatyana; Koehler, Karen; Livingston, Robert J; King, Mary-Claire; Walsh, Tom; Pritchard, Colin C

2014-10-01

Single-exon inversions have rarely been described in clinical syndromes and are challenging to detect using Sanger sequencing. We report the case of a 40-year-old woman with adenomatous colon polyps too numerous to count and who had a complex inversion spanning the entire exon 10 in APC (the gene encoding for adenomatous polyposis coli), causing exon skipping and resulting in a frameshift and premature protein truncation. In this study, we employed complete APC gene sequencing using high-coverage next-generation sequencing by ColoSeq, analysis with BreakDancer and SLOPE software, and confirmatory transcript analysis. ColoSeq identified a complex small genomic rearrangement consisting of an inversion that results in translational skipping of exon 10 in the APC gene. This mutation would not have been detected by traditional sequencing or gene-dosage methods. We report a case of adenomatous polyposis resulting from a complex single-exon inversion. Our report highlights the benefits of large-scale sequencing methods that capture intronic sequences with high enough depth of coverage-as well as the use of informatics tools-to enable detection of small pathogenic structural rearrangements.

Strand-Specific Analysis of DNA Synthesis and Proteins Association with DNA Replication Forks in Budding Yeast.

PubMed

Yu, Chuanhe; Gan, Haiyun; Zhang, Zhiguo

2018-01-01

DNA replication initiates at DNA replication origins after unwinding of double-strand DNA(dsDNA) by replicative helicase to generate single-stranded DNA (ssDNA) templates for the continuous synthesis of leading-strand and the discontinuous synthesis of lagging-strand. Therefore, methods capable of detecting strand-specific information will likely yield insight into the association of proteins at leading and lagging strand of DNA replication forks and the regulation of leading and lagging strand synthesis during DNA replication. The enrichment and Sequencing of Protein-Associated Nascent DNA (eSPAN), which measure the relative amounts of proteins at nascent leading and lagging strands of DNA replication forks, is a step-wise procedure involving the chromatin immunoprecipitation (ChIP) of a protein of interest followed by the enrichment of protein-associated nascent DNA through BrdU immunoprecipitation. The isolated ssDNA is then subjected to strand-specific sequencing. This method can detect whether a protein is enriched at leading or lagging strand of DNA replication forks. In addition to eSPAN, two other strand-specific methods, (ChIP-ssSeq), which detects potential protein-ssDNA binding and BrdU-IP-ssSeq, which can measure synthesis of both leading and lagging strand, were developed along the way. These methods can provide strand-specific and complementary information about the association of the target protein with DNA replication forks as well as synthesis of leading and lagging strands genome wide. Below, we describe the detailed eSPAN, ChIP-ssSeq, and BrdU-IP-ssSeq protocols.

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

PubMed Central

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

2017-01-01

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

Geoseq: a tool for dissecting deep-sequencing datasets.

PubMed

Gurtowski, James; Cancio, Anthony; Shah, Hardik; Levovitz, Chaya; George, Ajish; Homann, Robert; Sachidanandam, Ravi

2010-10-12

Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a) identify differential isoform expression in mRNA-seq datasets, b) identify miRNAs (microRNAs) in libraries, and identify mature and star sequences in miRNAS and c) to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

Genomic maps of lincRNA occupancy reveal principles of RNA-chromatin interactions

PubMed Central

Chu, Ci; Qu, Kun; Zhong, Franklin; Artandi, Steven E.; Chang, Howard Y.

2011-01-01

SUMMARY Long intergenic noncoding RNAs (lincRNAs) are key regulators of chromatin state, yet the nature and sites of RNA-chromatin interaction are mostly unknown. Here we introduce Chromatin Isolation by RNA Purification (ChIRP), where tiling oligonucleotides retrieve specific lincRNAs with bound protein and DNA sequences, which are enumerated by deep sequencing. ChIRP-seq of three lincRNAs reveal that RNA occupancy sites in the genome are focal, sequence-specific, and numerous. Drosophila roX2 RNA occupies male X-linked gene bodies with increasing tendency toward the 3’ end, peaking at CES sites. Human telomerase RNA TERC occupies telomeres and Wnt pathway genes. HOTAIR lincRNA preferentially occupies a GA-rich DNA motif to nucleate broad domains of Polycomb occupancy and histone H3 lysine 27 trimethylation. HOTAIR occupancy occurs independently of EZH2, suggesting the order of RNA guidance of Polycomb occupancy. ChIRP-seq is generally applicable to illuminate the intersection of RNA and chromatin with newfound precision genome-wide. PMID:21963238

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma

PubMed Central

Wrzeszczynski, Kazimierz O.; Frank, Mayu O.; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A.; Moore Vogel, Julia L.; Bruce, Jeffrey N.; Lassman, Andrew B.; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V.; Zody, Michael C.; Jobanputra, Vaidehi; Royyuru, Ajay K.

2017-01-01

Objective: To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Methods: Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. Results: More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. Conclusions: The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. ClinicalTrials.gov identifier: NCT02725684. PMID:28740869

Development of a High-Throughput Resequencing Array for the Detection of Pathogenic Mutations in Osteogenesis Imperfecta

PubMed Central

Wang, Yao; Cui, Yazhou; Zhou, Xiaoyan; Han, Jinxiang

2015-01-01

Objective Osteogenesis imperfecta (OI) is a rare inherited skeletal disease, characterized by bone fragility and low bone density. The mutations in this disorder have been widely reported to be on various exonal hotspots of the candidate genes, including COL1A1, COL1A2, CRTAP, LEPRE1, and FKBP10, thus creating a great demand for precise genetic tests. However, large genome sizes make the process daunting and the analyses, inefficient and expensive. Therefore, we aimed at developing a fast, accurate, efficient, and cheaper sequencing platform for OI diagnosis; and to this end, use of an advanced array-based technique was proposed. Method A CustomSeq Affymetrix Resequencing Array was established for high-throughput sequencing of five genes simultaneously. Genomic DNA extraction from 13 OI patients and 85 normal controls and amplification using long-range PCR (LR-PCR) were followed by DNA fragmentation and chip hybridization, according to standard Affymetrix protocols. Hybridization signals were determined using GeneChip Sequence Analysis Software (GSEQ). To examine the feasibility, the outcome from new resequencing approach was validated by conventional capillary sequencing method. Result Overall call rates using resequencing array was 96–98% and the agreement between microarray and capillary sequencing was 99.99%. 11 out of 13 OI patients with pathogenic mutations were successfully detected by the chip analysis without adjustment, and one mutation could also be identified using manual visual inspection. Conclusion A high-throughput resequencing array was developed that detects the disease-associated mutations in OI, providing a potential tool to facilitate large-scale genetic screening for OI patients. Through this method, a novel mutation was also found. PMID:25742658

19 CFR 12.39 - Imported articles involving unfair methods of competition or practices.

Code of Federal Regulations, 2011 CFR

2011-04-01

... the authorization or consent of the Government. (e) Importations of semiconductor chip products. (1) In accordance with the Semiconductor Chip Protection Act of 1984 (17 U.S.C. 901 et seq.), if the... imported semiconductor chip products which infringe his rights in such mask work, the owner must obtain a...

Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform

PubMed Central

Van Nostrand, Joy D.; Ning, Daliang; Sun, Bo; Xue, Kai; Liu, Feifei; Deng, Ye; Liang, Yuting; Zhou, Jizhong

2017-01-01

Illumina’s MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1–3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility. PMID:28453559

Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform

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

Wen, Chongqing; Wu, Liyou; Qin, Yujia

Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered,more » the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.« less

Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform

DOE PAGES

Wen, Chongqing; Wu, Liyou; Qin, Yujia; ...

2017-04-28

Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered,more » the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.« less

Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform.

PubMed

Wen, Chongqing; Wu, Liyou; Qin, Yujia; Van Nostrand, Joy D; Ning, Daliang; Sun, Bo; Xue, Kai; Liu, Feifei; Deng, Ye; Liang, Yuting; Zhou, Jizhong

2017-01-01

Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.

Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish

PubMed Central

2010-01-01

Background Systematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE) are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish. Results RNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution. Conclusion This study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host-pathogen interactions and evolutionary history of immunogenetics from fish to mammals. PMID:20707909

ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data.

PubMed

Yang, Jian-Hua; Li, Jun-Hao; Jiang, Shan; Zhou, Hui; Qu, Liang-Hu

2013-01-01

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) represent two classes of important non-coding RNAs in eukaryotes. Although these non-coding RNAs have been implicated in organismal development and in various human diseases, surprisingly little is known about their transcriptional regulation. Recent advances in chromatin immunoprecipitation with next-generation DNA sequencing (ChIP-Seq) have provided methods of detecting transcription factor binding sites (TFBSs) with unprecedented sensitivity. In this study, we describe ChIPBase (http://deepbase.sysu.edu.cn/chipbase/), a novel database that we have developed to facilitate the comprehensive annotation and discovery of transcription factor binding maps and transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. The current release of ChIPBase includes high-throughput sequencing data that were generated by 543 ChIP-Seq experiments in diverse tissues and cell lines from six organisms. By analysing millions of TFBSs, we identified tens of thousands of TF-lncRNA and TF-miRNA regulatory relationships. Furthermore, two web-based servers were developed to annotate and discover transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. In addition, we developed two genome browsers, deepView and genomeView, to provide integrated views of multidimensional data. Moreover, our web implementation supports diverse query types and the exploration of TFs, lncRNAs, miRNAs, gene ontologies and pathways.

PolyA_DB 3 catalogs cleavage and polyadenylation sites identified by deep sequencing in multiple genomes

PubMed Central

Wang, Ruijia; Nambiar, Ram; Zheng, Dinghai

2018-01-01

Abstract PolyA_DB is a database cataloging cleavage and polyadenylation sites (PASs) in several genomes. Previous versions were based mainly on expressed sequence tags (ESTs), which had a limited amount and could lead to inaccurate PAS identification due to the presence of internal A-rich sequences in transcripts. Here, we present an updated version of the database based solely on deep sequencing data. First, PASs are mapped by the 3′ region extraction and deep sequencing (3′READS) method, ensuring unequivocal PAS identification. Second, a large volume of data based on diverse biological samples increases PAS coverage by 3.5-fold over the EST-based version and provides PAS usage information. Third, strand-specific RNA-seq data are used to extend annotated 3′ ends of genes to obtain more thorough annotations of alternative polyadenylation (APA) sites. Fourth, conservation information of PAS across mammals sheds light on significance of APA sites. The database (URL: http://www.polya-db.org/v3) currently holds PASs in human, mouse, rat and chicken, and has links to the UCSC genome browser for further visualization and for integration with other genomic data. PMID:29069441

Genome-wide identification and characterisation of human DNA replication origins by initiation site sequencing (ini-seq)

PubMed Central

Langley, Alexander R.; Gräf, Stefan; Smith, James C.; Krude, Torsten

2016-01-01

Next-generation sequencing has enabled the genome-wide identification of human DNA replication origins. However, different approaches to mapping replication origins, namely (i) sequencing isolated small nascent DNA strands (SNS-seq); (ii) sequencing replication bubbles (bubble-seq) and (iii) sequencing Okazaki fragments (OK-seq), show only limited concordance. To address this controversy, we describe here an independent high-resolution origin mapping technique that we call initiation site sequencing (ini-seq). In this approach, newly replicated DNA is directly labelled with digoxigenin-dUTP near the sites of its initiation in a cell-free system. The labelled DNA is then immunoprecipitated and genomic locations are determined by DNA sequencing. Using this technique we identify >25,000 discrete origin sites at sub-kilobase resolution on the human genome, with high concordance between biological replicates. Most activated origins identified by ini-seq are found at transcriptional start sites and contain G-quadruplex (G4) motifs. They tend to cluster in early-replicating domains, providing a correlation between early replication timing and local density of activated origins. Origins identified by ini-seq show highest concordance with sites identified by SNS-seq, followed by OK-seq and bubble-seq. Furthermore, germline origins identified by positive nucleotide distribution skew jumps overlap with origins identified by ini-seq and OK-seq more frequently and more specifically than do sites identified by either SNS-seq or bubble-seq. PMID:27587586

Genome-wide identification and characterisation of human DNA replication origins by initiation site sequencing (ini-seq).

PubMed

Langley, Alexander R; Gräf, Stefan; Smith, James C; Krude, Torsten

2016-12-01

Next-generation sequencing has enabled the genome-wide identification of human DNA replication origins. However, different approaches to mapping replication origins, namely (i) sequencing isolated small nascent DNA strands (SNS-seq); (ii) sequencing replication bubbles (bubble-seq) and (iii) sequencing Okazaki fragments (OK-seq), show only limited concordance. To address this controversy, we describe here an independent high-resolution origin mapping technique that we call initiation site sequencing (ini-seq). In this approach, newly replicated DNA is directly labelled with digoxigenin-dUTP near the sites of its initiation in a cell-free system. The labelled DNA is then immunoprecipitated and genomic locations are determined by DNA sequencing. Using this technique we identify >25,000 discrete origin sites at sub-kilobase resolution on the human genome, with high concordance between biological replicates. Most activated origins identified by ini-seq are found at transcriptional start sites and contain G-quadruplex (G4) motifs. They tend to cluster in early-replicating domains, providing a correlation between early replication timing and local density of activated origins. Origins identified by ini-seq show highest concordance with sites identified by SNS-seq, followed by OK-seq and bubble-seq. Furthermore, germline origins identified by positive nucleotide distribution skew jumps overlap with origins identified by ini-seq and OK-seq more frequently and more specifically than do sites identified by either SNS-seq or bubble-seq. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA.

PubMed

Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare

2017-01-01

The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We highlight both the advantages and caveats of three commonly used genome-wide 5hmC profiling technologies and show that interpretation of 5hmC data can be significantly influenced by the sensitivity of methods used, especially as the levels of 5hmC are low and vary in different cell types and different genomic locations.

Nbs1 ChIP-Seq Identifies Off-Target DNA Double-Strand Breaks Induced by AID in Activated Splenic B Cells

PubMed Central

Linehan, Erin K.; Schrader, Carol E.; Stavnezer, Janet

2015-01-01

Activation-induced cytidine deaminase (AID) is required for initiation of Ig class switch recombination (CSR) and somatic hypermutation (SHM) of antibody genes during immune responses. AID has also been shown to induce chromosomal translocations, mutations, and DNA double-strand breaks (DSBs) involving non-Ig genes in activated B cells. To determine what makes a DNA site a target for AID-induced DSBs, we identify off-target DSBs induced by AID by performing chromatin immunoprecipitation (ChIP) for Nbs1, a protein that binds DSBs, followed by deep sequencing (ChIP-Seq). We detect and characterize hundreds of off-target AID-dependent DSBs. Two types of tandem repeats are highly enriched within the Nbs1-binding sites: long CA repeats, which can form Z-DNA, and tandem pentamers containing the AID target hotspot WGCW. These tandem repeats are not nearly as enriched at AID-independent DSBs, which we also identified. Msh2, a component of the mismatch repair pathway and important for genome stability, increases off-target DSBs, similar to its effect on Ig switch region DSBs, which are required intermediates during CSR. Most of the off-target DSBs are two-ended, consistent with generation during G1 phase, similar to DSBs in Ig switch regions. However, a minority are one-ended, presumably due to conversion of single-strand breaks to DSBs during replication. One-ended DSBs are repaired by processes involving homologous recombination, including break-induced replication repair, which can lead to genome instability. Off-target DSBs, especially those present during S phase, can lead to chromosomal translocations, deletions and gene amplifications, resulting in the high frequency of B cell lymphomas derived from cells that express or have expressed AID. PMID:26263206

Emergent HIV-1 Drug Resistance Mutations Were Not Present at Low-Frequency at Baseline in Non-Nucleoside Reverse Transcriptase Inhibitor-Treated Subjects in the STaR Study

PubMed Central

Porter, Danielle P.; Daeumer, Martin; Thielen, Alexander; Chang, Silvia; Martin, Ross; Cohen, Cal; Miller, Michael D.; White, Kirsten L.

2015-01-01

At Week 96 of the Single-Tablet Regimen (STaR) study, more treatment-naïve subjects that received rilpivirine/emtricitabine/tenofovir DF (RPV/FTC/TDF) developed resistance mutations compared to those treated with efavirenz (EFV)/FTC/TDF by population sequencing. Furthermore, more RPV/FTC/TDF-treated subjects with baseline HIV-1 RNA >100,000 copies/mL developed resistance compared to subjects with baseline HIV-1 RNA ≤100,000 copies/mL. Here, deep sequencing was utilized to assess the presence of pre-existing low-frequency variants in subjects with and without resistance development in the STaR study. Deep sequencing (Illumina MiSeq) was performed on baseline and virologic failure samples for all subjects analyzed for resistance by population sequencing during the clinical study (n = 33), as well as baseline samples from control subjects with virologic response (n = 118). Primary NRTI or NNRTI drug resistance mutations present at low frequency (≥2% to 20%) were detected in 6.6% of baseline samples by deep sequencing, all of which occurred in control subjects. Deep sequencing results were generally consistent with population sequencing but detected additional primary NNRTI and NRTI resistance mutations at virologic failure in seven samples. HIV-1 drug resistance mutations emerging while on RPV/FTC/TDF or EFV/FTC/TDF treatment were not present at low frequency at baseline in the STaR study. PMID:26690199

Emergent HIV-1 Drug Resistance Mutations Were Not Present at Low-Frequency at Baseline in Non-Nucleoside Reverse Transcriptase Inhibitor-Treated Subjects in the STaR Study.

PubMed

Porter, Danielle P; Daeumer, Martin; Thielen, Alexander; Chang, Silvia; Martin, Ross; Cohen, Cal; Miller, Michael D; White, Kirsten L

2015-12-07

At Week 96 of the Single-Tablet Regimen (STaR) study, more treatment-naïve subjects that received rilpivirine/emtricitabine/tenofovir DF (RPV/FTC/TDF) developed resistance mutations compared to those treated with efavirenz (EFV)/FTC/TDF by population sequencing. Furthermore, more RPV/FTC/TDF-treated subjects with baseline HIV-1 RNA >100,000 copies/mL developed resistance compared to subjects with baseline HIV-1 RNA ≤100,000 copies/mL. Here, deep sequencing was utilized to assess the presence of pre-existing low-frequency variants in subjects with and without resistance development in the STaR study. Deep sequencing (Illumina MiSeq) was performed on baseline and virologic failure samples for all subjects analyzed for resistance by population sequencing during the clinical study (n = 33), as well as baseline samples from control subjects with virologic response (n = 118). Primary NRTI or NNRTI drug resistance mutations present at low frequency (≥2% to 20%) were detected in 6.6% of baseline samples by deep sequencing, all of which occurred in control subjects. Deep sequencing results were generally consistent with population sequencing but detected additional primary NNRTI and NRTI resistance mutations at virologic failure in seven samples. HIV-1 drug resistance mutations emerging while on RPV/FTC/TDF or EFV/FTC/TDF treatment were not present at low frequency at baseline in the STaR study.

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding

PubMed Central

Gilad, Yoav; Pritchard, Jonathan K.; Stephens, Matthew

2015-01-01

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede. PMID:26406244

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding.

PubMed

Raj, Anil; Shim, Heejung; Gilad, Yoav; Pritchard, Jonathan K; Stephens, Matthew

2015-01-01

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede.

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

PubMed Central

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

2011-01-01

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

Comparison and evaluation of two exome capture kits and sequencing platforms for variant calling.

PubMed

Zhang, Guoqiang; Wang, Jianfeng; Yang, Jin; Li, Wenjie; Deng, Yutian; Li, Jing; Huang, Jun; Hu, Songnian; Zhang, Bing

2015-08-05

To promote the clinical application of next-generation sequencing, it is important to obtain accurate and consistent variants of target genomic regions at low cost. Ion Proton, the latest updated semiconductor-based sequencing instrument from Life Technologies, is designed to provide investigators with an inexpensive platform for human whole exome sequencing that achieves a rapid turnaround time. However, few studies have comprehensively compared and evaluated the accuracy of variant calling between Ion Proton and Illumina sequencing platforms such as HiSeq 2000, which is the most popular sequencing platform for the human genome. The Ion Proton sequencer combined with the Ion TargetSeq Exome Enrichment Kit together make up TargetSeq-Proton, whereas SureSelect-Hiseq is based on the Agilent SureSelect Human All Exon v4 Kit and the HiSeq 2000 sequencer. Here, we sequenced exonic DNA from four human blood samples using both TargetSeq-Proton and SureSelect-HiSeq. We then called variants in the exonic regions that overlapped between the two exome capture kits (33.6 Mb). The rates of shared variant loci called by two sequencing platforms were from 68.0 to 75.3% in four samples, whereas the concordance of co-detected variant loci reached 99%. Sanger sequencing validation revealed that the validated rate of concordant single nucleotide polymorphisms (SNPs) (91.5%) was higher than the SNPs specific to TargetSeq-Proton (60.0%) or specific to SureSelect-HiSeq (88.3%). With regard to 1-bp small insertions and deletions (InDels), the Sanger sequencing validated rates of concordant variants (100.0%) and SureSelect-HiSeq-specific (89.6%) were higher than those of TargetSeq-Proton-specific (15.8%). In the sequencing of exonic regions, a combination of using of two sequencing strategies (SureSelect-HiSeq and TargetSeq-Proton) increased the variant calling specificity for concordant variant loci and the sensitivity for variant loci called by any one platform. However, for the sequencing of platform-specific variants, the accuracy of variant calling by HiSeq 2000 was higher than that of Ion Proton, specifically for the InDel detection. Moreover, the variant calling software also influences the detection of SNPs and, specifically, InDels in Ion Proton exome sequencing.

Proteogenomic database construction driven from large scale RNA-seq data.

PubMed

Woo, Sunghee; Cha, Seong Won; Merrihew, Gennifer; He, Yupeng; Castellana, Natalie; Guest, Clark; MacCoss, Michael; Bafna, Vineet

2014-01-03

The advent of inexpensive RNA-seq technologies and other deep sequencing technologies for RNA has the promise to radically improve genomic annotation, providing information on transcribed regions and splicing events in a variety of cellular conditions. Using MS-based proteogenomics, many of these events can be confirmed directly at the protein level. However, the integration of large amounts of redundant RNA-seq data and mass spectrometry data poses a challenging problem. Our paper addresses this by construction of a compact database that contains all useful information expressed in RNA-seq reads. Applying our method to cumulative C. elegans data reduced 496.2 GB of aligned RNA-seq SAM files to 410 MB of splice graph database written in FASTA format. This corresponds to 1000× compression of data size, without loss of sensitivity. We performed a proteogenomics study using the custom data set, using a completely automated pipeline, and identified a total of 4044 novel events, including 215 novel genes, 808 novel exons, 12 alternative splicings, 618 gene-boundary corrections, 245 exon-boundary changes, 938 frame shifts, 1166 reverse strands, and 42 translated UTRs. Our results highlight the usefulness of transcript + proteomic integration for improved genome annotations.

Effects of calcium supplements on the quality and acrylamide content of puffed shrimp chips.

PubMed

Chen, Tai-Yuan; Luo, Hsuan-Min; Hsu, Pang-Hung; Sung, Wen-Chieh

2016-01-01

The quality and acrylamide content of deep-fried and microwave-puffed shrimp chips fortified with 0.1%, 0.5%, or 1.0% calcium salts (calcium lactate, calcium carbonate, calcium citrate, or calcium acetate) were investigated. Microwave-puffed shrimp chips contained higher amounts of acrylamide (130.43 ppb) than did deep-fried shrimp chips. The greatest mitigation of acrylamide formation in overfried chips was obtained with 0.1% calcium lactate. All browning indexes of fortified shrimp chips, whether deep-fried or microwave-puffed, were reduced. L* values of microwave-puffed shrimp chips were higher than those of deep-fried shrimp chips, whereas a* and b* values and browning indexes were lower. Color differences (ΔE) between deep-fried puffed shrimp chips fortified with calcium salts and a control sample were higher than 5, and the sensory scores of shrimp chips were significantly decreased by the addition of calcium lactate. Copyright © 2015. Published by Elsevier B.V.

SeqLib: a C ++ API for rapid BAM manipulation, sequence alignment and sequence assembly

PubMed Central

Wala, Jeremiah; Beroukhim, Rameen

2017-01-01

Abstract We present SeqLib, a C ++ API and command line tool that provides a rapid and user-friendly interface to BAM/SAM/CRAM files, global sequence alignment operations and sequence assembly. Four C libraries perform core operations in SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment and Fermi for error correction and sequence assembly. Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence analysis APIs. We demonstrate an example of how minimal SeqLib code can extract, error-correct and assemble reads from a CRAM file and then align with BWA-MEM. SeqLib also provides additional capabilities, including chromosome-aware interval queries and read plotting. Command line tools are available for performing integrated error correction, micro-assemblies and alignment. Availability and Implementation: SeqLib is available on Linux and OSX for the C ++98 standard and later at github.com/walaj/SeqLib. SeqLib is released under the Apache2 license. Additional capabilities for BLAT alignment are available under the BLAT license. Contact: jwala@broadinstitue.org; rameen@broadinstitute.org PMID:28011768

SeqLib: a C ++ API for rapid BAM manipulation, sequence alignment and sequence assembly.

PubMed

Wala, Jeremiah; Beroukhim, Rameen

2017-03-01

We present SeqLib, a C ++ API and command line tool that provides a rapid and user-friendly interface to BAM/SAM/CRAM files, global sequence alignment operations and sequence assembly. Four C libraries perform core operations in SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment and Fermi for error correction and sequence assembly. Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence analysis APIs. We demonstrate an example of how minimal SeqLib code can extract, error-correct and assemble reads from a CRAM file and then align with BWA-MEM. SeqLib also provides additional capabilities, including chromosome-aware interval queries and read plotting. Command line tools are available for performing integrated error correction, micro-assemblies and alignment. SeqLib is available on Linux and OSX for the C ++98 standard and later at github.com/walaj/SeqLib. SeqLib is released under the Apache2 license. Additional capabilities for BLAT alignment are available under the BLAT license. jwala@broadinstitue.org ; rameen@broadinstitute.org. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach

PubMed Central

Hua, Xiao-Mei; Liang, Li; Wen, Zhong-Ling; Du, Mei-Hang; Meng, Fan-Fan; Pang, Yan-Jun; Tang, Cheng-Yi

2018-01-01

The worldwide commercial cultivation of transgenic crops, including glyphosate-tolerant (GT) soybeans, has increased widely during the past 20 years. However, it is accompanied with a growing concern about potential effects of transgenic crops on the soil microbial communities, especially on rhizosphere bacterial communities. Our previous study found that the GT soybean line NZL06-698 (N698) significantly affected rhizosphere bacteria, including some unidentified taxa, through 16S rRNA gene (16S rDNA) V4 region amplicon deep sequencing via Illumina MiSeq. In this study, we performed 16S rDNA V5–V7 region amplicon deep sequencing via Illumina MiSeq and shotgun metagenomic approaches to identify those major taxa. Results of these processes revealed that the species richness and evenness increased in the rhizosphere bacterial communities of N698, the beta diversity of the rhizosphere bacterial communities of N698 was affected, and that certain dominant bacterial phyla and genera were related to N698 compared with its control cultivar Mengdou12. Consistent with our previous findings, this study showed that N698 affects the rhizosphere bacterial communities. In specific, N698 negatively affects Rahnella, Janthinobacterium, Stenotrophomonas, Sphingomonas and Luteibacter while positively affecting Arthrobacter, Bradyrhizobium, Ramlibacter and Nitrospira. PMID:29659545

Comparative Analysis of Single-Cell RNA Sequencing Methods.

PubMed

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

2017-02-16

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

Cell culture compositions

DOEpatents

Dunn-Coleman, Nigel; Goedegebuur, Frits; Ward, Michael; Yiao, Jian

2014-03-18

The present invention provides a novel endoglucanase nucleic acid sequence, designated egl6 (SEQ ID NO:1 encodes the full length endoglucanase; SEQ ID NO:4 encodes the mature form), and the corresponding endoglucanase VI amino acid sequence ("EGVI"; SEQ ID NO:3 is the signal sequence; SEQ ID NO:2 is the mature sequence). The invention also provides expression vectors and host cells comprising a nucleic acid sequence encoding EGVI, recombinant EGVI proteins and methods for producing the same.

rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

PubMed

Shen, Shihao; Park, Juw Won; Lu, Zhi-xiang; Lin, Lan; Henry, Michael D; Wu, Ying Nian; Zhou, Qing; Xing, Yi

2014-12-23

Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.

Integrated digital error suppression for improved detection of circulating tumor DNA

PubMed Central

Kurtz, David M.; Chabon, Jacob J.; Scherer, Florian; Stehr, Henning; Liu, Chih Long; Bratman, Scott V.; Say, Carmen; Zhou, Li; Carter, Justin N.; West, Robert B.; Sledge, George W.; Shrager, Joseph B.; Loo, Billy W.; Neal, Joel W.; Wakelee, Heather A.; Diehn, Maximilian; Alizadeh, Ash A.

2016-01-01

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by ~3 fold, and synergize when combined to yield ~15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to clinical non-small cell lung cancer (NSCLC) samples, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and 96% specificity and detection of ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings. PMID:27018799

Considerations on Experimental Design and Data Analysis of Chromatin Immunoprecipitation Experiments.

PubMed

Jordán-Pla, Antonio; Visa, Neus

2018-01-01

Arguably one of the most valuable techniques to study chromatin organization, ChIP is the method of choice to map the contacts established between proteins and genomic DNA. Ever since its inception, more than 30 years ago, ChIP has been constantly evolving, improving, and expanding its capabilities and reach. Despite its widespread use by many laboratories across a wide variety of disciplines, ChIP assays can be sometimes challenging to design, and are often sensitive to variations in practical implementation.In this chapter, we provide a general overview of the ChIP method and its most common variations, with a special focus on ChIP-seq. We try to address some of the most important aspects that need to be taken into account in order to design and perform experiments that generate the most reproducible, high-quality data. Some of the main topics covered include the use of properly characterized antibodies, alternatives to chromatin preparation, the need for proper controls, and some recommendations about ChIP-seq data analysis.

Discovery of common sequences absent in the human reference genome using pooled samples from next generation sequencing.

PubMed

Liu, Yu; Koyutürk, Mehmet; Maxwell, Sean; Xiang, Min; Veigl, Martina; Cooper, Richard S; Tayo, Bamidele O; Li, Li; LaFramboise, Thomas; Wang, Zhenghe; Zhu, Xiaofeng; Chance, Mark R

2014-08-16

Sequences up to several megabases in length have been found to be present in individual genomes but absent in the human reference genome. These sequences may be common in populations, and their absence in the reference genome may indicate rare variants in the genomes of individuals who served as donors for the human genome project. As the reference genome is used in probe design for microarray technology and mapping short reads in next generation sequencing (NGS), this missing sequence could be a source of bias in functional genomic studies and variant analysis. One End Anchor (OEA) and/or orphan reads from paired-end sequencing have been used to identify novel sequences that are absent in reference genome. However, there is no study to investigate the distribution, evolution and functionality of those sequences in human populations. To systematically identify and study the missing common sequences (micSeqs), we extended the previous method by pooling OEA reads from large number of individuals and applying strict filtering methods to remove false sequences. The pipeline was applied to data from phase 1 of the 1000 Genomes Project. We identified 309 micSeqs that are present in at least 1% of the human population, but absent in the reference genome. We confirmed 76% of these 309 micSeqs by comparison to other primate genomes, individual human genomes, and gene expression data. Furthermore, we randomly selected fifteen micSeqs and confirmed their presence using PCR validation in 38 additional individuals. Functional analysis using published RNA-seq and ChIP-seq data showed that eleven micSeqs are highly expressed in human brain and three micSeqs contain transcription factor (TF) binding regions, suggesting they are functional elements. In addition, the identified micSeqs are absent in non-primates and show dynamic acquisition during primate evolution culminating with most micSeqs being present in Africans, suggesting some micSeqs may be important sources of human diversity. 76% of micSeqs were confirmed by a comparative genomics approach. Fourteen micSeqs are expressed in human brain or contain TF binding regions. Some micSeqs are primate-specific, conserved and may play a role in the evolution of primates.

Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons

DOE PAGES

Wetmore, Kelly M.; Price, Morgan N.; Waters, Robert J.; ...

2015-05-12

Transposon mutagenesis with next-generation sequencing (TnSeq) is a powerful approach to annotate gene function in bacteria, but existing protocols for TnSeq require laborious preparation of every sample before sequencing. Thus, the existing protocols are not amenable to the throughput necessary to identify phenotypes and functions for the majority of genes in diverse bacteria. Here, we present a method, random bar code transposon-site sequencing (RB-TnSeq), which increases the throughput of mutant fitness profiling by incorporating random DNA bar codes into Tn5 and mariner transposons and by using bar code sequencing (BarSeq) to assay mutant fitness. RB-TnSeq can be used with anymore » transposon, and TnSeq is performed once per organism instead of once per sample. Each BarSeq assay requires only a simple PCR, and 48 to 96 samples can be sequenced on one lane of an Illumina HiSeq system. We demonstrate the reproducibility and biological significance of RB-TnSeq with Escherichia coli, Phaeobacter inhibens, Pseudomonas stutzeri, Shewanella amazonensis, and Shewanella oneidensis. To demonstrate the increased throughput of RB-TnSeq, we performed 387 successful genome-wide mutant fitness assays representing 130 different bacterium-carbon source combinations and identified 5,196 genes with significant phenotypes across the five bacteria. In P. inhibens, we used our mutant fitness data to identify genes important for the utilization of diverse carbon substrates, including a putative D-mannose isomerase that is required for mannitol catabolism. RB-TnSeq will enable the cost-effective functional annotation of diverse bacteria using mutant fitness profiling. A large challenge in microbiology is the functional assessment of the millions of uncharacterized genes identified by genome sequencing. Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach to assign phenotypes and functions to genes. However, the current strategies for TnSeq are too laborious to be applied to hundreds of experimental conditions across multiple bacteria. Here, we describe an approach, random bar code transposon-site sequencing (RB-TnSeq), which greatly simplifies the measurement of gene fitness by using bar code sequencing (BarSeq) to monitor the abundance of mutants. We performed 387 genome-wide fitness assays across five bacteria and identified phenotypes for over 5,000 genes. RB-TnSeq can be applied to diverse bacteria and is a powerful tool to annotate uncharacterized genes using phenotype data.« less

Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons

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

Wetmore, Kelly M.; Price, Morgan N.; Waters, Robert J.

Transposon mutagenesis with next-generation sequencing (TnSeq) is a powerful approach to annotate gene function in bacteria, but existing protocols for TnSeq require laborious preparation of every sample before sequencing. Thus, the existing protocols are not amenable to the throughput necessary to identify phenotypes and functions for the majority of genes in diverse bacteria. Here, we present a method, random bar code transposon-site sequencing (RB-TnSeq), which increases the throughput of mutant fitness profiling by incorporating random DNA bar codes into Tn5 and mariner transposons and by using bar code sequencing (BarSeq) to assay mutant fitness. RB-TnSeq can be used with anymore » transposon, and TnSeq is performed once per organism instead of once per sample. Each BarSeq assay requires only a simple PCR, and 48 to 96 samples can be sequenced on one lane of an Illumina HiSeq system. We demonstrate the reproducibility and biological significance of RB-TnSeq with Escherichia coli, Phaeobacter inhibens, Pseudomonas stutzeri, Shewanella amazonensis, and Shewanella oneidensis. To demonstrate the increased throughput of RB-TnSeq, we performed 387 successful genome-wide mutant fitness assays representing 130 different bacterium-carbon source combinations and identified 5,196 genes with significant phenotypes across the five bacteria. In P. inhibens, we used our mutant fitness data to identify genes important for the utilization of diverse carbon substrates, including a putative D-mannose isomerase that is required for mannitol catabolism. RB-TnSeq will enable the cost-effective functional annotation of diverse bacteria using mutant fitness profiling. A large challenge in microbiology is the functional assessment of the millions of uncharacterized genes identified by genome sequencing. Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach to assign phenotypes and functions to genes. However, the current strategies for TnSeq are too laborious to be applied to hundreds of experimental conditions across multiple bacteria. Here, we describe an approach, random bar code transposon-site sequencing (RB-TnSeq), which greatly simplifies the measurement of gene fitness by using bar code sequencing (BarSeq) to monitor the abundance of mutants. We performed 387 genome-wide fitness assays across five bacteria and identified phenotypes for over 5,000 genes. RB-TnSeq can be applied to diverse bacteria and is a powerful tool to annotate uncharacterized genes using phenotype data.« less

groHMM: a computational tool for identifying unannotated and cell type-specific transcription units from global run-on sequencing data.

PubMed

Chae, Minho; Danko, Charles G; Kraus, W Lee

2015-07-16

Global run-on coupled with deep sequencing (GRO-seq) provides extensive information on the location and function of coding and non-coding transcripts, including primary microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and enhancer RNAs (eRNAs), as well as yet undiscovered classes of transcripts. However, few computational tools tailored toward this new type of sequencing data are available, limiting the applicability of GRO-seq data for identifying novel transcription units. Here, we present groHMM, a computational tool in R, which defines the boundaries of transcription units de novo using a two state hidden-Markov model (HMM). A systematic comparison of the performance between groHMM and two existing peak-calling methods tuned to identify broad regions (SICER and HOMER) favorably supports our approach on existing GRO-seq data from MCF-7 breast cancer cells. To demonstrate the broader utility of our approach, we have used groHMM to annotate a diverse array of transcription units (i.e., primary transcripts) from four GRO-seq data sets derived from cells representing a variety of different human tissue types, including non-transformed cells (cardiomyocytes and lung fibroblasts) and transformed cells (LNCaP and MCF-7 cancer cells), as well as non-mammalian cells (from flies and worms). As an example of the utility of groHMM and its application to questions about the transcriptome, we show how groHMM can be used to analyze cell type-specific enhancers as defined by newly annotated enhancer transcripts. Our results show that groHMM can reveal new insights into cell type-specific transcription by identifying novel transcription units, and serve as a complete and useful tool for evaluating functional genomic elements in cells.

Fungal diversity in deep-sea sediments of a hydrothermal vent system in the Southwest Indian Ridge

NASA Astrophysics Data System (ADS)

Xu, Wei; Gong, Lin-feng; Pang, Ka-Lai; Luo, Zhu-Hua

2018-01-01

Deep-sea hydrothermal sediment is known to support remarkably diverse microbial consortia. In deep sea environments, fungal communities remain less studied despite their known taxonomic and functional diversity. High-throughput sequencing methods have augmented our capacity to assess eukaryotic diversity and their functions in microbial ecology. Here we provide the first description of the fungal community diversity found in deep sea sediments collected at the Southwest Indian Ridge (SWIR) using culture-dependent and high-throughput sequencing approaches. A total of 138 fungal isolates were cultured from seven different sediment samples using various nutrient media, and these isolates were identified to 14 fungal taxa, including 11 Ascomycota taxa (7 genera) and 3 Basidiomycota taxa (2 genera) based on internal transcribed spacers (ITS1, ITS2 and 5.8S) of rDNA. Using illumina HiSeq sequencing, a total of 757,467 fungal ITS2 tags were recovered from the samples and clustered into 723 operational taxonomic units (OTUs) belonging to 79 taxa (Ascomycota and Basidiomycota contributed to 99% of all samples) based on 97% sequence similarity. Results from both approaches suggest that there is a high fungal diversity in the deep-sea sediments collected in the SWIR and fungal communities were shown to be slightly different by location, although all were collected from adjacent sites at the SWIR. This study provides baseline data of the fungal diversity and biogeography, and a glimpse to the microbial ecology associated with the deep-sea sediments of the hydrothermal vent system of the Southwest Indian Ridge.

Construction of Pseudomolecule Sequences of the aus Rice Cultivar Kasalath for Comparative Genomics of Asian Cultivated Rice

PubMed Central

Sakai, Hiroaki; Kanamori, Hiroyuki; Arai-Kichise, Yuko; Shibata-Hatta, Mari; Ebana, Kaworu; Oono, Youko; Kurita, Kanako; Fujisawa, Hiroko; Katagiri, Satoshi; Mukai, Yoshiyuki; Hamada, Masao; Itoh, Takeshi; Matsumoto, Takashi; Katayose, Yuichi; Wakasa, Kyo; Yano, Masahiro; Wu, Jianzhong

2014-01-01

Having a deep genetic structure evolved during its domestication and adaptation, the Asian cultivated rice (Oryza sativa) displays considerable physiological and morphological variations. Here, we describe deep whole-genome sequencing of the aus rice cultivar Kasalath by using the advanced next-generation sequencing (NGS) technologies to gain a better understanding of the sequence and structural changes among highly differentiated cultivars. The de novo assembled Kasalath sequences represented 91.1% (330.55 Mb) of the genome and contained 35 139 expressed loci annotated by RNA-Seq analysis. We detected 2 787 250 single-nucleotide polymorphisms (SNPs) and 7393 large insertion/deletion (indel) sites (>100 bp) between Kasalath and Nipponbare, and 2 216 251 SNPs and 3780 large indels between Kasalath and 93-11. Extensive comparison of the gene contents among these cultivars revealed similar rates of gene gain and loss. We detected at least 7.39 Mb of inserted sequences and 40.75 Mb of unmapped sequences in the Kasalath genome in comparison with the Nipponbare reference genome. Mapping of the publicly available NGS short reads from 50 rice accessions proved the necessity and the value of using the Kasalath whole-genome sequence as an additional reference to capture the sequence polymorphisms that cannot be discovered by using the Nipponbare sequence alone. PMID:24578372

A deep learning-based multi-model ensemble method for cancer prediction.

PubMed

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproduction-related genes.

PubMed

Lan, DaoLiang; Xiong, XianRong; Wei, YanLi; Xu, Tong; Zhong, JinCheng; Zhi, XiangDong; Wang, Yong; Li, Jian

2014-09-01

RNA-Seq, a high-throughput (HT) sequencing technique, has been used effectively in large-scale transcriptomic studies, and is particularly useful for improving gene structure information and mining of new genes. In this study, RNA-Seq HT technology was employed to analyze the transcriptome of yak ovary. After Illumina-Solexa deep sequencing, 26826516 clean reads with a total of 4828772880 bp were obtained from the ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome and 3734 of these genes were involved in alternative splicing. Gene structure refinement analysis showed that 7340 genes that were annotated in the yak genome could be extended at the 5' or 3' ends based on the alignments been the transcripts and the genome sequence. Novel transcript prediction analysis identified 6321 new transcripts with lengths ranging from 180 to 14884 bp, and 2267 of them were predicted to code proteins. BLAST analysis of the new transcripts showed that 1200?4933 mapped to the non-redundant (nr), nucleotide (nt) and/or SwissProt sequence databases. Comparative statistical analysis of the new mapped transcripts showed that the majority of them were similar to genes in Bos taurus (41.4%), Bos grunniens mutus (33.0%), Ovis aries (6.3%), Homo sapiens (2.8%), Mus musculus (1.6%) and other species. Functional analysis showed that these expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes pathways. GO analysis of the new transcripts found that the largest proportion of them was associated with reproduction. The results of this study will provide a basis for describing the normal transcriptome map of yak ovary and for future studies on yak breeding performance. Moreover, the results confirmed that RNA-Seq HT technology is highly advantageous in improving gene structure information and mining of new genes, as well as in providing valuable data to expand the yak genome information.

Detection of non-coding RNA in bacteria and archaea using the DETR'PROK Galaxy pipeline.

