DNA Sequence-Dependent Ionic Currents in Ultra-Small Solid-State Nanopores†

PubMed Central

Comer, Jeffrey

2016-01-01

Measurements of ionic currents through nanopores partially blocked by DNA have emerged as a powerful method for characterization of the DNA nucleotide sequence. Although the effect of the nucleotide sequence on the nanopore blockade current has been experimentally demonstrated, prediction and interpretation of such measurements remain a formidable challenge. Using atomic resolution computational approaches, here we show how the sequence, molecular conformation, and pore geometry affect the blockade ionic current in model solid-state nanopores. We demonstrate that the blockade current from a DNA molecule is determined by the chemical identities and conformations of at least three consecutive nucleotides. We find the blockade currents produced by the nucleotide triplets to vary considerably with their nucleotide sequence despite having nearly identical molecular conformations. Encouragingly, we find blockade current differences as large as 25% for single-base substitutions in ultra small (1.6 nm × 1.1 nm cross section; 2 nm length) solid-state nanopores. Despite the complex dependence of the blockade current on the sequence and conformation of the DNA triplets, we find that, under many conditions, the number of thymine bases is positively correlated with the current, whereas the number of purine bases and the presence of both purine and pyrimidines in the triplet are negatively correlated with the current. Based on these observations, we construct a simple theoretical model that relates the ion current to the base content of a solid-state nanopore. Furthermore, we show that compact conformations of DNA in narrow pores provide the greatest signal-to-noise ratio for single base detection, whereas reduction of the nanopore length increases the ionic current noise. Thus, the sequence dependence of nanopore blockade current can be theoretically rationalized, although the predictions will likely need to be customized for each nanopore type. PMID:27103233

Using single cell sequencing data to model the evolutionary history of a tumor.

PubMed

Kim, Kyung In; Simon, Richard

2014-01-24

The introduction of next-generation sequencing (NGS) technology has made it possible to detect genomic alterations within tumor cells on a large scale. However, most applications of NGS show the genetic content of mixtures of cells. Recently developed single cell sequencing technology can identify variation within a single cell. Characterization of multiple samples from a tumor using single cell sequencing can potentially provide information on the evolutionary history of that tumor. This may facilitate understanding how key mutations accumulate and evolve in lineages to form a heterogeneous tumor. We provide a computational method to infer an evolutionary mutation tree based on single cell sequencing data. Our approach differs from traditional phylogenetic tree approaches in that our mutation tree directly describes temporal order relationships among mutation sites. Our method also accommodates sequencing errors. Furthermore, we provide a method for estimating the proportion of time from the earliest mutation event of the sample to the most recent common ancestor of the sample of cells. Finally, we discuss current limitations on modeling with single cell sequencing data and possible improvements under those limitations. Inferring the temporal ordering of mutational sites using current single cell sequencing data is a challenge. Our proposed method may help elucidate relationships among key mutations and their role in tumor progression.

Investigation of timing effects in modified composite quadrupolar echo pulse sequences by mean of average Hamiltonian theory

NASA Astrophysics Data System (ADS)

Mananga, Eugene Stephane

2018-01-01

The utility of the average Hamiltonian theory and its antecedent the Magnus expansion is presented. We assessed the concept of convergence of the Magnus expansion in quadrupolar spectroscopy of spin-1 via the square of the magnitude of the average Hamiltonian. We investigated this approach for two specific modified composite pulse sequences: COM-Im and COM-IVm. It is demonstrated that the size of the square of the magnitude of zero order average Hamiltonian obtained on the appropriated basis is a viable approach to study the convergence of the Magnus expansion. The approach turns to be efficient in studying pulse sequences in general and can be very useful to investigate coherent averaging in the development of high resolution NMR technique in solids. This approach allows comparing theoretically the two modified composite pulse sequences COM-Im and COM-IVm. We also compare theoretically the current modified composite sequences (COM-Im and COM-IVm) to the recently published modified composite pulse sequences (MCOM-I, MCOM-IV, MCOM-I_d, MCOM-IV_d).

PhyloTreePruner: A Phylogenetic Tree-Based Approach for Selection of Orthologous Sequences for Phylogenomics.

PubMed

Kocot, Kevin M; Citarella, Mathew R; Moroz, Leonid L; Halanych, Kenneth M

2013-01-01

Molecular phylogenetics relies on accurate identification of orthologous sequences among the taxa of interest. Most orthology inference programs available for use in phylogenomics rely on small sets of pre-defined orthologs from model organisms or phenetic approaches such as all-versus-all sequence comparisons followed by Markov graph-based clustering. Such approaches have high sensitivity but may erroneously include paralogous sequences. We developed PhyloTreePruner, a software utility that uses a phylogenetic approach to refine orthology inferences made using phenetic methods. PhyloTreePruner checks single-gene trees for evidence of paralogy and generates a new alignment for each group containing only sequences inferred to be orthologs. Importantly, PhyloTreePruner takes into account support values on the tree and avoids unnecessarily deleting sequences in cases where a weakly supported tree topology incorrectly indicates paralogy. A test of PhyloTreePruner on a dataset generated from 11 completely sequenced arthropod genomes identified 2,027 orthologous groups sampled for all taxa. Phylogenetic analysis of the concatenated supermatrix yielded a generally well-supported topology that was consistent with the current understanding of arthropod phylogeny. PhyloTreePruner is freely available from http://sourceforge.net/projects/phylotreepruner/.

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. PMID:24861618

Transforming clinical microbiology with bacterial genome sequencing.

PubMed

Didelot, Xavier; Bowden, Rory; Wilson, Daniel J; Peto, Tim E A; Crook, Derrick W

2012-09-01

Whole-genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for addressing many microbiological questions. Here, we review the current status of clinical microbiology and how it has already begun to be transformed by using next-generation sequencing. We focus on three essential tasks: identifying the species of an isolate, testing its properties, such as resistance to antibiotics and virulence, and monitoring the emergence and spread of bacterial pathogens. We predict that the application of next-generation sequencing will soon be sufficiently fast, accurate and cheap to be used in routine clinical microbiology practice, where it could replace many complex current techniques with a single, more efficient workflow.

Transforming clinical microbiology with bacterial genome sequencing

PubMed Central

2016-01-01

Whole genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for addressing many microbiological questions. Here we review the current status of clinical microbiology and how it has already begun to be transformed by the use of next-generation sequencing. We focus on three essential tasks: identifying the species of an isolate, testing its properties such as resistance to antibiotics and virulence, and monitoring the emergence and spread of bacterial pathogens. The application of next-generation sequencing will soon be sufficiently fast, accurate and cheap to be used in routine clinical microbiology practice, where it could replace many complex current techniques with a single, more efficient workflow. PMID:22868263

Multiplex De Novo Sequencing of Peptide Antibiotics

NASA Astrophysics Data System (ADS)

Mohimani, Hosein; Liu, Wei-Ting; Yang, Yu-Liang; Gaudêncio, Susana P.; Fenical, William; Dorrestein, Pieter C.; Pevzner, Pavel A.

Proliferation of drug-resistant diseases raises the challenge of searching for new, more efficient antibiotics. Currently, some of the most effective antibiotics (i.e., Vancomycin and Daptomycin) are cyclic peptides produced by non-ribosomal biosynthetic pathways. The isolation and sequencing of cyclic peptide antibiotics, unlike the same activity with linear peptides, is time-consuming and error-prone. The dominant technique for sequencing cyclic peptides is NMR-based and requires large amounts (milligrams) of purified materials that, for most compounds, are not possible to obtain. Given these facts, there is a need for new tools to sequence cyclic NRPs using picograms of material. Since nearly all cyclic NRPs are produced along with related analogs, we develop a mass spectrometry approach for sequencing all related peptides at once (in contrast to the existing approach that analyzes individual peptides). Our results suggest that instead of attempting to isolate and NMR-sequence the most abundant compound, one should acquire spectra of many related compounds and sequence all of them simultaneously using tandem mass spectrometry. We illustrate applications of this approach by sequencing new variants of cyclic peptide antibiotics from Bacillus brevis, as well as sequencing a previously unknown familiy of cyclic NRPs produced by marine bacteria.

Tapping the promise of genomics in species with complex, nonmodel genomes.

PubMed

Hirsch, Candice N; Buell, C Robin

2013-01-01

Genomics is enabling a renaissance in all disciplines of plant biology. However, many plant genomes are complex and remain recalcitrant to current genomic technologies. The complexities of these nonmodel plant genomes are attributable to gene and genome duplication, heterozygosity, ploidy, and/or repetitive sequences. Methods are available to simplify the genome and reduce these barriers, including inbreeding and genome reduction, making these species amenable to current sequencing and assembly methods. Some, but not all, of the complexities in nonmodel genomes can be bypassed by sequencing the transcriptome rather than the genome. Additionally, comparative genomics approaches, which leverage phylogenetic relatedness, can aid in the interpretation of complex genomes. Although there are limitations in accessing complex nonmodel plant genomes using current sequencing technologies, genome manipulation and resourceful analyses can allow access to even the most recalcitrant plant genomes.

Exploration of the Genomic Diversity and Core Genome of the Bifidobacterium adolescentis Phylogenetic Group by Means of a Polyphasic Approach

PubMed Central

Duranti, Sabrina; Turroni, Francesca; Milani, Christian; Foroni, Elena; Bottacini, Francesca; Dal Bello, Fabio; Ferrarini, Alberto; Delledonne, Massimo; van Sinderen, Douwe

2013-01-01

In the current work, we describe genome diversity and core genome sequences among representatives of three bifidobacterial species, i.e., Bifidobacterium adolescentis, Bifidobacterium catenulatum, and Bifidobacterium pseudocatenulatum, by employing a polyphasic approach involving analysis of 16S rRNA gene and 16S-23S internal transcribed spacer (ITS) sequences, pulsed-field gel electrophoresis (PFGE), and comparative genomic hybridization (CGH) assays. PMID:23064340

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

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

2017-10-09

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

Whole-genome CNV analysis: advances in computational approaches.

PubMed

Pirooznia, Mehdi; Goes, Fernando S; Zandi, Peter P

2015-01-01

Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development.

Potential for Monitoring Gut Microbiota for Diagnosing Infections and Graft-versus-Host Disease in Cancer and Stem Cell Transplant Patients.

PubMed

Koh, Andrew Y

2017-11-01

Gut microbiota, the collective community of microorganisms inhabiting the intestine, have been shown to provide many beneficial functions for the host. Recent advances in next-generation sequencing and advanced molecular biology approaches have allowed researchers to identify gut microbiota signatures associated with disease processes and, in some cases, establish causality and elucidate underlying mechanisms. This report reviews 3 commonly used methods for studying the gut microbiota and microbiome (the collective genomes of the gut microorganisms): 16S rRNA gene sequencing, bacterial group or species-specific quantitative polymerase chain reaction (qPCR), and metagenomic shotgun sequencing (MSS). The technical approaches and resources needed for each approach are outlined, and advantages and disadvantages for each approach are summarized. The findings regarding the role of the gut microbiota in the health of patients with cancer and stem cell transplant (SCT) patients (specifically in modulating the development of gut-derived bacterial infections and a posttransplant immune-mediated complication known as graft-vs-host-disease) are reviewed. Finally, there is discussion of the potential viability of these approaches in the actual clinical treatment of cancer and SCT patients. Advances in next-generation sequencing have revolutionized our understanding of the importance of the gut microbiome to human health. Both 16S rRNA gene sequencing and MSS are currently too labor-intensive or computationally burdensome to incorporate into real-time clinical monitoring of gut microbiomes. Yet, the lessons learned from these technologies could be adapted to currently used methods (e.g., qPCR) that could then be rigorously tested in the clinical care of these patients. © 2017 American Association for Clinical Chemistry.

Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor transcriptome.

PubMed

Samad, Abdul Fatah A; Nazaruddin, Nazaruddin; Murad, Abdul Munir Abdul; Jani, Jaeyres; Zainal, Zamri; Ismail, Ismanizan

2018-03-01

In current era, majority of microRNA (miRNA) are being discovered through computational approaches which are more confined towards model plants. Here, for the first time, we have described the identification and characterization of novel miRNA in a non-model plant, Persicaria minor ( P . minor ) using computational approach. Unannotated sequences from deep sequencing were analyzed based on previous well-established parameters. Around 24 putative novel miRNAs were identified from 6,417,780 reads of the unannotated sequence which represented 11 unique putative miRNA sequences. PsRobot target prediction tool was deployed to identify the target transcripts of putative novel miRNAs. Most of the predicted target transcripts (mRNAs) were known to be involved in plant development and stress responses. Gene ontology showed that majority of the putative novel miRNA targets involved in cellular component (69.07%), followed by molecular function (30.08%) and biological process (0.85%). Out of 11 unique putative miRNAs, 7 miRNAs were validated through semi-quantitative PCR. These novel miRNAs discoveries in P . minor may develop and update the current public miRNA database.

LOVD: easy creation of a locus-specific sequence variation database using an "LSDB-in-a-box" approach.

PubMed

Fokkema, Ivo F A C; den Dunnen, Johan T; Taschner, Peter E M

2005-08-01

The completion of the human genome project has initiated, as well as provided the basis for, the collection and study of all sequence variation between individuals. Direct access to up-to-date information on sequence variation is currently provided most efficiently through web-based, gene-centered, locus-specific databases (LSDBs). We have developed the Leiden Open (source) Variation Database (LOVD) software approaching the "LSDB-in-a-Box" idea for the easy creation and maintenance of a fully web-based gene sequence variation database. LOVD is platform-independent and uses PHP and MySQL open source software only. The basic gene-centered and modular design of the database follows the recommendations of the Human Genome Variation Society (HGVS) and focuses on the collection and display of DNA sequence variations. With minimal effort, the LOVD platform is extendable with clinical data. The open set-up should both facilitate and promote functional extension with scripts written by the community. The LOVD software is freely available from the Leiden Muscular Dystrophy pages (www.DMD.nl/LOVD/). To promote the use of LOVD, we currently offer curators the possibility to set up an LSDB on our Leiden server. (c) 2005 Wiley-Liss, Inc.

A new strategy for genome assembly using short sequence reads and reduced representation libraries.

PubMed

Young, Andrew L; Abaan, Hatice Ozel; Zerbino, Daniel; Mullikin, James C; Birney, Ewan; Margulies, Elliott H

2010-02-01

We have developed a novel approach for using massively parallel short-read sequencing to generate fast and inexpensive de novo genomic assemblies comparable to those generated by capillary-based methods. The ultrashort (<100 base) sequences generated by this technology pose specific biological and computational challenges for de novo assembly of large genomes. To account for this, we devised a method for experimentally partitioning the genome using reduced representation (RR) libraries prior to assembly. We use two restriction enzymes independently to create a series of overlapping fragment libraries, each containing a tractable subset of the genome. Together, these libraries allow us to reassemble the entire genome without the need of a reference sequence. As proof of concept, we applied this approach to sequence and assembled the majority of the 125-Mb Drosophila melanogaster genome. We subsequently demonstrate the accuracy of our assembly method with meaningful comparisons against the current available D. melanogaster reference genome (dm3). The ease of assembly and accuracy for comparative genomics suggest that our approach will scale to future mammalian genome-sequencing efforts, saving both time and money without sacrificing quality.

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA.

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems

NASA Technical Reports Server (NTRS)

Heyward, Ann O.

1989-01-01

A two-stage heuristic solution approach for a class of multiobjective, n-job, 1-machine scheduling problems is described. Minimization of job-to-job interference for n jobs is sought. The first stage generates alternative schedule sequences by interchanging pairs of schedule elements. The set of alternative sequences can represent nodes of a decision tree; each node is reached via decision to interchange job elements. The second stage selects the parent node for the next generation of alternative sequences through automated paired comparison of objective performance for all current nodes. An application of the heuristic approach to communications satellite systems planning is presented.

A new approach for detecting fungal and oomycete plant pathogens in next generation sequencing metagenome data utilising electronic probes

USDA-ARS?s Scientific Manuscript database

Early stage infections caused by fungal/oomycete spores can remain undetected until signs or symptoms develop. Serological and molecular techniques are currently used for detecting these pathogens. Next-generation sequencing (NGS) has potential as a diagnostic tool, due to the capacity to target mul...

Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

PubMed Central

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

PubMed

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

Assessing the utility of the Oxford Nanopore MinION for snake venom gland cDNA sequencing.

PubMed

Hargreaves, Adam D; Mulley, John F

2015-01-01

Portable DNA sequencers such as the Oxford Nanopore MinION device have the potential to be truly disruptive technologies, facilitating new approaches and analyses and, in some cases, taking sequencing out of the lab and into the field. However, the capabilities of these technologies are still being revealed. Here we show that single-molecule cDNA sequencing using the MinION accurately characterises venom toxin-encoding genes in the painted saw-scaled viper, Echis coloratus. We find the raw sequencing error rate to be around 12%, improved to 0-2% with hybrid error correction and 3% with de novo error correction. Our corrected data provides full coding sequences and 5' and 3' UTRs for 29 of 33 candidate venom toxins detected, far superior to Illumina data (13/40 complete) and Sanger-based ESTs (15/29). We suggest that, should the current pace of improvement continue, the MinION will become the default approach for cDNA sequencing in a variety of species.

Assessing the utility of the Oxford Nanopore MinION for snake venom gland cDNA sequencing

PubMed Central

Hargreaves, Adam D.

2015-01-01

Portable DNA sequencers such as the Oxford Nanopore MinION device have the potential to be truly disruptive technologies, facilitating new approaches and analyses and, in some cases, taking sequencing out of the lab and into the field. However, the capabilities of these technologies are still being revealed. Here we show that single-molecule cDNA sequencing using the MinION accurately characterises venom toxin-encoding genes in the painted saw-scaled viper, Echis coloratus. We find the raw sequencing error rate to be around 12%, improved to 0–2% with hybrid error correction and 3% with de novo error correction. Our corrected data provides full coding sequences and 5′ and 3′ UTRs for 29 of 33 candidate venom toxins detected, far superior to Illumina data (13/40 complete) and Sanger-based ESTs (15/29). We suggest that, should the current pace of improvement continue, the MinION will become the default approach for cDNA sequencing in a variety of species. PMID:26623194

An approach to large scale identification of non-obvious structural similarities between proteins

PubMed Central

Cherkasov, Artem; Jones, Steven JM

2004-01-01

Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence. PMID:15147578

Mutation Detection with Next-Generation Resequencing through a Mediator Genome

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

Wurtzel, Omri; Dori-Bachash, Mally; Pietrokovski, Shmuel

2010-12-31

The affordability of next generation sequencing (NGS) is transforming the field of mutation analysis in bacteria. The genetic basis for phenotype alteration can be identified directly by sequencing the entire genome of the mutant and comparing it to the wild-type (WT) genome, thus identifying acquired mutations. A major limitation for this approach is the need for an a-priori sequenced reference genome for the WT organism, as the short reads of most current NGS approaches usually prohibit de-novo genome assembly. To overcome this limitation we propose a general framework that utilizes the genome of relative organisms as mediators for comparing WTmore » and mutant bacteria. Under this framework, both mutant and WT genomes are sequenced with NGS, and the short sequencing reads are mapped to the mediator genome. Variations between the mutant and the mediator that recur in the WT are ignored, thus pinpointing the differences between the mutant and the WT. To validate this approach we sequenced the genome of Bdellovibrio bacteriovorus 109J, an obligatory bacterial predator, and its prey-independent mutant, and compared both to the mediator species Bdellovibrio bacteriovorus HD100. Although the mutant and the mediator sequences differed in more than 28,000 nucleotide positions, our approach enabled pinpointing the single causative mutation. Experimental validation in 53 additional mutants further established the implicated gene. Our approach extends the applicability of NGS-based mutant analyses beyond the domain of available reference genomes.« less

BAUM: improving genome assembly by adaptive unique mapping and local overlap-layout-consensus approach.

PubMed

Wang, Anqi; Wang, Zhanyu; Li, Zheng; Li, Lei M

2018-06-15

It is highly desirable to assemble genomes of high continuity and consistency at low cost. The current bottleneck of draft genome continuity using the second generation sequencing (SGS) reads is primarily caused by uncertainty among repetitive sequences. Even though the single-molecule real-time sequencing technology is very promising to overcome the uncertainty issue, its relatively high cost and error rate add burden on budget or computation. Many long-read assemblers take the overlap-layout-consensus (OLC) paradigm, which is less sensitive to sequencing errors, heterozygosity and variability of coverage. However, current assemblers of SGS data do not sufficiently take advantage of the OLC approach. Aiming at minimizing uncertainty, the proposed method BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can (i) perform reference-assisted assembly based on the genome of a close species (ii) or improve the results of existing assemblies that are obtained based on short or long sequencing reads. The tests on two eukaryote genomes, a wild rice Oryza longistaminata and a parrot Melopsittacus undulatus, show that BAUM achieved substantial improvement on genome size and continuity. Besides, BAUM reconstructed a considerable amount of repetitive regions that failed to be assembled by existing short read assemblers. We also propose statistical approaches to control the uncertainty in different steps of BAUM. http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum. Supplementary data are available at Bioinformatics online.

A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution.

PubMed

Reinharz, Vladimir; Ponty, Yann; Waldispühl, Jérôme

2013-07-01

The design of RNA sequences folding into predefined secondary structures is a milestone for many synthetic biology and gene therapy studies. Most of the current software uses similar local search strategies (i.e. a random seed is progressively adapted to acquire the desired folding properties) and more importantly do not allow the user to control explicitly the nucleotide distribution such as the GC-content in their sequences. However, the latter is an important criterion for large-scale applications as it could presumably be used to design sequences with better transcription rates and/or structural plasticity. In this article, we introduce IncaRNAtion, a novel algorithm to design RNA sequences folding into target secondary structures with a predefined nucleotide distribution. IncaRNAtion uses a global sampling approach and weighted sampling techniques. We show that our approach is fast (i.e. running time comparable or better than local search methods), seedless (we remove the bias of the seed in local search heuristics) and successfully generates high-quality sequences (i.e. thermodynamically stable) for any GC-content. To complete this study, we develop a hybrid method combining our global sampling approach with local search strategies. Remarkably, our glocal methodology overcomes both local and global approaches for sampling sequences with a specific GC-content and target structure. IncaRNAtion is available at csb.cs.mcgill.ca/incarnation/. Supplementary data are available at Bioinformatics online.

Sequencing technologies - the next generation.

PubMed

Metzker, Michael L

2010-01-01

Demand has never been greater for revolutionary technologies that deliver fast, inexpensive and accurate genome information. This challenge has catalysed the development of next-generation sequencing (NGS) technologies. The inexpensive production of large volumes of sequence data is the primary advantage over conventional methods. Here, I present a technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments. I also outline the broad range of applications for NGS technologies, in addition to providing guidelines for platform selection to address biological questions of interest.

Microfluidic droplet enrichment for targeted sequencing

PubMed Central

Eastburn, Dennis J.; Huang, Yong; Pellegrino, Maurizio; Sciambi, Adam; Ptáček, Louis J.; Abate, Adam R.

2015-01-01

Targeted sequence enrichment enables better identification of genetic variation by providing increased sequencing coverage for genomic regions of interest. Here, we report the development of a new target enrichment technology that is highly differentiated from other approaches currently in use. Our method, MESA (Microfluidic droplet Enrichment for Sequence Analysis), isolates genomic DNA fragments in microfluidic droplets and performs TaqMan PCR reactions to identify droplets containing a desired target sequence. The TaqMan positive droplets are subsequently recovered via dielectrophoretic sorting, and the TaqMan amplicons are removed enzymatically prior to sequencing. We demonstrated the utility of this approach by generating an average 31.6-fold sequence enrichment across 250 kb of targeted genomic DNA from five unique genomic loci. Significantly, this enrichment enabled a more comprehensive identification of genetic polymorphisms within the targeted loci. MESA requires low amounts of input DNA, minimal prior locus sequence information and enriches the target region without PCR bias or artifacts. These features make it well suited for the study of genetic variation in a number of research and diagnostic applications. PMID:25873629

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

PubMed

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

2018-01-10

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

The long reads ahead: de novo genome assembly using the MinION

PubMed Central

de Lannoy, Carlos; de Ridder, Dick; Risse, Judith

2017-01-01

Nanopore technology provides a novel approach to DNA sequencing that yields long, label-free reads of constant quality. The first commercial implementation of this approach, the MinION, has shown promise in various sequencing applications. This review gives an up-to-date overview of the MinION's utility as a de novo sequencing device. It is argued that the MinION may allow for portable and affordable de novo sequencing of even complex genomes in the near future, despite the currently error-prone nature of its reads. Through continuous updates to the MinION hardware and the development of new assembly pipelines, both sequencing accuracy and assembly quality have already risen rapidly. However, this fast pace of development has also lead to a lack of overview of the expanding landscape of analysis tools, as performance evaluations are outdated quickly. As the MinION is approaching a state of maturity, its user community would benefit from a thorough comparative benchmarking effort of de novo assembly pipelines in the near future. An earlier version of this article can be found on  bioRxiv. PMID:29375809

Effect of Noise on DNA Sequencing via Transverse Electronic Transport

PubMed Central

Krems, Matt; Zwolak, Michael; Pershin, Yuriy V.; Di Ventra, Massimiliano

2009-01-01

Abstract Previous theoretical studies have shown that measuring the transverse current across DNA strands while they translocate through a nanopore or channel may provide a statistically distinguishable signature of the DNA bases, and may thus allow for rapid DNA sequencing. However, fluctuations of the environment, such as ionic and DNA motion, introduce important scattering processes that may affect the viability of this approach to sequencing. To understand this issue, we have analyzed a simple model that captures the role of this complex environment in electronic dephasing and its ability to remove charge carriers from current-carrying states. We find that these effects do not strongly influence the current distributions due to the off-resonant nature of tunneling through the nucleotides—a result we expect to be a common feature of transport in molecular junctions. In particular, only large scattering strengths, as compared to the energetic gap between the molecular states and the Fermi level, significantly alter the form of the current distributions. Since this gap itself is quite large, the current distributions remain protected from this type of noise, further supporting the possibility of using transverse electronic transport measurements for DNA sequencing. PMID:19804730

Environmental microbiology through the lens of high-throughput DNA sequencing: synopsis of current platforms and bioinformatics approaches.

PubMed

Logares, Ramiro; Haverkamp, Thomas H A; Kumar, Surendra; Lanzén, Anders; Nederbragt, Alexander J; Quince, Christopher; Kauserud, Håvard

2012-10-01

The incursion of High-Throughput Sequencing (HTS) in environmental microbiology brings unique opportunities and challenges. HTS now allows a high-resolution exploration of the vast taxonomic and metabolic diversity present in the microbial world, which can provide an exceptional insight on global ecosystem functioning, ecological processes and evolution. This exploration has also economic potential, as we will have access to the evolutionary innovation present in microbial metabolisms, which could be used for biotechnological development. HTS is also challenging the research community, and the current bottleneck is present in the data analysis side. At the moment, researchers are in a sequence data deluge, with sequencing throughput advancing faster than the computer power needed for data analysis. However, new tools and approaches are being developed constantly and the whole process could be depicted as a fast co-evolution between sequencing technology, informatics and microbiologists. In this work, we examine the most popular and recently commercialized HTS platforms as well as bioinformatics methods for data handling and analysis used in microbial metagenomics. This non-exhaustive review is intended to serve as a broad state-of-the-art guide to researchers expanding into this rapidly evolving field. Copyright © 2012 Elsevier B.V. All rights reserved.

Harnessing Whole Genome Sequencing in Medical Mycology.

PubMed

Cuomo, Christina A

2017-01-01

Comparative genome sequencing studies of human fungal pathogens enable identification of genes and variants associated with virulence and drug resistance. This review describes current approaches, resources, and advances in applying whole genome sequencing to study clinically important fungal pathogens. Genomes for some important fungal pathogens were only recently assembled, revealing gene family expansions in many species and extreme gene loss in one obligate species. The scale and scope of species sequenced is rapidly expanding, leveraging technological advances to assemble and annotate genomes with higher precision. By using iteratively improved reference assemblies or those generated de novo for new species, recent studies have compared the sequence of isolates representing populations or clinical cohorts. Whole genome approaches provide the resolution necessary for comparison of closely related isolates, for example, in the analysis of outbreaks or sampled across time within a single host. Genomic analysis of fungal pathogens has enabled both basic research and diagnostic studies. The increased scale of sequencing can be applied across populations, and new metagenomic methods allow direct analysis of complex samples.

Hybrid error correction and de novo assembly of single-molecule sequencing reads

PubMed Central

Koren, Sergey; Schatz, Michael C.; Walenz, Brian P.; Martin, Jeffrey; Howard, Jason; Ganapathy, Ganeshkumar; Wang, Zhong; Rasko, David A.; McCombie, W. Richard; Jarvis, Erich D.; Phillippy, Adam M.

2012-01-01

Emerging single-molecule sequencing instruments can generate multi-kilobase sequences with the potential to dramatically improve genome and transcriptome assembly. However, the high error rate of single-molecule reads is challenging, and has limited their use to resequencing bacteria. To address this limitation, we introduce a novel correction algorithm and assembly strategy that utilizes shorter, high-identity sequences to correct the error in single-molecule sequences. We demonstrate the utility of this approach on Pacbio RS reads of phage, prokaryotic, and eukaryotic whole genomes, including the novel genome of the parrot Melopsittacus undulatus, as well as for RNA-seq reads of the corn (Zea mays) transcriptome. Our approach achieves over 99.9% read correction accuracy and produces substantially better assemblies than current sequencing strategies: in the best example, quintupling the median contig size relative to high-coverage, second-generation assemblies. Greater gains are predicted if read lengths continue to increase, including the prospect of single-contig bacterial chromosome assembly. PMID:22750884

Individual predictions of eye-movements with dynamic scenes

NASA Astrophysics Data System (ADS)

Barth, Erhardt; Drewes, Jan; Martinetz, Thomas

2003-06-01

We present a model that predicts saccadic eye-movements and can be tuned to a particular human observer who is viewing a dynamic sequence of images. Our work is motivated by applications that involve gaze-contingent interactive displays on which information is displayed as a function of gaze direction. The approach therefore differs from standard approaches in two ways: (1) we deal with dynamic scenes, and (2) we provide means of adapting the model to a particular observer. As an indicator for the degree of saliency we evaluate the intrinsic dimension of the image sequence within a geometric approach implemented by using the structure tensor. Out of these candidate saliency-based locations, the currently attended location is selected according to a strategy found by supervised learning. The data are obtained with an eye-tracker and subjects who view video sequences. The selection algorithm receives candidate locations of current and past frames and a limited history of locations attended in the past. We use a linear mapping that is obtained by minimizing the quadratic difference between the predicted and the actually attended location by gradient descent. Being linear, the learned mapping can be quickly adapted to the individual observer.

Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.

PubMed

Song, Jiangning; Yuan, Zheng; Tan, Hao; Huber, Thomas; Burrage, Kevin

2007-12-01

Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications. We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects. The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide

Rolling circle amplification of metazoan mitochondrialgenomes

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

Simison, W. Brian; Lindberg, D.R.; Boore, J.L.

2005-07-31

Here we report the successful use of rolling circle amplification (RCA) for the amplification of complete metazoan mt genomes to make a product that is amenable to high-throughput genome sequencing techniques. The benefits of RCA over PCR are many and with further development and refinement of RCA, the sequencing of organellar genomics will require far less time and effort than current long PCR approaches.

A statistical method for the detection of variants from next-generation resequencing of DNA pools.

PubMed

Bansal, Vikas

2010-06-15

Next-generation sequencing technologies have enabled the sequencing of several human genomes in their entirety. However, the routine resequencing of complete genomes remains infeasible. The massive capacity of next-generation sequencers can be harnessed for sequencing specific genomic regions in hundreds to thousands of individuals. Sequencing-based association studies are currently limited by the low level of multiplexing offered by sequencing platforms. Pooled sequencing represents a cost-effective approach for studying rare variants in large populations. To utilize the power of DNA pooling, it is important to accurately identify sequence variants from pooled sequencing data. Detection of rare variants from pooled sequencing represents a different challenge than detection of variants from individual sequencing. We describe a novel statistical approach, CRISP [Comprehensive Read analysis for Identification of Single Nucleotide Polymorphisms (SNPs) from Pooled sequencing] that is able to identify both rare and common variants by using two approaches: (i) comparing the distribution of allele counts across multiple pools using contingency tables and (ii) evaluating the probability of observing multiple non-reference base calls due to sequencing errors alone. Information about the distribution of reads between the forward and reverse strands and the size of the pools is also incorporated within this framework to filter out false variants. Validation of CRISP on two separate pooled sequencing datasets generated using the Illumina Genome Analyzer demonstrates that it can detect 80-85% of SNPs identified using individual sequencing while achieving a low false discovery rate (3-5%). Comparison with previous methods for pooled SNP detection demonstrates the significantly lower false positive and false negative rates for CRISP. Implementation of this method is available at http://polymorphism.scripps.edu/~vbansal/software/CRISP/.

Prediction of multi-drug resistance transporters using a novel sequence analysis method [version 2; referees: 2 approved

DOE PAGES

McDermott, Jason E.; Bruillard, Paul; Overall, Christopher C.; ...

2015-03-09

There are many examples of groups of proteins that have similar function, but the determinants of functional specificity may be hidden by lack of sequencesimilarity, or by large groups of similar sequences with different functions. Transporters are one such protein group in that the general function, transport, can be easily inferred from the sequence, but the substrate specificity can be impossible to predict from sequence with current methods. In this paper we describe a linguistic-based approach to identify functional patterns from groups of unaligned protein sequences and its application to predict multi-drug resistance transporters (MDRs) from bacteria. We first showmore » that our method can recreate known patterns from PROSITE for several motifs from unaligned sequences. We then show that the method, MDRpred, can predict MDRs with greater accuracy and positive predictive value than a collection of currently available family-based models from the Pfam database. Finally, we apply MDRpred to a large collection of protein sequences from an environmental microbiome study to make novel predictions about drug resistance in a potential environmental reservoir.« less

How Can We Better Detect Unauthorized GMOs in Food and Feed Chains?

PubMed

Fraiture, Marie-Alice; Herman, Philippe; De Loose, Marc; Debode, Frédéric; Roosens, Nancy H

2017-06-01

Current GMO detection systems have limited abilities to detect unauthorized genetically modified organisms (GMOs). Here, we propose a new workflow, based on next-generation sequencing (NGS) technology, to overcome this problem. In providing information about DNA sequences, this high-throughput workflow can distinguish authorized and unauthorized GMOs by strengthening the tools commonly used by enforcement laboratories with the help of NGS technology. In addition, thanks to its massive sequencing capacity, this workflow could be used to monitor GMOs present in the food and feed chain. In view of its potential implementation by enforcement laboratories, we discuss this innovative approach, its current limitations, and its sustainability of use over time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detecting atypical examples of known domain types by sequence similarity searching: the SBASE domain library approach.

PubMed

Dhir, Somdutta; Pacurar, Mircea; Franklin, Dino; Gáspári, Zoltán; Kertész-Farkas, Attila; Kocsor, András; Eisenhaber, Frank; Pongor, Sándor

2010-11-01

SBASE is a project initiated to detect known domain types and predicting domain architectures using sequence similarity searching (Simon et al., Protein Seq Data Anal, 5: 39-42, 1992, Pongor et al, Nucl. Acids. Res. 21:3111-3115, 1992). The current approach uses a curated collection of domain sequences - the SBASE domain library - and standard similarity search algorithms, followed by postprocessing which is based on a simple statistics of the domain similarity network (http://hydra.icgeb.trieste.it/sbase/). It is especially useful in detecting rare, atypical examples of known domain types which are sometimes missed even by more sophisticated methodologies. This approach does not require multiple alignment or machine learning techniques, and can be a useful complement to other domain detection methodologies. This article gives an overview of the project history as well as of the concepts and principles developed within this the project.

MBMC: An Effective Markov Chain Approach for Binning Metagenomic Reads from Environmental Shotgun Sequencing Projects.

PubMed

Wang, Ying; Hu, Haiyan; Li, Xiaoman

2016-08-01

Metagenomics is a next-generation omics field currently impacting postgenomic life sciences and medicine. Binning metagenomic reads is essential for the understanding of microbial function, compositions, and interactions in given environments. Despite the existence of dozens of computational methods for metagenomic read binning, it is still very challenging to bin reads. This is especially true for reads from unknown species, from species with similar abundance, and/or from low-abundance species in environmental samples. In this study, we developed a novel taxonomy-dependent and alignment-free approach called MBMC (Metagenomic Binning by Markov Chains). Different from all existing methods, MBMC bins reads by measuring the similarity of reads to the trained Markov chains for different taxa instead of directly comparing reads with known genomic sequences. By testing on more than 24 simulated and experimental datasets with species of similar abundance, species of low abundance, and/or unknown species, we report here that MBMC reliably grouped reads from different species into separate bins. Compared with four existing approaches, we demonstrated that the performance of MBMC was comparable with existing approaches when binning reads from sequenced species, and superior to existing approaches when binning reads from unknown species. MBMC is a pivotal tool for binning metagenomic reads in the current era of Big Data and postgenomic integrative biology. The MBMC software can be freely downloaded at http://hulab.ucf.edu/research/projects/metagenomics/MBMC.html .

Teaching Electrical Energy, Voltage and Current: An Alternative Approach.

ERIC Educational Resources Information Center

Licht, Pieter

1991-01-01

A program for teaching the concepts of electric energy, voltage, and current is proposed. The ideas and concepts are introduced in a sequence that places more emphasis on some aspects that are normally treated very briefly. A phenomenological orientation, qualitative and quantitative micro- and macroscopic treatments, and the inclusion of the…

The Electric Circuit as a System: A New Approach.

ERIC Educational Resources Information Center

Hartel, H.

1982-01-01

Traditionally, the terms "current,""voltage," and "resistance" are introduced in a linear sequence according to structure of the discipline and based on measurement operations. A new approach is discussed, the terms being introduced simultaneously in a qualitative way, using the system aspect of the electric circuit as an integrative base.…

Toward the 1,000 dollars human genome.

PubMed

Bennett, Simon T; Barnes, Colin; Cox, Anthony; Davies, Lisa; Brown, Clive

2005-06-01

Revolutionary new technologies, capable of transforming the economics of sequencing, are providing an unparalleled opportunity to analyze human genetic variation comprehensively at the whole-genome level within a realistic timeframe and at affordable costs. Current estimates suggest that it would cost somewhere in the region of 30 million US dollars to sequence an entire human genome using Sanger-based sequencing, and on one machine it would take about 60 years. Solexa is widely regarded as a company with the necessary disruptive technology to be the first to achieve the ultimate goal of the so-called 1,000 dollars human genome - the conceptual cost-point needed for routine analysis of individual genomes. Solexa's technology is based on completely novel sequencing chemistry capable of sequencing billions of individual DNA molecules simultaneously, a base at a time, to enable highly accurate, low cost analysis of an entire human genome in a single experiment. When applied over a large enough genomic region, these new approaches to resequencing will enable the simultaneous detection and typing of known, as well as unknown, polymorphisms, and will also offer information about patterns of linkage disequilibrium in the population being studied. Technological progress, leading to the advent of single-molecule-based approaches, is beginning to dramatically drive down costs and increase throughput to unprecedented levels, each being several orders of magnitude better than that which is currently available. A new sequencing paradigm based on single molecules will be faster, cheaper and more sensitive, and will permit routine analysis at the whole-genome level.

Outbreak of poliomyelitis in Finland in 1984-85 - Re-analysis of viral sequences using the current standard approach.

PubMed

Simonen, Marja-Leena; Roivainen, Merja; Iber, Jane; Burns, Cara; Hovi, Tapani

2010-01-01

In 1984, a wild type 3 poliovirus (PV3/FIN84) spread all over Finland causing nine cases of paralytic poliomyelitis and one case of aseptic meningitis. The outbreak was ended in 1985 with an intensive vaccination campaign. By limited sequence comparison with previously isolated PV3 strains, closest relatives of PV3/FIN84 were found among strains circulating in the Mediterranean region. Now we wanted to reanalyse the relationships using approaches currently exploited in poliovirus surveillance. Cell lysates of 22 strains isolated during the outbreak and stored frozen were subjected to RT-PCR amplification in three genomic regions without prior subculture. Sequences of the entire VP1 coding region, 150 nucleotides in the VP1-2A junction, most of the 5' non-coding region, partial sequences of the 3D RNA polymerase coding region and partial 3' non-coding region were compared within the outbreak and with sequences available in data banks. In addition, complete nucleotide sequences were obtained for 2 strains isolated from two different cases of disease during the outbreak. The results confirmed the previously described wide intraepidemic variation of the strains, including amino acid substitutions in antigenic sites, as well as the likely Mediterranean region origin of the strains. Simplot and bootscanning analyses of the complete genomes indicated complicated evolutionary history of the non-capsid coding regions of the genome suggesting several recombinations with different HEV-C viruses in the past.

Shotgun protein sequencing: assembly of peptide tandem mass spectra from mixtures of modified proteins.

PubMed

Bandeira, Nuno; Clauser, Karl R; Pevzner, Pavel A

2007-07-01

Despite significant advances in the identification of known proteins, the analysis of unknown proteins by MS/MS still remains a challenging open problem. Although Klaus Biemann recognized the potential of MS/MS for sequencing of unknown proteins in the 1980s, low throughput Edman degradation followed by cloning still remains the main method to sequence unknown proteins. The automated interpretation of MS/MS spectra has been limited by a focus on individual spectra and has not capitalized on the information contained in spectra of overlapping peptides. Indeed the powerful shotgun DNA sequencing strategies have not been extended to automated protein sequencing. We demonstrate, for the first time, the feasibility of automated shotgun protein sequencing of protein mixtures by utilizing MS/MS spectra of overlapping and possibly modified peptides generated via multiple proteases of different specificities. We validate this approach by generating highly accurate de novo reconstructions of multiple regions of various proteins in western diamondback rattlesnake venom. We further argue that shotgun protein sequencing has the potential to overcome the limitations of current protein sequencing approaches and thus catalyze the otherwise impractical applications of proteomics methodologies in studies of unknown proteins.

Biophysical and structural considerations for protein sequence evolution

PubMed Central

2011-01-01

Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS < 1 and gamma-distributed rates across sites. Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model. PMID:22171550

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

PubMed

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

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.

Real-time UAV trajectory generation using feature points matching between video image sequences

NASA Astrophysics Data System (ADS)

Byun, Younggi; Song, Jeongheon; Han, Dongyeob

2017-09-01

Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

Project 1: Microbial Genomes: A Genomic Approach to Understanding the Evolution of Virulence. Project 2: From Genomes to Life: Drosophilia Development in Space and Time

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

Robert DeSalle

2004-09-10

This project seeks to use the genomes of two close relatives, A. actinomycetemcomitans and H. aphrophilus, to understand the evolutionary changes that take place in a genome to make it more or less virulent. Our primary specific aim of this project was to sequence, annotate, and analyze the genomes of Actinobacillus actinomycetemcomitans (CU1000, serotype f) and Haemophilus aphrophilus. With these genome sequences we have then compared the whole genome sequences to each other and to the current Aa (HK1651 www.genome.ou.edu) genome project sequence along with other fully sequenced Pasteurellaceae to determine inter and intra species differences that may account formore » the differences and similarities in disease. We also propose to create and curate a comprehensive database where sequence information and analysis for the Pasteurellaceae (family that includes the genera Actinobacillus and Haemophilus) are readily accessible. And finally we have proposed to develop phylogenetic techniques that can be used to efficiently and accurately examine the evolution of genomes. Below we report on progress we have made on these major specific aims. Progress on the specific aims is reported below under two major headings--experimental approaches and bioinformatics and systematic biology approaches.« less

Current strategies for mobilome research.

PubMed

Jørgensen, Tue S; Kiil, Anne S; Hansen, Martin A; Sørensen, Søren J; Hansen, Lars H

2014-01-01

Mobile genetic elements (MGEs) are pivotal for bacterial evolution and adaptation, allowing shuffling of genes even between distantly related bacterial species. The study of these elements is biologically interesting as the mode of genetic propagation is kaleidoscopic and important, as MGEs are the main vehicles of the increasing bacterial antibiotic resistance that causes thousands of human deaths each year. The study of MGEs has previously focused on plasmids from individual isolates, but the revolution in sequencing technology has allowed the study of mobile genomic elements of entire communities using metagenomic approaches. The problem in using metagenomic sequencing for the study of MGEs is that plasmids and other mobile elements only comprise a small fraction of the total genetic content that are difficult to separate from chromosomal DNA based on sequence alone. The distinction between plasmid and chromosome is important as the mobility and regulation of genes largely depend on their genetic context. Several different approaches have been proposed that specifically enrich plasmid DNA from community samples. Here, we review recent approaches used to study entire plasmid pools from complex environments, and point out possible future developments for and pitfalls of these approaches. Further, we discuss the use of the PacBio long-read sequencing technology for MGE discovery.

Y and W Chromosome Assemblies: Approaches and Discoveries.

PubMed

Tomaszkiewicz, Marta; Medvedev, Paul; Makova, Kateryna D

2017-04-01

Hundreds of vertebrate genomes have been sequenced and assembled to date. However, most sequencing projects have ignored the sex chromosomes unique to the heterogametic sex - Y and W - that are known as sex-limited chromosomes (SLCs). Indeed, haploid and repetitive Y chromosomes in species with male heterogamety (XY), and W chromosomes in species with female heterogamety (ZW), are difficult to sequence and assemble. Nevertheless, obtaining their sequences is important for understanding the intricacies of vertebrate genome function and evolution. Recent progress has been made towards the adaptation of next-generation sequencing (NGS) techniques to deciphering SLC sequences. We review here currently available methodology and results with regard to SLC sequencing and assembly. We focus on vertebrates, but bring in some examples from other taxa. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transcriptogenomics identification and characterization of RNA editing sites in human primary monocytes using high-depth next generation sequencing data.

PubMed

Leong, Wai-Mun; Ripen, Adiratna Mat; Mirsafian, Hoda; Mohamad, Saharuddin Bin; Merican, Amir Feisal

2018-06-07

High-depth next generation sequencing data provide valuable insights into the number and distribution of RNA editing events. Here, we report the RNA editing events at cellular level of human primary monocyte using high-depth whole genomic and transcriptomic sequencing data. We identified over a ten thousand putative RNA editing sites and 69% of the sites were A-to-I editing sites. The sites enriched in repetitive sequences and intronic regions. High-depth sequencing datasets revealed that 90% of the canonical sites were edited at lower frequencies (<0.7). Single and multiple human monocytes and brain tissues samples were analyzed through genome sequence independent approach. The later approach was observed to identify more editing sites. Monocytes was observed to contain more C-to-U editing sites compared to brain tissues. Our results establish comparable pipeline that can address current limitations as well as demonstrate the potential for highly sensitive detection of RNA editing events in single cell type. Copyright © 2018 Elsevier Inc. All rights reserved.

The proximal-to-distal sequence in upper-limb motions on multiple levels and time scales.

PubMed

Serrien, Ben; Baeyens, Jean-Pierre

2017-10-01

The proximal-to-distal sequence is a phenomenon that can be observed in a large variety of motions of the upper limbs in both humans and other mammals. The mechanisms behind this sequence are not completely understood and motor control theories able to explain this phenomenon are currently incomplete. The aim of this narrative review is to take a theoretical constraints-led approach to the proximal-to-distal sequence and provide a broad multidisciplinary overview of relevant literature. This sequence exists at multiple levels (brain, spine, muscles, kinetics and kinematics) and on multiple time scales (motion, motor learning and development, growth and possibly even evolution). We hypothesize that the proximodistal spatiotemporal direction on each time scale and level provides part of the organismic constraints that guide the dynamics at the other levels and time scales. The constraint-led approach in this review may serve as a first onset towards integration of evidence and a framework for further experimentation to reveal the dynamics of the proximal-to-distal sequence. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Classification of DNA nucleotides with transverse tunneling currents

NASA Astrophysics Data System (ADS)

Nyvold Pedersen, Jonas; Boynton, Paul; Di Ventra, Massimiliano; Jauho, Antti-Pekka; Flyvbjerg, Henrik

2017-01-01

It has been theoretically suggested and experimentally demonstrated that fast and low-cost sequencing of DNA, RNA, and peptide molecules might be achieved by passing such molecules between electrodes embedded in a nanochannel. The experimental realization of this scheme faces major challenges, however. In realistic liquid environments, typical currents in tunneling devices are of the order of picoamps. This corresponds to only six electrons per microsecond, and this number affects the integration time required to do current measurements in real experiments. This limits the speed of sequencing, though current fluctuations due to Brownian motion of the molecule average out during the required integration time. Moreover, data acquisition equipment introduces noise, and electronic filters create correlations in time-series data. We discuss how these effects must be included in the analysis of, e.g., the assignment of specific nucleobases to current signals. As the signals from different molecules overlap, unambiguous classification is impossible with a single measurement. We argue that the assignment of molecules to a signal is a standard pattern classification problem and calculation of the error rates is straightforward. The ideas presented here can be extended to other sequencing approaches of current interest.

Animation control of surface motion capture.

PubMed

Tejera, Margara; Casas, Dan; Hilton, Adrian

2013-12-01

Surface motion capture (SurfCap) of actor performance from multiple view video provides reconstruction of the natural nonrigid deformation of skin and clothing. This paper introduces techniques for interactive animation control of SurfCap sequences which allow the flexibility in editing and interactive manipulation associated with existing tools for animation from skeletal motion capture (MoCap). Laplacian mesh editing is extended using a basis model learned from SurfCap sequences to constrain the surface shape to reproduce natural deformation. Three novel approaches for animation control of SurfCap sequences, which exploit the constrained Laplacian mesh editing, are introduced: 1) space–time editing for interactive sequence manipulation; 2) skeleton-driven animation to achieve natural nonrigid surface deformation; and 3) hybrid combination of skeletal MoCap driven and SurfCap sequence to extend the range of movement. These approaches are combined with high-level parametric control of SurfCap sequences in a hybrid surface and skeleton-driven animation control framework to achieve natural surface deformation with an extended range of movement by exploiting existing MoCap archives. Evaluation of each approach and the integrated animation framework are presented on real SurfCap sequences for actors performing multiple motions with a variety of clothing styles. Results demonstrate that these techniques enable flexible control for interactive animation with the natural nonrigid surface dynamics of the captured performance and provide a powerful tool to extend current SurfCap databases by incorporating new motions from MoCap sequences.

A chemogenomic analysis of the human proteome: application to enzyme families.

PubMed

Bernasconi, Paul; Chen, Min; Galasinski, Scott; Popa-Burke, Ioana; Bobasheva, Anna; Coudurier, Louis; Birkos, Steve; Hallam, Rhonda; Janzen, William P

2007-10-01

Sequence-based phylogenies (SBP) are well-established tools for describing relationships between proteins. They have been used extensively to predict the behavior and sensitivity toward inhibitors of enzymes within a family. The utility of this approach diminishes when comparing proteins with little sequence homology. Even within an enzyme family, SBPs must be complemented by an orthogonal method that is independent of sequence to better predict enzymatic behavior. A chemogenomic approach is demonstrated here that uses the inhibition profile of a 130,000 diverse molecule library to uncover relationships within a set of enzymes. The profile is used to construct a semimetric additive distance matrix. This matrix, in turn, defines a sequence-independent phylogeny (SIP). The method was applied to 97 enzymes (kinases, proteases, and phosphatases). SIP does not use structural information from the molecules used for establishing the profile, thus providing a more heuristic method than the current approaches, which require knowledge of the specific inhibitor's structure. Within enzyme families, SIP shows a good overall correlation with SBP. More interestingly, SIP uncovers distances within families that are not recognizable by sequence-based methods. In addition, SIP allows the determination of distance between enzymes with no sequence homology, thus uncovering novel relationships not predicted by SBP. This chemogenomic approach, used in conjunction with SBP, should prove to be a powerful tool for choosing target combinations for drug discovery programs as well as for guiding the selection of profiling and liability targets.

AACR precision medicine series: Highlights of the integrating clinical genomics and cancer therapy meeting.

PubMed

Maggi, Elaine; Montagna, Cristina

2015-12-01

The American Association for Cancer Research (AACR) Precision Medicine Series "Integrating Clinical Genomics and Cancer Therapy" took place June 13-16, 2015 in Salt Lake City, Utah. The conference was co-chaired by Charles L. Sawyers form Memorial Sloan Kettering Cancer Center in New York, Elaine R. Mardis form Washington University School of Medicine in St. Louis, and Arul M. Chinnaiyan from University of Michigan in Ann Arbor. About 500 clinicians, basic science investigators, bioinformaticians, and postdoctoral fellows joined together to discuss the current state of Clinical Genomics and the advances and challenges of integrating Next Generation Sequencing (NGS) technologies into clinical practice. The plenary sessions and panel discussions covered current platforms and sequencing approaches adopted for NGS assays of cancer genome at several national and international institutions, different approaches used to map and classify targetable sequence variants, and how information acquired with the sequencing of the cancer genome is used to guide treatment options. While challenges still exist from a technological perspective, it emerged that there exists considerable need for the development of tools to aid the identification of the therapy most suitable based on the mutational profile of the somatic cancer genome. The process to match patients to ongoing clinical trials is still complex. In addition, the need for centralized data repositories, preferably linked to well annotated clinical records, that aid sharing of sequencing information is central to begin understanding the contribution of variants of unknown significance to tumor etiology and response to therapy. Here we summarize the highlights of this stimulating four-day conference with a major emphasis on the open problems that the clinical genomics community is currently facing and the tools most needed for advancing this field. Copyright © 2015. Published by Elsevier B.V. All rights reserved.

The history and advances of reversible terminators used in new generations of sequencing technology.

PubMed

Chen, Fei; Dong, Mengxing; Ge, Meng; Zhu, Lingxiang; Ren, Lufeng; Liu, Guocheng; Mu, Rong

2013-02-01

DNA sequencing using reversible terminators, as one sequencing by synthesis strategy, has garnered a great deal of interest due to its popular application in the second-generation high-throughput DNA sequencing technology. In this review, we provided its history of development, classification, and working mechanism of this technology. We also outlined the screening strategies for DNA polymerases to accommodate the reversible terminators as substrates during polymerization; particularly, we introduced the "REAP" method developed by us. At the end of this review, we discussed current limitations of this approach and provided potential solutions to extend its application. Copyright © 2013. Production and hosting by Elsevier Ltd.

Enhanced Methods for Local Ancestry Assignment in Sequenced Admixed Individuals

PubMed Central

Brown, Robert; Pasaniuc, Bogdan

2014-01-01

Inferring the ancestry at each locus in the genome of recently admixed individuals (e.g., Latino Americans) plays a major role in medical and population genetic inferences, ranging from finding disease-risk loci, to inferring recombination rates, to mapping missing contigs in the human genome. Although many methods for local ancestry inference have been proposed, most are designed for use with genotyping arrays and fail to make use of the full spectrum of data available from sequencing. In addition, current haplotype-based approaches are very computationally demanding, requiring large computational time for moderately large sample sizes. Here we present new methods for local ancestry inference that leverage continent-specific variants (CSVs) to attain increased performance over existing approaches in sequenced admixed genomes. A key feature of our approach is that it incorporates the admixed genomes themselves jointly with public datasets, such as 1000 Genomes, to improve the accuracy of CSV calling. We use simulations to show that our approach attains accuracy similar to widely used computationally intensive haplotype-based approaches with large decreases in runtime. Most importantly, we show that our method recovers comparable local ancestries, as the 1000 Genomes consensus local ancestry calls in the real admixed individuals from the 1000 Genomes Project. We extend our approach to account for low-coverage sequencing and show that accurate local ancestry inference can be attained at low sequencing coverage. Finally, we generalize CSVs to sub-continental population-specific variants (sCSVs) and show that in some cases it is possible to determine the sub-continental ancestry for short chromosomal segments on the basis of sCSVs. PMID:24743331

Pulseq: A rapid and hardware-independent pulse sequence prototyping framework.