PubMed

Toffano-Nioche, Claire; Luo, Yufei; Kuchly, Claire; Wallon, Claire; Steinbach, Delphine; Zytnicki, Matthias; Jacq, Annick; Gautheret, Daniel

2013-09-01

RNA-seq experiments are now routinely used for the large scale sequencing of transcripts. In bacteria or archaea, such deep sequencing experiments typically produce 10-50 million fragments that cover most of the genome, including intergenic regions. In this context, the precise delineation of the non-coding elements is challenging. Non-coding elements include untranslated regions (UTRs) of mRNAs, independent small RNA genes (sRNAs) and transcripts produced from the antisense strand of genes (asRNA). Here we present a computational pipeline (DETR'PROK: detection of ncRNAs in prokaryotes) based on the Galaxy framework that takes as input a mapping of deep sequencing reads and performs successive steps of clustering, comparison with existing annotation and identification of transcribed non-coding fragments classified into putative 5' UTRs, sRNAs and asRNAs. We provide a step-by-step description of the protocol using real-life example data sets from Vibrio splendidus and Escherichia coli. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

w4CSeq: software and web application to analyze 4C-seq data.

PubMed

Cai, Mingyang; Gao, Fan; Lu, Wange; Wang, Kai

2016-11-01

Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a powerful technique to identify genome-wide partners interacting with a pre-specified genomic locus. Here, we present a computational and statistical approach to analyze 4C-Seq data generated from both enzyme digestion and sonication fragmentation-based methods. We implemented a command line software tool and a web interface called w4CSeq, which takes in the raw 4C sequencing data (FASTQ files) as input, performs automated statistical analysis and presents results in a user-friendly manner. Besides providing users with the list of candidate interacting sites/regions, w4CSeq generates figures showing genome-wide distribution of interacting regions, and sketches the enrichment of key features such as TSSs, TTSs, CpG sites and DNA replication timing around 4C sites. Users can establish their own web server by downloading source codes at https://github.com/WGLab/w4CSeq Additionally, a demo web server is available at http://w4cseq.wglab.org CONTACT: kaiwang@usc.edu or wangelu@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

DRREP: deep ridge regressed epitope predictor.

PubMed

Sher, Gene; Zhi, Degui; Zhang, Shaojie

2017-10-03

The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

Carbohydrate degrading polypeptide and uses thereof

DOEpatents

Sagt, Cornelis Maria Jacobus; Schooneveld-Bergmans, Margot Elisabeth Francoise; Roubos, Johannes Andries; Los, Alrik Pieter

2015-10-20

The invention relates to a polypeptide having carbohydrate material degrading activity which comprises the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1 or SEQ ID NO: 4, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 96% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 96% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional protein and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

The complete mitochondrial genome of Haliotis laevigata (Gastropoda: Haliotidae) using MiSeq and HiSeq sequencing.

PubMed

Robinson, Nick A; Hall, Nathan E; Ross, Elizabeth M; Cooke, Ira R; Shiel, Brett P; Robinson, Andrew J; Strugnell, Jan M

2016-01-01

The mitochondrial genome of greenlip abalone, Haliotis laevigata, is reported. MiSeq and HiSeq sequencing of one individual was assembled to yield a single 16,545 bp contig. The sequence shares 92% identity to the H. rubra mitochondrial genome (a closely related species that hybridize with H. laevigata in the wild). The sequence will be useful for determining the maternal contribution to hybrid populations, for investigating population structure and stock-enhancement effectiveness.

Rapid Quantification of Mutant Fitness in Diverse Bacteria by Sequencing Randomly Bar-Coded Transposons

PubMed Central

Wetmore, Kelly M.; Price, Morgan N.; Waters, Robert J.; Lamson, Jacob S.; He, Jennifer; Hoover, Cindi A.; Blow, Matthew J.; Bristow, James; Butland, Gareth

2015-01-01

ABSTRACT Transposon mutagenesis with next-generation sequencing (TnSeq) is a powerful approach to annotate gene function in bacteria, but existing protocols for TnSeq require laborious preparation of every sample before sequencing. Thus, the existing protocols are not amenable to the throughput necessary to identify phenotypes and functions for the majority of genes in diverse bacteria. Here, we present a method, random bar code transposon-site sequencing (RB-TnSeq), which increases the throughput of mutant fitness profiling by incorporating random DNA bar codes into Tn5 and mariner transposons and by using bar code sequencing (BarSeq) to assay mutant fitness. RB-TnSeq can be used with any transposon, and TnSeq is performed once per organism instead of once per sample. Each BarSeq assay requires only a simple PCR, and 48 to 96 samples can be sequenced on one lane of an Illumina HiSeq system. We demonstrate the reproducibility and biological significance of RB-TnSeq with Escherichia coli, Phaeobacter inhibens, Pseudomonas stutzeri, Shewanella amazonensis, and Shewanella oneidensis. To demonstrate the increased throughput of RB-TnSeq, we performed 387 successful genome-wide mutant fitness assays representing 130 different bacterium-carbon source combinations and identified 5,196 genes with significant phenotypes across the five bacteria. In P. inhibens, we used our mutant fitness data to identify genes important for the utilization of diverse carbon substrates, including a putative d-mannose isomerase that is required for mannitol catabolism. RB-TnSeq will enable the cost-effective functional annotation of diverse bacteria using mutant fitness profiling. PMID:25968644

Maximum entropy methods for extracting the learned features of deep neural networks.

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

19 CFR 12.39 - Imported articles involving unfair methods of competition or practices.

Code of Federal Regulations, 2010 CFR

2010-04-01

... economically operated United States industry, or to restrain or monopolize trade and commerce in the United... the authorization or consent of the Government. (e) Importations of semiconductor chip products. (1) In accordance with the Semiconductor Chip Protection Act of 1984 (17 U.S.C. 901 et seq.), if the...

MRO DKF Post-Processing Tool

NASA Technical Reports Server (NTRS)

Ayap, Shanti; Fisher, Forest; Gladden, Roy; Khanampompan, Teerapat

2008-01-01

This software tool saves time and reduces risk by automating two labor-intensive and error-prone post-processing steps required for every DKF [DSN (Deep Space Network) Keyword File] that MRO (Mars Reconnaissance Orbiter) produces, and is being extended to post-process the corresponding TSOE (Text Sequence Of Events) as well. The need for this post-processing step stems from limitations in the seq-gen modeling resulting in incorrect DKF generation that is then cleaned up in post-processing.

Mediator binding to UASs is broadly uncoupled from transcription and cooperative with TFIID recruitment to promoters.

PubMed

Grünberg, Sebastian; Henikoff, Steven; Hahn, Steven; Zentner, Gabriel E

2016-11-15

Mediator is a conserved, essential transcriptional coactivator complex, but its in vivo functions have remained unclear due to conflicting data regarding its genome-wide binding pattern obtained by genome-wide ChIP Here, we used ChEC-seq, a method orthogonal to ChIP, to generate a high-resolution map of Mediator binding to the yeast genome. We find that Mediator associates with upstream activating sequences (UASs) rather than the core promoter or gene body under all conditions tested. Mediator occupancy is surprisingly correlated with transcription levels at only a small fraction of genes. Using the same approach to map TFIID, we find that TFIID is associated with both TFIID- and SAGA-dependent genes and that TFIID and Mediator occupancy is cooperative. Our results clarify Mediator recruitment and binding to the genome, showing that Mediator binding to UASs is widespread, partially uncoupled from transcription, and mediated in part by TFIID. © 2016 The Authors.

Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Version 3.0 User Guide

EPA Science Inventory

User Guide to describe the complete functionality of the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Version 3.0 online tool. The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility tool (SeqAPASS; https://seqa...

Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro.

PubMed

Nalpas, Nicolas C; Park, Stephen D E; Magee, David A; Taraktsoglou, Maria; Browne, John A; Conlon, Kevin M; Rue-Albrecht, Kévin; Killick, Kate E; Hokamp, Karsten; Lohan, Amanda J; Loftus, Brendan J; Gormley, Eamonn; Gordon, Stephen V; MacHugh, David E

2013-04-08

Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA.

Guidelines for whole genome bisulphite sequencing of intact and FFPET DNA on the Illumina HiSeq X Ten.

PubMed

Nair, Shalima S; Luu, Phuc-Loi; Qu, Wenjia; Maddugoda, Madhavi; Huschtscha, Lily; Reddel, Roger; Chenevix-Trench, Georgia; Toso, Martina; Kench, James G; Horvath, Lisa G; Hayes, Vanessa M; Stricker, Phillip D; Hughes, Timothy P; White, Deborah L; Rasko, John E J; Wong, Justin J-L; Clark, Susan J

2018-05-28

Comprehensive genome-wide DNA methylation profiling is critical to gain insights into epigenetic reprogramming during development and disease processes. Among the different genome-wide DNA methylation technologies, whole genome bisulphite sequencing (WGBS) is considered the gold standard for assaying genome-wide DNA methylation at single base resolution. However, the high sequencing cost to achieve the optimal depth of coverage limits its application in both basic and clinical research. To achieve 15× coverage of the human methylome, using WGBS, requires approximately three lanes of 100-bp-paired-end Illumina HiSeq 2500 sequencing. It is important, therefore, for advances in sequencing technologies to be developed to enable cost-effective high-coverage sequencing. In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16-20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r > 0.9×). Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.

Microfluidic affinity and ChIP-seq analyses converge on a conserved FOXP2-binding motif in chimp and human, which enables the detection of evolutionarily novel targets.

PubMed

Nelson, Christopher S; Fuller, Chris K; Fordyce, Polly M; Greninger, Alexander L; Li, Hao; DeRisi, Joseph L

2013-07-01

The transcription factor forkhead box P2 (FOXP2) is believed to be important in the evolution of human speech. A mutation in its DNA-binding domain causes severe speech impairment. Humans have acquired two coding changes relative to the conserved mammalian sequence. Despite intense interest in FOXP2, it has remained an open question whether the human protein's DNA-binding specificity and chromatin localization are conserved. Previous in vitro and ChIP-chip studies have provided conflicting consensus sequences for the FOXP2-binding site. Using MITOMI 2.0 microfluidic affinity assays, we describe the binding site of FOXP2 and its affinity profile in base-specific detail for all substitutions of the strongest binding site. We find that human and chimp FOXP2 have similar binding sites that are distinct from previously suggested consensus binding sites. Additionally, through analysis of FOXP2 ChIP-seq data from cultured neurons, we find strong overrepresentation of a motif that matches our in vitro results and identifies a set of genes with FOXP2 binding sites. The FOXP2-binding sites tend to be conserved, yet we identified 38 instances of evolutionarily novel sites in humans. Combined, these data present a comprehensive portrait of FOXP2's-binding properties and imply that although its sequence specificity has been conserved, some of its genomic binding sites are newly evolved.

Microfluidic affinity and ChIP-seq analyses converge on a conserved FOXP2-binding motif in chimp and human, which enables the detection of evolutionarily novel targets

PubMed Central

Nelson, Christopher S.; Fuller, Chris K.; Fordyce, Polly M.; Greninger, Alexander L.; Li, Hao; DeRisi, Joseph L.

2013-01-01

The transcription factor forkhead box P2 (FOXP2) is believed to be important in the evolution of human speech. A mutation in its DNA-binding domain causes severe speech impairment. Humans have acquired two coding changes relative to the conserved mammalian sequence. Despite intense interest in FOXP2, it has remained an open question whether the human protein’s DNA-binding specificity and chromatin localization are conserved. Previous in vitro and ChIP-chip studies have provided conflicting consensus sequences for the FOXP2-binding site. Using MITOMI 2.0 microfluidic affinity assays, we describe the binding site of FOXP2 and its affinity profile in base-specific detail for all substitutions of the strongest binding site. We find that human and chimp FOXP2 have similar binding sites that are distinct from previously suggested consensus binding sites. Additionally, through analysis of FOXP2 ChIP-seq data from cultured neurons, we find strong overrepresentation of a motif that matches our in vitro results and identifies a set of genes with FOXP2 binding sites. The FOXP2-binding sites tend to be conserved, yet we identified 38 instances of evolutionarily novel sites in humans. Combined, these data present a comprehensive portrait of FOXP2’s-binding properties and imply that although its sequence specificity has been conserved, some of its genomic binding sites are newly evolved. PMID:23625967

Whole-Exome Sequencing in a South American Cohort Links ALDH1A3, FOXN1 and Retinoic Acid Regulation Pathways to Autism Spectrum Disorders.

PubMed

Moreno-Ramos, Oscar A; Olivares, Ana María; Haider, Neena B; de Autismo, Liga Colombiana; Lattig, María Claudia

2015-01-01

Autism spectrum disorders (ASDs) are a range of complex neurodevelopmental conditions principally characterized by dysfunctions linked to mental development. Previous studies have shown that there are more than 1000 genes likely involved in ASD, expressed mainly in brain and highly interconnected among them. We applied whole exome sequencing in Colombian-South American trios. Two missense novel SNVs were found in the same child: ALDH1A3 (RefSeq NM_000693: c.1514T>C (p.I505T)) and FOXN1 (RefSeq NM_003593: c.146C>T (p.S49L)). Gene expression studies reveal that Aldh1a3 and Foxn1 are expressed in ~E13.5 mouse embryonic brain, as well as in adult piriform cortex (PC; ~P30). Conserved Retinoic Acid Response Elements (RAREs) upstream of human ALDH1A3 and FOXN1 and in mouse Aldh1a3 and Foxn1 genes were revealed using bioinformatic approximation. Chromatin immunoprecipitation (ChIP) assay using Retinoid Acid Receptor B (Rarb) as the immunoprecipitation target suggests RA regulation of Aldh1a3 and Foxn1 in mice. Our results frame a possible link of RA regulation in brain to ASD etiology, and a feasible non-additive effect of two apparently unrelated variants in ALDH1A3 and FOXN1 recognizing that every result given by next generation sequencing should be cautiously analyzed, as it might be an incidental finding.

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

PubMed

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

2015-01-01

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

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

PubMed

Rhodes, Johanna; Beale, Mathew A; Fisher, Matthew C

2014-01-01

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

PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data.

PubMed

Zhang, Yanju; Lameijer, Eric-Wubbo; 't Hoen, Peter A C; Ning, Zemin; Slagboom, P Eline; Ye, Kai

2012-02-15

RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon-exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge. We developed PASSion, a pattern growth algorithm-based pipeline for splice site detection in paired-end RNA-Seq reads. Comparing the performance of PASSion to three existing RNA-Seq analysis pipelines, TopHat, MapSplice and HMMSplicer, revealed that PASSion is competitive with these packages. Moreover, the performance of PASSion is not affected by read length and coverage. It performs better than the other three approaches when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools. Of the two public RNA-Seq datasets, PASSion predicted ≈ 137,000 and 173,000 splicing events, of which on average 82 are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, our package can discover differential and shared splicing patterns among multiple samples. The code and utilities can be freely downloaded from https://trac.nbic.nl/passion and ftp://ftp.sanger.ac.uk/pub/zn1/passion.

Genome-wide mapping of alternative splicing in Arabidopsis thaliana

PubMed Central

Filichkin, Sergei A.; Priest, Henry D.; Givan, Scott A.; Shen, Rongkun; Bryant, Douglas W.; Fox, Samuel E.; Wong, Weng-Keen; Mockler, Todd C.

2010-01-01

Alternative splicing can enhance transcriptome plasticity and proteome diversity. In plants, alternative splicing can be manifested at different developmental stages, and is frequently associated with specific tissue types or environmental conditions such as abiotic stress. We mapped the Arabidopsis transcriptome at single-base resolution using the Illumina platform for ultrahigh-throughput RNA sequencing (RNA-seq). Deep transcriptome sequencing confirmed a majority of annotated introns and identified thousands of novel alternatively spliced mRNA isoforms. Our analysis suggests that at least ∼42% of intron-containing genes in Arabidopsis are alternatively spliced; this is significantly higher than previous estimates based on cDNA/expressed sequence tag sequencing. Random validation confirmed that novel splice isoforms empirically predicted by RNA-seq can be detected in vivo. Novel introns detected by RNA-seq were substantially enriched in nonconsensus terminal dinucleotide splice signals. Alternative isoforms with premature termination codons (PTCs) comprised the majority of alternatively spliced transcripts. Using an example of an essential circadian clock gene, we show that intron retention can generate relatively abundant PTC+ isoforms and that this specific event is highly conserved among diverse plant species. Alternatively spliced PTC+ isoforms can be potentially targeted for degradation by the nonsense mediated mRNA decay (NMD) surveillance machinery or regulate the level of functional transcripts by the mechanism of regulated unproductive splicing and translation (RUST). We demonstrate that the relative ratios of the PTC+ and reference isoforms for several key regulatory genes can be considerably shifted under abiotic stress treatments. Taken together, our results suggest that like in animals, NMD and RUST may be widespread in plants and may play important roles in regulating gene expression. PMID:19858364

Genome-Wide Profiling of p63 DNA–Binding Sites Identifies an Element that Regulates Gene Expression during Limb Development in the 7q21 SHFM1 Locus

PubMed Central

Oti, Martin; Dutilh, Bas E.; Alonso, M. Eva; de la Calle-Mustienes, Elisa; Smeenk, Leonie; Rinne, Tuula; Parsaulian, Lilian; Bolat, Emine; Jurgelenaite, Rasa; Huynen, Martijn A.; Hoischen, Alexander; Veltman, Joris A.; Brunner, Han G.; Roscioli, Tony; Oates, Emily; Wilson, Meredith; Manzanares, Miguel; Gómez-Skarmeta, José Luis; Stunnenberg, Hendrik G.; Lohrum, Marion; van Bokhoven, Hans; Zhou, Huiqing

2010-01-01

Heterozygous mutations in p63 are associated with split hand/foot malformations (SHFM), orofacial clefting, and ectodermal abnormalities. Elucidation of the p63 gene network that includes target genes and regulatory elements may reveal new genes for other malformation disorders. We performed genome-wide DNA–binding profiling by chromatin immunoprecipitation (ChIP), followed by deep sequencing (ChIP–seq) in primary human keratinocytes, and identified potential target genes and regulatory elements controlled by p63. We show that p63 binds to an enhancer element in the SHFM1 locus on chromosome 7q and that this element controls expression of DLX6 and possibly DLX5, both of which are important for limb development. A unique micro-deletion including this enhancer element, but not the DLX5/DLX6 genes, was identified in a patient with SHFM. Our study strongly indicates disruption of a non-coding cis-regulatory element located more than 250 kb from the DLX5/DLX6 genes as a novel disease mechanism in SHFM1. These data provide a proof-of-concept that the catalogue of p63 binding sites identified in this study may be of relevance to the studies of SHFM and other congenital malformations that resemble the p63-associated phenotypes. PMID:20808887

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

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

Polypeptide having or assisting in carbohydrate material degrading activity and uses thereof

DOEpatents

Schooneveld-Bergmans, Margot Elisabeth Francoise; Heijne, Wilbert Herman Marie; Los, Alrik Pieter

2016-02-16

The invention relates to a polypeptide which comprises the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 76% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 76% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Polypeptide having beta-glucosidase activity and uses thereof

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

Schoonneveld-Bergmans, Margot Elisabeth Francoise; Heijne, Wilbert Herman Marie; De Jong, Rene Marcel

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 96% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 96% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well asmore » the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.« less

Polypeptide having swollenin activity and uses thereof

DOEpatents

Schoonneveld-Bergmans, Margot Elizabeth Francoise; Heijne, Wilbert Herman Marie; Vlasie, Monica D; Damveld, Robbertus Antonius

2015-11-04

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 73% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 73% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Polypeptide having beta-glucosidase activity and uses thereof

DOEpatents

Schooneveld-Bergmans, Margot Elisabeth Francoise; Heijne, Wilbert Herman Marie; De Jong, Rene Marcel; Damveld, Robbertus Antonius

2015-09-01

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 70% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 70% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Polypeptide having cellobiohydrolase activity and uses thereof

DOEpatents

Sagt, Cornelis Maria Jacobus; Schooneveld-Bergmans, Margot Elisabeth Francoise; Roubos, Johannes Andries; Los, Alrik Pieter

2015-09-15

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 93% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 93% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Polypeptide having acetyl xylan esterase activity and uses thereof

DOEpatents

Schoonneveld-Bergmans, Margot Elisabeth Francoise; Heijne, Wilbert Herman Marie; Los, Alrik Pieter

2015-10-20

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 82% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 82% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Polypeptide having carbohydrate degrading activity and uses thereof

DOEpatents

Schooneveld-Bergmans, Margot Elisabeth Francoise; Heijne, Wilbert Herman Marie; Vlasie, Monica Diana; Damveld, Robbertus Antonius

2015-08-18

The invention relates to a polypeptide comprising the amino acid sequence set out in SEQ ID NO: 2 or an amino acid sequence encoded by the nucleotide sequence of SEQ ID NO: 1, or a variant polypeptide or variant polynucleotide thereof, wherein the variant polypeptide has at least 73% sequence identity with the sequence set out in SEQ ID NO: 2 or the variant polynucleotide encodes a polypeptide that has at least 73% sequence identity with the sequence set out in SEQ ID NO: 2. The invention features the full length coding sequence of the novel gene as well as the amino acid sequence of the full-length functional polypeptide and functional equivalents of the gene or the amino acid sequence. The invention also relates to methods for using the polypeptide in industrial processes. Also included in the invention are cells transformed with a polynucleotide according to the invention suitable for producing these proteins.

Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion

PubMed Central

Thomsen, Martin Christen Frølund; Nielsen, Morten

2012-01-01

Seq2Logo is a web-based sequence logo generator. Sequence logos are a graphical representation of the information content stored in a multiple sequence alignment (MSA) and provide a compact and highly intuitive representation of the position-specific amino acid composition of binding motifs, active sites, etc. in biological sequences. Accurate generation of sequence logos is often compromised by sequence redundancy and low number of observations. Moreover, most methods available for sequence logo generation focus on displaying the position-specific enrichment of amino acids, discarding the equally valuable information related to amino acid depletion. Seq2logo aims at resolving these issues allowing the user to include sequence weighting to correct for data redundancy, pseudo counts to correct for low number of observations and different logotype representations each capturing different aspects related to amino acid enrichment and depletion. Besides allowing input in the format of peptides and MSA, Seq2Logo accepts input as Blast sequence profiles, providing easy access for non-expert end-users to characterize and identify functionally conserved/variable amino acids in any given protein of interest. The output from the server is a sequence logo and a PSSM. Seq2Logo is available at http://www.cbs.dtu.dk/biotools/Seq2Logo (14 May 2012, date last accessed). PMID:22638583

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

PubMed Central

Villacreses, Javier; Rojas-Herrera, Marcelo; Sánchez, Carolina; Hewstone, Nicole; Undurraga, Soledad F.; Alzate, Juan F.; Manque, Patricio; Maracaja-Coutinho, Vinicius; Polanco, Victor

2015-01-01

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. PMID:25855242

In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

EPA Science Inventory

The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

GRID-seq reveals the global RNA-chromatin interactome

PubMed Central

Li, Xiao; Zhou, Bing; Chen, Liang; Gou, Lan-Tao; Li, Hairi; Fu, Xiang-Dong

2017-01-01

Higher eukaryotic genomes are bound by a large number of coding and non-coding RNAs, but approaches to comprehensively map the identity and binding sites of these RNAs are lacking. Here we report a method to in situ capture global RNA interactions with DNA by deep sequencing (GRID-seq), which enables the comprehensive identification of the entire repertoire of chromatin-interacting RNAs and their respective binding sites. In human, mouse and Drosophila cells, we detected a large set of tissue-specific coding and non-coding RNAs that are bound to active promoters and enhancers, especially super-enhancers. Assuming that most mRNA-chromatin interactions indicate the physical proximity of a promoter and an enhancer, we constructed a three-dimensional global connectivity map of promoters and enhancers, revealing transcription activity-linked genomic interactions in the nucleus. PMID:28922346

Dopamine Signaling Leads to Loss of Polycomb Repression and Aberrant Gene Activation in Experimental Parkinsonism

PubMed Central

Lerdrup, Mads; Gomes, Ana-Luisa; Kryh, Hanna; Spigolon, Giada; Caboche, Jocelyne; Fisone, Gilberto; Hansen, Klaus

2014-01-01

Polycomb group (PcG) proteins bind to and repress genes in embryonic stem cells through lineage commitment to the terminal differentiated state. PcG repressed genes are commonly characterized by the presence of the epigenetic histone mark H3K27me3, catalyzed by the Polycomb repressive complex 2. Here, we present in vivo evidence for a previously unrecognized plasticity of PcG-repressed genes in terminally differentiated brain neurons of parkisonian mice. We show that acute administration of the dopamine precursor, L-DOPA, induces a remarkable increase in H3K27me3S28 phosphorylation. The induction of the H3K27me3S28p histone mark specifically occurs in medium spiny neurons expressing dopamine D1 receptors and is dependent on Msk1 kinase activity and DARPP-32-mediated inhibition of protein phosphatase-1. Chromatin immunoprecipitation (ChIP) experiments showed that increased H3K27me3S28p was accompanied by reduced PcG binding to regulatory regions of genes. An analysis of the genome wide distribution of L-DOPA-induced H3K27me3S28 phosphorylation by ChIP sequencing (ChIP-seq) in combination with expression analysis by RNA-sequencing (RNA-seq) showed that the induction of H3K27me3S28p correlated with increased expression of a subset of PcG repressed genes. We found that induction of H3K27me3S28p persisted during chronic L-DOPA administration to parkisonian mice and correlated with aberrant gene expression. We propose that dopaminergic transmission can activate PcG repressed genes in the adult brain and thereby contribute to long-term maladaptive responses including the motor complications, or dyskinesia, caused by prolonged administration of L-DOPA in Parkinson's disease. PMID:25254549

mRNA-Seq Reveals Novel Molecular Mechanisms and a Robust Fingerprint in Graves' Disease

PubMed Central

Sachidanandam, Ravi; Morshed, Syed; Latif, Rauf; Shi, Ruijin; Davies, Terry F.

2014-01-01

Context: The immune response in autoimmune thyroid disease has been shown to occur primarily within the thyroid gland in which the most abundant antigens can be found. A variety of capture molecules are known to be expressed by thyroid epithelial cells and serve to attract and help retain an intrathyroidal immune infiltrate. Objective: To explore the entire repertoire of expressed genes in human thyroid tissue, we have deep sequenced the transcriptome (referred to as mRNA-Seq). Design and Patients: We applied mRNA-Seq to thyroid tissue from nine patients with Graves' disease subjected to total thyroidectomy and compared the data with 12 samples of normal thyroid tissue obtained from patients having a thyroid nodule removed. The expression for each gene was calculated from the sequencing data by taking the median of the coverage across the length of the gene. The expression levels were quantile normalized and a gene signature was derived from these. Results: On comparison of expression levels in tissues derived from Graves' patients and controls, there was clear evidence for overexpression of the antigen presentation pathway consisting of HLA and associated genes. We also found a robust disease signature and discovered active innate and adaptive immune signaling networks. Conclusions: These data reveal an active immune defense system in Graves' disease, which involves novel molecular mechanisms in its pathogenesis and development. PMID:24971664

Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation.

PubMed

O'Leary, Nuala A; Wright, Mathew W; Brister, J Rodney; Ciufo, Stacy; Haddad, Diana; McVeigh, Rich; Rajput, Bhanu; Robbertse, Barbara; Smith-White, Brian; Ako-Adjei, Danso; Astashyn, Alexander; Badretdin, Azat; Bao, Yiming; Blinkova, Olga; Brover, Vyacheslav; Chetvernin, Vyacheslav; Choi, Jinna; Cox, Eric; Ermolaeva, Olga; Farrell, Catherine M; Goldfarb, Tamara; Gupta, Tripti; Haft, Daniel; Hatcher, Eneida; Hlavina, Wratko; Joardar, Vinita S; Kodali, Vamsi K; Li, Wenjun; Maglott, Donna; Masterson, Patrick; McGarvey, Kelly M; Murphy, Michael R; O'Neill, Kathleen; Pujar, Shashikant; Rangwala, Sanjida H; Rausch, Daniel; Riddick, Lillian D; Schoch, Conrad; Shkeda, Andrei; Storz, Susan S; Sun, Hanzhen; Thibaud-Nissen, Francoise; Tolstoy, Igor; Tully, Raymond E; Vatsan, Anjana R; Wallin, Craig; Webb, David; Wu, Wendy; Landrum, Melissa J; Kimchi, Avi; Tatusova, Tatiana; DiCuccio, Michael; Kitts, Paul; Murphy, Terence D; Pruitt, Kim D

2016-01-04

The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Identifying EGFR-Expressed Cells and Detecting EGFR Multi-Mutations at Single-Cell Level by Microfluidic Chip

NASA Astrophysics Data System (ADS)

Li, Ren; Zhou, Mingxing; Li, Jine; Wang, Zihua; Zhang, Weikai; Yue, Chunyan; Ma, Yan; Peng, Hailin; Wei, Zewen; Hu, Zhiyuan

2018-03-01

EGFR mutations companion diagnostics have been proved to be crucial for the efficacy of tyrosine kinase inhibitor targeted cancer therapies. To uncover multiple mutations occurred in minority of EGFR-mutated cells, which may be covered by the noises from majority of un-mutated cells, is currently becoming an urgent clinical requirement. Here we present the validation of a microfluidic-chip-based method for detecting EGFR multi-mutations at single-cell level. By trapping and immunofluorescently imaging single cells in specifically designed silicon microwells, the EGFR-expressed cells were easily identified. By in situ lysing single cells, the cell lysates of EGFR-expressed cells were retrieved without cross-contamination. Benefited from excluding the noise from cells without EGFR expression, the simple and cost-effective Sanger's sequencing, but not the expensive deep sequencing of the whole cell population, was used to discover multi-mutations. We verified the new method with precisely discovering three most important EGFR drug-related mutations from a sample in which EGFR-mutated cells only account for a small percentage of whole cell population. The microfluidic chip is capable of discovering not only the existence of specific EGFR multi-mutations, but also other valuable single-cell-level information: on which specific cells the mutations occurred, or whether different mutations coexist on the same cells. This microfluidic chip constitutes a promising method to promote simple and cost-effective Sanger's sequencing to be a routine test before performing targeted cancer therapy.[Figure not available: see fulltext.

Diff-seq: A high throughput sequencing-based mismatch detection assay for DNA variant enrichment and discovery

PubMed Central

Karas, Vlad O; Sinnott-Armstrong, Nicholas A; Varghese, Vici; Shafer, Robert W; Greenleaf, William J; Sherlock, Gavin

2018-01-01

Abstract Much of the within species genetic variation is in the form of single nucleotide polymorphisms (SNPs), typically detected by whole genome sequencing (WGS) or microarray-based technologies. However, WGS produces mostly uninformative reads that perfectly match the reference, while microarrays require genome-specific reagents. We have developed Diff-seq, a sequencing-based mismatch detection assay for SNP discovery without the requirement for specialized nucleic-acid reagents. Diff-seq leverages the Surveyor endonuclease to cleave mismatched DNA molecules that are generated after cross-annealing of a complex pool of DNA fragments. Sequencing libraries enriched for Surveyor-cleaved molecules result in increased coverage at the variant sites. Diff-seq detected all mismatches present in an initial test substrate, with specific enrichment dependent on the identity and context of the variation. Application to viral sequences resulted in increased observation of variant alleles in a biologically relevant context. Diff-Seq has the potential to increase the sensitivity and efficiency of high-throughput sequencing in the detection of variation. PMID:29361139

Oasis: online analysis of small RNA deep sequencing data.

PubMed

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.

ePIANNO: ePIgenomics ANNOtation tool.

PubMed

Liu, Chia-Hsin; Ho, Bing-Ching; Chen, Chun-Ling; Chang, Ya-Hsuan; Hsu, Yi-Chiung; Li, Yu-Cheng; Yuan, Shin-Sheng; Huang, Yi-Huan; Chang, Chi-Sheng; Li, Ker-Chau; Chen, Hsuan-Yu

2016-01-01

Recently, with the development of next generation sequencing (NGS), the combination of chromatin immunoprecipitation (ChIP) and NGS, namely ChIP-seq, has become a powerful technique to capture potential genomic binding sites of regulatory factors, histone modifications and chromatin accessible regions. For most researchers, additional information including genomic variations on the TF binding site, allele frequency of variation between different populations, variation associated disease, and other neighbour TF binding sites are essential to generate a proper hypothesis or a meaningful conclusion. Many ChIP-seq datasets had been deposited on the public domain to help researchers make new discoveries. However, researches are often intimidated by the complexity of data structure and largeness of data volume. Such information would be more useful if they could be combined or downloaded with ChIP-seq data. To meet such demands, we built a webtool: ePIgenomic ANNOtation tool (ePIANNO, http://epianno.stat.sinica.edu.tw/index.html). ePIANNO is a web server that combines SNP information of populations (1000 Genomes Project) and gene-disease association information of GWAS (NHGRI) with ChIP-seq (hmChIP, ENCODE, and ROADMAP epigenomics) data. ePIANNO has a user-friendly website interface allowing researchers to explore, navigate, and extract data quickly. We use two examples to demonstrate how users could use functions of ePIANNO webserver to explore useful information about TF related genomic variants. Users could use our query functions to search target regions, transcription factors, or annotations. ePIANNO may help users to generate hypothesis or explore potential biological functions for their studies.

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

PubMed

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

2012-01-01

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

Detection of microRNAs in color space.

PubMed

Marco, Antonio; Griffiths-Jones, Sam

2012-02-01

Deep sequencing provides inexpensive opportunities to characterize the transcriptional diversity of known genomes. The AB SOLiD technology generates millions of short sequencing reads in color-space; that is, the raw data is a sequence of colors, where each color represents 2 nt and each nucleotide is represented by two consecutive colors. This strategy is purported to have several advantages, including increased ability to distinguish sequencing errors from polymorphisms. Several programs have been developed to map short reads to genomes in color space. However, a number of previously unexplored technical issues arise when using SOLiD technology to characterize microRNAs. Here we explore these technical difficulties. First, since the sequenced reads are longer than the biological sequences, every read is expected to contain linker fragments. The color-calling error rate increases toward the 3(') end of the read such that recognizing the linker sequence for removal becomes problematic. Second, mapping in color space may lead to the loss of the first nucleotide of each read. We propose a sequential trimming and mapping approach to map small RNAs. Using our strategy, we reanalyze three published insect small RNA deep sequencing datasets and characterize 22 new microRNAs. A bash shell script to perform the sequential trimming and mapping procedure, called SeqTrimMap, is available at: http://www.mirbase.org/tools/seqtrimmap/ antonio.marco@manchester.ac.uk Supplementary data are available at Bioinformatics online.

BAsE-Seq: a method for obtaining long viral haplotypes from short sequence reads.

PubMed

Hong, Lewis Z; Hong, Shuzhen; Wong, Han Teng; Aw, Pauline P K; Cheng, Yan; Wilm, Andreas; de Sessions, Paola F; Lim, Seng Gee; Nagarajan, Niranjan; Hibberd, Martin L; Quake, Stephen R; Burkholder, William F

2014-01-01

We present a method for obtaining long haplotypes, of over 3 kb in length, using a short-read sequencer, Barcode-directed Assembly for Extra-long Sequences (BAsE-Seq). BAsE-Seq relies on transposing a template-specific barcode onto random segments of the template molecule and assembling the barcoded short reads into complete haplotypes. We applied BAsE-Seq on mixed clones of hepatitis B virus and accurately identified haplotypes occurring at frequencies greater than or equal to 0.4%, with >99.9% specificity. Applying BAsE-Seq to a clinical sample, we obtained over 9,000 viral haplotypes, which provided an unprecedented view of hepatitis B virus population structure during chronic infection. BAsE-Seq is readily applicable for monitoring quasispecies evolution in viral diseases.

Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs.

PubMed

Hayashi, Tetsutaro; Ozaki, Haruka; Sasagawa, Yohei; Umeda, Mana; Danno, Hiroki; Nikaido, Itoshi

2018-02-12

Total RNA sequencing has been used to reveal poly(A) and non-poly(A) RNA expression, RNA processing and enhancer activity. To date, no method for full-length total RNA sequencing of single cells has been developed despite the potential of this technology for single-cell biology. Here we describe random displacement amplification sequencing (RamDA-seq), the first full-length total RNA-sequencing method for single cells. Compared with other methods, RamDA-seq shows high sensitivity to non-poly(A) RNA and near-complete full-length transcript coverage. Using RamDA-seq with differentiation time course samples of mouse embryonic stem cells, we reveal hundreds of dynamically regulated non-poly(A) transcripts, including histone transcripts and long noncoding RNA Neat1. Moreover, RamDA-seq profiles recursive splicing in >300-kb introns. RamDA-seq also detects enhancer RNAs and their cell type-specific activity in single cells. Taken together, we demonstrate that RamDA-seq could help investigate the dynamics of gene expression, RNA-processing events and transcriptional regulation in single cells.

Deep developmental transcriptome sequencing uncovers numerous new genes and enhances gene annotation in the sponge Amphimedon queenslandica.

PubMed

Fernandez-Valverde, Selene L; Calcino, Andrew D; Degnan, Bernard M

2015-05-15

The demosponge Amphimedon queenslandica is amongst the few early-branching metazoans with an assembled and annotated draft genome, making it an important species in the study of the origin and early evolution of animals. Current gene models in this species are largely based on in silico predictions and low coverage expressed sequence tag (EST) evidence. Amphimedon queenslandica protein-coding gene models are improved using deep RNA-Seq data from four developmental stages and CEL-Seq data from 82 developmental samples. Over 86% of previously predicted genes are retained in the new gene models, although 24% have additional exons; there is also a marked increase in the total number of annotated 3' and 5' untranslated regions (UTRs). Importantly, these new developmental transcriptome data reveal numerous previously unannotated protein-coding genes in the Amphimedon genome, increasing the total gene number by 25%, from 30,060 to 40,122. In general, Amphimedon genes have introns that are markedly smaller than those in other animals and most of the alternatively spliced genes in Amphimedon undergo intron-retention; exon-skipping is the least common mode of alternative splicing. Finally, in addition to canonical polyadenylation signal sequences, Amphimedon genes are enriched in a number of unique AT-rich motifs in their 3' UTRs. The inclusion of developmental transcriptome data has substantially improved the structure and composition of protein-coding gene models in Amphimedon queenslandica, providing a more accurate and comprehensive set of genes for functional and comparative studies. These improvements reveal the Amphimedon genome is comprised of a remarkably high number of tightly packed genes. These genes have small introns and there is pervasive intron retention amongst alternatively spliced transcripts. These aspects of the sponge genome are more similar unicellular opisthokont genomes than to other animal genomes.

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

PubMed Central

2011-01-01

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. PMID:21251255

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

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

PubMed

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.

Identification of microRNA-like RNAs from Curvularia lunata associated with maize leaf spot by bioinformation analysis and deep sequencing.

PubMed

Liu, Tong; Hu, John; Zuo, Yuhu; Jin, Yazhong; Hou, Jumei

2016-04-01

Deep sequencing of small RNAs is a useful tool to identify novel small RNAs that may be involved in fungal growth and pathogenesis. In this study, we used HiSeq deep sequencing to identify 747,487 unique small RNAs from Curvularia lunata. Among these small RNAs were 1012 microRNA-like RNAs (milRNAs), which are similar to other known microRNAs, and 48 potential novel milRNAs without homologs in other organisms have been identified using the miRBase© database. We used quantitative PCR to analyze the expression of four of these milRNAs from C. lunata at different developmental stages. The analysis revealed several changes associated with germinating conidia and mycelial growth, suggesting that these milRNAs may play a role in pathogen infection and mycelial growth. A total of 8334 target mRNAs for the 1012 milRNAs that were identified, and 256 target mRNAs for the 48 novel milRNAs were predicted by computational analysis. These target mRNAs of milRNAs were also performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our knowledge, this study is the first report of C. lunata's milRNA profiles. This information will provide a better understanding of pathogen development and infection mechanism.

RNA-Seq for Bacterial Gene Expression.

PubMed

Poulsen, Line Dahl; Vinther, Jeppe

2018-06-01

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

Inferring nucleosome positions with their histone mark annotation from ChIP data

PubMed Central

Mammana, Alessandro; Vingron, Martin; Chung, Ho-Ryun

2013-01-01

Motivation: The nucleosome is the basic repeating unit of chromatin. It contains two copies each of the four core histones H2A, H2B, H3 and H4 and about 147 bp of DNA. The residues of the histone proteins are subject to numerous post-translational modifications, such as methylation or acetylation. Chromatin immunoprecipitiation followed by sequencing (ChIP-seq) is a technique that provides genome-wide occupancy data of these modified histone proteins, and it requires appropriate computational methods. Results: We present NucHunter, an algorithm that uses the data from ChIP-seq experiments directed against many histone modifications to infer positioned nucleosomes. NucHunter annotates each of these nucleosomes with the intensities of the histone modifications. We demonstrate that these annotations can be used to infer nucleosomal states with distinct correlations to underlying genomic features and chromatin-related processes, such as transcriptional start sites, enhancers, elongation by RNA polymerase II and chromatin-mediated repression. Thus, NucHunter is a versatile tool that can be used to predict positioned nucleosomes from a panel of histone modification ChIP-seq experiments and infer distinct histone modification patterns associated to different chromatin states. Availability: The software is available at http://epigen.molgen.mpg.de/nuchunter/. Contact: chung@molgen.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23981350

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)-A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes.

PubMed

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare . However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop plants with large and complex genomes.

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

PubMed Central

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop plants with large and complex genomes. PMID:29250096

Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

PubMed Central

2015-01-01

Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects should be carefully taken into account before using metabarcoding in quantitative ecological research and monitoring programmes of marine biodiversity. PMID:26701112

Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

PubMed

Dell'Anno, Antonio; Carugati, Laura; Corinaldesi, Cinzia; Riccioni, Giulia; Danovaro, Roberto

2015-01-01

Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects should be carefully taken into account before using metabarcoding in quantitative ecological research and monitoring programmes of marine biodiversity.

Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data

PubMed Central

Carroll, Thomas S.; Liang, Ziwei; Salama, Rafik; Stark, Rory; de Santiago, Ines

2014-01-01

With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium's large scale analysis of transcription factor binding and epigenetic marks as well as concordant work on ChIP-seq by other laboratories has established a new generation of ChIP-seq quality control measures. The use of these metrics alongside common processing steps has however not been evaluated. In this study, we investigate the effects of blacklisting and removal of duplicated reads on established metrics of ChIP-seq quality and show that the interpretation of these metrics is highly dependent on the ChIP-seq preprocessing steps applied. Further to this we perform the first investigation of the use of these metrics for ChIP-exo data and make recommendations for the adaptation of the NSC statistic to allow for the assessment of ChIP-exo efficiency. PMID:24782889

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

PubMed

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

2018-03-09

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

Comparison of Next-Generation Sequencing Systems

PubMed Central

Liu, Lin; Li, Yinhu; Li, Siliang; Hu, Ni; He, Yimin; Pong, Ray; Lin, Danni; Lu, Lihua; Law, Maggie

2012-01-01

With fast development and wide applications of next-generation sequencing (NGS) technologies, genomic sequence information is within reach to aid the achievement of goals to decode life mysteries, make better crops, detect pathogens, and improve life qualities. NGS systems are typically represented by SOLiD/Ion Torrent PGM from Life Sciences, Genome Analyzer/HiSeq 2000/MiSeq from Illumina, and GS FLX Titanium/GS Junior from Roche. Beijing Genomics Institute (BGI), which possesses the world's biggest sequencing capacity, has multiple NGS systems including 137 HiSeq 2000, 27 SOLiD, one Ion Torrent PGM, one MiSeq, and one 454 sequencer. We have accumulated extensive experience in sample handling, sequencing, and bioinformatics analysis. In this paper, technologies of these systems are reviewed, and first-hand data from extensive experience is summarized and analyzed to discuss the advantages and specifics associated with each sequencing system. At last, applications of NGS are summarized. PMID:22829749

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

PubMed

Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

2014-01-01

Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances ChIP-seq data analysis and allows the identification of multiple SUMOylated TF binding sites simultaneously, which can then be utilized for other functional PTM binding site prediction in future.

Rapid Response of Eastern Mediterranean Deep Sea Microbial Communities to Oil

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

Liu, Jiang; Techtmann, Stephen M.; Woo, Hannah L.

Deep marine oil spills like the Deepwater Horizon (DWH) in the Gulf of Mexico have the potential to drastically impact marine systems. Crude oil contamination in marine systems remains a concern, especially for countries around the Mediterranean Sea with off shore oil production. The goal of this study was to investigate the response of indigenous microbial communities to crude oil in the deep Eastern Mediterranean Sea (E. Med.) water column and to minimize potential bias associated with storage and shifts in microbial community structure from sample storage. 16S rRNA amplicon sequencing was combined with GeoChip metagenomic analysis to monitor themore » microbial community changes to the crude oil and dispersant in on-ship microcosms set up immediately after water collection. After 3 days of incubation at 14 °C, the microbial communities from two different water depths: 824 m and 1210 m became dominated by well-known oil degrading bacteria. The archaeal population and the overall microbial community diversity drastically decreased. Similarly, GeoChip metagenomic analysis revealed a tremendous enrichment of genes related to oil biodegradation, which was consistent with the results from the DWH oil spill. These results highlight a rapid microbial adaption to oil contamination in the deep E. Med., and indicate strong oil biodegradation potentia« less

Whole-Exome Sequencing in a South American Cohort Links ALDH1A3, FOXN1 and Retinoic Acid Regulation Pathways to Autism Spectrum Disorders

PubMed Central

Moreno-Ramos, Oscar A.; Olivares, Ana María; Haider, Neena B.; de Autismo, Liga Colombiana; Lattig, María Claudia

2015-01-01

Autism spectrum disorders (ASDs) are a range of complex neurodevelopmental conditions principally characterized by dysfunctions linked to mental development. Previous studies have shown that there are more than 1000 genes likely involved in ASD, expressed mainly in brain and highly interconnected among them. We applied whole exome sequencing in Colombian—South American trios. Two missense novel SNVs were found in the same child: ALDH1A3 (RefSeq NM_000693: c.1514T>C (p.I505T)) and FOXN1 (RefSeq NM_003593: c.146C>T (p.S49L)). Gene expression studies reveal that Aldh1a3 and Foxn1 are expressed in ~E13.5 mouse embryonic brain, as well as in adult piriform cortex (PC; ~P30). Conserved Retinoic Acid Response Elements (RAREs) upstream of human ALDH1A3 and FOXN1 and in mouse Aldh1a3 and Foxn1 genes were revealed using bioinformatic approximation. Chromatin immunoprecipitation (ChIP) assay using Retinoid Acid Receptor B (Rarb) as the immunoprecipitation target suggests RA regulation of Aldh1a3 and Foxn1 in mice. Our results frame a possible link of RA regulation in brain to ASD etiology, and a feasible non-additive effect of two apparently unrelated variants in ALDH1A3 and FOXN1 recognizing that every result given by next generation sequencing should be cautiously analyzed, as it might be an incidental finding. PMID:26352270

A Transcriptome Map of Actinobacillus pleuropneumoniae at Single-Nucleotide Resolution Using Deep RNA-Seq

PubMed Central

Su, Zhipeng; Zhu, Jiawen; Xu, Zhuofei; Xiao, Ran; Zhou, Rui; Li, Lu; Chen, Huanchun

2016-01-01

Actinobacillus pleuropneumoniae is the pathogen of porcine contagious pleuropneumoniae, a highly contagious respiratory disease of swine. Although the genome of A. pleuropneumoniae was sequenced several years ago, limited information is available on the genome-wide transcriptional analysis to accurately annotate the gene structures and regulatory elements. High-throughput RNA sequencing (RNA-seq) has been applied to study the transcriptional landscape of bacteria, which can efficiently and accurately identify gene expression regions and unknown transcriptional units, especially small non-coding RNAs (sRNAs), UTRs and regulatory regions. The aim of this study is to comprehensively analyze the transcriptome of A. pleuropneumoniae by RNA-seq in order to improve the existing genome annotation and promote our understanding of A. pleuropneumoniae gene structures and RNA-based regulation. In this study, we utilized RNA-seq to construct a single nucleotide resolution transcriptome map of A. pleuropneumoniae. More than 3.8 million high-quality reads (average length ~90 bp) from a cDNA library were generated and aligned to the reference genome. We identified 32 open reading frames encoding novel proteins that were mis-annotated in the previous genome annotations. The start sites for 35 genes based on the current genome annotation were corrected. Furthermore, 51 sRNAs in the A. pleuropneumoniae genome were discovered, of which 40 sRNAs were never reported in previous studies. The transcriptome map also enabled visualization of 5'- and 3'-UTR regions, in which contained 11 sRNAs. In addition, 351 operons covering 1230 genes throughout the whole genome were identified. The RNA-Seq based transcriptome map validated annotated genes and corrected annotations of open reading frames in the genome, and led to the identification of many functional elements (e.g. regions encoding novel proteins, non-coding sRNAs and operon structures). The transcriptional units described in this study provide a foundation for future studies concerning the gene functions and the transcriptional regulatory architectures of this pathogen. PMID:27018591

RNA-Seq Technology and Its Application in Fish Transcriptomics

PubMed Central

Ba, Yi; Zhuang, Qianfeng

2014-01-01

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

Additional annotation of the pig transcriptome using integrated Iso-seq and Illumina RNA-seq analysis

USDA-ARS?s Scientific Manuscript database

Alternative splicing is a well-known phenomenon that dramatically increases eukaryotic transcriptome diversity. The extent of mRNA isoform diversity among porcine tissues was assessed using Pacific Biosciences single-molecule long-read isoform sequencing (Iso-Seq) and Illumina short read sequencing ...

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

PubMed Central

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G.; Rigoutsos, Isidore

2017-01-01

Abstract Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. PMID:28108659

Bacterial and archaeal communities in the deep-sea sediments of inactive hydrothermal vents in the Southwest India Ridge

NASA Astrophysics Data System (ADS)

Zhang, Likui; Kang, Manyu; Xu, Jiajun; Xu, Jian; Shuai, Yinjie; Zhou, Xiaojian; Yang, Zhihui; Ma, Kesen

2016-05-01

Active deep-sea hydrothermal vents harbor abundant thermophilic and hyperthermophilic microorganisms. However, microbial communities in inactive hydrothermal vents have not been well documented. Here, we investigated bacterial and archaeal communities in the two deep-sea sediments (named as TVG4 and TVG11) collected from inactive hydrothermal vents in the Southwest India Ridge using the high-throughput sequencing technology of Illumina MiSeq2500 platform. Based on the V4 region of 16S rRNA gene, sequence analysis showed that bacterial communities in the two samples were dominated by Proteobacteria, followed by Bacteroidetes, Actinobacteria and Firmicutes. Furthermore, archaeal communities in the two samples were dominated by Thaumarchaeota and Euryarchaeota. Comparative analysis showed that (i) TVG4 displayed the higher bacterial richness and lower archaeal richness than TVG11; (ii) the two samples had more divergence in archaeal communities than bacterial communities. Bacteria and archaea that are potentially associated with nitrogen, sulfur metal and methane cycling were detected in the two samples. Overall, we first provided a comparative picture of bacterial and archaeal communities and revealed their potentially ecological roles in the deep-sea environments of inactive hydrothermal vents in the Southwest Indian Ridge, augmenting microbial communities in inactive hydrothermal vents.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

PubMed

Madrigal, Pedro

2017-03-01

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Human jagged polypeptide, encoding nucleic acids and methods of use

DOEpatents

Li, Linheng; Hood, Leroy

2000-01-01

The present invention provides an isolated polypeptide exhibiting substantially the same amino acid sequence as JAGGED, or an active fragment thereof, provided that the polypeptide does not have the amino acid sequence of SEQ ID NO:5 or SEQ ID NO:6. The invention further provides an isolated nucleic acid molecule containing a nucleotide sequence encoding substantially the same amino acid sequence as JAGGED, or an active fragment thereof, provided that the nucleotide sequence does not encode the amino acid sequence of SEQ ID NO:5 or SEQ ID NO:6. Also provided herein is a method of inhibiting differentiation of hematopoietic progenitor cells by contacting the progenitor cells with an isolated JAGGED polypeptide, or active fragment thereof. The invention additionally provides a method of diagnosing Alagille Syndrome in an individual. The method consists of detecting an Alagille Syndrome disease-associated mutation linked to a JAGGED locus.

Methods of diagnosing alagille syndrome

DOEpatents

Li, Linheng; Hood, Leroy; Krantz, Ian D.; Spinner, Nancy B.

2004-03-09

The present invention provides an isolated polypeptide exhibiting substantially the same amino acid sequence as JAGGED, or an active fragment thereof, provided that the polypeptide does not have the amino acid sequence of SEQ ID NO:5 or SEQ ID NO:6. The invention further provides an isolated nucleic acid molecule containing a nucleotide sequence encoding substantially the same amino acid sequence as JAGGED, or an active fragment thereof, provided that the nucleotide sequence does not encode the amino acid sequence of SEQ ID NO:5 or SEQ ID NO:6. Also provided herein is a method of inhibiting differentiation of hematopoietic progenitor cells by contacting the progenitor cells with an isolated JAGGED polypeptide, or active fragment thereof. The invention additionally provides a method of diagnosing Alagille Syndrome in an individual. The method consists of detecting an Alagille Syndrome disease-associated mutation linked to a JAGGED locus.

DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

PubMed

Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh

2017-01-01

A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.

Advances in single-cell RNA sequencing and its applications in cancer research.

PubMed

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-08-08

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years' development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5.

Advances in single-cell RNA sequencing and its applications in cancer research

PubMed Central

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-01-01

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5. Perspectives PMID:28881849

A weighted U-statistic for genetic association analyses of sequencing data.

PubMed

Wei, Changshuai; Li, Ming; He, Zihuai; Vsevolozhskaya, Olga; Schaid, Daniel J; Lu, Qing

2014-12-01

With advancements in next-generation sequencing technology, a massive amount of sequencing data is generated, which offers a great opportunity to comprehensively investigate the role of rare variants in the genetic etiology of complex diseases. Nevertheless, the high-dimensional sequencing data poses a great challenge for statistical analysis. The association analyses based on traditional statistical methods suffer substantial power loss because of the low frequency of genetic variants and the extremely high dimensionality of the data. We developed a Weighted U Sequencing test, referred to as WU-SEQ, for the high-dimensional association analysis of sequencing data. Based on a nonparametric U-statistic, WU-SEQ makes no assumption of the underlying disease model and phenotype distribution, and can be applied to a variety of phenotypes. Through simulation studies and an empirical study, we showed that WU-SEQ outperformed a commonly used sequence kernel association test (SKAT) method when the underlying assumptions were violated (e.g., the phenotype followed a heavy-tailed distribution). Even when the assumptions were satisfied, WU-SEQ still attained comparable performance to SKAT. Finally, we applied WU-SEQ to sequencing data from the Dallas Heart Study (DHS), and detected an association between ANGPTL 4 and very low density lipoprotein cholesterol. © 2014 WILEY PERIODICALS, INC.

Library construction for next-generation sequencing: Overviews and challenges

PubMed Central

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

2014-01-01

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

A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers.

PubMed

Quail, Michael A; Smith, Miriam; Coupland, Paul; Otto, Thomas D; Harris, Simon R; Connor, Thomas R; Bertoni, Anna; Swerdlow, Harold P; Gu, Yong

2012-07-24

Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent's PGM, Pacific Biosciences' RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

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

PubMed

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

2015-12-16

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

iSeq: Web-Based RNA-seq Data Analysis and Visualization.

PubMed

Zhang, Chao; Fan, Caoqi; Gan, Jingbo; Zhu, Ping; Kong, Lei; Li, Cheng

2018-01-01

Transcriptome sequencing (RNA-seq) is becoming a standard experimental methodology for genome-wide characterization and quantification of transcripts at single base-pair resolution. However, downstream analysis of massive amount of sequencing data can be prohibitively technical for wet-lab researchers. A functionally integrated and user-friendly platform is required to meet this demand. Here, we present iSeq, an R-based Web server, for RNA-seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyze their RNA-seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. iSeq is accessible via Web browsers on any operating system at http://iseq.cbi.pku.edu.cn .

A quantitative and qualitative comparison of illumina MiSeq and 454 amplicon sequencing for genotyping the highly polymorphic major histocompatibility complex (MHC) in a non-model species.

PubMed

Razali, Haslina; O'Connor, Emily; Drews, Anna; Burke, Terry; Westerdahl, Helena

2017-07-28

High-throughput sequencing enables high-resolution genotyping of extremely duplicated genes. 454 amplicon sequencing (454) has become the standard technique for genotyping the major histocompatibility complex (MHC) genes in non-model organisms. However, illumina MiSeq amplicon sequencing (MiSeq), which offers a much higher read depth, is now superseding 454. The aim of this study was to quantitatively and qualitatively evaluate the performance of MiSeq in relation to 454 for genotyping MHC class I alleles using a house sparrow (Passer domesticus) dataset with pedigree information. House sparrows provide a good study system for this comparison as their MHC class I genes have been studied previously and, consequently, we had prior expectations concerning the number of alleles per individual. We found that 454 and MiSeq performed equally well in genotyping amplicons with low diversity, i.e. amplicons from individuals that had fewer than 6 alleles. Although there was a higher rate of failure in the 454 dataset in resolving amplicons with higher diversity (6-9 alleles), the same genotypes were identified by both 454 and MiSeq in 98% of cases. We conclude that low diversity amplicons are equally well genotyped using either 454 or MiSeq, but the higher coverage afforded by MiSeq can lead to this approach outperforming 454 in amplicons with higher diversity.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

PubMed

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G; Rigoutsos, Isidore; Kirino, Yohei

2017-05-19

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed Central

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

2015-01-01

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

Network analysis of ChIP-Seq data reveals key genes in prostate cancer.

PubMed

Zhang, Yu; Huang, Zhen; Zhu, Zhiqiang; Liu, Jianwei; Zheng, Xin; Zhang, Yuhai

2014-09-03

Prostate cancer (PC) is the second most common cancer among men in the United States, and it imposes a considerable threat to human health. A deep understanding of its underlying molecular mechanisms is the premise for developing effective targeted therapies. Recently, deep transcriptional sequencing has been used as an effective genomic assay to obtain insights into diseases and may be helpful in the study of PC. In present study, ChIP-Seq data for PC and normal samples were compared, and differential peaks identified, based upon fold changes (with P-values calculated with t-tests). Annotations of these peaks were performed. Protein-protein interaction (PPI) network analysis was performed with BioGRID and constructed with Cytoscape, following which the highly connected genes were screened. We obtained a total of 5,570 differential peaks, including 3,726 differentially enriched peaks in tumor samples and 1,844 differentially enriched peaks in normal samples. There were eight significant regions of the peaks. The intergenic region possessed the highest score (51%), followed by intronic (31%) and exonic (11%) regions. The analysis revealed the top 35 highly connected genes, which comprised 33 differential genes (such as YWHAQ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein and θ polypeptide) from ChIP-Seq data and 2 differential genes retrieved from the PPI network: UBA52 (ubiquitin A-52 residue ribosomal protein fusion product (1) and SUMO2 (SMT3 suppressor of mif two 3 homolog (2) . Our findings regarding potential PC-related genes increase the understanding of PC and provides direction for future research.

A Concise Atlas of Thyroid Cancer Next-Generation Sequencing Panel ThyroSeq v.2

PubMed Central

Alsina, Jorge; Alsina, Raul; Gulec, Seza

2017-01-01

The next-generation sequencing technology allows high out-put genomic analysis. An innovative assay in thyroid cancer, ThyroSeq® was developed for targeted mutation detection by next generation sequencing technology in fine needle aspiration and tissue samples. ThyroSeq v.2 next generation sequencing panel offers simultaneous sequencing and detection in >1000 hotspots of 14 thyroid cancer-related genes and for 42 types of gene fusions known to occur in thyroid cancer. ThyroSeq is being increasingly used to further narrow the indeterminate category defined by cytology for thyroid nodules. From a surgical perspective, genomic profiling also provides prognostic and predictive information and closely relates to determination of surgical strategy. Both the genomic analysis technology and the informatics for the cancer genome data base are rapidly developing. In this paper, we have gathered existing information on the thyroid cancer-related genes involved in the initiation and progression of thyroid cancer. Our goal is to assemble a glossary for the current ThyroSeq genomic panel that can help elucidate the role genomics play in thyroid cancer oncogenesis. PMID:28117295

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

PubMed

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

2017-12-12

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

LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias.

PubMed

Johansen, Christopher T; Dubé, Joseph B; Loyzer, Melissa N; MacDonald, Austin; Carter, David E; McIntyre, Adam D; Cao, Henian; Wang, Jian; Robinson, John F; Hegele, Robert A

2014-04-01

We report the design of a targeted resequencing panel for monogenic dyslipidemias, LipidSeq, for the purpose of replacing Sanger sequencing in the clinical detection of dyslipidemia-causing variants. We also evaluate the performance of the LipidSeq approach versus Sanger sequencing in 84 patients with a range of phenotypes including extreme blood lipid concentrations as well as additional dyslipidemias and related metabolic disorders. The panel performs well, with high concordance (95.2%) in samples with known mutations based on Sanger sequencing and a high detection rate (57.9%) of mutations likely to be causative for disease in samples not previously sequenced. Clinical implementation of LipidSeq has the potential to aid in the molecular diagnosis of patients with monogenic dyslipidemias with a high degree of speed and accuracy and at lower cost than either Sanger sequencing or whole exome sequencing. Furthermore, LipidSeq will help to provide a more focused picture of monogenic and polygenic contributors that underlie dyslipidemia while excluding the discovery of incidental pathogenic clinically actionable variants in nonmetabolism-related genes, such as oncogenes, that would otherwise be identified by a whole exome approach, thus minimizing potential ethical issues.

LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias[S

PubMed Central

Johansen, Christopher T.; Dubé, Joseph B.; Loyzer, Melissa N.; MacDonald, Austin; Carter, David E.; McIntyre, Adam D.; Cao, Henian; Wang, Jian; Robinson, John F.; Hegele, Robert A.

2014-01-01

We report the design of a targeted resequencing panel for monogenic dyslipidemias, LipidSeq, for the purpose of replacing Sanger sequencing in the clinical detection of dyslipidemia-causing variants. We also evaluate the performance of the LipidSeq approach versus Sanger sequencing in 84 patients with a range of phenotypes including extreme blood lipid concentrations as well as additional dyslipidemias and related metabolic disorders. The panel performs well, with high concordance (95.2%) in samples with known mutations based on Sanger sequencing and a high detection rate (57.9%) of mutations likely to be causative for disease in samples not previously sequenced. Clinical implementation of LipidSeq has the potential to aid in the molecular diagnosis of patients with monogenic dyslipidemias with a high degree of speed and accuracy and at lower cost than either Sanger sequencing or whole exome sequencing. Furthermore, LipidSeq will help to provide a more focused picture of monogenic and polygenic contributors that underlie dyslipidemia while excluding the discovery of incidental pathogenic clinically actionable variants in nonmetabolism-related genes, such as oncogenes, that would otherwise be identified by a whole exome approach, thus minimizing potential ethical issues. PMID:24503134

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

PubMed

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

2018-04-15

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

Evaluation of the utility of the new rainbow trout genome assembly for analyzing RNA-seq data from stress response experiments

USDA-ARS?s Scientific Manuscript database

The newly released rainbow trout genome assembly in NCBI RefSeq has greatly expanded our abilities for analyzing rainbow trout sequencing data. In this poster, we evaluate the utility of this genome assembly for analyzing RNA sequencing (RNA-seq) data of rainbow trout responses to various stressors,...

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

PubMed Central

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

2016-01-01

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

PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data

PubMed Central

Zhang, Yanju; Lameijer, Eric-Wubbo; 't Hoen, Peter A. C.; Ning, Zemin; Slagboom, P. Eline; Ye, Kai

2012-01-01

Motivation: RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon–exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge. Results: We developed PASSion, a pattern growth algorithm-based pipeline for splice site detection in paired-end RNA-Seq reads. Comparing the performance of PASSion to three existing RNA-Seq analysis pipelines, TopHat, MapSplice and HMMSplicer, revealed that PASSion is competitive with these packages. Moreover, the performance of PASSion is not affected by read length and coverage. It performs better than the other three approaches when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools. Of the two public RNA-Seq datasets, PASSion predicted ∼ 137 000 and 173 000 splicing events, of which on average 82 are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, our package can discover differential and shared splicing patterns among multiple samples. Availability: The code and utilities can be freely downloaded from https://trac.nbic.nl/passion and ftp://ftp.sanger.ac.uk/pub/zn1/passion Contact: y.zhang@lumc.nl; k.ye@lumc.nl Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22219203

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Nebula--a web-server for advanced ChIP-seq data analysis.

PubMed

Boeva, Valentina; Lermine, Alban; Barette, Camille; Guillouf, Christel; Barillot, Emmanuel

2012-10-01

ChIP-seq consists of chromatin immunoprecipitation and deep sequencing of the extracted DNA fragments. It is the technique of choice for accurate characterization of the binding sites of transcription factors and other DNA-associated proteins. We present a web service, Nebula, which allows inexperienced users to perform a complete bioinformatics analysis of ChIP-seq data. Nebula was designed for both bioinformaticians and biologists. It is based on the Galaxy open source framework. Galaxy already includes a large number of functionalities for mapping reads and peak calling. We added the following to Galaxy: (i) peak calling with FindPeaks and a module for immunoprecipitation quality control, (ii) de novo motif discovery with ChIPMunk, (iii) calculation of the density and the cumulative distribution of peak locations relative to gene transcription start sites, (iv) annotation of peaks with genomic features and (v) annotation of genes with peak information. Nebula generates the graphs and the enrichment statistics at each step of the process. During Steps 3-5, Nebula optionally repeats the analysis on a control dataset and compares these results with those from the main dataset. Nebula can also incorporate gene expression (or gene modulation) data during these steps. In summary, Nebula is an innovative web service that provides an advanced ChIP-seq analysis pipeline providing ready-to-publish results. Nebula is available at http://nebula.curie.fr/ Supplementary data are available at Bioinformatics online.

How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data

PubMed Central

Kovaltsuk, Aleksandr; Krawczyk, Konrad; Galson, Jacob D.; Kelly, Dominic F.; Deane, Charlotte M.; Trück, Johannes

2017-01-01

Next-generation sequencing of immunoglobulin gene repertoires (Ig-seq) allows the investigation of large-scale antibody dynamics at a sequence level. However, structural information, a crucial descriptor of antibody binding capability, is not collected in Ig-seq protocols. Developing systematic relationships between the antibody sequence information gathered from Ig-seq and low-throughput techniques such as X-ray crystallography could radically improve our understanding of antibodies. The mapping of Ig-seq datasets to known antibody structures can indicate structurally, and perhaps functionally, uncharted areas. Furthermore, contrasting naïve and antigenically challenged datasets using structural antibody descriptors should provide insights into antibody maturation. As the number of antibody structures steadily increases and more and more Ig-seq datasets become available, the opportunities that arise from combining the two types of information increase as well. Here, we review how these data types enrich one another and show potential for advancing our knowledge of the immune system and improving antibody engineering. PMID:29276518

Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

PubMed Central

2011-01-01

Background Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. Methods We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. Results Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. Conclusions Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer. PMID:21261984

Analysis of miRNA expression profiles in melatonin-exposed GC-1 spg cell line.

PubMed

Zhu, Xiaoling; Chen, Shuxiong; Jiang, Yanwen; Xu, Ying; Zhao, Yun; Chen, Lu; Li, Chunjin; Zhou, Xu

2018-02-05

Melatonin is an endocrine neurohormone secreted by pinealocytes in the pineal gland. It exerts diverse physiological effects, such as circadian rhythm regulator and antioxidant. However, the functional importance of melatonin in spermatogenesis regulation remains unclear. The objectives of this study are to: (1) detect melatonin affection on miRNA expression profiles in GC-1 spg cells by miRNA deep sequencing (DeepSeq) and (2) define melatonin affected miRNA-mRNA interactions and associated biological processes using bioinformatics analysis. GC-1 spg cells were cultured with melatonin (10 -7 M) for 24h. DeepSeq data were validated using quantitative real-time reverse transcription polymerase chain reaction analysis (qRT-PCR). A total of 176 miRNA expressions were found to be significantly different between two groups (fold change of >2 or <0.5 and FDR<0.05). Among these expressions, 171 were up-regulated, and 5 were down-regulated. Ontology analysis of biological processes of these targets indicated a variety of biological functions. Pathway analysis indicated that the predicted targets were involved in cancers, apoptosis and signaling pathways, such as VEGF, TNF, Ras and Notch. Results implicated that melatonin could regulate the expression of miRNA to perform its physiological effects in GC-1 spg cells. These results should be useful to investigate the biological function of miRNAs regulated by melatonin in spermatogenesis and testicular germ cell tumor. Copyright © 2017 Elsevier B.V. All rights reserved.

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells.

PubMed

Wu, Liang; Zhang, Xiaolong; Zhao, Zhikun; Wang, Ling; Li, Bo; Li, Guibo; Dean, Michael; Yu, Qichao; Wang, Yanhui; Lin, Xinxin; Rao, Weijian; Mei, Zhanlong; Li, Yang; Jiang, Runze; Yang, Huan; Li, Fuqiang; Xie, Guoyun; Xu, Liqin; Wu, Kui; Zhang, Jie; Chen, Jianghao; Wang, Ting; Kristiansen, Karsten; Zhang, Xiuqing; Li, Yingrui; Yang, Huanming; Wang, Jian; Hou, Yong; Xu, Xun

2015-01-01

Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) Webinar Series

Cancer.gov

The Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) Webinar Series provides an opportunity for our grantees and other interested individuals to share lessons learned and practical information regarding the application of next generation sequencing to cancer epidemiology studies.

Incorporation of unique molecular identifiers in TruSeq adapters improves the accuracy of quantitative sequencing.

PubMed

Hong, Jungeui; Gresham, David

2017-11-01

Quantitative analysis of next-generation sequencing (NGS) data requires discriminating duplicate reads generated by PCR from identical molecules that are of unique origin. Typically, PCR duplicates are identified as sequence reads that align to the same genomic coordinates using reference-based alignment. However, identical molecules can be independently generated during library preparation. Misidentification of these molecules as PCR duplicates can introduce unforeseen biases during analyses. Here, we developed a cost-effective sequencing adapter design by modifying Illumina TruSeq adapters to incorporate a unique molecular identifier (UMI) while maintaining the capacity to undertake multiplexed, single-index sequencing. Incorporation of UMIs into TruSeq adapters (TrUMIseq adapters) enables identification of bona fide PCR duplicates as identically mapped reads with identical UMIs. Using TrUMIseq adapters, we show that accurate removal of PCR duplicates results in improved accuracy of both allele frequency (AF) estimation in heterogeneous populations using DNA sequencing and gene expression quantification using RNA-Seq.

Partial bisulfite conversion for unique template sequencing

PubMed Central

Kumar, Vijay; Rosenbaum, Julie; Wang, Zihua; Forcier, Talitha; Ronemus, Michael; Wigler, Michael

2018-01-01

Abstract We introduce a new protocol, mutational sequencing or muSeq, which uses sodium bisulfite to randomly deaminate unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling 135 000 restriction fragments in a PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone. PMID:29161423

SPAR: small RNA-seq portal for analysis of sequencing experiments.

PubMed

Kuksa, Pavel P; Amlie-Wolf, Alexandre; Katanic, Živadin; Valladares, Otto; Wang, Li-San; Leung, Yuk Yee

2018-05-04

The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data. SPAR is freely available at https://www.lisanwanglab.org/SPAR.

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

PubMed

Song, Li; Florea, Liliana

2015-01-01

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

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

PubMed

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

2016-03-01

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

Next-generation sequencing reveals low-dose effects of cationic dendrimers in primary human bronchial epithelial cells.

PubMed

Feliu, Neus; Kohonen, Pekka; Ji, Jie; Zhang, Yuning; Karlsson, Hanna L; Palmberg, Lena; Nyström, Andreas; Fadeel, Bengt

2015-01-27

Gene expression profiling has developed rapidly in recent years with the advent of deep sequencing technologies such as RNA sequencing (RNA Seq) and could be harnessed to predict and define mechanisms of toxicity of chemicals and nanomaterials. However, the full potential of these technologies in (nano)toxicology is yet to be realized. Here, we show that systems biology approaches can uncover mechanisms underlying cellular responses to nanomaterials. Using RNA Seq and computational approaches, we found that cationic poly(amidoamine) dendrimers (PAMAM-NH2) are capable of triggering down-regulation of cell-cycle-related genes in primary human bronchial epithelial cells at doses that do not elicit acute cytotoxicity, as demonstrated using conventional cell viability assays, while gene transcription was not affected by neutral PAMAM-OH dendrimers. The PAMAMs were internalized in an active manner by lung cells and localized mainly in lysosomes; amine-terminated dendrimers were internalized more efficiently when compared to the hydroxyl-terminated dendrimers. Upstream regulator analysis implicated NF-κB as a putative transcriptional regulator, and subsequent cell-based assays confirmed that PAMAM-NH2 caused NF-κB-dependent cell cycle arrest. However, PAMAM-NH2 did not affect cell cycle progression in the human A549 adenocarcinoma cell line. These results demonstrate the feasibility of applying systems biology approaches to predict cellular responses to nanomaterials and highlight the importance of using relevant (primary) cell models.

GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

PubMed

Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien

2017-08-01

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . gagneur@in.tum.de. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Cysteine-containing peptide tag for site-specific conjugation of proteins

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2008-04-08

The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety bound to the targeting moiety; the biological conjugate having a covalent bond between the thiol group of SEQ ID NO:2 and a functional group in the binding moiety. The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety that comprises an adapter protein, the adapter protein having a thiol group; the biological conjugate having a disulfide bond between the thiol group of SEQ ID NO:2 and the thiol group of the adapter protein. The present invention is also directed to biological sequences employed in the above biological conjugates, as well as pharmaceutical preparations and methods using the above biological conjugates.

Cysteine-containing peptide tag for site-specific conjugation of proteins

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2010-10-05

The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety bound to the targeting moiety; the biological conjugate having a covalent bond between the thiol group of SEQ ID NO:2 and a functional group in the binding moiety. The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety that comprises an adapter protein, the adapter protein having a thiol group; the biological conjugate having a disulfide bond between the thiol group of SEQ ID NO:2 and the thiol group of the adapter protein. The present invention is also directed to biological sequences employed in the above biological conjugates, as well as pharmaceutical preparations and methods using the above biological conjugates.

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

Progress in ion torrent semiconductor chip based sequencing.

PubMed

Merriman, Barry; Rothberg, Jonathan M

2012-12-01

In order for next-generation sequencing to become widely used as a diagnostic in the healthcare industry, sequencing instrumentation will need to be mass produced with a high degree of quality and economy. One way to achieve this is to recast DNA sequencing in a format that fully leverages the manufacturing base created for computer chips, complementary metal-oxide semiconductor chip fabrication, which is the current pinnacle of large scale, high quality, low-cost manufacturing of high technology. To achieve this, ideally the entire sensory apparatus of the sequencer would be embodied in a standard semiconductor chip, manufactured in the same fab facilities used for logic and memory chips. Recently, such a sequencing chip, and the associated sequencing platform, has been developed and commercialized by Ion Torrent, a division of Life Technologies, Inc. Here we provide an overview of this semiconductor chip based sequencing technology, and summarize the progress made since its commercial introduction. We described in detail the progress in chip scaling, sequencing throughput, read length, and accuracy. We also summarize the enhancements in the associated platform, including sample preparation, data processing, and engagement of the broader development community through open source and crowdsourcing initiatives. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

PubMed Central

2010-01-01

Background High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to avoid database contamination with artefactual sequences. The arrival of pyrosequencing enhances this problem and necessitates customisable pre-processing algorithms. Results SeqTrim has been implemented both as a Web and as a standalone command line application. Already-published and newly-designed algorithms have been included to identify sequence inserts, to remove low quality, vector, adaptor, low complexity and contaminant sequences, and to detect chimeric reads. The availability of several input and output formats allows its inclusion in sequence processing workflows. Due to its specific algorithms, SeqTrim outperforms other pre-processors implemented as Web services or standalone applications. It performs equally well with sequences from EST libraries, SSH libraries, genomic DNA libraries and pyrosequencing reads and does not lead to over-trimming. Conclusions SeqTrim is an efficient pipeline designed for pre-processing of any type of sequence read, including next-generation sequencing. It is easily configurable and provides a friendly interface that allows users to know what happened with sequences at every pre-processing stage, and to verify pre-processing of an individual sequence if desired. The recommended pipeline reveals more information about each sequence than previously described pre-processors and can discard more sequencing or experimental artefacts. PMID:20089148

Single-virion sequencing of lamivudine-treated HBV populations reveal population evolution dynamics and demographic history.

PubMed

Zhu, Yuan O; Aw, Pauline P K; de Sessions, Paola Florez; Hong, Shuzhen; See, Lee Xian; Hong, Lewis Z; Wilm, Andreas; Li, Chen Hao; Hue, Stephane; Lim, Seng Gee; Nagarajan, Niranjan; Burkholder, William F; Hibberd, Martin

2017-10-27

Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients - once before antiviral treatment and once after viral rebound due to resistance. With single-virion sequencing, we obtained 248-8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells.

PubMed

Beltman, Joost B; Urbanus, Jos; Velds, Arno; van Rooij, Nienke; Rohr, Jan C; Naik, Shalin H; Schumacher, Ton N

2016-04-02

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags. Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences. Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop.

PubMed

Schumacher, André; Pireddu, Luca; Niemenmaa, Matti; Kallio, Aleksi; Korpelainen, Eija; Zanetti, Gianluigi; Heljanko, Keijo

2014-01-01

Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig's scalability over many computing nodes and illustrate its use with example scripts. Available under the open source MIT license at http://sourceforge.net/projects/seqpig/

Isoform Sequencing and State-of-Art Applications for Unravelling Complexity of Plant Transcriptomes

PubMed Central

An, Dong; Li, Changsheng; Humbeck, Klaus

2018-01-01

Single-molecule real-time (SMRT) sequencing developed by PacBio, also called third-generation sequencing (TGS), offers longer reads than the second-generation sequencing (SGS). Given its ability to obtain full-length transcripts without assembly, isoform sequencing (Iso-Seq) of transcriptomes by PacBio is advantageous for genome annotation, identification of novel genes and isoforms, as well as the discovery of long non-coding RNA (lncRNA). In addition, Iso-Seq gives access to the direct detection of alternative splicing, alternative polyadenylation (APA), gene fusion, and DNA modifications. Such applications of Iso-Seq facilitate the understanding of gene structure, post-transcriptional regulatory networks, and subsequently proteomic diversity. In this review, we summarize its applications in plant transcriptome study, specifically pointing out challenges associated with each step in the experimental design and highlight the development of bioinformatic pipelines. We aim to provide the community with an integrative overview and a comprehensive guidance to Iso-Seq, and thus to promote its applications in plant research. PMID:29346292

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control consortium

PubMed Central

2014-01-01

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings. PMID:25150838

PRAPI: post-transcriptional regulation analysis pipeline for Iso-Seq.

PubMed

Gao, Yubang; Wang, Huiyuan; Zhang, Hangxiao; Wang, Yongsheng; Chen, Jinfeng; Gu, Lianfeng

2018-05-01

The single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) based on Pacific Bioscience (PacBio) platform has received increasing attention for its ability to explore full-length isoforms. Thus, comprehensive tools for Iso-Seq bioinformatics analysis are extremely useful. Here, we present a one-stop solution for Iso-Seq analysis, called PRAPI to analyze alternative transcription initiation (ATI), alternative splicing (AS), alternative cleavage and polyadenylation (APA), natural antisense transcripts (NAT), and circular RNAs (circRNAs) comprehensively. PRAPI is capable of combining Iso-Seq full-length isoforms with short read data, such as RNA-Seq or polyadenylation site sequencing (PAS-seq) for differential expression analysis of NAT, AS, APA and circRNAs. Furthermore, PRAPI can annotate new genes and correct mis-annotated genes when gene annotation is available. Finally, PRAPI generates high-quality vector graphics to visualize and highlight the Iso-Seq results. The Dockerfile of PRAPI is available at http://www.bioinfor.org/tool/PRAPI. lfgu@fafu.edu.cn.

A new method for enhancer prediction based on deep belief network.

PubMed

Bu, Hongda; Gan, Yanglan; Wang, Yang; Zhou, Shuigeng; Guan, Jihong

2017-10-16

Studies have shown that enhancers are significant regulatory elements to play crucial roles in gene expression regulation. Since enhancers are unrelated to the orientation and distance to their target genes, it is a challenging mission for scholars and researchers to accurately predicting distal enhancers. In the past years, with the high-throughout ChiP-seq technologies development, several computational techniques emerge to predict enhancers using epigenetic or genomic features. Nevertheless, the inconsistency of computational models across different cell-lines and the unsatisfactory prediction performance call for further research in this area. Here, we propose a new Deep Belief Network (DBN) based computational method for enhancer prediction, which is called EnhancerDBN. This method combines diverse features, composed of DNA sequence compositional features, DNA methylation and histone modifications. Our computational results indicate that 1) EnhancerDBN outperforms 13 existing methods in prediction, and 2) GC content and DNA methylation can serve as relevant features for enhancer prediction. Deep learning is effective in boosting the performance of enhancer prediction.

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

PubMed

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

2018-05-03

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

Partial bisulfite conversion for unique template sequencing.

PubMed

Kumar, Vijay; Rosenbaum, Julie; Wang, Zihua; Forcier, Talitha; Ronemus, Michael; Wigler, Michael; Levy, Dan

2018-01-25

We introduce a new protocol, mutational sequencing or muSeq, which uses sodium bisulfite to randomly deaminate unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling 135 000 restriction fragments in a PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

SeqHound: biological sequence and structure database as a platform for bioinformatics research

PubMed Central

2002-01-01

Background SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. Results SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. Conclusions The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit. PMID:12401134

Nucleic and amino acid sequences relating to a novel transketolase, and methods for the expression thereof

DOEpatents

Croteau, Rodney Bruce; Wildung, Mark Raymond; Lange, Bernd Markus; McCaskill, David G.

2001-01-01

cDNAs encoding 1-deoxyxylulose-5-phosphate synthase from peppermint (Mentha piperita) have been isolated and sequenced, and the corresponding amino acid sequences have been determined. Accordingly, isolated DNA sequences (SEQ ID NO:3, SEQ ID NO:5, SEQ ID NO:7) are provided which code for the expression of 1-deoxyxylulose-5-phosphate synthase from plants. In another aspect the present invention provides for isolated, recombinant DXPS proteins, such as the proteins having the sequences set forth in SEQ ID NO:4, SEQ ID NO:6 and SEQ ID NO:8. In other aspects, replicable recombinant cloning vehicles are provided which code for plant 1-deoxyxylulose-5-phosphate synthases, or for a base sequence sufficiently complementary to at least a portion of 1-deoxyxylulose-5-phosphate synthase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding a plant 1-deoxyxylulose-5-phosphate synthase. Thus, systems and methods are provided for the recombinant expression of the aforementioned recombinant 1-deoxyxylulose-5-phosphate synthase that may be used to facilitate its production, isolation and purification in significant amounts. Recombinant 1-deoxyxylulose-5-phosphate synthase may be used to obtain expression or enhanced expression of 1-deoxyxylulose-5-phosphate synthase in plants in order to enhance the production of 1-deoxyxylulose-5-phosphate, or its derivatives such as isopentenyl diphosphate (BP), or may be otherwise employed for the regulation or expression of 1-deoxyxylulose-5-phosphate synthase, or the production of its products.

Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations

PubMed Central

Jupe, Florian; Witek, Kamil; Verweij, Walter; Śliwka, Jadwiga; Pritchard, Leighton; Etherington, Graham J; Maclean, Dan; Cock, Peter J; Leggett, Richard M; Bryan, Glenn J; Cardle, Linda; Hein, Ingo; Jones, Jonathan DG

2013-01-01

Summary RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ∼80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum ‘Heinz 1706’ extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines. PMID:23937694

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.

PubMed

Haque, Ashraful; Engel, Jessica; Teichmann, Sarah A; Lönnberg, Tapio

2017-08-18

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation.

Exploring single nucleotide polymorphism (SNP), microsatellite (SSR) and differentially expressed genes in the jellyfish (Rhopilema esculentum) by transcriptome sequencing.

PubMed

Li, Yunfeng; Zhou, Zunchun; Tian, Meilin; Tian, Yi; Dong, Ying; Li, Shilei; Liu, Weidong; He, Chongbo

2017-08-01

In this study, single nucleotide polymorphism (SNP), microsatellite (SSR) and differentially expressed genes (DEGs) in the oral parts, gonads, and umbrella parts of the jellyfish Rhopilema esculentum were analyzed by RNA-Seq technology. A total of 76.4 million raw reads and 72.1 million clean reads were generated from deep sequencing. Approximately 119,874 tentative unigenes and 149,239 transcripts were obtained. A total of 1,034,708 SNP markers were detected in the three tissues. For microsatellite mining, 5088 SSRs were identified from the unigene sequences. The most frequent repeat motifs were mononucleotide repeats, which accounted for 61.93%. Transcriptome comparison of the three tissues yielded a total of 8841 DEGs, of which 3560 were up-regulated and 5281 were down-regulated. This study represents the greatest sequencing effort carried out for a jellyfish and provides the first high-throughput transcriptomic resource for jellyfish. Copyright © 2017 Elsevier B.V. All rights reserved.

The effect of Bacopa monnieri on gene expression levels in SH-SY5Y human neuroblastoma cells.

PubMed

Leung, How-Wing; Foo, Gabriel; Banumurthy, Gokulakrishna; Chai, Xiaoran; Ghosh, Sujoy; Mitra-Ganguli, Tora; VanDongen, Antonius M J

2017-01-01

Bacopa monnieri is a plant used as a nootropic in Ayurveda, a 5000-year-old system of traditional Indian medicine. Although both animal and clinical studies supported its role as a memory enhancer, the molecular and cellular mechanism underlying Bacopa's nootropic action are not understood. In this study, we used deep sequencing (RNA-Seq) to identify the transcriptome changes upon Bacopa treatment on SH-SY5Y human neuroblastoma cells. We identified several genes whose expression levels were regulated by Bacopa. Biostatistical analysis of the RNA-Seq data identified biological pathways and molecular functions that were regulated by Bacopa, including regulation of mRNA translation and transmembrane transport, responses to oxidative stress and protein misfolding. Pathway analysis using the Ingenuity platform suggested that Bacopa may protect against brain damage and improve brain development. These newly identified molecular and cellular determinants may contribute to the nootropic action of Bacopa and open up a new direction of investigation into its mechanism of action.

The effect of Bacopa monnieri on gene expression levels in SH-SY5Y human neuroblastoma cells

PubMed Central

Foo, Gabriel; Banumurthy, Gokulakrishna; Chai, Xiaoran; Ghosh, Sujoy

2017-01-01

Bacopa monnieri is a plant used as a nootropic in Ayurveda, a 5000-year-old system of traditional Indian medicine. Although both animal and clinical studies supported its role as a memory enhancer, the molecular and cellular mechanism underlying Bacopa’s nootropic action are not understood. In this study, we used deep sequencing (RNA-Seq) to identify the transcriptome changes upon Bacopa treatment on SH-SY5Y human neuroblastoma cells. We identified several genes whose expression levels were regulated by Bacopa. Biostatistical analysis of the RNA-Seq data identified biological pathways and molecular functions that were regulated by Bacopa, including regulation of mRNA translation and transmembrane transport, responses to oxidative stress and protein misfolding. Pathway analysis using the Ingenuity platform suggested that Bacopa may protect against brain damage and improve brain development. These newly identified molecular and cellular determinants may contribute to the nootropic action of Bacopa and open up a new direction of investigation into its mechanism of action. PMID:28832626

Transcription start site associated RNAs (TSSaRNAs) are ubiquitous in all domains of life.