PubMed

Layton, Kelvin J; Kroboth, Stefan; Jia, Feng; Littin, Sebastian; Yu, Huijun; Leupold, Jochen; Nielsen, Jon-Fredrik; Stöcker, Tony; Zaitsev, Maxim

2017-04-01

Implementing new magnetic resonance experiments, or sequences, often involves extensive programming on vendor-specific platforms, which can be time consuming and costly. This situation is exacerbated when research sequences need to be implemented on several platforms simultaneously, for example, at different field strengths. This work presents an alternative programming environment that is hardware-independent, open-source, and promotes rapid sequence prototyping. A novel file format is described to efficiently store the hardware events and timing information required for an MR pulse sequence. Platform-dependent interpreter modules convert the file to appropriate instructions to run the sequence on MR hardware. Sequences can be designed in high-level languages, such as MATLAB, or with a graphical interface. Spin physics simulation tools are incorporated into the framework, allowing for comparison between real and virtual experiments. Minimal effort is required to implement relatively advanced sequences using the tools provided. Sequences are executed on three different MR platforms, demonstrating the flexibility of the approach. A high-level, flexible and hardware-independent approach to sequence programming is ideal for the rapid development of new sequences. The framework is currently not suitable for large patient studies or routine scanning although this would be possible with deeper integration into existing workflows. Magn Reson Med 77:1544-1552, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Osmylated DNA, a novel concept for sequencing DNA using nanopores

NASA Astrophysics Data System (ADS)

Kanavarioti, Anastassia

2015-03-01

Saenger sequencing has led the advances in molecular biology, while faster and cheaper next generation technologies are urgently needed. A newer approach exploits nanopores, natural or solid-state, set in an electrical field, and obtains base sequence information from current variations due to the passage of a ssDNA molecule through the pore. A hurdle in this approach is the fact that the four bases are chemically comparable to each other which leads to small differences in current obstruction. ‘Base calling’ becomes even more challenging because most nanopores sense a short sequence and not individual bases. Perhaps sequencing DNA via nanopores would be more manageable, if only the bases were two, and chemically very different from each other; a sequence of 1s and 0s comes to mind. Osmylated DNA comes close to such a sequence of 1s and 0s. Osmylation is the addition of osmium tetroxide bipyridine across the C5-C6 double bond of the pyrimidines. Osmylation adds almost 400% mass to the reactive base, creates a sterically and electronically notably different molecule, labeled 1, compared to the unreactive purines, labeled 0. If osmylated DNA were successfully sequenced, the result would be a sequence of osmylated pyrimidines (1), and purines (0), and not of the actual nucleobases. To solve this problem we studied the osmylation reaction with short oligos and with M13mp18, a long ssDNA, developed a UV-vis assay to measure extent of osmylation, and designed two protocols. Protocol A uses mild conditions and yields osmylated thymidines (1), while leaving the other three bases (0) practically intact. Protocol B uses harsher conditions and effectively osmylates both pyrimidines, but not the purines. Applying these two protocols also to the complementary of the target polynucleotide yields a total of four osmylated strands that collectively could define the actual base sequence of the target DNA.

Genomic sequencing in cystic fibrosis newborn screening: what works best, two-tier predefined CFTR mutation panels or second-tier CFTR panel followed by third-tier sequencing?

PubMed

Currier, Robert J; Sciortino, Stan; Liu, Ruiling; Bishop, Tracey; Alikhani Koupaei, Rasoul; Feuchtbaum, Lisa

2017-10-01

PurposeThe purpose of this study was to model the performance of several known two-tier, predefined mutation panels and three-tier algorithms for cystic fibrosis (CF) screening utilizing the ethnically diverse California population.MethodsThe cystic fibrosis transmembrane conductance regulator (CFTR) mutations identified among the 317 CF cases in California screened between 12 August 2008 and 18 December 2012 were used to compare the expected CF detection rates for several two- and three-tier screening approaches, including the current California approach, which consists of a population-specific 40-mutation panel followed by third-tier sequencing when indicated.ResultsThe data show that the strategy of using third-tier sequencing improves CF detection following an initial elevated immunoreactive trypsinogen and detection of only one mutation on a second-tier panel.ConclusionIn a diverse population, the use of a second-tier panel followed by third-tier CFTR gene sequencing provides a better detection rate for CF, compared with the use of a second-tier approach alone, and is an effective way to minimize the referrals of CF carriers for sweat testing. Restricting screening to a second-tier testing to predefined mutation panels, even broad ones, results in some missed CF cases and demonstrates the limited utility of this approach in states that have diverse multiethnic populations.

Biomolecule Sequencer: Next-Generation DNA Sequencing Technology for In-Flight Environmental Monitoring, Research, and Beyond

NASA Technical Reports Server (NTRS)

Smith, David J.; Burton, Aaron; Castro-Wallace, Sarah; John, Kristen; Stahl, Sarah E.; Dworkin, Jason Peter; Lupisella, Mark L.

2016-01-01

On the International Space Station (ISS), technologies capable of rapid microbial identification and disease diagnostics are not currently available. NASA still relies upon sample return for comprehensive, molecular-based sample characterization. Next-generation DNA sequencing is a powerful approach for identifying microorganisms in air, water, and surfaces onboard spacecraft. The Biomolecule Sequencer payload, manifested to SpaceX-9 and scheduled on the Increment 4748 research plan (June 2016), will assess the functionality of a commercially-available next-generation DNA sequencer in the microgravity environment of ISS. The MinION device from Oxford Nanopore Technologies (Oxford, UK) measures picoamp changes in electrical current dependent on nucleotide sequences of the DNA strand migrating through nanopores in the system. The hardware is exceptionally small (9.5 x 3.2 x 1.6 cm), lightweight (120 grams), and powered only by a USB connection. For the ISS technology demonstration, the Biomolecule Sequencer will be powered by a Microsoft Surface Pro3. Ground-prepared samples containing lambda bacteriophage, Escherichia coli, and mouse genomic DNA, will be launched and stored frozen on the ISS until experiment initiation. Immediately prior to sequencing, a crew member will collect and thaw frozen DNA samples, connect the sequencer to the Surface Pro3, inject thawed samples into a MinION flow cell, and initiate sequencing. At the completion of the sequencing run, data will be downlinked for ground analysis. Identical, synchronous ground controls will be used for data comparisons to determine sequencer functionality, run-time sequence, current dynamics, and overall accuracy. We will present our latest results from the ISS flight experiment the first time DNA has ever been sequenced in space and discuss the many potential applications of the Biomolecule Sequencer for environmental monitoring, medical diagnostics, higher fidelity and more adaptable Space Biology Human Research Program investigations, and even life detection experiments for astrobiology missions.

Library preparation and data analysis packages for rapid genome sequencing.

PubMed

Pomraning, Kyle R; Smith, Kristina M; Bredeweg, Erin L; Connolly, Lanelle R; Phatale, Pallavi A; Freitag, Michael

2012-01-01

High-throughput sequencing (HTS) has quickly become a valuable tool for comparative genetics and genomics and is now regularly carried out in laboratories that are not connected to large sequencing centers. Here we describe an updated version of our protocol for constructing single- and paired-end Illumina sequencing libraries, beginning with purified genomic DNA. The present protocol can also be used for "multiplexing," i.e. the analysis of several samples in a single flowcell lane by generating "barcoded" or "indexed" Illumina sequencing libraries in a way that is independent from Illumina-supported methods. To analyze sequencing results, we suggest several independent approaches but end users should be aware that this is a quickly evolving field and that currently many alignment (or "mapping") and counting algorithms are being developed and tested.

Phylogenomics from Whole Genome Sequences Using aTRAM.

PubMed

Allen, Julie M; Boyd, Bret; Nguyen, Nam-Phuong; Vachaspati, Pranjal; Warnow, Tandy; Huang, Daisie I; Grady, Patrick G S; Bell, Kayce C; Cronk, Quentin C B; Mugisha, Lawrence; Pittendrigh, Barry R; Leonardi, M Soledad; Reed, David L; Johnson, Kevin P

2017-09-01

Novel sequencing technologies are rapidly expanding the size of data sets that can be applied to phylogenetic studies. Currently the most commonly used phylogenomic approaches involve some form of genome reduction. While these approaches make assembling phylogenomic data sets more economical for organisms with large genomes, they reduce the genomic coverage and thereby the long-term utility of the data. Currently, for organisms with moderate to small genomes ($<$1000 Mbp) it is feasible to sequence the entire genome at modest coverage ($10-30\\times$). Computational challenges for handling these large data sets can be alleviated by assembling targeted reads, rather than assembling the entire genome, to produce a phylogenomic data matrix. Here we demonstrate the use of automated Target Restricted Assembly Method (aTRAM) to assemble 1107 single-copy ortholog genes from whole genome sequencing of sucking lice (Anoplura) and out-groups. We developed a pipeline to extract exon sequences from the aTRAM assemblies by annotating them with respect to the original target protein. We aligned these protein sequences with the inferred amino acids and then performed phylogenetic analyses on both the concatenated matrix of genes and on each gene separately in a coalescent analysis. Finally, we tested the limits of successful assembly in aTRAM by assembling 100 genes from close- to distantly related taxa at high to low levels of coverage.Both the concatenated analysis and the coalescent-based analysis produced the same tree topology, which was consistent with previously published results and resolved weakly supported nodes. These results demonstrate that this approach is successful at developing phylogenomic data sets from raw genome sequencing reads. Further, we found that with coverages above $5-10\\times$, aTRAM was successful at assembling 80-90% of the contigs for both close and distantly related taxa. As sequencing costs continue to decline, we expect full genome sequencing will become more feasible for a wider array of organisms, and aTRAM will enable mining of these genomic data sets for an extensive variety of applications, including phylogenomics. [aTRAM; gene assembly; genome sequencing; phylogenomics.]. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants.

PubMed

Taheri, Sima; Lee Abdullah, Thohirah; Yusop, Mohd Rafii; Hanafi, Mohamed Musa; Sahebi, Mahbod; Azizi, Parisa; Shamshiri, Redmond Ramin

2018-02-13

Microsatellites, or simple sequence repeats (SSRs), are one of the most informative and multi-purpose genetic markers exploited in plant functional genomics. However, the discovery of SSRs and development using traditional methods are laborious, time-consuming, and costly. Recently, the availability of high-throughput sequencing technologies has enabled researchers to identify a substantial number of microsatellites at less cost and effort than traditional approaches. Illumina is a noteworthy transcriptome sequencing technology that is currently used in SSR marker development. Although 454 pyrosequencing datasets can be used for SSR development, this type of sequencing is no longer supported. This review aims to present an overview of the next generation sequencing, with a focus on the efficient use of de novo transcriptome sequencing (RNA-Seq) and related tools for mining and development of microsatellites in plants.

Next Generation Sequence Analysis and Computational Genomics Using Graphical Pipeline Workflows

PubMed Central

Torri, Federica; Dinov, Ivo D.; Zamanyan, Alen; Hobel, Sam; Genco, Alex; Petrosyan, Petros; Clark, Andrew P.; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Knowles, James A.; Ames, Joseph; Kesselman, Carl; Toga, Arthur W.; Potkin, Steven G.; Vawter, Marquis P.; Macciardi, Fabio

2012-01-01

Whole-genome and exome sequencing have already proven to be essential and powerful methods to identify genes responsible for simple Mendelian inherited disorders. These methods can be applied to complex disorders as well, and have been adopted as one of the current mainstream approaches in population genetics. These achievements have been made possible by next generation sequencing (NGS) technologies, which require substantial bioinformatics resources to analyze the dense and complex sequence data. The huge analytical burden of data from genome sequencing might be seen as a bottleneck slowing the publication of NGS papers at this time, especially in psychiatric genetics. We review the existing methods for processing NGS data, to place into context the rationale for the design of a computational resource. We describe our method, the Graphical Pipeline for Computational Genomics (GPCG), to perform the computational steps required to analyze NGS data. The GPCG implements flexible workflows for basic sequence alignment, sequence data quality control, single nucleotide polymorphism analysis, copy number variant identification, annotation, and visualization of results. These workflows cover all the analytical steps required for NGS data, from processing the raw reads to variant calling and annotation. The current version of the pipeline is freely available at http://pipeline.loni.ucla.edu. These applications of NGS analysis may gain clinical utility in the near future (e.g., identifying miRNA signatures in diseases) when the bioinformatics approach is made feasible. Taken together, the annotation tools and strategies that have been developed to retrieve information and test hypotheses about the functional role of variants present in the human genome will help to pinpoint the genetic risk factors for psychiatric disorders. PMID:23139896

A Systematic Bayesian Integration of Epidemiological and Genetic Data

PubMed Central

Lau, Max S. Y.; Marion, Glenn; Streftaris, George; Gibson, Gavin

2015-01-01

Genetic sequence data on pathogens have great potential to inform inference of their transmission dynamics ultimately leading to better disease control. Where genetic change and disease transmission occur on comparable timescales additional information can be inferred via the joint analysis of such genetic sequence data and epidemiological observations based on clinical symptoms and diagnostic tests. Although recently introduced approaches represent substantial progress, for computational reasons they approximate genuine joint inference of disease dynamics and genetic change in the pathogen population, capturing partially the joint epidemiological-evolutionary dynamics. Improved methods are needed to fully integrate such genetic data with epidemiological observations, for achieving a more robust inference of the transmission tree and other key epidemiological parameters such as latent periods. Here, building on current literature, a novel Bayesian framework is proposed that infers simultaneously and explicitly the transmission tree and unobserved transmitted pathogen sequences. Our framework facilitates the use of realistic likelihood functions and enables systematic and genuine joint inference of the epidemiological-evolutionary process from partially observed outbreaks. Using simulated data it is shown that this approach is able to infer accurately joint epidemiological-evolutionary dynamics, even when pathogen sequences and epidemiological data are incomplete, and when sequences are available for only a fraction of exposures. These results also characterise and quantify the value of incomplete and partial sequence data, which has important implications for sampling design, and demonstrate the abilities of the introduced method to identify multiple clusters within an outbreak. The framework is used to analyse an outbreak of foot-and-mouth disease in the UK, enhancing current understanding of its transmission dynamics and evolutionary process. PMID:26599399

SwiSpot: modeling riboswitches by spotting out switching sequences.

PubMed

Barsacchi, Marco; Novoa, Eva Maria; Kellis, Manolis; Bechini, Alessio

2016-11-01

Riboswitches are cis-regulatory elements in mRNA, mostly found in Bacteria, which exhibit two main secondary structure conformations. Although one of them prevents the gene from being expressed, the other conformation allows its expression, and this switching process is typically driven by the presence of a specific ligand. Although there are a handful of known riboswitches, our knowledge in this field has been greatly limited due to our inability to identify their alternate structures from their sequences. Indeed, current methods are not able to predict the presence of the two functionally distinct conformations just from the knowledge of the plain RNA nucleotide sequence. Whether this would be possible, for which cases, and what prediction accuracy can be achieved, are currently open questions. Here we show that the two alternate secondary structures of riboswitches can be accurately predicted once the 'switching sequence' of the riboswitch has been properly identified. The proposed SwiSpot approach is capable of identifying the switching sequence inside a putative, complete riboswitch sequence, on the basis of pairing behaviors, which are evaluated on proper sets of configurations. Moreover, it is able to model the switching behavior of riboswitches whose generated ensemble covers both alternate configurations. Beyond structural predictions, the approach can also be paired to homology-based riboswitch searches. SwiSpot software, along with the reference dataset files, is available at: http://www.iet.unipi.it/a.bechini/swispot/Supplementary information: Supplementary data are available at Bioinformatics online. a.bechini@ing.unipi.it. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Window Into Clinical Next-Generation Sequencing-Based Oncology Testing Practices.

PubMed

Nagarajan, Rakesh; Bartley, Angela N; Bridge, Julia A; Jennings, Lawrence J; Kamel-Reid, Suzanne; Kim, Annette; Lazar, Alexander J; Lindeman, Neal I; Moncur, Joel; Rai, Alex J; Routbort, Mark J; Vasalos, Patricia; Merker, Jason D

2017-12-01

- Detection of acquired variants in cancer is a paradigm of precision medicine, yet little has been reported about clinical laboratory practices across a broad range of laboratories. - To use College of American Pathologists proficiency testing survey results to report on the results from surveys on next-generation sequencing-based oncology testing practices. - College of American Pathologists proficiency testing survey results from more than 250 laboratories currently performing molecular oncology testing were used to determine laboratory trends in next-generation sequencing-based oncology testing. - These presented data provide key information about the number of laboratories that currently offer or are planning to offer next-generation sequencing-based oncology testing. Furthermore, we present data from 60 laboratories performing next-generation sequencing-based oncology testing regarding specimen requirements and assay characteristics. The findings indicate that most laboratories are performing tumor-only targeted sequencing to detect single-nucleotide variants and small insertions and deletions, using desktop sequencers and predesigned commercial kits. Despite these trends, a diversity of approaches to testing exists. - This information should be useful to further inform a variety of topics, including national discussions involving clinical laboratory quality systems, regulation and oversight of next-generation sequencing-based oncology testing, and precision oncology efforts in a data-driven manner.

A Pictorial Approach to Lenz's Law

NASA Astrophysics Data System (ADS)

Duffy, Andrew

2018-04-01

This paper describes a pictorial approach to Lenz's law that involves following four steps and drawing three pictures to determine the direction of the current induced by a changing magnetic flux. Lenz's law accompanies Faraday's law, stating that, for a closed conducting loop, the induced emf (electromotive force) created by a changing magnetic flux sets up a current in the loop that tends to oppose the change in flux. Students are often confused by this, but drawing a sequence of three pictures can make it clearer to students how Lenz's law is applied.

Maximizing ecological and evolutionary insight in bisulfite sequencing data sets

PubMed Central

Lea, Amanda J.; Vilgalys, Tauras P.; Durst, Paul A.P.; Tung, Jenny

2017-01-01

Preface Genome-scale bisulfite sequencing approaches have opened the door to ecological and evolutionary studies of DNA methylation in many organisms. These approaches can be powerful. However, they introduce new methodological and statistical considerations, some of which are particularly relevant to non-model systems. Here, we highlight how these considerations influence a study’s power to link methylation variation with a predictor variable of interest. Relative to current practice, we argue that sample sizes will need to increase to provide robust insights. We also provide recommendations for overcoming common challenges and an R Shiny app to aid in study design. PMID:29046582

A Simulation Based Approach for Contingency Planning for Aircraft Turnaround Operation System Activities in Airline Hubs

NASA Technical Reports Server (NTRS)

Adeleye, Sanya; Chung, Christopher

2006-01-01

Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.

A gradient-boosting approach for filtering de novo mutations in parent-offspring trios.

PubMed

Liu, Yongzhuang; Li, Bingshan; Tan, Renjie; Zhu, Xiaolin; Wang, Yadong

2014-07-01

Whole-genome and -exome sequencing on parent-offspring trios is a powerful approach to identifying disease-associated genes by detecting de novo mutations in patients. Accurate detection of de novo mutations from sequencing data is a critical step in trio-based genetic studies. Existing bioinformatic approaches usually yield high error rates due to sequencing artifacts and alignment issues, which may either miss true de novo mutations or call too many false ones, making downstream validation and analysis difficult. In particular, current approaches have much worse specificity than sensitivity, and developing effective filters to discriminate genuine from spurious de novo mutations remains an unsolved challenge. In this article, we curated 59 sequence features in whole genome and exome alignment context which are considered to be relevant to discriminating true de novo mutations from artifacts, and then employed a machine-learning approach to classify candidates as true or false de novo mutations. Specifically, we built a classifier, named De Novo Mutation Filter (DNMFilter), using gradient boosting as the classification algorithm. We built the training set using experimentally validated true and false de novo mutations as well as collected false de novo mutations from an in-house large-scale exome-sequencing project. We evaluated DNMFilter's theoretical performance and investigated relative importance of different sequence features on the classification accuracy. Finally, we applied DNMFilter on our in-house whole exome trios and one CEU trio from the 1000 Genomes Project and found that DNMFilter could be coupled with commonly used de novo mutation detection approaches as an effective filtering approach to significantly reduce false discovery rate without sacrificing sensitivity. The software DNMFilter implemented using a combination of Java and R is freely available from the website at http://humangenome.duke.edu/software. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A user's guide to quantitative and comparative analysis of metagenomic datasets.

PubMed

Luo, Chengwei; Rodriguez-R, Luis M; Konstantinidis, Konstantinos T

2013-01-01

Metagenomics has revolutionized microbiological studies during the past decade and provided new insights into the diversity, dynamics, and metabolic potential of natural microbial communities. However, metagenomics still represents a field in development, and standardized tools and approaches to handle and compare metagenomes have not been established yet. An important reason accounting for the latter is the continuous changes in the type of sequencing data available, for example, long versus short sequencing reads. Here, we provide a guide to bioinformatic pipelines developed to accomplish the following tasks, focusing primarily on those developed by our team: (i) assemble a metagenomic dataset; (ii) determine the level of sequence coverage obtained and the amount of sequencing required to obtain complete coverage; (iii) identify the taxonomic affiliation of a metagenomic read or assembled contig; and (iv) determine differentially abundant genes, pathways, and species between different datasets. Most of these pipelines do not depend on the type of sequences available or can be easily adjusted to fit different types of sequences, and are freely available (for instance, through our lab Web site: http://www.enve-omics.gatech.edu/). The limitations of current approaches, as well as the computational aspects that can be further improved, will also be briefly discussed. The work presented here provides practical guidelines on how to perform metagenomic analysis of microbial communities characterized by varied levels of diversity and establishes approaches to handle the resulting data, independent of the sequencing platform employed. © 2013 Elsevier Inc. All rights reserved.

Current strategies for mobilome research

PubMed Central

Jørgensen, Tue S.; Kiil, Anne S.; Hansen, Martin A.; Sørensen, Søren J.; Hansen, Lars H.

2015-01-01

Mobile genetic elements (MGEs) are pivotal for bacterial evolution and adaptation, allowing shuffling of genes even between distantly related bacterial species. The study of these elements is biologically interesting as the mode of genetic propagation is kaleidoscopic and important, as MGEs are the main vehicles of the increasing bacterial antibiotic resistance that causes thousands of human deaths each year. The study of MGEs has previously focused on plasmids from individual isolates, but the revolution in sequencing technology has allowed the study of mobile genomic elements of entire communities using metagenomic approaches. The problem in using metagenomic sequencing for the study of MGEs is that plasmids and other mobile elements only comprise a small fraction of the total genetic content that are difficult to separate from chromosomal DNA based on sequence alone. The distinction between plasmid and chromosome is important as the mobility and regulation of genes largely depend on their genetic context. Several different approaches have been proposed that specifically enrich plasmid DNA from community samples. Here, we review recent approaches used to study entire plasmid pools from complex environments, and point out possible future developments for and pitfalls of these approaches. Further, we discuss the use of the PacBio long-read sequencing technology for MGE discovery. PMID:25657641

Antimicrobial activity predictors benchmarking analysis using shuffled and designed synthetic peptides.

PubMed

Porto, William F; Pires, Állan S; Franco, Octavio L

2017-08-07

The antimicrobial activity prediction tools aim to help the novel antimicrobial peptides (AMP) sequences discovery, utilizing machine learning methods. Such approaches have gained increasing importance in the generation of novel synthetic peptides by means of rational design techniques. This study focused on predictive ability of such approaches to determine the antimicrobial sequence activities, which were previously characterized at the protein level by in vitro studies. Using four web servers and one standalone software, we evaluated 78 sequences generated by the so-called linguistic model, being 40 designed and 38 shuffled sequences, with ∼60 and ∼25% of identity to AMPs, respectively. The ab initio molecular modelling of such sequences indicated that the structure does not affect the predictions, as both sets present similar structures. Overall, the systems failed on predicting shuffled versions of designed peptides, as they are identical in AMPs composition, which implies in accuracies below 30%. The prediction accuracy is negatively affected by the low specificity of all systems here evaluated, as they, on the other hand, reached 100% of sensitivity. Our results suggest that complementary approaches with high specificity, not necessarily high accuracy, should be developed to be used together with the current systems, overcoming their limitations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and expansion of high-quality control region databases to improve forensic mtDNA evidence interpretation.

PubMed

Irwin, Jodi A; Saunier, Jessica L; Strouss, Katharine M; Sturk, Kimberly A; Diegoli, Toni M; Just, Rebecca S; Coble, Michael D; Parson, Walther; Parsons, Thomas J

2007-06-01

In an effort to increase the quantity, breadth and availability of mtDNA databases suitable for forensic comparisons, we have developed a high-throughput process to generate approximately 5000 control region sequences per year from regional US populations, global populations from which the current US population is derived and global populations currently under-represented in available forensic databases. The system utilizes robotic instrumentation for all laboratory steps from pre-extraction through sequence detection, and a rigorous eight-step, multi-laboratory data review process with entirely electronic data transfer. Over the past 3 years, nearly 10,000 control region sequences have been generated using this approach. These data are being made publicly available and should further address the need for consistent, high-quality mtDNA databases for forensic testing.

Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism

PubMed Central

Jeanne, Nicolas; Saliou, Adrien; Carcenac, Romain; Lefebvre, Caroline; Dubois, Martine; Cazabat, Michelle; Nicot, Florence; Loiseau, Claire; Raymond, Stéphanie; Izopet, Jacques; Delobel, Pierre

2015-01-01

HIV-1 coreceptor usage must be accurately determined before starting CCR5 antagonist-based treatment as the presence of undetected minor CXCR4-using variants can cause subsequent virological failure. Ultra-deep pyrosequencing of HIV-1 V3 env allows to detect low levels of CXCR4-using variants that current genotypic approaches miss. However, the computation of the mass of sequence data and the need to identify true minor variants while excluding artifactual sequences generated during amplification and ultra-deep pyrosequencing is rate-limiting. Arbitrary fixed cut-offs below which minor variants are discarded are currently used but the errors generated during ultra-deep pyrosequencing are sequence-dependant rather than random. We have developed an automated processing of HIV-1 V3 env ultra-deep pyrosequencing data that uses biological filters to discard artifactual or non-functional V3 sequences followed by statistical filters to determine position-specific sensitivity thresholds, rather than arbitrary fixed cut-offs. It allows to retain authentic sequences with point mutations at V3 positions of interest and discard artifactual ones with accurate sensitivity thresholds. PMID:26585833

Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism.

PubMed

Jeanne, Nicolas; Saliou, Adrien; Carcenac, Romain; Lefebvre, Caroline; Dubois, Martine; Cazabat, Michelle; Nicot, Florence; Loiseau, Claire; Raymond, Stéphanie; Izopet, Jacques; Delobel, Pierre

2015-11-20

HIV-1 coreceptor usage must be accurately determined before starting CCR5 antagonist-based treatment as the presence of undetected minor CXCR4-using variants can cause subsequent virological failure. Ultra-deep pyrosequencing of HIV-1 V3 env allows to detect low levels of CXCR4-using variants that current genotypic approaches miss. However, the computation of the mass of sequence data and the need to identify true minor variants while excluding artifactual sequences generated during amplification and ultra-deep pyrosequencing is rate-limiting. Arbitrary fixed cut-offs below which minor variants are discarded are currently used but the errors generated during ultra-deep pyrosequencing are sequence-dependant rather than random. We have developed an automated processing of HIV-1 V3 env ultra-deep pyrosequencing data that uses biological filters to discard artifactual or non-functional V3 sequences followed by statistical filters to determine position-specific sensitivity thresholds, rather than arbitrary fixed cut-offs. It allows to retain authentic sequences with point mutations at V3 positions of interest and discard artifactual ones with accurate sensitivity thresholds.

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

PubMed Central

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

2011-01-01

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

Extensive characterization of Tupaia belangeri neuropeptidome using an integrated mass spectrometric approach.

PubMed

Petruzziello, Filomena; Fouillen, Laetitia; Wadensten, Henrik; Kretz, Robert; Andren, Per E; Rainer, Gregor; Zhang, Xiaozhe

2012-02-03

Neuropeptidomics is used to characterize endogenous peptides in the brain of tree shrews (Tupaia belangeri). Tree shrews are small animals similar to rodents in size but close relatives of primates, and are excellent models for brain research. Currently, tree shrews have no complete proteome information available on which direct database search can be allowed for neuropeptide identification. To increase the capability in the identification of neuropeptides in tree shrews, we developed an integrated mass spectrometry (MS)-based approach that combines methods including data-dependent, directed, and targeted liquid chromatography (LC)-Fourier transform (FT)-tandem MS (MS/MS) analysis, database construction, de novo sequencing, precursor protein search, and homology analysis. Using this integrated approach, we identified 107 endogenous peptides that have sequences identical or similar to those from other mammalian species. High accuracy MS and tandem MS information, with BLAST analysis and chromatographic characteristics were used to confirm the sequences of all the identified peptides. Interestingly, further sequence homology analysis demonstrated that tree shrew peptides have a significantly higher degree of homology to equivalent sequences in humans than those in mice or rats, consistent with the close phylogenetic relationship between tree shrews and primates. Our results provide the first extensive characterization of the peptidome in tree shrews, which now permits characterization of their function in nervous and endocrine system. As the approach developed fully used the conservative properties of neuropeptides in evolution and the advantage of high accuracy MS, it can be portable for identification of neuropeptides in other species for which the fully sequenced genomes or proteomes are not available.

A review of bioinformatic methods for forensic DNA analyses.

PubMed

Liu, Yao-Yuan; Harbison, SallyAnn

2018-03-01

Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.

Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics.

PubMed

Munchel, Sarah; Hoang, Yen; Zhao, Yue; Cottrell, Joseph; Klotzle, Brandy; Godwin, Andrew K; Koestler, Devin; Beyerlein, Peter; Fan, Jian-Bing; Bibikova, Marina; Chien, Jeremy

2015-09-22

Current genomic studies are limited by the poor availability of fresh-frozen tissue samples. Although formalin-fixed diagnostic samples are in abundance, they are seldom used in current genomic studies because of the concern of formalin-fixation artifacts. Better characterization of these artifacts will allow the use of archived clinical specimens in translational and clinical research studies. To provide a systematic analysis of formalin-fixation artifacts on Illumina sequencing, we generated 26 DNA sequencing data sets from 13 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tissue samples. The results indicate high rate of concordant calls between matched FF/FFPE pairs at reference and variant positions in three commonly used sequencing approaches (whole genome, whole exome, and targeted exon sequencing). Global mismatch rates and C · G > T · A substitutions were comparable between matched FF/FFPE samples, and discordant rates were low (<0.26%) in all samples. Finally, low-pass whole genome sequencing produces similar pattern of copy number alterations between FF/FFPE pairs. The results from our studies suggest the potential use of diagnostic FFPE samples for cancer genomic studies to characterize and catalog variations in cancer genomes.

Next-generation sequencing in schizophrenia and other neuropsychiatric disorders.

PubMed

Schreiber, Matthew; Dorschner, Michael; Tsuang, Debby

2013-10-01

Schizophrenia is a debilitating lifelong illness that lacks a cure and poses a worldwide public health burden. The disease is characterized by a heterogeneous clinical and genetic presentation that complicates research efforts to identify causative genetic variations. This review examines the potential of current findings in schizophrenia and in other related neuropsychiatric disorders for application in next-generation technologies, particularly whole-exome sequencing (WES) and whole-genome sequencing (WGS). These approaches may lead to the discovery of underlying genetic factors for schizophrenia and may thereby identify and target novel therapeutic targets for this devastating disorder. © 2013 Wiley Periodicals, Inc.

Sequencing the Connectome

PubMed Central

Zador, Anthony M.; Dubnau, Joshua; Oyibo, Hassana K.; Zhan, Huiqing; Cao, Gang; Peikon, Ian D.

2012-01-01

Connectivity determines the function of neural circuits. Historically, circuit mapping has usually been viewed as a problem of microscopy, but no current method can achieve high-throughput mapping of entire circuits with single neuron precision. Here we describe a novel approach to determining connectivity. We propose BOINC (“barcoding of individual neuronal connections”), a method for converting the problem of connectivity into a form that can be read out by high-throughput DNA sequencing. The appeal of using sequencing is that its scale—sequencing billions of nucleotides per day is now routine—is a natural match to the complexity of neural circuits. An inexpensive high-throughput technique for establishing circuit connectivity at single neuron resolution could transform neuroscience research. PMID:23109909

High-Resolution Sequence-Function Mapping of Full-Length Proteins

PubMed Central

Kowalsky, Caitlin A.; Klesmith, Justin R.; Stapleton, James A.; Kelly, Vince; Reichkitzer, Nolan; Whitehead, Timothy A.

2015-01-01

Comprehensive sequence-function mapping involves detailing the fitness contribution of every possible single mutation to a gene by comparing the abundance of each library variant before and after selection for the phenotype of interest. Deep sequencing of library DNA allows frequency reconstruction for tens of thousands of variants in a single experiment, yet short read lengths of current sequencers makes it challenging to probe genes encoding full-length proteins. Here we extend the scope of sequence-function maps to entire protein sequences with a modular, universal sequence tiling method. We demonstrate the approach with both growth-based selections and FACS screening, offer parameters and best practices that simplify design of experiments, and present analytical solutions to normalize data across independent selections. Using this protocol, sequence-function maps covering full sequences can be obtained in four to six weeks. Best practices introduced in this manuscript are fully compatible with, and complementary to, other recently published sequence-function mapping protocols. PMID:25790064

Genetic mutations in human rectal cancers detected by targeted sequencing.

PubMed

Bai, Jun; Gao, Jinglong; Mao, Zhijun; Wang, Jianhua; Li, Jianhui; Li, Wensheng; Lei, Yu; Li, Shuaishuai; Wu, Zhuo; Tang, Chuanning; Jones, Lindsey; Ye, Hua; Lou, Feng; Liu, Zhiyuan; Dong, Zhishou; Guo, Baishuai; Huang, Xue F; Chen, Si-Yi; Zhang, Enke

2015-10-01

Colorectal cancer (CRC) is widespread with significant mortality. Both inherited and sporadic mutations in various signaling pathways influence the development and progression of the cancer. Identifying genetic mutations in CRC is important for optimal patient treatment and many approaches currently exist to uncover these mutations, including next-generation sequencing (NGS) and commercially available kits. In the present study, we used a semiconductor-based targeted DNA-sequencing approach to sequence and identify genetic mutations in 91 human rectal cancer samples. Analysis revealed frequent mutations in KRAS (58.2%), TP53 (28.6%), APC (16.5%), FBXW7 (9.9%) and PIK3CA (9.9%), and additional mutations in BRAF, CTNNB1, ERBB2 and SMAD4 were also detected at lesser frequencies. Thirty-eight samples (41.8%) also contained two or more mutations, with common combination mutations occurring between KRAS and TP53 (42.1%), and KRAS and APC (31.6%). DNA sequencing for individual cancers is of clinical importance for targeted drug therapy and the advantages of such targeted gene sequencing over other NGS platforms or commercially available kits in sensitivity, cost and time effectiveness may aid clinicians in treating CRC patients in the near future.

AFRESh: an adaptive framework for compression of reads and assembled sequences with random access functionality.

PubMed

Paridaens, Tom; Van Wallendael, Glenn; De Neve, Wesley; Lambert, Peter

2017-05-15

The past decade has seen the introduction of new technologies that lowered the cost of genomic sequencing increasingly. We can even observe that the cost of sequencing is dropping significantly faster than the cost of storage and transmission. The latter motivates a need for continuous improvements in the area of genomic data compression, not only at the level of effectiveness (compression rate), but also at the level of functionality (e.g. random access), configurability (effectiveness versus complexity, coding tool set …) and versatility (support for both sequenced reads and assembled sequences). In that regard, we can point out that current approaches mostly do not support random access, requiring full files to be transmitted, and that current approaches are restricted to either read or sequence compression. We propose AFRESh, an adaptive framework for no-reference compression of genomic data with random access functionality, targeting the effective representation of the raw genomic symbol streams of both reads and assembled sequences. AFRESh makes use of a configurable set of prediction and encoding tools, extended by a Context-Adaptive Binary Arithmetic Coding scheme (CABAC), to compress raw genetic codes. To the best of our knowledge, our paper is the first to describe an effective implementation CABAC outside of its' original application. By applying CABAC, the compression effectiveness improves by up to 19% for assembled sequences and up to 62% for reads. By applying AFRESh to the genomic symbols of the MPEG genomic compression test set for reads, a compression gain is achieved of up to 51% compared to SCALCE, 42% compared to LFQC and 44% compared to ORCOM. When comparing to generic compression approaches, a compression gain is achieved of up to 41% compared to GNU Gzip and 22% compared to 7-Zip at the Ultra setting. Additionaly, when compressing assembled sequences of the Human Genome, a compression gain is achieved up to 34% compared to GNU Gzip and 16% compared to 7-Zip at the Ultra setting. A Windows executable version can be downloaded at https://github.com/tparidae/AFresh . tom.paridaens@ugent.be. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Virus Identification in Unknown Tropical Febrile Illness Cases Using Deep Sequencing

PubMed Central

Balmaseda, Angel; Harris, Eva; DeRisi, Joseph L.

2012-01-01

Dengue virus is an emerging infectious agent that infects an estimated 50–100 million people annually worldwide, yet current diagnostic practices cannot detect an etiologic pathogen in ∼40% of dengue-like illnesses. Metagenomic approaches to pathogen detection, such as viral microarrays and deep sequencing, are promising tools to address emerging and non-diagnosable disease challenges. In this study, we used the Virochip microarray and deep sequencing to characterize the spectrum of viruses present in human sera from 123 Nicaraguan patients presenting with dengue-like symptoms but testing negative for dengue virus. We utilized a barcoding strategy to simultaneously deep sequence multiple serum specimens, generating on average over 1 million reads per sample. We then implemented a stepwise bioinformatic filtering pipeline to remove the majority of human and low-quality sequences to improve the speed and accuracy of subsequent unbiased database searches. By deep sequencing, we were able to detect virus sequence in 37% (45/123) of previously negative cases. These included 13 cases with Human Herpesvirus 6 sequences. Other samples contained sequences with similarity to sequences from viruses in the Herpesviridae, Flaviviridae, Circoviridae, Anelloviridae, Asfarviridae, and Parvoviridae families. In some cases, the putative viral sequences were virtually identical to known viruses, and in others they diverged, suggesting that they may derive from novel viruses. These results demonstrate the utility of unbiased metagenomic approaches in the detection of known and divergent viruses in the study of tropical febrile illness. PMID:22347512

Next-generation sequencing library construction on a surface.

PubMed

Feng, Kuan; Costa, Justin; Edwards, Jeremy S

2018-05-30

Next-generation sequencing (NGS) has revolutionized almost all fields of biology, agriculture and medicine, and is widely utilized to analyse genetic variation. Over the past decade, the NGS pipeline has been steadily improved, and the entire process is currently relatively straightforward. However, NGS instrumentation still requires upfront library preparation, which can be a laborious process, requiring significant hands-on time. Herein, we present a simple but robust approach to streamline library preparation by utilizing surface bound transposases to construct DNA libraries directly on a flowcell surface. The surface bound transposases directly fragment genomic DNA while simultaneously attaching the library molecules to the flowcell. We sequenced and analysed a Drosophila genome library generated by this surface tagmentation approach, and we showed that our surface bound library quality was comparable to the quality of the library from a commercial kit. In addition to the time and cost savings, our approach does not require PCR amplification of the library, which eliminates potential problems associated with PCR duplicates. We described the first study to construct libraries directly on a flowcell. We believe our technique could be incorporated into the existing Illumina sequencing pipeline to simplify the workflow, reduce costs, and improve data quality.

Rational Protein Engineering Guided by Deep Mutational Scanning

PubMed Central

Shin, HyeonSeok; Cho, Byung-Kwan

2015-01-01

Sequence–function relationship in a protein is commonly determined by the three-dimensional protein structure followed by various biochemical experiments. However, with the explosive increase in the number of genome sequences, facilitated by recent advances in sequencing technology, the gap between protein sequences available and three-dimensional structures is rapidly widening. A recently developed method termed deep mutational scanning explores the functional phenotype of thousands of mutants via massive sequencing. Coupled with a highly efficient screening system, this approach assesses the phenotypic changes made by the substitution of each amino acid sequence that constitutes a protein. Such an informational resource provides the functional role of each amino acid sequence, thereby providing sufficient rationale for selecting target residues for protein engineering. Here, we discuss the current applications of deep mutational scanning and consider experimental design. PMID:26404267

Molecular ecology studies of species radiations: current research gaps, opportunities and challenges.

PubMed

de la Harpe, Marylaure; Paris, Margot; Karger, Dirk N; Rolland, Jonathan; Kessler, Michael; Salamin, Nicolas; Lexer, Christian

2017-05-01

Understanding the drivers and limits of species radiations is a crucial goal of evolutionary genetics and molecular ecology, yet research on this topic has been hampered by the notorious difficulty of connecting micro- and macroevolutionary approaches to studying the drivers of diversification. To chart the current research gaps, opportunities and challenges of molecular ecology approaches to studying radiations, we examine the literature in the journal Molecular Ecology and revisit recent high-profile examples of evolutionary genomic research on radiations. We find that available studies of radiations are highly unevenly distributed among taxa, with many ecologically important and species-rich organismal groups remaining severely understudied, including arthropods, plants and fungi. Most studies employed molecular methods suitable over either short or long evolutionary time scales, such as microsatellites or restriction site-associated DNA sequencing (RAD-seq) in the former case and conventional amplicon sequencing of organellar DNA in the latter. The potential of molecular ecology studies to address and resolve patterns and processes around the species level in radiating groups of taxa is currently limited primarily by sample size and a dearth of information on radiating nuclear genomes as opposed to organellar ones. Based on our literature survey and personal experience, we suggest possible ways forward in the coming years. We touch on the potential and current limitations of whole-genome sequencing (WGS) in studies of radiations. We suggest that WGS and targeted ('capture') resequencing emerge as the methods of choice for scaling up the sampling of populations, species and genomes, including currently understudied organismal groups and the genes or regulatory elements expected to matter most to species radiations. © 2017 John Wiley & Sons Ltd.

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

Acceleration of short and long DNA read mapping without loss of accuracy using suffix array.

PubMed

Tárraga, Joaquín; Arnau, Vicente; Martínez, Héctor; Moreno, Raul; Cazorla, Diego; Salavert-Torres, José; Blanquer-Espert, Ignacio; Dopazo, Joaquín; Medina, Ignacio

2014-12-01

HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20× for long reads) and more sensitive (over 98% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies. https://github.com/opencb/hpg-aligner. © The Author 2014. Published by Oxford University Press.

Aspergillus and Penicillium identification using DNA sequences: Barcode or MLST?

USDA-ARS?s Scientific Manuscript database

Current methods in DNA technology can detect single nucleotide polymorphisms with measurable accuracy using several different approaches appropriate for different uses. If there are even single nucleotide differences that are invariant markers of the species, we can accomplish identification through...

The MICRO-BOSS scheduling system: Current status and future efforts

NASA Technical Reports Server (NTRS)

Sadeh, Norman M.

1992-01-01

In this paper, a micro-opportunistic approach to factory scheduling was described that closely monitors the evolution of bottlenecks during the construction of the schedule and continuously redirects search towards the bottleneck that appears to be most critical. This approach differs from earlier opportunistic approaches, as it does not require scheduling large resource subproblems or large job subproblems before revising the current scheduling strategy. This micro-opportunistic approach was implemented in the context of the MICRO-BOSS factory scheduling system. A study comparing MICRO-BOSS against a macro-opportunistic scheduler suggests that the additional flexibility of the micro-opportunistic approach to scheduling generally yields important reductions in both tardiness and inventory. Current research efforts include: adaptation of MICRO-BOSS to deal with sequence-dependent setups and development of micro-opportunistic reactive scheduling techniques that will enable the system to patch the schedule in the presence of contingencies such as machine breakdowns, raw materials arriving late, job cancellations, etc.

Real-time image sequence segmentation using curve evolution

NASA Astrophysics Data System (ADS)

Zhang, Jun; Liu, Weisong

2001-04-01

In this paper, we describe a novel approach to image sequence segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve evolution to extract whole objects. Our algorithm is implemented on a standard PC running the Windows operating system with video capture from a USB camera that is a standard Windows video capture device. Using the Windows standard video I/O functionalities, our segmentation software is highly portable and easy to maintain and upgrade. In its current implementation on a Pentium 400, the system can perform segmentation at 5 frames/sec with a frame resolution of 160 by 120.

Separation of endogenous viral elements from infectious Penaeus stylirostris densovirus using recombinase polymerase amplification.

PubMed

Jaroenram, Wansadaj; Owens, Leigh

2014-01-01

Non-infectious Penaeus stylirostris densovirus (PstDV)-related sequences in the shrimp genome cause false positive results with current PCR protocols. Here, we examined and mapped PstDV insertion profile in the genome of Australian Penaeus monodon. A DNA sequence which is likely to represent infectious PstDV was also identified and used as a target sequence for recombinase polymerase amplification (RPA)-based approach, developed for specifically detecting PstDV. The RPA protocol at 37 °C for 30 min showed no cross-reaction with other shrimp viruses, and was 10 times more sensitive than the 309F/R PCR protocol currently recommended by the World Organization for Animal Health (OIE) for PstDV diagnosis. These features, together with the simplicity of the protocol, requiring only a heating block for the reaction, offer opportunities for rapid and efficient detection of PstDV. Copyright © 2014 Elsevier Ltd. All rights reserved.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Independent assessment and improvement of wheat genome sequence assemblies using Fosill jumping libraries.

PubMed

Lu, Fu-Hao; McKenzie, Neil; Kettleborough, George; Heavens, Darren; Clark, Matthew D; Bevan, Michael W

2018-05-01

The accurate sequencing and assembly of very large, often polyploid, genomes remains a challenging task, limiting long-range sequence information and phased sequence variation for applications such as plant breeding. The 15-Gb hexaploid bread wheat (Triticum aestivum) genome has been particularly challenging to sequence, and several different approaches have recently generated long-range assemblies. Mapping and understanding the types of assembly errors are important for optimising future sequencing and assembly approaches and for comparative genomics. Here we use a Fosill 38-kb jumping library to assess medium and longer-range order of different publicly available wheat genome assemblies. Modifications to the Fosill protocol generated longer Illumina sequences and enabled comprehensive genome coverage. Analyses of two independent Bacterial Artificial Chromosome (BAC)-based chromosome-scale assemblies, two independent Illumina whole genome shotgun assemblies, and a hybrid Single Molecule Real Time (SMRT-PacBio) and short read (Illumina) assembly were carried out. We revealed a surprising scale and variety of discrepancies using Fosill mate-pair mapping and validated several of each class. In addition, Fosill mate-pairs were used to scaffold a whole genome Illumina assembly, leading to a 3-fold increase in N50 values. Our analyses, using an independent means to validate different wheat genome assemblies, show that whole genome shotgun assemblies based solely on Illumina sequences are significantly more accurate by all measures compared to BAC-based chromosome-scale assemblies and hybrid SMRT-Illumina approaches. Although current whole genome assemblies are reasonably accurate and useful, additional improvements will be needed to generate complete assemblies of wheat genomes using open-source, computationally efficient, and cost-effective methods.

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

PubMed

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Numerical classification of coding sequences

NASA Technical Reports Server (NTRS)

Collins, D. W.; Liu, C. C.; Jukes, T. H.

1992-01-01

DNA sequences coding for protein may be represented by counts of nucleotides or codons. A complete reading frame may be abbreviated by its base count, e.g. A76C158G121T74, or with the corresponding codon table, e.g. (AAA)0(AAC)1(AAG)9 ... (TTT)0. We propose that these numerical designations be used to augment current methods of sequence annotation. Because base counts and codon tables do not require revision as knowledge of function evolves, they are well-suited to act as cross-references, for example to identify redundant GenBank entries. These descriptors may be compared, in place of DNA sequences, to extract homologous genes from large databases. This approach permits rapid searching with good selectivity.

Bambus 2: scaffolding metagenomes.

PubMed

Koren, Sergey; Treangen, Todd J; Pop, Mihai

2011-11-01

Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources. We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly. Bambus 2 is open source and available from http://amos.sf.net. mpop@umiacs.umd.edu. Supplementary data are available at Bioinformatics online.

Bambus 2: scaffolding metagenomes

PubMed Central

Koren, Sergey; Treangen, Todd J.; Pop, Mihai

2011-01-01

Motivation: Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources. Results: We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly. Availability: Bambus 2 is open source and available from http://amos.sf.net. Contact: mpop@umiacs.umd.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21926123

Skin microbiome: genomics-based insights into the diversity and role of skin microbes

PubMed Central

Kong, Heidi H.

2011-01-01

Recent advances in DNA sequencing methodology have enabled studies of human skin microbes that circumvent difficulties in isolating and characterizing fastidious microbes. Sequence-based approaches have identified greater diversity of cutaneous bacteria than studies using traditional cultivation techniques. However, improved sequencing technologies and analytical methods are needed to study all skin microbes, including bacteria, archaea, fungi, viruses, and mites, and how they interact with each other and their human hosts. This review discusses current skin microbiome research, with a primary focus on bacteria, and the challenges facing investigators striving to understand how skin micro-organisms contribute to health and disease. PMID:21376666

A Systems Approach towards an Intelligent and Self-Controlling Platform for Integrated Continuous Reaction Sequences**

PubMed Central

Ingham, Richard J; Battilocchio, Claudio; Fitzpatrick, Daniel E; Sliwinski, Eric; Hawkins, Joel M; Ley, Steven V

2015-01-01

Performing reactions in flow can offer major advantages over batch methods. However, laboratory flow chemistry processes are currently often limited to single steps or short sequences due to the complexity involved with operating a multi-step process. Using new modular components for downstream processing, coupled with control technologies, more advanced multi-step flow sequences can be realized. These tools are applied to the synthesis of 2-aminoadamantane-2-carboxylic acid. A system comprising three chemistry steps and three workup steps was developed, having sufficient autonomy and self-regulation to be managed by a single operator. PMID:25377747

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

PubMed

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

2018-02-01

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

DLocalMotif: a discriminative approach for discovering local motifs in protein sequences.

PubMed

Mehdi, Ahmed M; Sehgal, Muhammad Shoaib B; Kobe, Bostjan; Bailey, Timothy L; Bodén, Mikael

2013-01-01

Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery. This article introduces the method DLocalMotif that makes use of positional information and negative data for local motif discovery in protein sequences. DLocalMotif combines three scoring functions, measuring degrees of motif over-representation, entropy and spatial confinement, specifically designed to discriminatively exploit the availability of negative data. The method is shown to outperform current methods that use only a subset of these motif characteristics. We apply the method to several biological datasets. The analysis of peroxisomal targeting signals uncovers several novel motifs that occur immediately upstream of the dominant peroxisomal targeting signal-1 signal. The analysis of proline-tyrosine nuclear localization signals uncovers multiple novel motifs that overlap with C2H2 zinc finger domains. We also evaluate the method on classical nuclear localization signals and endoplasmic reticulum retention signals and find that DLocalMotif successfully recovers biologically relevant sequence properties. http://bioinf.scmb.uq.edu.au/dlocalmotif/

Current and future molecular diagnostics for ocular infectious diseases.

PubMed

Doan, Thuy; Pinsky, Benjamin A

2016-11-01

Confirmation of ocular infections can pose great challenges to the clinician. A fundamental limitation is the small amounts of specimen that can be obtained from the eye. Molecular diagnostics can circumvent this limitation and have been shown to be more sensitive than conventional culture. The purpose of this review is to describe new molecular methods and to discuss the applications of next-generation sequencing-based approaches in the diagnosis of ocular infections. Efforts have focused on improving the sensitivity of pathogen detection using molecular methods. This review describes a new molecular target for Toxoplasma gondii-directed polymerase chain reaction assays. Molecular diagnostics for Chlamydia trachomatis and Acanthamoeba species are also discussed. Finally, we describe a hypothesis-free approach, metagenomic deep sequencing, which can detect DNA and RNA pathogens from a single specimen in one test. In some cases, this method can provide the geographic location and timing of the infection. Pathogen-directed PCRs have been powerful tools in the diagnosis of ocular infections for over 20 years. The use of next-generation sequencing-based approaches, when available, will further improve sensitivity of detection with the potential to improve patient care.

DELIMINATE--a fast and efficient method for loss-less compression of genomic sequences: sequence analysis.

PubMed

Mohammed, Monzoorul Haque; Dutta, Anirban; Bose, Tungadri; Chadaram, Sudha; Mande, Sharmila S

2012-10-01

An unprecedented quantity of genome sequence data is currently being generated using next-generation sequencing platforms. This has necessitated the development of novel bioinformatics approaches and algorithms that not only facilitate a meaningful analysis of these data but also aid in efficient compression, storage, retrieval and transmission of huge volumes of the generated data. We present a novel compression algorithm (DELIMINATE) that can rapidly compress genomic sequence data in a loss-less fashion. Validation results indicate relatively higher compression efficiency of DELIMINATE when compared with popular general purpose compression algorithms, namely, gzip, bzip2 and lzma. Linux, Windows and Mac implementations (both 32 and 64-bit) of DELIMINATE are freely available for download at: http://metagenomics.atc.tcs.com/compression/DELIMINATE. sharmila@atc.tcs.com Supplementary data are available at Bioinformatics online.

IMNGS: A comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies.

PubMed

Lagkouvardos, Ilias; Joseph, Divya; Kapfhammer, Martin; Giritli, Sabahattin; Horn, Matthias; Haller, Dirk; Clavel, Thomas

2016-09-23

The SRA (Sequence Read Archive) serves as primary depository for massive amounts of Next Generation Sequencing data, and currently host over 100,000 16S rRNA gene amplicon-based microbial profiles from various host habitats and environments. This number is increasing rapidly and there is a dire need for approaches to utilize this pool of knowledge. Here we created IMNGS (Integrated Microbial Next Generation Sequencing), an innovative platform that uniformly and systematically screens for and processes all prokaryotic 16S rRNA gene amplicon datasets available in SRA and uses them to build sample-specific sequence databases and OTU-based profiles. Via a web interface, this integrative sequence resource can easily be queried by users. We show examples of how the approach allows testing the ecological importance of specific microorganisms in different hosts or ecosystems, and performing targeted diversity studies for selected taxonomic groups. The platform also offers a complete workflow for de novo analysis of users' own raw 16S rRNA gene amplicon datasets for the sake of comparison with existing data. IMNGS can be accessed at www.imngs.org.

Competitive Genomic Screens of Barcoded Yeast Libraries

PubMed Central

Urbanus, Malene; Proctor, Michael; Heisler, Lawrence E.; Giaever, Guri; Nislow, Corey

2011-01-01

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment. PMID:21860376

Characterization and analysis of a transcriptome from the boreal spider crab Hyas araneus.

PubMed

Harms, Lars; Frickenhaus, Stephan; Schiffer, Melanie; Mark, Felix C; Storch, Daniela; Pörtner, Hans-Otto; Held, Christoph; Lucassen, Magnus

2013-12-01

Research investigating the genetic basis of physiological responses has significantly broadened our understanding of the mechanisms underlying organismic response to environmental change. However, genomic data are currently available for few taxa only, thus excluding physiological model species from this approach. In this study we report the transcriptome of the model organism Hyas araneus from Spitsbergen (Arctic). We generated 20,479 transcripts, using the 454 GS FLX sequencing technology in combination with an Illumina HiSeq sequencing approach. Annotation by Blastx revealed 7159 blast hits in the NCBI non-redundant protein database. The comparison between the spider crab H. araneus transcriptome and EST libraries of the European lobster Homarus americanus and the porcelain crab Petrolisthes cinctipes yielded 3229/2581 sequences with a significant hit, respectively. The clustering by the Markov Clustering Algorithm (MCL) revealed a common core of 1710 clusters present in all three species and 5903 unique clusters for H. araneus. The combined sequencing approaches generated transcripts that will greatly expand the limited genomic data available for crustaceans. We introduce the MCL clustering for transcriptome comparisons as a simple approach to estimate similarities between transcriptomic libraries of different size and quality and to analyze homologies within the selected group of species. In particular, we identified a large variety of reverse transcriptase (RT) sequences not only in the H. araneus transcriptome and other decapod crustaceans, but also sea urchin, supporting the hypothesis of a heritable, anti-viral immunity and the proposed viral fragment integration by host-derived RTs in marine invertebrates. © 2013.

Single-molecule study of thymidine glycol and i-motif through the alpha-hemolysin ion channel

NASA Astrophysics Data System (ADS)

He, Lidong

Nanopore-based devices have emerged as a single-molecule detection and analysis tool for a wide range of applications. Through electrophoretically driving DNA molecules across a nanosized pore, a lot of information can be received, including unfolding kinetics and DNA-protein interactions. This single-molecule method has the potential to sequence kilobase length DNA polymers without amplification or labeling, approaching "the third generation" genome sequencing for around $1000 within 24 hours. alpha-Hemolysin biological nanopores have the advantages of excellent stability, low-noise level, and precise site-directed mutagenesis for engineering this protein nanopore. The first work presented in this thesis established the current signal of the thymidine glycol lesion in DNA oligomers through an immobilization experiment. The thymidine glycol enantiomers were differentiated from each other by different current blockage levels. Also, the effect of bulky hydrophobic adducts to the current blockage was investigated. Secondly, the alpha-hemolysin nanopore was used to study the human telomere i-motif and RET oncogene i-motif at a single-molecule level. In Chapter 3, it was demonstrated that the alpha-hemolysin nanopore can differentiate an i-motif form and single-strand DNA form at different pH values based on the same sequence. In addition, it shows potential to differentiate the folding topologies generated from the same DNA sequence.

Cardiovascular magnetic resonance physics for clinicians: part II

PubMed Central

2012-01-01

This is the second of two reviews that is intended to cover the essential aspects of cardiovascular magnetic resonance (CMR) physics in a way that is understandable and relevant to clinicians using CMR in their daily practice. Starting with the basic pulse sequences and contrast mechanisms described in part I, it briefly discusses further approaches to accelerate image acquisition. It then continues by showing in detail how the contrast behaviour of black blood fast spin echo and bright blood cine gradient echo techniques can be modified by adding rf preparation pulses to derive a number of more specialised pulse sequences. The simplest examples described include T2-weighted oedema imaging, fat suppression and myocardial tagging cine pulse sequences. Two further important derivatives of the gradient echo pulse sequence, obtained by adding preparation pulses, are used in combination with the administration of a gadolinium-based contrast agent for myocardial perfusion imaging and the assessment of myocardial tissue viability using a late gadolinium enhancement (LGE) technique. These two imaging techniques are discussed in more detail, outlining the basic principles of each pulse sequence, the practical steps required to achieve the best results in a clinical setting and, in the case of perfusion, explaining some of the factors that influence current approaches to perfusion image analysis. The key principles of contrast-enhanced magnetic resonance angiography (CE-MRA) are also explained in detail, especially focusing on timing of the acquisition following contrast agent bolus administration, and current approaches to achieving time resolved MRA. Alternative MRA techniques that do not require the use of an endogenous contrast agent are summarised, and the specialised pulse sequence used to image the coronary arteries, using respiratory navigator gating, is described in detail. The article concludes by explaining the principle behind phase contrast imaging techniques which create images that represent the phase of the MR signal rather than the magnitude. It is shown how this principle can be used to generate velocity maps by designing gradient waveforms that give rise to a relative phase change that is proportional to velocity. Choice of velocity encoding range and key pitfalls in the use of this technique are discussed. PMID:22995744

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

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

Daily, Jeffrey A.

2015-05-01

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of alreadymore » annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.« less

Current and Emerging Technology Approaches in Genomics

PubMed Central

Conley, Yvette P.; Biesecker, Leslie G.; Gonsalves, Stephen; Merkle, Carrie J.; Kirk, Maggie; Aouizerat, Bradley E.

2013-01-01

Purpose To introduce current and emerging approaches that are being utilized in the field of genomics so the reader can conceptually evaluate the literature and appreciate how these approaches are advancing our understanding of health-related issues. Organizing Construct Each approach is described and includes information related to how it is advancing research, its potential clinical utility, exemplars of current uses, challenges related to technologies used for these approaches, and when appropriate information related to understanding the evidence base for clinical utilization of each approach is provided. Web-based resources are included for the reader who would like more in-depth information and to provide opportunity to stay up to date with these approaches and their utility. Conclusions The chosen approaches– genome sequencing, genome-wide association studies, epigenomics, and gene expression– are extremely valuable approaches for collecting research data to help us better understand the pathophysiology of a variety of health-related conditions, but they are also gaining in utility for clinical assessment and testing purposes. Clinical Relevance Our increased understanding of the molecular underpinnings of disease will assist with better development of screening tests, diagnostic tests, tests that allow us to prognosticate, tests that allow for individualized treatments, and tests to facilitate post-treatment surveillance. PMID:23294727

A field ornithologist’s guide to genomics: Practical considerations for ecology and conservation

USGS Publications Warehouse

Oyler-McCance, Sara J.; Oh, Kevin; Langin, Kathryn; Aldridge, Cameron L.

2016-01-01

Vast improvements in sequencing technology have made it practical to simultaneously sequence millions of nucleotides distributed across the genome, opening the door for genomic studies in virtually any species. Ornithological research stands to benefit in three substantial ways. First, genomic methods enhance our ability to parse and simultaneously analyze both neutral and non-neutral genomic regions, thus providing insight into adaptive evolution and divergence. Second, the sheer quantity of sequence data generated by current sequencing platforms allows increased precision and resolution in analyses. Third, high-throughput sequencing can benefit applications that focus on a small number of loci that are otherwise prohibitively expensive, time-consuming, and technically difficult using traditional sequencing methods. These advances have improved our ability to understand evolutionary processes like speciation and local adaptation, but they also offer many practical applications in the fields of population ecology, migration tracking, conservation planning, diet analyses, and disease ecology. This review provides a guide for field ornithologists interested in incorporating genomic approaches into their research program, with an emphasis on techniques related to ecology and conservation. We present a general overview of contemporary genomic approaches and methods, as well as important considerations when selecting a genomic technique. We also discuss research questions that are likely to benefit from utilizing high-throughput sequencing instruments, highlighting select examples from recent avian studies.

In vitro manipulation of gene expression in larval Schistosoma: a model for postgenomic approaches in Trematoda

PubMed Central

YOSHINO, TIMOTHY P.; DINGUIRARD, NATHALIE; DE MORAES MOURÃO, MARINA

2013-01-01

SUMMARY With rapid developments in DNA and protein sequencing technologies, combined with powerful bioinformatics tools, a continued acceleration of gene identification in parasitic helminths is predicted, potentially leading to discovery of new drug and vaccine targets, enhanced diagnostics and insights into the complex biology underlying host-parasite interactions. For the schistosome blood flukes, with the recent completion of genome sequencing and comprehensive transcriptomic datasets, there has accumulated massive amounts of gene sequence data, for which, in the vast majority of cases, little is known about actual functions within the intact organism. In this review we attempt to bring together traditional in vitro cultivation approaches and recent emergent technologies of molecular genomics, transcriptomics and genetic manipulation to illustrate the considerable progress made in our understanding of trematode gene expression and function during development of the intramolluscan larval stages. Using several prominent trematode families (Schistosomatidae, Fasciolidae, Echinostomatidae), we have focused on the current status of in vitro larval isolation/cultivation as a source of valuable raw material supporting gene discovery efforts in model digeneans that include whole genome sequencing, transcript and protein expression profiling during larval development, and progress made in the in vitro manipulation of genes and their expression in larval trematodes using transgenic and RNA interference (RNAi) approaches. PMID:19961646

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

PubMed Central

2011-01-01

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

Acoustic sequences in non-human animals: a tutorial review and prospectus.

PubMed

Kershenbaum, Arik; Blumstein, Daniel T; Roch, Marie A; Akçay, Çağlar; Backus, Gregory; Bee, Mark A; Bohn, Kirsten; Cao, Yan; Carter, Gerald; Cäsar, Cristiane; Coen, Michael; DeRuiter, Stacy L; Doyle, Laurance; Edelman, Shimon; Ferrer-i-Cancho, Ramon; Freeberg, Todd M; Garland, Ellen C; Gustison, Morgan; Harley, Heidi E; Huetz, Chloé; Hughes, Melissa; Hyland Bruno, Julia; Ilany, Amiyaal; Jin, Dezhe Z; Johnson, Michael; Ju, Chenghui; Karnowski, Jeremy; Lohr, Bernard; Manser, Marta B; McCowan, Brenda; Mercado, Eduardo; Narins, Peter M; Piel, Alex; Rice, Megan; Salmi, Roberta; Sasahara, Kazutoshi; Sayigh, Laela; Shiu, Yu; Taylor, Charles; Vallejo, Edgar E; Waller, Sara; Zamora-Gutierrez, Veronica

2016-02-01

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise - let alone understand - the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality. © 2014 Cambridge Philosophical Society.

Acoustic sequences in non-human animals: a tutorial review and prospectus

PubMed Central

Kershenbaum, Arik; Blumstein, Daniel T.; Roch, Marie A.; Akçay, Çağlar; Backus, Gregory; Bee, Mark A.; Bohn, Kirsten; Cao, Yan; Carter, Gerald; Cäsar, Cristiane; Coen, Michael; DeRuiter, Stacy L.; Doyle, Laurance; Edelman, Shimon; Ferrer-i-Cancho, Ramon; Freeberg, Todd M.; Garland, Ellen C.; Gustison, Morgan; Harley, Heidi E.; Huetz, Chloé; Hughes, Melissa; Bruno, Julia Hyland; Ilany, Amiyaal; Jin, Dezhe Z.; Johnson, Michael; Ju, Chenghui; Karnowski, Jeremy; Lohr, Bernard; Manser, Marta B.; McCowan, Brenda; Mercado, Eduardo; Narins, Peter M.; Piel, Alex; Rice, Megan; Salmi, Roberta; Sasahara, Kazutoshi; Sayigh, Laela; Shiu, Yu; Taylor, Charles; Vallejo, Edgar E.; Waller, Sara; Zamora-Gutierrez, Veronica

2015-01-01

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, “Analysing vocal sequences in animals”. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality. PMID:25428267

VaDiR: an integrated approach to Variant Detection in RNA.

PubMed

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

2018-02-01

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

A proteomic map of the unsequenced kala-azar vector Phlebotomus papatasi using cell line.

PubMed

Pawar, Harsh; Chavan, Sandip; Mahale, Kiran; Khobragade, Sweta; Kulkarni, Aditi; Patil, Arun; Chaphekar, Deepa; Varriar, Pratyasha; Sudeep, Anakkathil; Pai, Kalpana; Prasad, T S K; Gowda, Harsha; Patole, Milind S

2015-12-01

The debilitating disease kala-azar or visceral leishmaniasis is caused by the kinetoplastid protozoan parasite Leishmania donovani. The parasite is transmitted by the hematophagous sand fly vector of the genus Phlebotomus in the old world and Lutzomyia in the new world. The predominant Phlebotomine species associated with the transmission of kala-azar are Phlebotomus papatasi and Phlebotomus argentipes. Understanding the molecular interaction of the sand fly and Leishmania, during the development of parasite within the sand fly gut is crucial to the understanding of the parasite life cycle. The complete genome sequences of sand flies (Phlebotomus and Lutzomyia) are currently not available and this hinders identification of proteins in the sand fly vector. The current study utilizes a three frame translated transcriptomic data of P. papatasi in the absence of genomic sequences to analyze the mass spectrometry data of P. papatasi cell line using a proteogenomic approach. Additionally, we have carried out the proteogenomic analysis of P. papatasi by comparative homology-based searches using related sequenced dipteran protein data. This study resulted in the identification of 1313 proteins from P. papatasi based on homology. Our study demonstrates the power of proteogenomic approaches in mapping the proteomes of unsequenced organisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Viral discovery in the invasive Australian cane toad (Rhinella marina) using metatranscriptomic and genomic approaches.

PubMed

Russo, Alice G; Eden, John-Sebastian; Enosi Tuipulotu, Daniel; Shi, Mang; Selechnik, Daniel; Shine, Richard; Rollins, Lee Ann; Holmes, Edward C; White, Peter A

2018-06-13

Cane toads are a notorious invasive species, inhabiting over 1.2 million km 2 of Australia and threatening native biodiversity. Release of pathogenic cane toad viruses is one possible biocontrol strategy yet is currently hindered by the poorly-described cane toad virome. Metatranscriptomic analysis of 16 cane toad livers revealed the presence of a novel and full-length picornavirus, Rhimavirus A (RhiV-A), a member of a reptile and amphibian specific-cluster of the Picornaviridae basal to the Kobuvirus -like group. In the combined liver transcriptome, we also identified a complete genome sequence of a distinct epsilonretrovirus, R. marina endogenous retrovirus (RMERV). The recently sequenced cane toad genome contains eight complete RMERV proviruses, as well as 21 additional truncated insertions. The oldest full length RMERV provirus was estimated to have inserted 1.9 MYA. To screen for these viral sequences in additional toads, we analysed publicly available transcriptomes from six diverse Australian locations. RhiV-A transcripts were identified in toads sampled from three locations across 1,000 km of Australia, stretching to the current Western Australia (WA) invasion front, whilst RMERV transcripts were observed at all six sites. Lastly, we scanned the cane toad genome for non-retroviral endogenous viral elements, finding three sequences related to small DNA viruses in the family Circoviridae This shows ancestral circoviral infection with subsequent genomic integration. The identification of these current and past viral infections enriches our knowledge of the cane toad virome, an understanding of which will facilitate future work on infection and disease in this important invasive species. Importance Cane toads are poisonous amphibians which were introduced to Australia in 1935 for insect control. Since then, their population has increased dramatically, and they now threat many native Australian species. One potential method to control the population is to release a cane toad virus with high mortality, yet few cane toad viruses have been characterised. This study samples cane toads from different Australian locations and uses an RNA sequencing and computational approach to find new viruses. We report novel complete picornavirus and retrovirus sequences which were genetically similar to viruses infecting frogs, reptiles and fish. Using data generated in other studies, we show that these viral sequences are present in cane toads from distinct Australian locations. Three sequences related to circoviruses were also found in the toad genome. The identification of new viral sequences will aid future studies which investigate their prevalence and potential as agents for biocontrol. Copyright © 2018 American Society for Microbiology.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

Sequences Associated with Centromere Competency in the Human Genome

PubMed Central

Hayden, Karen E.; Strome, Erin D.; Merrett, Stephanie L.; Lee, Hye-Ran; Rudd, M. Katharine

2013-01-01

Centromeres, the sites of spindle attachment during mitosis and meiosis, are located in specific positions in the human genome, normally coincident with diverse subsets of alpha satellite DNA. While there is strong evidence supporting the association of some subfamilies of alpha satellite with centromere function, the basis for establishing whether a given alpha satellite sequence is or is not designated a functional centromere is unknown, and attempts to understand the role of particular sequence features in establishing centromere identity have been limited by the near identity and repetitive nature of satellite sequences. Utilizing a broadly applicable experimental approach to test sequence competency for centromere specification, we have carried out a genomic and epigenetic functional analysis of endogenous human centromere sequences available in the current human genome assembly. The data support a model in which functionally competent sequences confer an opportunity for centromere specification, integrating genomic and epigenetic signals and promoting the concept of context-dependent centromere inheritance. PMID:23230266

Heuristics for multiobjective multiple sequence alignment.

PubMed

Abbasi, Maryam; Paquete, Luís; Pereira, Francisco B

2016-07-15

Aligning multiple sequences arises in many tasks in Bioinformatics. However, the alignments produced by the current software packages are highly dependent on the parameters setting, such as the relative importance of opening gaps with respect to the increase of similarity. Choosing only one parameter setting may provide an undesirable bias in further steps of the analysis and give too simplistic interpretations. In this work, we reformulate multiple sequence alignment from a multiobjective point of view. The goal is to generate several sequence alignments that represent a trade-off between maximizing the substitution score and minimizing the number of indels/gaps in the sum-of-pairs score function. This trade-off gives to the practitioner further information about the similarity of the sequences, from which she could analyse and choose the most plausible alignment. We introduce several heuristic approaches, based on local search procedures, that compute a set of sequence alignments, which are representative of the trade-off between the two objectives (substitution score and indels). Several algorithm design options are discussed and analysed, with particular emphasis on the influence of the starting alignment and neighborhood search definitions on the overall performance. A perturbation technique is proposed to improve the local search, which provides a wide range of high-quality alignments. The proposed approach is tested experimentally on a wide range of instances. We performed several experiments with sequences obtained from the benchmark database BAliBASE 3.0. To evaluate the quality of the results, we calculate the hypervolume indicator of the set of score vectors returned by the algorithms. The results obtained allow us to identify reasonably good choices of parameters for our approach. Further, we compared our method in terms of correctly aligned pairs ratio and columns correctly aligned ratio with respect to reference alignments. Experimental results show that our approaches can obtain better results than TCoffee and Clustal Omega in terms of the first ratio.

Auroral Substorms: Search for Processes Causing the Expansion Phase in Terms of the Electric Current Approach

NASA Astrophysics Data System (ADS)

Akasofu, Syun-Ichi

2017-10-01

Auroral substorms are mostly manifestations of dissipative processes of electromagnetic energy. Thus, we consider a sequence of processes consisting of the power supply (dynamo), transmission (currents/circuits) and dissipations (auroral substorms-the end product), namely the electric current line approach. This work confirms quantitatively that after accumulating magnetic energy during the growth phase, the magnetosphere unloads the stored magnetic energy impulsively in order to stabilize itself. This work is based on our result that substorms are caused by two current systems, the directly driven (DD) current system and the unloading system (UL). The most crucial finding in this work is the identification of the UL (unloading) current system which is responsible for the expansion phase. A very tentative sequence of the processes leading to the expansion phase (the generation of the UL current system) is suggested for future discussions. (1) The solar wind-magnetosphere dynamo enhances significantly the plasma sheet current when its power is increased above 10^{18} erg/s (10^{11} w). (2) The magnetosphere accumulates magnetic energy during the growth phase, because the ionosphere cannot dissipate the increasing power because of a low conductivity. As a result, the magnetosphere is inflated, accumulating magnetic energy. (3) When the power reaches 3-5× 10^{18} erg/s (3-5× 10^{11} w) for about one hour and the stored magnetic energy reaches 3-5×10^{22} ergs (10^{15} J), the magnetosphere begins to develop perturbations caused by current instabilities (the current density {≈}3× 10^{-12} A/cm2 and the total current {≈}106 A at 6 Re). As a result, the plasma sheet current is reduced. (4) The magnetosphere is thus deflated. The current reduction causes partial B/partial t > 0 in the main body of the magnetosphere, producing an earthward electric field. As it is transmitted to the ionosphere, it becomes equatorward-directed electric field which drives both Pedersen and Hall currents and thus generates the UL current system. (5) A significant part of the magnetic energy is accumulated in the main body of the magnetosphere (the inner plasma sheet) between 4 Re and 10 Re, because the power (Poynting flux [ E × B ]) is mainly directed toward this region which can hold the substorm energy. (6) The substorm intensity depends on the location of the energy accumulation (between 4 Re and 10 Re), the closer the location to the earth, the more intense substorms becomes, because the capacity of holding the energy is higher at closer distances. The convective flow toward the earth brings both the ring current and the plasma sheet current closer when the dynamo power becomes higher. This proposed sequence is not necessarily new. Individual processes involved have been considered by many, but the electric current approach can bring them together systematically and provide some new quantitative insights.

TotalReCaller: improved accuracy and performance via integrated alignment and base-calling.

PubMed

Menges, Fabian; Narzisi, Giuseppe; Mishra, Bud

2011-09-01

Currently, re-sequencing approaches use multiple modules serially to interpret raw sequencing data from next-generation sequencing platforms, while remaining oblivious to the genomic information until the final alignment step. Such approaches fail to exploit the full information from both raw sequencing data and the reference genome that can yield better quality sequence reads, SNP-calls, variant detection, as well as an alignment at the best possible location in the reference genome. Thus, there is a need for novel reference-guided bioinformatics algorithms for interpreting analog signals representing sequences of the bases ({A, C, G, T}), while simultaneously aligning possible sequence reads to a source reference genome whenever available. Here, we propose a new base-calling algorithm, TotalReCaller, to achieve improved performance. A linear error model for the raw intensity data and Burrows-Wheeler transform (BWT) based alignment are combined utilizing a Bayesian score function, which is then globally optimized over all possible genomic locations using an efficient branch-and-bound approach. The algorithm has been implemented in soft- and hardware [field-programmable gate array (FPGA)] to achieve real-time performance. Empirical results on real high-throughput Illumina data were used to evaluate TotalReCaller's performance relative to its peers-Bustard, BayesCall, Ibis and Rolexa-based on several criteria, particularly those important in clinical and scientific applications. Namely, it was evaluated for (i) its base-calling speed and throughput, (ii) its read accuracy and (iii) its specificity and sensitivity in variant calling. A software implementation of TotalReCaller as well as additional information, is available at: http://bioinformatics.nyu.edu/wordpress/projects/totalrecaller/ fabian.menges@nyu.edu.

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

PubMed

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

2016-09-01

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

A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature

PubMed Central

Song, Yuhyun; Leman, Scotland; Monteil, Caroline L.; Heath, Lenwood S.; Vinatzer, Boris A.

2014-01-01

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research. PMID:24586551

Large-Scale Modeling of Wordform Learning and Representation

ERIC Educational Resources Information Center

Sibley, Daragh E.; Kello, Christopher T.; Plaut, David C.; Elman, Jeffrey L.

2008-01-01

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through the graphical user interface ( http://compbio.math.hr/ ). Our results show that scanning with a carefully parameterized motif-HMM is an effective approach for annotation of protein families with low sequence similarity and conserved motifs. The results of this study expand current knowledge and provide new insights into the evolution of the large GDSL-lipase family in land plants.

Design of a final approach spacing tool for TRACON air traffic control

NASA Technical Reports Server (NTRS)

Davis, Thomas J.; Erzberger, Heinz; Bergeron, Hugh

1989-01-01

This paper describes an automation tool that assists air traffic controllers in the Terminal Radar Approach Control (TRACON) Facilities in providing safe and efficient sequencing and spacing of arrival traffic. The automation tool, referred to as the Final Approach Spacing Tool (FAST), allows the controller to interactively choose various levels of automation and advisory information ranging from predicted time errors to speed and heading advisories for controlling time error. FAST also uses a timeline to display current scheduling and sequencing information for all aircraft in the TRACON airspace. FAST combines accurate predictive algorithms and state-of-the-art mouse and graphical interface technology to present advisory information to the controller. Furthermore, FAST exchanges various types of traffic information and communicates with automation tools being developed for the Air Route Traffic Control Center. Thus it is part of an integrated traffic management system for arrival traffic at major terminal areas.

A novel and efficient technique for identification and classification of GPCRs.

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

G-protein coupled receptors (GPCRs) play a vital role in different biological processes, such as regulation of growth, death, and metabolism of cells. GPCRs are the focus of significant amount of current pharmaceutical research since they interact with more than 50% of prescription drugs. The dipeptide-based support vector machine (SVM) approach is the most accurate technique to identify and classify the GPCRs. However, this approach has two major disadvantages. First, the dimension of dipeptide-based feature vector is equal to 400. The large dimension makes the classification task computationally and memory wise inefficient. Second, it does not consider the biological properties of protein sequence for identification and classification of GPCRs. In this paper, we present a novel-feature-based SVM classification technique. The novel features are derived by applying wavelet-based time series analysis approach on protein sequences. The proposed feature space summarizes the variance information of seven important biological properties of amino acids in a protein sequence. In addition, the dimension of the feature vector for proposed technique is equal to 35. Experiments were performed on GPCRs protein sequences available at GPCRs Database. Our approach achieves an accuracy of 99.9%, 98.06%, 97.78%, and 94.08% for GPCR superfamily, families, subfamilies, and subsubfamilies (amine group), respectively, when evaluated using fivefold cross-validation. Further, an accuracy of 99.8%, 97.26%, and 97.84% was obtained when evaluated on unseen or recall datasets of GPCR superfamily, families, and subfamilies, respectively. Comparison with dipeptide-based SVM technique shows the effectiveness of our approach.

DNA barcoding for the identification of sand fly species (Diptera, Psychodidae, Phlebotominae) in Colombia.

PubMed

Contreras Gutiérrez, María Angélica; Vivero, Rafael J; Vélez, Iván D; Porter, Charles H; Uribe, Sandra

2014-01-01

Sand flies include a group of insects that are of medical importance and that vary in geographic distribution, ecology, and pathogen transmission. Approximately 163 species of sand flies have been reported in Colombia. Surveillance of the presence of sand fly species and the actualization of species distribution are important for predicting risks for and monitoring the expansion of diseases which sand flies can transmit. Currently, the identification of phlebotomine sand flies is based on morphological characters. However, morphological identification requires considerable skills and taxonomic expertise. In addition, significant morphological similarity between some species, especially among females, may cause difficulties during the identification process. DNA-based approaches have become increasingly useful and promising tools for estimating sand fly diversity and for ensuring the rapid and accurate identification of species. A partial sequence of the mitochondrial cytochrome oxidase gene subunit I (COI) is currently being used to differentiate species in different animal taxa, including insects, and it is referred as a barcoding sequence. The present study explored the utility of the DNA barcode approach for the identification of phlebotomine sand flies in Colombia. We sequenced 700 bp of the COI gene from 36 species collected from different geographic localities. The COI barcode sequence divergence within a single species was <2% in most cases, whereas this divergence ranged from 9% to 26.6% among different species. These results indicated that the barcoding gene correctly discriminated among the previously morphologically identified species with an efficacy of nearly 100%. Analyses of the generated sequences indicated that the observed species groupings were consistent with the morphological identifications. In conclusion, the barcoding gene was useful for species discrimination in sand flies from Colombia.

DNA Barcoding for the Identification of Sand Fly Species (Diptera, Psychodidae, Phlebotominae) in Colombia

PubMed Central

Contreras Gutiérrez, María Angélica; Vivero, Rafael J.; Vélez, Iván D.; Porter, Charles H.; Uribe, Sandra

2014-01-01

Sand flies include a group of insects that are of medical importance and that vary in geographic distribution, ecology, and pathogen transmission. Approximately 163 species of sand flies have been reported in Colombia. Surveillance of the presence of sand fly species and the actualization of species distribution are important for predicting risks for and monitoring the expansion of diseases which sand flies can transmit. Currently, the identification of phlebotomine sand flies is based on morphological characters. However, morphological identification requires considerable skills and taxonomic expertise. In addition, significant morphological similarity between some species, especially among females, may cause difficulties during the identification process. DNA-based approaches have become increasingly useful and promising tools for estimating sand fly diversity and for ensuring the rapid and accurate identification of species. A partial sequence of the mitochondrial cytochrome oxidase gene subunit I (COI) is currently being used to differentiate species in different animal taxa, including insects, and it is referred as a barcoding sequence. The present study explored the utility of the DNA barcode approach for the identification of phlebotomine sand flies in Colombia. We sequenced 700 bp of the COI gene from 36 species collected from different geographic localities. The COI barcode sequence divergence within a single species was <2% in most cases, whereas this divergence ranged from 9% to 26.6% among different species. These results indicated that the barcoding gene correctly discriminated among the previously morphologically identified species with an efficacy of nearly 100%. Analyses of the generated sequences indicated that the observed species groupings were consistent with the morphological identifications. In conclusion, the barcoding gene was useful for species discrimination in sand flies from Colombia. PMID:24454877

Deep sequencing-based transcriptome analysis of Plutella xylostella larvae parasitized by Diadegma semiclausum

PubMed Central

2011-01-01

Background Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported. Results De novo assembly of cDNA sequence data generated 172,660 contigs between 100 and 10000 bp in length; with 35% of > 200 bp in length. Parasitization had significant impacts on expression levels of 928 identified insect host transcripts. Gene ontology data illustrated that the majority of the differentially expressed genes are involved in binding, catalytic activity, and metabolic and cellular processes. In addition, the results show that transcription levels of antimicrobial peptides, such as gloverin, cecropin E and lysozyme, were up-regulated after parasitism. Expression of ichnovirus genes were detected in parasitized larvae with 19 unique sequences identified from five PDV gene families including vankyrin, viral innexin, repeat elements, a cysteine-rich motif, and polar residue rich protein. Vankyrin 1 and repeat element 1 genes showed the highest transcription levels among the DsIV genes. Conclusion This study provides detailed information on differential expression of P. xylostella larval genes following parasitization, DsIV genes expressed in the host and also improves our current understanding of this host-parasitoid interaction. PMID:21906285

GASP: Gapped Ancestral Sequence Prediction for proteins

PubMed Central

Edwards, Richard J; Shields, Denis C

2004-01-01

Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. PMID:15350199

Assessing pooled BAC and whole genome shotgun strategies for assembly of complex genomes.

PubMed

Haiminen, Niina; Feltus, F Alex; Parida, Laxmi

2011-04-15

We investigate if pooling BAC clones and sequencing the pools can provide for more accurate assembly of genome sequences than the "whole genome shotgun" (WGS) approach. Furthermore, we quantify this accuracy increase. We compare the pooled BAC and WGS approaches using in silico simulations. Standard measures of assembly quality focus on assembly size and fragmentation, which are desirable for large whole genome assemblies. We propose additional measures enabling easy and visual comparison of assembly quality, such as rearrangements and redundant sequence content, relative to the known target sequence. The best assembly quality scores were obtained using 454 coverage of 15× linear and 5× paired (3kb insert size) reads (15L-5P) on Arabidopsis. This regime gave similarly good results on four additional plant genomes of very different GC and repeat contents. BAC pooling improved assembly scores over WGS assembly, coverage and redundancy scores improving the most. BAC pooling works better than WGS, however, both require a physical map to order the scaffolds. Pool sizes up to 12Mbp work well, suggesting this pooling density to be effective in medium-scale re-sequencing applications such as targeted sequencing of QTL intervals for candidate gene discovery. Assuming the current Roche/454 Titanium sequencing limitations, a 12 Mbp region could be re-sequenced with a full plate of linear reads and a half plate of paired-end reads, yielding 15L-5P coverage after read pre-processing. Our simulation suggests that massively over-sequencing may not improve accuracy. Our scoring measures can be used generally to evaluate and compare results of simulated genome assemblies.

Accurate, Rapid Taxonomic Classification of Fungal Large-Subunit rRNA Genes

PubMed Central

Liu, Kuan-Liang; Porras-Alfaro, Andrea; Eichorst, Stephanie A.

2012-01-01

Taxonomic and phylogenetic fingerprinting based on sequence analysis of gene fragments from the large-subunit rRNA (LSU) gene or the internal transcribed spacer (ITS) region is becoming an integral part of fungal classification. The lack of an accurate and robust classification tool trained by a validated sequence database for taxonomic placement of fungal LSU genes is a severe limitation in taxonomic analysis of fungal isolates or large data sets obtained from environmental surveys. Using a hand-curated set of 8,506 fungal LSU gene fragments, we determined the performance characteristics of a naïve Bayesian classifier across multiple taxonomic levels and compared the classifier performance to that of a sequence similarity-based (BLASTN) approach. The naïve Bayesian classifier was computationally more rapid (>460-fold with our system) than the BLASTN approach, and it provided equal or superior classification accuracy. Classifier accuracies were compared using sequence fragments of 100 bp and 400 bp and two different PCR primer anchor points to mimic sequence read lengths commonly obtained using current high-throughput sequencing technologies. Accuracy was higher with 400-bp sequence reads than with 100-bp reads. It was also significantly affected by sequence location across the 1,400-bp test region. The highest accuracy was obtained across either the D1 or D2 variable region. The naïve Bayesian classifier provides an effective and rapid means to classify fungal LSU sequences from large environmental surveys. The training set and tool are publicly available through the Ribosomal Database Project (http://rdp.cme.msu.edu/classifier/classifier.jsp). PMID:22194300

Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor

DOE PAGES

Faulon, Jean-Loup; Misra, Milind; Martin, Shawn; ...

2007-11-23

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. Additionally, there is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein–chemical interactions using heterogeneous input consisting of both protein sequence and chemical information. Results: Our method relies on expressing proteins and chemicals with a common cheminformaticsmore » representation. We demonstrate our approach by predicting whether proteins can catalyze reactions not present in training sets. We also predict whether a given drug can bind a target, in the absence of prior binding information for that drug and target. Lastly, such predictions cannot be made with current machine-learning techniques requiring binding information for individual reactions or individual targets.« less

Investigation of the Evolutionary Development of the Genus Bifidobacterium by Comparative Genomics

PubMed Central

Lugli, Gabriele Andrea; Milani, Christian; Turroni, Francesca; Duranti, Sabrina; Ferrario, Chiara; Viappiani, Alice; Mancabelli, Leonardo; Mangifesta, Marta; Taminiau, Bernard; Delcenserie, Véronique; van Sinderen, Douwe

2014-01-01

The Bifidobacterium genus currently encompasses 48 recognized taxa, which have been isolated from different ecosystems. However, the current phylogeny of bifidobacteria is hampered by the relative paucity of genotypic data. Here, we reassessed the taxonomy of this bacterial genus using genome-based approaches, which demonstrated that the previous taxonomic view of bifidobacteria contained several inconsistencies. In particular, high levels of genetic relatedness were shown to exist between particular Bifidobacterium taxa which would not justify their status as separate species. The results presented are here based on average nucleotide identity analysis involving the genome sequences for each type strain of the 48 bifidobacterial taxa, as well as phylogenetic comparative analysis of the predicted core genome of the Bifidobacterium genus. The results of this study demonstrate that the availability of complete genome sequences allows the reconstruction of a more robust bifidobacterial phylogeny than that obtained from a single gene-based sequence comparison, thus discouraging the assignment of a new or separate bifidobacterial taxon without such a genome-based validation. PMID:25107967

A global sampling approach to designing and reengineering RNA secondary structures.

PubMed

Levin, Alex; Lis, Mieszko; Ponty, Yann; O'Donnell, Charles W; Devadas, Srinivas; Berger, Bonnie; Waldispühl, Jérôme

2012-11-01

The development of algorithms for designing artificial RNA sequences that fold into specific secondary structures has many potential biomedical and synthetic biology applications. To date, this problem remains computationally difficult, and current strategies to address it resort to heuristics and stochastic search techniques. The most popular methods consist of two steps: First a random seed sequence is generated; next, this seed is progressively modified (i.e. mutated) to adopt the desired folding properties. Although computationally inexpensive, this approach raises several questions such as (i) the influence of the seed; and (ii) the efficiency of single-path directed searches that may be affected by energy barriers in the mutational landscape. In this article, we present RNA-ensign, a novel paradigm for RNA design. Instead of taking a progressive adaptive walk driven by local search criteria, we use an efficient global sampling algorithm to examine large regions of the mutational landscape under structural and thermodynamical constraints until a solution is found. When considering the influence of the seeds and the target secondary structures, our results show that, compared to single-path directed searches, our approach is more robust, succeeds more often and generates more thermodynamically stable sequences. An ensemble approach to RNA design is thus well worth pursuing as a complement to existing approaches. RNA-ensign is available at http://csb.cs.mcgill.ca/RNAensign.

A global sampling approach to designing and reengineering RNA secondary structures

PubMed Central

Levin, Alex; Lis, Mieszko; Ponty, Yann; O’Donnell, Charles W.; Devadas, Srinivas; Berger, Bonnie; Waldispühl, Jérôme

2012-01-01

The development of algorithms for designing artificial RNA sequences that fold into specific secondary structures has many potential biomedical and synthetic biology applications. To date, this problem remains computationally difficult, and current strategies to address it resort to heuristics and stochastic search techniques. The most popular methods consist of two steps: First a random seed sequence is generated; next, this seed is progressively modified (i.e. mutated) to adopt the desired folding properties. Although computationally inexpensive, this approach raises several questions such as (i) the influence of the seed; and (ii) the efficiency of single-path directed searches that may be affected by energy barriers in the mutational landscape. In this article, we present RNA-ensign, a novel paradigm for RNA design. Instead of taking a progressive adaptive walk driven by local search criteria, we use an efficient global sampling algorithm to examine large regions of the mutational landscape under structural and thermodynamical constraints until a solution is found. When considering the influence of the seeds and the target secondary structures, our results show that, compared to single-path directed searches, our approach is more robust, succeeds more often and generates more thermodynamically stable sequences. An ensemble approach to RNA design is thus well worth pursuing as a complement to existing approaches. RNA-ensign is available at http://csb.cs.mcgill.ca/RNAensign. PMID:22941632

TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences

PubMed Central

Song, Jiangning; Tan, Hao; Wang, Mingjun; Webb, Geoffrey I.; Akutsu, Tatsuya

2012-01-01

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the Cα-N bond (Phi) and the Cα-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/. PMID:22319565

Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus.

PubMed

Condon, David E; Tran, Phu V; Lien, Yu-Chin; Schug, Jonathan; Georgieff, Michael K; Simmons, Rebecca A; Won, Kyoung-Jae

2018-02-05

Identification of differentially methylated regions (DMRs) is the initial step towards the study of DNA methylation-mediated gene regulation. Previous approaches to call DMRs suffer from false prediction, use extreme resources, and/or require library installation and input conversion. We developed a new approach called Defiant to identify DMRs. Employing Weighted Welch Expansion (WWE), Defiant showed superior performance to other predictors in the series of benchmarking tests on artificial and real data. Defiant was subsequently used to investigate DNA methylation changes in iron-deficient rat hippocampus. Defiant identified DMRs close to genes associated with neuronal development and plasticity, which were not identified by its competitor. Importantly, Defiant runs between 5 to 479 times faster than currently available software packages. Also, Defiant accepts 10 different input formats widely used for DNA methylation data. Defiant effectively identifies DMRs for whole-genome bisulfite sequencing (WGBS), reduced-representation bisulfite sequencing (RRBS), Tet-assisted bisulfite sequencing (TAB-seq), and HpaII tiny fragment enrichment by ligation-mediated PCR-tag (HELP) assays.

Capturing the genetic makeup of the active microbiome in situ.

PubMed

Singer, Esther; Wagner, Michael; Woyke, Tanja

2017-09-01

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and that have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.

Capturing the genetic makeup of the active microbiome in situ

PubMed Central

Singer, Esther; Wagner, Michael; Woyke, Tanja

2017-01-01

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and that have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions. PMID:28574490

Using High-Throughput Sequencing to Leverage Surveillance of Genetic Diversity and Oseltamivir Resistance: A Pilot Study during the 2009 Influenza A(H1N1) Pandemic

PubMed Central

Téllez-Sosa, Juan; Rodríguez, Mario Henry; Gómez-Barreto, Rosa E.; Valdovinos-Torres, Humberto; Hidalgo, Ana Cecilia; Cruz-Hervert, Pablo; Luna, René Santos; Carrillo-Valenzo, Erik; Ramos, Celso; García-García, Lourdes; Martínez-Barnetche, Jesús

2013-01-01

Background Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The “deep sequencing” approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples. Methodology and Principal Findings We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n  =  299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance. Conclusions NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach presented here can be scaled up for global genetic surveillance of influenza and other infectious diseases. PMID:23843978

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

PubMed Central

2013-01-01

Background The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions Many current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another. PMID:23870653

High-Throughput Next-Generation Sequencing of Polioviruses

PubMed Central

Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

2016-01-01

ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

Genetic Analyses in Small-for-Gestational-Age Newborns.

PubMed

Stalman, Susanne E; Solanky, Nita; Ishida, Miho; Alemán-Charlet, Cristina; Abu-Amero, Sayeda; Alders, Marielle; Alvizi, Lucas; Baird, William; Demetriou, Charalambos; Henneman, Peter; James, Chela; Knegt, Lia C; Leon, Lydia J; Mannens, Marcel M A M; Mul, Adi N; Nibbering, Nicole A; Peskett, Emma; Rezwan, Faisal I; Ris-Stalpers, Carrie; van der Post, Joris A M; Kamp, Gerdine A; Plötz, Frans B; Wit, Jan M; Stanier, Philip; Moore, Gudrun E; Hennekam, Raoul C

2018-03-01

Small for gestational age (SGA) can be the result of fetal growth restriction, which is associated with perinatal morbidity and mortality. Mechanisms that control prenatal growth are poorly understood. The aim of the current study was to gain more insight into prenatal growth failure and determine an effective diagnostic approach in SGA newborns. We hypothesized that one or more copy number variations (CNVs) and disturbed methylation and sequence variants may be present in genes associated with fetal growth. A prospective cohort study of subjects with a low birth weight for gestational age. The study was conducted at an academic pediatric research institute. A total of 21 SGA newborns with a mean birth weight below the first centile and a control cohort of 24 appropriate-for-gestational-age newborns were studied. Array comparative genomic hybridization, genome-wide methylation studies, and exome sequencing were performed. The numbers of CNVs, methylation disturbances, and sequence variants. The genetic analyses demonstrated three CNVs, one systematically disturbed methylation pattern, and one sequence variant explaining SGA. Additional methylation disturbances and sequence variants were present in 20 patients. In 19 patients, multiple abnormalities were found. Our results confirm the influence of a large number of mechanisms explaining dysregulation of fetal growth. We concluded that CNVs, methylation disturbances, and sequence variants all contribute to prenatal growth failure. These genetic workups can be an effective diagnostic approach in SGA newborns.

A Novel Targeted Approach for Noninvasive Detection of Paternally Inherited Mutations in Maternal Plasma.

PubMed

van den Oever, Jessica M E; van Minderhout, Ivonne J H M; Harteveld, Cornelis L; den Hollander, Nicolette S; Bakker, Egbert; van der Stoep, Nienke; Boon, Elles M J

2015-09-01

The challenge in noninvasive prenatal diagnosis for monogenic disorders lies in the detection of low levels of fetal variants in the excess of maternal cell-free plasma DNA. Next-generation sequencing, which is the main method used for noninvasive prenatal testing and diagnosis, can overcome this challenge. However, this method may not be accessible to all genetic laboratories. Moreover, shotgun next-generation sequencing as, for instance, currently applied for noninvasive fetal trisomy screening may not be suitable for the detection of inherited mutations. We have developed a sensitive, mutation-specific, and fast alternative for next-generation sequencing-mediated noninvasive prenatal diagnosis using a PCR-based method. For this proof-of-principle study, noninvasive fetal paternally inherited mutation detection was performed using cell-free DNA from maternal plasma. Preferential amplification of the paternally inherited allele was accomplished through a personalized approach using a blocking probe against maternal sequences in a high-resolution melting curve analysis-based assay. Enhanced detection of the fetal paternally inherited mutation was obtained for both an autosomal dominant and a recessive monogenic disorder by blocking the amplification of maternal sequences in maternal plasma. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Cryptosporidium in fish: alternative sequencing approaches and analyses at multiple loci to resolve mixed infections.

PubMed

Paparini, Andrea; Yang, Rongchang; Chen, Linda; Tong, Kaising; Gibson-Kueh, Susan; Lymbery, Alan; Ryan, Una M

2017-11-01

Currently, the systematics, biology and epidemiology of piscine Cryptosporidium species are poorly understood. Here, we compared Sanger ‒ and next-generation ‒ sequencing (NGS), of piscine Cryptosporidium, at the 18S rRNA and actin genes. The hosts comprised 11 ornamental fish species, spanning four orders and eight families. The objectives were: to (i) confirm the rich genetic diversity of the parasite and the high frequency of mixed infections; and (ii) explore the potential of NGS in the presence of complex genetic mixtures. By Sanger sequencing, four main genotypes were obtained at the actin locus, while for the 18S locus, seven genotypes were identified. At both loci, NGS revealed frequent mixed infections, consisting of one highly dominant variant plus substantially rarer genotypes. Both sequencing methods detected novel Cryptosporidium genotypes at both loci, including a novel and highly abundant actin genotype that was identified by both Sanger sequencing and NGS. Importantly, this genotype accounted for 68·9% of all NGS reads from all samples (249 585/362 372). The present study confirms that aquarium fish can harbour a large and unexplored Cryptosporidium genetic diversity. Although commonly used in molecular parasitology studies, nested PCR prevents quantitative comparisons and thwarts the advantages of NGS, when this latter approach is used to investigate multiple infections.

Accurate Sample Assignment in a Multiplexed, Ultrasensitive, High-Throughput Sequencing Assay for Minimal Residual Disease.

PubMed

Bartram, Jack; Mountjoy, Edward; Brooks, Tony; Hancock, Jeremy; Williamson, Helen; Wright, Gary; Moppett, John; Goulden, Nick; Hubank, Mike

2016-07-01

High-throughput sequencing (HTS) (next-generation sequencing) of the rearranged Ig and T-cell receptor genes promises to be less expensive and more sensitive than current methods of monitoring minimal residual disease (MRD) in patients with acute lymphoblastic leukemia. However, the adoption of new approaches by clinical laboratories requires careful evaluation of all potential sources of error and the development of strategies to ensure the highest accuracy. Timely and efficient clinical use of HTS platforms will depend on combining multiple samples (multiplexing) in each sequencing run. Here we examine the Ig heavy-chain gene HTS on the Illumina MiSeq platform for MRD. We identify errors associated with multiplexing that could potentially impact the accuracy of MRD analysis. We optimize a strategy that combines high-purity, sequence-optimized oligonucleotides, dual indexing, and an error-aware demultiplexing approach to minimize errors and maximize sensitivity. We present a probability-based, demultiplexing pipeline Error-Aware Demultiplexer that is suitable for all MiSeq strategies and accurately assigns samples to the correct identifier without excessive loss of data. Finally, using controls quantified by digital PCR, we show that HTS-MRD can accurately detect as few as 1 in 10(6) copies of specific leukemic MRD. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

PubMed

Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

2018-06-01

Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

A ddRAD-based genetic map and its integration with the genome assembly of Japanese eel (Anguilla japonica) provides insights into genome evolution after the teleost-specific genome duplication

PubMed Central

2014-01-01

Background Recent advancements in next-generation sequencing technology have enabled cost-effective sequencing of whole or partial genomes, permitting the discovery and characterization of molecular polymorphisms. Double-digest restriction-site associated DNA sequencing (ddRAD-seq) is a powerful and inexpensive approach to developing numerous single nucleotide polymorphism (SNP) markers and constructing a high-density genetic map. To enrich genomic resources for Japanese eel (Anguilla japonica), we constructed a ddRAD-based genetic map using an Ion Torrent Personal Genome Machine and anchored scaffolds of the current genome assembly to 19 linkage groups of the Japanese eel. Furthermore, we compared the Japanese eel genome with genomes of model fishes to infer the history of genome evolution after the teleost-specific genome duplication. Results We generated the ddRAD-based linkage map of the Japanese eel, where the maps for female and male spanned 1748.8 cM and 1294.5 cM, respectively, and were arranged into 19 linkage groups. A total of 2,672 SNP markers and 115 Simple Sequence Repeat markers provide anchor points to 1,252 scaffolds covering 151 Mb (13%) of the current genome assembly of the Japanese eel. Comparisons among the Japanese eel, medaka, zebrafish and spotted gar genomes showed highly conserved synteny among teleosts and revealed part of the eight major chromosomal rearrangement events that occurred soon after the teleost-specific genome duplication. Conclusions The ddRAD-seq approach combined with the Ion Torrent Personal Genome Machine sequencing allowed us to conduct efficient and flexible SNP genotyping. The integration of the genetic map and the assembled sequence provides a valuable resource for fine mapping and positional cloning of quantitative trait loci associated with economically important traits and for investigating comparative genomics of the Japanese eel. PMID:24669946

A ddRAD-based genetic map and its integration with the genome assembly of Japanese eel (Anguilla japonica) provides insights into genome evolution after the teleost-specific genome duplication.

PubMed

Kai, Wataru; Nomura, Kazuharu; Fujiwara, Atushi; Nakamura, Yoji; Yasuike, Motoshige; Ojima, Nobuhiko; Masaoka, Tetsuji; Ozaki, Akiyuki; Kazeto, Yukinori; Gen, Koichiro; Nagao, Jiro; Tanaka, Hideki; Kobayashi, Takanori; Ototake, Mitsuru

2014-03-26

Recent advancements in next-generation sequencing technology have enabled cost-effective sequencing of whole or partial genomes, permitting the discovery and characterization of molecular polymorphisms. Double-digest restriction-site associated DNA sequencing (ddRAD-seq) is a powerful and inexpensive approach to developing numerous single nucleotide polymorphism (SNP) markers and constructing a high-density genetic map. To enrich genomic resources for Japanese eel (Anguilla japonica), we constructed a ddRAD-based genetic map using an Ion Torrent Personal Genome Machine and anchored scaffolds of the current genome assembly to 19 linkage groups of the Japanese eel. Furthermore, we compared the Japanese eel genome with genomes of model fishes to infer the history of genome evolution after the teleost-specific genome duplication. We generated the ddRAD-based linkage map of the Japanese eel, where the maps for female and male spanned 1748.8 cM and 1294.5 cM, respectively, and were arranged into 19 linkage groups. A total of 2,672 SNP markers and 115 Simple Sequence Repeat markers provide anchor points to 1,252 scaffolds covering 151 Mb (13%) of the current genome assembly of the Japanese eel. Comparisons among the Japanese eel, medaka, zebrafish and spotted gar genomes showed highly conserved synteny among teleosts and revealed part of the eight major chromosomal rearrangement events that occurred soon after the teleost-specific genome duplication. The ddRAD-seq approach combined with the Ion Torrent Personal Genome Machine sequencing allowed us to conduct efficient and flexible SNP genotyping. The integration of the genetic map and the assembled sequence provides a valuable resource for fine mapping and positional cloning of quantitative trait loci associated with economically important traits and for investigating comparative genomics of the Japanese eel.

Combining genomic and proteomic approaches for epigenetics research

PubMed Central

Han, Yumiao; Garcia, Benjamin A

2014-01-01

Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656

Chasing down the triple-negative myeloproliferative neoplasms: Implications for molecular diagnostics.

PubMed

Langabeer, Stephen E

2016-01-01

The majority of patients with classical myeloproliferative neoplasms (MPN) of polycythemia vera, essential thrombocythemia, and primary myelofibrosis harbor distinct disease-driving mutations within the JAK2 , CALR , or MPL genes. The term triple-negative has been recently applied to those MPN without evidence of these consistent mutations, prompting whole or targeted exome sequencing approaches to determine the driver mutational status of this subgroup. These strategies have identified numerous novel mutations that occur in alternative exons of both JAK2 and MPL , the majority of which result in functional activation. Current molecular diagnostic approaches may possess insufficient coverage to detect these alternative mutations, prompting further consideration of targeted exon sequencing into routine diagnostic practice. How to incorporate these illuminating findings into the expanding molecular diagnostic algorithm for MPN requires continual attention.

Sequence variation and recognition specificity of the avirulence gene AvrPiz-t in Magnaporthe oryzae field populations

USDA-ARS?s Scientific Manuscript database

Magnaporthe oryzae, the rice blast pathogen, causes significant annual yield loss of rice worldwide. Currently, the most effective disease control approach is deployment of host resistance through introduction of resistance (R) genes into elite cultivars. The function of each R gene relies on the sp...

Dissecting the human microbiome with single-cell genomics.

PubMed

Tolonen, Andrew C; Xavier, Ramnik J

2017-06-14

Recent advances in genome sequencing of single microbial cells enable the assignment of functional roles to members of the human microbiome that cannot currently be cultured. This approach can reveal the genomic basis of phenotypic variation between closely related strains and can be applied to the targeted study of immunogenic bacteria in disease.

Sequence alignment to predict across species susceptibility (SeqAPASS): Cross species extrapolation in the 21st century

EPA Science Inventory

An objective of the U.S. Environmental Protection Agency is to develop innovative approaches and decision support tools for the safety assessment of current and emerging chemicals in relation to their impact on the environment. To support this goal, there is a compelling need for...

Low noise charge ramp electrometer

DOEpatents

Morgan, John P.; Piper, Thomas C.

1992-01-01

An electrometer capable of measuring small currents without the use of a feedback resistor which tends to contribute a large noise factor to the measured data. The electrometer eliminates the feedback resistor through the use of a feedback capacitor located across the electrometer amplifier. The signal from the electrometer amplifier is transferred to a electrometer buffer amplifier which serves to transfer the signal to several receptors. If the electrometer amplifier is approaching saturation, the buffer amplifier signals a reset discriminator which energizes a coil whose magnetic field closes a magnetic relay switch which in turn resets or zeros the feedback capacitor. In turn, a reset complete discriminator restarts the measurement process when the electrometer amplifier approaches its initial condition. The buffer amplifier also transmits the voltage signal from the electrometer amplifier to a voltage-to-frequency converter. The signals from the voltage-to-frequency converter are counted over a fixed period of time and the information is relayed to a data processor. The timing and sequencing of the small current measuring system is under the control of a sequence control logic unit.

Low noise charge ramp electrometer

DOEpatents

Morgan, J.P.; Piper, T.C.

1992-10-06

An electrometer capable of measuring small currents without the use of a feedback resistor which tends to contribute a large noise factor to the measured data. The electrometer eliminates the feedback resistor through the use of a feedback capacitor located across the electrometer amplifier. The signal from the electrometer amplifier is transferred to a electrometer buffer amplifier which serves to transfer the signal to several receptors. If the electrometer amplifier is approaching saturation, the buffer amplifier signals a reset discriminator which energizes a coil whose magnetic field closes a magnetic relay switch which in turn resets or zeros the feedback capacitor. In turn, a reset complete discriminator restarts the measurement process when the electrometer amplifier approaches its initial condition. The buffer amplifier also transmits the voltage signal from the electrometer amplifier to a voltage-to-frequency converter. The signals from the voltage-to-frequency converter are counted over a fixed period of time and the information is relayed to a data processor. The timing and sequencing of the small current measuring system is under the control of a sequence control logic unit. 2 figs.

A hybrid spatiotemporal and Hough-based motion estimation approach applied to magnetic resonance cardiac images

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Sroubek, F.; Ledesma-Carbayo, M. J.; Santos, A.

2006-08-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation to the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach, more specifically on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The later is a well-known line and shape detection method very robust against incomplete data and noise. The rationale of using the HT in this context is because it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results with synthetic sequences are compared against an implementation of the variational technique for local and global motion estimation, where it is shown that the results obtained here are accurate and robust to noise degradations. Real cardiac magnetic resonance images have been tested and evaluated with the current method.

Yeast One-Hybrid Gγ Recruitment System for Identification of Protein Lipidation Motifs

PubMed Central

Fukuda, Nobuo; Doi, Motomichi; Honda, Shinya

2013-01-01

Fatty acids and isoprenoids can be covalently attached to a variety of proteins. These lipid modifications regulate protein structure, localization and function. Here, we describe a yeast one-hybrid approach based on the Gγ recruitment system that is useful for identifying sequence motifs those influence lipid modification to recruit proteins to the plasma membrane. Our approach facilitates the isolation of yeast cells expressing lipid-modified proteins via a simple and easy growth selection assay utilizing G-protein signaling that induces diploid formation. In the current study, we selected the N-terminal sequence of Gα subunits as a model case to investigate dual lipid modification, i.e., myristoylation and palmitoylation, a modification that is widely conserved from yeast to higher eukaryotes. Our results suggest that both lipid modifications are required for restoration of G-protein signaling. Although we could not differentiate between myristoylation and palmitoylation, N-terminal position 7 and 8 play some critical role. Moreover, we tested the preference for specific amino-acid residues at position 7 and 8 using library-based screening. This new approach will be useful to explore protein-lipid associations and to determine the corresponding sequence motifs. PMID:23922919

Computational approaches to predict bacteriophage–host relationships

PubMed Central

Edwards, Robert A.; McNair, Katelyn; Faust, Karoline; Raes, Jeroen; Dutilh, Bas E.

2015-01-01

Metagenomics has changed the face of virus discovery by enabling the accurate identification of viral genome sequences without requiring isolation of the viruses. As a result, metagenomic virus discovery leaves the first and most fundamental question about any novel virus unanswered: What host does the virus infect? The diversity of the global virosphere and the volumes of data obtained in metagenomic sequencing projects demand computational tools for virus–host prediction. We focus on bacteriophages (phages, viruses that infect bacteria), the most abundant and diverse group of viruses found in environmental metagenomes. By analyzing 820 phages with annotated hosts, we review and assess the predictive power of in silico phage–host signals. Sequence homology approaches are the most effective at identifying known phage–host pairs. Compositional and abundance-based methods contain significant signal for phage–host classification, providing opportunities for analyzing the unknowns in viral metagenomes. Together, these computational approaches further our knowledge of the interactions between phages and their hosts. Importantly, we find that all reviewed signals significantly link phages to their hosts, illustrating how current knowledge and insights about the interaction mechanisms and ecology of coevolving phages and bacteria can be exploited to predict phage–host relationships, with potential relevance for medical and industrial applications. PMID:26657537

Translational genomics for plant breeding with the genome sequence explosion.