PubMed

Zaramela, Livia S; Vêncio, Ricardo Z N; ten-Caten, Felipe; Baliga, Nitin S; Koide, Tie

2014-01-01

A plethora of non-coding RNAs has been discovered using high-resolution transcriptomics tools, indicating that transcriptional and post-transcriptional regulation is much more complex than previously appreciated. Small RNAs associated with transcription start sites of annotated coding regions (TSSaRNAs) are pervasive in both eukaryotes and bacteria. Here, we provide evidence for existence of TSSaRNAs in several archaeal transcriptomes including: Halobacterium salinarum, Pyrococcus furiosus, Methanococcus maripaludis, and Sulfolobus solfataricus. We validated TSSaRNAs from the model archaeon Halobacterium salinarum NRC-1 by deep sequencing two independent small-RNA enriched (RNA-seq) and a primary-transcript enriched (dRNA-seq) strand-specific libraries. We identified 652 transcripts, of which 179 were shown to be primary transcripts (∼7% of the annotated genome). Distinct growth-associated expression patterns between TSSaRNAs and their cognate genes were observed, indicating a possible role in environmental responses that may result from RNA polymerase with varying pausing rhythms. This work shows that TSSaRNAs are ubiquitous across all domains of life.

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer.

PubMed

Zhao, Yiru Chen; Madak Erdogan, Zeynep

2016-03-17

With the advent of the -omics approaches our understanding of the chronic diseases like cancer and metabolic syndrome has improved. However, effective mining of the information in the large-scale datasets that are obtained from gene expression microarrays, deep sequencing experiments or metabolic profiling is essential to uncover and then effectively target the critical regulators of diseased cell phenotypes. Estrogen Receptor α (ERα) is one of the master transcription factors regulating the gene programs that are important for estrogen responsive breast cancers. In order to understand to role of ERα signaling in breast cancer metabolism we utilized transcriptomic, cistromic and metabolomic data from MCF-7 cells treated with estradiol. In this report we described generation of samples for RNA-Seq, ChIP-Seq and metabolomics experiments and the integrative computational analysis of the obtained data. This approach is useful in delineating novel molecular mechanisms and gene regulatory circuits that are regulated by a particular transcription factor which impacts metabolism of normal or diseased cells.

Towards Clinical Molecular Diagnosis of Inherited Cardiac Conditions: A Comparison of Bench-Top Genome DNA Sequencers

PubMed Central

Wilkinson, Samuel L.; John, Shibu; Walsh, Roddy; Novotny, Tomas; Valaskova, Iveta; Gupta, Manu; Game, Laurence; Barton, Paul J R.; Cook, Stuart A.; Ware, James S.

2013-01-01

Background Molecular genetic testing is recommended for diagnosis of inherited cardiac disease, to guide prognosis and treatment, but access is often limited by cost and availability. Recently introduced high-throughput bench-top DNA sequencing platforms have the potential to overcome these limitations. Methodology/Principal Findings We evaluated two next-generation sequencing (NGS) platforms for molecular diagnostics. The protein-coding regions of six genes associated with inherited arrhythmia syndromes were amplified from 15 human samples using parallelised multiplex PCR (Access Array, Fluidigm), and sequenced on the MiSeq (Illumina) and Ion Torrent PGM (Life Technologies). Overall, 97.9% of the target was sequenced adequately for variant calling on the MiSeq, and 96.8% on the Ion Torrent PGM. Regions missed tended to be of high GC-content, and most were problematic for both platforms. Variant calling was assessed using 107 variants detected using Sanger sequencing: within adequately sequenced regions, variant calling on both platforms was highly accurate (Sensitivity: MiSeq 100%, PGM 99.1%. Positive predictive value: MiSeq 95.9%, PGM 95.5%). At the time of the study the Ion Torrent PGM had a lower capital cost and individual runs were cheaper and faster. The MiSeq had a higher capacity (requiring fewer runs), with reduced hands-on time and simpler laboratory workflows. Both provide significant cost and time savings over conventional methods, even allowing for adjunct Sanger sequencing to validate findings and sequence exons missed by NGS. Conclusions/Significance MiSeq and Ion Torrent PGM both provide accurate variant detection as part of a PCR-based molecular diagnostic workflow, and provide alternative platforms for molecular diagnosis of inherited cardiac conditions. Though there were performance differences at this throughput, platforms differed primarily in terms of cost, scalability, protocol stability and ease of use. Compared with current molecular genetic diagnostic tests for inherited cardiac arrhythmias, these NGS approaches are faster, less expensive, and yet more comprehensive. PMID:23861798

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

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

Shi, CY; Yang, H; Wei, CL

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 intomore » 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 time PCR (qRT-PCR). An extensive transcriptome dataset has been obtained from the deep sequencing of tea plant. The coverage of the transcriptome is comprehensive enough to discover all known genes of several major metabolic pathways. This transcriptome dataset can serve as an important public information platform for gene expression, genomics, and functional genomic studies in C. sinensis.« less

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

PubMed Central

2011-01-01

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 analyzed by RT-PCR and quantitative real time PCR (qRT-PCR). Conclusions An extensive transcriptome dataset has been obtained from the deep sequencing of tea plant. The coverage of the transcriptome is comprehensive enough to discover all known genes of several major metabolic pathways. This transcriptome dataset can serve as an important public information platform for gene expression, genomics, and functional genomic studies in C. sinensis. PMID:21356090

Comparison of Deep-Water Viromes from the Atlantic Ocean and the Mediterranean Sea

PubMed Central

Winter, Christian; Garcia, Juan A. L.; Weinbauer, Markus G.; DuBow, Michael S.; Herndl, Gerhard J.

2014-01-01

The aim of this study was to compare the composition of two deep-sea viral communities obtained from the Romanche Fracture Zone in the Atlantic Ocean (collected at 5200 m depth) and the southwest Mediterranean Sea (from 2400 m depth) using a pyro-sequencing approach. The results are based on 18.7% and 6.9% of the sequences obtained from the Atlantic Ocean and the Mediterranean Sea, respectively, with hits to genomes in the non-redundant viral RefSeq database. The identifiable richness and relative abundance in both viromes were dominated by archaeal and bacterial viruses accounting for 92.3% of the relative abundance in the Atlantic Ocean and for 83.6% in the Mediterranean Sea. Despite characteristic differences in hydrographic features between the sampling sites in the Atlantic Ocean and the Mediterranean Sea, 440 virus genomes were found in both viromes. An additional 431 virus genomes were identified in the Atlantic Ocean and 75 virus genomes were only found in the Mediterranean Sea. The results indicate that the rather contrasting deep-sea environments of the Atlantic Ocean and the Mediterranean Sea share a common core set of virus types constituting the majority of both virus communities in terms of relative abundance (Atlantic Ocean: 81.4%; Mediterranean Sea: 88.7%). PMID:24959907

SeqAPASS (Sequence Alignment to Predict Across Species Susceptibility) software and documentation

EPA Science Inventory

SeqAPASS is a software application facilitates rapid and streamlined, yet transparent, comparisons of the similarity of toxicologically-significant molecular targets across species. The present application facilitates analysis of primary amino acid sequence similarity (including ...

Hysteretic energy prediction method for mainshock-aftershock sequences

NASA Astrophysics Data System (ADS)

Zhai, Changhai; Ji, Duofa; Wen, Weiping; Li, Cuihua; Lei, Weidong; Xie, Lili

2018-04-01

Structures located in seismically active regions may be subjected to mainshock-aftershock (MSAS) sequences. Strong aftershocks significantly affect the hysteretic energy demand of structures. The hysteretic energy, E H,seq, is normalized by mass m and expressed in terms of the equivalent velocity, V D,seq, to quantitatively investigate aftershock effects on the hysteretic energy of structures. The equivalent velocity, V D,seq, is computed by analyzing the response time-history of an inelastic single-degree-of-freedom (SDOF) system with a varying vibration period subjected to 309 MSAS sequences. The present study selected two kinds of MSAS sequences, with one aftershock and two aftershocks, respectively. The aftershocks are scaled to maintain different relative intensities. The variation of the equivalent velocity, V D,seq, is studied for consideration of the ductility values, site conditions, relative intensities, number of aftershocks, hysteretic models, and damping ratios. The MSAS sequence with one aftershock exhibited a 10% to 30% hysteretic energy increase, whereas the MSAS sequence with two aftershocks presented a 20% to 40% hysteretic energy increase. Finally, a hysteretic energy prediction equation is proposed as a function of the vibration period, ductility value, and damping ratio to estimate hysteretic energy for mainshock-aftershock sequences.

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC

PubMed Central

Walter, Vonn; Patel, Nirali M.; Eberhard, David A.; Hayward, Michele C.; Salazar, Ashley H.; Jo, Heejoon; Soloway, Matthew G.; Wilkerson, Matthew D.; Parker, Joel S.; Yin, Xiaoying; Zhang, Guosheng; Siegel, Marni B.; Rosson, Gary B.; Earp, H. Shelton; Sharpless, Norman E.; Gulley, Margaret L.; Weck, Karen E.

2015-01-01

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07–0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11–1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion. PMID:26076459

JVM: Java Visual Mapping tool for next generation sequencing read.

PubMed

Yang, Ye; Liu, Juan

2015-01-01

We developed a program JVM (Java Visual Mapping) for mapping next generation sequencing read to reference sequence. The program is implemented in Java and is designed to deal with millions of short read generated by sequence alignment using the Illumina sequencing technology. It employs seed index strategy and octal encoding operations for sequence alignments. JVM is useful for DNA-Seq, RNA-Seq when dealing with single-end resequencing. JVM is a desktop application, which supports reads capacity from 1 MB to 10 GB.

SeqMule: automated pipeline for analysis of human exome/genome sequencing data.

PubMed

Guo, Yunfei; Ding, Xiaolei; Shen, Yufeng; Lyon, Gholson J; Wang, Kai

2015-09-18

Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies exist among aligners and variant callers. We developed a computational pipeline, SeqMule, to perform automated variant calling from NGS data on human genomes and exomes. SeqMule integrates computational-cluster-free parallelization capability built on top of the variant callers, and facilitates normalization/intersection of variant calls to generate consensus set with high confidence. SeqMule integrates 5 alignment tools, 5 variant calling algorithms and accepts various combinations all by one-line command, therefore allowing highly flexible yet fully automated variant calling. In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, SeqMule generates annotated VCF files in a day from a 30X whole-genome sequencing data set; when more accurate calling is needed, SeqMule generates consensus call set that improves over single callers, as measured by both Mendelian error rate and consistency. SeqMule supports Sun Grid Engine for parallel processing, offers turn-key solution for deployment on Amazon Web Services, allows quality check, Mendelian error check, consistency evaluation, HTML-based reports. SeqMule is available at http://seqmule.openbioinformatics.org.

oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets

PubMed Central

Kwon, Andrew T.; Arenillas, David J.; Hunt, Rebecca Worsley; Wasserman, Wyeth W.

2012-01-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca. PMID:22973536

oPOSSUM-3: advanced analysis of regulatory motif over-representation across genes or ChIP-Seq datasets.

PubMed

Kwon, Andrew T; Arenillas, David J; Worsley Hunt, Rebecca; Wasserman, Wyeth W

2012-09-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca.

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

PubMed Central

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

2007-01-01

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

Metagenomics Reveals Microbial Community Composition And Function With Depth In Arctic Permafrost Cores

NASA Astrophysics Data System (ADS)

Jansson, J.; Tas, N.; Wu, Y.; Ulrich, C.; Kneafsey, T. J.; Torn, M. S.; Hubbard, S. S.; Chakraborty, R.; Graham, D. E.; Wullschleger, S. D.

2013-12-01

The Arctic is one of the most climatically sensitive regions on Earth and current surveys show that permafrost degradation is widespread in arctic soils. Biogeochemical feedbacks of permafrost thaw are expected to be dominated by the release of currently stored carbon back into the atmosphere as CO2 and CH4. Understanding the dynamics of C release from permafrost requires assessment of microbial functions from different soil compartments. To this end, as part of the Next Generation Ecosystem Experiment in the Arctic, we collected two replicate permafrost cores (1m and 3m deep) from a transitional polygon near Barrow, AK. At this location, permafrost starts from 0.5m in depth and is characterized by variable ice content and higher pH than surface soils. Prior to sectioning, the cores were CT-scanned to determine the physical heterogeneity throughout the cores. In addition to detailed geochemical characterization, we used Illumina MiSeq technology to sequence 16SrRNA genes throughout the depths of the cores at 1 cm intervals. Selected depths were also chosen for metagenome sequencing of total DNA (including phylogenetic and functional genes) using the Illumina HiSeq platform. The 16S rRNA gene sequence data revealed that the microbial community composition and diversity changed dramatically with depth. The microbial diversity decreased sharply below the first few centimeters of the permafrost and then gradually increased in deeper layers. Based on the metagenome sequence data, the permafrost microbial communities were found to contain members with a large metabolic potential for carbon processing, including pathways for fermentation and methanogenesis. The surface active layers had more representatives of Verrucomicrobia (potential methane oxidizers) whereas the deep permafrost layers were dominated by several different species of Actinobacteria. The latter are known to have a diverse metabolic capability and are able to adapt to stress by entering a dormant yet viable state. In addition, several isolates were obtained from different depths throughout the cores, including methanogens from some of the deeper layers. Together these data present a new view of potential geochemical cycles carried out by microorganisms in permafrost and reveal how community members and functions are distributed with depth.

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma.

PubMed

Jiang, Yanwen; Nie, Kui; Redmond, David; Melnick, Ari M; Tam, Wayne; Elemento, Olivier

2015-12-28

Understanding tumor clonality is critical to understanding the mechanisms involved in tumorigenesis and disease progression. In addition, understanding the clonal composition changes that occur within a tumor in response to certain micro-environment or treatments may lead to the design of more sophisticated and effective approaches to eradicate tumor cells. However, tracking tumor clonal sub-populations has been challenging due to the lack of distinguishable markers. To address this problem, a VDJ-seq protocol was created to trace the clonal evolution patterns of diffuse large B cell lymphoma (DLBCL) relapse by exploiting VDJ recombination and somatic hypermutation (SHM), two unique features of B cell lymphomas. In this protocol, Next-Generation sequencing (NGS) libraries with indexing potential were constructed from amplified rearranged immunoglobulin heavy chain (IgH) VDJ region from pairs of primary diagnosis and relapse DLBCL samples. On average more than half million VDJ sequences per sample were obtained after sequencing, which contain both VDJ rearrangement and SHM information. In addition, customized bioinformatics pipelines were developed to fully utilize sequence information for the characterization of IgH-VDJ repertoire within these samples. Furthermore, the pipeline allows the reconstruction and comparison of the clonal architecture of individual tumors, which enables the examination of the clonal heterogeneity within the diagnosis tumors and deduction of clonal evolution patterns between diagnosis and relapse tumor pairs. When applying this analysis to several diagnosis-relapse pairs, we uncovered key evidence that multiple distinctive tumor evolutionary patterns could lead to DLBCL relapse. Additionally, this approach can be expanded into other clinical aspects, such as identification of minimal residual disease, monitoring relapse progress and treatment response, and investigation of immune repertoires in non-lymphoma contexts.

Deep mRNA Sequencing of the Tritonia diomedea Brain Transcriptome Provides Access to Gene Homologues for Neuronal Excitability, Synaptic Transmission and Peptidergic Signalling

PubMed Central

Senatore, Adriano; Edirisinghe, Neranjan; Katz, Paul S.

2015-01-01

Background The sea slug Tritonia diomedea (Mollusca, Gastropoda, Nudibranchia), has a simple and highly accessible nervous system, making it useful for studying neuronal and synaptic mechanisms underlying behavior. Although many important contributions have been made using Tritonia, until now, a lack of genetic information has impeded exploration at the molecular level. Results We performed Illumina sequencing of central nervous system mRNAs from Tritonia, generating 133.1 million 100 base pair, paired-end reads. De novo reconstruction of the RNA-Seq data yielded a total of 185,546 contigs, which partitioned into 123,154 non-redundant gene clusters (unigenes). BLAST comparison with RefSeq and Swiss-Prot protein databases, as well as mRNA data from other invertebrates (gastropod molluscs: Aplysia californica, Lymnaea stagnalis and Biomphalaria glabrata; cnidarian: Nematostella vectensis) revealed that up to 76,292 unigenes in the Tritonia transcriptome have putative homologues in other databases, 18,246 of which are below a more stringent E-value cut-off of 1x10-6. In silico prediction of secreted proteins from the Tritonia transcriptome shotgun assembly (TSA) produced a database of 579 unique sequences of secreted proteins, which also exhibited markedly higher expression levels compared to other genes in the TSA. Conclusions Our efforts greatly expand the availability of gene sequences available for Tritonia diomedea. We were able to extract full length protein sequences for most queried genes, including those involved in electrical excitability, synaptic vesicle release and neurotransmission, thus confirming that the transcriptome will serve as a useful tool for probing the molecular correlates of behavior in this species. We also generated a neurosecretome database that will serve as a useful tool for probing peptidergic signalling systems in the Tritonia brain. PMID:25719197

NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

PubMed Central

Pruitt, Kim D.; Tatusova, Tatiana; Maglott, Donna R.

2005-01-01

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) provides a non-redundant collection of sequences representing genomic data, transcripts and proteins. Although the goal is to provide a comprehensive dataset representing the complete sequence information for any given species, the database pragmatically includes sequence data that are currently publicly available in the archival databases. The database incorporates data from over 2400 organisms and includes over one million proteins representing significant taxonomic diversity spanning prokaryotes, eukaryotes and viruses. Nucleotide and protein sequences are explicitly linked, and the sequences are linked to other resources including the NCBI Map Viewer and Gene. Sequences are annotated to include coding regions, conserved domains, variation, references, names, database cross-references, and other features using a combined approach of collaboration and other input from the scientific community, automated annotation, propagation from GenBank and curation by NCBI staff. PMID:15608248

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

PubMed

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

2015-10-28

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

Gene expression profiling of human breast tissue samples using SAGE-Seq.

PubMed

Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

2010-12-01

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

The molecular topography of silenced chromatin in Saccharomyces cerevisiae

PubMed Central

Thurtle, Deborah M.; Rine, Jasper

2014-01-01

Heterochromatin imparts regional, promoter-independent repression of genes and is epigenetically heritable. Understanding how silencing achieves this regional repression is a fundamental problem in genetics and development. Current models of yeast silencing posit that Sir proteins, recruited by transcription factors bound to the silencers, spread throughout the silenced region. To test this model directly at high resolution, we probed the silenced chromatin architecture by chromatin immunoprecipitation (ChIP) followed by next-generation sequencing (ChIP-seq) of Sir proteins, histones, and a key histone modification, H4K16-acetyl. These analyses revealed that Sir proteins are strikingly concentrated at and immediately adjacent to the silencers, with lower levels of enrichment over the promoters at HML and HMR, the critical targets for transcriptional repression. The telomeres also showed discrete peaks of Sir enrichment yet a continuous domain of hypoacetylated histone H4K16. Surprisingly, ChIP-seq of cross-linked chromatin revealed a distribution of nucleosomes at silenced loci that was similar to Sir proteins, whereas native nucleosome maps showed a regular distribution throughout silenced loci, indicating that cross-linking captured a specialized chromatin organization imposed by Sir proteins. This specialized chromatin architecture observed in yeast informs the importance of a steric contribution to regional repression in other organisms. PMID:24493645

CRISPR-Cas9-Edited Site Sequencing (CRES-Seq): An Efficient and High-Throughput Method for the Selection of CRISPR-Cas9-Edited Clones.

PubMed

Veeranagouda, Yaligara; Debono-Lagneaux, Delphine; Fournet, Hamida; Thill, Gilbert; Didier, Michel

2018-01-16

The emergence of clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-Cas9) gene editing systems has enabled the creation of specific mutants at low cost, in a short time and with high efficiency, in eukaryotic cells. Since a CRISPR-Cas9 system typically creates an array of mutations in targeted sites, a successful gene editing project requires careful selection of edited clones. This process can be very challenging, especially when working with multiallelic genes and/or polyploid cells (such as cancer and plants cells). Here we described a next-generation sequencing method called CRISPR-Cas9 Edited Site Sequencing (CRES-Seq) for the efficient and high-throughput screening of CRISPR-Cas9-edited clones. CRES-Seq facilitates the precise genotyping up to 96 CRISPR-Cas9-edited sites (CRES) in a single MiniSeq (Illumina) run with an approximate sequencing cost of $6/clone. CRES-Seq is particularly useful when multiple genes are simultaneously targeted by CRISPR-Cas9, and also for screening of clones generated from multiallelic genes/polyploid cells. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

SeqHBase: a big data toolset for family based sequencing data analysis.

PubMed

He, Min; Person, Thomas N; Hebbring, Scott J; Heinzen, Ethan; Ye, Zhan; Schrodi, Steven J; McPherson, Elizabeth W; Lin, Simon M; Peissig, Peggy L; Brilliant, Murray H; O'Rawe, Jason; Robison, Reid J; Lyon, Gholson J; Wang, Kai

2015-04-01

Whole-genome sequencing (WGS) and whole-exome sequencing (WES) technologies are increasingly used to identify disease-contributing mutations in human genomic studies. It can be a significant challenge to process such data, especially when a large family or cohort is sequenced. Our objective was to develop a big data toolset to efficiently manipulate genome-wide variants, functional annotations and coverage, together with conducting family based sequencing data analysis. Hadoop is a framework for reliable, scalable, distributed processing of large data sets using MapReduce programming models. Based on Hadoop and HBase, we developed SeqHBase, a big data-based toolset for analysing family based sequencing data to detect de novo, inherited homozygous, or compound heterozygous mutations that may contribute to disease manifestations. SeqHBase takes as input BAM files (for coverage at every site), variant call format (VCF) files (for variant calls) and functional annotations (for variant prioritisation). We applied SeqHBase to a 5-member nuclear family and a 10-member 3-generation family with WGS data, as well as a 4-member nuclear family with WES data. Analysis times were almost linearly scalable with number of data nodes. With 20 data nodes, SeqHBase took about 5 secs to analyse WES familial data and approximately 1 min to analyse WGS familial data. These results demonstrate SeqHBase's high efficiency and scalability, which is necessary as WGS and WES are rapidly becoming standard methods to study the genetics of familial disorders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Monitoring Error Rates In Illumina Sequencing.

PubMed

Manley, Leigh J; Ma, Duanduan; Levine, Stuart S

2016-12-01

Guaranteeing high-quality next-generation sequencing data in a rapidly changing environment is an ongoing challenge. The introduction of the Illumina NextSeq 500 and the depreciation of specific metrics from Illumina's Sequencing Analysis Viewer (SAV; Illumina, San Diego, CA, USA) have made it more difficult to determine directly the baseline error rate of sequencing runs. To improve our ability to measure base quality, we have created an open-source tool to construct the Percent Perfect Reads (PPR) plot, previously provided by the Illumina sequencers. The PPR program is compatible with HiSeq 2000/2500, MiSeq, and NextSeq 500 instruments and provides an alternative to Illumina's quality value (Q) scores for determining run quality. Whereas Q scores are representative of run quality, they are often overestimated and are sourced from different look-up tables for each platform. The PPR's unique capabilities as a cross-instrument comparison device, as a troubleshooting tool, and as a tool for monitoring instrument performance can provide an increase in clarity over SAV metrics that is often crucial for maintaining instrument health. These capabilities are highlighted.

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

PubMed Central

Trapnell, Cole; Roberts, Adam; Goff, Loyal; Pertea, Geo; Kim, Daehwan; Kelley, David R; Pimentel, Harold; Salzberg, Steven L; Rinn, John L; Pachter, Lior

2012-01-01

Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ~1 h of hands-on time. PMID:22383036

Micropathogen Community Analysis in Hyalomma rufipes via High-Throughput Sequencing of Small RNAs

PubMed Central

Luo, Jin; Liu, Min-Xuan; Ren, Qiao-Yun; Chen, Ze; Tian, Zhan-Cheng; Hao, Jia-Wei; Wu, Feng; Liu, Xiao-Cui; Luo, Jian-Xun; Yin, Hong; Wang, Hui; Liu, Guang-Yuan

2017-01-01

Ticks are important vectors in the transmission of a broad range of micropathogens to vertebrates, including humans. Because of the role of ticks in disease transmission, identifying and characterizing the micropathogen profiles of tick populations have become increasingly important. The objective of this study was to survey the micropathogens of Hyalomma rufipes ticks. Illumina HiSeq2000 technology was utilized to perform deep sequencing of small RNAs (sRNAs) extracted from field-collected H. rufipes ticks in Gansu Province, China. The resultant sRNA library data revealed that the surveyed tick populations produced reads that were homologous to St. Croix River Virus (SCRV) sequences. We also observed many reads that were homologous to microbial and/or pathogenic isolates, including bacteria, protozoa, and fungi. As part of this analysis, a phylogenetic tree was constructed to display the relationships among the homologous sequences that were identified. The study offered a unique opportunity to gain insight into the micropathogens of H. rufipes ticks. The effective control of arthropod vectors in the future will require knowledge of the micropathogen composition of vectors harboring infectious agents. Understanding the ecological factors that regulate vector propagation in association with the prevalence and persistence of micropathogen lineages is also imperative. These interactions may affect the evolution of micropathogen lineages, especially if the micropathogens rely on the vector or host for dispersal. The sRNA deep-sequencing approach used in this analysis provides an intuitive method to survey micropathogen prevalence in ticks and other vector species. PMID:28861401

Transcriptome sequencing analysis of novel sRNAs of Kineococcus radiotolerans in response to ionizing radiation.

PubMed

Chen, Zhouwei; Li, Lufeng; Shan, Zhan; Huang, Hannian; Chen, Huan; Ding, Xianfeng; Guo, Jiangfeng; Liu, Lili

2016-11-01

Kineococcus radiotolerans is a Gram-positive, radio-resistant bacterium isolated from a radioactive environment. The small noncoding RNAs (sRNAs) in bacteria are reported to play roles in the immediate response to stress and/or the recovery from stress. The analysis of K. radiotolerans transcriptome sequencing results can identify these sRNAs in a genome-wide detection, using RNA sequencing (RNA-seq) by the deep sequencing technique. In this study, the raw data of radiation-exposed samples (RS) and control samples (CS) were acquired separately from the sequencing platform. There were 217 common sRNA candidates in the two samples screened in the genome-wide scale by bioinformatics analysis. There were 43 differentially expressed sRNA candidates, including 28 up-regulated and 15 down-regulated ones. The down-regulated sRNAs were selected for the sRNA target prediction, of which 12 sRNAs that may modulate the genes related to the transcription regulation and DNA repair were considered as the candidates involved in the radio-resistance regulation system. Copyright © 2016 Elsevier GmbH. All rights reserved.

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

PubMed Central

Schumacher, André; Pireddu, Luca; Niemenmaa, Matti; Kallio, Aleksi; Korpelainen, Eija; Zanetti, Gianluigi; Heljanko, Keijo

2014-01-01

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts. Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/ Contact: andre.schumacher@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24149054

Comparison and quantitative verification of mapping algorithms for whole genome bisulfite sequencing

USDA-ARS?s Scientific Manuscript database

Coupling bisulfite conversion with next-generation sequencing (Bisulfite-seq) enables genome-wide measurement of DNA methylation, but poses unique challenges for mapping. However, despite a proliferation of Bisulfite-seq mapping tools, no systematic comparison of their genomic coverage and quantitat...

The bench scientist's guide to RNA-Seq analysis

USDA-ARS?s Scientific Manuscript database

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

De novo assembly and next-generation sequencing to analyse full-length gene variants from codon-barcoded libraries.

PubMed

Cho, Namjin; Hwang, Byungjin; Yoon, Jung-ki; Park, Sangun; Lee, Joongoo; Seo, Han Na; Lee, Jeewon; Huh, Sunghoon; Chung, Jinsoo; Bang, Duhee

2015-09-21

Interpreting epistatic interactions is crucial for understanding evolutionary dynamics of complex genetic systems and unveiling structure and function of genetic pathways. Although high resolution mapping of en masse variant libraries renders molecular biologists to address genotype-phenotype relationships, long-read sequencing technology remains indispensable to assess functional relationship between mutations that lie far apart. Here, we introduce JigsawSeq for multiplexed sequence identification of pooled gene variant libraries by combining a codon-based molecular barcoding strategy and de novo assembly of short-read data. We first validate JigsawSeq on small sub-pools and observed high precision and recall at various experimental settings. With extensive simulations, we then apply JigsawSeq to large-scale gene variant libraries to show that our method can be reliably scaled using next-generation sequencing. JigsawSeq may serve as a rapid screening tool for functional genomics and offer the opportunity to explore evolutionary trajectories of protein variants.

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

PubMed

Honda, Shozo; Morichika, Keisuke; Kirino, Yohei

2016-03-01

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

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Quantum-Sequencing: Biophysics of quantum tunneling through nucleic acids

NASA Astrophysics Data System (ADS)

Casamada Ribot, Josep; Chatterjee, Anushree; Nagpal, Prashant

2014-03-01

Tunneling microscopy and spectroscopy has extensively been used in physical surface sciences to study quantum tunneling to measure electronic local density of states of nanomaterials and to characterize adsorbed species. Quantum-Sequencing (Q-Seq) is a new method based on tunneling microscopy for electronic sequencing of single molecule of nucleic acids. A major goal of third-generation sequencing technologies is to develop a fast, reliable, enzyme-free single-molecule sequencing method. Here, we present the unique ``electronic fingerprints'' for all nucleotides on DNA and RNA using Q-Seq along their intrinsic biophysical parameters. We have analyzed tunneling spectra for the nucleotides at different pH conditions and analyzed the HOMO, LUMO and energy gap for all of them. In addition we show a number of biophysical parameters to further characterize all nucleobases (electron and hole transition voltage and energy barriers). These results highlight the robustness of Q-Seq as a technique for next-generation sequencing.

Monoterpene synthases from common sage (Salvia officinalis)

DOEpatents

Croteau, Rodney Bruce; Wise, Mitchell Lynn; Katahira, Eva Joy; Savage, Thomas Jonathan

1999-01-01

cDNAs encoding (+)-bornyl diphosphate synthase, 1,8-cineole synthase and (+)-sabinene synthase from common sage (Salvia officinalis) have been isolated and sequenced, and the corresponding amino acid sequences has been determined. Accordingly, isolated DNA sequences (SEQ ID No:1; SEQ ID No:3 and SEQ ID No:5) are provided which code for the expression of (+)-bornyl diphosphate synthase (SEQ ID No:2), 1,8-cineole synthase (SEQ ID No:4) and (+)-sabinene synthase SEQ ID No:6), respectively, from sage (Salvia officinalis). In other aspects, replicable recombinant cloning vehicles are provided which code for (+)-bornyl diphosphate synthase, 1,8-cineole synthase or (+)-sabinene synthase, or for a base sequence sufficiently complementary to at least a portion of (+)-bornyl diphosphate synthase, 1,8-cineole synthase or (+)-sabinene synthase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding (+)-bornyl diphosphate synthase, 1,8-cineole synthase or (+)-sabinene synthase. Thus, systems and methods are provided for the recombinant expression of the aforementioned recombinant monoterpene synthases that may be used to facilitate their production, isolation and purification in significant amounts. Recombinant (+)-bornyl diphosphate synthase, 1,8-cineole synthase and (+)-sabinene synthase may be used to obtain expression or enhanced expression of (+)-bornyl diphosphate synthase, 1,8-cineole synthase and (+)-sabinene synthase in plants in order to enhance the production of monoterpenoids, or may be otherwise employed for the regulation or expression of (+)-bornyl diphosphate synthase, 1,8-cineole synthase and (+)-sabinene synthase, or the production of their products.

Deep UV laser-induced fluorescence detection of unlabeled drugs and proteins in microchip electrophoresis.

PubMed

Schulze, Philipp; Ludwig, Martin; Kohler, Frank; Belder, Detlev

2005-03-01

Deep UV fluorescence detection at 266-nm excitation wavelength has been realized for sensitive detection in microchip electrophoresis. For this purpose, an epifluorescence setup was developed enabling the coupling of a deep UV laser into a commercial fluorescence microscope. Deep UV laser excitation utilizing a frequency quadrupled pulsed laser operating at 266 nm shows an impressive performance for native fluorescence detection of various compounds in fused-silica microfluidic devices. Aromatic low molecular weight compounds such as serotonin, propranolol, a diol, and tryptophan could be detected at low-micromolar concentrations. Deep UV fluorescence detection was also successfully employed for the detection of unlabeled basic proteins. For this purpose, fused-silica chips dynamically coated with hydroxypropylmethyl cellulose were employed to suppress analyte adsorption. Utilizing fused-silica chips permanently coated with poly(vinyl alcohol), it was also possible to separate and detect egg white chicken proteins. These data show that deep UV fluorescence detection significantly widens the application range of fluorescence detection in chip-based analysis techniques.

Illumina MiSeq Sequencing for Preliminary Analysis of Microbiome Causing Primary Endodontic Infections in Egypt

PubMed Central

Azab, Marwa Mohamed; Fayyad, Dalia Mukhtar

2018-01-01

The use of high throughput next generation technologies has allowed more comprehensive analysis than traditional Sanger sequencing. The specific aim of this study was to investigate the microbial diversity of primary endodontic infections using Illumina MiSeq sequencing platform in Egyptian patients. Samples were collected from 19 patients in Suez Canal University Hospital (Endodontic Department) using sterile # 15K file and paper points. DNA was extracted using Mo Bio power soil DNA isolation extraction kit followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized on the basis of the V3 and V4 hypervariable region of the 16S rRNA gene by using paired-end sequencing on Illumina MiSeq device. MOTHUR software was used in sequence filtration and analysis of sequenced data. A total of 1858 operational taxonomic units at 97% similarity were assigned to 26 phyla, 245 families, and 705 genera. Four main phyla Firmicutes, Bacteroidetes, Proteobacteria, and Synergistetes were predominant in all samples. At genus level, Prevotella, Bacillus, Porphyromonas, Streptococcus, and Bacteroides were the most abundant. Illumina MiSeq platform sequencing can be used to investigate oral microbiome composition of endodontic infections. Elucidating the ecology of endodontic infections is a necessary step in developing effective intracanal antimicrobials. PMID:29849646

Identification of Alternative Splicing and Fusion Transcripts in Non-Small Cell Lung Cancer by RNA Sequencing.

PubMed

Hong, Yoonki; Kim, Woo Jin; Bang, Chi Young; Lee, Jae Cheol; Oh, Yeon-Mok

2016-04-01

Lung cancer is the most common cause of cancer related death. Alterations in gene sequence, structure, and expression have an important role in the pathogenesis of lung cancer. Fusion genes and alternative splicing of cancer-related genes have the potential to be oncogenic. In the current study, we performed RNA-sequencing (RNA-seq) to investigate potential fusion genes and alternative splicing in non-small cell lung cancer. RNA was isolated from lung tissues obtained from 86 subjects with lung cancer. The RNA samples from lung cancer and normal tissues were processed with RNA-seq using the HiSeq 2000 system. Fusion genes were evaluated using Defuse and ChimeraScan. Candidate fusion transcripts were validated by Sanger sequencing. Alternative splicing was analyzed using multivariate analysis of transcript sequencing and validated using quantitative real time polymerase chain reaction. RNA-seq data identified oncogenic fusion genes EML4-ALK and SLC34A2-ROS1 in three of 86 normal-cancer paired samples. Nine distinct fusion transcripts were selected using DeFuse and ChimeraScan; of which, four fusion transcripts were validated by Sanger sequencing. In 33 squamous cell carcinoma, 29 tumor specific skipped exon events and six mutually exclusive exon events were identified. ITGB4 and PYCR1 were top genes that showed significant tumor specific splice variants. In conclusion, RNA-seq data identified novel potential fusion transcripts and splice variants. Further evaluation of their functional significance in the pathogenesis of lung cancer is required.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2016-11-01

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

Evaluation of ribosomal RNA removal protocols for Salmonella RNA-Seq projects

USDA-ARS?s Scientific Manuscript database

Next generation sequencing is a powerful technology and its application to sequencing entire RNA populations of food-borne pathogens will provide valuable insights. A problem unique to prokaryotic RNA-Seq is the massive abundance of ribosomal RNA. Unlike eukaryotic messenger RNA (mRNA), bacterial ...

RNA-Seq Atlas of Glycine max: a guide to the soybean transcriptome

USDA-ARS?s Scientific Manuscript database

A first analysis of the Glycine max (L.) Merr. (soybean) transcriptome using next generation sequencing technology and RNA-Sequencing (RNA-Seq) is presented. This analysis will provide an important resource for understanding transcription and gene co-regulatory networks in soybean, the most economic...

Systematic evaluation of the impact of ChIP-seq read designs on genome coverage, peak identification, and allele-specific binding detection.

PubMed

Zhang, Qi; Zeng, Xin; Younkin, Sam; Kawli, Trupti; Snyder, Michael P; Keleş, Sündüz

2016-02-24

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments revolutionized genome-wide profiling of transcription factors and histone modifications. Although maturing sequencing technologies allow these experiments to be carried out with short (36-50 bps), long (75-100 bps), single-end, or paired-end reads, the impact of these read parameters on the downstream data analysis are not well understood. In this paper, we evaluate the effects of different read parameters on genome sequence alignment, coverage of different classes of genomic features, peak identification, and allele-specific binding detection. We generated 101 bps paired-end ChIP-seq data for many transcription factors from human GM12878 and MCF7 cell lines. Systematic evaluations using in silico variations of these data as well as fully simulated data, revealed complex interplay between the sequencing parameters and analysis tools, and indicated clear advantages of paired-end designs in several aspects such as alignment accuracy, peak resolution, and most notably, allele-specific binding detection. Our work elucidates the effect of design on the downstream analysis and provides insights to investigators in deciding sequencing parameters in ChIP-seq experiments. We present the first systematic evaluation of the impact of ChIP-seq designs on allele-specific binding detection and highlights the power of pair-end designs in such studies.

Evaluation of partial 16S ribosomal DNA sequencing for identification of nocardia species by using the MicroSeq 500 system with an expanded database.

PubMed

Cloud, Joann L; Conville, Patricia S; Croft, Ann; Harmsen, Dag; Witebsky, Frank G; Carroll, Karen C

2004-02-01

Identification of clinically significant nocardiae to the species level is important in patient diagnosis and treatment. A study was performed to evaluate Nocardia species identification obtained by partial 16S ribosomal DNA (rDNA) sequencing by the MicroSeq 500 system with an expanded database. The expanded portion of the database was developed from partial 5' 16S rDNA sequences derived from 28 reference strains (from the American Type Culture Collection and the Japanese Collection of Microorganisms). The expanded MicroSeq 500 system was compared to (i). conventional identification obtained from a combination of growth characteristics with biochemical and drug susceptibility tests; (ii). molecular techniques involving restriction enzyme analysis (REA) of portions of the 16S rRNA and 65-kDa heat shock protein genes; and (iii). when necessary, sequencing of a 999-bp fragment of the 16S rRNA gene. An unknown isolate was identified as a particular species if the sequence obtained by partial 16S rDNA sequencing by the expanded MicroSeq 500 system was 99.0% similar to that of the reference strain. Ninety-four nocardiae representing 10 separate species were isolated from patient specimens and examined by using the three different methods. Sequencing of partial 16S rDNA by the expanded MicroSeq 500 system resulted in only 72% agreement with conventional methods for species identification and 90% agreement with the alternative molecular methods. Molecular methods for identification of Nocardia species provide more accurate and rapid results than the conventional methods using biochemical and susceptibility testing. With an expanded database, the MicroSeq 500 system for partial 16S rDNA was able to correctly identify the human pathogens N. brasiliensis, N. cyriacigeorgica, N. farcinica, N. nova, N. otitidiscaviarum, and N. veterana.

Genome-Wide Association Study of a Validated Case Definition of Gulf War Illness in a Population-Representative Sample

DTIC Science & Technology

2013-09-01

sequence dataset. All procedures were performed by personnel in the IIMT UT Southwestern Genomics and Microarray Core using standard protocols. More... sequencing run, samples were demultiplexed using standard algorithms in the Genomics and Microarray Core and processed into individual sample Illumina single... Sequencing (RNA-Seq), using Illumina’s multiplexing mRNA-Seq to generate full sequence libraries from the poly-A tailed RNA to a read depth of 30

Chip design for thin-film deep ultraviolet LEDs fabricated by laser lift-off of the sapphire substrate

NASA Astrophysics Data System (ADS)

Cho, H. K.; Krüger, O.; Külberg, A.; Rass, J.; Zeimer, U.; Kolbe, T.; Knauer, A.; Einfeldt, S.; Weyers, M.; Kneissl, M.

2017-12-01

We report on a chip design which allows the laser lift-off (LLO) of the sapphire substrate sustaining the epitaxial film of flip-chip mounted deep ultraviolet light emitting diodes. A nanosecond pulsed excimer laser with a wavelength of 248 nm was used for the LLO. A mechanically stable chip design was found to be the key to prevent crack formation in the epitaxial layers and material chipping during the LLO process. Stabilization was achieved by introducing a Ti/Au leveling layer that mechanically supports the fragile epitaxial film. The electrical and optical characterization of devices before and after the LLO process shows that the device performance did not degrade by the LLO.

High-throughput illumina strand-specific RNA sequencing library preparation

USDA-ARS?s Scientific Manuscript database

Conventional Illumina RNA-Seq does not have the resolution to decode the complex eukaryote transcriptome due to the lack of RNA polarity information. Strand-specific RNA sequencing (ssRNA-Seq) can overcome these limitations and as such is better suited for genome annotation, de novo transcriptome as...

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells

PubMed Central

Pott, Sebastian

2017-01-01

Gaining insights into the regulatory mechanisms that underlie the transcriptional variation observed between individual cells necessitates the development of methods that measure chromatin organization in single cells. Here I adapted Nucleosome Occupancy and Methylome-sequencing (NOMe-seq) to measure chromatin accessibility and endogenous DNA methylation in single cells (scNOMe-seq). scNOMe-seq recovered characteristic accessibility and DNA methylation patterns at DNase hypersensitive sites (DHSs). An advantage of scNOMe-seq is that sequencing reads are sampled independently of the accessibility measurement. scNOMe-seq therefore controlled for fragment loss, which enabled direct estimation of the fraction of accessible DHSs within individual cells. In addition, scNOMe-seq provided high resolution of chromatin accessibility within individual loci which was exploited to detect footprints of CTCF binding events and to estimate the average nucleosome phasing distances in single cells. scNOMe-seq is therefore well-suited to characterize the chromatin organization of single cells in heterogeneous cellular mixtures. DOI: http://dx.doi.org/10.7554/eLife.23203.001 PMID:28653622

RNA-Skim: a rapid method for RNA-Seq quantification at transcript level

PubMed Central

Zhang, Zhaojun; Wang, Wei

2014-01-01

Motivation: RNA-Seq technique has been demonstrated as a revolutionary means for exploring transcriptome because it provides deep coverage and base pair-level resolution. RNA-Seq quantification is proven to be an efficient alternative to Microarray technique in gene expression study, and it is a critical component in RNA-Seq differential expression analysis. Most existing RNA-Seq quantification tools require the alignments of fragments to either a genome or a transcriptome, entailing a time-consuming and intricate alignment step. To improve the performance of RNA-Seq quantification, an alignment-free method, Sailfish, has been recently proposed to quantify transcript abundances using all k-mers in the transcriptome, demonstrating the feasibility of designing an efficient alignment-free method for transcriptome quantification. Even though Sailfish is substantially faster than alternative alignment-dependent methods such as Cufflinks, using all k-mers in the transcriptome quantification impedes the scalability of the method. Results: We propose a novel RNA-Seq quantification method, RNA-Skim, which partitions the transcriptome into disjoint transcript clusters based on sequence similarity, and introduces the notion of sig-mers, which are a special type of k-mers uniquely associated with each cluster. We demonstrate that the sig-mer counts within a cluster are sufficient for estimating transcript abundances with accuracy comparable with any state-of-the-art method. This enables RNA-Skim to perform transcript quantification on each cluster independently, reducing a complex optimization problem into smaller optimization tasks that can be run in parallel. As a result, RNA-Skim uses <4% of the k-mers and <10% of the CPU time required by Sailfish. It is able to finish transcriptome quantification in <10 min per sample by using just a single thread on a commodity computer, which represents >100 speedup over the state-of-the-art alignment-based methods, while delivering comparable or higher accuracy. Availability and implementation: The software is available at http://www.csbio.unc.edu/rs. Contact: weiwang@cs.ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24931995

SNP discovery in the bovine milk transcriptome using RNA-Seq technology.

PubMed

Cánovas, Angela; Rincon, Gonzalo; Islas-Trejo, Alma; Wickramasinghe, Saumya; Medrano, Juan F

2010-12-01

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle.

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

Early Detection of NSCLC Using Stromal Markers in Peripheral Blood

DTIC Science & Technology

2016-09-01

circulating myeloid cells, flow cytometry, RNA -sequencing, expression profiling. 3. ACCOMPLISHMENTS:  What were the major goals of the project...Subtask 2: Flow cytometry sorting of circulating myeloid cells. Subtask 3: RNA -Sequencing Subtask 4: RNA -seq data analysis Subtask 5: Feasible RT-PCR...accomplished the patient recruitment, flow cytometry sorting of circulating myeloid cells, RNA -sequencing of the samples. During the RNA - seq data analysis, we

Stroma Based Prognosticators Incorporating Differences between African and European Americans

DTIC Science & Technology

2017-10-01

amenable to bisulfite sequencing of more than a few genes. Exploiting the recent three-fold reduction in the cost of sequencing per read , we developed oligo...cards. The ability of the HiSeq 4000 to obtain about three times as many reads as the HiSeq2500, at the same price, means we can stay on track, though...capture, and sequencing (Table 2). We obtain tens of millions of mapped deduplicated reads per sample, while using only 5% of a sequencing lane per sample

Switchgrass ubiquitin promoter (PVUBI2) and uses thereof

DOEpatents

Stewart, C. Neal; Mann, David George James

2013-12-10

The subject application provides polynucleotides, compositions thereof and methods for regulating gene expression in a plant. Polynucleotides disclosed herein comprise novel sequences for a promoter isolated from Panicum virgatum (switchgrass) that initiates transcription of an operably linked nucleotide sequence. Thus, various embodiments of the invention comprise the nucleotide sequence of SEQ ID NO: 2 or fragments thereof comprising nucleotides 1 to 692 of SEQ ID NO: 2 that are capable of driving the expression of an operably linked nucleic acid sequence.

Processing and population genetic analysis of multigenic datasets with ProSeq3 software.

PubMed

Filatov, Dmitry A

2009-12-01

The current tendency in molecular population genetics is to use increasing numbers of genes in the analysis. Here I describe a program for handling and population genetic analysis of DNA polymorphism data collected from multiple genes. The program includes a sequence/alignment editor and an internal relational database that simplify the preparation and manipulation of multigenic DNA polymorphism datasets. The most commonly used DNA polymorphism analyses are implemented in ProSeq3, facilitating population genetic analysis of large multigenic datasets. Extensive input/output options make ProSeq3 a convenient hub for sequence data processing and analysis. The program is available free of charge from http://dps.plants.ox.ac.uk/sequencing/proseq.htm.

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

PubMed

David, Fabrice P A; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

HTSstation: A Web Application and Open-Access Libraries for High-Throughput Sequencing Data Analysis

PubMed Central

David, Fabrice P. A.; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J.; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch. PMID:24475057

Congruent Deep Relationships in the Grape Family (Vitaceae) Based on Sequences of Chloroplast Genomes and Mitochondrial Genes via Genome Skimming

PubMed Central

Zhang, Ning; Wen, Jun; Zimmer, Elizabeth A.

2015-01-01

Vitaceae is well-known for having one of the most economically important fruits, i.e., the grape (Vitis vinifera). The deep phylogeny of the grape family was not resolved until a recent phylogenomic analysis of 417 nuclear genes from transcriptome data. However, it has been reported extensively that topologies based on nuclear and organellar genes may be incongruent due to differences in their evolutionary histories. Therefore, it is important to reconstruct a backbone phylogeny of the grape family using plastomes and mitochondrial genes. In this study, next-generation sequencing data sets of 27 species were obtained using genome skimming with total DNAs from silica-gel preserved tissue samples on an Illumina HiSeq 2500 instrument. Plastomes were assembled using the combination of de novo and reference genome (of V. vinifera) methods. Sixteen mitochondrial genes were also obtained via genome skimming using the reference genome of V. vinifera. Extensive phylogenetic analyses were performed using maximum likelihood and Bayesian methods. The topology based on either plastome data or mitochondrial genes is congruent with the one using hundreds of nuclear genes, indicating that the grape family did not exhibit significant reticulation at the deep level. The results showcase the power of genome skimming in capturing extensive phylogenetic data: especially from chloroplast and mitochondrial DNAs. PMID:26656830

Congruent Deep Relationships in the Grape Family (Vitaceae) Based on Sequences of Chloroplast Genomes and Mitochondrial Genes via Genome Skimming.

PubMed

Zhang, Ning; Wen, Jun; Zimmer, Elizabeth A

2015-01-01

Vitaceae is well-known for having one of the most economically important fruits, i.e., the grape (Vitis vinifera). The deep phylogeny of the grape family was not resolved until a recent phylogenomic analysis of 417 nuclear genes from transcriptome data. However, it has been reported extensively that topologies based on nuclear and organellar genes may be incongruent due to differences in their evolutionary histories. Therefore, it is important to reconstruct a backbone phylogeny of the grape family using plastomes and mitochondrial genes. In this study,next-generation sequencing data sets of 27 species were obtained using genome skimming with total DNAs from silica-gel preserved tissue samples on an Illumina NextSeq 500 instrument [corrected]. Plastomes were assembled using the combination of de novo and reference genome (of V. vinifera) methods. Sixteen mitochondrial genes were also obtained via genome skimming using the reference genome of V. vinifera. Extensive phylogenetic analyses were performed using maximum likelihood and Bayesian methods. The topology based on either plastome data or mitochondrial genes is congruent with the one using hundreds of nuclear genes, indicating that the grape family did not exhibit significant reticulation at the deep level. The results showcase the power of genome skimming in capturing extensive phylogenetic data: especially from chloroplast and mitochondrial DNAs.

FREQ-Seq: A Rapid, Cost-Effective, Sequencing-Based Method to Determine Allele Frequencies Directly from Mixed Populations

PubMed Central

Delaney, Nigel F.; Marx, Christopher J.

2012-01-01

Understanding evolutionary dynamics within microbial populations requires the ability to accurately follow allele frequencies through time. Here we present a rapid, cost-effective method (FREQ-Seq) that leverages Illumina next-generation sequencing for localized, quantitative allele frequency detection. Analogous to RNA-Seq, FREQ-Seq relies upon counts from the >105 reads generated per locus per time-point to determine allele frequencies. Loci of interest are directly amplified from a mixed population via two rounds of PCR using inexpensive, user-designed oligonucleotides and a bar-coded bridging primer system that can be regenerated in-house. The resulting bar-coded PCR products contain the adapters needed for Illumina sequencing, eliminating further library preparation. We demonstrate the utility of FREQ-Seq by determining the order and dynamics of beneficial alleles that arose as a microbial population, founded with an engineered strain of Methylobacterium, evolved to grow on methanol. Quantifying allele frequencies with minimal bias down to 1% abundance allowed effective analysis of SNPs, small in-dels and insertions of transposable elements. Our data reveal large-scale clonal interference during the early stages of adaptation and illustrate the utility of FREQ-Seq as a cost-effective tool for tracking allele frequencies in populations. PMID:23118913

High-throughput detection of RNA processing in bacteria.

PubMed

Gill, Erin E; Chan, Luisa S; Winsor, Geoffrey L; Dobson, Neil; Lo, Raymond; Ho Sui, Shannan J; Dhillon, Bhavjinder K; Taylor, Patrick K; Shrestha, Raunak; Spencer, Cory; Hancock, Robert E W; Unrau, Peter J; Brinkman, Fiona S L

2018-03-27

Understanding the RNA processing of an organism's transcriptome is an essential but challenging step in understanding its biology. Here we investigate with unprecedented detail the transcriptome of Pseudomonas aeruginosa PAO1, a medically important and innately multi-drug resistant bacterium. We systematically mapped RNA cleavage and dephosphorylation sites that result in 5'-monophosphate terminated RNA (pRNA) using monophosphate RNA-Seq (pRNA-Seq). Transcriptional start sites (TSS) were also mapped using differential RNA-Seq (dRNA-Seq) and both datasets were compared to conventional RNA-Seq performed in a variety of growth conditions. The pRNA-Seq library revealed known tRNA, rRNA and transfer-messenger RNA (tmRNA) processing sites, together with previously uncharacterized RNA cleavage events that were found disproportionately near the 5' ends of transcripts associated with basic bacterial functions such as oxidative phosphorylation and purine metabolism. The majority (97%) of the processed mRNAs were cleaved at precise codon positions within defined sequence motifs indicative of distinct endonucleolytic activities. The most abundant of these motifs corresponded closely to an E. coli RNase E site previously established in vitro. Using the dRNA-Seq library, we performed an operon analysis and predicted 3159 potential TSS. A correlation analysis uncovered 105 antiparallel pairs of TSS that were separated by 18 bp from each other and were centered on single palindromic TAT(A/T)ATA motifs (likely - 10 promoter elements), suggesting that, consistent with previous in vitro experimentation, these sites can initiate transcription bi-directionally and may thus provide a novel form of transcriptional regulation. TSS and RNA-Seq analysis allowed us to confirm expression of small non-coding RNAs (ncRNAs), many of which are differentially expressed in swarming and biofilm formation conditions. This study uses pRNA-Seq, a method that provides a genome-wide survey of RNA processing, to study the bacterium Pseudomonas aeruginosa and discover extensive transcript processing not previously appreciated. We have also gained novel insight into RNA maturation and turnover as well as a potential novel form of transcription regulation. NOTE: All sequence data has been submitted to the NCBI sequence read archive. Accession numbers are as follows: [NCBI sequence read archive: SRX156386, SRX157659, SRX157660, SRX157661, SRX157683 and SRX158075]. The sequence data is viewable using Jbrowse on www.pseudomonas.com .

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

PubMed

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

2013-04-01

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

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

PubMed

Prakash, Celine; Haeseler, Arndt Von

2017-03-01

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

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

PubMed Central

Haeseler, Arndt Von

2017-01-01

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

Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and Genome Analyzer systems

PubMed Central

2011-01-01

Background The generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases. Results We provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range. Conclusions The errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms. PMID:22067484

Sunflower centromeres consist of a centromere-specific LINE and a chromosome-specific tandem repeat.

PubMed

Nagaki, Kiyotaka; Tanaka, Keisuke; Yamaji, Naoki; Kobayashi, Hisato; Murata, Minoru

2015-01-01

The kinetochore is a protein complex including kinetochore-specific proteins that plays a role in chromatid segregation during mitosis and meiosis. The complex associates with centromeric DNA sequences that are usually species-specific. In plant species, tandem repeats including satellite DNA sequences and retrotransposons have been reported as centromeric DNA sequences. In this study on sunflowers, a cDNA-encoding centromere-specific histone H3 (CENH3) was isolated from a cDNA pool from a seedling, and an antibody was raised against a peptide synthesized from the deduced cDNA. The antibody specifically recognized the sunflower CENH3 (HaCENH3) and showed centromeric signals by immunostaining and immunohistochemical staining analysis. The antibody was also applied in chromatin immunoprecipitation (ChIP)-Seq to isolate centromeric DNA sequences and two different types of repetitive DNA sequences were identified. One was a long interspersed nuclear element (LINE)-like sequence, which showed centromere-specific signals on almost all chromosomes in sunflowers. This is the first report of a centromeric LINE sequence, suggesting possible centromere targeting ability. Another type of identified repetitive DNA was a tandem repeat sequence with a 187-bp unit that was found only on a pair of chromosomes. The HaCENH3 content of the tandem repeats was estimated to be much higher than that of the LINE, which implies centromere evolution from LINE-based centromeres to more stable tandem-repeat-based centromeres. In addition, the epigenetic status of the sunflower centromeres was investigated by immunohistochemical staining and ChIP, and it was found that centromeres were heterochromatic.

Genome-Wide Mutant Fitness Profiling Identifies Nutritional Requirements for Optimal Growth of Yersinia pestis in Deep Tissue

PubMed Central

Palace, Samantha G.; Proulx, Megan K.; Lu, Shan; Baker, Richard E.

2014-01-01

ABSTRACT Rapid growth in deep tissue is essential to the high virulence of Yersinia pestis, causative agent of plague. To better understand the mechanisms underlying this unusual ability, we used transposon mutagenesis and high-throughput sequencing (Tn-seq) to systematically probe the Y. pestis genome for elements contributing to fitness during infection. More than a million independent insertion mutants representing nearly 200,000 unique genotypes were generated in fully virulent Y. pestis. Each mutant in the library was assayed for its ability to proliferate in vitro on rich medium and in mice following intravenous injection. Virtually all genes previously established to contribute to virulence following intravenous infection showed significant fitness defects, with the exception of genes for yersiniabactin biosynthesis, which were masked by strong intercellular complementation effects. We also identified more than 30 genes with roles in nutrient acquisition and metabolism as experiencing strong selection during infection. Many of these genes had not previously been implicated in Y. pestis virulence. We further examined the fitness defects of strains carrying mutations in two such genes—encoding a branched-chain amino acid importer (brnQ) and a glucose importer (ptsG)—both in vivo and in a novel defined synthetic growth medium with nutrient concentrations matching those in serum. Our findings suggest that diverse nutrient limitations in deep tissue play a more important role in controlling bacterial infection than has heretofore been appreciated. Because much is known about Y. pestis pathogenesis, this study also serves as a test case that assesses the ability of Tn-seq to detect virulence genes. PMID:25139902

ScaffoldSeq: Software for characterization of directed evolution populations.

PubMed

Woldring, Daniel R; Holec, Patrick V; Hackel, Benjamin J

2016-07-01

ScaffoldSeq is software designed for the numerous applications-including directed evolution analysis-in which a user generates a population of DNA sequences encoding for partially diverse proteins with related functions and would like to characterize the single site and pairwise amino acid frequencies across the population. A common scenario for enzyme maturation, antibody screening, and alternative scaffold engineering involves naïve and evolved populations that contain diversified regions, varying in both sequence and length, within a conserved framework. Analyzing the diversified regions of such populations is facilitated by high-throughput sequencing platforms; however, length variability within these regions (e.g., antibody CDRs) encumbers the alignment process. To overcome this challenge, the ScaffoldSeq algorithm takes advantage of conserved framework sequences to quickly identify diverse regions. Beyond this, unintended biases in sequence frequency are generated throughout the experimental workflow required to evolve and isolate clones of interest prior to DNA sequencing. ScaffoldSeq software uniquely handles this issue by providing tools to quantify and remove background sequences, cluster similar protein families, and dampen the impact of dominant clones. The software produces graphical and tabular summaries for each region of interest, allowing users to evaluate diversity in a site-specific manner as well as identify epistatic pairwise interactions. The code and detailed information are freely available at http://research.cems.umn.edu/hackel. Proteins 2016; 84:869-874. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

High resolution Chromatin Immunoprecipitation (ChIP) sequencing reveals novel bindings targets and prognostic role for SOX11 in Mantle cell lymphoma

PubMed Central

Kuo, Pei-Yu; Leshchenko, Violetta V.; Fazzari, Melissa J.; Perumal, Deepak; Gellen, Tobias; He, Tianfang; Iqbal, Javeed; Baumgartner-Wennerholm, Stefanie; Nygren, Lina; Zhang, Fan; Zhang, Weijia; Suh, K. Stephen; Goy, Andre; Yang, David T.; Chan, Wing-Chung; Kahl, Brad S.; Verma, Amit K.; Gascoyne, Randy D.; Kimby, Eva; Sander, Birgitta; Ye, B. Hilda; Melnick, Ari M.; Parekh, Samir

2015-01-01

SOX11 (Sex determining region Y-box 11) expression is specific for MCL as compared to other Non-Hodgkin's lymphomas. However, the function and direct binding targets of SOX11 in MCL are largely unknown. We used high-resolution ChIP-Seq to identify the direct target genes of SOX11 in a genome-wide, unbiased manner and elucidate its functional significance. Pathway analysis identified WNT, PKA and TGF-beta signaling pathways as significantly enriched by SOX11 target genes. qCHIP and promoter reporter assays confirmed that SOX11 directly binds to individual genes and modulates their transcription activities in these pathways in MCL. Functional studies using RNA interference demonstrate that SOX11 directly regulates WNT in MCL. We analyzed SOX11 expression in three independent well-annotated tissue microarrays from the University of Wisconsin (UW), Karolinska Institute and British Columbia Cancer Agency (BCCA). Our findings suggest that high SOX11 expression is associated with improved survival in a subset of MCL patients, particularly those treated with intensive chemotherapy. Transcriptional regulation of WNT and other biological pathways affected by SOX11 target genes may help explain the impact of SOX11 expression on patient outcomes. PMID:24681958

Simultaneous identification and molecular characterization of viruses associated with an apple tree with mosaic symptom

USDA-ARS?s Scientific Manuscript database

We conducted genomic sequencing to identify viruses associated with mosaic disease of an apple tree using the high-throughput sequencing (HTS) Illumina RNA-seq platform. The objective was to examine if rapid identification and characterization of viruses could be effectively achieved by RNA-seq anal...

Swine transcriptome characterization by combined Iso-Seq and RNA-seq for annotating the emerging long read-based reference genome

USDA-ARS?s Scientific Manuscript database

PacBio long-read sequencing technology is increasingly popular in genome sequence assembly and transcriptome cataloguing. Recently, a new-generation pig reference genome was assembled based on long reads from this technology. To finely annotate this genome assembly, transcriptomes of nine tissues fr...

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

PubMed

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

2015-04-01

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

Genome-wide Target Enrichment-aided Chip Design: a 66 K SNP Chip for Cashmere Goat.

PubMed

Qiao, Xian; Su, Rui; Wang, Yang; Wang, Ruijun; Yang, Ting; Li, Xiaokai; Chen, Wei; He, Shiyang; Jiang, Yu; Xu, Qiwu; Wan, Wenting; Zhang, Yaolei; Zhang, Wenguang; Chen, Jiang; Liu, Bin; Liu, Xin; Fan, Yixing; Chen, Duoyuan; Jiang, Huaizhi; Fang, Dongming; Liu, Zhihong; Wang, Xiaowen; Zhang, Yanjun; Mao, Danqing; Wang, Zhiying; Di, Ran; Zhao, Qianjun; Zhong, Tao; Yang, Huanming; Wang, Jian; Wang, Wen; Dong, Yang; Chen, Xiaoli; Xu, Xun; Li, Jinquan

2017-08-17

Compared with the commercially available single nucleotide polymorphism (SNP) chip based on the Bead Chip technology, the solution hybrid selection (SHS)-based target enrichment SNP chip is not only design-flexible, but also cost-effective for genotype sequencing. In this study, we propose to design an animal SNP chip using the SHS-based target enrichment strategy for the first time. As an update to the international collaboration on goat research, a 66 K SNP chip for cashmere goat was created from the whole-genome sequencing data of 73 individuals. Verification of this 66 K SNP chip with the whole-genome sequencing data of 436 cashmere goats showed that the SNP call rates was between 95.3% and 99.8%. The average sequencing depth for target SNPs were 40X. The capture regions were shown to be 200 bp that flank target SNPs. This chip was further tested in a genome-wide association analysis of cashmere fineness (fiber diameter). Several top hit loci were found marginally associated with signaling pathways involved in hair growth. These results demonstrate that the 66 K SNP chip is a useful tool in the genomic analyses of cashmere goats. The successful chip design shows that the SHS-based target enrichment strategy could be applied to SNP chip design in other species.

PeakRanger: A cloud-enabled peak caller for ChIP-seq data

PubMed Central

2011-01-01

Background Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks. Results In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project. Conclusions Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: http://www.modencode.org/software/ranger/ PMID:21554709

A deep transcriptomic analysis of pod development in the vanilla orchid (Vanilla planifolia).

PubMed

Rao, Xiaolan; Krom, Nick; Tang, Yuhong; Widiez, Thomas; Havkin-Frenkel, Daphna; Belanger, Faith C; Dixon, Richard A; Chen, Fang

2014-11-07

Pods of the vanilla orchid (Vanilla planifolia) accumulate large amounts of the flavor compound vanillin (3-methoxy, 4-hydroxy-benzaldehyde) as a glucoside during the later stages of their development. At earlier stages, the developing seeds within the pod synthesize a novel lignin polymer, catechyl (C) lignin, in their coats. Genomic resources for determining the biosynthetic routes to these compounds and other flavor components in V. planifolia are currently limited. Using next-generation sequencing technologies, we have generated very large gene sequence datasets from vanilla pods at different times of development, and representing different tissue types, including the seeds, hairs, placental and mesocarp tissues. This developmental series was chosen as being the most informative for interrogation of pathways of vanillin and C-lignin biosynthesis in the pod and seed, respectively. The combined 454/Illumina RNA-seq platforms provide both deep sequence coverage and high quality de novo transcriptome assembly for this non-model crop species. The annotated sequence data provide a foundation for understanding multiple aspects of the biochemistry and development of the vanilla bean, as exemplified by the identification of candidate genes involved in lignin biosynthesis. Our transcriptome data indicate that C-lignin formation in the seed coat involves coordinate expression of monolignol biosynthetic genes with the exception of those encoding the caffeoyl coenzyme A 3-O-methyltransferase for conversion of caffeoyl to feruloyl moieties. This database provides a general resource for further studies on this important flavor species.

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

PubMed

Reid-Bayliss, Kate S; Loeb, Lawrence A

2017-08-29

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

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories.

PubMed

Corrie, Brian D; Marthandan, Nishanth; Zimonja, Bojan; Jaglale, Jerome; Zhou, Yang; Barr, Emily; Knoetze, Nicole; Breden, Frances M W; Christley, Scott; Scott, Jamie K; Cowell, Lindsay G; Breden, Felix

2018-07-01

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Peregrine

PubMed Central

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

2013-01-01

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

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

PubMed

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

2017-03-01

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

Integrative analyses of RNA editing, alternative splicing, and expression of young genes in human brain transcriptome by deep RNA sequencing.

PubMed

Wu, Dong-Dong; Ye, Ling-Qun; Li, Yan; Sun, Yan-Bo; Shao, Yi; Chen, Chunyan; Zhu, Zhu; Zhong, Li; Wang, Lu; Irwin, David M; Zhang, Yong E; Zhang, Ya-Ping

2015-08-01

Next-generation RNA sequencing has been successfully used for identification of transcript assembly, evaluation of gene expression levels, and detection of post-transcriptional modifications. Despite these large-scale studies, additional comprehensive RNA-seq data from different subregions of the human brain are required to fully evaluate the evolutionary patterns experienced by the human brain transcriptome. Here, we provide a total of 6.5 billion RNA-seq reads from different subregions of the human brain. A significant correlation was observed between the levels of alternative splicing and RNA editing, which might be explained by a competition between the molecular machineries responsible for the splicing and editing of RNA. Young human protein-coding genes demonstrate biased expression to the neocortical and non-neocortical regions during evolution on the lineage leading to humans. We also found that a significantly greater number of young human protein-coding genes are expressed in the putamen, a tissue that was also observed to have the highest level of RNA-editing activity. The putamen, which previously received little attention, plays an important role in cognitive ability, and our data suggest a potential contribution of the putamen to human evolution. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.

PubMed

Gierahn, Todd M; Wadsworth, Marc H; Hughes, Travis K; Bryson, Bryan D; Butler, Andrew; Satija, Rahul; Fortune, Sarah; Love, J Christopher; Shalek, Alex K

2017-04-01

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq.

PubMed

Wills, Quin F; Mellado-Gomez, Esther; Nolan, Rory; Warner, Damien; Sharma, Eshita; Broxholme, John; Wright, Benjamin; Lockstone, Helen; James, William; Lynch, Mark; Gonzales, Michael; West, Jay; Leyrat, Anne; Padilla-Parra, Sergi; Filippi, Sarah; Holmes, Chris; Moore, Michael D; Bowden, Rory

2017-01-07

Single-cell RNA-Seq can be a valuable and unbiased tool to dissect cellular heterogeneity, despite the transcriptome's limitations in describing higher functional phenotypes and protein events. Perhaps the most important shortfall with transcriptomic 'snapshots' of cell populations is that they risk being descriptive, only cataloging heterogeneity at one point in time, and without microenvironmental context. Studying the genetic ('nature') and environmental ('nurture') modifiers of heterogeneity, and how cell population dynamics unfold over time in response to these modifiers is key when studying highly plastic cells such as macrophages. We introduce the programmable Polaris™ microfluidic lab-on-chip for single-cell sequencing, which performs live-cell imaging while controlling for the culture microenvironment of each cell. Using gene-edited macrophages we demonstrate how previously unappreciated knockout effects of SAMHD1, such as an altered oxidative stress response, have a large paracrine signaling component. Furthermore, we demonstrate single-cell pathway enrichments for cell cycle arrest and APOBEC3G degradation, both associated with the oxidative stress response and altered proteostasis. Interestingly, SAMHD1 and APOBEC3G are both HIV-1 inhibitors ('restriction factors'), with no known co-regulation. As single-cell methods continue to mature, so will the ability to move beyond simple 'snapshots' of cell populations towards studying the determinants of population dynamics. By combining single-cell culture, live-cell imaging, and single-cell sequencing, we have demonstrated the ability to study cell phenotypes and microenvironmental influences. It's these microenvironmental components - ignored by standard single-cell workflows - that likely determine how macrophages, for example, react to inflammation and form treatment resistant HIV reservoirs.

Experimental study on deep hole drilling of 17-4PH material

NASA Astrophysics Data System (ADS)

Uzhanfeng, LI; Uquantai, LI

2018-02-01

This paper uses 17-4PH material as the research object, according to the material characteristics of 17-4PH, designed and carried out deep hole drilling test. The purpose of the experiment is to study and discuss the three major problems of tool wear, chip shape and axial deviation of the hole in the process of deep hole drilling of 17-4PH materials. Through the deep hole drilling test of 17-4PH material, the variation of the chip shape and the deflection of the hole axis was obtained under different wear conditions.

Intratumor heterogeneity and clonal evolution in an aggressive papillary thyroid cancer and matched metastases.

PubMed

Le Pennec, Soazig; Konopka, Tomasz; Gacquer, David; Fimereli, Danai; Tarabichi, Maxime; Tomás, Gil; Savagner, Frédérique; Decaussin-Petrucci, Myriam; Trésallet, Christophe; Andry, Guy; Larsimont, Denis; Detours, Vincent; Maenhaut, Carine

2015-04-01

The contribution of intratumor heterogeneity to thyroid metastatic cancers is still unknown. The clonal relationships between the primary thyroid tumors and lymph nodes (LN) or distant metastases are also poorly understood. The objective of this study was to determine the phylogenetic relationships between matched primary thyroid tumors and metastases. We searched for non-synonymous single-nucleotide variants (nsSNVs), gene fusions, alternative transcripts, and loss of heterozygosity (LOH) by paired-end massively parallel sequencing of cDNA (RNA-Seq) in a patient diagnosed with an aggressive papillary thyroid cancer (PTC). Seven tumor samples from a stage IVc PTC patient were analyzed by RNA-Seq: two areas from the primary tumor, four areas from two LN metastases, and one area from a pleural metastasis (PLM). A large panel of other thyroid tumors was used for Sanger sequencing screening. We identified seven new nsSNVs. Some of these were early events clonally present in both the primary PTC and the three matched metastases. Other nsSNVs were private to the primary tumor, the LN metastases and/or the PLM. Three new gene fusions were identified. A novel cancer-specific KAZN alternative transcript was detected in this aggressive PTC and in dozens of additional thyroid tumors. The PLM harbored an exclusive whole-chromosome 19 LOH. We have presented the first, to our knowledge, deep sequencing study comparing the mutational spectra in a PTC and both LN and distant metastases. This study has yielded novel findings concerning intra-tumor heterogeneity, clonal evolution and metastases dissemination in thyroid cancer. © 2015 Society for Endocrinology.

Deep Sequencing of RNA from Ancient Maize Kernels

PubMed Central

Rasmussen, Morten; Cappellini, Enrico; Romero-Navarro, J. Alberto; Wales, Nathan; Alquezar-Planas, David E.; Penfield, Steven; Brown, Terence A.; Vielle-Calzada, Jean-Philippe; Montiel, Rafael; Jørgensen, Tina; Odegaard, Nancy; Jacobs, Michael; Arriaza, Bernardo; Higham, Thomas F. G.; Ramsey, Christopher Bronk; Willerslev, Eske; Gilbert, M. Thomas P.

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 hypothesize that seeds offer a plausible refuge for long-term RNA survival, due to the fundamental role of RNA during seed germination. Using RNA-Seq on cDNA synthesized from nucleic acid extracts, we validate this hypothesis through demonstration of partial transcriptomal recovery from two sources of ancient maize kernels. The results suggest that ancient seed transcriptomics may offer a powerful new tool with which to study plant domestication. PMID:23326310

Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A web-based tool for addressing the challenges of cross-species extrapolation of chemical toxicity

EPA Science Inventory

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitat...

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

PubMed

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

2017-12-28

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

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data

PubMed Central

Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie

2018-01-01

Abstract Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power. PMID:29106630

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

In vivo insertion pool sequencing identifies virulence factors in a complex fungal–host interaction

PubMed Central

Uhse, Simon; Pflug, Florian G.; Stirnberg, Alexandra; Ehrlinger, Klaus; von Haeseler, Arndt

2018-01-01

Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U. maydis. iPool-Seq features tagmentation, unique molecular barcodes, and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues. In a proof of concept using iPool-Seq, we identified 28 virulence factors, including 23 that were previously uncharacterized, from an initial pool of 195 candidate effector mutants. Because of its sensitivity and quantitative nature, iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts. PMID:29684023

Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles.

PubMed

Gadala-Maria, Daniel; Yaari, Gur; Uduman, Mohamed; Kleinstein, Steven H

2015-02-24

Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

Recovering complete mitochondrial genome sequences from RNA-Seq: A case study of Polytomella non-photosynthetic green algae.

PubMed

Tian, Yao; Smith, David Roy

2016-05-01

Thousands of mitochondrial genomes have been sequenced, but there are comparatively few available mitochondrial transcriptomes. This might soon be changing. High-throughput RNA sequencing (RNA-Seq) techniques have made it fast and cheap to generate massive amounts of mitochondrial transcriptomic data. Here, we explore the utility of RNA-Seq for assembling mitochondrial genomes and studying their expression patterns. Specifically, we investigate the mitochondrial transcriptomes from Polytomella non-photosynthetic green algae, which have among the smallest, most reduced mitochondrial genomes from the Archaeplastida as well as fragmented rRNA-coding regions, palindromic genes, and linear chromosomes with telomeres. Isolation of whole genomic RNA from the four known Polytomella species followed by Illumina paired-end sequencing generated enough mitochondrial-derived reads to easily recover almost-entire mitochondrial genome sequences. Read-mapping and coverage statistics also gave insights into Polytomella mitochondrial transcriptional architecture, revealing polycistronic transcripts and the expression of telomeres and palindromic genes. Ultimately, RNA-Seq is a promising, cost-effective technique for studying mitochondrial genetics, but it does have drawbacks, which are discussed. One of its greatest potentials, as shown here, is that it can be used to generate near-complete mitochondrial genome sequences, which could be particularly useful in situations where there is a lack of available mtDNA data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2017-01-01

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

MiSNPDb: a web-based genomic resources of tropical ecology fruit mango (Mangifera indica L.) for phylogeography and varietal differentiation.

PubMed

Iquebal, M A; Jaiswal, Sarika; Mahato, Ajay Kumar; Jayaswal, Pawan K; Angadi, U B; Kumar, Neeraj; Sharma, Nimisha; Singh, Anand K; Srivastav, Manish; Prakash, Jai; Singh, S K; Khan, Kasim; Mishra, Rupesh K; Rajan, Shailendra; Bajpai, Anju; Sandhya, B S; Nischita, Puttaraju; Ravishankar, K V; Dinesh, M R; Rai, Anil; Kumar, Dinesh; Sharma, Tilak R; Singh, Nagendra K

2017-11-02

Mango is one of the most important fruits of tropical ecological region of the world, well known for its nutritive value, aroma and taste. Its world production is >45MT worth >200 billion US dollars. Genomic resources are required for improvement in productivity and management of mango germplasm. There is no web-based genomic resources available for mango. Hence rapid and cost-effective high throughput putative marker discovery is required to develop such resources. RAD-based marker discovery can cater this urgent need till whole genome sequence of mango becomes available. Using a panel of 84 mango varieties, a total of 28.6 Gb data was generated by ddRAD-Seq approach on Illumina HiSeq 2000 platform. A total of 1.25 million SNPs were discovered. Phylogenetic tree using 749 common SNPs across these varieties revealed three major lineages which was compared with geographical locations. A web genomic resources MiSNPDb, available at http://webtom.cabgrid.res.in/mangosnps/ is based on 3-tier architecture, developed using PHP, MySQL and Javascript. This web genomic resources can be of immense use in the development of high density linkage map, QTL discovery, varietal differentiation, traceability, genome finishing and SNP chip development for future GWAS in genomic selection program. We report here world's first web-based genomic resources for genetic improvement and germplasm management of mango.

Engagement and communication among participants in the ClinSeq Genomic Sequencing Study.

PubMed

Hooker, Gillian W; Umstead, Kendall L; Lewis, Katie L; Koehly, Laura K; Biesecker, Leslie G; Biesecker, Barbara B

2017-01-01

As clinical genome sequencing expand its reach, understanding how individuals engage with this process are of critical importance. In this study, we aimed to describe internal engagement and its correlates among a ClinSeq cohort of adults consented to genome sequencing and receipt of results. This study was framed using the precaution adoption process model (PAPM), in which knowledge predicts engagement and engagement predicts subsequent behaviors. Prior to receipt of sequencing results, 630 participants in the study completed a baseline survey. Engagement was assessed as the frequency with which participants thought about their participation in ClinSeq since enrollment. Results were consistent with the PAPM: those with higher genomics knowledge reported higher engagement (r = 0.13, P = 0.001) and those who were more engaged reported more frequent communication with their physicians (r = 0.28, P < 0.001) and family members (r = 0.35, P < 0.001) about ClinSeq. Characteristics of those with higher engagement included poorer overall health (r = -0.13, P = 0.002), greater seeking of health information (r = 0.16, P < 0.001), and more recent study enrollment (r = -0.21, P < 0.001). These data support the importance of internal engagement in communication related to genomic sequencing.Genet Med 19 1, 98-103.

A Novel Computational Strategy to Identify A-to-I RNA Editing Sites by RNA-Seq Data: De Novo Detection in Human Spinal Cord Tissue

PubMed Central

Picardi, Ernesto; Gallo, Angela; Galeano, Federica; Tomaselli, Sara; Pesole, Graziano

2012-01-01

RNA editing is a post-transcriptional process occurring in a wide range of organisms. In human brain, the A-to-I RNA editing, in which individual adenosine (A) bases in pre-mRNA are modified to yield inosine (I), is the most frequent event. Modulating gene expression, RNA editing is essential for cellular homeostasis. Indeed, its deregulation has been linked to several neurological and neurodegenerative diseases. To date, many RNA editing sites have been identified by next generation sequencing technologies employing massive transcriptome sequencing together with whole genome or exome sequencing. While genome and transcriptome reads are not always available for single individuals, RNA-Seq data are widespread through public databases and represent a relevant source of yet unexplored RNA editing sites. In this context, we propose a simple computational strategy to identify genomic positions enriched in novel hypothetical RNA editing events by means of a new two-steps mapping procedure requiring only RNA-Seq data and no a priori knowledge of RNA editing characteristics and genomic reads. We assessed the suitability of our procedure by confirming A-to-I candidates using conventional Sanger sequencing and performing RNA-Seq as well as whole exome sequencing of human spinal cord tissue from a single individual. PMID:22957051

Retrotransposon Capture Sequencing (RC-Seq): A Targeted, High-Throughput Approach to Resolve Somatic L1 Retrotransposition in Humans.

PubMed

Sanchez-Luque, Francisco J; Richardson, Sandra R; Faulkner, Geoffrey J

2016-01-01

Mobile genetic elements (MGEs) are of critical importance in genomics and developmental biology. Polymorphic and somatic MGE insertions have the potential to impact the phenotype of an individual, depending on their genomic locations and functional consequences. However, the identification of polymorphic and somatic insertions among the plethora of copies residing in the genome presents a formidable technical challenge. Whole genome sequencing has the potential to address this problem; however, its efficacy depends on the abundance of cells carrying the new insertion. Robust detection of somatic insertions present in only a subset of cells within a given sample can also be prohibitively expensive due to a requirement for high sequencing depth. Here, we describe retrotransposon capture sequencing (RC-seq), a sequence capture approach in which Illumina libraries are enriched for fragments containing the 5' and 3' termini of specific MGEs. RC-seq allows the detection of known polymorphic insertions present in an individual, as well as the identification of rare or private germline insertions not previously described. Furthermore, RC-seq can be used to detect and characterize somatic insertions, providing a valuable tool to elucidate the extent and characteristics of MGE activity in healthy tissues and in various disease states.

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing

PubMed Central

Tourlousse, Dieter M.; Yoshiike, Satowa; Ohashi, Akiko; Matsukura, Satoko; Noda, Naohiro

2017-01-01

Abstract High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible identity to known nucleotide sequences, permitting unambiguous identification of spike-in sequences in 16S-seq read data from any microbiome sample. Using defined mock communities and environmental microbiota, we characterized the performance of the spike-in standards and demonstrated their utility for evaluating data quality on a per-sample basis. Further, we showed that staggered spike-in mixtures added at the point of DNA extraction enable concurrent estimation of absolute microbial abundances suitable for comparative analysis. Results also underscored that template-specific Illumina sequencing artifacts may lead to biases in the perceived abundance of certain taxa. Taken together, the spike-in standards represent a novel bioanalytical tool that can substantially improve 16S-seq-based microbiome studies by enabling comprehensive quality control along with absolute quantification. PMID:27980100

Indel detection from DNA and RNA sequencing data with transIndel.

PubMed

Yang, Rendong; Van Etten, Jamie L; Dehm, Scott M

2018-04-19

Insertions and deletions (indels) are a major class of genomic variation associated with human disease. Indels are primarily detected from DNA sequencing (DNA-seq) data but their transcriptional consequences remain unexplored due to challenges in discriminating medium-sized and large indels from splicing events in RNA-seq data. Here, we developed transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. TransIndel exhibits competitive or superior performance over eight state-of-the-art indel detection tools on benchmarks using both synthetic and real DNA-seq data. Additionally, we applied transIndel to DNA-seq and RNA-seq datasets from 333 primary prostate cancer patients from The Cancer Genome Atlas (TCGA) and 59 metastatic prostate cancer patients from AACR-PCF Stand-Up- To-Cancer (SU2C) studies. TransIndel enhanced the taxonomy of DNA- and RNA-level alterations in prostate cancer by identifying recurrent FOXA1 indels as well as exitron splicing in genes implicated in disease progression. Our study demonstrates that transIndel is a robust tool for elucidation of medium- and large-sized indels from DNA-seq and RNA-seq data. Including RNA-seq in indel discovery efforts leads to significant improvements in sensitivity for identification of med-sized and large indels missed by DNA-seq, and reveals non-canonical RNA-splicing events in genes associated with disease pathology.

COBRA-Seq: Sensitive and Quantitative Methylome Profiling

PubMed Central

Varinli, Hilal; Statham, Aaron L.; Clark, Susan J.; Molloy, Peter L.; Ross, Jason P.

2015-01-01

Combined Bisulfite Restriction Analysis (COBRA) quantifies DNA methylation at a specific locus. It does so via digestion of PCR amplicons produced from bisulfite-treated DNA, using a restriction enzyme that contains a cytosine within its recognition sequence, such as TaqI. Here, we introduce COBRA-seq, a genome wide reduced methylome method that requires minimal DNA input (0.1–1.0 μg) and can either use PCR or linear amplification to amplify the sequencing library. Variants of COBRA-seq can be used to explore CpG-depleted as well as CpG-rich regions in vertebrate DNA. The choice of enzyme influences enrichment for specific genomic features, such as CpG-rich promoters and CpG islands, or enrichment for less CpG dense regions such as enhancers. COBRA-seq coupled with linear amplification has the additional advantage of reduced PCR bias by producing full length fragments at high abundance. Unlike other reduced representative methylome methods, COBRA-seq has great flexibility in the choice of enzyme and can be multiplexed and tuned, to reduce sequencing costs and to interrogate different numbers of sites. Moreover, COBRA-seq is applicable to non-model organisms without the reference genome and compatible with the investigation of non-CpG methylation by using restriction enzymes containing CpA, CpT, and CpC in their recognition site. PMID:26512698

Determination of fetal DNA fraction from the plasma of pregnant women using sequence read counts.

PubMed

Kim, Sung K; Hannum, Gregory; Geis, Jennifer; Tynan, John; Hogg, Grant; Zhao, Chen; Jensen, Taylor J; Mazloom, Amin R; Oeth, Paul; Ehrich, Mathias; van den Boom, Dirk; Deciu, Cosmin

2015-08-01

This study introduces a novel method, referred to as SeqFF, for estimating the fetal DNA fraction in the plasma of pregnant women and to infer the underlying mechanism that allows for such statistical modeling. Autosomal regional read counts from whole-genome massively parallel single-end sequencing of circulating cell-free DNA (ccfDNA) from the plasma of 25 312 pregnant women were used to train a multivariate model. The pretrained model was then applied to 505 pregnant samples to assess the performance of SeqFF against known methodologies for fetal DNA fraction calculations. Pearson's correlation between chromosome Y and SeqFF for pregnancies with male fetuses from two independent cohorts ranged from 0.932 to 0.938. Comparison between a single-nucleotide polymorphism-based approach and SeqFF yielded a Pearson's correlation of 0.921. Paired-end sequencing suggests that shorter ccfDNA, that is, less than 150 bp in length, is nonuniformly distributed across the genome. Regions exhibiting an increased proportion of short ccfDNA, which are more likely of fetal origin, tend to provide more information in the SeqFF calculations. SeqFF is a robust and direct method to determine fetal DNA fraction. Furthermore, the method is applicable to both male and female pregnancies and can greatly improve the accuracy of noninvasive prenatal testing for fetal copy number variation. © 2015 John Wiley & Sons, Ltd.

TSSAR: TSS annotation regime for dRNA-seq data.

PubMed

Amman, Fabian; Wolfinger, Michael T; Lorenz, Ronny; Hofacker, Ivo L; Stadler, Peter F; Findeiß, Sven

2014-03-27

Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased. Here, we present TSSAR, a tool for automated de novo TSS annotation from dRNA-seq data that respects the statistics of dRNA-seq libraries. TSSAR uses the premise that the number of sequencing reads starting at a certain genomic position within a transcriptional active region follows a Poisson distribution with a parameter that depends on the local strength of expression. The differences of two dRNA-seq library counts thus follow a Skellam distribution. This provides a statistical basis to identify significantly enriched primary transcripts.We assessed the performance by analyzing a publicly available dRNA-seq data set using TSSAR and two simple approaches that utilize user-defined score cutoffs. We evaluated the power of reproducing the manual TSS annotation. Furthermore, the same data set was used to reproduce 74 experimentally validated TSS in H. pylori from reliable techniques such as RACE or primer extension. Both analyses showed that TSSAR outperforms the static cutoff-dependent approaches. Having an automated and efficient tool for analyzing dRNA-seq data facilitates the use of the dRNA-seq technique and promotes its application to more sophisticated analysis. For instance, monitoring the plasticity and dynamics of the transcriptomal architecture triggered by different stimuli and growth conditions becomes possible.The main asset of a novel tool for dRNA-seq analysis that reaches out to a broad user community is usability. As such, we provide TSSAR both as intuitive RESTful Web service ( http://rna.tbi.univie.ac.at/TSSAR) together with a set of post-processing and analysis tools, as well as a stand-alone version for use in high-throughput dRNA-seq data analysis pipelines.