PubMed

Kang, Yang Jae; Lee, Taeyoung; Lee, Jayern; Shim, Sangrea; Jeong, Haneul; Satyawan, Dani; Kim, Moon Young; Lee, Suk-Ha

2016-04-01

The use of next-generation sequencers and advanced genotyping technologies has propelled the field of plant genomics in model crops and plants and enhanced the discovery of hidden bridges between genotypes and phenotypes. The newly generated reference sequences of unstudied minor plants can be annotated by the knowledge of model plants via translational genomics approaches. Here, we reviewed the strategies of translational genomics and suggested perspectives on the current databases of genomic resources and the database structures of translated information on the new genome. As a draft picture of phenotypic annotation, translational genomics on newly sequenced plants will provide valuable assistance for breeders and researchers who are interested in genetic studies. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Exploring microbial dark matter to resolve the deep archaeal ancestry of eukaryotes

DOE PAGES

Saw, Jimmy H.; Spang, Anja; Zaremba-Niedzwiedzka, Katarzyna; ...

2015-08-31

The origin of eukaryotes represents an enigmatic puzzle, which is still lacking a number of essential pieces. Whereas it is currently accepted that the process of eukaryogenesis involved an interplay between a host cell and an alphaproteobacterial endosymbiont, we currently lack detailed information regarding the identity and nature of these players. A number of studies have provided increasing support for the emergence of the eukaryotic host cell from within the archaeal domain of life, displaying a specific affiliation with the archaeal TACK superphylum. Recent studies have shown that genomic exploration of yet-uncultivated archaea, the so-called archaeal 'dark matter', is ablemore » to provide unprecedented insights into the process of eukaryogenesis. Here, we provide an overview of state-of-the-art cultivation-independent approaches, and demonstrate how these methods were used to obtain draft genome sequences of several novel members of the TACK superphylum, including Lokiarchaeum, two representatives of the Miscellaneous Crenarchaeotal Group (Bathyarchaeota), and a Korarchaeum-related lineage. In conclusion, the maturation of cultivation-independent genomics approaches, as well as future developments in next-generation sequencing technologies, will revolutionize our current view of microbial evolution and diversity, and provide profound new insights into the early evolution of life, including the enigmatic origin of the eukaryotic cell.« less

Exploring microbial dark matter to resolve the deep archaeal ancestry of eukaryotes

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

Saw, Jimmy H.; Spang, Anja; Zaremba-Niedzwiedzka, Katarzyna

The origin of eukaryotes represents an enigmatic puzzle, which is still lacking a number of essential pieces. Whereas it is currently accepted that the process of eukaryogenesis involved an interplay between a host cell and an alphaproteobacterial endosymbiont, we currently lack detailed information regarding the identity and nature of these players. A number of studies have provided increasing support for the emergence of the eukaryotic host cell from within the archaeal domain of life, displaying a specific affiliation with the archaeal TACK superphylum. Recent studies have shown that genomic exploration of yet-uncultivated archaea, the so-called archaeal 'dark matter', is ablemore » to provide unprecedented insights into the process of eukaryogenesis. Here, we provide an overview of state-of-the-art cultivation-independent approaches, and demonstrate how these methods were used to obtain draft genome sequences of several novel members of the TACK superphylum, including Lokiarchaeum, two representatives of the Miscellaneous Crenarchaeotal Group (Bathyarchaeota), and a Korarchaeum-related lineage. In conclusion, the maturation of cultivation-independent genomics approaches, as well as future developments in next-generation sequencing technologies, will revolutionize our current view of microbial evolution and diversity, and provide profound new insights into the early evolution of life, including the enigmatic origin of the eukaryotic cell.« less

The use of piezocone tests for high-resolution stratigraphy of Quaternary sediment sequences in the Brazilian coast.

PubMed

de Mio, Giuliano; Giacheti, Heraldo L

2007-03-01

Correlations between mapping units of costal sedimentary basin and interpretation of piezocone test results are presented and discussed based on examples from Caravelas strandplain, (State of Bahia), Paranaguá (State of Paraná) and Guarujá bays (State of São Paulo), Brazil. Recognizing that the sedimentary environment was mainly controlled by sea level fluctuations led to the interpretation of transgressive and regressive sedimentary sequences, which is in a good agreement with the sea level fluctuation curves currently accepted for these regions. The interpretation of piezocone test results shows that the sedimentary sequences of Caravelas and Guarujá sites are similar and they have a good correlation to the sea level fluctuation curve accepted for Salvador region, State of Bahia. On the other hand, the piezocone test results from Paranaguá site indicate a different sedimentary sequence from the previous ones, relating to the sea level fluctuation curve accepted for Paranaguá region. The results show the high applicability of piezocone testing for stratigraphical logging and suggest that it is possible to integrate it with other current techniques used for paleo-environmental studies in Brazil, in accordance with recent approaches used in international research on the subject.

Design and cloning strategies for constructing shRNA expression vectors

PubMed Central

McIntyre, Glen J; Fanning, Gregory C

2006-01-01

Background Short hairpin RNA (shRNA) encoded within an expression vector has proven an effective means of harnessing the RNA interference (RNAi) pathway in mammalian cells. A survey of the literature revealed that shRNA vector construction can be hindered by high mutation rates and the ensuing sequencing is often problematic. Current options for constructing shRNA vectors include the use of annealed complementary oligonucleotides (74 % of surveyed studies), a PCR approach using hairpin containing primers (22 %) and primer extension of hairpin templates (4 %). Results We considered primer extension the most attractive method in terms of cost. However, in initial experiments we encountered a mutation frequency of 50 % compared to a reported 20 – 40 % for other strategies. By modifying the technique to be an isothermal reaction using the DNA polymerase Phi29, we reduced the error rate to 10 %, making primer extension the most efficient and cost-effective approach tested. We also found that inclusion of a restriction site in the loop could be exploited for confirming construct integrity by automated sequencing, while maintaining intended gene suppression. Conclusion In this study we detail simple improvements for constructing and sequencing shRNA that overcome current limitations. We also compare the advantages of our solutions against proposed alternatives. Our technical modifications will be of tangible benefit to researchers looking for a more efficient and reliable shRNA construction process. PMID:16396676

Integrating linear optimization with structural modeling to increase HIV neutralization breadth.

PubMed

Sevy, Alexander M; Panda, Swetasudha; Crowe, James E; Meiler, Jens; Vorobeychik, Yevgeniy

2018-02-01

Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.

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

PubMed

Broughton, James P; Pasquinelli, Amy E

2016-04-04

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

Low-Cost Ultra-Wide Genotyping Using Roche/454 Pyrosequencing for Surveillance of HIV Drug Resistance

PubMed Central

Dudley, Dawn M.; Chin, Emily N.; Bimber, Benjamin N.; Sanabani, Sabri S.; Tarosso, Leandro F.; Costa, Priscilla R.; Sauer, Mariana M.; Kallas, Esper G.; O.’Connor, David H.

2012-01-01

Background Great efforts have been made to increase accessibility of HIV antiretroviral therapy (ART) in low and middle-income countries. The threat of wide-scale emergence of drug resistance could severely hamper ART scale-up efforts. Population-based surveillance of transmitted HIV drug resistance ensures the use of appropriate first-line regimens to maximize efficacy of ART programs where drug options are limited. However, traditional HIV genotyping is extremely expensive, providing a cost barrier to wide-scale and frequent HIV drug resistance surveillance. Methods/Results We have developed a low-cost laboratory-scale next-generation sequencing-based genotyping method to monitor drug resistance. We designed primers specifically to amplify protease and reverse transcriptase from Brazilian HIV subtypes and developed a multiplexing scheme using multiplex identifier tags to minimize cost while providing more robust data than traditional genotyping techniques. Using this approach, we characterized drug resistance from plasma in 81 HIV infected individuals collected in São Paulo, Brazil. We describe the complexities of analyzing next-generation sequencing data and present a simplified open-source workflow to analyze drug resistance data. From this data, we identified drug resistance mutations in 20% of treatment naïve individuals in our cohort, which is similar to frequencies identified using traditional genotyping in Brazilian patient samples. Conclusion The developed ultra-wide sequencing approach described here allows multiplexing of at least 48 patient samples per sequencing run, 4 times more than the current genotyping method. This method is also 4-fold more sensitive (5% minimal detection frequency vs. 20%) at a cost 3–5× less than the traditional Sanger-based genotyping method. Lastly, by using a benchtop next-generation sequencer (Roche/454 GS Junior), this approach can be more easily implemented in low-resource settings. This data provides proof-of-concept that next-generation HIV drug resistance genotyping is a feasible and low-cost alternative to current genotyping methods and may be particularly beneficial for in-country surveillance of transmitted drug resistance. PMID:22574170

Identification and correction of abnormal, incomplete and mispredicted proteins in public databases.

PubMed

Nagy, Alinda; Hegyi, Hédi; Farkas, Krisztina; Tordai, Hedvig; Kozma, Evelin; Bányai, László; Patthy, László

2008-08-27

Despite significant improvements in computational annotation of genomes, sequences of abnormal, incomplete or incorrectly predicted genes and proteins remain abundant in public databases. Since the majority of incomplete, abnormal or mispredicted entries are not annotated as such, these errors seriously affect the reliability of these databases. Here we describe the MisPred approach that may provide an efficient means for the quality control of databases. The current version of the MisPred approach uses five distinct routines for identifying abnormal, incomplete or mispredicted entries based on the principle that a sequence is likely to be incorrect if some of its features conflict with our current knowledge about protein-coding genes and proteins: (i) conflict between the predicted subcellular localization of proteins and the absence of the corresponding sequence signals; (ii) presence of extracellular and cytoplasmic domains and the absence of transmembrane segments; (iii) co-occurrence of extracellular and nuclear domains; (iv) violation of domain integrity; (v) chimeras encoded by two or more genes located on different chromosomes. Analyses of predicted EnsEMBL protein sequences of nine deuterostome (Homo sapiens, Mus musculus, Rattus norvegicus, Monodelphis domestica, Gallus gallus, Xenopus tropicalis, Fugu rubripes, Danio rerio and Ciona intestinalis) and two protostome species (Caenorhabditis elegans and Drosophila melanogaster) have revealed that the absence of expected signal peptides and violation of domain integrity account for the majority of mispredictions. Analyses of sequences predicted by NCBI's GNOMON annotation pipeline show that the rates of mispredictions are comparable to those of EnsEMBL. Interestingly, even the manually curated UniProtKB/Swiss-Prot dataset is contaminated with mispredicted or abnormal proteins, although to a much lesser extent than UniProtKB/TrEMBL or the EnsEMBL or GNOMON-predicted entries. MisPred works efficiently in identifying errors in predictions generated by the most reliable gene prediction tools such as the EnsEMBL and NCBI's GNOMON pipelines and also guides the correction of errors. We suggest that application of the MisPred approach will significantly improve the quality of gene predictions and the associated databases.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Rational design of DNA sequences for nanotechnology, microarrays and molecular computers using Eulerian graphs.

PubMed

Pancoska, Petr; Moravek, Zdenek; Moll, Ute M

2004-01-01

Nucleic acids are molecules of choice for both established and emerging nanoscale technologies. These technologies benefit from large functional densities of 'DNA processing elements' that can be readily manufactured. To achieve the desired functionality, polynucleotide sequences are currently designed by a process that involves tedious and laborious filtering of potential candidates against a series of requirements and parameters. Here, we present a complete novel methodology for the rapid rational design of large sets of DNA sequences. This method allows for the direct implementation of very complex and detailed requirements for the generated sequences, thus avoiding 'brute force' filtering. At the same time, these sequences have narrow distributions of melting temperatures. The molecular part of the design process can be done without computer assistance, using an efficient 'human engineering' approach by drawing a single blueprint graph that represents all generated sequences. Moreover, the method eliminates the necessity for extensive thermodynamic calculations. Melting temperature can be calculated only once (or not at all). In addition, the isostability of the sequences is independent of the selection of a particular set of thermodynamic parameters. Applications are presented for DNA sequence designs for microarrays, universal microarray zip sequences and electron transfer experiments.

How mass spectrometric approaches applied to bacterial identification have revolutionized the study of human gut microbiota.

PubMed

Grégory, Dubourg; Chaudet, Hervé; Lagier, Jean-Christophe; Raoult, Didier

2018-03-01

Describing the human hut gut microbiota is one the most exciting challenges of the 21 st century. Currently, high-throughput sequencing methods are considered as the gold standard for this purpose, however, they suffer from several drawbacks, including their inability to detect minority populations. The advent of mass-spectrometric (MS) approaches to identify cultured bacteria in clinical microbiology enabled the creation of the culturomics approach, which aims to establish a comprehensive repertoire of cultured prokaryotes from human specimens using extensive culture conditions. Areas covered: This review first underlines how mass spectrometric approaches have revolutionized clinical microbiology. It then highlights the contribution of MS-based methods to culturomics studies, paying particular attention to the extension of the human gut microbiota repertoire through the discovery of new bacterial species. Expert commentary: MS-based approaches have enabled cultivation methods to be resuscitated to study the human gut microbiota and thus to fill in the blanks left by high-throughput sequencing methods in terms of culturing minority populations. Continued efforts to recover new taxa using culture methods, combined with their rapid implementation in genomic databases, would allow for an exhaustive analysis of the gut microbiota through the use of a comprehensive approach.

On the Origin of Protein Superfamilies and Superfolds

NASA Astrophysics Data System (ADS)

Magner, Abram; Szpankowski, Wojciech; Kihara, Daisuke

2015-02-01

Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are found to follow a power law, consistent with those observed for proteins in nature. Importantly, the skewed distributions of sequences and folds are suggested to have different origins: the skewed distribution of sequences is due to evolutionary pressure to achieve efficient coding of necessary folds, whereas that of folds is based on the thermodynamic stability of folds. The current study provides a new information theoretic framework for proteins that could be widely applied for understanding protein sequences, structures, functions, and interactions.

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

PubMed

Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

2015-01-20

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

BioMaS: a modular pipeline for Bioinformatic analysis of Metagenomic AmpliconS.

PubMed

Fosso, Bruno; Santamaria, Monica; Marzano, Marinella; Alonso-Alemany, Daniel; Valiente, Gabriel; Donvito, Giacinto; Monaco, Alfonso; Notarangelo, Pasquale; Pesole, Graziano

2015-07-01

Substantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche. If the investigation is aimed only at the microbiome taxonomic structure, a target-based metagenomic approach, here also referred as Meta-barcoding, is generally applied. This approach commonly involves the selective amplification of a species-specific genetic marker (DNA meta-barcode) in the whole taxonomic range of interest and the exploration of its taxon-related variants through High-Throughput Sequencing (HTS) technologies. The accessibility to proper computational systems for the large-scale bioinformatic analysis of HTS data represents, currently, one of the major challenges in advanced Meta-barcoding projects. BioMaS (Bioinformatic analysis of Metagenomic AmpliconS) is a new bioinformatic pipeline designed to support biomolecular researchers involved in taxonomic studies of environmental microbial communities by a completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data upload and cleaning to final taxonomic identification, that are absolutely required in an appropriately designed Meta-barcoding HTS-based experiment. In its current version, BioMaS allows the analysis of both bacterial and fungal environments starting directly from the raw sequencing data from either Roche 454 or Illumina HTS platforms, following two alternative paths, respectively. BioMaS is implemented into a public web service available at https://recasgateway.ba.infn.it/ and is also available in Galaxy at http://galaxy.cloud.ba.infn.it:8080 (only for Illumina data). BioMaS is a friendly pipeline for Meta-barcoding HTS data analysis specifically designed for users without particular computing skills. A comparative benchmark, carried out by using a simulated dataset suitably designed to broadly represent the currently known bacterial and fungal world, showed that BioMaS outperforms QIIME and MOTHUR in terms of extent and accuracy of deep taxonomic sequence assignments.

Molecular Diagnosis of Usher Syndrome: Application of Two Different Next Generation Sequencing-Based Procedures

PubMed Central

Licastro, Danilo; Mutarelli, Margherita; Peluso, Ivana; Neveling, Kornelia; Wieskamp, Nienke; Rispoli, Rossella; Vozzi, Diego; Athanasakis, Emmanouil; D'Eustacchio, Angela; Pizzo, Mariateresa; D'Amico, Francesca; Ziviello, Carmela; Simonelli, Francesca; Fabretto, Antonella; Scheffer, Hans; Gasparini, Paolo; Banfi, Sandro; Nigro, Vincenzo

2012-01-01

Usher syndrome (USH) is a clinically and genetically heterogeneous disorder characterized by visual and hearing impairments. Clinically, it is subdivided into three subclasses with nine genes identified so far. In the present study, we investigated whether the currently available Next Generation Sequencing (NGS) technologies are already suitable for molecular diagnostics of USH. We analyzed a total of 12 patients, most of which were negative for previously described mutations in known USH genes upon primer extension-based microarray genotyping. We enriched the NGS template either by whole exome capture or by Long-PCR of the known USH genes. The main NGS sequencing platforms were used: SOLiD for whole exome sequencing, Illumina (Genome Analyzer II) and Roche 454 (GS FLX) for the Long-PCR sequencing. Long-PCR targeting was more efficient with up to 94% of USH gene regions displaying an overall coverage higher than 25×, whereas whole exome sequencing yielded a similar coverage for only 50% of those regions. Overall this integrated analysis led to the identification of 11 novel sequence variations in USH genes (2 homozygous and 9 heterozygous) out of 18 detected. However, at least two cases were not genetically solved. Our result highlights the current limitations in the diagnostic use of NGS for USH patients. The limit for whole exome sequencing is linked to the need of a strong coverage and to the correct interpretation of sequence variations with a non obvious, pathogenic role, whereas the targeted approach suffers from the high genetic heterogeneity of USH that may be also caused by the presence of additional causative genes yet to be identified. PMID:22952768

A multi-model approach to nucleic acid-based drug development.

PubMed

Gautherot, Isabelle; Sodoyer, Regís

2004-01-01

With the advent of functional genomics and the shift of interest towards sequence-based therapeutics, the past decades have witnessed intense research efforts on nucleic acid-mediated gene regulation technologies. Today, RNA interference is emerging as a groundbreaking discovery, holding promise for development of genetic modulators of unprecedented potency. Twenty-five years after the discovery of antisense RNA and ribozymes, gene control therapeutics are still facing developmental difficulties, with only one US FDA-approved antisense drug currently available in the clinic. Limited predictability of target site selection models is recognized as one major stumbling block that is shared by all of the so-called complementary technologies, slowing the progress towards a commercial product. Currently employed in vitro systems for target site selection include RNAse H-based mapping, antisense oligonucleotide microarrays, and functional screening approaches using libraries of catalysts with randomized target-binding arms to identify optimal ribozyme/DNAzyme cleavage sites. Individually, each strategy has its drawbacks from a drug development perspective. Utilization of message-modulating sequences as therapeutic agents requires that their action on a given target transcript meets criteria of potency and selectivity in the natural physiological environment. In addition to sequence-dependent characteristics, other factors will influence annealing reactions and duplex stability, as well as nucleic acid-mediated catalysis. Parallel consideration of physiological selection systems thus appears essential for screening for nucleic acid compounds proposed for therapeutic applications. Cellular message-targeting studies face issues relating to efficient nucleic acid delivery and appropriate analysis of response. For reliability and simplicity, prokaryotic systems can provide a rapid and cost-effective means of studying message targeting under pseudo-cellular conditions, but such approaches also have limitations. To streamline nucleic acid drug discovery, we propose a multi-model strategy integrating high-throughput-adapted bacterial screening, followed by reporter-based and/or natural cellular models and potentially also in vitro assays for characterization of the most promising candidate sequences, before final in vivo testing.

A pragmatic approach to infants with Robin sequence: a retrospective cohort study and presence of a treatment algorithm.

PubMed

Paes, Emma C; van Nunen, Daan P F; Speleman, Lucienne; Muradin, Marvick S M; Smarius, Bram; Kon, Moshe; Mink van der Molen, Aebele B; van der Molen, Aebele B Mink; Niers, Titia L E M; Veldhoen, Esther S; Breugem, Corstiaan C

2015-11-01

Initial approaches to and treatments of infants with Robin sequence (RS) is diverse and inconsistent. The care of these sometimes critically ill infants involves many different medical specialties, which can make the decision process complex and difficult. To optimize the care of infants with RS, we present our institution's approach and a review of the current literature. A retrospective cohort study was conducted among 75 infants diagnosed with RS and managed at our institution in the 1996-2012 period. Additionally, the conducted treatment regimen in this paper was discussed with recent literature describing the approach of infants with RS. Forty-four infants (59%) were found to have been treated conservatively. A significant larger proportion of nonisolated RS infants than isolated RS infants needed surgical intervention (53 vs. 25%, p = .014). A mandibular distraction was conducted in 24% (n = 18) of cases, a tracheotomy in 9% (n = 7), and a tongue-lip adhesion in 8% (n = 6). Seventy-seven percent of all infants had received temporary nasogastric tube feeding. The literature review of 31 studies showed that initial examinations and the indications to perform a surgical intervention varied and were often not clearly described. RS is a heterogenic group with a wide spectrum of associated anomalies. As a result, the decisional process is challenging, and a multidisciplinary approach to treatment is desirable. Current treatment options in literature vary, and a more uniform approach is recommended. We provide a comprehensive and pragmatic approach to the analysis and treatment of infants with RS, which could serve as useful guidance in other clinics.

Genetic engineering of industrial Saccharomyces cerevisiae strains using a selection/counter-selection approach.

PubMed

Kutyna, Dariusz R; Cordente, Antonio G; Varela, Cristian

2014-01-01

Gene modification of laboratory yeast strains is currently a very straightforward task thanks to the availability of the entire yeast genome sequence and the high frequency with which yeast can incorporate exogenous DNA into its genome. Unfortunately, laboratory strains do not perform well in industrial settings, indicating the need for strategies to modify industrial strains to enable strain development for industrial applications. Here we describe approaches we have used to genetically modify industrial strains used in winemaking.

Assessing pooled BAC and whole genome shotgun strategies for assembly of complex genomes

PubMed Central

2011-01-01

Background We investigate if pooling BAC clones and sequencing the pools can provide for more accurate assembly of genome sequences than the "whole genome shotgun" (WGS) approach. Furthermore, we quantify this accuracy increase. We compare the pooled BAC and WGS approaches using in silico simulations. Standard measures of assembly quality focus on assembly size and fragmentation, which are desirable for large whole genome assemblies. We propose additional measures enabling easy and visual comparison of assembly quality, such as rearrangements and redundant sequence content, relative to the known target sequence. Results The best assembly quality scores were obtained using 454 coverage of 15× linear and 5× paired (3kb insert size) reads (15L-5P) on Arabidopsis. This regime gave similarly good results on four additional plant genomes of very different GC and repeat contents. BAC pooling improved assembly scores over WGS assembly, coverage and redundancy scores improving the most. Conclusions BAC pooling works better than WGS, however, both require a physical map to order the scaffolds. Pool sizes up to 12Mbp work well, suggesting this pooling density to be effective in medium-scale re-sequencing applications such as targeted sequencing of QTL intervals for candidate gene discovery. Assuming the current Roche/454 Titanium sequencing limitations, a 12 Mbp region could be re-sequenced with a full plate of linear reads and a half plate of paired-end reads, yielding 15L-5P coverage after read pre-processing. Our simulation suggests that massively over-sequencing may not improve accuracy. Our scoring measures can be used generally to evaluate and compare results of simulated genome assemblies. PMID:21496274

Optimizing Illumina next-generation sequencing library preparation for extremely AT-biased genomes.

PubMed

Oyola, Samuel O; Otto, Thomas D; Gu, Yong; Maslen, Gareth; Manske, Magnus; Campino, Susana; Turner, Daniel J; Macinnis, Bronwyn; Kwiatkowski, Dominic P; Swerdlow, Harold P; Quail, Michael A

2012-01-03

Massively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences. We have used our optimized conditions in parallel with standard methods to prepare Illumina sequencing libraries from a non-clinical and a clinical isolate (containing ~53% host contamination). By analyzing and comparing the quality of sequence data generated, we show that our optimized conditions that involve a PCR additive (TMAC), produces amplified libraries with improved coverage of extremely AT-rich regions and reduced bias toward GC neutral templates. We have developed a robust and optimized Next-Generation Sequencing library amplification method suitable for extremely AT-rich genomes. The new amplification conditions significantly reduce bias and retain the complexity of either extremes of base composition. This development will greatly benefit sequencing clinical samples that often require amplification due to low mass of DNA starting material.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations.

PubMed

Fuentes-Pardo, Angela P; Ruzzante, Daniel E

2017-10-01

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology. © 2017 John Wiley & Sons Ltd.

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

PubMed

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

PubMed Central

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing.

PubMed

Yu, Stephanie C Y; Chan, K C Allen; Zheng, Yama W L; Jiang, Peiyong; Liao, Gary J W; Sun, Hao; Akolekar, Ranjit; Leung, Tak Y; Go, Attie T J I; van Vugt, John M G; Minekawa, Ryoko; Oudejans, Cees B M; Nicolaides, Kypros H; Chiu, Rossa W K; Lo, Y M Dennis

2014-06-10

Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring.

Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing

PubMed Central

Yu, Stephanie C. Y.; Chan, K. C. Allen; Zheng, Yama W. L.; Jiang, Peiyong; Liao, Gary J. W.; Sun, Hao; Akolekar, Ranjit; Leung, Tak Y.; Go, Attie T. J. I.; van Vugt, John M. G.; Minekawa, Ryoko; Oudejans, Cees B. M.; Nicolaides, Kypros H.; Chiu, Rossa W. K.; Lo, Y. M. Dennis

2014-01-01

Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring. PMID:24843150

Performance evaluation of Sanger sequencing for the diagnosis of primary hyperoxaluria and comparison with targeted next generation sequencing

PubMed Central

Williams, Emma L; Bagg, Eleanor A L; Mueller, Michael; Vandrovcova, Jana; Aitman, Timothy J; Rumsby, Gill

2015-01-01

Definitive diagnosis of primary hyperoxaluria (PH) currently utilizes sequential Sanger sequencing of the AGXT, GRPHR, and HOGA1 genes but efficacy is unproven. This analysis is time-consuming, relatively expensive, and delays in diagnosis and inappropriate treatment can occur if not pursued early in the diagnostic work-up. We reviewed testing outcomes of Sanger sequencing in 200 consecutive patient samples referred for analysis. In addition, the Illumina Truseq custom amplicon system was evaluated for paralleled next-generation sequencing (NGS) of AGXT,GRHPR, and HOGA1 in 90 known PH patients. AGXT sequencing was requested in all patients, permitting a diagnosis of PH1 in 50%. All remaining patients underwent targeted exon sequencing of GRHPR and HOGA1 with 8% diagnosed with PH2 and 8% with PH3. Complete sequencing of both GRHPR and HOGA1 was not requested in 25% of patients referred leaving their diagnosis in doubt. NGS analysis showed 98% agreement with Sanger sequencing and both approaches had 100% diagnostic specificity. Diagnostic sensitivity of Sanger sequencing was 98% and for NGS it was 97%. NGS has comparable diagnostic performance to Sanger sequencing for the diagnosis of PH and, if implemented, would screen for all forms of PH simultaneously ensuring prompt diagnosis at decreased cost. PMID:25629080

TDRSS telecommunications system, PN code analysis

NASA Technical Reports Server (NTRS)

Dixon, R.; Gold, R.; Kaiser, F.

1976-01-01

The pseudo noise (PN) codes required to support the TDRSS telecommunications services are analyzed and the impact of alternate coding techniques on the user transponder equipment, the TDRSS equipment, and all factors that contribute to the acquisition and performance of these telecommunication services is assessed. Possible alternatives to the currently proposed hybrid FH/direct sequence acquisition procedures are considered and compared relative to acquisition time, implementation complexity, operational reliability, and cost. The hybrid FH/direct sequence technique is analyzed and rejected in favor of a recommended approach which minimizes acquisition time and user transponder complexity while maximizing probability of acquisition and overall link reliability.

Learning Multisensory Representations

DTIC Science & Technology

2016-05-23

public release. Erdogan , G., Yildirim, I., & Jacobs, R. A. (2014). Transfer of object shape knowledge across visual and haptic modalities. Proceedings...2014). The adaptive nature of visual working memory. Current Directions in Psychological Science, 23, 164-170. Erdogan , G., Yildirim, I...sequence category knowledge: A probabilistic language of thought approach. Psychonomic Bulletin and Review, 22, 673-686. Erdogan , G., Chen, Q., Garcea, F

76 FR 28990 - Ultra High Throughput Sequencing for Clinical Diagnostic Applications-Approaches To Assess...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-19

...: 900). If you have never attended a Connect Pro meeting before, test your connection at: https://collaboration.fda.gov/common/help/en/support/meeting_test.htm . To get a quick overview of the Connect Pro... technologies are currently extensively used in research and are entering clinical diagnostic use; they are...

Conserved sequences in the current strains of HIV-1 subtype A in Russia are effectively targeted by artificial RNAi in vitro.

PubMed

Tchurikov, Nickolai A; Fedoseeva, Daria M; Gashnikova, Natalya M; Sosin, Dmitri V; Gorbacheva, Maria A; Alembekov, Ildar R; Chechetkin, Vladimir R; Kravatsky, Yuri V; Kretova, Olga V

2016-05-25

Highly active antiretroviral therapy has greatly reduced the morbidity and mortality of AIDS. However, many of the antiretroviral drugs are toxic with long-term use, and all currently used anti-HIV agents generate drug-resistant mutants. Therefore, there is a great need for new approaches to AIDS therapy. RNAi is a powerful means of inhibiting HIV-1 production in human cells. We propose to use RNAi for gene therapy of HIV/AIDS. Previously we identified a number of new biologically active siRNAs targeting several moderately conserved regions in HIV-1 transcripts. Here we analyze the heterogeneity of nucleotide sequences in three RNAi targets in sequences encoding the reverse transcriptase and integrase domains of current isolates of HIV-1 subtype A in Russia. These data were used to generate genetic constructs expressing short hairpin RNAs 28-30-bp in length that could be processed in cells into siRNAs. After transfection of the constructs we observed siRNAs that efficiently attacked the selected targets. We expect that targeting several viral genes important for HIV-1 reproduction will help overcome the problem of viral adaptation and will prevent the appearance of RNAi escape mutants in current virus strains, an important feature of gene therapy of HIV/AIDS. Copyright © 2016 Elsevier B.V. All rights reserved.

DNA barcode-based delineation of putative species: efficient start for taxonomic workflows

PubMed Central

Kekkonen, Mari; Hebert, Paul D N

2014-01-01

The analysis of DNA barcode sequences with varying techniques for cluster recognition provides an efficient approach for recognizing putative species (operational taxonomic units, OTUs). This approach accelerates and improves taxonomic workflows by exposing cryptic species and decreasing the risk of synonymy. This study tested the congruence of OTUs resulting from the application of three analytical methods (ABGD, BIN, GMYC) to sequence data for Australian hypertrophine moths. OTUs supported by all three approaches were viewed as robust, but 20% of the OTUs were only recognized by one or two of the methods. These OTUs were examined for three criteria to clarify their status. Monophyly and diagnostic nucleotides were both uninformative, but information on ranges was useful as sympatric sister OTUs were viewed as distinct, while allopatric OTUs were merged. This approach revealed 124 OTUs of Hypertrophinae, a more than twofold increase from the currently recognized 51 species. Because this analytical protocol is both fast and repeatable, it provides a valuable tool for establishing a basic understanding of species boundaries that can be validated with subsequent studies. PMID:24479435

Genomics: The Science and Technology Behind the Human Genome Project (by Charles R. Cantor and Cassandra L. Smith)

NASA Astrophysics Data System (ADS)

Serra, Reviewed By Martin J.

2000-01-01

Genomics is one of the most rapidly expanding areas of science. This book is an outgrowth of a series of lectures given by one of the former heads (CRC) of the Human Genome Initiative. The book is designed to reach a wide audience, from biologists with little chemical or physical science background through engineers, computer scientists, and physicists with little current exposure to the chemical or biological principles of genetics. The text starts with a basic review of the chemical and biological properties of DNA. However, without either a biochemistry background or a supplemental biochemistry text, this chapter and much of the rest of the text would be difficult to digest. The second chapter is designed to put DNA into the context of the larger chromosomal unit. Specialized chromosomal structures and sequences (centromeres, telomeres) are introduced, leading to a section on chromosome organization and purification. The next 4 chapters cover the physical (hybridization, electrophoresis), chemical (polymerase chain reaction), and biological (genetic) techniques that provide the backbone of genomic analysis. These chapters cover in significant detail the fundamental principles underlying each technique and provide a firm background for the remainder of the text. Chapters 7­9 consider the need and methods for the development of physical maps. Chapter 7 primarily discusses chromosomal localization techniques, including in situ hybridization, FISH, and chromosome paintings. The next two chapters focus on the development of libraries and clones. In particular, Chapter 9 considers the limitations of current mapping and clone production. The current state and future of DNA sequencing is covered in the next three chapters. The first considers the current methods of DNA sequencing - especially gel-based methods of analysis, although other possible approaches (mass spectrometry) are introduced. Much of the chapter addresses the limitations of current methods, including analysis of error in sequencing and current bottlenecks in the sequencing effort. The next chapter describes the steps necessary to scale current technologies for the sequencing of entire genomes. Chapter 12 examines alternate methods for DNA sequencing. Initially, methods of single-molecule sequencing and sequencing by microscopy are introduced; the majority of the chapter is devoted to the development of DNA sequencing methods using chip microarrays and hybridization. The remaining chapters (13-15) consider the uses and analysis of DNA sequence information. The initial focus is on the identification of genes. Several examples are given of the use of DNA sequence information for diagnosis of inherited or infectious diseases. The sequence-specific manipulation of DNA is discussed in Chapter 14. The final chapter deals with the implications of large-scale sequencing, including methods for identifying genes and finding errors in DNA sequences, to the development of computer algorithms for the interpretation of DNA sequence information. The text figures are black and white line drawings that, although clearly done, seem a bit primitive for 1999. While I appreciated the simplicity of the drawings, many students accustomed to more colorful presentations will find them wanting. The four color figures in the center of the text seem an afterthought and add little to the text's clarity. Each chapter has a set of additional reading sources, mostly primary sources. Often, specialized topics are offset into boxes that provide clarification and amplification without cluttering the text. An appendix includes a list of the Web-based database resources. As an undergraduate instructor who has previously taught biochemistry, molecular biology, and a course on the human genome, I found many interesting tidbits and amplifications throughout the text. I would recommend this book as a text for an advanced undergraduate or beginning graduate course in genomics. Although the text works though several examples of genetic and genome analysis, additional problem/homework sets would need to be developed to ensure student comprehension. The text steers clear of the ethical implications of the Human Genome Initiative and remains true to its subtitle The Science and Technology .

First Pass Annotation of Promoters on Human Chromosome 22

PubMed Central

Scherf, Matthias; Klingenhoff, Andreas; Frech, Kornelie; Quandt, Kerstin; Schneider, Ralf; Grote, Korbinian; Frisch, Matthias; Gailus-Durner, Valérie; Seidel, Alexander; Brack-Werner, Ruth; Werner, Thomas

2001-01-01

The publication of the first almost complete sequence of a human chromosome (chromosome 22) is a major milestone in human genomics. Together with the sequence, an excellent annotation of genes was published which certainly will serve as an information resource for numerous future projects. We noted that the annotation did not cover regulatory regions; in particular, no promoter annotation has been provided. Here we present an analysis of the complete published chromosome 22 sequence for promoters. A recent breakthrough in specific in silico prediction of promoter regions enabled us to attempt large-scale prediction of promoter regions on chromosome 22. Scanning of sequence databases revealed only 20 experimentally verified promoters, of which 10 were correctly predicted by our approach. Nearly 40% of our 465 predicted promoter regions are supported by the currently available gene annotation. Promoter finding also provides a biologically meaningful method for “chromosomal scaffolding”, by which long genomic sequences can be divided into segments starting with a gene. As one example, the combination of promoter region prediction with exon/intron structure predictions greatly enhances the specificity of de novo gene finding. The present study demonstrates that it is possible to identify promoters in silico on the chromosomal level with sufficient reliability for experimental planning and indicates that a wealth of information about regulatory regions can be extracted from current large-scale (megabase) sequencing projects. Results are available on-line at http://genomatix.gsf.de/chr22/. PMID:11230158

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

PubMed Central

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

2017-01-01

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

Temporal enhancement of two-dimensional color doppler echocardiography

NASA Astrophysics Data System (ADS)

Terentjev, Alexey B.; Settlemier, Scott H.; Perrin, Douglas P.; del Nido, Pedro J.; Shturts, Igor V.; Vasilyev, Nikolay V.

2016-03-01

Two-dimensional color Doppler echocardiography is widely used for assessing blood flow inside the heart and blood vessels. Currently, frame acquisition time for this method varies from tens to hundreds of milliseconds, depending on Doppler sector parameters. This leads to low frame rates of resulting video sequences equal to tens of Hz, which is insufficient for some diagnostic purposes, especially in pediatrics. In this paper, we present a new approach for reconstruction of 2D color Doppler cardiac images, which results in the frame rate being increased to hundreds of Hz. This approach relies on a modified method of frame reordering originally applied to real-time 3D echocardiography. There are no previous publications describing application of this method to 2D Color Doppler data. The approach has been tested on several in-vivo cardiac 2D color Doppler datasets with approximate duration of 30 sec and native frame rate of 15 Hz. The resulting image sequences had equivalent frame rates to 500Hz.

Using Maximum Entropy to Find Patterns in Genomes

NASA Astrophysics Data System (ADS)

Liu, Sophia; Hockenberry, Adam; Lancichinetti, Andrea; Jewett, Michael; Amaral, Luis

The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. To accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. This approach can also be easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes. National Institute of General Medical Science, Northwestern University Presidential Fellowship, National Science Foundation, David and Lucile Packard Foundation, Camille Dreyfus Teacher Scholar Award.

Microsatellite analysis in the genome of Acanthaceae: An in silico approach.

PubMed

Kaliswamy, Priyadharsini; Vellingiri, Srividhya; Nathan, Bharathi; Selvaraj, Saravanakumar

2015-01-01

Acanthaceae is one of the advanced and specialized families with conventionally used medicinal plants. Simple sequence repeats (SSRs) play a major role as molecular markers for genome analysis and plant breeding. The microsatellites existing in the complete genome sequences would help to attain a direct role in the genome organization, recombination, gene regulation, quantitative genetic variation, and evolution of genes. The current study reports the frequency of microsatellites and appropriate markers for the Acanthaceae family genome sequences. The whole nucleotide sequences of Acanthaceae species were obtained from National Center for Biotechnology Information database and screened for the presence of SSRs. SSR Locator tool was used to predict the microsatellites and inbuilt Primer3 module was used for primer designing. Totally 110 repeats from 108 sequences of Acanthaceae family plant genomes were identified, and the occurrence of dinucleotide repeats was found to be abundant in the genome sequences. The essential amino acid isoleucine was found rich in all the sequences. We also designed the SSR-based primers/markers for 59 sequences of this family that contains microsatellite repeats in their genome. The identified microsatellites and primers might be useful for breeding and genetic studies of plants that belong to Acanthaceae family in the future.

Nanopore sequencing technology: a new route for the fast detection of unauthorized GMO.

PubMed

Fraiture, Marie-Alice; Saltykova, Assia; Hoffman, Stefan; Winand, Raf; Deforce, Dieter; Vanneste, Kevin; De Keersmaecker, Sigrid C J; Roosens, Nancy H C

2018-05-21

In order to strengthen the current genetically modified organism (GMO) detection system for unauthorized GMO, we have recently developed a new workflow based on DNA walking to amplify unknown sequences surrounding a known DNA region. This DNA walking is performed on transgenic elements, commonly found in GMO, that were earlier detected by real-time PCR (qPCR) screening. Previously, we have demonstrated the ability of this approach to detect unauthorized GMO via the identification of unique transgene flanking regions and the unnatural associations of elements from the transgenic cassette. In the present study, we investigate the feasibility to integrate the described workflow with the MinION Next-Generation-Sequencing (NGS). The MinION sequencing platform can provide long read-lengths and deal with heterogenic DNA libraries, allowing for rapid and efficient delivery of sequences of interest. In addition, the ability of this NGS platform to characterize unauthorized and unknown GMO without any a priori knowledge has been assessed.

Identification of novel biomass-degrading enzymes from genomic dark matter: Populating genomic sequence space with functional annotation.

PubMed

Piao, Hailan; Froula, Jeff; Du, Changbin; Kim, Tae-Wan; Hawley, Erik R; Bauer, Stefan; Wang, Zhong; Ivanova, Nathalia; Clark, Douglas S; Klenk, Hans-Peter; Hess, Matthias

2014-08-01

Although recent nucleotide sequencing technologies have significantly enhanced our understanding of microbial genomes, the function of ∼35% of genes identified in a genome currently remains unknown. To improve the understanding of microbial genomes and consequently of microbial processes it will be crucial to assign a function to this "genomic dark matter." Due to the urgent need for additional carbohydrate-active enzymes for improved production of transportation fuels from lignocellulosic biomass, we screened the genomes of more than 5,500 microorganisms for hypothetical proteins that are located in the proximity of already known cellulases. We identified, synthesized and expressed a total of 17 putative cellulase genes with insufficient sequence similarity to currently known cellulases to be identified as such using traditional sequence annotation techniques that rely on significant sequence similarity. The recombinant proteins of the newly identified putative cellulases were subjected to enzymatic activity assays to verify their hydrolytic activity towards cellulose and lignocellulosic biomass. Eleven (65%) of the tested enzymes had significant activity towards at least one of the substrates. This high success rate highlights that a gene context-based approach can be used to assign function to genes that are otherwise categorized as "genomic dark matter" and to identify biomass-degrading enzymes that have little sequence similarity to already known cellulases. The ability to assign function to genes that have no related sequence representatives with functional annotation will be important to enhance our understanding of microbial processes and to identify microbial proteins for a wide range of applications. © 2014 Wiley Periodicals, Inc.

Real-time single-molecule electronic DNA sequencing by synthesis using polymer-tagged nucleotides on a nanopore array

PubMed Central

Fuller, Carl W.; Kumar, Shiv; Porel, Mintu; Chien, Minchen; Bibillo, Arek; Stranges, P. Benjamin; Dorwart, Michael; Tao, Chuanjuan; Li, Zengmin; Guo, Wenjing; Shi, Shundi; Korenblum, Daniel; Trans, Andrew; Aguirre, Anne; Liu, Edward; Harada, Eric T.; Pollard, James; Bhat, Ashwini; Cech, Cynthia; Yang, Alexander; Arnold, Cleoma; Palla, Mirkó; Hovis, Jennifer; Chen, Roger; Morozova, Irina; Kalachikov, Sergey; Russo, James J.; Kasianowicz, John J.; Davis, Randy; Roever, Stefan; Church, George M.; Ju, Jingyue

2016-01-01

DNA sequencing by synthesis (SBS) offers a robust platform to decipher nucleic acid sequences. Recently, we reported a single-molecule nanopore-based SBS strategy that accurately distinguishes four bases by electronically detecting and differentiating four different polymer tags attached to the 5′-phosphate of the nucleotides during their incorporation into a growing DNA strand catalyzed by DNA polymerase. Further developing this approach, we report here the use of nucleotides tagged at the terminal phosphate with oligonucleotide-based polymers to perform nanopore SBS on an α-hemolysin nanopore array platform. We designed and synthesized several polymer-tagged nucleotides using tags that produce different electrical current blockade levels and verified they are active substrates for DNA polymerase. A highly processive DNA polymerase was conjugated to the nanopore, and the conjugates were complexed with primer/template DNA and inserted into lipid bilayers over individually addressable electrodes of the nanopore chip. When an incoming complementary-tagged nucleotide forms a tight ternary complex with the primer/template and polymerase, the tag enters the pore, and the current blockade level is measured. The levels displayed by the four nucleotides tagged with four different polymers captured in the nanopore in such ternary complexes were clearly distinguishable and sequence-specific, enabling continuous sequence determination during the polymerase reaction. Thus, real-time single-molecule electronic DNA sequencing data with single-base resolution were obtained. The use of these polymer-tagged nucleotides, combined with polymerase tethering to nanopores and multiplexed nanopore sensors, should lead to new high-throughput sequencing methods. PMID:27091962

muBLASTP: database-indexed protein sequence search on multicore CPUs.

PubMed

Zhang, Jing; Misra, Sanchit; Wang, Hao; Feng, Wu-Chun

2016-11-04

The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.

Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels.

PubMed

Kerkhof, Jennifer; Schenkel, Laila C; Reilly, Jack; McRobbie, Sheri; Aref-Eshghi, Erfan; Stuart, Alan; Rupar, C Anthony; Adams, Paul; Hegele, Robert A; Lin, Hanxin; Rodenhiser, David; Knoll, Joan; Ainsworth, Peter J; Sadikovic, Bekim

2017-11-01

Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89%-100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation-dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Object tracking using plenoptic image sequences

NASA Astrophysics Data System (ADS)

Kim, Jae Woo; Bae, Seong-Joon; Park, Seongjin; Kim, Do Hyung

2017-05-01

Object tracking is a very important problem in computer vision research. Among the difficulties of object tracking, partial occlusion problem is one of the most serious and challenging problems. To address the problem, we proposed novel approaches to object tracking on plenoptic image sequences. Our approaches take advantage of the refocusing capability that plenoptic images provide. Our approaches input the sequences of focal stacks constructed from plenoptic image sequences. The proposed image selection algorithms select the sequence of optimal images that can maximize the tracking accuracy from the sequence of focal stacks. Focus measure approach and confidence measure approach were proposed for image selection and both of the approaches were validated by the experiments using thirteen plenoptic image sequences that include heavily occluded target objects. The experimental results showed that the proposed approaches were satisfactory comparing to the conventional 2D object tracking algorithms.

Describing the diversity of Ag specific receptors in vertebrates: Contribution of repertoire deep sequencing.

PubMed

Castro, Rosario; Navelsaker, Sofie; Krasnov, Aleksei; Du Pasquier, Louis; Boudinot, Pierre

2017-10-01

During the last decades, gene and cDNA cloning identified TCR and Ig genes across vertebrates; genome sequencing of TCR and Ig loci in many species revealed the different organizations selected during evolution under the pressure of generating diverse repertoires of Ag receptors. By detecting clonotypes over a wide range of frequency, deep sequencing of Ig and TCR transcripts provides a new way to compare the structure of expressed repertoires in species of various sizes, at different stages of development, with different physiologies, and displaying multiple adaptations to the environment. In this review, we provide a short overview of the technologies currently used to produce global description of immune repertoires, describe how they have already been used in comparative immunology, and we discuss the future potential of such approaches. The development of these methodologies in new species holds promise for new discoveries concerning particular adaptations. As an example, understanding the development of adaptive immunity across metamorphosis in frogs has been made possible by such approaches. Repertoire sequencing is now widely used, not only in basic research but also in the context of immunotherapy and vaccination. Analysis of fish responses to pathogens and vaccines has already benefited from these methods. Finally, we also discuss potential advances based on repertoire sequencing of multigene families of immune sensors and effectors in invertebrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

i-rDNA: alignment-free algorithm for rapid in silico detection of ribosomal gene fragments from metagenomic sequence data sets.

PubMed

Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Chadaram, Sudha; Mande, Sharmila S

2011-11-30

Obtaining accurate estimates of microbial diversity using rDNA profiling is the first step in most metagenomics projects. Consequently, most metagenomic projects spend considerable amounts of time, money and manpower for experimentally cloning, amplifying and sequencing the rDNA content in a metagenomic sample. In the second step, the entire genomic content of the metagenome is extracted, sequenced and analyzed. Since DNA sequences obtained in this second step also contain rDNA fragments, rapid in silico identification of these rDNA fragments would drastically reduce the cost, time and effort of current metagenomic projects by entirely bypassing the experimental steps of primer based rDNA amplification, cloning and sequencing. In this study, we present an algorithm called i-rDNA that can facilitate the rapid detection of 16S rDNA fragments from amongst millions of sequences in metagenomic data sets with high detection sensitivity. Performance evaluation with data sets/database variants simulating typical metagenomic scenarios indicates the significantly high detection sensitivity of i-rDNA. Moreover, i-rDNA can process a million sequences in less than an hour on a simple desktop with modest hardware specifications. In addition to the speed of execution, high sensitivity and low false positive rate, the utility of the algorithmic approach discussed in this paper is immense given that it would help in bypassing the entire experimental step of primer-based rDNA amplification, cloning and sequencing. Application of this algorithmic approach would thus drastically reduce the cost, time and human efforts invested in all metagenomic projects. A web-server for the i-rDNA algorithm is available at http://metagenomics.atc.tcs.com/i-rDNA/

An accurate algorithm for the detection of DNA fragments from dilution pool sequencing experiments.

PubMed

Bansal, Vikas

2018-01-01

The short read lengths of current high-throughput sequencing technologies limit the ability to recover long-range haplotype information. Dilution pool methods for preparing DNA sequencing libraries from high molecular weight DNA fragments enable the recovery of long DNA fragments from short sequence reads. These approaches require computational methods for identifying the DNA fragments using aligned sequence reads and assembling the fragments into long haplotypes. Although a number of computational methods have been developed for haplotype assembly, the problem of identifying DNA fragments from dilution pool sequence data has not received much attention. We formulate the problem of detecting DNA fragments from dilution pool sequencing experiments as a genome segmentation problem and develop an algorithm that uses dynamic programming to optimize a likelihood function derived from a generative model for the sequence reads. This algorithm uses an iterative approach to automatically infer the mean background read depth and the number of fragments in each pool. Using simulated data, we demonstrate that our method, FragmentCut, has 25-30% greater sensitivity compared with an HMM based method for fragment detection and can also detect overlapping fragments. On a whole-genome human fosmid pool dataset, the haplotypes assembled using the fragments identified by FragmentCut had greater N50 length, 16.2% lower switch error rate and 35.8% lower mismatch error rate compared with two existing methods. We further demonstrate the greater accuracy of our method using two additional dilution pool datasets. FragmentCut is available from https://bansal-lab.github.io/software/FragmentCut. vibansal@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Alternative Splicing as a Target for Cancer Treatment.

PubMed

Martinez-Montiel, Nancy; Rosas-Murrieta, Nora Hilda; Anaya Ruiz, Maricruz; Monjaraz-Guzman, Eduardo; Martinez-Contreras, Rebeca

2018-02-11

Alternative splicing is a key mechanism determinant for gene expression in metazoan. During alternative splicing, non-coding sequences are removed to generate different mature messenger RNAs due to a combination of sequence elements and cellular factors that contribute to splicing regulation. A different combination of splicing sites, exonic or intronic sequences, mutually exclusive exons or retained introns could be selected during alternative splicing to generate different mature mRNAs that could in turn produce distinct protein products. Alternative splicing is the main source of protein diversity responsible for 90% of human gene expression, and it has recently become a hallmark for cancer with a full potential as a prognostic and therapeutic tool. Currently, more than 15,000 alternative splicing events have been associated to different aspects of cancer biology, including cell proliferation and invasion, apoptosis resistance and susceptibility to different chemotherapeutic drugs. Here, we present well established and newly discovered splicing events that occur in different cancer-related genes, their modification by several approaches and the current status of key tools developed to target alternative splicing with diagnostic and therapeutic purposes.

The Use of a Combined Bioinformatics Approach to Locate Antibiotic Resistance Genes on Plasmids From Whole Genome Sequences of Salmonella enterica Serovars From Humans in Ghana.

PubMed

Kudirkiene, Egle; Andoh, Linda A; Ahmed, Shahana; Herrero-Fresno, Ana; Dalsgaard, Anders; Obiri-Danso, Kwasi; Olsen, John E

2018-01-01

In the current study, we identified plasmids carrying antimicrobial resistance genes in draft whole genome sequences of 16 selected Salmonella enterica isolates representing six different serovars from humans in Ghana. The plasmids and the location of resistance genes in the genomes were predicted using a combination of PlasmidFinder, ResFinder, plasmidSPAdes and BLAST genomic analysis tools. Subsequently, S1-PFGE was employed for analysis of plasmid profiles. Whole genome sequencing confirmed the presence of antimicrobial resistance genes in Salmonella isolates showing multidrug resistance phenotypically. ESBL, either bla TEM52-B or bla CTX-M15 were present in two cephalosporin resistant isolates of S . Virchow and S . Poona, respectively. The systematic genome analysis revealed the presence of different plasmids in different serovars, with or without insertion of antimicrobial resistance genes. In S . Enteritidis, resistance genes were carried predominantly on plasmids of IncN type, in S . Typhimurium on plasmids of IncFII(S)/IncFIB(S)/IncQ1 type. In S . Virchow and in S . Poona, resistance genes were detected on plasmids of IncX1 and TrfA/IncHI2/IncHI2A type, respectively. The latter two plasmids were described for the first time in these serovars. The combination of genomic analytical tools allowed nearly full mapping of the resistance plasmids in all Salmonella strains analyzed. The results suggest that the improved analytical approach used in the current study may be used to identify plasmids that are specifically associated with resistance phenotypes in whole genome sequences. Such knowledge would allow the development of rapid multidrug resistance tracking tools in Salmonella populations using WGS.

Capturing the genetic makeup of the active microbiome in situ

DOE PAGES

Singer, Esther; Wagner, Michael; Woyke, Tanja

2017-06-02

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and thatmore » have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.« less

Mismatch repair defects and Lynch syndrome: The role of the basic scientist in the battle against cancer.

PubMed

Heinen, Christopher D

2016-02-01

We have currently entered a genomic era of cancer research which may soon lead to a genomic era of cancer treatment. Patient DNA sequencing information may lead to a personalized approach to managing an individual's cancer as well as future cancer risk. The success of this approach, however, begins not necessarily in the clinician's office, but rather at the laboratory bench of the basic scientist. The basic scientist plays a critical role since the DNA sequencing information is of limited use unless one knows the function of the gene that is altered and the manner by which a sequence alteration affects that function. The role of basic science research in aiding the clinical management of a disease is perhaps best exemplified by considering the case of Lynch syndrome, a hereditary disease that predisposes patients to colorectal and other cancers. This review will examine how the diagnosis, treatment and even prevention of Lynch syndrome-associated cancers has benefitted from extensive basic science research on the DNA mismatch repair genes whose alteration underlies this condition. Copyright © 2015 Elsevier B.V. All rights reserved.

Capturing the genetic makeup of the active microbiome in situ

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

Singer, Esther; Wagner, Michael; Woyke, Tanja

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and thatmore » have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.« less

Current and future molecular approaches in the diagnosis of cystic fibrosis.

PubMed

Bergougnoux, Anne; Taulan-Cadars, Magali; Claustres, Mireille; Raynal, Caroline

2018-05-01

Cystic Fibrosis is among the first diseases to have general population genetic screening tests and one of the most common indications of prenatal and preimplantation genetic diagnosis for single gene disorders. During the past twenty years, thanks to the evolution of diagnostic techniques, our knowledge of CFTR genetics and pathophysiological mechanisms involved in cystic fibrosis has significantly improved. Areas covered: Sanger sequencing and quantitative methods greatly contributed to the identification of more than 2,000 sequence variations reported worldwide in the CFTR gene. We are now entering a new technological age with the generalization of high throughput approaches such as Next Generation Sequencing and Droplet Digital PCR technologies in diagnostics laboratories. These powerful technologies open up new perspectives for scanning the entire CFTR locus, exploring modifier factors that possibly influence the clinical evolution of patients, and for preimplantation and prenatal diagnosis. Expert commentary: Such breakthroughs would, however, require powerful bioinformatics tools and relevant functional tests of variants for analysis and interpretation of the resulting data. Ultimately, an optimal use of all those resources may improve patient care and therapeutic decision-making.

Paediatric genomics: diagnosing rare disease in children.

PubMed

Wright, Caroline F; FitzPatrick, David R; Firth, Helen V

2018-05-01

The majority of rare diseases affect children, most of whom have an underlying genetic cause for their condition. However, making a molecular diagnosis with current technologies and knowledge is often still a challenge. Paediatric genomics is an immature but rapidly evolving field that tackles this issue by incorporating next-generation sequencing technologies, especially whole-exome sequencing and whole-genome sequencing, into research and clinical workflows. This complex multidisciplinary approach, coupled with the increasing availability of population genetic variation data, has already resulted in an increased discovery rate of causative genes and in improved diagnosis of rare paediatric disease. Importantly, for affected families, a better understanding of the genetic basis of rare disease translates to more accurate prognosis, management, surveillance and genetic advice; stimulates research into new therapies; and enables provision of better support.