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

PubMed Central

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

2015-01-01

Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki. PMID:26248053

Chromatin Immunoprecipitation Sequencing (ChIP-Seq) for Transcription Factors and Chromatin Factors in Arabidopsis thaliana Roots: From Material Collection to Data Analysis.

PubMed

Cortijo, Sandra; Charoensawan, Varodom; Roudier, François; Wigge, Philip A

2018-01-01

Chromatin immunoprecipitation combined with next-generation sequencing (ChIP-seq) is a powerful technique to investigate in vivo transcription factor (TF) binding to DNA, as well as chromatin marks. Here we provide a detailed protocol for all the key steps to perform ChIP-seq in Arabidopsis thaliana roots, also working on other A. thaliana tissues and in most non-ligneous plants. We detail all steps from material collection, fixation, chromatin preparation, immunoprecipitation, library preparation, and finally computational analysis based on a combination of publicly available tools.

Mapping RNA-seq Reads with STAR

PubMed Central

Dobin, Alexander; Gingeras, Thomas R.

2015-01-01

Mapping of large sets of high-throughput sequencing reads to a reference genome is one of the foundational steps in RNA-seq data analysis. The STAR software package performs this task with high levels of accuracy and speed. In addition to detecting annotated and novel splice junctions, STAR is capable of discovering more complex RNA sequence arrangements, such as chimeric and circular RNA. STAR can align spliced sequences of any length with moderate error rates providing scalability for emerging sequencing technologies. STAR generates output files that can be used for many downstream analyses such as transcript/gene expression quantification, differential gene expression, novel isoform reconstruction, signal visualization, and so forth. In this unit we describe computational protocols that produce various output files, use different RNA-seq datatypes, and utilize different mapping strategies. STAR is Open Source software that can be run on Unix, Linux or Mac OS X systems. PMID:26334920

Mapping RNA-seq Reads with STAR.

PubMed

Dobin, Alexander; Gingeras, Thomas R

2015-09-03

Mapping of large sets of high-throughput sequencing reads to a reference genome is one of the foundational steps in RNA-seq data analysis. The STAR software package performs this task with high levels of accuracy and speed. In addition to detecting annotated and novel splice junctions, STAR is capable of discovering more complex RNA sequence arrangements, such as chimeric and circular RNA. STAR can align spliced sequences of any length with moderate error rates, providing scalability for emerging sequencing technologies. STAR generates output files that can be used for many downstream analyses such as transcript/gene expression quantification, differential gene expression, novel isoform reconstruction, and signal visualization. In this unit, we describe computational protocols that produce various output files, use different RNA-seq datatypes, and utilize different mapping strategies. STAR is open source software that can be run on Unix, Linux, or Mac OS X systems. Copyright © 2015 John Wiley & Sons, Inc.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

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

PubMed Central

Li, Jun; Tibshirani, Robert

2015-01-01

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

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

PubMed

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

2015-09-03

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

GUIDE-Seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases

PubMed Central

Nguyen, Nhu T.; Liebers, Matthew; Topkar, Ved V.; Thapar, Vishal; Wyvekens, Nicolas; Khayter, Cyd; Iafrate, A. John; Le, Long P.; Aryee, Martin J.; Joung, J. Keith

2014-01-01

CRISPR RNA-guided nucleases (RGNs) are widely used genome-editing reagents, but methods to delineate their genome-wide off-target cleavage activities have been lacking. Here we describe an approach for global detection of DNA double-stranded breaks (DSBs) introduced by RGNs and potentially other nucleases. This method, called Genome-wide Unbiased Identification of DSBs Enabled by Sequencing (GUIDE-Seq), relies on capture of double-stranded oligodeoxynucleotides into breaks Application of GUIDE-Seq to thirteen RGNs in two human cell lines revealed wide variability in RGN off-target activities and unappreciated characteristics of off-target sequences. The majority of identified sites were not detected by existing computational methods or ChIP-Seq. GUIDE-Seq also identified RGN-independent genomic breakpoint ‘hotspots’. Finally, GUIDE-Seq revealed that truncated guide RNAs exhibit substantially reduced RGN-induced off-target DSBs. Our experiments define the most rigorous framework for genome-wide identification of RGN off-target effects to date and provide a method for evaluating the safety of these nucleases prior to clinical use. PMID:25513782

SEQ-REVIEW: A tool for reviewing and checking spacecraft sequences

NASA Astrophysics Data System (ADS)

Maldague, Pierre F.; El-Boushi, Mekki; Starbird, Thomas J.; Zawacki, Steven J.

1994-11-01

A key component of JPL's strategy to make space missions faster, better and cheaper is the Advanced Multi-Mission Operations System (AMMOS), a ground software intensive system currently in use and in further development. AMMOS intends to eliminate the cost of re-engineering a ground system for each new JPL mission. This paper discusses SEQ-REVIEW, a component of AMMOS that was designed to facilitate and automate the task of reviewing and checking spacecraft sequences. SEQ-REVIEW is a smart browser for inspecting files created by other sequence generation tools in the AMMOS system. It can parse sequence-related files according to a computer-readable version of a 'Software Interface Specification' (SIS), which is a standard document for defining file formats. It lets users display one or several linked files and check simple constraints using a Basic-like 'Little Language'. SEQ-REVIEW represents the first application of the Quality Function Development (QFD) method to sequence software development at JPL. The paper will show how the requirements for SEQ-REVIEW were defined and converted into a design based on object-oriented principles. The process starts with interviews of potential users, a small but diverse group that spans multiple disciplines and 'cultures'. It continues with the development of QFD matrices that related product functions and characteristics to user-demanded qualities. These matrices are then turned into a formal Software Requirements Document (SRD). The process concludes with the design phase, in which the CRC (Class, Responsibility, Collaboration) approach was used to convert requirements into a blueprint for the final product.

SEQ-REVIEW: A tool for reviewing and checking spacecraft sequences

NASA Technical Reports Server (NTRS)

Maldague, Pierre F.; El-Boushi, Mekki; Starbird, Thomas J.; Zawacki, Steven J.

1994-01-01

A key component of JPL's strategy to make space missions faster, better and cheaper is the Advanced Multi-Mission Operations System (AMMOS), a ground software intensive system currently in use and in further development. AMMOS intends to eliminate the cost of re-engineering a ground system for each new JPL mission. This paper discusses SEQ-REVIEW, a component of AMMOS that was designed to facilitate and automate the task of reviewing and checking spacecraft sequences. SEQ-REVIEW is a smart browser for inspecting files created by other sequence generation tools in the AMMOS system. It can parse sequence-related files according to a computer-readable version of a 'Software Interface Specification' (SIS), which is a standard document for defining file formats. It lets users display one or several linked files and check simple constraints using a Basic-like 'Little Language'. SEQ-REVIEW represents the first application of the Quality Function Development (QFD) method to sequence software development at JPL. The paper will show how the requirements for SEQ-REVIEW were defined and converted into a design based on object-oriented principles. The process starts with interviews of potential users, a small but diverse group that spans multiple disciplines and 'cultures'. It continues with the development of QFD matrices that related product functions and characteristics to user-demanded qualities. These matrices are then turned into a formal Software Requirements Document (SRD). The process concludes with the design phase, in which the CRC (Class, Responsibility, Collaboration) approach was used to convert requirements into a blueprint for the final product.

Whole-genome sequencing for comparative genomics and de novo genome assembly.

PubMed

Benjak, Andrej; Sala, Claudia; Hartkoorn, Ruben C

2015-01-01

Next-generation sequencing technologies for whole-genome sequencing of mycobacteria are rapidly becoming an attractive alternative to more traditional sequencing methods. In particular this technology is proving useful for genome-wide identification of mutations in mycobacteria (comparative genomics) as well as for de novo assembly of whole genomes. Next-generation sequencing however generates a vast quantity of data that can only be transformed into a usable and comprehensible form using bioinformatics. Here we describe the methodology one would use to prepare libraries for whole-genome sequencing, and the basic bioinformatics to identify mutations in a genome following Illumina HiSeq or MiSeq sequencing, as well as de novo genome assembly following sequencing using Pacific Biosciences (PacBio).

Evaluation of Multiplexed 16S rRNA Microbial Population Surveys Using Illumina MiSeq Platform (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

ScienceCinema

Tremblay, Julien

2018-01-22

Julien Tremblay from DOE JGI presents "Evaluation of Multiplexed 16S rRNA Microbial Population Surveys Using Illumina MiSeq Platorm" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Comparative RNA-Seq profiling of berry development between table grape ‘Kyoho’ and its early-ripening mutant ’Fengzao’

USDA-ARS?s Scientific Manuscript database

About 447 millions of RNA-Seq sequences were generated from 40 RNA libraries covering 8 different berry developmental stages of table grape ‘Kyoho’ and its early ripening bud mutant ‘Fengzao’. These sequences were mapped to 23,178 and 22,982 genes in the flesh and peel tissues, respectively. While m...

Evaluation of Multiplexed 16S rRNA Microbial Population Surveys Using Illumina MiSeq Platform (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

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

Tremblay, Julien

2012-06-01

Julien Tremblay from DOE JGI presents "Evaluation of Multiplexed 16S rRNA Microbial Population Surveys Using Illumina MiSeq Platorm" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Sequence information signal processor for local and global string comparisons

DOEpatents

Peterson, John C.; Chow, Edward T.; Waterman, Michael S.; Hunkapillar, Timothy J.

1997-01-01

A sequence information signal processing integrated circuit chip designed to perform high speed calculation of a dynamic programming algorithm based upon the algorithm defined by Waterman and Smith. The signal processing chip of the present invention is designed to be a building block of a linear systolic array, the performance of which can be increased by connecting additional sequence information signal processing chips to the array. The chip provides a high speed, low cost linear array processor that can locate highly similar global sequences or segments thereof such as contiguous subsequences from two different DNA or protein sequences. The chip is implemented in a preferred embodiment using CMOS VLSI technology to provide the equivalent of about 400,000 transistors or 100,000 gates. Each chip provides 16 processing elements, and is designed to provide 16 bit, two's compliment operation for maximum score precision of between -32,768 and +32,767. It is designed to provide a comparison between sequences as long as 4,194,304 elements without external software and between sequences of unlimited numbers of elements with the aid of external software. Each sequence can be assigned different deletion and insertion weight functions. Each processor is provided with a similarity measure device which is independently variable. Thus, each processor can contribute to maximum value score calculation using a different similarity measure.

RSAT 2018: regulatory sequence analysis tools 20th anniversary.

PubMed

Nguyen, Nga Thi Thuy; Contreras-Moreira, Bruno; Castro-Mondragon, Jaime A; Santana-Garcia, Walter; Ossio, Raul; Robles-Espinoza, Carla Daniela; Bahin, Mathieu; Collombet, Samuel; Vincens, Pierre; Thieffry, Denis; van Helden, Jacques; Medina-Rivera, Alejandra; Thomas-Chollier, Morgane

2018-05-02

RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

Gel-seq: A Method for Simultaneous Sequencing Library Preparation of DNA and RNA Using Hydrogel Matrices.

PubMed

Hoople, Gordon D; Richards, Andrew; Wu, Yan; Pisano, Albert P; Zhang, Kun

2018-03-26

The ability to amplify and sequence either DNA or RNA from small starting samples has only been achieved in the last five years. Unfortunately, the standard protocols for generating genomic or transcriptomic libraries are incompatible and researchers must choose whether to sequence DNA or RNA for a particular sample. Gel-seq solves this problem by enabling researchers to simultaneously prepare libraries for both DNA and RNA starting with 100 - 1000 cells using a simple hydrogel device. This paper presents a detailed approach for the fabrication of the device as well as the biological protocol to generate paired libraries. We designed Gel-seq so that it could be easily implemented by other researchers; many genetics labs already have the necessary equipment to reproduce the Gel-seq device fabrication. Our protocol employs commonly-used kits for both whole-transcript amplification (WTA) and library preparation, which are also likely to be familiar to researchers already versed in generating genomic and transcriptomic libraries. Our approach allows researchers to bring to bear the power of both DNA and RNA sequencing on a single sample without splitting and with negligible added cost.

Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data.

PubMed

Waszak, Sebastian M; Kilpinen, Helena; Gschwind, Andreas R; Orioli, Andrea; Raghav, Sunil K; Witwicki, Robert M; Migliavacca, Eugenia; Yurovsky, Alisa; Lappalainen, Tuuli; Hernandez, Nouria; Reymond, Alexandre; Dermitzakis, Emmanouil T; Deplancke, Bart

2014-01-15

High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays. The R package abs filter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter

Traditional karyotyping vs copy number variation sequencing for detection of chromosomal abnormalities associated with spontaneous miscarriage.

PubMed

Liu, S; Song, L; Cram, D S; Xiong, L; Wang, K; Wu, R; Liu, J; Deng, K; Jia, B; Zhong, M; Yang, F

2015-10-01

To compare the performance of traditional G-banding karyotyping with that of copy number variation sequencing (CNV-Seq) for detection of chromosomal abnormalities associated with miscarriage. Products of conception (POC) were collected from spontaneous miscarriages. Chromosomal abnormalities were detected using high-resolution G-banding karyotyping and CNV sequencing. Quantitative fluorescent polymerase chain reaction analysis of maternal and POC DNA for short tandem repeat (STR) markers was used to both monitor maternal cell contamination and confirm the chromosomal status and sex of the miscarriage tissue. A total of 64 samples of POC, comprising 16 with an abnormal and 48 with a normal karyotype, were selected and coded for analysis by CNV-Seq. CNV-Seq results were concordant for 14 (87.5%) of the 16 gross chromosomal abnormalities identified by karyotyping, including 11 autosomal trisomies and three sex chromosomal aneuploidies (45,X). Of the two discordant results, a 69,XXX polyploidy was missed by CNV-Seq, although supporting STR marker analysis confirmed the triploidy. In contrast, CNV-Seq identified a sample with 45,X karyotype as a 45,X/46,XY mosaic. In the remaining 48 samples of POC with a normal karyotype, CNV-Seq detected a 2.58-Mb 22q deletion associated with DiGeorge syndrome and nine different smaller CNVs of no apparent clinical significance. CNV-Seq used in parallel with STR profiling is a reliable and accurate alternative to karyotyping for identifying chromosome copy number abnormalities associated with spontaneous miscarriage. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

PubMed

Johnson, Benjamin K; Scholz, Matthew B; Teal, Tracy K; Abramovitch, Robert B

2016-02-04

Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience. To make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. SPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.

SeqSIMLA2_exact: simulate multiple disease sites in large pedigrees with given disease status for diseases with low prevalence.

PubMed

Yao, Po-Ju; Chung, Ren-Hua

2016-02-15

It is difficult for current simulation tools to simulate sequence data in a pre-specified pedigree structure and pre-specified affection status. Previously, we developed a flexible tool, SeqSIMLA2, for simulating sequence data in either unrelated case-control or family samples with different disease and quantitative trait models. Here we extended the tool to efficiently simulate sequences with multiple disease sites in large pedigrees with a given disease status for each pedigree member, assuming that the disease prevalence is low. SeqSIMLA2_exact is implemented with C++ and is available at http://seqsimla.sourceforge.net. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Whole blood transcriptional profiling comparison between different milk yield of Chinese Holstein cows using RNA-seq data.

PubMed

Bai, Xue; Zheng, Zhuqing; Liu, Bin; Ji, Xiaoyang; Bai, Yongsheng; Zhang, Wenguang

2016-08-22

The objective of this research was to investigate the variation of gene expression in the blood transcriptome profile of Chinese Holstein cows associated to the milk yield traits. We used RNA-seq to generate the bovine transcriptome from the blood of 23 lactating Chinese Holstein cows with extremely high and low milk yield. A total of 100 differentially expressed genes (DEGs) (p < 0.05, FDR < 0.05) were revealed between the high and low groups. Gene ontology (GO) analysis demonstrated that the 100 DEGs were enriched in specific biological processes with regard to defense response, immune response, inflammatory response, icosanoid metabolic process, and fatty acid metabolic process (p < 0.05). The KEGG pathway analysis with 100 DEGs revealed that the most statistically-significant metabolic pathway was related with Toll-like receptor signaling pathway (p < 0.05). The expression level of four selected DEGs was analyzed by qRT-PCR, and the results indicated that the expression patterns were consistent with the deep sequencing results by RNA-Seq. Furthermore, alternative splicing analysis of 100 DEGs demonstrated that there were different splicing pattern between high and low yielders. The alternative 3' splicing site was the major splicing pattern detected in high yielders. However, in low yielders the major type was exon skipping. This study provides a non-invasive method to identify the DEGs in cattle blood using RNA-seq for milk yield. The revealed 100 DEGs between Holstein cows with extremely high and low milk yield, and immunological pathway are likely involved in milk yield trait. Finally, this study allowed us to explore associations between immune traits and production traits related to milk production.

Integrating restriction site-associated DNA sequencing (RAD-seq) with morphological cladistic analysis clarifies evolutionary relationships among major species groups of bee orchids

PubMed Central

Sramkó, Gábor; Paun, Ovidiu

2018-01-01

Abstract Background and Aims Bee orchids (Ophrys) have become the most popular model system for studying reproduction via insect-mediated pseudo-copulation and for exploring the consequent, putatively adaptive, evolutionary radiations. However, despite intensive past research, both the phylogenetic structure and species diversity within the genus remain highly contentious. Here, we integrate next-generation sequencing and morphological cladistic techniques to clarify the phylogeny of the genus. Methods At least two accessions of each of the ten species groups previously circumscribed from large-scale cloned nuclear ribosomal internal transcibed spacer (nrITS) sequencing were subjected to restriction site-associated sequencing (RAD-seq). The resulting matrix of 4159 single nucleotide polymorphisms (SNPs) for 34 accessions was used to construct an unrooted network and a rooted maximum likelihood phylogeny. A parallel morphological cladistic matrix of 43 characters generated both polymorphic and non-polymorphic sets of parsimony trees before being mapped across the RAD-seq topology. Key Results RAD-seq data strongly support the monophyly of nine out of ten groups previously circumscribed using nrITS and resolve three major clades; in contrast, supposed microspecies are barely distinguishable. Strong incongruence separated the RAD-seq trees from both the morphological trees and traditional classifications; mapping of the morphological characters across the RAD-seq topology rendered them far more homoplastic. Conclusions The comparatively high level of morphological homoplasy reflects extensive convergence, whereas the derived placement of the fusca group is attributed to paedomorphic simplification. The phenotype of the most recent common ancestor of the extant lineages is inferred, but it post-dates the majority of the character-state changes that typify the genus. RAD-seq may represent the high-water mark of the contribution of molecular phylogenetics to understanding evolution within Ophrys; further progress will require large-scale population-level studies that integrate phenotypic and genotypic data in a cogent conceptual framework. PMID:29325077

Integrating restriction site-associated DNA sequencing (RAD-seq) with morphological cladistic analysis clarifies evolutionary relationships among major species groups of bee orchids.

PubMed

Bateman, Richard M; Sramkó, Gábor; Paun, Ovidiu

2018-01-25

Bee orchids (Ophrys) have become the most popular model system for studying reproduction via insect-mediated pseudo-copulation and for exploring the consequent, putatively adaptive, evolutionary radiations. However, despite intensive past research, both the phylogenetic structure and species diversity within the genus remain highly contentious. Here, we integrate next-generation sequencing and morphological cladistic techniques to clarify the phylogeny of the genus. At least two accessions of each of the ten species groups previously circumscribed from large-scale cloned nuclear ribosomal internal transcibed spacer (nrITS) sequencing were subjected to restriction site-associated sequencing (RAD-seq). The resulting matrix of 4159 single nucleotide polymorphisms (SNPs) for 34 accessions was used to construct an unrooted network and a rooted maximum likelihood phylogeny. A parallel morphological cladistic matrix of 43 characters generated both polymorphic and non-polymorphic sets of parsimony trees before being mapped across the RAD-seq topology. RAD-seq data strongly support the monophyly of nine out of ten groups previously circumscribed using nrITS and resolve three major clades; in contrast, supposed microspecies are barely distinguishable. Strong incongruence separated the RAD-seq trees from both the morphological trees and traditional classifications; mapping of the morphological characters across the RAD-seq topology rendered them far more homoplastic. The comparatively high level of morphological homoplasy reflects extensive convergence, whereas the derived placement of the fusca group is attributed to paedomorphic simplification. The phenotype of the most recent common ancestor of the extant lineages is inferred, but it post-dates the majority of the character-state changes that typify the genus. RAD-seq may represent the high-water mark of the contribution of molecular phylogenetics to understanding evolution within Ophrys; further progress will require large-scale population-level studies that integrate phenotypic and genotypic data in a cogent conceptual framework. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company.

Low-coverage MiSeq next generation sequencing reveals the mitochondrial genome of the Eastern Rock Lobster, Sagmariasus verreauxi.

PubMed

Doyle, Stephen R; Griffith, Ian S; Murphy, Nick P; Strugnell, Jan M

2015-01-01

The complete mitochondrial genome of the Eastern Rock lobster, Sagmariasus verreauxi, is reported for the first time. Using low-coverage, long read MiSeq next generation sequencing, we constructed and determined the mtDNA genome organization of the 15,470 bp sequence from two isolates from Eastern Tasmania, Australia and Northern New Zealand, and identified 46 polymorphic nucleotides between the two sequences. This genome sequence and its genetic polymorphisms will likely be useful in understanding the distribution and population connectivity of the Eastern Rock Lobster, and in the fisheries management of this commercially important species.

SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean

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

Song, Qijian; Jia, Gaofeng; Hyten, David L.

A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of largemore » scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.« less

SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean

DOE PAGES

Song, Qijian; Jia, Gaofeng; Hyten, David L.; ...

2015-08-28

A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of largemore » scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.« less

SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean.

PubMed

Song, Qijian; Jia, Gaofeng; Hyten, David L; Jenkins, Jerry; Hwang, Eun-Young; Schroeder, Steven G; Osorno, Juan M; Schmutz, Jeremy; Jackson, Scott A; McClean, Phillip E; Cregan, Perry B

2015-08-28

A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of large scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad. Copyright © 2015 Song et al.

RNA-seq Data: Challenges in and Recommendations for Experimental Design and Analysis.

PubMed

Williams, Alexander G; Thomas, Sean; Wyman, Stacia K; Holloway, Alisha K

2014-10-01

RNA-seq is widely used to determine differential expression of genes or transcripts as well as identify novel transcripts, identify allele-specific expression, and precisely measure translation of transcripts. Thoughtful experimental design and choice of analysis tools are critical to ensure high-quality data and interpretable results. Important considerations for experimental design include number of replicates, whether to collect paired-end or single-end reads, sequence length, and sequencing depth. Common analysis steps in all RNA-seq experiments include quality control, read alignment, assigning reads to genes or transcripts, and estimating gene or transcript abundance. Our aims are two-fold: to make recommendations for common components of experimental design and assess tool capabilities for each of these steps. We also test tools designed to detect differential expression, since this is the most widespread application of RNA-seq. We hope that these analyses will help guide those who are new to RNA-seq and will generate discussion about remaining needs for tool improvement and development. Copyright © 2014 John Wiley & Sons, Inc.

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons

PubMed Central

Krishnaswami, Suguna Rani; Grindberg, Rashel V; Novotny, Mark; Venepally, Pratap; Lacar, Benjamin; Bhutani, Kunal; Linker, Sara B; Pham, Son; Erwin, Jennifer A; Miller, Jeremy A; Hodge, Rebecca; McCarthy, James K; Kelder, Martin; McCorrison, Jamison; Aevermann, Brian D; Fuertes, Francisco Diez; Scheuermann, Richard H; Lee, Jun; Lein, Ed S; Schork, Nicholas; McConnell, Michael J; Gage, Fred H; Lasken, Roger S

2016-01-01

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing. PMID:26890679

An interactive environment for agile analysis and visualization of ChIP-sequencing data.

PubMed

Lerdrup, Mads; Johansen, Jens Vilstrup; Agrawal-Singh, Shuchi; Hansen, Klaus

2016-04-01

To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

TopHat: discovering splice junctions with RNA-Seq

PubMed Central

Trapnell, Cole; Pachter, Lior; Salzberg, Steven L.

2009-01-01

Motivation: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites. Results: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20 000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development. Availability: TopHat is free, open-source software available from http://tophat.cbcb.umd.edu Contact: cole@cs.umd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19289445

A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA.

PubMed

Aberg, Karolina A; Chan, Robin F; Shabalin, Andrey A; Zhao, Min; Turecki, Gustavo; Staunstrup, Nicklas Heine; Starnawska, Anna; Mors, Ole; Xie, Lin Y; van den Oord, Edwin Jcg

2017-09-01

We recently showed that, after optimization, our methyl-CpG binding domain sequencing (MBD-seq) application approximates the methylome-wide coverage obtained with whole-genome bisulfite sequencing (WGB-seq), but at a cost that enables adequately powered large-scale association studies. A prior drawback of MBD-seq is the relatively large amount of genomic DNA (ideally >1 µg) required to obtain high-quality data. Biomaterials are typically expensive to collect, provide a finite amount of DNA, and may simply not yield sufficient starting material. The ability to use low amounts of DNA will increase the breadth and number of studies that can be conducted. Therefore, we further optimized the enrichment step. With this low starting material protocol, MBD-seq performed equally well, or better, than the protocol requiring ample starting material (>1 µg). Using only 15 ng of DNA as input, there is minimal loss in data quality, achieving 93% of the coverage of WGB-seq (with standard amounts of input DNA) at similar false/positive rates. Furthermore, across a large number of genomic features, the MBD-seq methylation profiles closely tracked those observed for WGB-seq with even slightly larger effect sizes. This suggests that MBD-seq provides similar information about the methylome and classifies methylation status somewhat more accurately. Performance decreases with <15 ng DNA as starting material but, even with as little as 5 ng, MBD-seq still achieves 90% of the coverage of WGB-seq with comparable genome-wide methylation profiles. Thus, the proposed protocol is an attractive option for adequately powered and cost-effective methylome-wide investigations using (very) low amounts of DNA.

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data.

PubMed

Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie; Zhang, Gong

2018-01-04

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs.

PubMed

Parekh, Swati; Ziegenhain, Christoph; Vieth, Beate; Enard, Wolfgang; Hellmann, Ines

2018-06-01

Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution. zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data.

Nitrogen Cycle Evaluation (NiCE) Chip for the Simultaneous Analysis of Multiple N-Cycle Associated Genes.

PubMed

Oshiki, Mamoru; Segawa, Takahiro; Ishii, Satoshi

2018-02-02

Various microorganisms play key roles in the Nitrogen (N) cycle. Quantitative PCR (qPCR) and PCR-amplicon sequencing of the N cycle functional genes allow us to analyze the abundance and diversity of microbes responsible in the N transforming reactions in various environmental samples. However, analysis of multiple target genes can be cumbersome and expensive. PCR-independent analysis, such as metagenomics and metatranscriptomics, is useful but expensive especially when we analyze multiple samples and try to detect N cycle functional genes present at relatively low abundance. Here, we present the application of microfluidic qPCR chip technology to simultaneously quantify and prepare amplicon sequence libraries for multiple N cycle functional genes as well as taxon-specific 16S rRNA gene markers for many samples. This approach, named as N cycle evaluation (NiCE) chip, was evaluated by using DNA from pure and artificially mixed bacterial cultures and by comparing the results with those obtained by conventional qPCR and amplicon sequencing methods. Quantitative results obtained by the NiCE chip were comparable to those obtained by conventional qPCR. In addition, the NiCE chip was successfully applied to examine abundance and diversity of N cycle functional genes in wastewater samples. Although non-specific amplification was detected on the NiCE chip, this could be overcome by optimizing the primer sequences in the future. As the NiCE chip can provide high-throughput format to quantify and prepare sequence libraries for multiple N cycle functional genes, this tool should advance our ability to explore N cycling in various samples. Importance. We report a novel approach, namely Nitrogen Cycle Evaluation (NiCE) chip by using microfluidic qPCR chip technology. By sequencing the amplicons recovered from the NiCE chip, we can assess diversities of the N cycle functional genes. The NiCE chip technology is applicable to analyze the temporal dynamics of the N cycle gene transcriptions in wastewater treatment bioreactors. The NiCE chip can provide high-throughput format to quantify and prepare sequence libraries for multiple N cycle functional genes. While there is a room for future improvement, this tool should significantly advance our ability to explore the N cycle in various environmental samples. Copyright © 2018 American Society for Microbiology.

Adapt or Die on the Highway To Hell: Metagenomic Insights into Altered Genomes of Firmicutes from the Deep Biosphere

NASA Astrophysics Data System (ADS)

Briggs, B. R.; Colwell, F. S.

2014-12-01

The ability of a microbe to persist in low-nutrient environments requires adaptive mechanisms to survive. These microorganisms must reduce metabolic energy and increase catabolic efficiency. For example, Escherichia coli surviving in low-nutrient extended stationary phase have mutations that confer a growth advantage in stationary phase (GASP) phenotype, thus allowing for persistence for years in low-nutrient environments. Based on the fact that subseafloor environments are characterized by energy flux decrease with time of burial we hypothesize that cells from older (deeper) sediment layers will have more altered genomes compared to sequenced surface relatives and that these differences reflect adaptations to a low-energy flux environment. To test this hypothesis, sediment samples were collected from the Andaman Sea from the depths of 21, 40 and 554 meters below seafloor, with the ages of 0.34, 0.66, and 8.76 million years, respectively. A single operational taxonomic unit within Firmicutes, based on full-length 16S rDNA, dominated these low diversity samples. This unique feature allowed for metagenomic sequencing using the Illumina HiSeq to identify nucleotide variations (NV) between the subsurface Firmicutes and the closest sequenced representative, Bacillus subtilis BEST7613. NVs were present at all depths in genes that code for proteins used in energy-dependent proteolysis, cell division, sporulation, and (similar to the GASP mutants) biosynthetic pathways for amino acids, nucleotides, and fatty acids. Conserved genes such as 16S rDNA did not contain NVs. More NVs were found in genes from deeper depths. These NV may be beneficial or harmful allowing them to survive for millions of years in the deep biosphere or may be latent deleterious gene alterations that are masked by the minimal-growth status of these deep microbes. Either way these results show that microbes present in the deep biosphere experience environmental forcing that alters the genome.

Missing data and technical variability in single-cell RNA-sequencing experiments.

PubMed

Hicks, Stephanie C; Townes, F William; Teng, Mingxiang; Irizarry, Rafael A

2017-11-06

Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands of cells to produce reliable measurements. Recent technical advances permit genome-wide gene expression measurement at the single-cell level. Single-cell RNA-Seq (scRNA-seq) is the most widely used and numerous publications are based on data produced with this technology. However, RNA-seq and scRNA-seq data are markedly different. In particular, unlike RNA-seq, the majority of reported expression levels in scRNA-seq are zeros, which could be either biologically-driven, genes not expressing RNA at the time of measurement, or technically-driven, genes expressing RNA, but not at a sufficient level to be detected by sequencing technology. Another difference is that the proportion of genes reporting the expression level to be zero varies substantially across single cells compared to RNA-seq samples. However, it remains unclear to what extent this cell-to-cell variation is being driven by technical rather than biological variation. Furthermore, while systematic errors, including batch effects, have been widely reported as a major challenge in high-throughput technologies, these issues have received minimal attention in published studies based on scRNA-seq technology. Here, we use an assessment experiment to examine data from published studies and demonstrate that systematic errors can explain a substantial percentage of observed cell-to-cell expression variability. Specifically, we present evidence that some of these reported zeros are driven by technical variation by demonstrating that scRNA-seq produces more zeros than expected and that this bias is greater for lower expressed genes. In addition, this missing data problem is exacerbated by the fact that this technical variation varies cell-to-cell. Then, we show how this technical cell-to-cell variability can be confused with novel biological results. Finally, we demonstrate and discuss how batch-effects and confounded experiments can intensify the problem. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

PubMed Central

Honda, Shozo; Morichika, Keisuke; Kirino, Yohei

2016-01-01

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

SparkSeq: fast, scalable and cloud-ready tool for the interactive genomic data analysis with nucleotide precision.

PubMed

Wiewiórka, Marek S; Messina, Antonio; Pacholewska, Alicja; Maffioletti, Sergio; Gawrysiak, Piotr; Okoniewski, Michał J

2014-09-15

Many time-consuming analyses of next -: generation sequencing data can be addressed with modern cloud computing. The Apache Hadoop-based solutions have become popular in genomics BECAUSE OF: their scalability in a cloud infrastructure. So far, most of these tools have been used for batch data processing rather than interactive data querying. The SparkSeq software has been created to take advantage of a new MapReduce framework, Apache Spark, for next-generation sequencing data. SparkSeq is a general-purpose, flexible and easily extendable library for genomic cloud computing. It can be used to build genomic analysis pipelines in Scala and run them in an interactive way. SparkSeq opens up the possibility of customized ad hoc secondary analyses and iterative machine learning algorithms. This article demonstrates its scalability and overall fast performance by running the analyses of sequencing datasets. Tests of SparkSeq also prove that the use of cache and HDFS block size can be tuned for the optimal performance on multiple worker nodes. Available under open source Apache 2.0 license: https://bitbucket.org/mwiewiorka/sparkseq/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed Central

Buschmann, Dominik; Haberberger, Anna; Kirchner, Benedikt; Spornraft, Melanie; Riedmaier, Irmgard; Schelling, Gustav; Pfaffl, Michael W.

2016-01-01

Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will encourage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions. PMID:27317696

A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes.

PubMed

Bazak, Lily; Haviv, Ami; Barak, Michal; Jacob-Hirsch, Jasmine; Deng, Patricia; Zhang, Rui; Isaacs, Farren J; Rechavi, Gideon; Li, Jin Billy; Eisenberg, Eli; Levanon, Erez Y

2014-03-01

RNA molecules transmit the information encoded in the genome and generally reflect its content. Adenosine-to-inosine (A-to-I) RNA editing by ADAR proteins converts a genomically encoded adenosine into inosine. It is known that most RNA editing in human takes place in the primate-specific Alu sequences, but the extent of this phenomenon and its effect on transcriptome diversity are not yet clear. Here, we analyzed large-scale RNA-seq data and detected ∼1.6 million editing sites. As detection sensitivity increases with sequencing coverage, we performed ultradeep sequencing of selected Alu sequences and showed that the scope of editing is much larger than anticipated. We found that virtually all adenosines within Alu repeats that form double-stranded RNA undergo A-to-I editing, although most sites exhibit editing at only low levels (<1%). Moreover, using high coverage sequencing, we observed editing of transcripts resulting from residual antisense expression, doubling the number of edited sites in the human genome. Based on bioinformatic analyses and deep targeted sequencing, we estimate that there are over 100 million human Alu RNA editing sites, located in the majority of human genes. These findings set the stage for exploring how this primate-specific massive diversification of the transcriptome is utilized.

A normalization strategy for comparing tag count data

PubMed Central

2012-01-01

Background High-throughput sequencing, such as ribonucleic acid sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) analyses, enables various features of organisms to be compared through tag counts. Recent studies have demonstrated that the normalization step for RNA-seq data is critical for a more accurate subsequent analysis of differential gene expression. Development of a more robust normalization method is desirable for identifying the true difference in tag count data. Results We describe a strategy for normalizing tag count data, focusing on RNA-seq. The key concept is to remove data assigned as potential differentially expressed genes (DEGs) before calculating the normalization factor. Several R packages for identifying DEGs are currently available, and each package uses its own normalization method and gene ranking algorithm. We compared a total of eight package combinations: four R packages (edgeR, DESeq, baySeq, and NBPSeq) with their default normalization settings and with our normalization strategy. Many synthetic datasets under various scenarios were evaluated on the basis of the area under the curve (AUC) as a measure for both sensitivity and specificity. We found that packages using our strategy in the data normalization step overall performed well. This result was also observed for a real experimental dataset. Conclusion Our results showed that the elimination of potential DEGs is essential for more accurate normalization of RNA-seq data. The concept of this normalization strategy can widely be applied to other types of tag count data and to microarray data. PMID:22475125

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.

PubMed

Tourlousse, Dieter M; Yoshiike, Satowa; Ohashi, Akiko; Matsukura, Satoko; Noda, Naohiro; Sekiguchi, Yuji

2017-02-28

High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible identity to known nucleotide sequences, permitting unambiguous identification of spike-in sequences in 16S-seq read data from any microbiome sample. Using defined mock communities and environmental microbiota, we characterized the performance of the spike-in standards and demonstrated their utility for evaluating data quality on a per-sample basis. Further, we showed that staggered spike-in mixtures added at the point of DNA extraction enable concurrent estimation of absolute microbial abundances suitable for comparative analysis. Results also underscored that template-specific Illumina sequencing artifacts may lead to biases in the perceived abundance of certain taxa. Taken together, the spike-in standards represent a novel bioanalytical tool that can substantially improve 16S-seq-based microbiome studies by enabling comprehensive quality control along with absolute quantification. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome-wide mapping of DNase I hypersensitive sites in rare cell populations using single-cell DNase sequencing.

PubMed

Cooper, James; Ding, Yi; Song, Jiuzhou; Zhao, Keji

2017-11-01

Increased chromatin accessibility is a feature of cell-type-specific cis-regulatory elements; therefore, mapping of DNase I hypersensitive sites (DHSs) enables the detection of active regulatory elements of transcription, including promoters, enhancers, insulators and locus-control regions. Single-cell DNase sequencing (scDNase-seq) is a method of detecting genome-wide DHSs when starting with either single cells or <1,000 cells from primary cell sources. This technique enables genome-wide mapping of hypersensitive sites in a wide range of cell populations that cannot be analyzed using conventional DNase I sequencing because of the requirement for millions of starting cells. Fresh cells, formaldehyde-cross-linked cells or cells recovered from formalin-fixed paraffin-embedded (FFPE) tissue slides are suitable for scDNase-seq assays. To generate scDNase-seq libraries, cells are lysed and then digested with DNase I. Circular carrier plasmid DNA is included during subsequent DNA purification and library preparation steps to prevent loss of the small quantity of DHS DNA. Libraries are generated for high-throughput sequencing on the Illumina platform using standard methods. Preparation of scDNase-seq libraries requires only 2 d. The materials and molecular biology techniques described in this protocol should be accessible to any general molecular biology laboratory. Processing of high-throughput sequencing data requires basic bioinformatics skills and uses publicly available bioinformatics software.

Pervasive, Genome-Wide Transcription in the Organelle Genomes of Diverse Plastid-Bearing Protists.

PubMed

Sanitá Lima, Matheus; Smith, David Roy

2017-11-06

Organelle genomes are among the most sequenced kinds of chromosome. This is largely because they are small and widely used in molecular studies, but also because next-generation sequencing technologies made sequencing easier, faster, and cheaper. However, studies of organelle RNA have not kept pace with those of DNA, despite huge amounts of freely available eukaryotic RNA-sequencing (RNA-seq) data. Little is known about organelle transcription in nonmodel species, and most of the available eukaryotic RNA-seq data have not been mined for organelle transcripts. Here, we use publicly available RNA-seq experiments to investigate organelle transcription in 30 diverse plastid-bearing protists with varying organelle genomic architectures. Mapping RNA-seq data to organelle genomes revealed pervasive, genome-wide transcription, regardless of the taxonomic grouping, gene organization, or noncoding content. For every species analyzed, transcripts covered ≥85% of the mitochondrial and/or plastid genomes (all of which were ≤105 kb), indicating that most of the organelle DNA-coding and noncoding-is transcriptionally active. These results follow earlier studies of model species showing that organellar transcription is coupled and ubiquitous across the genome, requiring significant downstream processing of polycistronic transcripts. Our findings suggest that noncoding organelle DNA can be transcriptionally active, raising questions about the underlying function of these transcripts and underscoring the utility of publicly available RNA-seq data for recovering complete genome sequences. If pervasive transcription is also found in bigger organelle genomes (>105 kb) and across a broader range of eukaryotes, this could indicate that noncoding organelle RNAs are regulating fundamental processes within eukaryotic cells. Copyright © 2017 Sanitá Lima and Smith.

ALEA: a toolbox for allele-specific epigenomics analysis.

PubMed

Younesy, Hamid; Möller, Torsten; Heravi-Moussavi, Alireza; Cheng, Jeffrey B; Costello, Joseph F; Lorincz, Matthew C; Karimi, Mohammad M; Jones, Steven J M

2014-04-15

The assessment of expression and epigenomic status using sequencing based methods provides an unprecedented opportunity to identify and correlate allelic differences with epigenomic status. We present ALEA, a computational toolbox for allele-specific epigenomics analysis, which incorporates allelic variation data within existing resources, allowing for the identification of significant associations between epigenetic modifications and specific allelic variants in human and mouse cells. ALEA provides a customizable pipeline of command line tools for allele-specific analysis of next-generation sequencing data (ChIP-seq, RNA-seq, etc.) that takes the raw sequencing data and produces separate allelic tracks ready to be viewed on genome browsers. The pipeline has been validated using human and hybrid mouse ChIP-seq and RNA-seq data. The package, test data and usage instructions are available online at http://www.bcgsc.ca/platform/bioinfo/software/alea CONTACT: : mkarimi1@interchange.ubc.ca or sjones@bcgsc.ca Supplementary information: Supplementary data are available at Bioinformatics online. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integrating RNA sequencing into neuro-oncology practice.

PubMed

Rogawski, David S; Vitanza, Nicholas A; Gauthier, Angela C; Ramaswamy, Vijay; Koschmann, Carl

2017-11-01

Malignant tumors of the central nervous system (CNS) cause substantial morbidity and mortality, yet efforts to optimize chemo- and radiotherapy have largely failed to improve dismal prognoses. Over the past decade, RNA sequencing (RNA-seq) has emerged as a powerful tool to comprehensively characterize the transcriptome of CNS tumor cells in one high-throughput step, leading to improved understanding of CNS tumor biology and suggesting new routes for targeted therapies. RNA-seq has been instrumental in improving the diagnostic classification of brain tumors, characterizing oncogenic fusion genes, and shedding light on intratumor heterogeneity. Currently, RNA-seq is beginning to be incorporated into regular neuro-oncology practice in the form of precision neuro-oncology programs, which use information from tumor sequencing to guide implementation of personalized targeted therapies. These programs show great promise in improving patient outcomes for tumors where single agent trials have been ineffective. As RNA-seq is a relatively new technique, many further applications yielding new advances in CNS tumor research and management are expected in the coming years. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

Han, Kook; Tjaden, Brian; Lory, Stephen

2016-12-22

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

Cost analysis of whole genome sequencing in German clinical practice.

PubMed

Plöthner, Marika; Frank, Martin; von der Schulenburg, J-Matthias Graf

2017-06-01

Whole genome sequencing (WGS) is an emerging tool in clinical diagnostics. However, little has been said about its procedure costs, owing to a dearth of related cost studies. This study helps fill this research gap by analyzing the execution costs of WGS within the setting of German clinical practice. First, to estimate costs, a sequencing process related to clinical practice was undertaken. Once relevant resources were identified, a quantification and monetary evaluation was conducted using data and information from expert interviews with clinical geneticists, and personnel at private enterprises and hospitals. This study focuses on identifying the costs associated with the standard sequencing process, and the procedure costs for a single WGS were analyzed on the basis of two sequencing platforms-namely, HiSeq 2500 and HiSeq Xten, both by Illumina, Inc. In addition, sensitivity analyses were performed to assess the influence of various uses of sequencing platforms and various coverage values on a fixed-cost degression. In the base case scenario-which features 80 % utilization and 30-times coverage-the cost of a single WGS analysis with the HiSeq 2500 was estimated at €3858.06. The cost of sequencing materials was estimated at €2848.08; related personnel costs of €396.94 and acquisition/maintenance costs (€607.39) were also found. In comparison, the cost of sequencing that uses the latest technology (i.e., HiSeq Xten) was approximately 63 % cheaper, at €1411.20. The estimated costs of WGS currently exceed the prediction of a 'US$1000 per genome', by more than a factor of 3.8. In particular, the material costs in themselves exceed this predicted cost.