Protein Structure Determination using Metagenome sequence data

PubMed Central

Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha; Huang, Po-Ssu; Pavlopoulos, Georgios A.; Kim, David E.; Kamisetty, Hetunandan; Kyrpides, Nikos C.; Baker, David

2017-01-01

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families, and that metagenome sequence data more than triples the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact based structure matching and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the PDB. This approach provides the representative models for large protein families originally envisioned as the goal of the protein structure initiative at a fraction of the cost. PMID:28104891

Bioinformatics Approaches for Fetal DNA Fraction Estimation in Noninvasive Prenatal Testing

PubMed Central

Peng, Xianlu Laura; Jiang, Peiyong

2017-01-01

The discovery of cell-free fetal DNA molecules in plasma of pregnant women has created a paradigm shift in noninvasive prenatal testing (NIPT). Circulating cell-free DNA in maternal plasma has been increasingly recognized as an important proxy to detect fetal abnormalities in a noninvasive manner. A variety of approaches for NIPT using next-generation sequencing have been developed, which have been rapidly transforming clinical practices nowadays. In such approaches, the fetal DNA fraction is a pivotal parameter governing the overall performance and guaranteeing the proper clinical interpretation of testing results. In this review, we describe the current bioinformatics approaches developed for estimating the fetal DNA fraction and discuss their pros and cons. PMID:28230760

Bioinformatics Approaches for Fetal DNA Fraction Estimation in Noninvasive Prenatal Testing.

PubMed

Peng, Xianlu Laura; Jiang, Peiyong

2017-02-20

The discovery of cell-free fetal DNA molecules in plasma of pregnant women has created a paradigm shift in noninvasive prenatal testing (NIPT). Circulating cell-free DNA in maternal plasma has been increasingly recognized as an important proxy to detect fetal abnormalities in a noninvasive manner. A variety of approaches for NIPT using next-generation sequencing have been developed, which have been rapidly transforming clinical practices nowadays. In such approaches, the fetal DNA fraction is a pivotal parameter governing the overall performance and guaranteeing the proper clinical interpretation of testing results. In this review, we describe the current bioinformatics approaches developed for estimating the fetal DNA fraction and discuss their pros and cons.

Wi-Fi location fingerprinting using an intelligent checkpoint sequence

NASA Astrophysics Data System (ADS)

Retscher, Günther; Hofer, Hannes

2017-09-01

For Wi-Fi positioning location fingerprinting is very common but has the disadvantage that it is very labour consuming for the establishment of a database (DB) with received signal strength (RSS) scans measured on a large number of known reference points (RPs). To overcome this drawback a novel approach is developed which uses a logical sequence of intelligent checkpoints (iCPs) instead of RPs distributed in a regular grid. The iCPs are the selected RPs which have to be passed along the way for navigation from a start point A to the destination B. They are twofold intelligent because of the fact that they depend on their meaningful selection and because of their logical sequence in their correct order. Thus, always the following iCP is known due to a vector graph allocation in the DB and only a small limited number of iCPs needs to be tested when matching the current RSS scans. This reduces the required processing time significantly. It is proven that the iCP approach achieves a higher success rate than conventional approaches. In average correct matching results of 90.0% were achieved using a joint DB including RSS scans of all employed smartphones. An even higher success rate is achieved if the same mobile device is used in both the training and positioning phase.

Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets.

PubMed

Vishnevsky, Oleg V; Bocharnikov, Andrey V; Kolchanov, Nikolay A

2018-02-01

The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

mCAL: A New Approach for Versatile Multiplex Action of Cas9 Using One sgRNA and Loci Flanked by a Programmed Target Sequence.

PubMed

Finnigan, Gregory C; Thorner, Jeremy

2016-07-07

Genome editing exploiting CRISPR/Cas9 has been adopted widely in academia and in the biotechnology industry to manipulate DNA sequences in diverse organisms. Molecular engineering of Cas9 itself and its guide RNA, and the strategies for using them, have increased efficiency, optimized specificity, reduced inappropriate off-target effects, and introduced modifications for performing other functions (transcriptional regulation, high-resolution imaging, protein recruitment, and high-throughput screening). Moreover, Cas9 has the ability to multiplex, i.e., to act at different genomic targets within the same nucleus. Currently, however, introducing concurrent changes at multiple loci involves: (i) identification of appropriate genomic sites, especially the availability of suitable PAM sequences; (ii) the design, construction, and expression of multiple sgRNA directed against those sites; (iii) potential difficulties in altering essential genes; and (iv) lingering concerns about "off-target" effects. We have devised a new approach that circumvents these drawbacks, as we demonstrate here using the yeast Saccharomyces cerevisiae First, any gene(s) of interest are flanked upstream and downstream with a single unique target sequence that does not normally exist in the genome. Thereafter, expression of one sgRNA and cotransformation with appropriate PCR fragments permits concomitant Cas9-mediated alteration of multiple genes (both essential and nonessential). The system we developed also allows for maintenance of the integrated, inducible Cas9-expression cassette or its simultaneous scarless excision. Our scheme-dubbed mCAL for " M: ultiplexing of C: as9 at A: rtificial L: oci"-can be applied to any organism in which the CRISPR/Cas9 methodology is currently being utilized. In principle, it can be applied to install synthetic sequences into the genome, to generate genomic libraries, and to program strains or cell lines so that they can be conveniently (and repeatedly) manipulated at multiple loci with extremely high efficiency. Copyright © 2016 Finnigan and Thorner.

Region-Based Prediction for Image Compression in the Cloud.

PubMed

Begaint, Jean; Thoreau, Dominique; Guillotel, Philippe; Guillemot, Christine

2018-04-01

Thanks to the increasing number of images stored in the cloud, external image similarities can be leveraged to efficiently compress images by exploiting inter-images correlations. In this paper, we propose a novel image prediction scheme for cloud storage. Unlike current state-of-the-art methods, we use a semi-local approach to exploit inter-image correlation. The reference image is first segmented into multiple planar regions determined from matched local features and super-pixels. The geometric and photometric disparities between the matched regions of the reference image and the current image are then compensated. Finally, multiple references are generated from the estimated compensation models and organized in a pseudo-sequence to differentially encode the input image using classical video coding tools. Experimental results demonstrate that the proposed approach yields significant rate-distortion performance improvements compared with the current image inter-coding solutions such as high efficiency video coding.

Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery

PubMed Central

Hoinka, Jan; Berezhnoy, Alexey; Dao, Phuong; Sauna, Zuben E.; Gilboa, Eli; Przytycka, Teresa M.

2015-01-01

High-Throughput (HT) SELEX combines SELEX (Systematic Evolution of Ligands by EXponential Enrichment), a method for aptamer discovery, with massively parallel sequencing technologies. This emerging technology provides data for a global analysis of the selection process and for simultaneous discovery of a large number of candidates but currently lacks dedicated computational approaches for their analysis. To close this gap, we developed novel in-silico methods to analyze HT-SELEX data and utilized them to study the emergence of polymerase errors during HT-SELEX. Rather than considering these errors as a nuisance, we demonstrated their utility for guiding aptamer discovery. Our approach builds on two main advancements in aptamer analysis: AptaMut—a novel technique allowing for the identification of polymerase errors conferring an improved binding affinity relative to the ‘parent’ sequence and AptaCluster—an aptamer clustering algorithm which is to our best knowledge, the only currently available tool capable of efficiently clustering entire aptamer pools. We applied these methods to an HT-SELEX experiment developing aptamers against Interleukin 10 receptor alpha chain (IL-10RA) and experimentally confirmed our predictions thus validating our computational methods. PMID:25870409

Evaluation of the Terminal Sequencing and Spacing System for Performance Based Navigation Arrivals

NASA Technical Reports Server (NTRS)

Thipphavong, Jane; Jung, Jaewoo; Swenson, Harry N.; Martin, Lynne; Lin, Melody; Nguyen, Jimmy

2013-01-01

NASA has developed the Terminal Sequencing and Spacing (TSS) system, a suite of advanced arrival management technologies combining timebased scheduling and controller precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals that have both current standard ATC routes and terminal Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. In collaboration with the FAA and MITRE's Center for Advanced Aviation System Development (CAASD), TSS system performance was evaluated in human-in-the-loop (HITL) simulations with currently active controllers as participants. Traffic scenarios had mixed Area Navigation (RNAV) and Required Navigation Performance (RNP) equipage, where the more advanced RNP-equipped aircraft had preferential treatment with a shorter approach option. Simulation results indicate the TSS system achieved benefits by enabling PBN, while maintaining high throughput rates-10% above baseline demand levels. Flight path predictability improved, where path deviation was reduced by 2 NM on average and variance in the downwind leg length was 75% less. Arrivals flew more fuel-efficient descents for longer, spending an average of 39 seconds less in step-down level altitude segments. Self-reported controller workload was reduced, with statistically significant differences at the p less than 0.01 level. The RNP-equipped arrivals were also able to more frequently capitalize on the benefits of being "Best-Equipped, Best- Served" (BEBS), where less vectoring was needed and nearly all RNP approaches were conducted without interruption.

Optimal treatment sequence in COPD: Can a consensus be found?

PubMed

Ferreira, J; Drummond, M; Pires, N; Reis, G; Alves, C; Robalo-Cordeiro, C

2016-01-01

There is currently no consensus on the treatment sequence in chronic obstructive pulmonary disease (COPD), although it is recognized that early diagnosis is of paramount importance to start treatment in the early stages of the disease. Although it is fairly consensual that initial treatment should be with an inhaled short-acting beta agonist, a short-acting muscarinic antagonist, a long-acting beta-agonist or a long-acting muscarinic antagonist. As the disease progresses, several therapeutic options are available, and which to choose at each disease stage remains controversial. When and in which patients to use dual bronchodilation? When to use inhaled corticosteroids? And triple therapy? Are the existing non-inhaled therapies, such as mucolytic agents, antibiotics, phosphodiesterase-4 inhibitors, methylxanthines and immunostimulating agents, useful? If so, which patients would benefit? Should co-morbidities be taken into account when choosing COPD therapy for a patient? This paper reviews current guidelines and available evidence and proposes a therapeutic scheme for COPD patients. We also propose a treatment algorithm in the hope that it will help physicians to decide the best approach for their patients. The authors conclude that, at present, a full consensus on optimal treatment sequence in COPD cannot be found, mainly due to disease heterogeneity and lack of biomarkers to guide treatment. For the time being, and although some therapeutic approaches are consensual, treatment of COPD should be patient-oriented. Copyright © 2015 Sociedade Portuguesa de Pneumologia. Published by Elsevier España, S.L.U. All rights reserved.

A proposal to rationalize within-species plant virus nomenclature: benefits and implications of inaction.

PubMed

Jones, Roger A C; Kehoe, Monica A

2016-07-01

Current approaches used to name within-species, plant virus phylogenetic groups are often misleading and illogical. They involve names based on biological properties, sequence differences and geographical, country or place-association designations, or any combination of these. This type of nomenclature is becoming increasingly unsustainable as numbers of sequences of the same virus from new host species and different parts of the world increase. Moreover, this increase is accelerating as world trade and agriculture expand, and climate change progresses. Serious consequences for virus research and disease management might arise from incorrect assumptions made when current within-species phylogenetic group names incorrectly identify properties of group members. This could result in development of molecular tools that incorrectly target dangerous virus strains, potentially leading to unjustified impediments to international trade or failure to prevent such strains being introduced to countries, regions or continents formerly free of them. Dangerous strains might be missed or misdiagnosed by diagnostic laboratories and monitoring programs, and new cultivars with incorrect strain-specific resistances released. Incorrect deductions are possible during phylogenetic analysis of plant virus sequences and errors from strain misidentification during molecular and biological virus research activities. A nomenclature system for within-species plant virus phylogenetic group names is needed which avoids such problems. We suggest replacing all other naming approaches with Latinized numerals, restricting biologically based names only to biological strains and removing geographically based names altogether. Our recommendations have implications for biosecurity authorities, diagnostic laboratories, disease-management programs, plant breeders and researchers.

Functional assessment of human enhancer activities using whole-genome STARR-sequencing.

PubMed

Liu, Yuwen; Yu, Shan; Dhiman, Vineet K; Brunetti, Tonya; Eckart, Heather; White, Kevin P

2017-11-20

Genome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome.  In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements. WHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach

PubMed Central

Watson, Mick; Minot, Samuel S.; Rivera, Maria C.; Franklin, Rima B.

2017-01-01

Abstract Background: Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up to 98% assignment accuracy at the species level. The observed community proportions for “equal” and “rare” synthetic libraries were close to the known proportions, deviating from 0.1% to 10% across all tests. For a 20-species mock community with staggered contributions, a sequencing run detected all but 3 species (each included at <0.05% of DNA in the total mixture), 91% of reads were assigned to the correct species, 93% of reads were assigned to the correct genus, and >99% of reads were assigned to the correct family. Conclusions: At the current level of output and sequence quality (just under 4 × 103 2D reads for a synthetic metagenome), MinION sequencing followed by Kraken or One Codex analysis has the potential to provide rapid and accurate metagenomic analysis where the consortium is comprised of a limited number of taxa. Important considerations noted in this study included: high sensitivity of the MinION platform to the quality of input DNA, high variability of sequencing results across libraries and flow cells, and relatively small numbers of 2D reads per analysis limit. Together, these limited detection of very rare components of the microbial consortia, and would likely limit the utility of MinION for the sequencing of high-complexity metagenomic communities where thousands of taxa are expected. Furthermore, the limitations of the currently available data analysis tools suggest there is considerable room for improvement in the analytical approaches for the characterization of microbial communities using long reads. Nevertheless, the fact that the accurate taxonomic assignment of high-quality reads generated by MinION is approaching 99.5% and, in most cases, the inferred community structure mirrors the known proportions of a synthetic mixture warrants further exploration of practical application to environmental metagenomics as the platform continues to develop and improve. With further improvement in sequence throughput and error rate reduction, this platform shows great promise for precise real-time analysis of the composition and structure of more complex microbial communities. PMID:28327976

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach.

PubMed

Brown, Bonnie L; Watson, Mick; Minot, Samuel S; Rivera, Maria C; Franklin, Rima B

2017-03-01

Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up to 98% assignment accuracy at the species level. The observed community proportions for “equal” and “rare” synthetic libraries were close to the known proportions, deviating from 0.1% to 10% across all tests. For a 20-species mock community with staggered contributions, a sequencing run detected all but 3 species (each included at <0.05% of DNA in the total mixture), 91% of reads were assigned to the correct species, 93% of reads were assigned to the correct genus, and >99% of reads were assigned to the correct family. Conclusions: At the current level of output and sequence quality (just under 4 × 103 2D reads for a synthetic metagenome), MinION sequencing followed by Kraken or One Codex analysis has the potential to provide rapid and accurate metagenomic analysis where the consortium is comprised of a limited number of taxa. Important considerations noted in this study included: high sensitivity of the MinION platform to the quality of input DNA, high variability of sequencing results across libraries and flow cells, and relatively small numbers of 2D reads per analysis limit. Together, these limited detection of very rare components of the microbial consortia, and would likely limit the utility of MinION for the sequencing of high-complexity metagenomic communities where thousands of taxa are expected. Furthermore, the limitations of the currently available data analysis tools suggest there is considerable room for improvement in the analytical approaches for the characterization of microbial communities using long reads. Nevertheless, the fact that the accurate taxonomic assignment of high-quality reads generated by MinION is approaching 99.5% and, in most cases, the inferred community structure mirrors the known proportions of a synthetic mixture warrants further exploration of practical application to environmental metagenomics as the platform continues to develop and improve. With further improvement in sequence throughput and error rate reduction, this platform shows great promise for precise real-time analysis of the composition and structure of more complex microbial communities. © The Author 2017. Published by Oxford University Press.

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

PubMed Central

2013-01-01

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

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

PubMed

Sepúlveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain, Arnab; Clark, Taane G

2013-02-26

The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.

Multi-loci diagnosis of acute lymphoblastic leukaemia with high-throughput sequencing and bioinformatics analysis.

PubMed

Ferret, Yann; Caillault, Aurélie; Sebda, Shéhérazade; Duez, Marc; Grardel, Nathalie; Duployez, Nicolas; Villenet, Céline; Figeac, Martin; Preudhomme, Claude; Salson, Mikaël; Giraud, Mathieu

2016-05-01

High-throughput sequencing (HTS) is considered a technical revolution that has improved our knowledge of lymphoid and autoimmune diseases, changing our approach to leukaemia both at diagnosis and during follow-up. As part of an immunoglobulin/T cell receptor-based minimal residual disease (MRD) assessment of acute lymphoblastic leukaemia patients, we assessed the performance and feasibility of the replacement of the first steps of the approach based on DNA isolation and Sanger sequencing, using a HTS protocol combined with bioinformatics analysis and visualization using the Vidjil software. We prospectively analysed the diagnostic and relapse samples of 34 paediatric patients, thus identifying 125 leukaemic clones with recombinations on multiple loci (TRG, TRD, IGH and IGK), including Dd2/Dd3 and Intron/KDE rearrangements. Sequencing failures were halved (14% vs. 34%, P = 0.0007), enabling more patients to be monitored. Furthermore, more markers per patient could be monitored, reducing the probability of false negative MRD results. The whole analysis, from sample receipt to clinical validation, was shorter than our current diagnostic protocol, with equal resources. V(D)J recombination was successfully assigned by the software, even for unusual recombinations. This study emphasizes the progress that HTS with adapted bioinformatics tools can bring to the diagnosis of leukaemia patients. © 2016 John Wiley & Sons Ltd.

Environmental surveillance of viruses by tangential flow filtration and metagenomic reconstruction.

PubMed

Furtak, Vyacheslav; Roivainen, Merja; Mirochnichenko, Olga; Zagorodnyaya, Tatiana; Laassri, Majid; Zaidi, Sohail Z; Rehman, Lubna; Alam, Muhammad M; Chizhikov, Vladimir; Chumakov, Konstantin

2016-04-14

An approach is proposed for environmental surveillance of poliovirus by concentrating sewage samples with tangential flow filtration (TFF) followed by deep sequencing of viral RNA. Subsequent to testing the method with samples from Finland, samples from Pakistan, a country endemic for poliovirus, were investigated. Genomic sequencing was either performed directly, for unbiased identification of viruses regardless of their ability to grow in cell cultures, or after virus enrichment by cell culture or immunoprecipitation. Bioinformatics enabled separation and determination of individual consensus sequences. Overall, deep sequencing of the entire viral population identified polioviruses, non-polio enteroviruses, and other viruses. In Pakistani sewage samples, adeno-associated virus, unable to replicate autonomously in cell cultures, was the most abundant human virus. The presence of recombinants of wild polioviruses of serotype 1 (WPV1) was also inferred, whereby currently circulating WPV1 of south-Asian (SOAS) lineage comprised two sub-lineages depending on their non-capsid region origin. Complete genome analyses additionally identified point mutants and intertypic recombinants between attenuated Sabin strains in the Pakistani samples, and in one Finnish sample. The approach could allow rapid environmental surveillance of viruses causing human infections. It creates a permanent digital repository of the entire virome potentially useful for retrospective screening of future discovered viruses.

Phylogenetics of modern birds in the era of genomics

PubMed Central

Edwards, Scott V; Bryan Jennings, W; Shedlock, Andrew M

2005-01-01

In the 14 years since the first higher-level bird phylogenies based on DNA sequence data, avian phylogenetics has witnessed the advent and maturation of the genomics era, the completion of the chicken genome and a suite of technologies that promise to add considerably to the agenda of avian phylogenetics. In this review, we summarize current approaches and data characteristics of recent higher-level bird studies and suggest a number of as yet untested molecular and analytical approaches for the unfolding tree of life for birds. A variety of comparative genomics strategies, including adoption of objective quality scores for sequence data, analysis of contiguous DNA sequences provided by large-insert genomic libraries, and the systematic use of retroposon insertions and other rare genomic changes all promise an integrated phylogenetics that is solidly grounded in genome evolution. The avian genome is an excellent testing ground for such approaches because of the more balanced representation of single-copy and repetitive DNA regions than in mammals. Although comparative genomics has a number of obvious uses in avian phylogenetics, its application to large numbers of taxa poses a number of methodological and infrastructural challenges, and can be greatly facilitated by a ‘community genomics’ approach in which the modest sequencing throughputs of single PI laboratories are pooled to produce larger, complementary datasets. Although the polymerase chain reaction era of avian phylogenetics is far from complete, the comparative genomics era—with its ability to vastly increase the number and type of molecular characters and to provide a genomic context for these characters—will usher in a host of new perspectives and opportunities for integrating genome evolution and avian phylogenetics. PMID:16024355

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

PubMed

Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

2014-04-30

Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

Shot sequencing based on biological equivalent dose considerations for multiple isocenter Gamma Knife radiosurgery.

PubMed

Ma, Lijun; Lee, Letitia; Barani, Igor; Hwang, Andrew; Fogh, Shannon; Nakamura, Jean; McDermott, Michael; Sneed, Penny; Larson, David A; Sahgal, Arjun

2011-11-21

Rapid delivery of multiple shots or isocenters is one of the hallmarks of Gamma Knife radiosurgery. In this study, we investigated whether the temporal order of shots delivered with Gamma Knife Perfexion would significantly influence the biological equivalent dose for complex multi-isocenter treatments. Twenty single-target cases were selected for analysis. For each case, 3D dose matrices of individual shots were extracted and single-fraction equivalent uniform dose (sEUD) values were determined for all possible shot delivery sequences, corresponding to different patterns of temporal dose delivery within the target. We found significant variations in the sEUD values among these sequences exceeding 15% for certain cases. However, the sequences for the actual treatment delivery were found to agree (<3%) and to correlate (R² = 0.98) excellently with the sequences yielding the maximum sEUD values for all studied cases. This result is applicable for both fast and slow growing tumors with α/β values of 2 to 20 according to the linear-quadratic model. In conclusion, despite large potential variations in different shot sequences for multi-isocenter Gamma Knife treatments, current clinical delivery sequences exhibited consistent biological target dosing that approached that maximally achievable for all studied cases.

Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next-generation sequencing.

PubMed

Liang, Chanjuan; van Dijk, Jeroen P; Scholtens, Ingrid M J; Staats, Martijn; Prins, Theo W; Voorhuijzen, Marleen M; da Silva, Andrea M; Arisi, Ana Carolina Maisonnave; den Dunnen, Johan T; Kok, Esther J

2014-04-01

The growing number of biotech crops with novel genetic elements increasingly complicates the detection of genetically modified organisms (GMOs) in food and feed samples using conventional screening methods. Unauthorized GMOs (UGMOs) in food and feed are currently identified through combining GMO element screening with sequencing the DNA flanking these elements. In this study, a specific and sensitive qPCR assay was developed for vip3A element detection based on the vip3Aa20 coding sequences of the recently marketed MIR162 maize and COT102 cotton. Furthermore, SiteFinding-PCR in combination with Sanger, Illumina or Pacific BioSciences (PacBio) sequencing was performed targeting the flanking DNA of the vip3Aa20 element in MIR162. De novo assembly and Basic Local Alignment Search Tool searches were used to mimic UGMO identification. PacBio data resulted in relatively long contigs in the upstream (1,326 nucleotides (nt); 95 % identity) and downstream (1,135 nt; 92 % identity) regions, whereas Illumina data resulted in two smaller contigs of 858 and 1,038 nt with higher sequence identity (>99 % identity). Both approaches outperformed Sanger sequencing, underlining the potential for next-generation sequencing in UGMO identification.

Current treatment paradigms in rheumatoid arthritis.

PubMed

Fries, J F

2000-06-01

Rheumatoid arthritis (RA) has traditionally been treated using the pyramid approach, in which non-steroidal anti-inflammatory drugs (NSAIDs) are the first-line treatment and disease-modifying anti-rheumatic drugs (DMARDs) are introduced relatively late in the disease. This approach is no longer valid. Previously regarded as a benign disease, RA is now recognized as causing substantial morbidity and mortality, as do the NSAIDs used in treatment. DMARDs are more effective in controlling the pain and disability of RA than NSAIDs, and are often no more toxic. The current treatment paradigm emphasizes early, consistent use of DMARDs. A 'sawtooth' strategy of DMARD use has been proposed, in which a rising but low level of disability triggers a change in therapy. Determining the most clinically useful DMARD combinations and the optimal sequence of DMARD use requires effectiveness studies, Bayesian approaches and analyses of long-term outcomes. Such approaches will allow optimization of multiple drug therapies in RA, and should substantially improve the long-term outcome for many patients.

Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

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

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less

Development of an antigen-based rapid diagnostic test for the identification of blowfly (Calliphoridae) species of forensic significance.

PubMed

McDonagh, Laura; Thornton, Chris; Wallman, James F; Stevens, Jamie R

2009-06-01

In this study we examine the limitations of currently used sequence-based approaches to blowfly (Calliphoridae) identification and evaluate the utility of an immunological approach to discriminate between blowfly species of forensic importance. By investigating antigenic similarity and dissimilarity between the first instar larval stages of four forensically important blowfly species, we have been able to identify immunoreactive proteins of potential use in the development of species-specific immuno-diagnostic tests. Here we outline our protein-based approach to species determination, and describe how it may be adapted to develop rapid diagnostic assays for the 'on-site' identification of blowfly species.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond.

PubMed

Hiraoka, Satoshi; Yang, Ching-Chia; Iwasaki, Wataru

2016-09-29

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

Anchoring historical sequences using a new source of astro-chronological tie-points

NASA Astrophysics Data System (ADS)

Dee, Michael W.; Pope, Benjamin J. S.

2016-08-01

The discovery of past spikes in atmospheric radiocarbon activity, caused by major solar energetic particle events, has opened up new possibilities for high-precision chronometry. The two spikes, or Miyake Events, have now been widely identified in tree-rings that grew in the years 775 and 994 CE. Furthermore, all other plant material that grew in these years would also have incorporated the anomalously high concentrations of radiocarbon. Crucially, some plant-based artefacts, such as papyrus documents, timber beams and linen garments, can also be allocated to specific positions within long, currently unfixed, historical sequences. Thus, Miyake Events represent a new source of tie-points that could provide the means for anchoring early chronologies to the absolute timescale. Here, we explore this possibility, outlining the most expeditious approaches, the current challenges and obstacles, and how they might best be overcome.

Variable speed wind turbine generator with zero-sequence filter

DOEpatents

Muljadi, Eduard

1998-01-01

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility.

Variable Speed Wind Turbine Generator with Zero-sequence Filter

DOEpatents

Muljadi, Eduard

1998-08-25

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility.

Variable speed wind turbine generator with zero-sequence filter

DOEpatents

Muljadi, E.

1998-08-25

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility. 14 figs.

Truly random number generation: an example

NASA Astrophysics Data System (ADS)

Frauchiger, Daniela; Renner, Renato

2013-10-01

Randomness is crucial for a variety of applications, ranging from gambling to computer simulations, and from cryptography to statistics. However, many of the currently used methods for generating randomness do not meet the criteria that are necessary for these applications to work properly and safely. A common problem is that a sequence of numbers may look random but nevertheless not be truly random. In fact, the sequence may pass all standard statistical tests and yet be perfectly predictable. This renders it useless for many applications. For example, in cryptography, the predictability of a "andomly" chosen password is obviously undesirable. Here, we review a recently developed approach to generating true | and hence unpredictable | randomness.

Problems in turbidite research: A need for COMFAN

USGS Publications Warehouse

Normark, W.R.; Mutti, E.; Bouma, A.H.

1984-01-01

Comparison of modern submarine fans and ancient turbidite sequences is still in its infancy, mainly because of the incompatibility of study approaches. Research on modern fan systems mainly deals with morphologic aspects and surficial sediments, while observations on ancient turbidite formations are mostly directed to vertical sequences. The lack of a common data set also results from different scales of observation. To review the current status of modern and ancient turbidite research, an international group of specialists formed COMFAN (Committee on Fans) and met in September 1982 at the Gulf Research and Development Company research facilities in Pennsylvania. ?? 1984 Springer-Verlag New York Inc.

ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing.

PubMed

Chen, Xingqi; Shen, Ying; Draper, Will; Buenrostro, Jason D; Litzenburger, Ulrike; Cho, Seung Woo; Satpathy, Ansuman T; Carter, Ava C; Ghosh, Rajarshi P; East-Seletsky, Alexandra; Doudna, Jennifer A; Greenleaf, William J; Liphardt, Jan T; Chang, Howard Y

2016-12-01

Spatial organization of the genome plays a central role in gene expression, DNA replication, and repair. But current epigenomic approaches largely map DNA regulatory elements outside of the native context of the nucleus. Here we report assay of transposase-accessible chromatin with visualization (ATAC-see), a transposase-mediated imaging technology that employs direct imaging of the accessible genome in situ, cell sorting, and deep sequencing to reveal the identity of the imaged elements. ATAC-see revealed the cell-type-specific spatial organization of the accessible genome and the coordinated process of neutrophil chromatin extrusion, termed NETosis. Integration of ATAC-see with flow cytometry enables automated quantitation and prospective cell isolation as a function of chromatin accessibility, and it reveals a cell-cycle dependence of chromatin accessibility that is especially dynamic in G1 phase. The integration of imaging and epigenomics provides a general and scalable approach for deciphering the spatiotemporal architecture of gene control.

Single-Cell Genomic Analysis in Plants

PubMed Central

Hu, Haifei; Scheben, Armin; Edwards, David

2018-01-01

Individual cells in an organism are variable, which strongly impacts cellular processes. Advances in sequencing technologies have enabled single-cell genomic analysis to become widespread, addressing shortcomings of analyses conducted on populations of bulk cells. While the field of single-cell plant genomics is in its infancy, there is great potential to gain insights into cell lineage and functional cell types to help understand complex cellular interactions in plants. In this review, we discuss current approaches for single-cell plant genomic analysis, with a focus on single-cell isolation, DNA amplification, next-generation sequencing, and bioinformatics analysis. We outline the technical challenges of analysing material from a single plant cell, and then examine applications of single-cell genomics and the integration of this approach with genome editing. Finally, we indicate future directions we expect in the rapidly developing field of plant single-cell genomic analysis. PMID:29361790

Genetic Characterization of Fasciola Isolates from West Azerbaijan Province Iran Based on ITS1 and ITS2 Sequence of Ribosomal DNA

PubMed Central

GALAVANI, Hossein; GHOLIZADEH, Saber; HAZRATI TAPPEH, Khosrow

2016-01-01

Background: Fascioliasis, caused by Fasciola hepatica and F. gigantica, has medical and economic importance in the world. Molecular approaches comparing traditional methods using for identification and characterization of Fasciola spp. are precise and reliable. The aims of current study were molecular characterization of Fasciola spp. in West Azerbaijan Province, Iran and then comparative analysis of them using GenBank sequences. Methods: A total number of 580 isolates were collected from different hosts in five cities of West Azerbaijan Province, in 2014 from 90 slaughtered cattle (n=50) and sheep (n=40). After morphological identification and DNA extraction, designing specific primer were used to amplification of ITS1, 5.8s and ITS2 regions, 50 samples were conducted to sequence, randomly. Result: Using morphometric characters 99.14% and 0.86% of isolates identified as F. hepatica and F. gigantica, respectively. PCR amplification of 1081 bp fragment and sequencing result showed 100% similarity with F. hepatica in ITS1 (428 bp), 5.8s (158 bp), and ITS2 (366 bp) regions. Sequence comparison among current study sequences and GenBank data showed 98% identity with 11 nucleotide mismatches. However, in phylogenetic tree F. hepatica sequences of West Azerbaijan Province, Iran, were in a close relationship with Iranian, Asian, and African isolates. Conclusions: Only F. hepatica species is distributed among sheep and cattle in West Azerbaijan Province Iran. However, 5 and 6 bp variation in ITS1 and ITS2 regions, respectively, is not enough to separate of Fasciola spp. Therefore, more studies are essential for designing new molecular markers to correct species identification. PMID:27095969

Precise detection of de novo single nucleotide variants in human genomes.

PubMed

Gómez-Romero, Laura; Palacios-Flores, Kim; Reyes, José; García, Delfino; Boege, Margareta; Dávila, Guillermo; Flores, Margarita; Schatz, Michael C; Palacios, Rafael

2018-05-22

The precise determination of de novo genetic variants has enormous implications across different fields of biology and medicine, particularly personalized medicine. Currently, de novo variations are identified by mapping sample reads from a parent-offspring trio to a reference genome, allowing for a certain degree of differences. While widely used, this approach often introduces false-positive (FP) results due to misaligned reads and mischaracterized sequencing errors. In a previous study, we developed an alternative approach to accurately identify single nucleotide variants (SNVs) using only perfect matches. However, this approach could be applied only to haploid regions of the genome and was computationally intensive. In this study, we present a unique approach, coverage-based single nucleotide variant identification (COBASI), which allows the exploration of the entire genome using second-generation short sequence reads without extensive computing requirements. COBASI identifies SNVs using changes in coverage of exactly matching unique substrings, and is particularly suited for pinpointing de novo SNVs. Unlike other approaches that require population frequencies across hundreds of samples to filter out any methodological biases, COBASI can be applied to detect de novo SNVs within isolated families. We demonstrate this capability through extensive simulation studies and by studying a parent-offspring trio we sequenced using short reads. Experimental validation of all 58 candidate de novo SNVs and a selection of non-de novo SNVs found in the trio confirmed zero FP calls. COBASI is available as open source at https://github.com/Laura-Gomez/COBASI for any researcher to use. Copyright © 2018 the Author(s). Published by PNAS.

A Segment of the Apospory-Specific Genomic Region Is Highly Microsyntenic Not Only between the Apomicts Pennisetum squamulatum and Buffelgrass, But Also with a Rice Chromosome 11 Centromeric-Proximal Genomic Region1[W

PubMed Central

Gualtieri, Gustavo; Conner, Joann A.; Morishige, Daryl T.; Moore, L. David; Mullet, John E.; Ozias-Akins, Peggy

2006-01-01

Bacterial artificial chromosome (BAC) clones from apomicts Pennisetum squamulatum and buffelgrass (Cenchrus ciliaris), isolated with the apospory-specific genomic region (ASGR) marker ugt197, were assembled into contigs that were extended by chromosome walking. Gene-like sequences from contigs were identified by shotgun sequencing and BLAST searches, and used to isolate orthologous rice contigs. Additional gene-like sequences in the apomicts' contigs were identified by bioinformatics using fully sequenced BACs from orthologous rice contigs as templates, as well as by interspecies, whole-contig cross-hybridizations. Hierarchical contig orthology was rapidly assessed by constructing detailed long-range contig molecular maps showing the distribution of gene-like sequences and markers, and searching for microsyntenic patterns of sequence identity and spatial distribution within and across species contigs. We found microsynteny between P. squamulatum and buffelgrass contigs. Importantly, this approach also enabled us to isolate from within the rice (Oryza sativa) genome contig Rice A, which shows the highest microsynteny and is most orthologous to the ugt197-containing C1C buffelgrass contig. Contig Rice A belongs to the rice genome database contig 77 (according to the current September 12, 2003, rice fingerprint contig build) that maps proximal to the chromosome 11 centromere, a feature that interestingly correlates with the mapping of ASGR-linked BACs proximal to the centromere or centromere-like sequences. Thus, relatedness between these two orthologous contigs is supported both by their molecular microstructure and by their centromeric-proximal location. Our discoveries promote the use of a microsynteny-based positional-cloning approach using the rice genome as a template to aid in constructing the ASGR toward the isolation of genes underlying apospory. PMID:16415213

A segment of the apospory-specific genomic region is highly microsyntenic not only between the apomicts Pennisetum squamulatum and buffelgrass, but also with a rice chromosome 11 centromeric-proximal genomic region.

PubMed

Gualtieri, Gustavo; Conner, Joann A; Morishige, Daryl T; Moore, L David; Mullet, John E; Ozias-Akins, Peggy

2006-03-01

Bacterial artificial chromosome (BAC) clones from apomicts Pennisetum squamulatum and buffelgrass (Cenchrus ciliaris), isolated with the apospory-specific genomic region (ASGR) marker ugt197, were assembled into contigs that were extended by chromosome walking. Gene-like sequences from contigs were identified by shotgun sequencing and BLAST searches, and used to isolate orthologous rice contigs. Additional gene-like sequences in the apomicts' contigs were identified by bioinformatics using fully sequenced BACs from orthologous rice contigs as templates, as well as by interspecies, whole-contig cross-hybridizations. Hierarchical contig orthology was rapidly assessed by constructing detailed long-range contig molecular maps showing the distribution of gene-like sequences and markers, and searching for microsyntenic patterns of sequence identity and spatial distribution within and across species contigs. We found microsynteny between P. squamulatum and buffelgrass contigs. Importantly, this approach also enabled us to isolate from within the rice (Oryza sativa) genome contig Rice A, which shows the highest microsynteny and is most orthologous to the ugt197-containing C1C buffelgrass contig. Contig Rice A belongs to the rice genome database contig 77 (according to the current September 12, 2003, rice fingerprint contig build) that maps proximal to the chromosome 11 centromere, a feature that interestingly correlates with the mapping of ASGR-linked BACs proximal to the centromere or centromere-like sequences. Thus, relatedness between these two orthologous contigs is supported both by their molecular microstructure and by their centromeric-proximal location. Our discoveries promote the use of a microsynteny-based positional-cloning approach using the rice genome as a template to aid in constructing the ASGR toward the isolation of genes underlying apospory.

Divide and Conquer (DC) BLAST: fast and easy BLAST execution within HPC environments

DOE PAGES

Yim, Won Cheol; Cushman, John C.

2017-07-22

Bioinformatics is currently faced with very large-scale data sets that lead to computational jobs, especially sequence similarity searches, that can take absurdly long times to run. For example, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST and BLAST+) suite, which is by far the most widely used tool for rapid similarity searching among nucleic acid or amino acid sequences, is highly central processing unit (CPU) intensive. While the BLAST suite of programs perform searches very rapidly, they have the potential to be accelerated. In recent years, distributed computing environments have become more widely accessible andmore » used due to the increasing availability of high-performance computing (HPC) systems. Therefore, simple solutions for data parallelization are needed to expedite BLAST and other sequence analysis tools. However, existing software for parallel sequence similarity searches often requires extensive computational experience and skill on the part of the user. In order to accelerate BLAST and other sequence analysis tools, Divide and Conquer BLAST (DCBLAST) was developed to perform NCBI BLAST searches within a cluster, grid, or HPC environment by using a query sequence distribution approach. Scaling from one (1) to 256 CPU cores resulted in significant improvements in processing speed. Thus, DCBLAST dramatically accelerates the execution of BLAST searches using a simple, accessible, robust, and parallel approach. DCBLAST works across multiple nodes automatically and it overcomes the speed limitation of single-node BLAST programs. DCBLAST can be used on any HPC system, can take advantage of hundreds of nodes, and has no output limitations. Thus, this freely available tool simplifies distributed computation pipelines to facilitate the rapid discovery of sequence similarities between very large data sets.« less

Divide and Conquer (DC) BLAST: fast and easy BLAST execution within HPC environments

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

Yim, Won Cheol; Cushman, John C.

Bioinformatics is currently faced with very large-scale data sets that lead to computational jobs, especially sequence similarity searches, that can take absurdly long times to run. For example, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST and BLAST+) suite, which is by far the most widely used tool for rapid similarity searching among nucleic acid or amino acid sequences, is highly central processing unit (CPU) intensive. While the BLAST suite of programs perform searches very rapidly, they have the potential to be accelerated. In recent years, distributed computing environments have become more widely accessible andmore » used due to the increasing availability of high-performance computing (HPC) systems. Therefore, simple solutions for data parallelization are needed to expedite BLAST and other sequence analysis tools. However, existing software for parallel sequence similarity searches often requires extensive computational experience and skill on the part of the user. In order to accelerate BLAST and other sequence analysis tools, Divide and Conquer BLAST (DCBLAST) was developed to perform NCBI BLAST searches within a cluster, grid, or HPC environment by using a query sequence distribution approach. Scaling from one (1) to 256 CPU cores resulted in significant improvements in processing speed. Thus, DCBLAST dramatically accelerates the execution of BLAST searches using a simple, accessible, robust, and parallel approach. DCBLAST works across multiple nodes automatically and it overcomes the speed limitation of single-node BLAST programs. DCBLAST can be used on any HPC system, can take advantage of hundreds of nodes, and has no output limitations. Thus, this freely available tool simplifies distributed computation pipelines to facilitate the rapid discovery of sequence similarities between very large data sets.« less

Ab initio electron propagator calculations of transverse conduction through DNA nucleotide bases in 1-nm nanopore corroborate third generation sequencing.

PubMed

Kletsov, Aleksey A; Glukhovskoy, Evgeny G; Chumakov, Aleksey S; Ortiz, Joseph V

2016-01-01

The conduction properties of DNA molecule, particularly its transverse conductance (electron transfer through nucleotide bridges), represent a point of interest for DNA chemistry community, especially for DNA sequencing. However, there is no fully developed first-principles theory for molecular conductance and current that allows one to analyze the transverse flow of electrical charge through a nucleotide base. We theoretically investigate the transverse electron transport through all four DNA nucleotide bases by implementing an unbiased ab initio theoretical approach, namely, the electron propagator theory. The electrical conductance and current through DNA nucleobases (guanine [G], cytosine [C], adenine [A] and thymine [T]) inserted into a model 1-nm Ag-Ag nanogap are calculated. The magnitudes of the calculated conductance and current are ordered in the following hierarchies: gA>gG>gC>gT and IG>IA>IT>IC correspondingly. The new distinguishing parameter for the nucleobase identification is proposed, namely, the onset bias magnitude. Nucleobases exhibit the following hierarchy with respect to this parameter: Vonset(A)

Bioinformatics and genomic analysis of transposable elements in eukaryotic genomes.

PubMed

Janicki, Mateusz; Rooke, Rebecca; Yang, Guojun

2011-08-01

A major portion of most eukaryotic genomes are transposable elements (TEs). During evolution, TEs have introduced profound changes to genome size, structure, and function. As integral parts of genomes, the dynamic presence of TEs will continue to be a major force in reshaping genomes. Early computational analyses of TEs in genome sequences focused on filtering out "junk" sequences to facilitate gene annotation. When the high abundance and diversity of TEs in eukaryotic genomes were recognized, these early efforts transformed into the systematic genome-wide categorization and classification of TEs. The availability of genomic sequence data reversed the classical genetic approaches to discovering new TE families and superfamilies. Curated TE databases and their accurate annotation of genome sequences in turn facilitated the studies on TEs in a number of frontiers including: (1) TE-mediated changes of genome size and structure, (2) the influence of TEs on genome and gene functions, (3) TE regulation by host, (4) the evolution of TEs and their population dynamics, and (5) genomic scale studies of TE activity. Bioinformatics and genomic approaches have become an integral part of large-scale studies on TEs to extract information with pure in silico analyses or to assist wet lab experimental studies. The current revolution in genome sequencing technology facilitates further progress in the existing frontiers of research and emergence of new initiatives. The rapid generation of large-sequence datasets at record low costs on a routine basis is challenging the computing industry on storage capacity and manipulation speed and the bioinformatics community for improvement in algorithms and their implementations.

Microsatellite analysis in the genome of Acanthaceae: An in silico approach

PubMed Central

Kaliswamy, Priyadharsini; Vellingiri, Srividhya; Nathan, Bharathi; Selvaraj, Saravanakumar

2015-01-01

Background: Acanthaceae is one of the advanced and specialized families with conventionally used medicinal plants. Simple sequence repeats (SSRs) play a major role as molecular markers for genome analysis and plant breeding. The microsatellites existing in the complete genome sequences would help to attain a direct role in the genome organization, recombination, gene regulation, quantitative genetic variation, and evolution of genes. Objective: The current study reports the frequency of microsatellites and appropriate markers for the Acanthaceae family genome sequences. Materials and Methods: The whole nucleotide sequences of Acanthaceae species were obtained from National Center for Biotechnology Information database and screened for the presence of SSRs. SSR Locator tool was used to predict the microsatellites and inbuilt Primer3 module was used for primer designing. Results: Totally 110 repeats from 108 sequences of Acanthaceae family plant genomes were identified, and the occurrence of dinucleotide repeats was found to be abundant in the genome sequences. The essential amino acid isoleucine was found rich in all the sequences. We also designed the SSR-based primers/markers for 59 sequences of this family that contains microsatellite repeats in their genome. Conclusion: The identified microsatellites and primers might be useful for breeding and genetic studies of plants that belong to Acanthaceae family in the future. PMID:25709226

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing

PubMed Central

Morgan, Horatio H.; du Toit, Maret; Setati, Mathabatha E.

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity. PMID:28553266

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing.

PubMed

Morgan, Horatio H; du Toit, Maret; Setati, Mathabatha E

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity.

Neuropeptide modulation of pattern-generating systems in crustaceans: comparative studies and approaches.

PubMed

Dickinson, Patsy S; Qu, Xuan; Stanhope, Meredith E

2016-12-01

Central pattern generators are subject to modulation by peptides, allowing for flexibility in patterned output. Current techniques used to characterize peptides include mass spectrometry and transcriptomics. In recent years, hundreds of neuropeptides have been sequenced from crustaceans; mass spectrometry has been used to identify peptides and to determine their levels and locations, setting the stage for comparative studies investigating the physiological roles of peptides. Such studies suggest that there is some evolutionary conservation of function, but also divergence of function even within a species. With current baseline data, it should be possible to begin using comparative approaches to ask fundamental questions about why peptides are encoded the way that they are and how this affects nervous system function. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-03-01

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

Current management of penetrating torso trauma: nontherapeutic is not good enough anymore.

PubMed

Ball, Chad G

2014-04-01

A highly organized approach to the evaluation and treatment of penetrating torso injuries based on regional anatomy provides rapid diagnostic and therapeutic consistency. It also minimizes delays in diagnosis, missed injuries and nontherapeutic laparotomies. This review discusses an optimal sequence of structured rapid assessments that allow the clinician to rapidly proceed to gold standard therapies with a minimal risk of associated morbidity.

Radial expansion of the tail current disruption during substorms - A new approach to the substorm onset region

NASA Technical Reports Server (NTRS)

Ohtani, S.; Kokubun, S.; Russell, C. T.

1992-01-01

A new method is used to examine the radial expansion of the tail current disruption and the substorm onset region. The expansion of the disruption region is specified by examining the time sequence (phase relationship) between the north-south component and the sun-earth component. This method is tested by applying it to the March 6, 1979, event. The phase relationship indicates that the current disruption started on the earthward side of the spacecraft, and expanded tailward past the spacecraft. The method was used for 13 events selected from the ISEE magnetometer data. The results indicate that the current disruption usually starts in the near-earth magnetotail and often within 15 RE from the earth.

Development of a real-time PCR for detection of Staphylococcus pseudintermedius using a novel automated comparison of whole-genome sequences.

PubMed

Verstappen, Koen M; Huijbregts, Loes; Spaninks, Mirlin; Wagenaar, Jaap A; Fluit, Ad C; Duim, Birgitta

2017-01-01

Staphylococcus pseudintermedius is an opportunistic pathogen in dogs and cats and occasionally causes infections in humans. S. pseudintermedius is often resistant to multiple classes of antimicrobials. It requires a reliable detection so that it is not misidentified as S. aureus. Phenotypic and currently-used molecular-based diagnostic assays lack specificity or are labour-intensive using multiplex PCR or nucleic acid sequencing. The aim of this study was to identify a specific target for real-time PCR by comparing whole genome sequences of S. pseudintermedius and non-pseudintermedius.Genome sequences were downloaded from public repositories and supplemented by isolates that were sequenced in this study. A Perl-script was written that analysed 300-nt fragments from a reference genome sequence of S. pseudintermedius and checked if this sequence was present in other S. pseudintermedius genomes (n = 74) and non-pseudintermedius genomes (n = 138). Six sequences specific for S. pseudintermedius were identified (sequence length between 300-500 nt). One sequence, which was located in the spsJ gene, was used to develop primers and a probe. The real-time PCR showed 100% specificity when testing for S. pseudintermedius isolates (n = 54), and eight other staphylococcal species (n = 43). In conclusion, a novel approach by comparing whole genome sequences identified a sequence that is specific for S. pseudintermedius and provided a real-time PCR target for rapid and reliable detection of S. pseudintermedius.

Identification of missing variants by combining multiple analytic pipelines.

PubMed

Ren, Yingxue; Reddy, Joseph S; Pottier, Cyril; Sarangi, Vivekananda; Tian, Shulan; Sinnwell, Jason P; McDonnell, Shannon K; Biernacka, Joanna M; Carrasquillo, Minerva M; Ross, Owen A; Ertekin-Taner, Nilüfer; Rademakers, Rosa; Hudson, Matthew; Mainzer, Liudmila Sergeevna; Asmann, Yan W

2018-04-16

After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires large sample sizes for statistical power and has brought up questions about whether the current variant calling practices are adequate for large cohorts. It is well-known that there are discrepancies between variants called by different pipelines, and that using a single pipeline always misses true variants exclusively identifiable by other pipelines. Nonetheless, it is common practice today to call variants by one pipeline due to computational cost and assume that false negative calls are a small percent of total. We analyzed 10,000 exomes from the Alzheimer's Disease Sequencing Project (ADSP) using multiple analytic pipelines consisting of different read aligners and variant calling strategies. We compared variants identified by using two aligners in 50,100, 200, 500, 1000, and 1952 samples; and compared variants identified by adding single-sample genotyping to the default multi-sample joint genotyping in 50,100, 500, 2000, 5000 and 10,000 samples. We found that using a single pipeline missed increasing numbers of high-quality variants correlated with sample sizes. By combining two read aligners and two variant calling strategies, we rescued 30% of pass-QC variants at sample size of 2000, and 56% at 10,000 samples. The rescued variants had higher proportions of low frequency (minor allele frequency [MAF] 1-5%) and rare (MAF < 1%) variants, which are the very type of variants of interest. In 660 Alzheimer's disease cases with earlier onset ages of ≤65, 4 out of 13 (31%) previously-published rare pathogenic and protective mutations in APP, PSEN1, and PSEN2 genes were undetected by the default one-pipeline approach but recovered by the multi-pipeline approach. Identification of the complete variant set from sequencing data is the prerequisite of genetic association analyses. The current analytic practice of calling genetic variants from sequencing data using a single bioinformatics pipeline is no longer adequate with the increasingly large projects. The number and percentage of quality variants that passed quality filters but are missed by the one-pipeline approach rapidly increased with sample size.

Classifying short genomic fragments from novel lineages using composition and homology

PubMed Central

2011-01-01

Background The assignment of taxonomic attributions to DNA fragments recovered directly from the environment is a vital step in metagenomic data analysis. Assignments can be made using rank-specific classifiers, which assign reads to taxonomic labels from a predetermined level such as named species or strain, or rank-flexible classifiers, which choose an appropriate taxonomic rank for each sequence in a data set. The choice of rank typically depends on the optimal model for a given sequence and on the breadth of taxonomic groups seen in a set of close-to-optimal models. Homology-based (e.g., LCA) and composition-based (e.g., PhyloPythia, TACOA) rank-flexible classifiers have been proposed, but there is at present no hybrid approach that utilizes both homology and composition. Results We first develop a hybrid, rank-specific classifier based on BLAST and Naïve Bayes (NB) that has comparable accuracy and a faster running time than the current best approach, PhymmBL. By substituting LCA for BLAST or allowing the inclusion of suboptimal NB models, we obtain a rank-flexible classifier. This hybrid classifier outperforms established rank-flexible approaches on simulated metagenomic fragments of length 200 bp to 1000 bp and is able to assign taxonomic attributions to a subset of sequences with few misclassifications. We then demonstrate the performance of different classifiers on an enhanced biological phosphorous removal metagenome, illustrating the advantages of rank-flexible classifiers when representative genomes are absent from the set of reference genomes. Application to a glacier ice metagenome demonstrates that similar taxonomic profiles are obtained across a set of classifiers which are increasingly conservative in their classification. Conclusions Our NB-based classification scheme is faster than the current best composition-based algorithm, Phymm, while providing equally accurate predictions. The rank-flexible variant of NB, which we term ε-NB, is complementary to LCA and can be combined with it to yield conservative prediction sets of very high confidence. The simple parameterization of LCA and ε-NB allows for tuning of the balance between more predictions and increased precision, allowing the user to account for the sensitivity of downstream analyses to misclassified or unclassified sequences. PMID:21827705

Sensitive and specific detection of EML4-ALK rearrangements in non-small cell lung cancer (NSCLC) specimens by multiplex amplicon RNA massive parallel sequencing.

PubMed

Moskalev, Evgeny A; Frohnauer, Judith; Merkelbach-Bruse, Sabine; Schildhaus, Hans-Ulrich; Dimmler, Arno; Schubert, Thomas; Boltze, Carsten; König, Helmut; Fuchs, Florian; Sirbu, Horia; Rieker, Ralf J; Agaimy, Abbas; Hartmann, Arndt; Haller, Florian

2014-06-01

Recurrent gene fusions of anaplastic lymphoma receptor tyrosine kinase (ALK) and echinoderm microtubule-associated protein-like 4 (EML4) have been recently identified in ∼5% of non-small cell lung cancers (NSCLCs) and are targets for selective tyrosine kinase inhibitors. While fluorescent in situ hybridization (FISH) is the current gold standard for detection of EML4-ALK rearrangements, several limitations exist including high costs, time-consuming evaluation and somewhat equivocal interpretation of results. In contrast, targeted massive parallel sequencing has been introduced as a powerful method for simultaneous and sensitive detection of multiple somatic mutations even in limited biopsies, and is currently evolving as the method of choice for molecular diagnostic work-up of NSCLCs. We developed a novel approach for indirect detection of EML4-ALK rearrangements based on 454 massive parallel sequencing after reverse transcription and subsequent multiplex amplification (multiplex ALK RNA-seq) which takes advantage of unbalanced expression of the 5' and 3' ALK mRNA regions. Two lung cancer cell lines and a selected series of 32 NSCLC samples including 11 cases with EML4-ALK rearrangement were analyzed with this novel approach in comparison to ALK FISH, ALK qRT-PCR and EML4-ALK RT-PCR. The H2228 cell line with known EML4-ALK rearrangement showed 171 and 729 reads for 5' and 3' ALK regions, respectively, demonstrating a clearly unbalanced expression pattern. In contrast, the H1299 cell line with ALK wildtype status displayed no reads for both ALK regions. Considering a threshold of 100 reads for 3' ALK region as indirect indicator of EML4-ALK rearrangement, there was 100% concordance between the novel multiplex ALK RNA-seq approach and ALK FISH among all 32 NSCLC samples. Multiplex ALK RNA-seq is a sensitive and specific method for indirect detection of EML4-ALK rearrangements, and can be easily implemented in panel based molecular diagnostic work-up of NSCLCs by massive parallel sequencing. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Application of the High Resolution Melting analysis for genetic mapping of Sequence Tagged Site markers in narrow-leafed lupin (Lupinus angustifolius L.).

PubMed

Kamel, Katarzyna A; Kroc, Magdalena; Święcicki, Wojciech

2015-01-01

Sequence tagged site (STS) markers are valuable tools for genetic and physical mapping that can be successfully used in comparative analyses among related species. Current challenges for molecular markers genotyping in plants include the lack of fast, sensitive and inexpensive methods suitable for sequence variant detection. In contrast, high resolution melting (HRM) is a simple and high-throughput assay, which has been widely applied in sequence polymorphism identification as well as in the studies of genetic variability and genotyping. The present study is the first attempt to use the HRM analysis to genotype STS markers in narrow-leafed lupin (Lupinus angustifolius L.). The sensitivity and utility of this method was confirmed by the sequence polymorphism detection based on melting curve profiles in the parental genotypes and progeny of the narrow-leafed lupin mapping population. Application of different approaches, including amplicon size and a simulated heterozygote analysis, has allowed for successful genetic mapping of 16 new STS markers in the narrow-leafed lupin genome.

Storage and utilization of HLA genomic data--new approaches to HLA typing.

PubMed

Helmberg, W

2000-01-01

Currently available DNA-based HLA typing assays can provide detailed information about sequence motifs of a tested sample. It is still a common practice, however, for information acquired by high-resolution sequence specific oligonucleotide probe (SSOP) typing or sequence specific priming (SSP) to be presented in a low-resolution serological format. Unfortunately, this representation can lead to significant loss of useful data in many cases. An alternative to assigning allele equivalents to suchDNA typing results is simply to store the observed typing pattern and utilize the information with the help of Virtual DNA Analysis (VDA). Interpretation of the stored typing patterns can then be updated based on newly defined alleles, assuming the sequence motifs detected by the typing reagents are known. Rather than updating reagent specificities in individual laboratories, such updates should be performed in a central, publicly available sequence database. By referring to this database, HLA genomic data can then be stored and transferred between laboratories without loss of information. The 13th International Histocompatibility Workshop offers an ideal opportunity to begin building this common database for the entire human MHC.