Assessment of the cPAS-based BGISEQ-500 platform for metagenomic sequencing.

PubMed

Fang, Chao; Zhong, Huanzi; Lin, Yuxiang; Chen, Bing; Han, Mo; Ren, Huahui; Lu, Haorong; Luber, Jacob M; Xia, Min; Li, Wangsheng; Stein, Shayna; Xu, Xun; Zhang, Wenwei; Drmanac, Radoje; Wang, Jian; Yang, Huanming; Hammarström, Lennart; Kostic, Aleksandar D; Kristiansen, Karsten; Li, Junhua

2018-03-01

More extensive use of metagenomic shotgun sequencing in microbiome research relies on the development of high-throughput, cost-effective sequencing. Here we present a comprehensive evaluation of the performance of the new high-throughput sequencing platform BGISEQ-500 for metagenomic shotgun sequencing and compare its performance with that of 2 Illumina platforms. Using fecal samples from 20 healthy individuals, we evaluated the intra-platform reproducibility for metagenomic sequencing on the BGISEQ-500 platform in a setup comprising 8 library replicates and 8 sequencing replicates. Cross-platform consistency was evaluated by comparing 20 pairwise replicates on the BGISEQ-500 platform vs the Illumina HiSeq 2000 platform and the Illumina HiSeq 4000 platform. In addition, we compared the performance of the 2 Illumina platforms against each other. By a newly developed overall accuracy quality control method, an average of 82.45 million high-quality reads (96.06% of raw reads) per sample, with 90.56% of bases scoring Q30 and above, was obtained using the BGISEQ-500 platform. Quantitative analyses revealed extremely high reproducibility between BGISEQ-500 intra-platform replicates. Cross-platform replicates differed slightly more than intra-platform replicates, yet a high consistency was observed. Only a low percentage (2.02%-3.25%) of genes exhibited significant differences in relative abundance comparing the BGISEQ-500 and HiSeq platforms, with a bias toward genes with higher GC content being enriched on the HiSeq platforms. Our study provides the first set of performance metrics for human gut metagenomic sequencing data using BGISEQ-500. The high accuracy and technical reproducibility confirm the applicability of the new platform for metagenomic studies, though caution is still warranted when combining metagenomic data from different platforms.

Deep sequencing of the Trypanosoma cruzi GP63 surface proteases reveals diversity and diversifying selection among chronic and congenital Chagas disease patients.

PubMed

Llewellyn, Martin S; Messenger, Louisa A; Luquetti, Alejandro O; Garcia, Lineth; Torrico, Faustino; Tavares, Suelene B N; Cheaib, Bachar; Derome, Nicolas; Delepine, Marc; Baulard, Céline; Deleuze, Jean-Francois; Sauer, Sascha; Miles, Michael A

2015-04-01

Chagas disease results from infection with the diploid protozoan parasite Trypanosoma cruzi. T. cruzi is highly genetically diverse, and multiclonal infections in individual hosts are common, but little studied. In this study, we explore T. cruzi infection multiclonality in the context of age, sex and clinical profile among a cohort of chronic patients, as well as paired congenital cases from Cochabamba, Bolivia and Goias, Brazil using amplicon deep sequencing technology. A 450bp fragment of the trypomastigote TcGP63I surface protease gene was amplified and sequenced across 70 chronic and 22 congenital cases on the Illumina MiSeq platform. In addition, a second, mitochondrial target--ND5--was sequenced across the same cohort of cases. Several million reads were generated, and sequencing read depths were normalized within patient cohorts (Goias chronic, n = 43, Goias congenital n = 2, Bolivia chronic, n = 27; Bolivia congenital, n = 20), Among chronic cases, analyses of variance indicated no clear correlation between intra-host sequence diversity and age, sex or symptoms, while principal coordinate analyses showed no clustering by symptoms between patients. Between congenital pairs, we found evidence for the transmission of multiple sequence types from mother to infant, as well as widespread instances of novel genotypes in infants. Finally, non-synonymous to synonymous (dn:ds) nucleotide substitution ratios among sequences of TcGP63Ia and TcGP63Ib subfamilies within each cohort provided powerful evidence of strong diversifying selection at this locus. Our results shed light on the diversity of parasite DTUs within each patient, as well as the extent to which parasite strains pass between mother and foetus in congenital cases. Although we were unable to find any evidence that parasite diversity accumulates with age in our study cohorts, putative diversifying selection within members of the TcGP63I gene family suggests a link between genetic diversity within this gene family and survival in the mammalian host.

Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

PubMed

Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

2016-08-11

Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

PubMed Central

Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

2016-01-01

Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

Dominance of Epsilonproteobacteria associated with a whale fall at a 4204 m depth - South Atlantic Ocean

NASA Astrophysics Data System (ADS)

Cavalett, Angélica; Silva, Marcus Adonai Castro da; Toyofuku, Takashi; Mendes, Rodrigo; Taketani, Rodrigo Gouvêa; Pedrini, Jéssica; Freitas, Robert Cardoso de; Sumida, Paulo Yukio Gomes; Yamanaka, Toshiro; Nagano, Yuriko; Pellizari, Vivian Helena; Perez, José Angel Alvarez; Kitazato, Hiroshi; Lima, André Oliveira de Souza

2017-12-01

The deep ocean is the largest marine environment on Earth and is home to a large reservoir of biodiversity. Within the deep ocean, large organic falls attract a suite of metazoans and microorganisms, which form an important community that, in part, relies on reduced chemical compounds. Here, we describe a deep-sea (4204 m) microbial community associated with sediments collected underneath a whale fall skeleton in the South Atlantic Ocean. Metagenomic analysis of 1 Gb of Illumina HiSeq. 2000 reads, including taxonomic and functional genes, was performed by using the MG-RAST pipeline, SEED, COG and the KEGG database. The results showed that Proteobacteria (79%) was the main phylum represented. The most dominant bacterial class in this phylum was Epsilonproteobacteria (69%), and Sulfurovum sp. NBC37-1 (97%) was the dominant species. Different species of Epsilonproteobacteria have been described in marine and terrestrial environments as important organisms for nutrient cycling. Functional analysis revealed key genes for nitrogen and sulfur cycles, including protein sequences for Sox system (sulfur oxidation) enzymes. These enzymes were mainly those of the Epsilonproteobacteria, indicating their importance for nitrogen and sulfur cycles and the balance of nutrients in this environment.

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

PubMed

Myschyshyn, Mike; Farren-Dai, Marco; Chuang, Tien-Jui; Vocadlo, David

2017-11-25

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically relevant data analysis, and the uncovering of variations in the time-dependent behavior of chromatin. TDCA automates the analysis of TC ChIP-seq experiments, permitting researchers to easily obtain raw and modeled data for specific loci or groups of loci with similar behavior while also enhancing consistency of data analysis of TC data within the genomics field.

Combining multiple ChIP-seq peak detection systems using combinatorial fusion.

PubMed

Schweikert, Christina; Brown, Stuart; Tang, Zuojian; Smith, Phillip R; Hsu, D Frank

2012-01-01

Due to the recent rapid development in ChIP-seq technologies, which uses high-throughput next-generation DNA sequencing to identify the targets of Chromatin Immunoprecipitation, there is an increasing amount of sequencing data being generated that provides us with greater opportunity to analyze genome-wide protein-DNA interactions. In particular, we are interested in evaluating and enhancing computational and statistical techniques for locating protein binding sites. Many peak detection systems have been developed; in this study, we utilize the following six: CisGenome, MACS, PeakSeq, QuEST, SISSRs, and TRLocator. We define two methods to merge and rescore the regions of two peak detection systems and analyze the performance based on average precision and coverage of transcription start sites. The results indicate that ChIP-seq peak detection can be improved by fusion using score or rank combination. Our method of combination and fusion analysis would provide a means for generic assessment of available technologies and systems and assist researchers in choosing an appropriate system (or fusion method) for analyzing ChIP-seq data. This analysis offers an alternate approach for increasing true positive rates, while decreasing false positive rates and hence improving the ChIP-seq peak identification process.

Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T Cell Receptors in High-risk MYCN-not-amplified Human Neuroblastoma.

PubMed

Wei, Jun S; Kuznetsov, Igor B; Zhang, Shile; Song, Young K; Asgharzadeh, Shahab; Sindiri, Sivasish; Wen, Xinyu; Patidar, Rajesh; Nagaraj, Sushma; Walton, Ashley; Guidry Auvil, Jaime M; Gerhard, Daniela S; Yuksel, Aysen; Catchpoole, Daniel R; Hewitt, Stephen M; Sondel, Paul M; Seeger, Robert C; Maris, John M; Khan, Javed

2018-05-21

High-risk neuroblastoma is an aggressive disease. DNA sequencing studies have revealed a paucity of actionable genomic alterations and a low mutation burden, posing challenges to develop effective novel therapies. We used RNA sequencing (RNA-seq) to investigate the biology of this disease including a focus on tumor-infiltrating lymphocytes (TILs). We performed deep RNA-seq on pre-treatment diagnostic tumors from 129 high-risk and 21 low- or intermediate-risk patients with neuroblastomas. We used single-sample gene set enrichment analysis to detect gene expression signatures of TILs in tumors and examined their association with clinical and molecular parameters including patient outcome. The expression profiles of 190 additional pre-treatment diagnostic neuroblastomas, a neuroblastoma tissue microarray, and T-cell receptor (TCR) sequencing were used to validate our findings. We found that MYCN -not-amplified ( MYCN -NA) tumors had significant higher cytotoxic TIL signatures compared to MYCN -amplified ( MYCN -A) tumors. A reported MYCN-activation-signature was significantly associated with poor outcome for high-risk patients with MYCN -NA tumors; however, a subgroup of these patients who had elevated activated NK cells, CD8+ T-cells, and cytolytic signatures showed improved outcome and expansion of infiltrating T-cell receptor (TCR) clones. Furthermore, we observed up-regulation of immune exhaustion marker genes, indicating an immune suppressive microenvironment in these neuroblastomas. Conclusions: This study provides evidence that RNA signatures of cytotoxic TIL are associated with the presence of activated NK-/T-cells and improved outcomes in high-risk neuroblastoma patients harboring MYCN -NA tumors. Our findings suggest that these high-risk patients with MYCN -NA neuroblastoma may benefit from additional immunotherapies incorporated into the current therapeutic strategies. Copyright ©2018, American Association for Cancer Research.

Transcriptome Profiling of a Multiple Recurrent Muscle-Invasive Urothelial Carcinoma of the Bladder by Deep Sequencing

PubMed Central

Zhang, Shufang; Liu, Yanxuan; Liu, Zhenxiang; Zhang, Chong; Cao, Hui; Ye, Yongqing; Wang, Shunlan; Zhang, Ying'ai; Xiao, Sifang; Yang, Peng; Li, Jindong; Bai, Zhiming

2014-01-01

Urothelial carcinoma of the bladder (UCB) is one of the commonly diagnosed cancers in the world. The UCB has the highest rate of recurrence of any malignancy. A genome-wide screening of transcriptome dysregulation between cancer and normal tissue would provide insight into the molecular basis of UCB recurrence and is a key step to discovering biomarkers for diagnosis and therapeutic targets. Compared with microarray technology, which is commonly used to identify expression level changes, the recently developed RNA-seq technique has the ability to detect other abnormal regulations in the cancer transcriptome, such as alternative splicing. In this study, we performed high-throughput transcriptome sequencing at ∼50× coverage on a recurrent muscle-invasive cisplatin-resistance UCB tissue and the adjacent non-tumor tissue. The results revealed cancer-specific differentially expressed genes between the tumor and non-tumor tissue enriched in the cell adhesion molecules, focal adhesion and ECM-receptor interaction pathway. Five dysregulated genes, including CDH1, VEGFA, PTPRF, CLDN7, and MMP2 were confirmed by Real time qPCR in the sequencing samples and the additional eleven samples. Our data revealed that more than three hundred genes showed differential splicing patterns between tumor tissue and non-tumor tissue. Among these genes, we filtered 24 cancer-associated alternative splicing genes with differential exon usage. The findings from RNA-Seq were validated by Real time qPCR for CD44, PDGFA, NUMB, and LPHN2. This study provides a comprehensive survey of the UCB transcriptome, which provides better insight into the complexity of regulatory changes during recurrence and metastasis. PMID:24622401

Deep Sequencing Reveals Uncharted Isoform Heterogeneity of the Protein-Coding Transcriptome in Cerebral Ischemia.

PubMed

Bhattarai, Sunil; Aly, Ahmed; Garcia, Kristy; Ruiz, Diandra; Pontarelli, Fabrizio; Dharap, Ashutosh

2018-06-03

Gene expression in cerebral ischemia has been a subject of intense investigations for several years. Studies utilizing probe-based high-throughput methodologies such as microarrays have contributed significantly to our existing knowledge but lacked the capacity to dissect the transcriptome in detail. Genome-wide RNA-sequencing (RNA-seq) enables comprehensive examinations of transcriptomes for attributes such as strandedness, alternative splicing, alternative transcription start/stop sites, and sequence composition, thus providing a very detailed account of gene expression. Leveraging this capability, we conducted an in-depth, genome-wide evaluation of the protein-coding transcriptome of the adult mouse cortex after transient focal ischemia at 6, 12, or 24 h of reperfusion using RNA-seq. We identified a total of 1007 transcripts at 6 h, 1878 transcripts at 12 h, and 1618 transcripts at 24 h of reperfusion that were significantly altered as compared to sham controls. With isoform-level resolution, we identified 23 splice variants arising from 23 genes that were novel mRNA isoforms. For a subset of genes, we detected reperfusion time-point-dependent splice isoform switching, indicating an expression and/or functional switch for these genes. Finally, for 286 genes across all three reperfusion time-points, we discovered multiple, distinct, simultaneously expressed and differentially altered isoforms per gene that were generated via alternative transcription start/stop sites. Of these, 165 isoforms derived from 109 genes were novel mRNAs. Together, our data unravel the protein-coding transcriptome of the cerebral cortex at an unprecedented depth to provide several new insights into the flexibility and complexity of stroke-related gene transcription and transcript organization.

Illumina MiSeq sequencing reveals microbial community in HA process for dyeing wastewater treatment fed with different co-substrates.

PubMed

Xie, Xuehui; Liu, Na; Ping, Jing; Zhang, Qingyun; Zheng, Xiulin; Liu, Jianshe

2018-06-01

In present study, a hydrolysis acidification (HA) reactor was used for simulated dyeing wastewater treatment. Co-substrates included starch, glucose, sucrose, yeast extract (YE) and peptone were fed sequentially into the HA reactor to enhance the HA process effects. The performance of the HA reactor and the microbial community structure in HA process were investigated under different co-substrates conditions. Results showed that different co-substrates had different influences on the performance of HA reactor. The highest decolorization (50.64%) and COD removal rate (60.73%) of the HA reactor were obtained when sucrose was as the co-substrate. And it found that carbon co-substrates starch, glucose and sucrose exhibited better decolorization and higher COD removal efficiency of the HA reactor than the nitrogen co-substrates YE and peptone. Microbial community structure in the HA process was analyzed by Illumina MiSeq sequencing. Results revealed different co-substrates had different influences on the community structure and microbial diversity in HA process. It was considered that sucrose could enrich the species such as Raoultella, Desulfovibrio, Tolumonas, Clostridium, which might be capable of degrading the dyes. Sucrose was considered to be the best co-substrate of enhancing the HA reactor's performance in this study. This work would provide deep insight into the influence of many different co-substrates on HA reactor performance and microbial communities in HA process. Copyright © 2018 Elsevier Ltd. All rights reserved.

Elucidating the 16S rRNA 3' boundaries and defining optimal SD/aSD pairing in Escherichia coli and Bacillus subtilis using RNA-Seq data.

PubMed

Wei, Yulong; Silke, Jordan R; Xia, Xuhua

2017-12-15

Bacterial translation initiation is influenced by base pairing between the Shine-Dalgarno (SD) sequence in the 5' UTR of mRNA and the anti-SD (aSD) sequence at the free 3' end of the 16S rRNA (3' TAIL) due to: 1) the SD/aSD sequence binding location and 2) SD/aSD binding affinity. In order to understand what makes an SD/aSD interaction optimal, we must define: 1) terminus of the 3' TAIL and 2) extent of the core aSD sequence within the 3' TAIL. Our approach to characterize these components in Escherichia coli and Bacillus subtilis involves 1) mapping the 3' boundary of the mature 16S rRNA using high-throughput RNA sequencing (RNA-Seq), and 2) identifying the segment within the 3' TAIL that is strongly preferred in SD/aSD pairing. Using RNA-Seq data, we resolve previous discrepancies in the reported 3' TAIL in B. subtilis and recovered the established 3' TAIL in E. coli. Furthermore, we extend previous studies to suggest that both highly and lowly expressed genes favor SD sequences with intermediate binding affinity, but this trend is exclusive to SD sequences that complement the core aSD sequences defined herein.

QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization.

PubMed

Zhao, Shanrong; Xi, Li; Quan, Jie; Xi, Hualin; Zhang, Ying; von Schack, David; Vincent, Michael; Zhang, Baohong

2016-01-08

RNA sequencing (RNA-seq), a next-generation sequencing technique for transcriptome profiling, is being increasingly used, in part driven by the decreasing cost of sequencing. Nevertheless, the analysis of the massive amounts of data generated by large-scale RNA-seq remains a challenge. Multiple algorithms pertinent to basic analyses have been developed, and there is an increasing need to automate the use of these tools so as to obtain results in an efficient and user friendly manner. Increased automation and improved visualization of the results will help make the results and findings of the analyses readily available to experimental scientists. By combing the best open source tools developed for RNA-seq data analyses and the most advanced web 2.0 technologies, we have implemented QuickRNASeq, a pipeline for large-scale RNA-seq data analyses and visualization. The QuickRNASeq workflow consists of three main steps. In Step #1, each individual sample is processed, including mapping RNA-seq reads to a reference genome, counting the numbers of mapped reads, quality control of the aligned reads, and SNP (single nucleotide polymorphism) calling. Step #1 is computationally intensive, and can be processed in parallel. In Step #2, the results from individual samples are merged, and an integrated and interactive project report is generated. All analyses results in the report are accessible via a single HTML entry webpage. Step #3 is the data interpretation and presentation step. The rich visualization features implemented here allow end users to interactively explore the results of RNA-seq data analyses, and to gain more insights into RNA-seq datasets. In addition, we used a real world dataset to demonstrate the simplicity and efficiency of QuickRNASeq in RNA-seq data analyses and interactive visualizations. The seamless integration of automated capabilites with interactive visualizations in QuickRNASeq is not available in other published RNA-seq pipelines. The high degree of automation and interactivity in QuickRNASeq leads to a substantial reduction in the time and effort required prior to further downstream analyses and interpretation of the analyses findings. QuickRNASeq advances primary RNA-seq data analyses to the next level of automation, and is mature for public release and adoption.

Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

PubMed

Devailly, Guillaume; Mantsoki, Anna; Joshi, Anagha

2016-11-01

Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Web application: http://www.heatstarseq.roslin.ed.ac.uk/ Source code: https://github.com/gdevailly CONTACT: Guillaume.Devailly@roslin.ed.ac.uk or Anagha.Joshi@roslin.ed.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations

PubMed Central

Munger, Steven C.; Raghupathy, Narayanan; Choi, Kwangbom; Simons, Allen K.; Gatti, Daniel M.; Hinerfeld, Douglas A.; Svenson, Karen L.; Keller, Mark P.; Attie, Alan D.; Hibbs, Matthew A.; Graber, Joel H.; Chesler, Elissa J.; Churchill, Gary A.

2014-01-01

Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized transcriptomes increases read mapping accuracy, improves estimation of transcript abundance, and enables the direct estimation of allele-specific expression. Moreover, when applied to expression QTL mapping we find that our individualized alignment strategy corrects false-positive linkage signals and unmasks hidden associations. We recommend the use of individualized diploid genomes over reference sequence alignment for all applications of high-throughput sequencing technology in genetically diverse populations. PMID:25236449

Filovirus RefSeq Entries: Evaluation and Selection of Filovirus Type Variants, Type Sequences, and Names

PubMed Central

Kuhn, Jens H.; Andersen, Kristian G.; Bào, Yīmíng; Bavari, Sina; Becker, Stephan; Bennett, Richard S.; Bergman, Nicholas H.; Blinkova, Olga; Bradfute, Steven; Brister, J. Rodney; Bukreyev, Alexander; Chandran, Kartik; Chepurnov, Alexander A.; Davey, Robert A.; Dietzgen, Ralf G.; Doggett, Norman A.; Dolnik, Olga; Dye, John M.; Enterlein, Sven; Fenimore, Paul W.; Formenty, Pierre; Freiberg, Alexander N.; Garry, Robert F.; Garza, Nicole L.; Gire, Stephen K.; Gonzalez, Jean-Paul; Griffiths, Anthony; Happi, Christian T.; Hensley, Lisa E.; Herbert, Andrew S.; Hevey, Michael C.; Hoenen, Thomas; Honko, Anna N.; Ignatyev, Georgy M.; Jahrling, Peter B.; Johnson, Joshua C.; Johnson, Karl M.; Kindrachuk, Jason; Klenk, Hans-Dieter; Kobinger, Gary; Kochel, Tadeusz J.; Lackemeyer, Matthew G.; Lackner, Daniel F.; Leroy, Eric M.; Lever, Mark S.; Mühlberger, Elke; Netesov, Sergey V.; Olinger, Gene G.; Omilabu, Sunday A.; Palacios, Gustavo; Panchal, Rekha G.; Park, Daniel J.; Patterson, Jean L.; Paweska, Janusz T.; Peters, Clarence J.; Pettitt, James; Pitt, Louise; Radoshitzky, Sheli R.; Ryabchikova, Elena I.; Saphire, Erica Ollmann; Sabeti, Pardis C.; Sealfon, Rachel; Shestopalov, Aleksandr M.; Smither, Sophie J.; Sullivan, Nancy J.; Swanepoel, Robert; Takada, Ayato; Towner, Jonathan S.; van der Groen, Guido; Volchkov, Viktor E.; Volchkova, Valentina A.; Wahl-Jensen, Victoria; Warren, Travis K.; Warfield, Kelly L.; Weidmann, Manfred; Nichol, Stuart T.

2014-01-01

Sequence determination of complete or coding-complete genomes of viruses is becoming common practice for supporting the work of epidemiologists, ecologists, virologists, and taxonomists. Sequencing duration and costs are rapidly decreasing, sequencing hardware is under modification for use by non-experts, and software is constantly being improved to simplify sequence data management and analysis. Thus, analysis of virus disease outbreaks on the molecular level is now feasible, including characterization of the evolution of individual virus populations in single patients over time. The increasing accumulation of sequencing data creates a management problem for the curators of commonly used sequence databases and an entry retrieval problem for end users. Therefore, utilizing the data to their fullest potential will require setting nomenclature and annotation standards for virus isolates and associated genomic sequences. The National Center for Biotechnology Information’s (NCBI’s) RefSeq is a non-redundant, curated database for reference (or type) nucleotide sequence records that supplies source data to numerous other databases. Building on recently proposed templates for filovirus variant naming [ ()////-], we report consensus decisions from a majority of past and currently active filovirus experts on the eight filovirus type variants and isolates to be represented in RefSeq, their final designations, and their associated sequences. PMID:25256396

SeqDepot: streamlined database of biological sequences and precomputed features.

PubMed

Ulrich, Luke E; Zhulin, Igor B

2014-01-15

Assembling and/or producing integrated knowledge of sequence features continues to be an onerous and redundant task despite a large number of existing resources. We have developed SeqDepot-a novel database that focuses solely on two primary goals: (i) assimilating known primary sequences with predicted feature data and (ii) providing the most simple and straightforward means to procure and readily use this information. Access to >28.5 million sequences and 300 million features is provided through a well-documented and flexible RESTful interface that supports fetching specific data subsets, bulk queries, visualization and searching by MD5 digests or external database identifiers. We have also developed an HTML5/JavaScript web application exemplifying how to interact with SeqDepot and Perl/Python scripts for use with local processing pipelines. Freely available on the web at http://seqdepot.net/. RESTaccess via http://seqdepot.net/api/v1. Database files and scripts maybe downloaded from http://seqdepot.net/download.

Actinobacterial diversity across a marine transgression in the deep subsurface off Shimokita Peninsula, Japan

NASA Astrophysics Data System (ADS)

Harrison, B. K.; Bailey, J. V.

2013-12-01

Sediment horizons represent a significant - but not permanent - barrier to microbial transport. Cells commonly attach to mineral surfaces in unconsolidated sediments. However, by taxis, growth, or passive migration under advecting fluids, some portion of the microbial community may transgress sedimentary boundaries. Few studies have attempted to constrain such transport of community signatures in the marine subsurface and its potential impact on biogeography. Integrated Ocean Drilling Program (IODP) Expedition 337 off the Shimokita Peninsula recovered sediments over a greater than 1km interval representing a gradual decrease of terrestrial influence, from tidal to continental shelf depositional settings. This sequence represents a key opportunity to link subsurface microbial communities to lithological variability and investigate the permanence of community signatures characteristic of distinct depositional regimes. The phylogenetic connectivity between marine and terrestrially-influenced deposits may demonstrate to what degree sediments offer a substantial barrier to cell transport in the subsurface. Previous work has demonstrated that the Actinobacterial phylum is broadly distributed in marine sediments (Maldonado et al., 2005), present and active in the deep subsurface (Orsi et al., 2013), and that marine and terrestrial lineages may potentially be distinguished by 16S rRNA gene sequencing (e.g. Prieto-Davó et al., 2013). We report on Actinobacteria-specific 16S rRNA gene diversity recovered between 1370 and 2642 mbsf with high-throughput sequencing using the Illumina MiSeq platform, as well as selective assembly and analysis of environmental clone libraries.

A biochemical landscape of A-to-I RNA editing in the human brain transcriptome

PubMed Central

Sakurai, Masayuki; Ueda, Hiroki; Yano, Takanori; Okada, Shunpei; Terajima, Hideki; Mitsuyama, Toutai; Toyoda, Atsushi; Fujiyama, Asao; Kawabata, Hitomi; Suzuki, Tsutomu

2014-01-01

Inosine is an abundant RNA modification in the human transcriptome and is essential for many biological processes in modulating gene expression at the post-transcriptional level. Adenosine deaminases acting on RNA (ADARs) catalyze the hydrolytic deamination of adenosines to inosines (A-to-I editing) in double-stranded regions. We previously established a biochemical method called “inosine chemical erasing” (ICE) to directly identify inosines on RNA strands with high reliability. Here, we have applied the ICE method combined with deep sequencing (ICE-seq) to conduct an unbiased genome-wide screening of A-to-I editing sites in the transcriptome of human adult brain. Taken together with the sites identified by the conventional ICE method, we mapped 19,791 novel sites and newly found 1258 edited mRNAs, including 66 novel sites in coding regions, 41 of which cause altered amino acid assignment. ICE-seq detected novel editing sites in various repeat elements as well as in short hairpins. Gene ontology analysis revealed that these edited mRNAs are associated with transcription, energy metabolism, and neurological disorders, providing new insights into various aspects of human brain functions. PMID:24407955

Evaluation of the hormonal state of columnar apple trees (Malus x domestica) based on high throughput gene expression studies.

PubMed

Krost, Clemens; Petersen, Romina; Lokan, Stefanie; Brauksiepe, Bastienne; Braun, Peter; Schmidt, Erwin R

2013-02-01

The columnar phenotype of apple trees (Malus x domestica) is characterized by a compact growth habit with fruit spurs instead of lateral branches. These properties provide significant economic advantages by enabling high density plantings. The columnar growth results from the presence of a dominant allele of the gene Columnar (Co) located on chromosome 10 which can appear in a heterozygous (Co/co) or homozygous (Co/Co) state. Although two deep sequencing approaches could shed some light on the transcriptome of columnar shoot apical meristems (SAMs), the molecular mechanisms of columnar growth are not yet elaborated. Since the influence of phytohormones is believed to have a pivotal role in the establishment of the phenotype, we performed RNA-Seq experiments to study genes associated with hormone homeostasis and clearly affected by the presence of Co. Our results provide a molecular explanation for earlier findings on the hormonal state of columnar apple trees. Additionally, they allow hypotheses on how the columnar phenotype might develop. Furthermore, we show a statistically approved enrichment of differentially regulated genes on chromosome 10 in the course of validating RNA-Seq results using additional gene expression studies.

RNA-Seq analyses reveal the order of tRNA processing events and the maturation of C/D box and CRISPR RNAs in the hyperthermophile Methanopyrus kandleri

PubMed Central

Su, Andreas A. H.; Tripp, Vanessa; Randau, Lennart

2013-01-01

The methanogenic archaeon Methanopyrus kandleri grows near the upper temperature limit for life. Genome analyses revealed strategies to adapt to these harsh conditions and elucidated a unique transfer RNA (tRNA) C-to-U editing mechanism at base 8 for 30 different tRNA species. Here, RNA-Seq deep sequencing methodology was combined with computational analyses to characterize the small RNome of this hyperthermophilic organism and to obtain insights into the RNA metabolism at extreme temperatures. A large number of 132 small RNAs were identified that guide RNA modifications, which are expected to stabilize structured RNA molecules. The C/D box guide RNAs were shown to exist as circular RNA molecules. In addition, clustered regularly interspaced short palindromic repeats RNA processing and potential regulatory RNAs were identified. Finally, the identification of tRNA precursors before and after the unique C8-to-U8 editing activity enabled the determination of the order of tRNA processing events with termini truncation preceding intron removal. This order of tRNA maturation follows the compartmentalized tRNA processing order found in Eukaryotes and suggests its conservation during evolution. PMID:23620296

Moisture changes in oak and hickory fuel chips on roofed and unroofed Louisiana air-drying grounds as affected by pile depth and turning of chips

Treesearch

Peter Koch

1983-01-01

Freshly cut whole-tree hickory chips had lower moisture content (MC) initially and dried more rapidly than those of southern red oak. Such chips spread during April 1981 in roofed trays did not dry to 20 percent MC, ovendry-weight basis, faster than those spread in October 1980. In roofed trays, unturned chips spread 4 inches deep generally dried more rapidly than if...

SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments.

PubMed

Ajawatanawong, Pravech; Atkinson, Gemma C; Watson-Haigh, Nathan S; Mackenzie, Bryony; Baldauf, Sandra L

2012-07-01

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

Experimental approaches to identify cellular G-quadruplex structures and functions.

PubMed

Di Antonio, Marco; Rodriguez, Raphaël; Balasubramanian, Shankar

2012-05-01

Guanine-rich nucleic acids can fold into non-canonical DNA secondary structures called G-quadruplexes. The formation of these structures can interfere with the biology that is crucial to sustain cellular homeostases and metabolism via mechanisms that include transcription, translation, splicing, telomere maintenance and DNA recombination. Thus, due to their implication in several biological processes and possible role promoting genomic instability, G-quadruplex forming sequences have emerged as potential therapeutic targets. There has been a growing interest in the development of synthetic molecules and biomolecules for sensing G-quadruplex structures in cellular DNA. In this review, we summarise and discuss recent methods developed for cellular imaging of G-quadruplexes, and the application of experimental genomic approaches to detect G-quadruplexes throughout genomic DNA. In particular, we will discuss the use of engineered small molecules and natural proteins to enable pull-down, ChIP-Seq, ChIP-chip and fluorescence imaging of G-quadruplex structures in cellular DNA. Copyright © 2012 Elsevier Inc. All rights reserved.

Recent advances in ChIP-seq analysis: from quality management to whole-genome annotation.

PubMed

Nakato, Ryuichiro; Shirahige, Katsuhiko

2017-03-01

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis can detect protein/DNA-binding and histone-modification sites across an entire genome. Recent advances in sequencing technologies and analyses enable us to compare hundreds of samples simultaneously; such large-scale analysis has potential to reveal the high-dimensional interrelationship level for regulatory elements and annotate novel functional genomic regions de novo. Because many experimental considerations are relevant to the choice of a method in a ChIP-seq analysis, the overall design and quality management of the experiment are of critical importance. This review offers guiding principles of computation and sample preparation for ChIP-seq analyses, highlighting the validity and limitations of the state-of-the-art procedures at each step. We also discuss the latest challenges of single-cell analysis that will encourage a new era in this field. © The Author 2016. Published by Oxford University Press.

Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experiments.

PubMed

Lott, Steffen C; Wolfien, Markus; Riege, Konstantin; Bagnacani, Andrea; Wolkenhauer, Olaf; Hoffmann, Steve; Hess, Wolfgang R

2017-11-10

RNA-Sequencing (RNA-Seq) has become a widely used approach to study quantitative and qualitative aspects of transcriptome data. The variety of RNA-Seq protocols, experimental study designs and the characteristic properties of the organisms under investigation greatly affect downstream and comparative analyses. In this review, we aim to explain the impact of structured pre-selection, classification and integration of best-performing tools within modularized data analysis workflows and ready-to-use computing infrastructures towards experimental data analyses. We highlight examples for workflows and use cases that are presented for pro-, eukaryotic and mixed dual RNA-Seq (meta-transcriptomics) experiments. In addition, we are summarizing the expertise of the laboratories participating in the project consortium "Structured Analysis and Integration of RNA-Seq experiments" (de.STAIR) and its integration with the Galaxy-workbench of the RNA Bioinformatics Center (RBC). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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

PubMed

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

2018-06-01

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

A ChIP-Seq Data Analysis Pipeline Based on Bioconductor Packages.

PubMed

Park, Seung-Jin; Kim, Jong-Hwan; Yoon, Byung-Ha; Kim, Seon-Young

2017-03-01

Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor: dada2, QuasR, mosaics, and ChIPseeker. 'dada2' performs trimming of the high-throughput sequencing data. 'QuasR' and 'mosaics' perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, 'ChIPseeker' performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github: https://github.com/ddhb/Workflow_of_Chipseq.git.

A ChIP-Seq Data Analysis Pipeline Based on Bioconductor Packages

PubMed Central

Park, Seung-Jin; Kim, Jong-Hwan; Yoon, Byung-Ha; Kim, Seon-Young

2017-01-01

Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor: dada2, QuasR, mosaics, and ChIPseeker. ‘dada2’ performs trimming of the high-throughput sequencing data. ‘QuasR’ and ‘mosaics’ perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, ‘ChIPseeker’ performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github: https://github.com/ddhb/Workflow_of_Chipseq.git. PMID:28416945

RnaSeqSampleSize: real data based sample size estimation for RNA sequencing.

PubMed

Zhao, Shilin; Li, Chung-I; Guo, Yan; Sheng, Quanhu; Shyr, Yu

2018-05-30

One of the most important and often neglected components of a successful RNA sequencing (RNA-Seq) experiment is sample size estimation. A few negative binomial model-based methods have been developed to estimate sample size based on the parameters of a single gene. However, thousands of genes are quantified and tested for differential expression simultaneously in RNA-Seq experiments. Thus, additional issues should be carefully addressed, including the false discovery rate for multiple statistic tests, widely distributed read counts and dispersions for different genes. To solve these issues, we developed a sample size and power estimation method named RnaSeqSampleSize, based on the distributions of gene average read counts and dispersions estimated from real RNA-seq data. Datasets from previous, similar experiments such as the Cancer Genome Atlas (TCGA) can be used as a point of reference. Read counts and their dispersions were estimated from the reference's distribution; using that information, we estimated and summarized the power and sample size. RnaSeqSampleSize is implemented in R language and can be installed from Bioconductor website. A user friendly web graphic interface is provided at http://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/ . RnaSeqSampleSize provides a convenient and powerful way for power and sample size estimation for an RNAseq experiment. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

Quantum-Sequencing: Fast electronic single DNA molecule sequencing

NASA Astrophysics Data System (ADS)

Casamada Ribot, Josep; Chatterjee, Anushree; Nagpal, Prashant

2014-03-01

A major goal of third-generation sequencing technologies is to develop a fast, reliable, enzyme-free, high-throughput and cost-effective, single-molecule sequencing method. Here, we present the first demonstration of unique ``electronic fingerprint'' of all nucleotides (A, G, T, C), with single-molecule DNA sequencing, using Quantum-tunneling Sequencing (Q-Seq) at room temperature. We show that the electronic state of the nucleobases shift depending on the pH, with most distinct states identified at acidic pH. We also demonstrate identification of single nucleotide modifications (methylation here). Using these unique electronic fingerprints (or tunneling data), we report a partial sequence of beta lactamase (bla) gene, which encodes resistance to beta-lactam antibiotics, with over 95% success rate. These results highlight the potential of Q-Seq as a robust technique for next-generation sequencing.

RefSeq microbial genomes database: new representation and annotation strategy.

PubMed

Tatusova, Tatiana; Ciufo, Stacy; Fedorov, Boris; O'Neill, Kathleen; Tolstoy, Igor

2014-01-01

The source of the microbial genomic sequences in the RefSeq collection is the set of primary sequence records submitted to the International Nucleotide Sequence Database public archives. These can be accessed through the Entrez search and retrieval system at http://www.ncbi.nlm.nih.gov/genome. Next-generation sequencing has enabled researchers to perform genomic sequencing at rates that were unimaginable in the past. Microbial genomes can now be sequenced in a matter of hours, which has led to a significant increase in the number of assembled genomes deposited in the public archives. This huge increase in DNA sequence data presents new challenges for the annotation, analysis and visualization bioinformatics tools. New strategies have been developed for the annotation and representation of reference genomes and sequence variations derived from population studies and clinical outbreaks.

Coverage Bias and Sensitivity of Variant Calling for Four Whole-genome Sequencing Technologies

PubMed Central

Lasitschka, Bärbel; Jones, David; Northcott, Paul; Hutter, Barbara; Jäger, Natalie; Kool, Marcel; Taylor, Michael; Lichter, Peter; Pfister, Stefan; Wolf, Stephan; Brors, Benedikt; Eils, Roland

2013-01-01

The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illumina’s HiSeq2000, Life Technologies’ SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics’ technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies’ platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes. PMID:23776689

The Porcelain Crab Transcriptome and PCAD, the Porcelain Crab Microarray and Sequence Database

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

Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika

2010-01-27

Background: With the emergence of a completed genome sequence of the freshwater crustacean Daphnia pulex, construction of genomic-scale sequence databases for additional crustacean sequences are important for comparative genomics and annotation. Porcelain crabs, genus Petrolisthes, have been powerful crustacean models for environmental and evolutionary physiology with respect to thermal adaptation and understanding responses of marine organisms to climate change. Here, we present a large-scale EST sequencing and cDNA microarray database project for the porcelain crab Petrolisthes cinctipes. Methodology/Principal Findings: A set of ~;;30K unique sequences (UniSeqs) representing ~;;19K clusters were generated from ~;;98K high quality ESTs from a set ofmore » tissue specific non-normalized and mixed-tissue normalized cDNA libraries from the porcelain crab Petrolisthes cinctipes. Homology for each UniSeq was assessed using BLAST, InterProScan, GO and KEGG database searches. Approximately 66percent of the UniSeqs had homology in at least one of the databases. All EST and UniSeq sequences along with annotation results and coordinated cDNA microarray datasets have been made publicly accessible at the Porcelain Crab Array Database (PCAD), a feature-enriched version of the Stanford and Longhorn Array Databases.Conclusions/Significance: The EST project presented here represents the third largest sequencing effort for any crustacean, and the largest effort for any crab species. Our assembly and clustering results suggest that our porcelain crab EST data set is equally diverse to the much larger EST set generated in the Daphnia pulex genome sequencing project, and thus will be an important resource to the Daphnia research community. Our homology results support the pancrustacea hypothesis and suggest that Malacostraca may be ancestral to Branchiopoda and Hexapoda. Our results also suggest that our cDNA microarrays cover as much of the transcriptome as can reasonably be captured in EST library sequencing approaches, and thus represent a rich resource for studies of environmental genomics.« less

rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

PubMed

Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

2015-07-01

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

GeneChip Resequencing of the Smallpox Virus Genome Can Identify Novel Strains: a Biodefense Application▿

PubMed Central

Sulaiman, Irshad M.; Tang, Kevin; Osborne, John; Sammons, Scott; Wohlhueter, Robert M.

2007-01-01

We developed a set of seven resequencing GeneChips, based on the complete genome sequences of 24 strains of smallpox virus (variola virus), for rapid characterization of this human-pathogenic virus. Each GeneChip was designed to analyze a divergent segment of approximately 30,000 bases of the smallpox virus genome. This study includes the hybridization results of 14 smallpox virus strains. Of the 14 smallpox virus strains hybridized, only 7 had sequence information included in the design of the smallpox virus resequencing GeneChips; similar information for the remaining strains was not tiled as a reference in these GeneChips. By use of variola virus-specific primers and long-range PCR, 22 overlapping amplicons were amplified to cover nearly the complete genome and hybridized with the smallpox virus resequencing GeneChip set. These GeneChips were successful in generating nucleotide sequences for all 14 of the smallpox virus strains hybridized. Analysis of the data indicated that the GeneChip resequencing by hybridization was fast and reproducible and that the smallpox virus resequencing GeneChips could differentiate the 14 smallpox virus strains characterized. This study also suggests that high-density resequencing GeneChips have potential biodefense applications and may be used as an alternate tool for rapid identification of smallpox virus in the future. PMID:17182757

Genotype calling from next-generation sequencing data using haplotype information of reads

PubMed Central

Zhi, Degui; Wu, Jihua; Liu, Nianjun; Zhang, Kui

2012-01-01

Motivation: Low coverage sequencing provides an economic strategy for whole genome sequencing. When sequencing a set of individuals, genotype calling can be challenging due to low sequencing coverage. Linkage disequilibrium (LD) based refinement of genotyping calling is essential to improve the accuracy. Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods. Results: In this article, we introduce a new Hidden Markov Model (HMM)-based method that can take into account jumping reads information across adjacent PPSs and implement it in the HapSeq program. Our method extends the HMM in Thunder and explicitly models jumping reads information as emission probabilities conditional on the states of adjacent PPSs. Our simulation results show that, compared to Thunder, HapSeq reduces the genotyping error rate by 30%, from 0.86% to 0.60%. The results from the 1000 Genomes Project show that HapSeq reduces the genotyping error rate by 12 and 9%, from 2.24% and 2.76% to 1.97% and 2.50% for individuals with European and African ancestry, respectively. We expect our program can improve genotyping qualities of the large number of ongoing and planned whole genome sequencing projects. Contact: dzhi@ms.soph.uab.edu; kzhang@ms.soph.uab.edu Availability: The software package HapSeq and its manual can be found and downloaded at www.ssg.uab.edu/hapseq/. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22285565

Hybrid De Novo Genome Assembly Using MiSeq and SOLiD Short Read Data

PubMed Central

Ikegami, Tsutomu; Inatsugi, Toyohiro; Kojima, Isao; Umemura, Myco; Hagiwara, Hiroko; Machida, Masayuki; Asai, Kiyoshi

2015-01-01

A hybrid de novo assembly pipeline was constructed to utilize both MiSeq and SOLiD short read data in combination in the assembly. The short read data were converted to a standard format of the pipeline, and were supplied to the pipeline components such as ABySS and SOAPdenovo. The assembly pipeline proceeded through several stages, and either MiSeq paired-end data, SOLiD mate-paired data, or both of them could be specified as input data at each stage separately. The pipeline was examined on the filamentous fungus Aspergillus oryzae RIB40, by aligning the assembly results against the reference sequences. Using both the MiSeq and the SOLiD data in the hybrid assembly, the alignment length was improved by a factor of 3 to 8, compared with the assemblies using either one of the data types. The number of the reproduced gene cluster regions encoding secondary metabolite biosyntheses (SMB) was also improved by the hybrid assemblies. These results imply that the MiSeq data with long read length are essential to construct accurate nucleotide sequences, while the SOLiD mate-paired reads with long insertion length enhance long-range arrangements of the sequences. The pipeline was also tested on the actinomycete Streptomyces avermitilis MA-4680, whose gene is known to have high-GC content. Although the quality of the SOLiD reads was too low to perform any meaningful assemblies by themselves, the alignment length to the reference was improved by a factor of 2, compared with the assembly using only the MiSeq data. PMID:25919614

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis.