A technique for setting analytical thresholds in massively parallel sequencing-based forensic DNA analysis

PubMed Central

2017-01-01

Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described. PMID:28542338

A technique for setting analytical thresholds in massively parallel sequencing-based forensic DNA analysis.

PubMed

Young, Brian; King, Jonathan L; Budowle, Bruce; Armogida, Luigi

2017-01-01

Amplicon (targeted) sequencing by massively parallel sequencing (PCR-MPS) is a potential method for use in forensic DNA analyses. In this application, PCR-MPS may supplement or replace other instrumental analysis methods such as capillary electrophoresis and Sanger sequencing for STR and mitochondrial DNA typing, respectively. PCR-MPS also may enable the expansion of forensic DNA analysis methods to include new marker systems such as single nucleotide polymorphisms (SNPs) and insertion/deletions (indels) that currently are assayable using various instrumental analysis methods including microarray and quantitative PCR. Acceptance of PCR-MPS as a forensic method will depend in part upon developing protocols and criteria that define the limitations of a method, including a defensible analytical threshold or method detection limit. This paper describes an approach to establish objective analytical thresholds suitable for multiplexed PCR-MPS methods. A definition is proposed for PCR-MPS method background noise, and an analytical threshold based on background noise is described.

International Standards for Genomes, Transcriptomes, and Metagenomes

PubMed Central

Mason, Christopher E.; Afshinnekoo, Ebrahim; Tighe, Scott; Wu, Shixiu; Levy, Shawn

2017-01-01

Challenges and biases in preparing, characterizing, and sequencing DNA and RNA can have significant impacts on research in genomics across all kingdoms of life, including experiments in single-cells, RNA profiling, and metagenomics (across multiple genomes). Technical artifacts and contamination can arise at each point of sample manipulation, extraction, sequencing, and analysis. Thus, the measurement and benchmarking of these potential sources of error are of paramount importance as next-generation sequencing (NGS) projects become more global and ubiquitous. Fortunately, a variety of methods, standards, and technologies have recently emerged that improve measurements in genomics and sequencing, from the initial input material to the computational pipelines that process and annotate the data. Here we review current standards and their applications in genomics, including whole genomes, transcriptomes, mixed genomic samples (metagenomes), and the modified bases within each (epigenomes and epitranscriptomes). These standards, tools, and metrics are critical for quantifying the accuracy of NGS methods, which will be essential for robust approaches in clinical genomics and precision medicine. PMID:28337071

16S rRNA Gene Sequencing for Deciphering the Colorectal Cancer Gut Microbiome: Current Protocols and Workflows.

PubMed

Osman, Muhammad-Afiq; Neoh, Hui-Min; Ab Mutalib, Nurul-Syakima; Chin, Siok-Fong; Jamal, Rahman

2018-01-01

The human gut holds the densest microbiome ecosystem essential in maintaining a healthy host physiology, whereby disruption of this ecosystem has been linked to the development of colorectal cancer (CRC). The advent of next-generation sequencing technologies such as the 16S rRNA gene sequencing has enabled characterization of the CRC gut microbiome architecture in an affordable and culture-free approach. Nevertheless, the lack of standardization in handling and storage of biospecimens, nucleic acid extraction, 16S rRNA gene primer selection, length, and depth of sequencing and bioinformatics analyses have contributed to discrepancies found in various published studies of this field. Accurate characterization of the CRC microbiome found in different stages of CRC has the potential to be developed into a screening tool in the clinical setting. This mini review aims to concisely compile all available CRC microbiome studies performed till end of 2016 and to suggest standardized protocols that are crucial in developing a gut microbiome screening panel for CRC.

GAMES identifies and annotates mutations in next-generation sequencing projects.

PubMed

Sana, Maria Elena; Iascone, Maria; Marchetti, Daniela; Palatini, Jeff; Galasso, Marco; Volinia, Stefano

2011-01-01

Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users. We developed GAMES (Genomic Analysis of Mutations Extracted by Sequencing), a pipeline aiming to serve as an efficient middleman between data deluge and investigators. GAMES attains multiple levels of filtering and annotation, such as aligning the reads to a reference genome, performing quality control and mutational analysis, integrating results with genome annotations and sorting each mismatch/deletion according to a range of parameters. Variations are matched to known polymorphisms. The prediction of functional mutations is achieved by using different approaches. Overall GAMES enables an effective complexity reduction in large-scale DNA-sequencing projects. GAMES is available free of charge to academic users and may be obtained from http://aqua.unife.it/GAMES.

A novel approach on accelerated ageing towards reliability optimization of high concentration photovoltaic cells

NASA Astrophysics Data System (ADS)

Tsanakas, John A.; Jaffre, Damien; Sicre, Mathieu; Elouamari, Rachid; Vossier, Alexis; de Salins, Jean-Edouard; Bechou, Laurent; Levrier, Bruno; Perona, Arnaud; Dollet, Alain

2014-09-01

This paper presents a preliminary study upon a novel approach proposed for highly accelerated ageing and reliability optimization of high concentrating photovoltaic (HCPV) cells and assemblies. The intended approach aims to overcome several limitations of some current accelerated ageing tests (AAT) adopted up today, proposing the use of an alternative experimental set-up for performing faster and more realistic thermal cycles, under real sun, without the involvement of environmental chamber. The study also includes specific characterization techniques, before and after each AAT sequence, which respectively provide the initial and final diagnosis on the condition of the tested sample. The acquired data from these diagnostic/characterization methods are then used as indices to determine both quantitatively and qualitatively the severity of degradation and, thus, the ageing level for each tested HCPV assembly or cell sample. Ultimate goal of such "initial diagnosis - AAT - final diagnosis" sequences is to provide the basis for a future work on the reliability analysis of the main degradation mechanisms and confident prediction of failure propagation in HCPV cells, by means of acceleration factor (AF) and mean-time-to-failure (MTTF) estimations.

A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative.

PubMed

Shashi, Vandana; Schoch, Kelly; Spillmann, Rebecca; Cope, Heidi; Tan, Queenie K-G; Walley, Nicole; Pena, Loren; McConkie-Rosell, Allyn; Jiang, Yong-Hui; Stong, Nicholas; Need, Anna C; Goldstein, David B

2018-06-15

Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10-15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. In 38 ES negative patients an individualized genomic-phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

Comprehensive evolutionary and phylogenetic analysis of Hepacivirus N (HNV).

PubMed

da Silva, M S; Junqueira, D M; Baumbach, L F; Cibulski, S P; Mósena, A C S; Weber, M N; Silveira, S; de Moraes, G M; Maia, R D; Coimbra, V C S; Canal, C W

2018-05-24

Hepaciviruses (HVs) have been detected in several domestic and wild animals and present high genetic diversity. The actual classification divides the genus Hepacivirus into 14 species (A-N), according to their phylogenetic relationships, including the bovine hepacivirus [Hepacivirus N (HNV)]. In this study, we confirmed HNV circulation in Brazil and sequenced the whole genome of two strains. Based on the current classification of HCV, which is divided into genotypes and subtypes, we analysed all available bovine hepacivirus sequences in the GenBank database and proposed an HNV classification. All of the sequences were grouped into a single genotype, putatively named 'genotype 1'. This genotype can be clearly divided into four subtypes: A and D containing sequences from Germany and Brazil, respectively, and B and C containing Ghanaian sequences. In addition, the NS3-coding region was used to estimate the time to the most recent common ancestor (TMRCA) of each subtype, using a Bayesian approach and a relaxed molecular clock model. The analyses indicated a common origin of the virus circulating in Germany and Brazil. Ghanaian sequences seemed to have an older TMRCA, indicating a long time of circulation of these viruses in the African continent.

Evolutionary dynamics of retrotransposons assessed by high-throughput sequencing in wild relatives of wheat.

PubMed

Senerchia, Natacha; Wicker, Thomas; Felber, François; Parisod, Christian

2013-01-01

Transposable elements (TEs) represent a major fraction of plant genomes and drive their evolution. An improved understanding of genome evolution requires the dynamics of a large number of TE families to be considered. We put forward an approach bypassing the required step of a complete reference genome to assess the evolutionary trajectories of high copy number TE families from genome snapshot with high-throughput sequencing. Low coverage sequencing of the complex genomes of Aegilops cylindrica and Ae. geniculata using 454 identified more than 70% of the sequences as known TEs, mainly long terminal repeat (LTR) retrotransposons. Comparing the abundance of reads as well as patterns of sequence diversity and divergence within and among genomes assessed the dynamics of 44 major LTR retrotransposon families of the 165 identified. In particular, molecular population genetics on individual TE copies distinguished recently active from quiescent families and highlighted different evolutionary trajectories of retrotransposons among related species. This work presents a suite of tools suitable for current sequencing data, allowing to address the genome-wide evolutionary dynamics of TEs at the family level and advancing our understanding of the evolution of nonmodel genomes.

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

PubMed Central

Aslam, Luqman; Beal, Kathryn; Ann Blomberg, Le; Bouffard, Pascal; Burt, David W.; Crasta, Oswald; Crooijmans, Richard P. M. A.; Cooper, Kristal; Coulombe, Roger A.; De, Supriyo; Delany, Mary E.; Dodgson, Jerry B.; Dong, Jennifer J.; Evans, Clive; Frederickson, Karin M.; Flicek, Paul; Florea, Liliana; Folkerts, Otto; Groenen, Martien A. M.; Harkins, Tim T.; Herrero, Javier; Hoffmann, Steve; Megens, Hendrik-Jan; Jiang, Andrew; de Jong, Pieter; Kaiser, Pete; Kim, Heebal; Kim, Kyu-Won; Kim, Sungwon; Langenberger, David; Lee, Mi-Kyung; Lee, Taeheon; Mane, Shrinivasrao; Marcais, Guillaume; Marz, Manja; McElroy, Audrey P.; Modise, Thero; Nefedov, Mikhail; Notredame, Cédric; Paton, Ian R.; Payne, William S.; Pertea, Geo; Prickett, Dennis; Puiu, Daniela; Qioa, Dan; Raineri, Emanuele; Ruffier, Magali; Salzberg, Steven L.; Schatz, Michael C.; Scheuring, Chantel; Schmidt, Carl J.; Schroeder, Steven; Searle, Stephen M. J.; Smith, Edward J.; Smith, Jacqueline; Sonstegard, Tad S.; Stadler, Peter F.; Tafer, Hakim; Tu, Zhijian (Jake); Van Tassell, Curtis P.; Vilella, Albert J.; Williams, Kelly P.; Yorke, James A.; Zhang, Liqing; Zhang, Hong-Bin; Zhang, Xiaojun; Zhang, Yang; Reed, Kent M.

2010-01-01

A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (∼1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest. PMID:20838655

Probing DNA Translocations with Inplane Current Signals in a Graphene Nanoribbon with a Nanopore

PubMed Central

2018-01-01

Many theoretical studies predict that DNA sequencing should be feasible by monitoring the transverse current through a graphene nanoribbon while a DNA molecule translocates through a nanopore in that ribbon. Such a readout would benefit from the special transport properties of graphene, provide ultimate spatial resolution because of the single-atom layer thickness of graphene, and facilitate high-bandwidth measurements. Previous experimental attempts to measure such transverse inplane signals were however dominated by a trivial capacitive response. Here, we explore the feasibility of the approach using a custom-made differential current amplifier that discriminates between the capacitive current signal and the resistive response in the graphene. We fabricate well-defined short and narrow (30 nm × 30 nm) nanoribbons with a 5 nm nanopore in graphene with a high-temperature scanning transmission electron microscope to retain the crystallinity and sensitivity of the graphene. We show that, indeed, resistive modulations can be observed in the graphene current due to DNA translocation through the nanopore, thus demonstrating that DNA sensing with inplane currents in graphene nanostructures is possible. The approach is however exceedingly challenging due to low yields in device fabrication connected to the complex multistep device layout. PMID:29474060

Data compression of discrete sequence: A tree based approach using dynamic programming

NASA Technical Reports Server (NTRS)

Shivaram, Gurusrasad; Seetharaman, Guna; Rao, T. R. N.

1994-01-01

A dynamic programming based approach for data compression of a ID sequence is presented. The compression of an input sequence of size N to that of a smaller size k is achieved by dividing the input sequence into k subsequences and replacing the subsequences by their respective average values. The partitioning of the input sequence is carried with the intention of reducing the mean squared error in the reconstructed sequence. The complexity involved in finding the partitions which would result in such an optimal compressed sequence is reduced by using the dynamic programming approach, which is presented.

NullSeq: A Tool for Generating Random Coding Sequences with Desired Amino Acid and GC Contents.

PubMed

Liu, Sophia S; Hockenberry, Adam J; Lancichinetti, Andrea; Jewett, Michael C; Amaral, Luís A N

2016-11-01

The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. In order to accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. While many tools have been developed to create random nucleotide sequences, protein coding sequences are subject to a unique set of constraints that complicates the process of generating appropriate null models. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content for the purpose of hypothesis testing. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content, which we have developed into a python package. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. Furthermore, this approach can easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes as well as more effective engineering of biological systems.

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.

PubMed

Ollikainen, Noah; de Jong, René M; Kortemme, Tanja

2015-01-01

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art "fixed backbone" design methods perform poorly on these tests, we develop a new "coupled moves" design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.

Transcriptome Profiling of Antimicrobial Resistance in Pseudomonas aeruginosa.

PubMed

Khaledi, Ariane; Schniederjans, Monika; Pohl, Sarah; Rainer, Roman; Bodenhofer, Ulrich; Xia, Boyang; Klawonn, Frank; Bruchmann, Sebastian; Preusse, Matthias; Eckweiler, Denitsa; Dötsch, Andreas; Häussler, Susanne

2016-08-01

Emerging resistance to antimicrobials and the lack of new antibiotic drug candidates underscore the need for optimization of current diagnostics and therapies to diminish the evolution and spread of multidrug resistance. As the antibiotic resistance status of a bacterial pathogen is defined by its genome, resistance profiling by applying next-generation sequencing (NGS) technologies may in the future accomplish pathogen identification, prompt initiation of targeted individualized treatment, and the implementation of optimized infection control measures. In this study, qualitative RNA sequencing was used to identify key genetic determinants of antibiotic resistance in 135 clinical Pseudomonas aeruginosa isolates from diverse geographic and infection site origins. By applying transcriptome-wide association studies, adaptive variations associated with resistance to the antibiotic classes fluoroquinolones, aminoglycosides, and β-lactams were identified. Besides potential novel biomarkers with a direct correlation to resistance, global patterns of phenotype-associated gene expression and sequence variations were identified by predictive machine learning approaches. Our research serves to establish genotype-based molecular diagnostic tools for the identification of the current resistance profiles of bacterial pathogens and paves the way for faster diagnostics for more efficient, targeted treatment strategies to also mitigate the future potential for resistance evolution. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Transcriptome Profiling of Antimicrobial Resistance in Pseudomonas aeruginosa

PubMed Central

Khaledi, Ariane; Schniederjans, Monika; Pohl, Sarah; Rainer, Roman; Bodenhofer, Ulrich; Xia, Boyang; Klawonn, Frank; Bruchmann, Sebastian; Preusse, Matthias; Eckweiler, Denitsa; Dötsch, Andreas

2016-01-01

Emerging resistance to antimicrobials and the lack of new antibiotic drug candidates underscore the need for optimization of current diagnostics and therapies to diminish the evolution and spread of multidrug resistance. As the antibiotic resistance status of a bacterial pathogen is defined by its genome, resistance profiling by applying next-generation sequencing (NGS) technologies may in the future accomplish pathogen identification, prompt initiation of targeted individualized treatment, and the implementation of optimized infection control measures. In this study, qualitative RNA sequencing was used to identify key genetic determinants of antibiotic resistance in 135 clinical Pseudomonas aeruginosa isolates from diverse geographic and infection site origins. By applying transcriptome-wide association studies, adaptive variations associated with resistance to the antibiotic classes fluoroquinolones, aminoglycosides, and β-lactams were identified. Besides potential novel biomarkers with a direct correlation to resistance, global patterns of phenotype-associated gene expression and sequence variations were identified by predictive machine learning approaches. Our research serves to establish genotype-based molecular diagnostic tools for the identification of the current resistance profiles of bacterial pathogens and paves the way for faster diagnostics for more efficient, targeted treatment strategies to also mitigate the future potential for resistance evolution. PMID:27216077

Detection of Spoofed MAC Addresses in 802.11 Wireless Networks

NASA Astrophysics Data System (ADS)

Tao, Kai; Li, Jing; Sampalli, Srinivas

Medium Access Control (MAC) address spoofing is considered as an important first step in a hacker's attempt to launch a variety of attacks on 802.11 wireless networks. Unfortunately, MAC address spoofing is hard to detect. Most current spoofing detection systems mainly use the sequence number (SN) tracking technique, which has drawbacks. Firstly, it may lead to an increase in the number of false positives. Secondly, such techniques cannot be used in systems with wireless cards that do not follow standard 802.11 sequence number patterns. Thirdly, attackers can forge sequence numbers, thereby causing the attacks to go undetected. We present a new architecture called WISE GUARD (Wireless Security Guard) for detection of MAC address spoofing on 802.11 wireless LANs. It integrates three detection techniques - SN tracking, Operating System (OS) fingerprinting & tracking and Received Signal Strength (RSS) fingerprinting & tracking. It also includes the fingerprinting of Access Point (AP) parameters as an extension to the OS fingerprinting for detection of AP address spoofing. We have implemented WISE GUARD on a test bed using off-the-shelf wireless devices and open source drivers. Experimental results show that the new design enhances the detection effectiveness and reduces the number of false positives in comparison with current approaches.

The Bouma Sequence and the turbidite mind set

NASA Astrophysics Data System (ADS)

Shanmugam, G.

1997-11-01

Conventionally, the Bouma Sequence [Bouma, A.H., 1962. Sedimentology of some Flysch Deposits: A Graphic Approach to Facies Interpretation. Elsevier, Amsterdam, 168 pp.], composed of T a, T b, T c, T d, and T e divisions, is interpreted to be the product of a turbidity current. However, recent core and outcrop studies show that the complete and partial Bouma sequences can also be interpreted to be deposits formed by processes other than turbidity currents, such as sandy debris flows and bottom-current reworking. Many published examples of turbidites, most of them hydrocarbon-bearing sands, in the North Sea, the Norwegian Sea, offshore Nigeria, offshore Gabon, Gulf of Mexico, and the Ouachita Mountains, are being reinterpreted by the present author as dominantly deposits of sandy debris flows and bottom-current reworking with only a minor percentage of true turbidites (i.e., deposits of turbidity currents with fluidal or Newtonian rheology in which sediment is suspended by fluid turbulence). This reinterpretation is based on detailed description of 21,000 ft (6402 m) of conventional cores and 1200 ft (365 m) of outcrop sections. The predominance of interpreted turbidites in these areas by other workers can be attributed to the following: (1) loose applications of turbidity-current concepts without regard for fluid rheology, flow state, and sediment-support mechanism that result in a category of 'turbidity currents' that includes debris flows and bottom currents; (2) field description of deep-water sands using the Bouma Sequence (an interpretive model) that invariably leads to a model-driven turbidite interpretation; (3) the prevailing turbidite mind set that subconsciously forces one to routinely interpret most deep-water sands as some kind of turbidites; (4) the use of our inability to interpret transport mechanism from the depositional record as an excuse for assuming deep-water sands as deposits of turbidity currents; (5) the flawed concept of high-density turbidity currents that allows room for interpreting debris-flow deposits as turbidites; (6) the flawed comparison of subaerial river currents (fluid-gravity flows dominated by bed-load transport) with subaqueous turbidity currents (sediment-gravity flows dominated by suspended load transport) that results in misinterpreting ungraded or parallel-stratified deep-sea deposits as turbidites; and (7) the attraction to use obsolete submarine-fan models with channels and lobes that require a turbidite interpretation. Although the turbidite paradigm is alive and well for now, the turbidites themselves are becoming an endangered facies!

Genomic identification of regulatory elements by evolutionary sequence comparison and functional analysis.

PubMed

Loots, Gabriela G

2008-01-01

Despite remarkable recent advances in genomics that have enabled us to identify most of the genes in the human genome, comparable efforts to define transcriptional cis-regulatory elements that control gene expression are lagging behind. The difficulty of this task stems from two equally important problems: our knowledge of how regulatory elements are encoded in genomes remains elementary, and there is a vast genomic search space for regulatory elements, since most of mammalian genomes are noncoding. Comparative genomic approaches are having a remarkable impact on the study of transcriptional regulation in eukaryotes and currently represent the most efficient and reliable methods of predicting noncoding sequences likely to control the patterns of gene expression. By subjecting eukaryotic genomic sequences to computational comparisons and subsequent experimentation, we are inching our way toward a more comprehensive catalog of common regulatory motifs that lie behind fundamental biological processes. We are still far from comprehending how the transcriptional regulatory code is encrypted in the human genome and providing an initial global view of regulatory gene networks, but collectively, the continued development of comparative and experimental approaches will rapidly expand our knowledge of the transcriptional regulome.

Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia.

PubMed

Ertefaie, Ashkan; Shortreed, Susan; Chakraborty, Bibhas

2016-06-15

Q-learning is a regression-based approach that uses longitudinal data to construct dynamic treatment regimes, which are sequences of decision rules that use patient information to inform future treatment decisions. An optimal dynamic treatment regime is composed of a sequence of decision rules that indicate how to optimally individualize treatment using the patients' baseline and time-varying characteristics to optimize the final outcome. Constructing optimal dynamic regimes using Q-learning depends heavily on the assumption that regression models at each decision point are correctly specified; yet model checking in the context of Q-learning has been largely overlooked in the current literature. In this article, we show that residual plots obtained from standard Q-learning models may fail to adequately check the quality of the model fit. We present a modified Q-learning procedure that accommodates residual analyses using standard tools. We present simulation studies showing the advantage of the proposed modification over standard Q-learning. We illustrate this new Q-learning approach using data collected from a sequential multiple assignment randomized trial of patients with schizophrenia. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The rise of genomic profiling in ovarian cancer

PubMed Central

Previs, Rebecca A.; Sood, Anil K.; Mills, Gordon B.; Westin, Shannon N.

2017-01-01

Introduction Next-generation sequencing and advances in ‘omics technology have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers. Areas covered Once characterized only by histologic appearance and clinical behavior, we now understand many of the molecular phenotypes that underlie the different ovarian cancer subtypes. While the current approach to treatment involves standard cytotoxic therapies after cytoreductive surgery for all ovarian cancers regardless of histologic or molecular characteristics, focus has shifted beyond a ‘one size fits all’ approach to ovarian cancer. Expert commentary Genomic profiling offers potentially ‘actionable’ opportunities for development of targeted therapies and a more individualized approach to treatment with concomitant improved outcomes and decreased toxicity. PMID:27828713

Single-Cell Genomics: Approaches and Utility in Immunology.

PubMed

Neu, Karlynn E; Tang, Qingming; Wilson, Patrick C; Khan, Aly A

2017-02-01

Single-cell genomics offers powerful tools for studying immune cells, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population level. Advances in computer science and single-cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single-cell RNA-sequencing data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning to segment mouse embryo cells

NASA Astrophysics Data System (ADS)

León, Juan; Pardo, Alejandro; Arbeláez, Pablo

2017-11-01

Recent advances in microscopy enable the capture of temporal sequences during cell development stages. However, the study of such sequences is a complex task and time consuming task. In this paper we propose an automatic strategy to adders the problem of semantic and instance segmentation of mouse embryos using NYU's Mouse Embryo Tracking Database. We obtain our instance proposals as refined predictions from the generalized hough transform, using prior knowledge of the embryo's locations and their current cell stage. We use two main approaches to learn the priors: Hand crafted features and automatic learned features. Our strategy increases the baseline jaccard index from 0.12 up to 0.24 using hand crafted features and 0.28 by using automatic learned ones.

A novel chaotic based image encryption using a hybrid model of deoxyribonucleic acid and cellular automata

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi

2015-08-01

Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.

Large-scale database searching using tandem mass spectra: looking up the answer in the back of the book.

PubMed

Sadygov, Rovshan G; Cociorva, Daniel; Yates, John R

2004-12-01

Database searching is an essential element of large-scale proteomics. Because these methods are widely used, it is important to understand the rationale of the algorithms. Most algorithms are based on concepts first developed in SEQUEST and PeptideSearch. Four basic approaches are used to determine a match between a spectrum and sequence: descriptive, interpretative, stochastic and probability-based matching. We review the basic concepts used by most search algorithms, the computational modeling of peptide identification and current challenges and limitations of this approach for protein identification.

PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.

PubMed

Thomas, Paul D; Kejariwal, Anish; Campbell, Michael J; Mi, Huaiyu; Diemer, Karen; Guo, Nan; Ladunga, Istvan; Ulitsky-Lazareva, Betty; Muruganujan, Anushya; Rabkin, Steven; Vandergriff, Jody A; Doremieux, Olivier

2003-01-01

The PANTHER database was designed for high-throughput analysis of protein sequences. One of the key features is a simplified ontology of protein function, which allows browsing of the database by biological functions. Biologist curators have associated the ontology terms with groups of protein sequences rather than individual sequences. Statistical models (Hidden Markov Models, or HMMs) are built from each of these groups. The advantage of this approach is that new sequences can be automatically classified as they become available. To ensure accurate functional classification, HMMs are constructed not only for families, but also for functionally distinct subfamilies. Multiple sequence alignments and phylogenetic trees, including curator-assigned information, are available for each family. The current version of the PANTHER database includes training sequences from all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classify gene products across the entire genomes of human, and Drosophila melanogaster. The ontology terms and protein families and subfamilies, as well as Drosophila gene c;assifications, can be browsed and searched for free. Due to outstanding contractual obligations, access to human gene classifications and to protein family trees and multiple sequence alignments will temporarily require a nominal registration fee. PANTHER is publicly available on the web at http://panther.celera.com.

Standardization and quality management in next-generation sequencing.

PubMed

Endrullat, Christoph; Glökler, Jörn; Franke, Philipp; Frohme, Marcus

2016-09-01

DNA sequencing continues to evolve quickly even after > 30 years. Many new platforms suddenly appeared and former established systems have vanished in almost the same manner. Since establishment of next-generation sequencing devices, this progress gains momentum due to the continually growing demand for higher throughput, lower costs and better quality of data. In consequence of this rapid development, standardized procedures and data formats as well as comprehensive quality management considerations are still scarce. Here, we listed and summarized current standardization efforts and quality management initiatives from companies, organizations and societies in form of published studies and ongoing projects. These comprise on the one hand quality documentation issues like technical notes, accreditation checklists and guidelines for validation of sequencing workflows. On the other hand, general standard proposals and quality metrics are developed and applied to the sequencing workflow steps with the main focus on upstream processes. Finally, certain standard developments for downstream pipeline data handling, processing and storage are discussed in brief. These standardization approaches represent a first basis for continuing work in order to prospectively implement next-generation sequencing in important areas such as clinical diagnostics, where reliable results and fast processing is crucial. Additionally, these efforts will exert a decisive influence on traceability and reproducibility of sequence data.

Combining Rosetta with molecular dynamics (MD): A benchmark of the MD-based ensemble protein design.

PubMed

Ludwiczak, Jan; Jarmula, Adam; Dunin-Horkawicz, Stanislaw

2018-07-01

Computational protein design is a set of procedures for computing amino acid sequences that will fold into a specified structure. Rosetta Design, a commonly used software for protein design, allows for the effective identification of sequences compatible with a given backbone structure, while molecular dynamics (MD) simulations can thoroughly sample near-native conformations. We benchmarked a procedure in which Rosetta design is started on MD-derived structural ensembles and showed that such a combined approach generates 20-30% more diverse sequences than currently available methods with only a slight increase in computation time. Importantly, the increase in diversity is achieved without a loss in the quality of the designed sequences assessed by their resemblance to natural sequences. We demonstrate that the MD-based procedure is also applicable to de novo design tasks started from backbone structures without any sequence information. In addition, we implemented a protocol that can be used to assess the stability of designed models and to select the best candidates for experimental validation. In sum our results demonstrate that the MD ensemble-based flexible backbone design can be a viable method for protein design, especially for tasks that require a large pool of diverse sequences. Copyright © 2018 Elsevier Inc. All rights reserved.

Shot sequencing based on biological equivalent dose considerations for multiple isocenter Gamma Knife radiosurgery

NASA Astrophysics Data System (ADS)

Ma, Lijun; Lee, Letitia; Barani, Igor; Hwang, Andrew; Fogh, Shannon; Nakamura, Jean; McDermott, Michael; Sneed, Penny; Larson, David A.; Sahgal, Arjun

2011-11-01

Rapid delivery of multiple shots or isocenters is one of the hallmarks of Gamma Knife radiosurgery. In this study, we investigated whether the temporal order of shots delivered with Gamma Knife Perfexion would significantly influence the biological equivalent dose for complex multi-isocenter treatments. Twenty single-target cases were selected for analysis. For each case, 3D dose matrices of individual shots were extracted and single-fraction equivalent uniform dose (sEUD) values were determined for all possible shot delivery sequences, corresponding to different patterns of temporal dose delivery within the target. We found significant variations in the sEUD values among these sequences exceeding 15% for certain cases. However, the sequences for the actual treatment delivery were found to agree (<3%) and to correlate (R2 = 0.98) excellently with the sequences yielding the maximum sEUD values for all studied cases. This result is applicable for both fast and slow growing tumors with α/β values of 2 to 20 according to the linear-quadratic model. In conclusion, despite large potential variations in different shot sequences for multi-isocenter Gamma Knife treatments, current clinical delivery sequences exhibited consistent biological target dosing that approached that maximally achievable for all studied cases.

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

PubMed Central

Pandey, Manish K.; Roorkiwal, Manish; Singh, Vikas K.; Ramalingam, Abirami; Kudapa, Himabindu; Thudi, Mahendar; Chitikineni, Anu; Rathore, Abhishek; Varshney, Rajeev K.

2016-01-01

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries. PMID:27199998

Strain/species identification in metagenomes using genome-specific markers

PubMed Central

Tu, Qichao; He, Zhili; Zhou, Jizhong

2014-01-01

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing. PMID:24523352

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

NASA Astrophysics Data System (ADS)

Rivers, A. R.

2016-02-01

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

ampliMethProfiler: a pipeline for the analysis of CpG methylation profiles of targeted deep bisulfite sequenced amplicons.

PubMed

Scala, Giovanni; Affinito, Ornella; Palumbo, Domenico; Florio, Ermanno; Monticelli, Antonella; Miele, Gennaro; Chiariotti, Lorenzo; Cocozza, Sergio

2016-11-25

CpG sites in an individual molecule may exist in a binary state (methylated or unmethylated) and each individual DNA molecule, containing a certain number of CpGs, is a combination of these states defining an epihaplotype. Classic quantification based approaches to study DNA methylation are intrinsically unable to fully represent the complexity of the underlying methylation substrate. Epihaplotype based approaches, on the other hand, allow methylation profiles of cell populations to be studied at the single molecule level. For such investigations, next-generation sequencing techniques can be used, both for quantitative and for epihaplotype analysis. Currently available tools for methylation analysis lack output formats that explicitly report CpG methylation profiles at the single molecule level and that have suited statistical tools for their interpretation. Here we present ampliMethProfiler, a python-based pipeline for the extraction and statistical epihaplotype analysis of amplicons from targeted deep bisulfite sequencing of multiple DNA regions. ampliMethProfiler tool provides an easy and user friendly way to extract and analyze the epihaplotype composition of reads from targeted bisulfite sequencing experiments. ampliMethProfiler is written in python language and requires a local installation of BLAST and (optionally) QIIME tools. It can be run on Linux and OS X platforms. The software is open source and freely available at http://amplimethprofiler.sourceforge.net .

Optimal rotation sequences for active perception

NASA Astrophysics Data System (ADS)

Nakath, David; Rachuy, Carsten; Clemens, Joachim; Schill, Kerstin

2016-05-01

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi- sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft

An efficient approach to BAC based assembly of complex genomes.

PubMed

Visendi, Paul; Berkman, Paul J; Hayashi, Satomi; Golicz, Agnieszka A; Bayer, Philipp E; Ruperao, Pradeep; Hurgobin, Bhavna; Montenegro, Juan; Chan, Chon-Kit Kenneth; Staňková, Helena; Batley, Jacqueline; Šimková, Hana; Doležel, Jaroslav; Edwards, David

2016-01-01

There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate 'gold' reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase.

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Music Activities as a Meaningful Context for Teaching Elementary Students Mathematics: A Quasi-Experiment Time Series Design with Random Assigned Control Group

ERIC Educational Resources Information Center

An, Song A.; Tillman, Daniel A.

2015-01-01

The purpose of the current research was to examine the effects of a sequence of classroom activities that integrated mathematics content with music elements aimed at providing teachers an alternative approach for teaching mathematics. Two classes of third grade students (n = 56) from an elementary school in the west coast of the United States…

Current management of penetrating torso trauma: nontherapeutic is not good enough anymore

PubMed Central

Ball, Chad G.

2014-01-01

A highly organized approach to the evaluation and treatment of penetrating torso injuries based on regional anatomy provides rapid diagnostic and therapeutic consistency. It also minimizes delays in diagnosis, missed injuries and nontherapeutic laparotomies. This review discusses an optimal sequence of structured rapid assessments that allow the clinician to rapidly proceed to gold standard therapies with a minimal risk of associated morbidity. PMID:24666458

Targeted amplicon sequencing (TAS): a scalable next-gen approach to multilocus, multitaxa phylogenetics.

PubMed

Bybee, Seth M; Bracken-Grissom, Heather; Haynes, Benjamin D; Hermansen, Russell A; Byers, Robert L; Clement, Mark J; Udall, Joshua A; Wilcox, Edward R; Crandall, Keith A

2011-01-01

Next-gen sequencing technologies have revolutionized data collection in genetic studies and advanced genome biology to novel frontiers. However, to date, next-gen technologies have been used principally for whole genome sequencing and transcriptome sequencing. Yet many questions in population genetics and systematics rely on sequencing specific genes of known function or diversity levels. Here, we describe a targeted amplicon sequencing (TAS) approach capitalizing on next-gen capacity to sequence large numbers of targeted gene regions from a large number of samples. Our TAS approach is easily scalable, simple in execution, neither time-nor labor-intensive, relatively inexpensive, and can be applied to a broad diversity of organisms and/or genes. Our TAS approach includes a bioinformatic application, BarcodeCrucher, to take raw next-gen sequence reads and perform quality control checks and convert the data into FASTA format organized by gene and sample, ready for phylogenetic analyses. We demonstrate our approach by sequencing targeted genes of known phylogenetic utility to estimate a phylogeny for the Pancrustacea. We generated data from 44 taxa using 68 different 10-bp multiplexing identifiers. The overall quality of data produced was robust and was informative for phylogeny estimation. The potential for this method to produce copious amounts of data from a single 454 plate (e.g., 325 taxa for 24 loci) significantly reduces sequencing expenses incurred from traditional Sanger sequencing. We further discuss the advantages and disadvantages of this method, while offering suggestions to enhance the approach.

Targeted Amplicon Sequencing (TAS): A Scalable Next-Gen Approach to Multilocus, Multitaxa Phylogenetics

PubMed Central

Bybee, Seth M.; Bracken-Grissom, Heather; Haynes, Benjamin D.; Hermansen, Russell A.; Byers, Robert L.; Clement, Mark J.; Udall, Joshua A.; Wilcox, Edward R.; Crandall, Keith A.

2011-01-01

Next-gen sequencing technologies have revolutionized data collection in genetic studies and advanced genome biology to novel frontiers. However, to date, next-gen technologies have been used principally for whole genome sequencing and transcriptome sequencing. Yet many questions in population genetics and systematics rely on sequencing specific genes of known function or diversity levels. Here, we describe a targeted amplicon sequencing (TAS) approach capitalizing on next-gen capacity to sequence large numbers of targeted gene regions from a large number of samples. Our TAS approach is easily scalable, simple in execution, neither time-nor labor-intensive, relatively inexpensive, and can be applied to a broad diversity of organisms and/or genes. Our TAS approach includes a bioinformatic application, BarcodeCrucher, to take raw next-gen sequence reads and perform quality control checks and convert the data into FASTA format organized by gene and sample, ready for phylogenetic analyses. We demonstrate our approach by sequencing targeted genes of known phylogenetic utility to estimate a phylogeny for the Pancrustacea. We generated data from 44 taxa using 68 different 10-bp multiplexing identifiers. The overall quality of data produced was robust and was informative for phylogeny estimation. The potential for this method to produce copious amounts of data from a single 454 plate (e.g., 325 taxa for 24 loci) significantly reduces sequencing expenses incurred from traditional Sanger sequencing. We further discuss the advantages and disadvantages of this method, while offering suggestions to enhance the approach. PMID:22002916

BG7: A New Approach for Bacterial Genome Annotation Designed for Next Generation Sequencing Data

PubMed Central

Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Pareja, Eduardo; Tobes, Raquel

2012-01-01

BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version – which is developed in Java, takes advantage of Amazon Web Services (AWS) cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future. PMID:23185310

Transcriptome and target DNA enrichment sequence data provide new insights into the phylogeny of vespid wasps (Hymenoptera: Aculeata: Vespidae).

PubMed

Bank, Sarah; Sann, Manuela; Mayer, Christoph; Meusemann, Karen; Donath, Alexander; Podsiadlowski, Lars; Kozlov, Alexey; Petersen, Malte; Krogmann, Lars; Meier, Rudolf; Rosa, Paolo; Schmitt, Thomas; Wurdack, Mareike; Liu, Shanlin; Zhou, Xin; Misof, Bernhard; Peters, Ralph S; Niehuis, Oliver

2017-11-01

The wasp family Vespidae comprises more than 5000 described species which represent life history strategies ranging from solitary and presocial to eusocial and socially parasitic. The phylogenetic relationships of the major vespid wasp lineages (i.e., subfamilies and tribes) have been investigated repeatedly by analyzing behavioral and morphological traits as well as nucleotide sequences of few selected genes with largely incongruent results. Here we reconstruct their phylogenetic relationships using a phylogenomic approach. We sequenced the transcriptomes of 24 vespid wasp and eight outgroup species and exploited the transcript sequences for design of probes for enriching 913 single-copy protein-coding genes to complement the transcriptome data with nucleotide sequence data from additional 25 ethanol-preserved vespid species. Results from phylogenetic analyses of the combined sequence data revealed the eusocial subfamily Stenogastrinae to be the sister group of all remaining Vespidae, while the subfamily Eumeninae turned out to be paraphyletic. Of the three currently recognized eumenine tribes, Odynerini is paraphyletic with respect to Eumenini, and Zethini is paraphyletic with respect to Polistinae and Vespinae. Our results are in conflict with the current tribal subdivision of Eumeninae and thus, we suggest granting subfamily rank to the two major clades of "Zethini": Raphiglossinae and Zethinae. Overall, our findings corroborate the hypothesis of two independent origins of eusociality in vespid wasps and suggest a single origin of using masticated and salivated plant material for building nests by Raphiglossinae, Zethinae, Polistinae, and Vespinae. The inferred phylogenetic relationships and the open access vespid wasp target DNA enrichment probes will provide a valuable tool for future comparative studies on species of the family Vespidae, including their genomes, life styles, evolution of sociality, and co-evolution with other organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

PubMed Central

Oniciuc, Elena A.; Likotrafiti, Eleni; Alvarez-Molina, Adrián; Alvarez-Ordóñez, Avelino

2018-01-01

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes. PMID:29789467

Assessing the Diversity of Rodent-Borne Viruses: Exploring of High-Throughput Sequencing and Classical Amplification/Sequencing Approaches.

PubMed

Drewes, Stephan; Straková, Petra; Drexler, Jan F; Jacob, Jens; Ulrich, Rainer G

2017-01-01

Rodents are distributed throughout the world and interact with humans in many ways. They provide vital ecosystem services, some species are useful models in biomedical research and some are held as pet animals. However, many rodent species can have adverse effects such as damage to crops and stored produce, and they are of health concern because of the transmission of pathogens to humans and livestock. The first rodent viruses were discovered by isolation approaches and resulted in break-through knowledge in immunology, molecular and cell biology, and cancer research. In addition to rodent-specific viruses, rodent-borne viruses are causing a large number of zoonotic diseases. Most prominent examples are reemerging outbreaks of human hemorrhagic fever disease cases caused by arena- and hantaviruses. In addition, rodents are reservoirs for vector-borne pathogens, such as tick-borne encephalitis virus and Borrelia spp., and may carry human pathogenic agents, but likely are not involved in their transmission to human. In our days, next-generation sequencing or high-throughput sequencing (HTS) is revolutionizing the speed of the discovery of novel viruses, but other molecular approaches, such as generic RT-PCR/PCR and rolling circle amplification techniques, contribute significantly to the rapidly ongoing process. However, the current knowledge still represents only the tip of the iceberg, when comparing the known human viruses to those known for rodents, the mammalian taxon with the largest species number. The diagnostic potential of HTS-based metagenomic approaches is illustrated by their use in the discovery and complete genome determination of novel borna- and adenoviruses as causative disease agents in squirrels. In conclusion, HTS, in combination with conventional RT-PCR/PCR-based approaches, resulted in a drastically increased knowledge of the diversity of rodent viruses. Future improvements of the used workflows, including bioinformatics analysis, will further enhance our knowledge and preparedness in case of the emergence of novel viruses. Classical virological and additional molecular approaches are needed for genome annotation and functional characterization of novel viruses, discovered by these technologies, and evaluation of their zoonotic potential. © 2017 Elsevier Inc. All rights reserved.

A long PCR–based approach for DNA enrichment prior to next-generation sequencing for systematic studies1

PubMed Central

Uribe-Convers, Simon; Duke, Justin R.; Moore, Michael J.; Tank, David C.

2014-01-01

• Premise of the study: We present an alternative approach for molecular systematic studies that combines long PCR and next-generation sequencing. Our approach can be used to generate templates from any DNA source for next-generation sequencing. Here we test our approach by amplifying complete chloroplast genomes, and we present a set of 58 potentially universal primers for angiosperms to do so. Additionally, this approach is likely to be particularly useful for nuclear and mitochondrial regions. • Methods and Results: Chloroplast genomes of 30 species across angiosperms were amplified to test our approach. Amplification success varied depending on whether PCR conditions were optimized for a given taxon. To further test our approach, some amplicons were sequenced on an Illumina HiSeq 2000. • Conclusions: Although here we tested this approach by sequencing plastomes, long PCR amplicons could be generated using DNA from any genome, expanding the possibilities of this approach for molecular systematic studies. PMID:25202592

Defining the wheat gluten peptide fingerprint via a discovery and targeted proteomics approach.

PubMed

Martínez-Esteso, María José; Nørgaard, Jørgen; Brohée, Marcel; Haraszi, Reka; Maquet, Alain; O'Connor, Gavin

2016-09-16

Accurate, reliable and sensitive detection methods for gluten are required to support current EU regulations. The enforcement of legislative levels requires that measurement results are comparable over time and between methods. This is not a trivial task for gluten which comprises a large number of protein targets. This paper describes a strategy for defining a set of specific analytical targets for wheat gluten. A comprehensive proteomic approach was applied by fractionating wheat gluten using RP-HPLC (reversed phase high performance liquid chromatography) followed by a multi-enzymatic digestion (LysC, trypsin and chymotrypsin) with subsequent mass spectrometric analysis. This approach identified 434 peptide sequences from gluten. Peptides were grouped based on two criteria: unique to a single gluten protein sequence; contained known immunogenic and toxic sequences in the context of coeliac disease. An LC-MS/MS method based on selected reaction monitoring (SRM) was developed on a triple quadrupole mass spectrometer for the specific detection of the target peptides. The SRM based screening approach was applied to gluten containing cereals (wheat, rye, barley and oats) and non-gluten containing flours (corn, soy and rice). A unique set of wheat gluten marker peptides were identified and are proposed as wheat specific markers. The measurement of gluten in processed food products in support of regulatory limits is performed routinely. Mass spectrometry is emerging as a viable alternative to ELISA based methods. Here we outline a set of peptide markers that are representative of gluten and consider the end user's needs in protecting those with coeliac disease. The approach taken has been applied to wheat but can be easily extended to include other species potentially enabling the MS quantification of different gluten containing species from the identified markers. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

SpliceRover: Interpretable Convolutional Neural: Networks for Improved Splice Site Prediction.

PubMed

Zuallaert, Jasper; Godin, Fréderic; Kim, Mijung; Soete, Arne; Saeys, Yvan; De Neve, Wesley

2018-06-21

During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is currently mostly done using automated genome annotation platforms, which mainly rely on integrated machine learning frameworks to identify different functional sites of interest, including splice sites. Splicing is an essential step in the gene regulation process, and the correct identification of splice sites is a major cornerstone in a genome annotation system. In this paper, we present SpliceRover, a predictive deep learning approach that outperforms the state-of-the-art in splice site prediction. SpliceRover uses convolutional neural networks (CNNs), which have been shown to obtain cutting edge performance on a wide variety of prediction tasks. We adapted this approach to deal with genomic sequence inputs, and show it consistently outperforms already existing approaches, with relative improvements in prediction effectiveness of up to 80.9% when measured in terms of false discovery rate. However, a major criticism of CNNs concerns their "black box" nature, as mechanisms to obtain insight into their reasoning processes are limited. To facilitate interpretability of the SpliceRover models, we introduce an approach to visualize the biologically relevant information learnt. We show that our visualization approach is able to recover features known to be important for splice site prediction (binding motifs around the splice site, presence of polypyrimidine tracts and branch points), as well as reveal new features (e.g., several types of exclusion patterns near splice sites). SpliceRover is available as a web service. The prediction tool and instructions can be found at http://bioit2.irc.ugent.be/splicerover/. Supplementary materials are available at Bioinformatics online.

Breaking the computational barriers of pairwise genome comparison.

PubMed

Torreno, Oscar; Trelles, Oswaldo

2015-08-11

Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of large biological sequence datasets by retrofitting existing algorithms or by creating new applications represents a major challenge for the bioinformatics community. We have developed C libraries for pairwise sequence comparison within diverse architectures, ranging from commodity systems to high performance and cloud computing environments. Exhaustive tests were performed using different datasets of closely- and distantly-related sequences that span from small viral genomes to large mammalian chromosomes. The tests demonstrated that our solution is capable of generating high quality results with a linear-time response and controlled memory consumption, being comparable or faster than the current state-of-the-art methods. We have addressed the problem of pairwise and all-versus-all comparison of large sequences in general, greatly increasing the limits on input data size. The approach described here is based on a modular out-of-core strategy that uses secondary storage to avoid reaching memory limits during the identification of High-scoring Segment Pairs (HSPs) between the sequences under comparison. Software engineering concepts were applied to avoid intermediate result re-calculation, to minimise the performance impact of input/output (I/O) operations and to modularise the process, thus enhancing application flexibility and extendibility. Our computationally-efficient approach allows tasks such as the massive comparison of complete genomes, evolutionary event detection, the identification of conserved synteny blocks and inter-genome distance calculations to be performed more effectively.

Centromere Locations in Brassica A and C Genomes Revealed Through Half-Tetrad Analysis

PubMed Central

Mason, Annaliese S.; Rousseau-Gueutin, Mathieu; Morice, Jérôme; Bayer, Philipp E.; Besharat, Naghmeh; Cousin, Anouska; Pradhan, Aneeta; Parkin, Isobel A. P.; Chèvre, Anne-Marie; Batley, Jacqueline; Nelson, Matthew N.

2016-01-01

Locating centromeres on genome sequences can be challenging. The high density of repetitive elements in these regions makes sequence assembly problematic, especially when using short-read sequencing technologies. It can also be difficult to distinguish between active and recently extinct centromeres through sequence analysis. An effective solution is to identify genetically active centromeres (functional in meiosis) by half-tetrad analysis. This genetic approach involves detecting heterozygosity along chromosomes in segregating populations derived from gametes (half-tetrads). Unreduced gametes produced by first division restitution mechanisms comprise complete sets of nonsister chromatids. Along these chromatids, heterozygosity is maximal at the centromeres, and homologous recombination events result in homozygosity toward the telomeres. We genotyped populations of half-tetrad-derived individuals (from Brassica interspecific hybrids) using a high-density array of physically anchored SNP markers (Illumina Brassica 60K Infinium array). Mapping the distribution of heterozygosity in these half-tetrad individuals allowed the genetic mapping of all 19 centromeres of the Brassica A and C genomes to the reference Brassica napus genome. Gene and transposable element density across the B. napus genome were also assessed and corresponded well to previously reported genetic map positions. Known centromere-specific sequences were located in the reference genome, but mostly matched unanchored sequences, suggesting that the core centromeric regions may not yet be assembled into the pseudochromosomes of the reference genome. The increasing availability of genetic markers physically anchored to reference genomes greatly simplifies the genetic and physical mapping of centromeres using half-tetrad analysis. We discuss possible applications of this approach, including in species where half-tetrads are currently difficult to isolate. PMID:26614742

Centromere Locations in Brassica A and C Genomes Revealed Through Half-Tetrad Analysis.

PubMed

Mason, Annaliese S; Rousseau-Gueutin, Mathieu; Morice, Jérôme; Bayer, Philipp E; Besharat, Naghmeh; Cousin, Anouska; Pradhan, Aneeta; Parkin, Isobel A P; Chèvre, Anne-Marie; Batley, Jacqueline; Nelson, Matthew N

2016-02-01

Locating centromeres on genome sequences can be challenging. The high density of repetitive elements in these regions makes sequence assembly problematic, especially when using short-read sequencing technologies. It can also be difficult to distinguish between active and recently extinct centromeres through sequence analysis. An effective solution is to identify genetically active centromeres (functional in meiosis) by half-tetrad analysis. This genetic approach involves detecting heterozygosity along chromosomes in segregating populations derived from gametes (half-tetrads). Unreduced gametes produced by first division restitution mechanisms comprise complete sets of nonsister chromatids. Along these chromatids, heterozygosity is maximal at the centromeres, and homologous recombination events result in homozygosity toward the telomeres. We genotyped populations of half-tetrad-derived individuals (from Brassica interspecific hybrids) using a high-density array of physically anchored SNP markers (Illumina Brassica 60K Infinium array). Mapping the distribution of heterozygosity in these half-tetrad individuals allowed the genetic mapping of all 19 centromeres of the Brassica A and C genomes to the reference Brassica napus genome. Gene and transposable element density across the B. napus genome were also assessed and corresponded well to previously reported genetic map positions. Known centromere-specific sequences were located in the reference genome, but mostly matched unanchored sequences, suggesting that the core centromeric regions may not yet be assembled into the pseudochromosomes of the reference genome. The increasing availability of genetic markers physically anchored to reference genomes greatly simplifies the genetic and physical mapping of centromeres using half-tetrad analysis. We discuss possible applications of this approach, including in species where half-tetrads are currently difficult to isolate. Copyright © 2016 by the Genetics Society of America.

Molecular Phylogenetics and Systematics of the Bivalve Family Ostreidae Based on rRNA Sequence-Structure Models and Multilocus Species Tree

PubMed Central

Salvi, Daniele; Macali, Armando; Mariottini, Paolo

2014-01-01

The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassotreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics. PMID:25250663

Molecular phylogenetics and systematics of the bivalve family Ostreidae based on rRNA sequence-structure models and multilocus species tree.

PubMed

Salvi, Daniele; Macali, Armando; Mariottini, Paolo

2014-01-01

The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassostreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized [corrected]. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics.

Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks.

PubMed

Rusconi, Brigida; Sanjar, Fatemeh; Koenig, Sara S K; Mammel, Mark K; Tarr, Phillip I; Eppinger, Mark

2016-01-01

Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies.

Whole Genome Sequencing for Genomics-Guided Investigations of Escherichia coli O157:H7 Outbreaks

PubMed Central

Rusconi, Brigida; Sanjar, Fatemeh; Koenig, Sara S. K.; Mammel, Mark K.; Tarr, Phillip I.; Eppinger, Mark

2016-01-01

Multi isolate whole genome sequencing (WGS) and typing for outbreak investigations has become a reality in the post-genomics era. We applied this technology to strains from Escherichia coli O157:H7 outbreaks. These include isolates from seven North America outbreaks, as well as multiple isolates from the same patient and from different infected individuals in the same household. Customized high-resolution bioinformatics sequence typing strategies were developed to assess the core genome and mobilome plasticity. Sequence typing was performed using an in-house single nucleotide polymorphism (SNP) discovery and validation pipeline. Discriminatory power becomes of particular importance for the investigation of isolates from outbreaks in which macrogenomic techniques such as pulse-field gel electrophoresis or multiple locus variable number tandem repeat analysis do not differentiate closely related organisms. We also characterized differences in the phage inventory, allowing us to identify plasticity among outbreak strains that is not detectable at the core genome level. Our comprehensive analysis of the mobilome identified multiple plasmids that have not previously been associated with this lineage. Applied phylogenomics approaches provide strong molecular evidence for exceptionally little heterogeneity of strains within outbreaks and demonstrate the value of intra-cluster comparisons, rather than basing the analysis on archetypal reference strains. Next generation sequencing and whole genome typing strategies provide the technological foundation for genomic epidemiology outbreak investigation utilizing its significantly higher sample throughput, cost efficiency, and phylogenetic relatedness accuracy. These phylogenomics approaches have major public health relevance in translating information from the sequence-based survey to support timely and informed countermeasures. Polymorphisms identified in this work offer robust phylogenetic signals that index both short- and long-term evolution and can complement currently employed typing schemes for outbreak ex- and inclusion, diagnostics, surveillance, and forensic studies. PMID:27446025

Using Behavior Sequence Analysis to Map Serial Killers' Life Histories.

PubMed

Keatley, David A; Golightly, Hayley; Shephard, Rebecca; Yaksic, Enzo; Reid, Sasha

2018-03-01

The aim of the current research was to provide a novel method for mapping the developmental sequences of serial killers' life histories. An in-depth biographical account of serial killers' lives, from birth through to conviction, was gained and analyzed using Behavior Sequence Analysis. The analyses highlight similarities in behavioral events across the serial killers' lives, indicating not only which risk factors occur, but the temporal order of these factors. Results focused on early childhood environment, indicating the role of parental abuse; behaviors and events surrounding criminal histories of serial killers, showing that many had previous convictions and were known to police for other crimes; behaviors surrounding their murders, highlighting differences in victim choice and modus operandi; and, finally, trial pleas and convictions. The present research, therefore, provides a novel approach to synthesizing large volumes of data on criminals and presenting results in accessible, understandable outcomes.

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Random access in large-scale DNA data storage.

PubMed

Organick, Lee; Ang, Siena Dumas; Chen, Yuan-Jyue; Lopez, Randolph; Yekhanin, Sergey; Makarychev, Konstantin; Racz, Miklos Z; Kamath, Govinda; Gopalan, Parikshit; Nguyen, Bichlien; Takahashi, Christopher N; Newman, Sharon; Parker, Hsing-Yeh; Rashtchian, Cyrus; Stewart, Kendall; Gupta, Gagan; Carlson, Robert; Mulligan, John; Carmean, Douglas; Seelig, Georg; Ceze, Luis; Strauss, Karin

2018-03-01

Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.

Secure self-calibrating quantum random-bit generator

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

Fiorentino, M.; Santori, C.; Spillane, S. M.

2007-03-15

Random-bit generators (RBGs) are key components of a variety of information processing applications ranging from simulations to cryptography. In particular, cryptographic systems require 'strong' RBGs that produce high-entropy bit sequences, but traditional software pseudo-RBGs have very low entropy content and therefore are relatively weak for cryptography. Hardware RBGs yield entropy from chaotic or quantum physical systems and therefore are expected to exhibit high entropy, but in current implementations their exact entropy content is unknown. Here we report a quantum random-bit generator (QRBG) that harvests entropy by measuring single-photon and entangled two-photon polarization states. We introduce and implement a quantum tomographicmore » method to measure a lower bound on the 'min-entropy' of the system, and we employ this value to distill a truly random-bit sequence. This approach is secure: even if an attacker takes control of the source of optical states, a secure random sequence can be distilled.« less

Pharmacological treatment of anxiety disorders: Current treatments and future directions✩

PubMed Central

Farach, Frank J.; Pruitt, Larry D.; Jun, Janie J.; Jerud, Alissa B.; Zoellner, Lori A.; Roy-Byrne, Peter P.