PubMed

Cornwell, MacIntosh; Vangala, Mahesh; Taing, Len; Herbert, Zachary; Köster, Johannes; Li, Bo; Sun, Hanfei; Li, Taiwen; Zhang, Jian; Qiu, Xintao; Pun, Matthew; Jeselsohn, Rinath; Brown, Myles; Liu, X Shirley; Long, Henry W

2018-04-12

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

Using the self-select paradigm to delineate the nature of speech motor programming.

PubMed

Wright, David L; Robin, Don A; Rhee, Jooyhun; Vaculin, Amber; Jacks, Adam; Guenther, Frank H; Fox, Peter T

2009-06-01

The authors examined the involvement of 2 speech motor programming processes identified by S. T. Klapp (1995, 2003) during the articulation of utterances differing in syllable and sequence complexity. According to S. T. Klapp, 1 process, INT, resolves the demands of the programmed unit, whereas a second process, SEQ, oversees the serial order demands of longer sequences. A modified reaction time paradigm was used to assess INT and SEQ demands. Specifically, syllable complexity was dependent on syllable structure, whereas sequence complexity involved either repeated or unique syllabi within an utterance. INT execution was slowed when articulating single syllables in the form CCCV compared to simpler CV syllables. Planning unique syllables within a multisyllabic utterance rather than repetitions of the same syllable slowed INT but not SEQ. The INT speech motor programming process, important for mental syllabary access, is sensitive to changes in both syllable structure and the number of unique syllables in an utterance.

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

PubMed

Matsunaga, Hiroko; Goto, Mari; Arikawa, Koji; Shirai, Masataka; Tsunoda, Hiroyuki; Huang, Huan; Kambara, Hideki

2015-02-15

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures

PubMed Central

Stanton, Kelly Patrick; Parisi, Fabio; Strino, Francesco; Rabin, Neta; Asp, Patrik; Kluger, Yuval

2013-01-01

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein–chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/. PMID:23873955

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures.

PubMed

Stanton, Kelly Patrick; Parisi, Fabio; Strino, Francesco; Rabin, Neta; Asp, Patrik; Kluger, Yuval

2013-09-01

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein-chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/.

Sequence Alignment to Predict Across Species Susceptibility ...

EPA Pesticide Factsheets

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target, so it is amenable to variable degrees of protein characterization, depending on available information about the chemical/protein interaction and the molecular target itself. To allow for flexibility in the analysis, a layered strategy was adopted for the tool. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of candidate orthologs), the second level evaluates sequence similarity within selected domains (e.g., ligand-binding domain, DNA binding domain), and the third level of analysis compares individual amino acid residue positions identified as being of importance for protein conformation and/or ligand binding upon chemical perturbation. Each level of the SeqAPASS analysis provides increasing evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further ev

metaseq: a Python package for integrative genome-wide analysis reveals relationships between chromatin insulators and associated nuclear mRNA.

PubMed

Dale, Ryan K; Matzat, Leah H; Lei, Elissa P

2014-08-01

Here we introduce metaseq, a software library written in Python, which enables loading multiple genomic data formats into standard Python data structures and allows flexible, customized manipulation and visualization of data from high-throughput sequencing studies. We demonstrate its practical use by analyzing multiple datasets related to chromatin insulators, which are DNA-protein complexes proposed to organize the genome into distinct transcriptional domains. Recent studies in Drosophila and mammals have implicated RNA in the regulation of chromatin insulator activities. Moreover, the Drosophila RNA-binding protein Shep has been shown to antagonize gypsy insulator activity in a tissue-specific manner, but the precise role of RNA in this process remains unclear. Better understanding of chromatin insulator regulation requires integration of multiple datasets, including those from chromatin-binding, RNA-binding, and gene expression experiments. We use metaseq to integrate RIP- and ChIP-seq data for Shep and the core gypsy insulator protein Su(Hw) in two different cell types, along with publicly available ChIP-chip and RNA-seq data. Based on the metaseq-enabled analysis presented here, we propose a model where Shep associates with chromatin cotranscriptionally, then is recruited to insulator complexes in trans where it plays a negative role in insulator activity. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

DNA methylome profiling of maternal peripheral blood and placentas reveal potential fetal DNA markers for non-invasive prenatal testing.

PubMed

Xiang, Yuqian; Zhang, Junyu; Li, Qiaoli; Zhou, Xinyao; Wang, Teng; Xu, Mingqing; Xia, Shihui; Xing, Qinghe; Wang, Lei; He, Lin; Zhao, Xinzhi

2014-09-01

Utilizing epigenetic (DNA methylation) differences to differentiate between maternal peripheral blood (PBL) and fetal (placental) DNA has been a promising strategy for non-invasive prenatal testing (NIPT). However, the differentially methylated regions (DMRs) have yet to be fully ascertained. In the present study, we performed genome-wide comparative methylome analysis between maternal PBL and placental DNA from pregnancies of first trimester by methylated DNA immunoprecipitation-sequencing (MeDIP-Seq) and Infinium HumanMethylation450 BeadChip assays. A total of 36 931 DMRs and 45 804 differentially methylated sites (DMSs) covering the whole genome, exclusive of the Y chromosome, were identified via MeDIP-Seq and Infinium 450k array, respectively, of which 3759 sites in 2188 regions were confirmed by both methods. Not only did we find the previously reported potential fetal DNA markers in our identified DMRs/DMSs but also we verified fully the identified DMRs/DMSs in the validation round by MassARRAY EpiTYPER. The screened potential fetal DNA markers may be used for NIPT on aneuploidies and other chromosomal diseases, such as cri du chat syndrome and velo-cardio-facial syndrome. In addition, these potential markers may have application in the early diagnosis of placental dysfunction, such as pre-eclampsia. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed Central

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

2017-01-01

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

Single-cell Transcriptome Study as Big Data

PubMed Central

Yu, Pingjian; Lin, Wei

2016-01-01

The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and primary objectives of single-cell studies. PMID:26876720

GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases.

PubMed

Zhu, Lihua Julie; Lawrence, Michael; Gupta, Ankit; Pagès, Hervé; Kucukural, Alper; Garber, Manuel; Wolfe, Scot A

2017-05-15

Genome editing technologies developed around the CRISPR-Cas9 nuclease system have facilitated the investigation of a broad range of biological questions. These nucleases also hold tremendous promise for treating a variety of genetic disorders. In the context of their therapeutic application, it is important to identify the spectrum of genomic sequences that are cleaved by a candidate nuclease when programmed with a particular guide RNA, as well as the cleavage efficiency of these sites. Powerful new experimental approaches, such as GUIDE-seq, facilitate the sensitive, unbiased genome-wide detection of nuclease cleavage sites within the genome. Flexible bioinformatics analysis tools for processing GUIDE-seq data are needed. Here, we describe an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria, and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity. The GUIDEseq package enables analysis of GUIDE-data from various nuclease platforms for any species with a defined genomic sequence. This software package has been used successfully to analyze several GUIDE-seq datasets. The software, source code and documentation are freely available at http://www.bioconductor.org/packages/release/bioc/html/GUIDEseq.html .

Plasmonic SERS nanochips and nanoprobes for medical diagnostics and bio-energy applications

NASA Astrophysics Data System (ADS)

Ngo, Hoan T.; Wang, Hsin-Neng; Crawford, Bridget M.; Fales, Andrew M.; Vo-Dinh, Tuan

2017-02-01

The development of rapid, easy-to-use, cost-effective, high accuracy, and high sensitive DNA detection methods for molecular diagnostics has been receiving increasing interest. Over the last five years, our laboratory has developed several chip-based DNA detection techniques including the molecular sentinel-on-chip (MSC), the multiplex MSC, and the inverse molecular sentinel-on-chip (iMS-on-Chip). In these techniques, plasmonic surface-enhanced Raman scattering (SERS) Nanowave chips were functionalized with DNA probes for single-step DNA detection. Sensing mechanisms were based on hybridization of target sequences and DNA probes, resulting in a distance change between SERS reporters and the Nanowave chip's gold surface. This distance change resulted in change in SERS intensity, thus indicating the presence and capture of the target sequences. Our techniques were single-step DNA detection techniques. Target sequences were detected by simple delivery of sample solutions onto DNA probe-functionalized Nanowave chips and SERS signals were measured after 1h - 2h incubation. Target sequence labeling or washing to remove unreacted components was not required, making the techniques simple, easy-to-use, and cost effective. The usefulness of the techniques for medical diagnostics was illustrated by the detection of genetic biomarkers for respiratory viral infection and of dengue virus 4 DNA.

Personal Genome Sequencing in Ostensibly Healthy Individuals and the PeopleSeq Consortium

PubMed Central

Linderman, Michael D.; Nielsen, Daiva E.; Green, Robert C.

2016-01-01

Thousands of ostensibly healthy individuals have had their exome or genome sequenced, but a much smaller number of these individuals have received any personal genomic results from that sequencing. We term those projects in which ostensibly healthy participants can receive sequencing-derived genetic findings and may also have access to their genomic data as participatory predispositional personal genome sequencing (PPGS). Here we are focused on genome sequencing applied in a pre-symptomatic context and so define PPGS to exclude diagnostic genome sequencing intended to identify the molecular cause of suspected or diagnosed genetic disease. In this report we describe the design of completed and underway PPGS projects, briefly summarize the results reported to date and introduce the PeopleSeq Consortium, a newly formed collaboration of PPGS projects designed to collect much-needed longitudinal outcome data. PMID:27023617

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

PubMed

Liao, Wei; Jordaan, Gwen; Nham, Phillipp; Phan, Ryan T; Pelegrini, Matteo; Sharma, Sanjai

2015-10-16

To determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed. Ten CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system. An average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1). The RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis.

Next-Generation Genomics Facility at C-CAMP: Accelerating Genomic Research in India

PubMed Central

S, Chandana; Russiachand, Heikham; H, Pradeep; S, Shilpa; M, Ashwini; S, Sahana; B, Jayanth; Atla, Goutham; Jain, Smita; Arunkumar, Nandini; Gowda, Malali

2014-01-01

Next-Generation Sequencing (NGS; http://www.genome.gov/12513162) is a recent life-sciences technological revolution that allows scientists to decode genomes or transcriptomes at a much faster rate with a lower cost. Genomic-based studies are in a relatively slow pace in India due to the non-availability of genomics experts, trained personnel and dedicated service providers. Using NGS there is a lot of potential to study India's national diversity (of all kinds). We at the Centre for Cellular and Molecular Platforms (C-CAMP) have launched the Next Generation Genomics Facility (NGGF) to provide genomics service to scientists, to train researchers and also work on national and international genomic projects. We have HiSeq1000 from Illumina and GS-FLX Plus from Roche454. The long reads from GS FLX Plus, and high sequence depth from HiSeq1000, are the best and ideal hybrid approaches for de novo and re-sequencing of genomes and transcriptomes. At our facility, we have sequenced around 70 different organisms comprising of more than 388 genomes and 615 transcriptomes – prokaryotes and eukaryotes (fungi, plants and animals). In addition we have optimized other unique applications such as small RNA (miRNA, siRNA etc), long Mate-pair sequencing (2 to 20 Kb), Coding sequences (Exome), Methylome (ChIP-Seq), Restriction Mapping (RAD-Seq), Human Leukocyte Antigen (HLA) typing, mixed genomes (metagenomes) and target amplicons, etc. Translating DNA sequence data from NGS sequencer into meaningful information is an important exercise. Under NGGF, we have bioinformatics experts and high-end computing resources to dissect NGS data such as genome assembly and annotation, gene expression, target enrichment, variant calling (SSR or SNP), comparative analysis etc. Our services (sequencing and bioinformatics) have been utilized by more than 45 organizations (academia and industry) both within India and outside, resulting several publications in peer-reviewed journals and several genomic/transcriptomic data is available at NCBI.

S-MART, a software toolbox to aid RNA-Seq data analysis.

PubMed

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci.

S-MART, A Software Toolbox to Aid RNA-seq Data Analysis

PubMed Central

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci. PMID:21998740

GenomicTools: a computational platform for developing high-throughput analytics in genomics.

PubMed

Tsirigos, Aristotelis; Haiminen, Niina; Bilal, Erhan; Utro, Filippo

2012-01-15

Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines. We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage. The GenomicTools platform (version 2.0.0) was implemented in C++. The source code, documentation, user manual, example datasets and scripts are available online at http://code.google.com/p/ibm-cbc-genomic-tools.

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

PubMed

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

2018-01-01

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

Detection and quantitation of chromosomal mosaicism in human blastocysts using copy number variation sequencing.

PubMed

Ruttanajit, Tida; Chanchamroen, Sujin; Cram, David S; Sawakwongpra, Kritchakorn; Suksalak, Wanwisa; Leng, Xue; Fan, Junmei; Wang, Li; Yao, Yuanqing; Quangkananurug, Wiwat

2016-02-01

Currently, our understanding of the nature and reproductive potential of blastocysts associated with trophectoderm (TE) lineage chromosomal mosaicism is limited. The objective of this study was to first validate copy number variation sequencing (CNV-Seq) for measuring the level of mosaicism and second, examine the nature and level of mosaicism in TE biopsies of patient's blastocysts. TE biopy samples were analysed by array comparative genomic hybridization (CGH) and CNV-Seq to discriminate between euploid, aneuploid and mosaic blastocysts. Using artificial models of TE mosaicism for five different chromosomes, CNV-Seq accurately and reproducibly quantitated mosaicism at levels of 50% and 20%. In a comparative 24-chromosome study of 49 blastocysts by array CGH and CNV-Seq, 43 blastocysts (87.8%) had a concordant diagnosis and 6 blastocysts (12.2%) were discordant. The discordance was attributed to low to medium levels of chromosomal mosaicism (30-70%) not detected by array CGH. In an expanded study of 399 blastocysts using CNV-Seq as the sole diagnostic method, the proportion of diploid-aneuploid mosaics (34, 8.5%) was significantly higher than aneuploid mosaics (18, 4.5%) (p < 0.02). Mosaicism is a significant chromosomal abnormality associated with the TE lineage of human blastocysts that can be reliably and accurately detected by CNV-Seq. © 2015 John Wiley & Sons, Ltd.

SeqCompress: an algorithm for biological sequence compression.

PubMed

Sardaraz, Muhammad; Tahir, Muhammad; Ikram, Ataul Aziz; Bajwa, Hassan

2014-10-01

The growth of Next Generation Sequencing technologies presents significant research challenges, specifically to design bioinformatics tools that handle massive amount of data efficiently. Biological sequence data storage cost has become a noticeable proportion of total cost in the generation and analysis. Particularly increase in DNA sequencing rate is significantly outstripping the rate of increase in disk storage capacity, which may go beyond the limit of storage capacity. It is essential to develop algorithms that handle large data sets via better memory management. This article presents a DNA sequence compression algorithm SeqCompress that copes with the space complexity of biological sequences. The algorithm is based on lossless data compression and uses statistical model as well as arithmetic coding to compress DNA sequences. The proposed algorithm is compared with recent specialized compression tools for biological sequences. Experimental results show that proposed algorithm has better compression gain as compared to other existing algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Performance Comparison of Bench-Top Next Generation Sequencers Using Microdroplet PCR-Based Enrichment for Targeted Sequencing in Patients with Autism Spectrum Disorder

PubMed Central

Okamoto, Nobuhiko; Nakashima, Mitsuko; Tsurusaki, Yoshinori; Miyake, Noriko; Saitsu, Hirotomo; Matsumoto, Naomichi

2013-01-01

Next-generation sequencing (NGS) combined with enrichment of target genes enables highly efficient and low-cost sequencing of multiple genes for genetic diseases. The aim of this study was to validate the accuracy and sensitivity of our method for comprehensive mutation detection in autism spectrum disorder (ASD). We assessed the performance of the bench-top Ion Torrent PGM and Illumina MiSeq platforms as optimized solutions for mutation detection, using microdroplet PCR-based enrichment of 62 ASD associated genes. Ten patients with known mutations were sequenced using NGS to validate the sensitivity of our method. The overall read quality was better with MiSeq, largely because of the increased indel-related error associated with PGM. The sensitivity of SNV detection was similar between the two platforms, suggesting they are both suitable for SNV detection in the human genome. Next, we used these methods to analyze 28 patients with ASD, and identified 22 novel variants in genes associated with ASD, with one mutation detected by MiSeq only. Thus, our results support the combination of target gene enrichment and NGS as a valuable molecular method for investigating rare variants in ASD. PMID:24066114

RNA-Seq for gene identification and transcript profiling of three Stevia rebaudiana genotypes.

PubMed

Chen, Junwen; Hou, Kai; Qin, Peng; Liu, Hongchang; Yi, Bin; Yang, Wenting; Wu, Wei

2014-07-07

Stevia (Stevia rebaudiana) is an important medicinal plant that yields diterpenoid steviol glycosides (SGs). SGs are currently used in the preparation of medicines, food products and neutraceuticals because of its sweetening property (zero calories and about 300 times sweeter than sugar). Recently, some progress has been made in understanding the biosynthesis of SGs in Stevia, but little is known about the molecular mechanisms underlying this process. Additionally, the genomics of Stevia, a non-model species, remains uncharacterized. The recent advent of RNA-Seq, a next generation sequencing technology, provides an opportunity to expand the identification of Stevia genes through in-depth transcript profiling. We present a comprehensive landscape of the transcriptome profiles of three genotypes of Stevia with divergent SG compositions characterized using RNA-seq. 191,590,282 high-quality reads were generated and then assembled into 171,837 transcripts with an average sequence length of 969 base pairs. A total of 80,160 unigenes were annotated, and 14,211 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. Gene sequences of all enzymes known to be involved in SG synthesis were examined. A total of 143 UDP-glucosyltransferase (UGT) unigenes were identified, some of which might be involved in SG biosynthesis. The expression patterns of eight of these genes were further confirmed by RT-QPCR. RNA-seq analysis identified candidate genes encoding enzymes responsible for the biosynthesis of SGs in Stevia, a non-model plant without a reference genome. The transcriptome data from this study yielded new insights into the process of SG accumulation in Stevia. Our results demonstrate that RNA-Seq can be successfully used for gene identification and transcript profiling in a non-model species.

MOCCS: Clarifying DNA-binding motif ambiguity using ChIP-Seq data.

PubMed

Ozaki, Haruka; Iwasaki, Wataru

2016-08-01

As a key mechanism of gene regulation, transcription factors (TFs) bind to DNA by recognizing specific short sequence patterns that are called DNA-binding motifs. A single TF can accept ambiguity within its DNA-binding motifs, which comprise both canonical (typical) and non-canonical motifs. Clarification of such DNA-binding motif ambiguity is crucial for revealing gene regulatory networks and evaluating mutations in cis-regulatory elements. Although chromatin immunoprecipitation sequencing (ChIP-seq) now provides abundant data on the genomic sequences to which a given TF binds, existing motif discovery methods are unable to directly answer whether a given TF can bind to a specific DNA-binding motif. Here, we report a method for clarifying the DNA-binding motif ambiguity, MOCCS. Given ChIP-Seq data of any TF, MOCCS comprehensively analyzes and describes every k-mer to which that TF binds. Analysis of simulated datasets revealed that MOCCS is applicable to various ChIP-Seq datasets, requiring only a few minutes per dataset. Application to the ENCODE ChIP-Seq datasets proved that MOCCS directly evaluates whether a given TF binds to each DNA-binding motif, even if known position weight matrix models do not provide sufficient information on DNA-binding motif ambiguity. Furthermore, users are not required to provide numerous parameters or background genomic sequence models that are typically unavailable. MOCCS is implemented in Perl and R and is freely available via https://github.com/yuifu/moccs. By complementing existing motif-discovery software, MOCCS will contribute to the basic understanding of how the genome controls diverse cellular processes via DNA-protein interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

SeqAPASS: Predicting chemical susceptibility to threatened/endangered species

EPA Science Inventory

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) application was devel...

Identification of SNPs associated with muscle yield and quality traits using allelic-imbalance analyses of pooled RNA-Seq samples in rainbow trout.

PubMed

Al-Tobasei, Rafet; Ali, Ali; Leeds, Timothy D; Liu, Sixin; Palti, Yniv; Kenney, Brett; Salem, Mohamed

2017-08-07

Coding/functional SNPs change the biological function of a gene and, therefore, could serve as "large-effect" genetic markers. In this study, we used two bioinformatics pipelines, GATK and SAMtools, for discovering coding/functional SNPs with allelic-imbalances associated with total body weight, muscle yield, muscle fat content, shear force, and whiteness. Phenotypic data were collected for approximately 500 fish, representing 98 families (5 fish/family), from a growth-selected line, and the muscle transcriptome was sequenced from 22 families with divergent phenotypes (4 low- versus 4 high-ranked families per trait). GATK detected 59,112 putative SNPs; of these SNPs, 4798 showed allelic imbalances (>2.0 as an amplification and <0.5 as loss of heterozygosity). SAMtools detected 87,066 putative SNPs; and of them, 4962 had allelic imbalances between the low- and high-ranked families. Only 1829 SNPs with allelic imbalances were common between the two datasets, indicating significant differences in algorithms. The two datasets contained 7930 non-redundant SNPs of which 4439 mapped to 1498 protein-coding genes (with 6.4% non-synonymous SNPs) and 684 mapped to 295 lncRNAs. Validation of a subset of 92 SNPs revealed 1) 86.7-93.8% success rate in calling polymorphic SNPs and 2) 95.4% consistent matching between DNA and cDNA genotypes indicating a high rate of identifying SNPs with allelic imbalances. In addition, 4.64% SNPs revealed random monoallelic expression. Genome distribution of the SNPs with allelic imbalances exhibited high density for all five traits in several chromosomes, especially chromosome 9, 20 and 28. Most of the SNP-harboring genes were assigned to important growth-related metabolic pathways. These results demonstrate utility of RNA-Seq in assessing phenotype-associated allelic imbalances in pooled RNA-Seq samples. The SNPs identified in this study were included in a new SNP-Chip design (available from Affymetrix) for genomic and genetic analyses in rainbow trout.

Construction of Pará rubber tree genome and multi-transcriptome database accelerates rubber researches.

PubMed

Makita, Yuko; Kawashima, Mika; Lau, Nyok Sean; Othman, Ahmad Sofiman; Matsui, Minami

2018-01-19

Natural rubber is an economically important material. Currently the Pará rubber tree, Hevea brasiliensis is the main commercial source. Little is known about rubber biosynthesis at the molecular level. Next-generation sequencing (NGS) technologies brought draft genomes of three rubber cultivars and a variety of RNA sequencing (RNA-seq) data. However, no current genome or transcriptome databases (DB) are organized by gene. A gene-oriented database is a valuable support for rubber research. Based on our original draft genome sequence of H. brasiliensis RRIM600, we constructed a rubber tree genome and transcriptome DB. Our DB provides genome information including gene functional annotations and multi-transcriptome data of RNA-seq, full-length cDNAs including PacBio Isoform sequencing (Iso-Seq), ESTs and genome wide transcription start sites (TSSs) derived from CAGE technology. Using our original and publically available RNA-seq data, we calculated co-expressed genes for identifying functionally related gene sets and/or genes regulated by the same transcription factor (TF). Users can access multi-transcriptome data through both a gene-oriented web page and a genome browser. For the gene searching system, we provide keyword search, sequence homology search and gene expression search; users can also select their expression threshold easily. The rubber genome and transcriptome DB provides rubber tree genome sequence and multi-transcriptomics data. This DB is useful for comprehensive understanding of the rubber transcriptome. This will assist both industrial and academic researchers for rubber and economically important close relatives such as R. communis, M. esculenta and J. curcas. The Rubber Transcriptome DB release 2017.03 is accessible at http://matsui-lab.riken.jp/rubber/ .

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

PubMed

Bansal, Vikas

2017-03-14

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

Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.

PubMed

Xu, Joshua; Gong, Binsheng; Wu, Leihong; Thakkar, Shraddha; Hong, Huixiao; Tong, Weida

2016-03-15

Studies on gene expression in response to therapy have led to the discovery of pharmacogenomics biomarkers and advances in precision medicine. Whole transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene expression and has received wide adoption in the biomedical research community. However, its value in regulatory decision making requires rigorous assessment and consensus between various stakeholders, including the research community, regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC) consortium has made considerable progress in this direction, and is the subject of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites to assess cross-site and cross-platform reproducibility. The results demonstrated that relative gene expression measurements were consistently comparable across labs and platforms, but not so for the measurement of absolute expression levels. As part of the quality evaluation several studies were included to evaluate the utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma study profiled tumor samples from 498 pediatric neuroblastoma patients by both microarray and RNA-seq. RNA-seq offers more utilities than microarray in determining the transcriptomic characteristics of cancer. However, RNA-seq and microarray-based models were comparable in clinical endpoint prediction, even when including additional features unique to RNA-seq beyond gene expression. The toxicogenomics study compared microarray and RNA-seq profiles of the liver samples from rats exposed to 27 different chemicals representing multiple toxicity modes of action. Cross-platform concordance was dependent on chemical treatment and transcript abundance. Though both RNA-seq and microarray are suitable for developing gene expression based predictive models with comparable prediction performance, RNA-seq offers advantages over microarray in profiling genes with low expression. The rat BodyMap study provided a comprehensive rat transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the transferability study demonstrated that signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development using a comprehensive approach with two large clinical data sets. This result suggests continued usefulness of legacy microarray data in the coming RNA-seq era. In conclusion, the SEQC project enhances our understanding of RNA-seq and provides valuable guidelines for RNA-seq based clinical application and safety evaluation to advance precision medicine.

An optimized methodology for whole genome sequencing of RNA respiratory viruses from nasopharyngeal aspirates.

PubMed

Goya, Stephanie; Valinotto, Laura E; Tittarelli, Estefania; Rojo, Gabriel L; Nabaes Jodar, Mercedes S; Greninger, Alexander L; Zaiat, Jonathan J; Marti, Marcelo A; Mistchenko, Alicia S; Viegas, Mariana

2018-01-01

Over the last decade, the number of viral genome sequences deposited in available databases has grown exponentially. However, sequencing methodology vary widely and many published works have relied on viral enrichment by viral culture or nucleic acid amplification with specific primers rather than through unbiased techniques such as metagenomics. The genome of RNA viruses is highly variable and these enrichment methodologies may be difficult to achieve or may bias the results. In order to obtain genomic sequences of human respiratory syncytial virus (HRSV) from positive nasopharyngeal aspirates diverse methodologies were evaluated and compared. A total of 29 nearly complete and complete viral genomes were obtained. The best performance was achieved with a DNase I treatment to the RNA directly extracted from the nasopharyngeal aspirate (NPA), sequence-independent single-primer amplification (SISPA) and library preparation performed with Nextera XT DNA Library Prep Kit with manual normalization. An average of 633,789 and 1,674,845 filtered reads per library were obtained with MiSeq and NextSeq 500 platforms, respectively. The higher output of NextSeq 500 was accompanied by the increasing of duplicated reads percentage generated during SISPA (from an average of 1.5% duplicated viral reads in MiSeq to an average of 74% in NextSeq 500). HRSV genome recovery was not affected by the presence or absence of duplicated reads but the computational demand during the analysis was increased. Considering that only samples with viral load ≥ E+06 copies/ml NPA were tested, no correlation between sample viral loads and number of total filtered reads was observed, nor with the mapped viral reads. The HRSV genomes showed a mean coverage of 98.46% with the best methodology. In addition, genomes of human metapneumovirus (HMPV), human rhinovirus (HRV) and human parainfluenza virus types 1-3 (HPIV1-3) were also obtained with the selected optimal methodology.

Grape RNA-Seq analysis pipeline environment

PubMed Central

Knowles, David G.; Röder, Maik; Merkel, Angelika; Guigó, Roderic

2013-01-01

Motivation: The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of cellular RNA, known as RNA-Seq. Although RNA-Seq provides similar or superior dynamic range than microarrays at similar or lower cost, the lack of standard and user-friendly pipelines is a bottleneck preventing RNA-Seq from becoming the standard for transcriptome analysis. Results: In this work we present a pipeline for processing and analyzing RNA-Seq data, that we have named Grape (Grape RNA-Seq Analysis Pipeline Environment). Grape supports raw sequencing reads produced by a variety of technologies, either in FASTA or FASTQ format, or as prealigned reads in SAM/BAM format. A minimal Grape configuration consists of the file location of the raw sequencing reads, the genome of the species and the corresponding gene and transcript annotation. Grape first runs a set of quality control steps, and then aligns the reads to the genome, a step that is omitted for prealigned read formats. Grape next estimates gene and transcript expression levels, calculates exon inclusion levels and identifies novel transcripts. Grape can be run on a single computer or in parallel on a computer cluster. It is distributed with specific mapping and quantification tools, but given its modular design, any tool supporting popular data interchange formats can be integrated. Availability: Grape can be obtained from the Bioinformatics and Genomics website at: http://big.crg.cat/services/grape. Contact: david.gonzalez@crg.eu or roderic.guigo@crg.eu PMID:23329413

Use of the MicroSeq 500 16S rRNA Gene-Based Sequencing for Identification of Bacterial Isolates That Commercial Automated Systems Failed To Identify Correctly

PubMed Central

Fontana, Carla; Favaro, Marco; Pelliccioni, Marco; Pistoia, Enrico Salvatore; Favalli, Cartesio

2005-01-01

Reliable automated identification and susceptibility testing of clinically relevant bacteria is an essential routine for microbiology laboratories, thus improving patient care. Examples of automated identification systems include the Phoenix (Becton Dickinson) and the VITEK 2 (bioMérieux). However, more and more frequently, microbiologists must isolate “difficult” strains that automated systems often fail to identify. An alternative approach could be the genetic identification of isolates; this is based on 16S rRNA gene sequencing and analysis. The aim of the present study was to evaluate the possible use of MicroSeq 500 (Applera) for sequencing the 16S rRNA gene to identify isolates whose identification is unobtainable by conventional systems. We analyzed 83 “difficult” clinical isolates: 25 gram-positive and 58 gram-negative strains that were contemporaneously identified by both systems—VITEK 2 and Phoenix—while genetic identification was performed by using the MicroSeq 500 system. The results showed that phenotypic identifications by VITEK 2 and Phoenix were remarkably similar: 74% for gram-negative strains (43 of 58) and 80% for gram-positive strains were concordant by both systems and also concordant with genetic characterization. The exceptions were the 15 gram-negative and 9 gram-positive isolates whose phenotypic identifications were contrasting or inconclusive. For these, the use of MicroSeq 500 was fundamental to achieving species identification. In clinical microbiology the use of MicroSeq 500, particularly for strains with ambiguous biochemical profiles (including slow-growing strains), identifies strains more easily than do conventional systems. Moreover, MicroSeq 500 is easy to use and cost-effective, making it applicable also in the clinical laboratory. PMID:15695654

Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform.

PubMed

Schirmer, Melanie; Ijaz, Umer Z; D'Amore, Rosalinda; Hall, Neil; Sloan, William T; Quince, Christopher

2015-03-31

With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata.

PubMed

Fracassetti, Marco; Griffin, Philippa C; Willi, Yvonne

2015-01-01

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

PubMed

Liu, Qiao; Xia, Fei; Yin, Qijin; Jiang, Rui

2018-03-01

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies. We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases. Deopen is freely available at https://github.com/kimmo1019/Deopen. ruijiang@tsinghua.edu.cn. 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

Illumina GA IIx& HiSeq 2000 Production Sequenccing and QC Analysis Pipelines at the DOE Joint Genome Institute

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

Daum, Christopher; Zane, Matthew; Han, James

2011-01-31

The U.S. Department of Energy (DOE) Joint Genome Institute's (JGI) Production Sequencing group is committed to the generation of high-quality genomic DNA sequence to support the mission areas of renewable energy generation, global carbon management, and environmental characterization and clean-up. Within the JGI's Production Sequencing group, a robust Illumina Genome Analyzer and HiSeq pipeline has been established. Optimization of the sesequencer pipelines has been ongoing with the aim of continual process improvement of the laboratory workflow, reducing operational costs and project cycle times to increases ample throughput, and improving the overall quality of the sequence generated. A sequence QC analysismore » pipeline has been implemented to automatically generate read and assembly level quality metrics. The foremost of these optimization projects, along with sequencing and operational strategies, throughput numbers, and sequencing quality results will be presented.« less

Error correcting code with chip kill capability and power saving enhancement

DOEpatents

Gara, Alan G [Mount Kisco, NY; Chen, Dong [Croton On Husdon, NY; Coteus, Paul W [Yorktown Heights, NY; Flynn, William T [Rochester, MN; Marcella, James A [Rochester, MN; Takken, Todd [Brewster, NY; Trager, Barry M [Yorktown Heights, NY; Winograd, Shmuel [Scarsdale, NY

2011-08-30

A method and system are disclosed for detecting memory chip failure in a computer memory system. The method comprises the steps of accessing user data from a set of user data chips, and testing the user data for errors using data from a set of system data chips. This testing is done by generating a sequence of check symbols from the user data, grouping the user data into a sequence of data symbols, and computing a specified sequence of syndromes. If all the syndromes are zero, the user data has no errors. If one of the syndromes is non-zero, then a set of discriminator expressions are computed, and used to determine whether a single or double symbol error has occurred. In the preferred embodiment, less than two full system data chips are used for testing and correcting the user data.

Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting.

PubMed

Khan, Tarik A; Friedensohn, Simon; Gorter de Vries, Arthur R; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T

2016-03-01

High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion-the intraclonal diversity index-which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology.

Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting

PubMed Central

Khan, Tarik A.; Friedensohn, Simon; de Vries, Arthur R. Gorter; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T.

2016-01-01

High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion—the intraclonal diversity index—which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology. PMID:26998518

RNA-Seq profiling reveals novel hepatic gene expression pattern in aflatoxin B1 treated rats.

PubMed

Merrick, B Alex; Phadke, Dhiral P; Auerbach, Scott S; Mav, Deepak; Stiegelmeyer, Suzy M; Shah, Ruchir R; Tice, Raymond R

2013-01-01

Deep sequencing was used to investigate the subchronic effects of 1 ppm aflatoxin B1 (AFB1), a potent hepatocarcinogen, on the male rat liver transcriptome prior to onset of histopathological lesions or tumors. We hypothesized RNA-Seq would reveal more differentially expressed genes (DEG) than microarray analysis, including low copy and novel transcripts related to AFB1's carcinogenic activity compared to feed controls (CTRL). Paired-end reads were mapped to the rat genome (Rn4) with TopHat and further analyzed by DESeq and Cufflinks-Cuffdiff pipelines to identify differentially expressed transcripts, new exons and unannotated transcripts. PCA and cluster analysis of DEGs showed clear separation between AFB1 and CTRL treatments and concordance among group replicates. qPCR of eight high and medium DEGs and three low DEGs showed good comparability among RNA-Seq and microarray transcripts. DESeq analysis identified 1,026 differentially expressed transcripts at greater than two-fold change (p<0.005) compared to 626 transcripts by microarray due to base pair resolution of transcripts by RNA-Seq, probe placement within transcripts or an absence of probes to detect novel transcripts, splice variants and exons. Pathway analysis among DEGs revealed signaling of Ahr, Nrf2, GSH, xenobiotic, cell cycle, extracellular matrix, and cell differentiation networks consistent with pathways leading to AFB1 carcinogenesis, including almost 200 upregulated transcripts controlled by E2f1-related pathways related to kinetochore structure, mitotic spindle assembly and tissue remodeling. We report 49 novel, differentially-expressed transcripts including confirmation by PCR-cloning of two unique, unannotated, hepatic AFB1-responsive transcripts (HAfT's) on chromosomes 1.q55 and 15.q11, overexpressed by 10 to 25-fold. Several potentially novel exons were found and exon refinements were made including AFB1 exon-specific induction of homologous family members, Ugt1a6 and Ugt1a7c. We find the rat transcriptome contains many previously unidentified, AFB1-responsive exons and transcripts supporting RNA-Seq's capabilities to provide new insights into AFB1-mediated gene expression leading to hepatocellular carcinoma.

Base-resolution detection of N 4-methylcytosine in genomic DNA using 4mC-Tet-assisted-bisulfite-sequencing

DOE PAGES

Yu, Miao; Ji, Lexiang; Neumann, Drexel A.; ...

2015-07-15

Restriction-modification (R-M) systems pose a major barrier to DNA transformation and genetic engineering of bacterial species. Systematic identification of DNA methylation in R-M systems, including N 6-methyladenine (6mA), 5-methylcytosine (5mC) and N 4-methylcytosine (4mC), will enable strategies to make these species genetically tractable. Although single-molecule, real time (SMRT) sequencing technology is capable of detecting 4mC directly for any bacterial species regardless of whether an assembled genome exists or not, it is not as scalable to profiling hundreds to thousands of samples compared with the commonly used next-generation sequencing technologies. Here, we present 4mC-Tet-assisted bisulfite-sequencing (4mC-TAB-seq), a next-generation sequencing method thatmore » rapidly and cost efficiently reveals the genome-wide locations of 4mC for bacterial species with an available assembled reference genome. In 4mC-TAB-seq, both cytosines and 5mCs are read out as thymines, whereas only 4mCs are read out as cytosines, revealing their specific positions throughout the genome. We applied 4mC-TAB-seq to study the methylation of a member of the hyperthermophilc genus, Caldicellulosiruptor, in which 4mC-related restriction is a major barrier to DNA transformation from other species. Lastly, in combination with MethylC-seq, both 4mC- and 5mC-containing motifs are identified which can assist in rapid and efficient genetic engineering of these bacteria in the future.« less

Variants of beta-glucosidase

DOEpatents

Fidantsef, Ana; Lamsa, Michael; Gorre-Clancy, Brian

2015-07-14

The present invention relates to variants of a parent beta-glucosidase, comprising a substitution at one or more positions corresponding to positions 142, 183, 266, and 703 of amino acids 1 to 842 of SEQ ID NO: 2 or corresponding to positions 142, 183, 266, and 705 of amino acids 1 to 844 of SEQ ID NO: 70, wherein the variant has beta-glucosidase activity. The present invention also relates to nucleotide sequences encoding the variant beta-glucosidases and to nucleic acid constructs, vectors, and host cells comprising the nucleotide sequences.

Variants of beta-glucosidases

DOEpatents

Fidantsef, Ana; Lamsa, Michael; Gorre-Clancy, Brian

2014-10-07

The present invention relates to variants of a parent beta-glucosidase, comprising a substitution at one or more positions corresponding to positions 142, 183, 266, and 703 of amino acids 1 to 842 of SEQ ID NO: 2 or corresponding to positions 142, 183, 266, and 705 of amino acids 1 to 844 of SEQ ID NO: 70, wherein the variant has beta-glucosidase activity. The present invention also relates to nucleotide sequences encoding the variant beta-glucosidases and to nucleic acid constructs, vectors, and host cells comprising the nucleotide sequences.

Variants of beta-glucosidase

DOEpatents

Fidantsef, Ana [Davis, CA; Lamsa, Michael [Davis, CA; Gorre-Clancy, Brian [Elk Grove, CA

2009-12-29

The present invention relates to variants of a parent beta-glucosidase, comprising a substitution at one or more positions corresponding to positions 142, 183, 266, and 703 of amino acids 1 to 842 of SEQ ID NO: 2 or corresponding to positions 142, 183, 266, and 705 of amino acids 1 to 844 of SEQ ID NO: 70, wherein the variant has beta-glucosidase activity. The present invention also relates to nucleotide sequences encoding the variant beta-glucosidases and to nucleic acid constructs, vectors, and host cells comprising the nucleotide sequences.

SeqAPASS v3.0 for Extrapolation of Toxicity Knowledge Across Species

EPA Science Inventory

The U.S. Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) tool was initially released to the public in 2016, providing a novel means to begin to address challenges in extrapolating toxicity ...

DNA Breaks and End Resection Measured Genome-wide by End Sequencing.

PubMed

Canela, Andres; Sridharan, Sriram; Sciascia, Nicholas; Tubbs, Anthony; Meltzer, Paul; Sleckman, Barry P; Nussenzweig, André

2016-09-01

DNA double-strand breaks (DSBs) arise during physiological transcription, DNA replication, and antigen receptor diversification. Mistargeting or misprocessing of DSBs can result in pathological structural variation and mutation. Here we describe a sensitive method (END-seq) to monitor DNA end resection and DSBs genome-wide at base-pair resolution in vivo. We utilized END-seq to determine the frequency and spectrum of restriction-enzyme-, zinc-finger-nuclease-, and RAG-induced DSBs. Beyond sequence preference, chromatin features dictate the repertoire of these genome-modifying enzymes. END-seq can detect at least one DSB per cell among 10,000 cells not harboring DSBs, and we estimate that up to one out of 60 cells contains off-target RAG cleavage. In addition to site-specific cleavage, we detect DSBs distributed over extended regions during immunoglobulin class-switch recombination. Thus, END-seq provides a snapshot of DNA ends genome-wide, which can be utilized for understanding genome-editing specificities and the influence of chromatin on DSB pathway choice. Published by Elsevier Inc.

DrImpute: imputing dropout events in single cell RNA sequencing data.

PubMed

Gong, Wuming; Kwak, Il-Youp; Pota, Pruthvi; Koyano-Nakagawa, Naoko; Garry, Daniel J

2018-06-08

The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological noise. Because of the low number of RNA transcriptomes and the stochastic nature of the gene expression pattern, there is a high chance of missing nonzero entries as zero, which are called dropout events. We develop DrImpute to impute dropout events in scRNA-seq data. We show that DrImpute has significantly better performance on the separation of the dropout zeros from true zeros than existing imputation algorithms. We also demonstrate that DrImpute can significantly improve the performance of existing tools for clustering, visualization and lineage reconstruction of nine published scRNA-seq datasets. DrImpute can serve as a very useful addition to the currently existing statistical tools for single cell RNA-seq analysis. DrImpute is implemented in R and is available at https://github.com/gongx030/DrImpute .

Hyb-Seq: Combining target enrichment and genome skimming for plant phylogenomics1

PubMed Central

Weitemier, Kevin; Straub, Shannon C. K.; Cronn, Richard C.; Fishbein, Mark; Schmickl, Roswitha; McDonnell, Angela; Liston, Aaron

2014-01-01

• Premise of the study: Hyb-Seq, the combination of target enrichment and genome skimming, allows simultaneous data collection for low-copy nuclear genes and high-copy genomic targets for plant systematics and evolution studies. • Methods and Results: Genome and transcriptome assemblies for milkweed (Asclepias syriaca) were used to design enrichment probes for 3385 exons from 768 genes (>1.6 Mbp) followed by Illumina sequencing of enriched libraries. Hyb-Seq of 12 individuals (10 Asclepias species and two related genera) resulted in at least partial assembly of 92.6% of exons and 99.7% of genes and an average assembly length >2 Mbp. Importantly, complete plastomes and nuclear ribosomal DNA cistrons were assembled using off-target reads. Phylogenomic analyses demonstrated signal conflict between genomes. • Conclusions: The Hyb-Seq approach enables targeted sequencing of thousands of low-copy nuclear exons and flanking regions, as well as genome skimming of high-copy repeats and organellar genomes, to efficiently produce genome-scale data sets for phylogenomics. PMID:25225629