2012-01-01

Modern pharmacological treatments for anxiety disorders are safer and more tolerable than they were 30 years ago. Unfortunately, treatment efficacy and duration have not improved in most cases despite a greater understanding of the pathophysiology of anxiety. Moreover, innovative treatments have not reached the market despite billions of research dollars invested in drug development. In reviewing the literature on current treatments, we argue that evidence-based practice would benefit from better research on the causes of incomplete treatment response as well as the comparative efficacy of drug combinations and sequencing. We also survey two broad approaches to the development of innovative anxiety treatments: the continued development of drugs based on specific neuroreceptors and the pharmacological manipulation of fear-related memory. We highlight directions for future research, as neither of these approaches is ready for routine clinical use. PMID:23023162

Prospects and challenges for fungal metatranscriptomes of complex communities

DOE PAGES

Kuske, Cheryl Rae; Hesse, Cedar Nelson; Challacombe, Jean Faust; ...

2015-01-22

We report that the ability to extract and purify messenger RNA directly from plants, decomposing organic matter and soil, followed by high-throughput sequencing of the pool of expressed genes, has spawned the emerging research area of metatranscriptomics. Each metatranscriptome provides a snapshot of the composition and relative abundance of actively transcribed genes, and thus provides an assessment of the interactions between soil microorganisms and plants, and collective microbial metabolic processes in many environments. We highlight current approaches for analysis of fungal transcriptome and metatranscriptome datasets across a gradient of community complexity, and note benefits and pitfalls associated with those approaches.more » Finally, we discuss knowledge gaps that limit our current ability to interpret metatranscriptome datasets and suggest future research directions that will require concerted efforts within the scientific community.« less

DNA/RNA transverse current sequencing: intrinsic structural noise from neighboring bases

PubMed Central

Alvarez, Jose R.; Skachkov, Dmitry; Massey, Steven E.; Kalitsov, Alan; Velev, Julian P.

2015-01-01

Nanopore DNA sequencing via transverse current has emerged as a promising candidate for third-generation sequencing technology. It produces long read lengths which could alleviate problems with assembly errors inherent in current technologies. However, the high error rates of nanopore sequencing have to be addressed. A very important source of the error is the intrinsic noise in the current arising from carrier dispersion along the chain of the molecule, i.e., from the influence of neighboring bases. In this work we perform calculations of the transverse current within an effective multi-orbital tight-binding model derived from first-principles calculations of the DNA/RNA molecules, to study the effect of this structural noise on the error rates in DNA/RNA sequencing via transverse current in nanopores. We demonstrate that a statistical technique, utilizing not only the currents through the nucleotides but also the correlations in the currents, can in principle reduce the error rate below any desired precision. PMID:26150827

Reliable Detection of Herpes Simplex Virus Sequence Variation by High-Throughput Resequencing.

PubMed

Morse, Alison M; Calabro, Kaitlyn R; Fear, Justin M; Bloom, David C; McIntyre, Lauren M

2017-08-16

High-throughput sequencing (HTS) has resulted in data for a number of herpes simplex virus (HSV) laboratory strains and clinical isolates. The knowledge of these sequences has been critical for investigating viral pathogenicity. However, the assembly of complete herpesviral genomes, including HSV, is complicated due to the existence of large repeat regions and arrays of smaller reiterated sequences that are commonly found in these genomes. In addition, the inherent genetic variation in populations of isolates for viruses and other microorganisms presents an additional challenge to many existing HTS sequence assembly pipelines. Here, we evaluate two approaches for the identification of genetic variants in HSV1 strains using Illumina short read sequencing data. The first, a reference-based approach, identifies variants from reads aligned to a reference sequence and the second, a de novo assembly approach, identifies variants from reads aligned to de novo assembled consensus sequences. Of critical importance for both approaches is the reduction in the number of low complexity regions through the construction of a non-redundant reference genome. We compared variants identified in the two methods. Our results indicate that approximately 85% of variants are identified regardless of the approach. The reference-based approach to variant discovery captures an additional 15% representing variants divergent from the HSV1 reference possibly due to viral passage. Reference-based approaches are significantly less labor-intensive and identify variants across the genome where de novo assembly-based approaches are limited to regions where contigs have been successfully assembled. In addition, regions of poor quality assembly can lead to false variant identification in de novo consensus sequences. For viruses with a well-assembled reference genome, a reference-based approach is recommended.

Integrating functional genomics to accelerate mechanistic personalized medicine.

PubMed

Tyner, Jeffrey W

2017-03-01

The advent of deep sequencing technologies has resulted in the deciphering of tremendous amounts of genetic information. These data have led to major discoveries, and many anecdotes now exist of individual patients whose clinical outcomes have benefited from novel, genetically guided therapeutic strategies. However, the majority of genetic events in cancer are currently undrugged, leading to a biological gap between understanding of tumor genetic etiology and translation to improved clinical approaches. Functional screening has made tremendous strides in recent years with the development of new experimental approaches to studying ex vivo and in vivo drug sensitivity. Numerous discoveries and anecdotes also exist for translation of functional screening into novel clinical strategies; however, the current clinical application of functional screening remains largely confined to small clinical trials at specific academic centers. The intersection between genomic and functional approaches represents an ideal modality to accelerate our understanding of drug sensitivities as they relate to specific genetic events and further understand the full mechanisms underlying drug sensitivity patterns.

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Compressing DNA sequence databases with coil.

PubMed

White, W Timothy J; Hendy, Michael D

2008-05-20

Publicly available DNA sequence databases such as GenBank are large, and are growing at an exponential rate. The sheer volume of data being dealt with presents serious storage and data communications problems. Currently, sequence data is usually kept in large "flat files," which are then compressed using standard Lempel-Ziv (gzip) compression - an approach which rarely achieves good compression ratios. While much research has been done on compressing individual DNA sequences, surprisingly little has focused on the compression of entire databases of such sequences. In this study we introduce the sequence database compression software coil. We have designed and implemented a portable software package, coil, for compressing and decompressing DNA sequence databases based on the idea of edit-tree coding. coil is geared towards achieving high compression ratios at the expense of execution time and memory usage during compression - the compression time represents a "one-off investment" whose cost is quickly amortised if the resulting compressed file is transmitted many times. Decompression requires little memory and is extremely fast. We demonstrate a 5% improvement in compression ratio over state-of-the-art general-purpose compression tools for a large GenBank database file containing Expressed Sequence Tag (EST) data. Finally, coil can efficiently encode incremental additions to a sequence database. coil presents a compelling alternative to conventional compression of flat files for the storage and distribution of DNA sequence databases having a narrow distribution of sequence lengths, such as EST data. Increasing compression levels for databases having a wide distribution of sequence lengths is a direction for future work.

Compressing DNA sequence databases with coil

PubMed Central

White, W Timothy J; Hendy, Michael D

2008-01-01

Background Publicly available DNA sequence databases such as GenBank are large, and are growing at an exponential rate. The sheer volume of data being dealt with presents serious storage and data communications problems. Currently, sequence data is usually kept in large "flat files," which are then compressed using standard Lempel-Ziv (gzip) compression – an approach which rarely achieves good compression ratios. While much research has been done on compressing individual DNA sequences, surprisingly little has focused on the compression of entire databases of such sequences. In this study we introduce the sequence database compression software coil. Results We have designed and implemented a portable software package, coil, for compressing and decompressing DNA sequence databases based on the idea of edit-tree coding. coil is geared towards achieving high compression ratios at the expense of execution time and memory usage during compression – the compression time represents a "one-off investment" whose cost is quickly amortised if the resulting compressed file is transmitted many times. Decompression requires little memory and is extremely fast. We demonstrate a 5% improvement in compression ratio over state-of-the-art general-purpose compression tools for a large GenBank database file containing Expressed Sequence Tag (EST) data. Finally, coil can efficiently encode incremental additions to a sequence database. Conclusion coil presents a compelling alternative to conventional compression of flat files for the storage and distribution of DNA sequence databases having a narrow distribution of sequence lengths, such as EST data. Increasing compression levels for databases having a wide distribution of sequence lengths is a direction for future work. PMID:18489794

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

Soup to Tree: The Phylogeny of Beetles Inferred by Mitochondrial Metagenomics of a Bornean Rainforest Sample

PubMed Central

Crampton-Platt, Alex; Timmermans, Martijn J.T.N.; Gimmel, Matthew L.; Kutty, Sujatha Narayanan; Cockerill, Timothy D.; Vun Khen, Chey; Vogler, Alfried P.

2015-01-01

In spite of the growth of molecular ecology, systematics and next-generation sequencing, the discovery and analysis of diversity is not currently integrated with building the tree-of-life. Tropical arthropod ecologists are well placed to accelerate this process if all specimens obtained through mass-trapping, many of which will be new species, could be incorporated routinely into phylogeny reconstruction. Here we test a shotgun sequencing approach, whereby mitochondrial genomes are assembled from complex ecological mixtures through mitochondrial metagenomics, and demonstrate how the approach overcomes many of the taxonomic impediments to the study of biodiversity. DNA from approximately 500 beetle specimens, originating from a single rainforest canopy fogging sample from Borneo, was pooled and shotgun sequenced, followed by de novo assembly of complete and partial mitogenomes for 175 species. The phylogenetic tree obtained from this local sample was highly similar to that from existing mitogenomes selected for global coverage of major lineages of Coleoptera. When all sequences were combined only minor topological changes were induced against this reference set, indicating an increasingly stable estimate of coleopteran phylogeny, while the ecological sample expanded the tip-level representation of several lineages. Robust trees generated from ecological samples now enable an evolutionary framework for ecology. Meanwhile, the inclusion of uncharacterized samples in the tree-of-life rapidly expands taxon and biogeographic representation of lineages without morphological identification. Mitogenomes from shotgun sequencing of unsorted environmental samples and their associated metadata, placed robustly into the phylogenetic tree, constitute novel DNA “superbarcodes” for testing hypotheses regarding global patterns of diversity. PMID:25957318

Fragment assignment in the cloud with eXpress-D

PubMed Central

2013-01-01

Background Probabilistic assignment of ambiguously mapped fragments produced by high-throughput sequencing experiments has been demonstrated to greatly improve accuracy in the analysis of RNA-Seq and ChIP-Seq, and is an essential step in many other sequence census experiments. A maximum likelihood method using the expectation-maximization (EM) algorithm for optimization is commonly used to solve this problem. However, batch EM-based approaches do not scale well with the size of sequencing datasets, which have been increasing dramatically over the past few years. Thus, current approaches to fragment assignment rely on heuristics or approximations for tractability. Results We present an implementation of a distributed EM solution to the fragment assignment problem using Spark, a data analytics framework that can scale by leveraging compute clusters within datacenters–“the cloud”. We demonstrate that our implementation easily scales to billions of sequenced fragments, while providing the exact maximum likelihood assignment of ambiguous fragments. The accuracy of the method is shown to be an improvement over the most widely used tools available and can be run in a constant amount of time when cluster resources are scaled linearly with the amount of input data. Conclusions The cloud offers one solution for the difficulties faced in the analysis of massive high-thoughput sequencing data, which continue to grow rapidly. Researchers in bioinformatics must follow developments in distributed systems–such as new frameworks like Spark–for ways to port existing methods to the cloud and help them scale to the datasets of the future. Our software, eXpress-D, is freely available at: http://github.com/adarob/express-d. PMID:24314033

BioNano genome mapping of individual chromosomes supports physical mapping and sequence assembly in complex plant genomes.

PubMed

Staňková, Helena; Hastie, Alex R; Chan, Saki; Vrána, Jan; Tulpová, Zuzana; Kubaláková, Marie; Visendi, Paul; Hayashi, Satomi; Luo, Mingcheng; Batley, Jacqueline; Edwards, David; Doležel, Jaroslav; Šimková, Hana

2016-07-01

The assembly of a reference genome sequence of bread wheat is challenging due to its specific features such as the genome size of 17 Gbp, polyploid nature and prevalence of repetitive sequences. BAC-by-BAC sequencing based on chromosomal physical maps, adopted by the International Wheat Genome Sequencing Consortium as the key strategy, reduces problems caused by the genome complexity and polyploidy, but the repeat content still hampers the sequence assembly. Availability of a high-resolution genomic map to guide sequence scaffolding and validate physical map and sequence assemblies would be highly beneficial to obtaining an accurate and complete genome sequence. Here, we chose the short arm of chromosome 7D (7DS) as a model to demonstrate for the first time that it is possible to couple chromosome flow sorting with genome mapping in nanochannel arrays and create a de novo genome map of a wheat chromosome. We constructed a high-resolution chromosome map composed of 371 contigs with an N50 of 1.3 Mb. Long DNA molecules achieved by our approach facilitated chromosome-scale analysis of repetitive sequences and revealed a ~800-kb array of tandem repeats intractable to current DNA sequencing technologies. Anchoring 7DS sequence assemblies obtained by clone-by-clone sequencing to the 7DS genome map provided a valuable tool to improve the BAC-contig physical map and validate sequence assembly on a chromosome-arm scale. Our results indicate that creating genome maps for the whole wheat genome in a chromosome-by-chromosome manner is feasible and that they will be an affordable tool to support the production of improved pseudomolecules. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

PubMed

Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

2018-02-01

Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

Human genomics projects and precision medicine.

PubMed

Carrasco-Ramiro, F; Peiró-Pastor, R; Aguado, B

2017-09-01

The completion of the Human Genome Project (HGP) in 2001 opened the floodgates to a deeper understanding of medicine. There are dozens of HGP-like projects which involve from a few tens to several million genomes currently in progress, which vary from having specialized goals or a more general approach. However, data generation, storage, management and analysis in public and private cloud computing platforms have raised concerns about privacy and security. The knowledge gained from further research has changed the field of genomics and is now slowly permeating into clinical medicine. The new precision (personalized) medicine, where genome sequencing and data analysis are essential components, allows tailored diagnosis and treatment according to the information from the patient's own genome and specific environmental factors. P4 (predictive, preventive, personalized and participatory) medicine is introducing new concepts, challenges and opportunities. This review summarizes current sequencing technologies, concentrates on ongoing human genomics projects, and provides some examples in which precision medicine has already demonstrated clinical impact in diagnosis and/or treatment.

Targeted genotyping-by-sequencing permits cost-effective identification and discrimination of pasture grass species and cultivars.

PubMed

Pembleton, Luke W; Drayton, Michelle C; Bain, Melissa; Baillie, Rebecca C; Inch, Courtney; Spangenberg, German C; Wang, Junping; Forster, John W; Cogan, Noel O I

2016-05-01

A targeted amplicon-based genotyping-by-sequencing approach has permitted cost-effective and accurate discrimination between ryegrass species (perennial, Italian and inter-species hybrid), and identification of cultivars based on bulked samples. Perennial ryegrass and Italian ryegrass are the most important temperate forage species for global agriculture, and are represented in the commercial pasture seed market by numerous cultivars each composed of multiple highly heterozygous individuals. Previous studies have identified difficulties in the use of morphophysiological criteria to discriminate between these two closely related taxa. Recently, a highly multiplexed single nucleotide polymorphism (SNP)-based genotyping assay has been developed that permits accurate differentiation between both species and cultivars of ryegrasses at the genetic level. This assay has since been further developed into an amplicon-based genotyping-by-sequencing (GBS) approach implemented on a second-generation sequencing platform, allowing accelerated throughput and ca. sixfold reduction in cost. Using the GBS approach, 63 cultivars of perennial, Italian and interspecific hybrid ryegrasses, as well as intergeneric Festulolium hybrids, were genotyped. The genetic relationships between cultivars were interpreted in terms of known breeding histories and indistinct species boundaries within the Lolium genus, as well as suitability of current cultivar registration methodologies. An example of applicability to quality assurance and control (QA/QC) of seed purity is also described. Rapid, low-cost genotypic assays provide new opportunities for breeders to more fully explore genetic diversity within breeding programs, allowing the combination of novel unique genetic backgrounds. Such tools also offer the potential to more accurately define cultivar identities, allowing protection of varieties in the commercial market and supporting processes of cultivar accreditation and quality assurance.

The evolution, diversity, and host associations of rhabdoviruses.

PubMed

Longdon, Ben; Murray, Gemma G R; Palmer, William J; Day, Jonathan P; Parker, Darren J; Welch, John J; Obbard, Darren J; Jiggins, Francis M

2015-01-01

Metagenomic studies are leading to the discovery of a hidden diversity of RNA viruses. These new viruses are poorly characterized and new approaches are needed predict the host species these viruses pose a risk to. The rhabdoviruses are a diverse family of RNA viruses that includes important pathogens of humans, animals, and plants. We have discovered thirty-two new rhabdoviruses through a combination of our own RNA sequencing of insects and searching public sequence databases. Combining these with previously known sequences we reconstructed the phylogeny of 195 rhabdovirus sequences, and produced the most in depth analysis of the family to date. In most cases we know nothing about the biology of the viruses beyond the host they were identified from, but our dataset provides a powerful phylogenetic approach to predict which are vector-borne viruses and which are specific to vertebrates or arthropods. By reconstructing ancestral and present host states we found that switches between major groups of hosts have occurred rarely during rhabdovirus evolution. This allowed us to propose seventy-six new likely vector-borne vertebrate viruses among viruses identified from vertebrates or biting insects. Based on currently available data, our analysis suggests it is likely there was a single origin of the known plant viruses and arthropod-borne vertebrate viruses, while vertebrate- and arthropod-specific viruses arose at least twice. There are also few transitions between aquatic and terrestrial ecosystems. Viruses also cluster together at a finer scale, with closely related viruses tending to be found in closely related hosts. Our data therefore suggest that throughout their evolution, rhabdoviruses have occasionally jumped between distantly related host species before spreading through related hosts in the same environment. This approach offers a way to predict the most probable biology and key traits of newly discovered viruses.

A Surrogate Approach to Study the Evolution of Noncoding DNA Elements That Organize Eukaryotic Genomes

PubMed Central

Vermaak, Danielle; Bayes, Joshua J.

2009-01-01

Comparative genomics provides a facile way to address issues of evolutionary constraint acting on different elements of the genome. However, several important DNA elements have not reaped the benefits of this new approach. Some have proved intractable to current day sequencing technology. These include centromeric and heterochromatic DNA, which are essential for chromosome segregation as well as gene regulation, but the highly repetitive nature of the DNA sequences in these regions make them difficult to assemble into longer contigs. Other sequences, like dosage compensation X chromosomal sites, origins of DNA replication, or heterochromatic sequences that encode piwi-associated RNAs, have proved difficult to study because they do not have recognizable DNA features that allow them to be described functionally or computationally. We have employed an alternate approach to the direct study of these DNA elements. By using proteins that specifically bind these noncoding DNAs as surrogates, we can indirectly assay the evolutionary constraints acting on these important DNA elements. We review the impact that such “surrogate strategies” have had on our understanding of the evolutionary constraints shaping centromeres, origins of DNA replication, and dosage compensation X chromosomal sites. These have begun to reveal that in contrast to the view that such structural DNA elements are either highly constrained (under purifying selection) or free to drift (under neutral evolution), some of them may instead be shaped by adaptive evolution and genetic conflicts (these are not mutually exclusive). These insights also help to explain why the same elements (e.g., centromeres and replication origins), which are so complex in some eukaryotic genomes, can be simple and well defined in other where similar conflicts do not exist. PMID:19635763

Computational Protein Engineering: Bridging the Gap between Rational Design and Laboratory Evolution

PubMed Central

Barrozo, Alexandre; Borstnar, Rok; Marloie, Gaël; Kamerlin, Shina Caroline Lynn

2012-01-01

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies. PMID:23202907

An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS.

PubMed

Silva, Genivaldo Gueiros Z; Lopes, Fabyano A C; Edwards, Robert A

2017-01-01

One of the main goals in metagenomics is to identify the functional profile of a microbial community from unannotated shotgun sequencing reads. Functional annotation is important in biological research because it enables researchers to identify the abundance of functional genes of the organisms present in the sample, answering the question, "What can the organisms in the sample do?" Most currently available approaches do not scale with increasing data volumes, which is important because both the number and lengths of the reads provided by sequencing platforms keep increasing. Here, we present SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with real metagenomes, and the results show that it accurately predicts the subsystems present in the profiled microbial communities, is computationally efficient, and up to 1000 times faster than other tools. SUPER-FOCUS is freely available at http://edwards.sdsu.edu/SUPERFOCUS .

Prokaryote genome fluidity: toward a system approach of the mobilome.

PubMed

Toussaint, Ariane; Chandler, Mick

2012-01-01

The importance of horizontal/lateral gene transfer (LGT) in shaping the genomes of prokaryotic organisms has been recognized in recent years as a result of analysis of the increasing number of available genome sequences. LGT is largely due to the transfer and recombination activities of mobile genetic elements (MGEs). Bacterial and archaeal genomes are mosaics of vertically and horizontally transmitted DNA segments. This generates reticulate relationships between members of the prokaryotic world that are better represented by networks than by "classical" phylogenetic trees. In this review we summarize the nature and activities of MGEs, and the problems that presently limit their analysis on a large scale. We propose routes to improve their annotation in the flow of genomic and metagenomic sequences that currently exist and those that become available. We describe network analysis of evolutionary relationships among some MGE categories and sketch out possible developments of this type of approach to get more insight into the role of the mobilome in bacterial adaptation and evolution.

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

PubMed Central

2013-01-01

Background The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Results Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. Conclusions In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. PMID:23442253

Next-Generation Sequencing: The Translational Medicine Approach from “Bench to Bedside to Population”

PubMed Central

Beigh, Mohammad Muzafar

2016-01-01

Humans have predicted the relationship between heredity and diseases for a long time. Only in the beginning of the last century, scientists begin to discover the connotations between different genes and disease phenotypes. Recent trends in next-generation sequencing (NGS) technologies have brought a great momentum in biomedical research that in turn has remarkably augmented our basic understanding of human biology and its associated diseases. State-of-the-art next generation biotechnologies have started making huge strides in our current understanding of mechanisms of various chronic illnesses like cancers, metabolic disorders, neurodegenerative anomalies, etc. We are experiencing a renaissance in biomedical research primarily driven by next generation biotechnologies like genomics, transcriptomics, proteomics, metabolomics, lipidomics etc. Although genomic discoveries are at the forefront of next generation omics technologies, however, their implementation into clinical arena had been painstakingly slow mainly because of high reaction costs and unavailability of requisite computational tools for large-scale data analysis. However rapid innovations and steadily lowering cost of sequence-based chemistries along with the development of advanced bioinformatics tools have lately prompted launching and implementation of large-scale massively parallel genome sequencing programs in different fields ranging from medical genetics, infectious biology, agriculture sciences etc. Recent advances in large-scale omics-technologies is bringing healthcare research beyond the traditional “bench to bedside” approach to more of a continuum that will include improvements, in public healthcare and will be primarily based on predictive, preventive, personalized, and participatory medicine approach (P4). Recent large-scale research projects in genetic and infectious disease biology have indicated that massively parallel whole-genome/whole-exome sequencing, transcriptome analysis, and other functional genomic tools can reveal large number of unique functional elements and/or markers that otherwise would be undetected by traditional sequencing methodologies. Therefore, latest trends in the biomedical research is giving birth to the new branch in medicine commonly referred to as personalized and/or precision medicine. Developments in the post-genomic era are believed to completely restructure the present clinical pattern of disease prevention and treatment as well as methods of diagnosis and prognosis. The next important step in the direction of the precision/personalized medicine approach should be its early adoption in clinics for future medical interventions. Consequently, in coming year’s next generation biotechnologies will reorient medical practice more towards disease prediction and prevention approaches rather than curing them at later stages of their development and progression, even at wider population level(s) for general public healthcare system. PMID:28930123

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.

Transcriptomic Modification in the Cerebral Cortex following Noninvasive Brain Stimulation: RNA-Sequencing Approach

PubMed Central

Holmes, Ben; Jung, Seung Ho; Lu, Jing; Wagner, Jessica A.; Rubbi, Liudmilla; Pellegrini, Matteo

2016-01-01

Transcranial direct current stimulation (tDCS) has been shown to modulate neuroplasticity. Beneficial effects are observed in patients with psychiatric disorders and enhancement of brain performance in healthy individuals has been observed following tDCS. However, few studies have attempted to elucidate the underlying molecular mechanisms of tDCS in the brain. This study was conducted to assess the impact of tDCS on gene expression within the rat cerebral cortex. Anodal tDCS was applied at 3 different intensities followed by RNA-sequencing and analysis. In each current intensity, approximately 1,000 genes demonstrated statistically significant differences compared to the sham group. A variety of functional pathways, biological processes, and molecular categories were found to be modified by tDCS. The impact of tDCS on gene expression was dependent on current intensity. Results show that inflammatory pathways, antidepressant-related pathways (GTP signaling, calcium ion binding, and transmembrane/signal peptide pathways), and receptor signaling pathways (serotonergic, adrenergic, GABAergic, dopaminergic, and glutamate) were most affected. Of the gene expression profiles induced by tDCS, some changes were observed across multiple current intensities while other changes were unique to a single stimulation intensity. This study demonstrates that tDCS can modify the expression profile of various genes in the cerebral cortex and that these tDCS-induced alterations are dependent on the current intensity applied. PMID:28119786

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

PubMed

Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

PubMed Central

Irizarry, Kristopher J. L.; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L.; Barrett, Gini; Barr, Margaret C.

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management. PMID:27376076

Robustly detecting differential expression in RNA sequencing data using observation weights

PubMed Central

Zhou, Xiaobei; Lindsay, Helen; Robinson, Mark D.

2014-01-01

A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods include some sort of ‘sharing of information’ across features to improve inferences in small samples. It is important to achieve an appropriate tradeoff between statistical power and protection against outliers. Here, we study the robustness of existing approaches for count-based differential expression analysis and propose a new strategy based on observation weights that can be used within existing frameworks. The results suggest that outliers can have a global effect on differential analyses. We demonstrate the effectiveness of our new approach with real data and simulated data that reflects properties of real datasets (e.g. dispersion-mean trend) and develop an extensible framework for comprehensive testing of current and future methods. In addition, we explore the origin of such outliers, in some cases highlighting additional biological or technical factors within the experiment. Further details can be downloaded from the project website: http://imlspenticton.uzh.ch/robinson_lab/edgeR_robust/. PMID:24753412

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

PubMed Central

Suciu, Maria C.; Telenius, Jelena

2017-01-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. PMID:28904015

A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

NASA Astrophysics Data System (ADS)

Haijun, Xiong; Qi, Zhang

2016-08-01

Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

Care delivery considerations for widespread and equitable implementation of inherited cancer predisposition testing

PubMed Central

Cragun, Deborah; Kinney, Anita Y; Pal, Tuya

2017-01-01

Introduction DNA sequencing advances through next-generation sequencing (NGS) and several practice changing events, have led to shifting paradigms for inherited cancer predisposition testing. These changes necessitated a means by which to maximize health benefits without unnecessarily inflating healthcare costs and exacerbating health disparities. Areas covered NGS-based tests encompass multi-gene panel tests, whole exome sequencing, and whole genome sequencing, all of which test for multiple genes simultaneously, compared to prior sequencing practices through which testing was performed sequentially for one or two genes. Taking an ecological approach, this article synthesizes the current literature to consider the broad impact of these advances from the individual patient-, interpersonal-, organizational-, community- and policy-levels. Furthermore, the authors describe how multi-level factors that impact genetic testing and follow-up care reveal great potential to widen existing health disparities if these issues are not addressed. Expert Commentary As we consider ways to maximize patient benefit from testing in a cost effective manner, it is important to consider perspectives from multiple levels. This information is needed to guide the development of interventions such that the promise of genomic testing may be realized by all populations, regardless of race, ethnicity and ability to pay. PMID:27910721

Navigating highly homologous genes in a molecular diagnostic setting: a resource for clinical next-generation sequencing.

PubMed

Mandelker, Diana; Schmidt, Ryan J; Ankala, Arunkanth; McDonald Gibson, Kristin; Bowser, Mark; Sharma, Himanshu; Duffy, Elizabeth; Hegde, Madhuri; Santani, Avni; Lebo, Matthew; Funke, Birgit

2016-12-01

Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

PubMed Central

Lipinski, Leszek; Dziembowski, Andrzej

2018-01-01

Abstract Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions. PMID:29346586

Using expected sequence features to improve basecalling accuracy of amplicon pyrosequencing data.

PubMed

Rask, Thomas S; Petersen, Bent; Chen, Donald S; Day, Karen P; Pedersen, Anders Gorm

2016-04-22

Amplicon pyrosequencing targets a known genetic region and thus inherently produces reads highly anticipated to have certain features, such as conserved nucleotide sequence, and in the case of protein coding DNA, an open reading frame. Pyrosequencing errors, consisting mainly of nucleotide insertions and deletions, are on the other hand likely to disrupt open reading frames. Such an inverse relationship between errors and expectation based on prior knowledge can be used advantageously to guide the process known as basecalling, i.e. the inference of nucleotide sequence from raw sequencing data. The new basecalling method described here, named Multipass, implements a probabilistic framework for working with the raw flowgrams obtained by pyrosequencing. For each sequence variant Multipass calculates the likelihood and nucleotide sequence of several most likely sequences given the flowgram data. This probabilistic approach enables integration of basecalling into a larger model where other parameters can be incorporated, such as the likelihood for observing a full-length open reading frame at the targeted region. We apply the method to 454 amplicon pyrosequencing data obtained from a malaria virulence gene family, where Multipass generates 20 % more error-free sequences than current state of the art methods, and provides sequence characteristics that allow generation of a set of high confidence error-free sequences. This novel method can be used to increase accuracy of existing and future amplicon sequencing data, particularly where extensive prior knowledge is available about the obtained sequences, for example in analysis of the immunoglobulin VDJ region where Multipass can be combined with a model for the known recombining germline genes. Multipass is available for Roche 454 data at http://www.cbs.dtu.dk/services/MultiPass-1.0 , and the concept can potentially be implemented for other sequencing technologies as well.

Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics.

PubMed

Gullapalli, Rama R; Desai, Ketaki V; Santana-Santos, Lucas; Kant, Jeffrey A; Becich, Michael J

2012-01-01

The Human Genome Project (HGP) provided the initial draft of mankind's DNA sequence in 2001. The HGP was produced by 23 collaborating laboratories using Sanger sequencing of mapped regions as well as shotgun sequencing techniques in a process that occupied 13 years at a cost of ~$3 billion. Today, Next Generation Sequencing (NGS) techniques represent the next phase in the evolution of DNA sequencing technology at dramatically reduced cost compared to traditional Sanger sequencing. A single laboratory today can sequence the entire human genome in a few days for a few thousand dollars in reagents and staff time. Routine whole exome or even whole genome sequencing of clinical patients is well within the realm of affordability for many academic institutions across the country. This paper reviews current sequencing technology methods and upcoming advancements in sequencing technology as well as challenges associated with data generation, data manipulation and data storage. Implementation of routine NGS data in cancer genomics is discussed along with potential pitfalls in the interpretation of the NGS data. The overarching importance of bioinformatics in the clinical implementation of NGS is emphasized.[7] We also review the issue of physician education which also is an important consideration for the successful implementation of NGS in the clinical workplace. NGS technologies represent a golden opportunity for the next generation of pathologists to be at the leading edge of the personalized medicine approaches coming our way. Often under-emphasized issues of data access and control as well as potential ethical implications of whole genome NGS sequencing are also discussed. Despite some challenges, it's hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease in the near future.

Filling Gaps in Biodiversity Knowledge for Macrofungi: Contributions and Assessment of an Herbarium Collection DNA Barcode Sequencing Project

PubMed Central

Osmundson, Todd W.; Robert, Vincent A.; Schoch, Conrad L.; Baker, Lydia J.; Smith, Amy; Robich, Giovanni; Mizzan, Luca; Garbelotto, Matteo M.

2013-01-01

Despite recent advances spearheaded by molecular approaches and novel technologies, species description and DNA sequence information are significantly lagging for fungi compared to many other groups of organisms. Large scale sequencing of vouchered herbarium material can aid in closing this gap. Here, we describe an effort to obtain broad ITS sequence coverage of the approximately 6000 macrofungal-species-rich herbarium of the Museum of Natural History in Venice, Italy. Our goals were to investigate issues related to large sequencing projects, develop heuristic methods for assessing the overall performance of such a project, and evaluate the prospects of such efforts to reduce the current gap in fungal biodiversity knowledge. The effort generated 1107 sequences submitted to GenBank, including 416 previously unrepresented taxa and 398 sequences exhibiting a best BLAST match to an unidentified environmental sequence. Specimen age and taxon affected sequencing success, and subsequent work on failed specimens showed that an ITS1 mini-barcode greatly increased sequencing success without greatly reducing the discriminating power of the barcode. Similarity comparisons and nonmetric multidimensional scaling ordinations based on pairwise distance matrices proved to be useful heuristic tools for validating the overall accuracy of specimen identifications, flagging potential misidentifications, and identifying taxa in need of additional species-level revision. Comparison of within- and among-species nucleotide variation showed a strong increase in species discriminating power at 1–2% dissimilarity, and identified potential barcoding issues (same sequence for different species and vice-versa). All sequences are linked to a vouchered specimen, and results from this study have already prompted revisions of species-sequence assignments in several taxa. PMID:23638077

Filling gaps in biodiversity knowledge for macrofungi: contributions and assessment of an herbarium collection DNA barcode sequencing project.

PubMed

Osmundson, Todd W; Robert, Vincent A; Schoch, Conrad L; Baker, Lydia J; Smith, Amy; Robich, Giovanni; Mizzan, Luca; Garbelotto, Matteo M

2013-01-01

Despite recent advances spearheaded by molecular approaches and novel technologies, species description and DNA sequence information are significantly lagging for fungi compared to many other groups of organisms. Large scale sequencing of vouchered herbarium material can aid in closing this gap. Here, we describe an effort to obtain broad ITS sequence coverage of the approximately 6000 macrofungal-species-rich herbarium of the Museum of Natural History in Venice, Italy. Our goals were to investigate issues related to large sequencing projects, develop heuristic methods for assessing the overall performance of such a project, and evaluate the prospects of such efforts to reduce the current gap in fungal biodiversity knowledge. The effort generated 1107 sequences submitted to GenBank, including 416 previously unrepresented taxa and 398 sequences exhibiting a best BLAST match to an unidentified environmental sequence. Specimen age and taxon affected sequencing success, and subsequent work on failed specimens showed that an ITS1 mini-barcode greatly increased sequencing success without greatly reducing the discriminating power of the barcode. Similarity comparisons and nonmetric multidimensional scaling ordinations based on pairwise distance matrices proved to be useful heuristic tools for validating the overall accuracy of specimen identifications, flagging potential misidentifications, and identifying taxa in need of additional species-level revision. Comparison of within- and among-species nucleotide variation showed a strong increase in species discriminating power at 1-2% dissimilarity, and identified potential barcoding issues (same sequence for different species and vice-versa). All sequences are linked to a vouchered specimen, and results from this study have already prompted revisions of species-sequence assignments in several taxa.

Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics

PubMed Central

Gullapalli, Rama R.; Desai, Ketaki V.; Santana-Santos, Lucas; Kant, Jeffrey A.; Becich, Michael J.

2012-01-01

The Human Genome Project (HGP) provided the initial draft of mankind's DNA sequence in 2001. The HGP was produced by 23 collaborating laboratories using Sanger sequencing of mapped regions as well as shotgun sequencing techniques in a process that occupied 13 years at a cost of ~$3 billion. Today, Next Generation Sequencing (NGS) techniques represent the next phase in the evolution of DNA sequencing technology at dramatically reduced cost compared to traditional Sanger sequencing. A single laboratory today can sequence the entire human genome in a few days for a few thousand dollars in reagents and staff time. Routine whole exome or even whole genome sequencing of clinical patients is well within the realm of affordability for many academic institutions across the country. This paper reviews current sequencing technology methods and upcoming advancements in sequencing technology as well as challenges associated with data generation, data manipulation and data storage. Implementation of routine NGS data in cancer genomics is discussed along with potential pitfalls in the interpretation of the NGS data. The overarching importance of bioinformatics in the clinical implementation of NGS is emphasized.[7] We also review the issue of physician education which also is an important consideration for the successful implementation of NGS in the clinical workplace. NGS technologies represent a golden opportunity for the next generation of pathologists to be at the leading edge of the personalized medicine approaches coming our way. Often under-emphasized issues of data access and control as well as potential ethical implications of whole genome NGS sequencing are also discussed. Despite some challenges, it's hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease in the near future. PMID:23248761

Designing robust watermark barcodes for multiplex long-read sequencing.

PubMed

Ezpeleta, Joaquín; Krsticevic, Flavia J; Bulacio, Pilar; Tapia, Elizabeth

2017-03-15

To attain acceptable sample misassignment rates, current approaches to multiplex single-molecule real-time sequencing require upstream quality improvement, which is obtained from multiple passes over the sequenced insert and significantly reduces the effective read length. In order to fully exploit the raw read length on multiplex applications, robust barcodes capable of dealing with the full single-pass error rates are needed. We present a method for designing sequencing barcodes that can withstand a large number of insertion, deletion and substitution errors and are suitable for use in multiplex single-molecule real-time sequencing. The manuscript focuses on the design of barcodes for full-length single-pass reads, impaired by challenging error rates in the order of 11%. The proposed barcodes can multiplex hundreds or thousands of samples while achieving sample misassignment probabilities as low as 10-7 under the above conditions, and are designed to be compatible with chemical constraints imposed by the sequencing process. Software tools for constructing watermark barcode sets and demultiplexing barcoded reads, together with example sets of barcodes and synthetic barcoded reads, are freely available at www.cifasis-conicet.gov.ar/ezpeleta/NS-watermark . ezpeleta@cifasis-conicet.gov.ar. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Phylogenetic relationships of Malassezia species based on multilocus sequence analysis.

PubMed

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

2014-01-01

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

Prediction of enhancer-promoter interactions via natural language processing.

PubMed

Zeng, Wanwen; Wu, Mengmeng; Jiang, Rui

2018-05-09

Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput. We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions. We first extract sequence embedding features, defined as fixed-length vector representations learned from variable-length sequences using an unsupervised deep learning method in natural language processing. Then, we train a classifier to predict EPIs using the learned representations in supervised way. Experimental results demonstrate that EP2vec obtains F1 scores ranging from 0.841~ 0.933 on different datasets, which outperforms existing methods. We prove the robustness of sequence embedding features by carrying out sensitivity analysis. Besides, we identify motifs that represent cell line-specific information through analysis of the learned sequence embedding features by adopting attention mechanism. Last, we show that even superior performance with F1 scores 0.889~ 0.940 can be achieved by combining sequence embedding features and experimental features. EP2vec sheds light on feature extraction for DNA sequences of arbitrary lengths and provides a powerful approach for EPIs identification.

Progress in Understanding and Sequencing the Genome of Brassica rapa

PubMed Central

Hong, Chang Pyo; Kwon, Soo-Jin; Kim, Jung Sun; Yang, Tae-Jin; Park, Beom-Seok; Lim, Yong Pyo

2008-01-01

Brassica rapa, which is closely related to Arabidopsis thaliana, is an important crop and a model plant for studying genome evolution via polyploidization. We report the current understanding of the genome structure of B. rapa and efforts for the whole-genome sequencing of the species. The tribe Brassicaceae, which comprises ca. 240 species, descended from a common hexaploid ancestor with a basic genome similar to that of Arabidopsis. Chromosome rearrangements, including fusions and/or fissions, resulted in the present-day “diploid” Brassica species with variation in chromosome number and phenotype. Triplicated genomic segments of B. rapa are collinear to those of A. thaliana with InDels. The genome triplication has led to an approximately 1.7-fold increase in the B. rapa gene number compared to that of A. thaliana. Repetitive DNA of B. rapa has also been extensively amplified and has diverged from that of A. thaliana. For its whole-genome sequencing, the Brassica rapa Genome Sequencing Project (BrGSP) consortium has developed suitable genomic resources and constructed genetic and physical maps. Ten chromosomes of B. rapa are being allocated to BrGSP consortium participants, and each chromosome will be sequenced by a BAC-by-BAC approach. Genome sequencing of B. rapa will offer a new perspective for plant biology and evolution in the context of polyploidization. PMID:18288250

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

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

Zemla, A; Lang, D; Kostova, T

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitatemore » the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position.« less

Balancing Selection and Its Effects on Sequences in Nearby Genome Regions

PubMed Central

Charlesworth, Deborah

2006-01-01

Our understanding of balancing selection is currently becoming greatly clarified by new sequence data being gathered from genes in which polymorphisms are known to be maintained by selection. The data can be interpreted in conjunction with results from population genetics models that include recombination between selected sites and nearby neutral marker variants. This understanding is making possible tests for balancing selection using molecular evolutionary approaches. Such tests do not necessarily require knowledge of the functional types of the different alleles at a locus, but such information, as well as information about the geographic distribution of alleles and markers near the genes, can potentially help towards understanding what form of balancing selection is acting, and how long alleles have been maintained. PMID:16683038

Emerging from the bottleneck: Benefits of the comparative approach to modern neuroscience

PubMed Central

Brenowitz, Eliot A.; Zakon, Harold H.

2015-01-01

Neuroscience historically exploited a wide diversity of animal taxa. Recently, however, research focused increasingly on a few model species. This trend accelerated with the genetic revolution, as genomic sequences and genetic tools became available for a few species, which formed a bottleneck. This coalescence on a small set of model species comes with several costs often not considered, especially in the current drive to use mice explicitly as models for human diseases. Comparative studies of strategically chosen non-model species can complement model species research and yield more rigorous studies. As genetic sequences and tools become available for many more species, we are poised to emerge from the bottleneck and once again exploit the rich biological diversity offered by comparative studies. PMID:25800324

Improved bacteriophage genome data is necessary for integrating viral and bacterial ecology.

PubMed

Bibby, Kyle

2014-02-01

The recent rise in "omics"-enabled approaches has lead to improved understanding in many areas of microbial ecology. However, despite the importance that viruses play in a broad microbial ecology context, viral ecology remains largely not integrated into high-throughput microbial ecology studies. A fundamental hindrance to the integration of viral ecology into omics-enabled microbial ecology studies is the lack of suitable reference bacteriophage genomes in reference databases-currently, only 0.001% of bacteriophage diversity is represented in genome sequence databases. This commentary serves to highlight this issue and to promote bacteriophage genome sequencing as a valuable scientific undertaking to both better understand bacteriophage diversity and move towards a more holistic view of microbial ecology.

The others: our biased perspective of eukaryotic genomes

PubMed Central

del Campo, Javier; Sieracki, Michael E.; Molestina, Robert; Keeling, Patrick; Massana, Ramon; Ruiz-Trillo, Iñaki

2015-01-01

Understanding the origin and evolution of the eukaryotic cell and the full diversity of eukaryotes is relevant to many biological disciplines. However, our current understanding of eukaryotic genomes is extremely biased, leading to a skewed view of eukaryotic biology. We argue that a phylogeny-driven initiative to cover the full eukaryotic diversity is needed to overcome this bias. We encourage the community: (i) to sequence a representative of the neglected groups available at public culture collections, (ii) to increase our culturing efforts, and (iii) to embrace single cell genomics to access organisms refractory to propagation in culture. We hope that the community will welcome this proposal, explore the approaches suggested, and join efforts to sequence the full diversity of eukaryotes. PMID:24726347

High-Throughput Sequencing and Metagenomics: Moving Forward in the Culture-Independent Analysis of Food Microbial Ecology

PubMed Central

2013-01-01

Following recent trends in environmental microbiology, food microbiology has benefited from the advances in molecular biology and adopted novel strategies to detect, identify, and monitor microbes in food. An in-depth study of the microbial diversity in food can now be achieved by using high-throughput sequencing (HTS) approaches after direct nucleic acid extraction from the sample to be studied. In this review, the workflow of applying culture-independent HTS to food matrices is described. The current scenario and future perspectives of HTS uses to study food microbiota are presented, and the decision-making process leading to the best choice of working conditions to fulfill the specific needs of food research is described. PMID:23475615

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

PubMed

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys.

Single molecule detection with graphene and other two-dimensional materials: nanopores and beyond

PubMed Central

Arjmandi-Tash, Hadi; Belyaeva, Liubov A.

2016-01-01

Graphene and other two dimensional (2D) materials are currently integrated into nanoscaled devices that may – one day – sequence genomes. The challenge to solve is conceptually straightforward: cut a sheet out of a 2D material and use the edge of the sheet to scan an unfolded biomolecule from head to tail. As the scan proceeds – and because 2D materials are atomically thin – the information provided by the edge might be used to identify different segments – ideally single nucleotides – in the biomolecular strand. So far, the most efficient approach was to drill a nano-sized pore in the sheet and use this pore as a channel to guide and detect individual molecules by measuring the electrochemical ionic current. Nanoscaled gaps between two electrodes in 2D materials recently emerged as powerful alternatives to nanopores. This article reviews the current status and prospects of integrating 2D materials in nanopores, nanogaps and similar devices for single molecule biosensing applications. We discuss the pros and cons, the challenges, and the latest achievements in the field. To achieve high-throughput sequencing with 2D materials, interdisciplinary research is essential. PMID:26612268

Nanopore analysis of polymers in solution.

NASA Astrophysics Data System (ADS)

Deamer, David

2002-03-01

Nanopores represent a novel approach for investigating macromolecules in solution. Polymers that have been analyzed by this technique include polyethylene glycol (PEG), certain proteins and nucleic acids. The a-hemolysin pore inserted into lipid bilayers provides continuous non-gated ion current through a pore diameter of approximately 1.5 - 2 nm. Nucleic acid molecules can be driven through the pore by imposing a voltage across the supporting membrane. Single stranded, but not double stranded nucleic acids pass through in strict linear sequence from one end of the molecule to the other. While in the pore, the molecule reduces ionic current, and properties of the ionic current blockade such as duration, mean amplitude and modulations of amplitude provide information about structure and composition of the nucleic acid. For a given molecular species, the duration of the blockade is a function of chain length, and the rate of blockades is linearly related to concentration. More recent studies have shown that the a-hemolysin nanopore can discriminate between synthetic DNA molecules differing by a single base pair or even a single nucleotide. These results indicate that a nanopore may have the resolution required for nucleic acid sequencing applications.

[Current advances and future prospects of genome editing technology in the field of biomedicine.

PubMed

Sakuma, Tetsushi

Genome editing technology can alter the genomic sequence at will, contributing the creation of cellular and animal models of human diseases including hereditary disorders and cancers, and the generation of the mutation-corrected human induced pluripotent stem cells for ex vivo regenerative medicine. In addition, novel approaches such as drug development using genome-wide CRISPR screening and cancer suppression using epigenome editing technology, which can change the epigenetic modifications in a site-specific manner, have also been conducted. In this article, I summarize the current advances and future prospects of genome editing technology in the field of biomedicine.

Current siRNA Targets in Atherosclerosis and Aortic Aneurysm

PubMed Central

Pradhan-Nabzdyk, Leena; Huang, Chenyu; Logerfo, Frank W.; Nabzdyk, Christoph S.

2014-01-01

Atherosclerosis (ATH) and aortic aneurysms (AA) remain challenging chronic diseases that confer high morbidity and mortality despite advances in medical, interventional, and surgical care. RNA interference represents a promising technology that may be utilized to silence genes contributing to ATH and AA. Despite positive results in preclinical and some clinical feasibility studies, challenges such as target/sequence validation, tissue specificity, transfection efficiency, and mitigation of unwanted off-target effects remain to be addressed. In this review the most current targets and some novel approaches in siRNA delivery are being discussed. Due to the plethora of investigated targets, only studies published between 2010 and 2014 were included. PMID:24882715

Barcoding snakeheads (Teleostei, Channidae) revisited: Discovering greater species diversity and resolving perpetuated taxonomic confusions

PubMed Central

Conte-Grand, Cecilia; Britz, Ralf; Dahanukar, Neelesh; Raghavan, Rajeev; Pethiyagoda, Rohan; Tan, Heok Hui; Hadiaty, Renny K.; Yaakob, Norsham S.

2017-01-01

Snakehead fishes of the family Channidae are predatory freshwater teleosts from Africa and Asia comprising 38 valid species. Snakeheads are important food fishes (aquaculture, live food trade) and have been introduced widely with several species becoming highly invasive. A channid barcode library was recently assembled by Serrao and co-workers to better detect and identify potential and established invasive snakehead species outside their native range. Comparing our own recent phylogenetic results of this taxonomically confusing group with those previously reported revealed several inconsistencies that prompted us to expand and improve on previous studies. By generating 343 novel snakehead coxI sequences and combining them with an additional 434 coxI sequences from GenBank we highlight several problems with previous efforts towards the assembly of a snakehead reference barcode library. We found that 16.3% of the channid coxI sequences deposited in GenBank are based on misidentifications. With the inclusion of our own data we were, however, able to solve these cases of perpetuated taxonomic confusion. Different species delimitation approaches we employed (BIN, GMYC, and PTP) were congruent in suggesting a potentially much higher species diversity within snakeheads than currently recognized. In total, 90 BINs were recovered and within a total of 15 currently recognized species multiple BINs were identified. This higher species diversity is mostly due to either the incorporation of undescribed, narrow range, endemics from the Eastern Himalaya biodiversity hotspot or the incorporation of several widespread species characterized by deep genetic splits between geographically well-defined lineages. In the latter case, over-lumping in the past has deflated the actual species numbers. Further integrative approaches are clearly needed for providing a better taxonomic understanding of snakehead diversity, new species descriptions and taxonomic revisions of the group. PMID:28931084

Next-Generation Sequencing Approaches in Genome-Wide Discovery of Single Nucleotide Polymorphism Markers Associated with Pungency and Disease Resistance in Pepper.

PubMed

Manivannan, Abinaya; Kim, Jin-Hee; Yang, Eun-Young; Ahn, Yul-Kyun; Lee, Eun-Su; Choi, Sena; Kim, Do-Sun

2018-01-01

Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS) approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP) indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.

ProGeRF: Proteome and Genome Repeat Finder Utilizing a Fast Parallel Hash Function

PubMed Central

Moraes, Walas Jhony Lopes; Rodrigues, Thiago de Souza; Bartholomeu, Daniella Castanheira

2015-01-01

Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity. PMID:25811026

Towards predictive models of the human gut microbiome

PubMed Central

2014-01-01

The intestinal microbiota is an ecosystem susceptible to external perturbations such as dietary changes and antibiotic therapies. Mathematical models of microbial communities could be of great value in the rational design of microbiota-tailoring diets and therapies. Here, we discuss how advances in another field, engineering of microbial communities for wastewater treatment bioreactors, could inspire development of mechanistic mathematical models of the gut microbiota. We review the current state-of-the-art in bioreactor modeling and current efforts in modeling the intestinal microbiota. Mathematical modeling could benefit greatly from the deluge of data emerging from metagenomic studies, but data-driven approaches such as network inference that aim to predict microbiome dynamics without explicit mechanistic knowledge seem better suited to model these data. Finally, we discuss how the integration of microbiome shotgun sequencing and metabolic modeling approaches such as flux balance analysis may fulfill the promise of a mechanistic model of the intestinal microbiota. PMID:24727124

Error and Error Mitigation in Low-Coverage Genome Assemblies

PubMed Central

Hubisz, Melissa J.; Lin, Michael F.; Kellis, Manolis; Siepel, Adam

2011-01-01

The recent release of twenty-two new genome sequences has dramatically increased the data available for mammalian comparative genomics, but twenty of these new sequences are currently limited to ∼2× coverage. Here we examine the extent of sequencing error in these 2× assemblies, and its potential impact in downstream analyses. By comparing 2× assemblies with high-quality sequences from the ENCODE regions, we estimate the rate of sequencing error to be 1–4 errors per kilobase. While this error rate is fairly modest, sequencing error can still have surprising effects. For example, an apparent lineage-specific insertion in a coding region is more likely to reflect sequencing error than a true biological event, and the length distribution of coding indels is strongly distorted by error. We find that most errors are contributed by a small fraction of bases with low quality scores, in particular, by the ends of reads in regions of single-read coverage in the assembly. We explore several approaches for automatic sequencing error mitigation (SEM), making use of the localized nature of sequencing error, the fact that it is well predicted by quality scores, and information about errors that comes from comparisons across species. Our automatic methods for error mitigation cannot replace the need for additional sequencing, but they do allow substantial fractions of errors to be masked or eliminated at the cost of modest amounts of over-correction, and they can reduce the impact of error in downstream phylogenomic analyses. Our error-mitigated alignments are available for download. PMID:21340033

Opportunities and challenges provided by cloud repositories for bioinformatics-enabled drug discovery.

PubMed

Dalpé, Gratien; Joly, Yann

2014-09-01

Healthcare-related bioinformatics databases are increasingly offering the possibility to maintain, organize, and distribute DNA sequencing data. Different national and international institutions are currently hosting such databases that offer researchers website platforms where they can obtain sequencing data on which they can perform different types of analysis. Until recently, this process remained mostly one-dimensional, with most analysis concentrated on a limited amount of data. However, newer genome sequencing technology is producing a huge amount of data that current computer facilities are unable to handle. An alternative approach has been to start adopting cloud computing services for combining the information embedded in genomic and model system biology data, patient healthcare records, and clinical trials' data. In this new technological paradigm, researchers use virtual space and computing power from existing commercial or not-for-profit cloud service providers to access, store, and analyze data via different application programming interfaces. Cloud services are an alternative to the need of larger data storage; however, they raise different ethical, legal, and social issues. The purpose of this Commentary is to summarize how cloud computing can contribute to bioinformatics-based drug discovery and to highlight some of the outstanding legal, ethical, and social issues that are inherent in the use of cloud services. © 2014 Wiley Periodicals, Inc.

Advances in DNA metabarcoding for food and wildlife forensic species identification.

PubMed

Staats, Martijn; Arulandhu, Alfred J; Gravendeel, Barbara; Holst-Jensen, Arne; Scholtens, Ingrid; Peelen, Tamara; Prins, Theo W; Kok, Esther

2016-07-01

Species identification using DNA barcodes has been widely adopted by forensic scientists as an effective molecular tool for tracking adulterations in food and for analysing samples from alleged wildlife crime incidents. DNA barcoding is an approach that involves sequencing of short DNA sequences from standardized regions and comparison to a reference database as a molecular diagnostic tool in species identification. In recent years, remarkable progress has been made towards developing DNA metabarcoding strategies, which involves next-generation sequencing of DNA barcodes for the simultaneous detection of multiple species in complex samples. Metabarcoding strategies can be used in processed materials containing highly degraded DNA e.g. for the identification of endangered and hazardous species in traditional medicine. This review aims to provide insight into advances of plant and animal DNA barcoding and highlights current practices and recent developments for DNA metabarcoding of food and wildlife forensic samples from a practical point of view. Special emphasis is placed on new developments for identifying species listed in the Convention on International Trade of Endangered Species (CITES) appendices for which reliable methods for species identification may signal and/or prevent illegal trade. Current technological developments and challenges of DNA metabarcoding for forensic scientists will be assessed in the light of stakeholders' needs.

Spherical: an iterative workflow for assembling metagenomic datasets.

PubMed

Hitch, Thomas C A; Creevey, Christopher J

2018-01-24

The consensus emerging from the study of microbiomes is that they are far more complex than previously thought, requiring better assemblies and increasingly deeper sequencing. However, current metagenomic assembly techniques regularly fail to incorporate all, or even the majority in some cases, of the sequence information generated for many microbiomes, negating this effort. This can especially bias the information gathered and the perceived importance of the minor taxa in a microbiome. We propose a simple but effective approach, implemented in Python, to address this problem. Based on an iterative methodology, our workflow (called Spherical) carries out successive rounds of assemblies with the sequencing reads not yet utilised. This approach also allows the user to reduce the resources required for very large datasets, by assembling random subsets of the whole in a "divide and conquer" manner. We demonstrate the accuracy of Spherical using simulated data based on completely sequenced genomes and the effectiveness of the workflow at retrieving lost information for taxa in three published metagenomics studies of varying sizes. Our results show that Spherical increased the amount of reads utilized in the assembly by up to 109% compared to the base assembly. The additional contigs assembled by the Spherical workflow resulted in a significant (P < 0.05) changes in the predicted taxonomic profile of all datasets analysed. Spherical is implemented in Python 2.7 and freely available for use under the MIT license. Source code and documentation is hosted publically at: https://github.com/thh32/Spherical .

Personalized genomic analyses for cancer mutation discovery and interpretation

PubMed Central

Jones, Siân; Anagnostou, Valsamo; Lytle, Karli; Parpart-Li, Sonya; Nesselbush, Monica; Riley, David R.; Shukla, Manish; Chesnick, Bryan; Kadan, Maura; Papp, Eniko; Galens, Kevin G.; Murphy, Derek; Zhang, Theresa; Kann, Lisa; Sausen, Mark; Angiuoli, Samuel V.; Diaz, Luis A.; Velculescu, Victor E.

2015-01-01

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients. PMID:25877891

Vibrio cholerae Serogroup O139: Isolation from Cholera Patients and Asymptomatic Household Family Members in Bangladesh between 2013 and 2014.

PubMed

Chowdhury, Fahima; Mather, Alison E; Begum, Yasmin Ara; Asaduzzaman, Muhammad; Baby, Nabilah; Sharmin, Salma; Biswas, Rajib; Uddin, Muhammad Ikhtear; LaRocque, Regina C; Harris, Jason B; Calderwood, Stephen B; Ryan, Edward T; Clemens, John D; Thomson, Nicholas R; Qadri, Firdausi

2015-11-01

Cholera is endemic in Bangladesh, with outbreaks reported annually. Currently, the majority of epidemic cholera reported globally is El Tor biotype Vibrio cholerae isolates of the serogroup O1. However, in Bangladesh, outbreaks attributed to V. cholerae serogroup O139 isolates, which fall within the same phylogenetic lineage as the O1 serogroup isolates, were seen between 1992 and 1993 and in 2002 to 2005. Since then, V. cholerae serogroup O139 has only been sporadically isolated in Bangladesh and is now rarely isolated elsewhere. Here, we present case histories of four cholera patients infected with V. cholerae serogroup O139 in 2013 and 2014 in Bangladesh. We comprehensively typed these isolates using conventional approaches, as well as by whole genome sequencing. Phenotypic typing and PCR confirmed all four isolates belonging to the O139 serogroup. Whole genome sequencing revealed that three of the isolates were phylogenetically closely related to previously sequenced El Tor biotype, pandemic 7, toxigenic V. cholerae O139 isolates originating from Bangladesh and elsewhere. The fourth isolate was a non-toxigenic V. cholerae that, by conventional approaches, typed as O139 serogroup but was genetically divergent from previously sequenced pandemic 7 V. cholerae lineages belonging to the O139 or O1 serogroups. These results suggest that previously observed lineages of V. cholerae O139 persist in Bangladesh and can cause clinical disease and that a novel disease-causing non-toxigenic O139 isolate also occurs.

Towards Spectral Library-free MALDI-TOF MS Bacterial Identification.

PubMed

Cheng, Ding; Qiao, Liang; Horvatovich, Péter

2018-05-11

Bacterial identification is of great importance in clinical diagnosis, environmental monitoring and food safety control. Among various strategies, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has drawn significant interests, and has been clinically used. Nevertheless, current bioinformatics solutions use spectral libraries for the identification of bacterial strains. Spectral library generation requires acquisition of MALDI-TOF spectra from monoculture bacterial colonies, which is time-consuming and not possible for many species and strains. We propose a strategy for bacterial typing by MALDI-TOF using protein sequences from public database, i.e. UniProt. Ten genes were identified to encode proteins most often observed by MALD-TOF from bacteria through 500 times repeated a 10-fold double cross-validation procedure, using 403 MALDI-TOF spectra corresponding to 14 genera, 81 species and 403 strains, and the protein sequences of 1276 species in UniProt. The 10 genes were then used to annotate peaks on MALDI-TOF spectra of bacteria for bacterial identification. With the approach, bacteria can be identified at the genus level by searching against a database containing the protein sequences of 42 genera of bacteria from UniProt. Our approach identified 84.1% of the 403 spectra correctly at the genus level. Source code of the algorithm is available at https://github.com/dipcarbon/BacteriaMSLF.

QUANTIFYING ALTERNATIVE SPLICING FROM PAIRED-END RNA-SEQUENCING DATA.

PubMed

Rossell, David; Stephan-Otto Attolini, Camille; Kroiss, Manuel; Stöcker, Almond

2014-03-01

RNA-sequencing has revolutionized biomedical research and, in particular, our ability to study gene alternative splicing. The problem has important implications for human health, as alternative splicing may be involved in malfunctions at the cellular level and multiple diseases. However, the high-dimensional nature of the data and the existence of experimental biases pose serious data analysis challenges. We find that the standard data summaries used to study alternative splicing are severely limited, as they ignore a substantial amount of valuable information. Current data analysis methods are based on such summaries and are hence sub-optimal. Further, they have limited flexibility in accounting for technical biases. We propose novel data summaries and a Bayesian modeling framework that overcome these limitations and determine biases in a non-parametric, highly flexible manner. These summaries adapt naturally to the rapid improvements in sequencing technology. We provide efficient point estimates and uncertainty assessments. The approach allows to study alternative splicing patterns for individual samples and can also be the basis for downstream analyses. We found a several fold improvement in estimation mean square error compared popular approaches in simulations, and substantially higher consistency between replicates in experimental data. Our findings indicate the need for adjusting the routine summarization and analysis of alternative splicing RNA-seq studies. We provide a software implementation in the R package casper.

Identifying currents in the gene pool for bacterial populations using an integrative approach.

PubMed

Tang, Jing; Hanage, William P; Fraser, Christophe; Corander, Jukka

2009-08-01

The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html.

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

PubMed

Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

Unbiased Characterization of Anopheles Mosquito Blood Meals by Targeted High-Throughput Sequencing

PubMed Central

Logue, Kyle; Keven, John Bosco; Cannon, Matthew V.; Reimer, Lisa; Siba, Peter; Walker, Edward D.; Zimmerman, Peter A.; Serre, David

2016-01-01

Understanding mosquito host choice is important for assessing vector competence or identifying disease reservoirs. Unfortunately, the availability of an unbiased method for comprehensively evaluating the composition of insect blood meals is very limited, as most current molecular assays only test for the presence of a few pre-selected species. These approaches also have limited ability to identify the presence of multiple mammalian hosts in a single blood meal. Here, we describe a novel high-throughput sequencing method that enables analysis of 96 mosquitoes simultaneously and provides a comprehensive and quantitative perspective on the composition of each blood meal. We validated in silico that universal primers targeting the mammalian mitochondrial 16S ribosomal RNA genes (16S rRNA) should amplify more than 95% of the mammalian 16S rRNA sequences present in the NCBI nucleotide database. We applied this method to 442 female Anopheles punctulatus s. l. mosquitoes collected in Papua New Guinea (PNG). While human (52.9%), dog (15.8%) and pig (29.2%) were the most common hosts identified in our study, we also detected DNA from mice, one marsupial species and two bat species. Our analyses also revealed that 16.3% of the mosquitoes fed on more than one host. Analysis of the human mitochondrial hypervariable region I in 102 human blood meals showed that 5 (4.9%) of the mosquitoes unambiguously fed on more than one person. Overall, analysis of PNG mosquitoes illustrates the potential of this approach to identify unsuspected hosts and characterize mixed blood meals, and shows how this approach can be adapted to evaluate inter-individual variations among human blood meals. Furthermore, this approach can be applied to any disease-transmitting arthropod and can be easily customized to investigate non-mammalian host sources. PMID:26963245

INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

PubMed Central

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B.

2013-01-01

Background The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. Results We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. Conclusions We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo. PMID:24324765

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

PubMed

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba Alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B

2013-01-01

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.

Assessing DNA Barcodes for Species Identification in North American Reptiles and Amphibians in Natural History Collections.

PubMed

Chambers, E Anne; Hebert, Paul D N

2016-01-01

High rates of species discovery and loss have led to the urgent need for more rapid assessment of species diversity in the herpetofauna. DNA barcoding allows for the preliminary identification of species based on sequence divergence. Prior DNA barcoding work on reptiles and amphibians has revealed higher biodiversity counts than previously estimated due to cases of cryptic and undiscovered species. Past studies have provided DNA barcodes for just 14% of the North American herpetofauna, revealing the need for expanded coverage. This study extends the DNA barcode reference library for North American herpetofauna, assesses the utility of this approach in aiding species delimitation, and examines the correspondence between current species boundaries and sequence clusters designated by the BIN system. Sequences were obtained from 730 specimens, representing 274 species (43%) from the North American herpetofauna. Mean intraspecific divergences were 1% and 3%, while average congeneric sequence divergences were 16% and 14% in amphibians and reptiles, respectively. BIN assignments corresponded with current species boundaries in 79% of amphibians, 100% of turtles, and 60% of squamates. Deep divergences (>2%) were noted in 35% of squamate and 16% of amphibian species, and low divergences (<2%) occurred in 12% of reptiles and 23% of amphibians, patterns reflected in BIN assignments. Sequence recovery declined with specimen age, and variation in recovery success was noted among collections. Within collections, barcodes effectively flagged seven mislabeled tissues, and barcode fragments were recovered from five formalin-fixed specimens. This study demonstrates that DNA barcodes can effectively flag errors in museum collections, while BIN splits and merges reveal taxa belonging to deeply diverged or hybridizing lineages. This study is the first effort to compile a reference library of DNA barcodes for herpetofauna on a continental scale.

Assessing DNA Barcodes for Species Identification in North American Reptiles and Amphibians in Natural History Collections

PubMed Central

Chambers, E. Anne; Hebert, Paul D. N.

2016-01-01

Background High rates of species discovery and loss have led to the urgent need for more rapid assessment of species diversity in the herpetofauna. DNA barcoding allows for the preliminary identification of species based on sequence divergence. Prior DNA barcoding work on reptiles and amphibians has revealed higher biodiversity counts than previously estimated due to cases of cryptic and undiscovered species. Past studies have provided DNA barcodes for just 14% of the North American herpetofauna, revealing the need for expanded coverage. Methodology/Principal Findings This study extends the DNA barcode reference library for North American herpetofauna, assesses the utility of this approach in aiding species delimitation, and examines the correspondence between current species boundaries and sequence clusters designated by the BIN system. Sequences were obtained from 730 specimens, representing 274 species (43%) from the North American herpetofauna. Mean intraspecific divergences were 1% and 3%, while average congeneric sequence divergences were 16% and 14% in amphibians and reptiles, respectively. BIN assignments corresponded with current species boundaries in 79% of amphibians, 100% of turtles, and 60% of squamates. Deep divergences (>2%) were noted in 35% of squamate and 16% of amphibian species, and low divergences (<2%) occurred in 12% of reptiles and 23% of amphibians, patterns reflected in BIN assignments. Sequence recovery declined with specimen age, and variation in recovery success was noted among collections. Within collections, barcodes effectively flagged seven mislabeled tissues, and barcode fragments were recovered from five formalin-fixed specimens. Conclusions/Significance This study demonstrates that DNA barcodes can effectively flag errors in museum collections, while BIN splits and merges reveal taxa belonging to deeply diverged or hybridizing lineages. This study is the first effort to compile a reference library of DNA barcodes for herpetofauna on a continental scale. PMID:27116180

Verifying Digital Components of Physical Systems: Experimental Evaluation of Test Quality

NASA Astrophysics Data System (ADS)

Laputenko, A. V.; López, J. E.; Yevtushenko, N. V.

2018-03-01

This paper continues the study of high quality test derivation for verifying digital components which are used in various physical systems; those are sensors, data transfer components, etc. We have used logic circuits b01-b010 of the package of ITC'99 benchmarks (Second Release) for experimental evaluation which as stated before, describe digital components of physical systems designed for various applications. Test sequences are derived for detecting the most known faults of the reference logic circuit using three different approaches to test derivation. Three widely used fault types such as stuck-at-faults, bridges, and faults which slightly modify the behavior of one gate are considered as possible faults of the reference behavior. The most interesting test sequences are short test sequences that can provide appropriate guarantees after testing, and thus, we experimentally study various approaches to the derivation of the so-called complete test suites which detect all fault types. In the first series of experiments, we compare two approaches for deriving complete test suites. In the first approach, a shortest test sequence is derived for testing each fault. In the second approach, a test sequence is pseudo-randomly generated by the use of an appropriate software for logic synthesis and verification (ABC system in our study) and thus, can be longer. However, after deleting sequences detecting the same set of faults, a test suite returned by the second approach is shorter. The latter underlines the fact that in many cases it is useless to spend `time and efforts' for deriving a shortest distinguishing sequence; it is better to use the test minimization afterwards. The performed experiments also show that the use of only randomly generated test sequences is not very efficient since such sequences do not detect all the faults of any type. After reaching the fault coverage around 70%, saturation is observed, and the fault coverage cannot be increased anymore. For deriving high quality short test suites, the approach that is the combination of randomly generated sequences together with sequences which are aimed to detect faults not detected by random tests, allows to reach the good fault coverage using shortest test sequences.

Analysis of Illumina Microbial Assemblies

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

Clum, Alicia; Foster, Brian; Froula, Jeff

2010-05-28

Since the emerging of second generation sequencing technologies, the evaluation of different sequencing approaches and their assembly strategies for different types of genomes has become an important undertaken. Next generation sequencing technologies dramatically increase sequence throughput while decreasing cost, making them an attractive tool for whole genome shotgun sequencing. To compare different approaches for de-novo whole genome assembly, appropriate tools and a solid understanding of both quantity and quality of the underlying sequence data are crucial. Here, we performed an in-depth analysis of short-read Illumina sequence assembly strategies for bacterial and archaeal genomes. Different types of Illumina libraries as wellmore » as different trim parameters and assemblers were evaluated. Results of the comparative analysis and sequencing platforms will be presented. The goal of this analysis is to develop a cost-effective approach for the increased throughput of the generation of high quality microbial genomes.« less

"Polymeromics": Mass spectrometry based strategies in polymer science toward complete sequencing approaches: a review.

PubMed

Altuntaş, Esra; Schubert, Ulrich S

2014-01-15

Mass spectrometry (MS) is the most versatile and comprehensive method in "OMICS" sciences (i.e. in proteomics, genomics, metabolomics and lipidomics). The applications of MS and tandem MS (MS/MS or MS(n)) provide sequence information of the full complement of biological samples in order to understand the importance of the sequences on their precise and specific functions. Nowadays, the control of polymer sequences and their accurate characterization is one of the significant challenges of current polymer science. Therefore, a similar approach can be very beneficial for characterizing and understanding the complex structures of synthetic macromolecules. MS-based strategies allow a relatively precise examination of polymeric structures (e.g. their molar mass distributions, monomer units, side chain substituents, end-group functionalities, and copolymer compositions). Moreover, tandem MS offer accurate structural information from intricate macromolecular structures; however, it produces vast amount of data to interpret. In "OMICS" sciences, the software application to interpret the obtained data has developed satisfyingly (e.g. in proteomics), because it is not possible to handle the amount of data acquired via (tandem) MS studies on the biological samples manually. It can be expected that special software tools will improve the interpretation of (tandem) MS output from the investigations of synthetic polymers as well. Eventually, the MS/MS field will also open up for polymer scientists who are not MS-specialists. In this review, we dissect the overall framework of the MS and MS/MS analysis of synthetic polymers into its key components. We discuss the fundamentals of polymer analyses as well as recent advances in the areas of tandem mass spectrometry, software developments, and the overall future perspectives on the way to polymer sequencing, one of the last Holy Grail in polymer science. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Core Genome Multilocus Sequence Typing Scheme for High-Resolution Typing of Enterococcus faecium

PubMed Central

de Been, Mark; Pinholt, Mette; Top, Janetta; Bletz, Stefan; van Schaik, Willem; Brouwer, Ellen; Rogers, Malbert; Kraat, Yvette; Bonten, Marc; Corander, Jukka; Westh, Henrik; Harmsen, Dag

2015-01-01

Enterococcus faecium, a common inhabitant of the human gut, has emerged in the last 2 decades as an important multidrug-resistant nosocomial pathogen. Since the start of the 21st century, multilocus sequence typing (MLST) has been used to study the molecular epidemiology of E. faecium. However, due to the use of a small number of genes, the resolution of MLST is limited. Whole-genome sequencing (WGS) now allows for high-resolution tracing of outbreaks, but current WGS-based approaches lack standardization, rendering them less suitable for interlaboratory prospective surveillance. To overcome this limitation, we developed a core genome MLST (cgMLST) scheme for E. faecium. cgMLST transfers genome-wide single nucleotide polymorphism (SNP) diversity into a standardized and portable allele numbering system that is far less computationally intensive than SNP-based analysis of WGS data. The E. faecium cgMLST scheme was built using 40 genome sequences that represented the diversity of the species. The scheme consists of 1,423 cgMLST target genes. To test the performance of the scheme, we performed WGS analysis of 103 outbreak isolates from five different hospitals in the Netherlands, Denmark, and Germany. The cgMLST scheme performed well in distinguishing between epidemiologically related and unrelated isolates, even between those that had the same sequence type (ST), which denotes the higher discriminatory power of this cgMLST scheme over that of conventional MLST. We also show that in terms of resolution, the performance of the E. faecium cgMLST scheme is equivalent to that of an SNP-based approach. In conclusion, the cgMLST scheme developed in this study facilitates rapid, standardized, and high-resolution tracing of E. faecium outbreaks. PMID:26400782

The role of MRI in axillary lymph node imaging in breast cancer patients: a systematic review.

PubMed

Kuijs, V J L; Moossdorff, M; Schipper, R J; Beets-Tan, R G H; Heuts, E M; Keymeulen, K B M I; Smidt, M L; Lobbes, M B I

2015-04-01

To assess whether MRI can exclude axillary lymph node metastasis, potentially replacing sentinel lymph node biopsy (SLNB), and consequently eliminating the risk of SLNB-associated morbidity. PubMed, Cochrane, Medline and Embase databases were searched for relevant publications up to July 2014. Studies were selected based on predefined inclusion and exclusion criteria and independently assessed by two reviewers using a standardised extraction form. Sixteen eligible studies were selected from 1,372 publications identified by the search. A dedicated axillary protocol [sensitivity 84.7 %, negative predictive value (NPV) 95.0 %] was superior to a standard protocol covering both the breast and axilla simultaneously (sensitivity 82.0 %, NPV 82.6 %). Dynamic, contrast-enhanced MRI had a lower median sensitivity (60.0 %) and NPV (80.0 %) compared to non-enhanced T1w/T2w sequences (88.4, 94.7 %), diffusion-weighted imaging (84.2, 90.6 %) and ultrasmall superparamagnetic iron oxide (USPIO)- enhanced T2*w sequences (83.0, 95.9 %). The most promising results seem to be achievable when using non-enhanced T1w/T2w and USPIO-enhanced T2*w sequences in combination with a dedicated axillary protocol (sensitivity 84.7 % and NPV 95.0 %). The diagnostic performance of some MRI protocols for excluding axillary lymph node metastases approaches the NPV needed to replace SLNB. However, current observations are based on studies with heterogeneous study designs and limited populations. • Some axillary MRI protocols approach the NPV of an SLNB procedure. • Dedicated axillary MRI is more accurate than protocols also covering the breast. • T1w/T2w protocols combined with USPIO-enhanced sequences are the most promising sequences.

Soup to Tree: The Phylogeny of Beetles Inferred by Mitochondrial Metagenomics of a Bornean Rainforest Sample.

PubMed

Crampton-Platt, Alex; Timmermans, Martijn J T N; Gimmel, Matthew L; Kutty, Sujatha Narayanan; Cockerill, Timothy D; Vun Khen, Chey; Vogler, Alfried P

2015-09-01

In spite of the growth of molecular ecology, systematics and next-generation sequencing, the discovery and analysis of diversity is not currently integrated with building the tree-of-life. Tropical arthropod ecologists are well placed to accelerate this process if all specimens obtained through mass-trapping, many of which will be new species, could be incorporated routinely into phylogeny reconstruction. Here we test a shotgun sequencing approach, whereby mitochondrial genomes are assembled from complex ecological mixtures through mitochondrial metagenomics, and demonstrate how the approach overcomes many of the taxonomic impediments to the study of biodiversity. DNA from approximately 500 beetle specimens, originating from a single rainforest canopy fogging sample from Borneo, was pooled and shotgun sequenced, followed by de novo assembly of complete and partial mitogenomes for 175 species. The phylogenetic tree obtained from this local sample was highly similar to that from existing mitogenomes selected for global coverage of major lineages of Coleoptera. When all sequences were combined only minor topological changes were induced against this reference set, indicating an increasingly stable estimate of coleopteran phylogeny, while the ecological sample expanded the tip-level representation of several lineages. Robust trees generated from ecological samples now enable an evolutionary framework for ecology. Meanwhile, the inclusion of uncharacterized samples in the tree-of-life rapidly expands taxon and biogeographic representation of lineages without morphological identification. Mitogenomes from shotgun sequencing of unsorted environmental samples and their associated metadata, placed robustly into the phylogenetic tree, constitute novel DNA "superbarcodes" for testing hypotheses regarding global patterns of diversity. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Core Genome Multilocus Sequence Typing Scheme for High- Resolution Typing of Enterococcus faecium.

PubMed

de Been, Mark; Pinholt, Mette; Top, Janetta; Bletz, Stefan; Mellmann, Alexander; van Schaik, Willem; Brouwer, Ellen; Rogers, Malbert; Kraat, Yvette; Bonten, Marc; Corander, Jukka; Westh, Henrik; Harmsen, Dag; Willems, Rob J L

2015-12-01

Enterococcus faecium, a common inhabitant of the human gut, has emerged in the last 2 decades as an important multidrug-resistant nosocomial pathogen. Since the start of the 21st century, multilocus sequence typing (MLST) has been used to study the molecular epidemiology of E. faecium. However, due to the use of a small number of genes, the resolution of MLST is limited. Whole-genome sequencing (WGS) now allows for high-resolution tracing of outbreaks, but current WGS-based approaches lack standardization, rendering them less suitable for interlaboratory prospective surveillance. To overcome this limitation, we developed a core genome MLST (cgMLST) scheme for E. faecium. cgMLST transfers genome-wide single nucleotide polymorphism(SNP) diversity into a standardized and portable allele numbering system that is far less computationally intensive than SNP-based analysis of WGS data. The E. faecium cgMLST scheme was built using 40 genome sequences that represented the diversity of the species. The scheme consists of 1,423 cgMLST target genes. To test the performance of the scheme, we performed WGS analysis of 103 outbreak isolates from five different hospitals in the Netherlands, Denmark, and Germany. The cgMLST scheme performed well in distinguishing between epidemiologically related and unrelated isolates, even between those that had the same sequence type (ST), which denotes the higher discriminatory power of this cgMLST scheme over that of conventional MLST. We also show that in terms of resolution, the performance of the E. faecium cgMLST scheme is equivalent to that of an SNP-based approach. In conclusion, the cgMLST scheme developed in this study facilitates rapid, standardized, and high-resolution tracing of E. faecium outbreaks.

Multiplex electrochemical DNA platform for femtomolar-level quantification of genetically modified soybean.

PubMed

Manzanares-Palenzuela, C Lorena; de-Los-Santos-Álvarez, Noemí; Lobo-Castañón, María Jesús; López-Ruiz, Beatriz

2015-06-15

Current EU regulations on the mandatory labeling of genetically modified organisms (GMOs) with a minimum content of 0.9% would benefit from the availability of reliable and rapid methods to detect and quantify DNA sequences specific for GMOs. Different genosensors have been developed to this aim, mainly intended for GMO screening. A remaining challenge, however, is the development of genosensing platforms for GMO quantification, which should be expressed as the number of event-specific DNA sequences per taxon-specific sequences. Here we report a simple and sensitive multiplexed electrochemical approach for the quantification of Roundup-Ready Soybean (RRS). Two DNA sequences, taxon (lectin) and event-specific (RR), are targeted via hybridization onto magnetic beads. Both sequences are simultaneously detected by performing the immobilization, hybridization and labeling steps in a single tube and parallel electrochemical readout. Hybridization is performed in a sandwich format using signaling probes labeled with fluorescein isothiocyanate (FITC) or digoxigenin (Dig), followed by dual enzymatic labeling using Fab fragments of anti-Dig and anti-FITC conjugated to peroxidase or alkaline phosphatase, respectively. Electrochemical measurement of the enzyme activity is finally performed on screen-printed carbon electrodes. The assay gave a linear range of 2-250 pM for both targets, with LOD values of 650 fM (160 amol) and 190 fM (50 amol) for the event-specific and the taxon-specific targets, respectively. Results indicate that the method could be applied for GMO quantification below the European labeling threshold level (0.9%), offering a general approach for the rapid quantification of specific GMO events in foods. Copyright © 2015 Elsevier B.V. All rights reserved.

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

PubMed Central

Freilich, Shiri; Goldovsky, Leon; Gottlieb, Assaf; Blanc, Eric; Tsoka, Sophia; Ouzounis, Christos A

2009-01-01

Background Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present rank-BLAST, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database. Results The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples. Conclusion Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples. PMID:19860884

Fast alignment-free sequence comparison using spaced-word frequencies.

PubMed

Leimeister, Chris-Andre; Boden, Marcus; Horwege, Sebastian; Lindner, Sebastian; Morgenstern, Burkhard

2014-07-15

Alignment-free methods for sequence comparison are increasingly used for genome analysis and phylogeny reconstruction; they circumvent various difficulties of traditional alignment-based approaches. In particular, alignment-free methods are much faster than pairwise or multiple alignments. They are, however, less accurate than methods based on sequence alignment. Most alignment-free approaches work by comparing the word composition of sequences. A well-known problem with these methods is that neighbouring word matches are far from independent. To reduce the statistical dependency between adjacent word matches, we propose to use 'spaced words', defined by patterns of 'match' and 'don't care' positions, for alignment-free sequence comparison. We describe a fast implementation of this approach using recursive hashing and bit operations, and we show that further improvements can be achieved by using multiple patterns instead of single patterns. To evaluate our approach, we use spaced-word frequencies as a basis for fast phylogeny reconstruction. Using real-world and simulated sequence data, we demonstrate that our multiple-pattern approach produces better phylogenies than approaches relying on contiguous words. Our program is freely available at http://spaced.gobics.de/. © The Author 2014. Published by Oxford University Press.

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

NASA Astrophysics Data System (ADS)

Chaudhari, Rajan; Heim, Andrew J.; Li, Zhijun

2015-05-01

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.

A knowledge engineering approach to recognizing and extracting sequences of nucleic acids from scientific literature.

PubMed

García-Remesal, Miguel; Maojo, Victor; Crespo, José

2010-01-01

In this paper we present a knowledge engineering approach to automatically recognize and extract genetic sequences from scientific articles. To carry out this task, we use a preliminary recognizer based on a finite state machine to extract all candidate DNA/RNA sequences. The latter are then fed into a knowledge-based system that automatically discards false positives and refines noisy and incorrectly merged sequences. We created the knowledge base by manually analyzing different manuscripts containing genetic sequences. Our approach was evaluated using a test set of 211 full-text articles in PDF format containing 3134 genetic sequences. For such set, we achieved 87.76% precision and 97.70% recall respectively. This method can facilitate different research tasks. These include text mining, information extraction, and information retrieval research dealing with large collections of documents containing genetic sequences.

Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics.

PubMed

Marchand, Jérémy; Martineau, Estelle; Guitton, Yann; Dervilly-Pinel, Gaud; Giraudeau, Patrick

2017-02-01

Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mean-field approaches to the totally asymmetric exclusion process with quenched disorder and large particles

NASA Astrophysics Data System (ADS)

Shaw, Leah B.; Sethna, James P.; Lee, Kelvin H.

2004-08-01

The process of protein synthesis in biological systems resembles a one-dimensional driven lattice gas in which the particles (ribosomes) have spatial extent, covering more than one lattice site. Realistic, nonuniform gene sequences lead to quenched disorder in the particle hopping rates. We study the totally asymmetric exclusion process with large particles and quenched disorder via several mean-field approaches and compare the mean-field results with Monte Carlo simulations. Mean-field equations obtained from the literature are found to be reasonably effective in describing this system. A numerical technique is developed for computing the particle current rapidly. The mean-field approach is extended to include two-point correlations between adjacent sites. The two-point results are found to match Monte Carlo simulations more closely.

Improving membrane protein expression by optimizing integration efficiency

PubMed Central

2017-01-01

The heterologous overexpression of integral membrane proteins in Escherichia coli often yields insufficient quantities of purifiable protein for applications of interest. The current study leverages a recently demonstrated link between co-translational membrane integration efficiency and protein expression levels to predict protein sequence modifications that improve expression. Membrane integration efficiencies, obtained using a coarse-grained simulation approach, robustly predicted effects on expression of the integral membrane protein TatC for a set of 140 sequence modifications, including loop-swap chimeras and single-residue mutations distributed throughout the protein sequence. Mutations that improve simulated integration efficiency were 4-fold enriched with respect to improved experimentally observed expression levels. Furthermore, the effects of double mutations on both simulated integration efficiency and experimentally observed expression levels were cumulative and largely independent, suggesting that multiple mutations can be introduced to yield higher levels of purifiable protein. This work provides a foundation for a general method for the rational overexpression of integral membrane proteins based on computationally simulated membrane integration efficiencies. PMID:28918393

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation.

PubMed

Schlötterer, C; Kofler, R; Versace, E; Tobler, R; Franssen, S U

2015-05-01

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype-phenotype link and serve as an important research tool for a broad range of evolutionary questions.

SA-Search: a web tool for protein structure mining based on a Structural Alphabet

PubMed Central

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-01-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search. PMID:15215446

SA-Search: a web tool for protein structure mining based on a Structural Alphabet.

PubMed

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-07-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search.

Social and behavioral research in genomic sequencing: approaches from the Clinical Sequencing Exploratory Research Consortium Outcomes and Measures Working Group.

PubMed

Gray, Stacy W; Martins, Yolanda; Feuerman, Lindsay Z; Bernhardt, Barbara A; Biesecker, Barbara B; Christensen, Kurt D; Joffe, Steven; Rini, Christine; Veenstra, David; McGuire, Amy L

2014-10-01

The routine use of genomic sequencing in clinical medicine has the potential to dramatically alter patient care and medical outcomes. To fully understand the psychosocial and behavioral impact of sequencing integration into clinical practice, it is imperative that we identify the factors that influence sequencing-related decision making and patient outcomes. In an effort to develop a collaborative and conceptually grounded approach to studying sequencing adoption, members of the National Human Genome Research Institute's Clinical Sequencing Exploratory Research Consortium formed the Outcomes and Measures Working Group. Here we highlight the priority areas of investigation and psychosocial and behavioral outcomes identified by the Working Group. We also review some of the anticipated challenges to measurement in social and behavioral research related to genomic sequencing; opportunities for instrument development; and the importance of qualitative, quantitative, and mixed-method approaches. This work represents the early, shared efforts of multiple research teams as we strive to understand individuals' experiences with genomic sequencing. The resulting body of knowledge will guide recommendations for the optimal use of sequencing in clinical practice.

SACCHARIS: an automated pipeline to streamline discovery of carbohydrate active enzyme activities within polyspecific families and de novo sequence datasets.

PubMed

Jones, Darryl R; Thomas, Dallas; Alger, Nicholas; Ghavidel, Ata; Inglis, G Douglas; Abbott, D Wade

2018-01-01

Deposition of new genetic sequences in online databases is expanding at an unprecedented rate. As a result, sequence identification continues to outpace functional characterization of carbohydrate active enzymes (CAZymes). In this paradigm, the discovery of enzymes with novel functions is often hindered by high volumes of uncharacterized sequences particularly when the enzyme sequence belongs to a family that exhibits diverse functional specificities (i.e., polyspecificity). Therefore, to direct sequence-based discovery and characterization of new enzyme activities we have developed an automated in silico pipeline entitled: Sequence Analysis and Clustering of CarboHydrate Active enzymes for Rapid Informed prediction of Specificity (SACCHARIS). This pipeline streamlines the selection of uncharacterized sequences for discovery of new CAZyme or CBM specificity from families currently maintained on the CAZy website or within user-defined datasets. SACCHARIS was used to generate a phylogenetic tree of a GH43, a CAZyme family with defined subfamily designations. This analysis confirmed that large datasets can be organized into sequence clusters of manageable sizes that possess related functions. Seeding this tree with a GH43 sequence from Bacteroides dorei DSM 17855 (BdGH43b, revealed it partitioned as a single sequence within the tree. This pattern was consistent with it possessing a unique enzyme activity for GH43 as BdGH43b is the first described α-glucanase described for this family. The capacity of SACCHARIS to extract and cluster characterized carbohydrate binding module sequences was demonstrated using family 6 CBMs (i.e., CBM6s). This CBM family displays a polyspecific ligand binding profile and contains many structurally determined members. Using SACCHARIS to identify a cluster of divergent sequences, a CBM6 sequence from a unique clade was demonstrated to bind yeast mannan, which represents the first description of an α-mannan binding CBM. Additionally, we have performed a CAZome analysis of an in-house sequenced bacterial genome and a comparative analysis of B. thetaiotaomicron VPI-5482 and B. thetaiotaomicron 7330, to demonstrate that SACCHARIS can generate "CAZome fingerprints", which differentiate between the saccharolytic potential of two related strains in silico. Establishing sequence-function and sequence-structure relationships in polyspecific CAZyme families are promising approaches for streamlining enzyme discovery. SACCHARIS facilitates this process by embedding CAZyme and CBM family trees generated from biochemically to structurally characterized sequences, with protein sequences that have unknown functions. In addition, these trees can be integrated with user-defined datasets (e.g., genomics, metagenomics, and transcriptomics) to inform experimental characterization of new CAZymes or CBMs not currently curated, and for researchers to compare differential sequence patterns between entire CAZomes. In this light, SACCHARIS provides an in silico tool that can be tailored for enzyme bioprospecting in datasets of increasing complexity and for diverse applications in glycobiotechnology.

Mapping Base Modifications in DNA by Transverse-Current Sequencing

NASA Astrophysics Data System (ADS)

Alvarez, Jose R.; Skachkov, Dmitry; Massey, Steven E.; Kalitsov, Alan; Velev, Julian P.

2018-02-01

Sequencing DNA modifications and lesions, such as methylation of cytosine and oxidation of guanine, is even more important and challenging than sequencing the genome itself. The traditional methods for detecting DNA modifications are either insensitive to these modifications or require additional processing steps to identify a particular type of modification. Transverse-current sequencing in nanopores can potentially identify the canonical bases and base modifications in the same run. In this work, we demonstrate that the most common DNA epigenetic modifications and lesions can be detected with any predefined accuracy based on their tunneling current signature. Our results are based on simulations of the nanopore tunneling current through DNA molecules, calculated using nonequilibrium electron-transport methodology within an effective multiorbital model derived from first-principles calculations, followed by a base-calling algorithm accounting for neighbor current-current correlations. This methodology can be integrated with existing experimental techniques to improve base-calling fidelity.

Feasibility of physical map construction from fingerprinted bacterial artificial chromosome libraries of polyploid plant species

PubMed Central

2010-01-01

Background The presence of closely related genomes in polyploid species makes the assembly of total genomic sequence from shotgun sequence reads produced by the current sequencing platforms exceedingly difficult, if not impossible. Genomes of polyploid species could be sequenced following the ordered-clone sequencing approach employing contigs of bacterial artificial chromosome (BAC) clones and BAC-based physical maps. Although BAC contigs can currently be constructed for virtually any diploid organism with the SNaPshot high-information-content-fingerprinting (HICF) technology, it is currently unknown if this is also true for polyploid species. It is possible that BAC clones from orthologous regions of homoeologous chromosomes would share numerous restriction fragments and be therefore included into common contigs. Because of this and other concerns, physical mapping utilizing the SNaPshot HICF of BAC libraries of polyploid species has not been pursued and the possibility of doing so has not been assessed. The sole exception has been in common wheat, an allohexaploid in which it is possible to construct single-chromosome or single-chromosome-arm BAC libraries from DNA of flow-sorted chromosomes and bypass the obstacles created by polyploidy. Results The potential of the SNaPshot HICF technology for physical mapping of polyploid plants utilizing global BAC libraries was evaluated by assembling contigs of fingerprinted clones in an in silico merged BAC library composed of single-chromosome libraries of two wheat homoeologous chromosome arms, 3AS and 3DS, and complete chromosome 3B. Because the chromosome arm origin of each clone was known, it was possible to estimate the fidelity of contig assembly. On average 97.78% or more clones, depending on the library, were from a single chromosome arm. A large portion of the remaining clones was shown to be library contamination from other chromosomes, a feature that is unavoidable during the construction of single-chromosome BAC libraries. Conclusions The negligibly low level of incorporation of clones from homoeologous chromosome arms into a contig during contig assembly suggested that it is feasible to construct contigs and physical maps using global BAC libraries of wheat and almost certainly also of other plant polyploid species with genome sizes comparable to that of wheat. Because of the high purity of the resulting assembled contigs, they can be directly used for genome sequencing. It is currently unknown but possible that equally good BAC contigs can be also constructed for polyploid species containing smaller, more gene-rich genomes. PMID:20170511

Applying Agrep to r-NSA to solve multiple sequences approximate matching.

PubMed

Ni, Bing; Wong, Man-Hon; Lam, Chi-Fai David; Leung, Kwong-Sak

2014-01-01

This paper addresses the approximate matching problem in a database consisting of multiple DNA sequences, where the proposed approach applies Agrep to a new truncated suffix array, r-NSA. The construction time of the structure is linear to the database size, and the computations of indexing a substring in the structure are constant. The number of characters processed in applying Agrep is analysed theoretically, and the theoretical upper-bound can approximate closely the empirical number of characters, which is obtained through enumerating the characters in the actual structure built. Experiments are carried out using (synthetic) random DNA sequences, as well as (real) genome sequences including Hepatitis-B Virus and X-chromosome. Experimental results show that, compared to the straight-forward approach that applies Agrep to multiple sequences individually, the proposed approach solves the matching problem in much shorter time. The speed-up of our approach depends on the sequence patterns, and for highly similar homologous genome sequences, which are the common cases in real-life genomes, it can be up to several orders of magnitude.

The Status, Quality, and Expansion of the NIH Full-Length cDNA Project: The Mammalian Gene Collection (MGC)

PubMed Central

2004-01-01

The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5′-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline. PMID:15489334

Early Miocene sequence development across the New Jersey margin

USGS Publications Warehouse

Monteverde, D.H.; Mountain, Gregory S.; Miller, K.G.

2008-01-01

Sequence stratigraphy provides an understanding of the interplay between eustasy, sediment supply and accommodation in the sedimentary construction of passive margins. We used this approach to follow the early to middle Miocene growth of the New Jersey margin and analyse the connection between relative changes of sea level and variable sediment supply. Eleven candidate sequence boundaries were traced in high-resolution multi-channel seismic profiles across the inner margin and matched to geophysical log signatures and lithologic changes in ODP Leg 150X onshore coreholes. Chronologies at these drill sites were then used to assign ages to the intervening seismic sequences. We conclude that the regional and global correlation of early Miocene sequences suggests a dominant role of global sea-level change but margin progradation was controlled by localized sediment contribution and that local conditions played a large role in sequence formation and preservation. Lowstand deposits were regionally restricted and their locations point to both single and multiple sediment sources. The distribution of highstand deposits, by contrast, documents redistribution by along shelf currents. We find no evidence that sea level fell below the elevation of the clinoform rollover, and the existence of extensive lowstand deposits seaward of this inflection point indicates efficient cross-shelf sediment transport mechanisms despite the apparent lack of well-developed fluvial drainage. ?? 2008 The Authors. Journal compilation ?? 2008 Blackwell Publishing.

Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.

A novel multi-locus sequence typing (MLST) protocol for Leuconostoc lactis isolates from traditional dairy products in China and Mongolia.

PubMed

Dan, Tong; Liu, Wenjun; Sun, Zhihong; Lv, Qiang; Xu, Haiyan; Song, Yuqin; Zhang, Heping

2014-06-09

Economically, Leuconostoc lactis is one of the most important species in the genus Leuconostoc. It plays an important role in the food industry including the production of dextrans and bacteriocins. Currently, traditional molecular typing approaches for characterisation of this species at the isolate level are either unavailable or are not sufficiently reliable for practical use. Multilocus sequence typing (MLST) is a robust and reliable method for characterising bacterial and fungal species at the molecular level. In this study, a novel MLST protocol was developed for 50 L. lactis isolates from Mongolia and China. Sequences from eight targeted genes (groEL, carB, recA, pheS, murC, pyrG, rpoB and uvrC) were obtained. Sequence analysis indicated 20 different sequence types (STs), with 13 of them being represented by a single isolate. Phylogenetic analysis based on the sequences of eight MLST loci indicated that the isolates belonged to two major groups, A (34 isolates) and B (16 isolates). Linkage disequilibrium analyses indicated that recombination occurred at a low frequency in L. lactis, indicating a clonal population structure. Split-decomposition analysis indicated that intraspecies recombination played a role in generating genotypic diversity amongst isolates. Our results indicated that MLST is a valuable tool for typing L. lactis isolates that can be used for further monitoring of evolutionary changes and population genetics.

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

Comprehensive comparison of three commercial human whole-exome capture platforms.

PubMed

Asan; Xu, Yu; Jiang, Hui; Tyler-Smith, Chris; Xue, Yali; Jiang, Tao; Wang, Jiawei; Wu, Mingzhi; Liu, Xiao; Tian, Geng; Wang, Jun; Wang, Jian; Yang, Huangming; Zhang, Xiuqing

2011-09-28

Exome sequencing, which allows the global analysis of protein coding sequences in the human genome, has become an effective and affordable approach to detecting causative genetic mutations in diseases. Currently, there are several commercial human exome capture platforms; however, the relative performances of these have not been characterized sufficiently to know which is best for a particular study. We comprehensively compared three platforms: NimbleGen's Sequence Capture Array and SeqCap EZ, and Agilent's SureSelect. We assessed their performance in a variety of ways, including number of genes covered and capture efficacy. Differences that may impact on the choice of platform were that Agilent SureSelect covered approximately 1,100 more genes, while NimbleGen provided better flanking sequence capture. Although all three platforms achieved similar capture specificity of targeted regions, the NimbleGen platforms showed better uniformity of coverage and greater genotype sensitivity at 30- to 100-fold sequencing depth. All three platforms showed similar power in exome SNP calling, including medically relevant SNPs. Compared with genotyping and whole-genome sequencing data, the three platforms achieved a similar accuracy of genotype assignment and SNP detection. Importantly, all three platforms showed similar levels of reproducibility, GC bias and reference allele bias. We demonstrate key differences between the three platforms, particularly advantages of solutions over array capture and the importance of a large gene target set.

Propellant Depots: The Future of Space Exploration

NASA Astrophysics Data System (ADS)

Crenwelge, Drew

NASA is currently exploring several options for mankind's return to the lunar surface and beyond. The selected option must stimulate both commercial and international involvement, support future missions to the Moon and other destinations, and above all, fit within the current budget profile. Contrary to the current Constellation approach, this paper describes the option of using an in-space propellant depot architecture that can refuel or top-off visiting vehicles at EML1, and how it fits within NASA's new space exploration criteria. In addition to receiving and transferring fuel, the propellant depot will also provide cryogenic propellant storage and management that utilizes flight proven technologies in conjunction with technologies currently under development. The propellant depot system, propellant management and acquisition devices, thermodynamic analysis, and key enabling technologies are also discussed. Depot design concepts along with an overview of a future lunar mission sequence are also presented.

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

PubMed

Schwessinger, Ron; Suciu, Maria C; McGowan, Simon J; Telenius, Jelena; Taylor, Stephen; Higgs, Doug R; Hughes, Jim R

2017-10-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k -mer-based analysis of DNase footprints to determine any k -mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. © 2017 Schwessinger et al.; Published by Cold Spring Harbor Laboratory Press.

Robust temporal alignment of multimodal cardiac sequences

NASA Astrophysics Data System (ADS)

Perissinotto, Andrea; Queirós, Sandro; Morais, Pedro; Baptista, Maria J.; Monaghan, Mark; Rodrigues, Nuno F.; D'hooge, Jan; Vilaça, João. L.; Barbosa, Daniel

2015-03-01

Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized cross-correlation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates different temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1.6 +/- 1.9% and 4.0 +/- 4.2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.

Sequences of 95 human MHC haplotypes reveal extreme coding variation in genes other than highly polymorphic HLA class I and II

PubMed Central

Norman, Paul J.; Norberg, Steven J.; Guethlein, Lisbeth A.; Nemat-Gorgani, Neda; Royce, Thomas; Wroblewski, Emily E.; Dunn, Tamsen; Mann, Tobias; Alicata, Claudia; Hollenbach, Jill A.; Chang, Weihua; Shults Won, Melissa; Gunderson, Kevin L.; Abi-Rached, Laurent; Ronaghi, Mostafa; Parham, Peter

2017-01-01

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B. It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome. PMID:28360230

Icing: Accretion, Detection, Protection

NASA Technical Reports Server (NTRS)

Reinmann, John J.

1994-01-01

The global aircraft industry and its regulatory agencies are currently involved in three major icing efforts: ground icing; advanced technologies for in-flight icing; and tailplane icing. These three major icing topics correspondingly support the three major segments of any aircraft flight profile: takeoff; cruise and hold; and approach and land. This lecture addressess these three topics in the same sequence as they appear in flight, starting with ground deicing, followed by advanced technologies for in-flight ice protection, and ending with tailplane icing.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

PubMed Central

Lindén, Henrik; Lansner, Anders

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison. PMID:27213810

Strategic cognitive sequencing: a computational cognitive neuroscience approach.

PubMed

Herd, Seth A; Krueger, Kai A; Kriete, Trenton E; Huang, Tsung-Ren; Hazy, Thomas E; O'Reilly, Randall C

2013-01-01

We address strategic cognitive sequencing, the "outer loop" of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or "self-instruction"). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a "bridging" state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.

Identification of genomic indels and structural variations using split reads

PubMed Central

2011-01-01

Background Recent studies have demonstrated the genetic significance of insertions, deletions, and other more complex structural variants (SVs) in the human population. With the development of the next-generation sequencing technologies, high-throughput surveys of SVs on the whole-genome level have become possible. Here we present split-read identification, calibrated (SRiC), a sequence-based method for SV detection. Results We start by mapping each read to the reference genome in standard fashion using gapped alignment. Then to identify SVs, we score each of the many initial mappings with an assessment strategy designed to take into account both sequencing and alignment errors (e.g. scoring more highly events gapped in the center of a read). All current SV calling methods have multilevel biases in their identifications due to both experimental and computational limitations (e.g. calling more deletions than insertions). A key aspect of our approach is that we calibrate all our calls against synthetic data sets generated from simulations of high-throughput sequencing (with realistic error models). This allows us to calculate sensitivity and the positive predictive value under different parameter-value scenarios and for different classes of events (e.g. long deletions vs. short insertions). We run our calculations on representative data from the 1000 Genomes Project. Coupling the observed numbers of events on chromosome 1 with the calibrations gleaned from the simulations (for different length events) allows us to construct a relatively unbiased estimate for the total number of SVs in the human genome across a wide range of length scales. We estimate in particular that an individual genome contains ~670,000 indels/SVs. Conclusions Compared with the existing read-depth and read-pair approaches for SV identification, our method can pinpoint the exact breakpoints of SV events, reveal the actual sequence content of insertions, and cover the whole size spectrum for deletions. Moreover, with the advent of the third-generation sequencing technologies that produce longer reads, we expect our method to be even more useful. PMID:21787423

RNAblueprint: flexible multiple target nucleic acid sequence design.

PubMed

Hammer, Stefan; Tschiatschek, Birgit; Flamm, Christoph; Hofacker, Ivo L; Findeiß, Sven

2017-09-15

Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility. We developed a C ++  library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages. RNAblueprint , Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA . s.hammer@univie.ac.at, ivo@tbi.univie.ac.at or sven@tbi.univie.ac.at. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Identification of species with DNA-based technology: current progress and challenges.

PubMed

Pereira, Filipe; Carneiro, João; Amorim, António

2008-01-01

One of the grand challenges of modern biology is to develop accurate and reliable technologies for a rapid screening of DNA sequence variation. This topic of research is of prime importance for the detection and identification of species in numerous fields of investigation, such as taxonomy, epidemiology, forensics, archaeology or ecology. Molecular identification is also central for the diagnosis, treatment and control of infections caused by different pathogens. In recent years, a variety of DNA-based approaches have been developed for the identification of individuals in a myriad of taxonomic groups. Here, we provide an overview of most commonly used assays, with emphasis on those based on DNA hybridizations, restriction enzymes, random PCR amplifications, species-specific PCR primers and DNA sequencing. A critical evaluation of all methods is presented focusing on their discriminatory power, reproducibility and user-friendliness. Having in mind that the current trend is to develop small-scale devices with a high-throughput capacity, we briefly review recent technological achievements for DNA analysis that offer great potentials for the identification of species.

Next-generation sequencing facilitates detection of the classic E13-A20 EML4-ALK fusion in an ALK-FISH/IHC inconclusive biopsy of a stage IV lung cancer patient: a case report.

PubMed

Volckmar, Anna-Lena; Endris, Volker; Bozorgmehr, Farastuk; Lier, Clemens; Porcel, Carlota; Kirchner, Martina; Leichsenring, Jonas; Penzel, Roland; Thomas, Michael; Schirmacher, Peter; Warth, Arne; Stenzinger, Albrecht

2016-11-18

Inhibition of the oncogenic fusion-gene EML4-ALK is a current first-line approach for patients with stage IV non-small cell lung cancer. While FISH was established as the gold standard for identifying these patients, there is accumulating evidence that other methods of detection, i.e., immunohistochemistry and next-generation sequencing (NGS), exist that may be equally successful. However, the concordance of these methods is under investigation. Adding to the current literature, we here report a 56 year old female never-smoker with stage IV lung adenocarcinoma whose biopsy was IHC and FISH inconclusive but positive in NGS. Retroactive profiling of the resection specimen corroborated fusion reads obtained by NGS, FISH-positivity and showed weak ALK-positivity by IHC. Consequently, we diagnosed the case as ALK-positive rendering the patient eligible to crizotinib treatment. With IHC on biopsy material only, this case would have been overlooked withholding effective therapy.

Novel Method for Reliable Identification of Siccibacter and Franconibacter Strains: from “Pseudo-Cronobacter” to New Enterobacteriaceae Genera

PubMed Central

Vlach, Jiří; Junková, Petra; Karamonová, Ludmila; Blažková, Martina; Fukal, Ladislav

2017-01-01

ABSTRACT In the last decade, strains of the genera Franconibacter and Siccibacter have been misclassified as first Enterobacter and later Cronobacter. Because Cronobacter is a serious foodborne pathogen that affects premature neonates and elderly individuals, such misidentification may not only falsify epidemiological statistics but also lead to tests of powdered infant formula or other foods giving false results. Currently, the main ways of identifying Franconibacter and Siccibacter strains are by biochemical testing or by sequencing of the fusA gene as part of Cronobacter multilocus sequence typing (MLST), but in relation to these strains the former is generally highly difficult and unreliable while the latter remains expensive. To address this, we developed a fast, simple, and most importantly, reliable method for Franconibacter and Siccibacter identification based on intact-cell matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Our method integrates the following steps: data preprocessing using mMass software; principal-component analysis (PCA) for the selection of mass spectrum fingerprints of Franconibacter and Siccibacter strains; optimization of the Biotyper database settings for the creation of main spectrum projections (MSPs). This methodology enabled us to create an in-house MALDI MS database that extends the current MALDI Biotyper database by including Franconibacter and Siccibacter strains. Finally, we verified our approach using seven previously unclassified strains, all of which were correctly identified, thereby validating our method. IMPORTANCE We show that the majority of methods currently used for the identification of Franconibacter and Siccibacter bacteria are not able to properly distinguish these strains from those of Cronobacter. While sequencing of the fusA gene as part of Cronobacter MLST remains the most reliable such method, it is highly expensive and time-consuming. Here, we demonstrate a cost-effective and reliable alternative that correctly distinguishes between Franconibacter, Siccibacter, and Cronobacter bacteria and identifies Franconibacter and Siccibacter at the species level. Using intact-cell MALDI-TOF MS, we extend the current MALDI Biotyper database with 11 Franconibacter and Siccibacter MSPs. In addition, the use of our approach is likely to lead to a more reliable identification scheme for Franconibacter and Siccibacter strains and, consequently, a more trustworthy epidemiological picture of their involvement in disease. PMID:28455327

Exploring Dance Movement Data Using Sequence Alignment Methods

PubMed Central

Chavoshi, Seyed Hossein; De Baets, Bernard; Neutens, Tijs; De Tré, Guy; Van de Weghe, Nico

2015-01-01

Despite the abundance of research on knowledge discovery from moving object databases, only a limited number of studies have examined the interaction between moving point objects in space over time. This paper describes a novel approach for measuring similarity in the interaction between moving objects. The proposed approach consists of three steps. First, we transform movement data into sequences of successive qualitative relations based on the Qualitative Trajectory Calculus (QTC). Second, sequence alignment methods are applied to measure the similarity between movement sequences. Finally, movement sequences are grouped based on similarity by means of an agglomerative hierarchical clustering method. The applicability of this approach is tested using movement data from samba and tango dancers. PMID:26181435

Label-free screening of single biomolecules through resistive pulse sensing technology for precision medicine applications

NASA Astrophysics Data System (ADS)

Harrer, S.; Kim, S. C.; Schieber, C.; Kannam, S.; Gunn, N.; Moore, S.; Scott, D.; Bathgate, R.; Skafidas, S.; Wagner, J. M.

2015-05-01

Employing integrated nano- and microfluidic circuits for detecting and characterizing biological compounds through resistive pulse sensing technology is a vibrant area of research at the interface of biotechnology and nanotechnology. Resistive pulse sensing platforms can be customized to study virtually any particle of choice which can be threaded through a fluidic channel and enable label-free single-particle interrogation with the primary read-out signal being an electric current fingerprint. The ability to perform label-free molecular screening with single-molecule and even single binding site resolution makes resistive pulse sensing technology a powerful tool for analyzing the smallest units of biological systems and how they interact with each other on a molecular level. This task is at the core of experimental systems biology and in particular ‘omics research which in combination with next-generation DNA-sequencing and next-generation drug discovery and design forms the foundation of a novel disruptive medical paradigm commonly referred to as personalized medicine or precision medicine. DNA-sequencing has approached the 1000-Dollar-Genome milestone allowing for decoding a complete human genome with unmatched speed and at low cost. Increased sequencing efficiency yields massive amounts of genomic data. Analyzing this data in combination with medical and biometric health data eventually enables understanding the pathways from individual genes to physiological functions. Access to this information triggers fundamental questions for doctors and patients alike: what are the chances of an outbreak for a specific disease? Can individual risks be managed and if so how? Which drugs are available and how should they be applied? Could a new drug be tailored to an individual’s genetic predisposition fast and in an affordable way? In order to provide answers and real-life value to patients, the rapid evolvement of novel computing approaches for analyzing big data in systems genomics has to be accompanied by an equally strong effort to develop next-generation DNA-sequencing and next-generation drug screening and design platforms. In that context lab-on-a-chip devices utilizing nanopore- and nanochannel based resistive pulse-sensing technology for DNA-sequencing and protein screening applications occupy a key role. This paper describes the status quo of resistive pulse sensing technology for these two application areas with a special focus on current technology trends and challenges ahead.

Label-free screening of single biomolecules through resistive pulse sensing technology for precision medicine applications.

PubMed

Harrer, S; Kim, S C; Schieber, C; Kannam, S; Gunn, N; Moore, S; Scott, D; Bathgate, R; Skafidas, S; Wagner, J M

2015-05-08

Employing integrated nano- and microfluidic circuits for detecting and characterizing biological compounds through resistive pulse sensing technology is a vibrant area of research at the interface of biotechnology and nanotechnology. Resistive pulse sensing platforms can be customized to study virtually any particle of choice which can be threaded through a fluidic channel and enable label-free single-particle interrogation with the primary read-out signal being an electric current fingerprint. The ability to perform label-free molecular screening with single-molecule and even single binding site resolution makes resistive pulse sensing technology a powerful tool for analyzing the smallest units of biological systems and how they interact with each other on a molecular level. This task is at the core of experimental systems biology and in particular 'omics research which in combination with next-generation DNA-sequencing and next-generation drug discovery and design forms the foundation of a novel disruptive medical paradigm commonly referred to as personalized medicine or precision medicine. DNA-sequencing has approached the 1000-Dollar-Genome milestone allowing for decoding a complete human genome with unmatched speed and at low cost. Increased sequencing efficiency yields massive amounts of genomic data. Analyzing this data in combination with medical and biometric health data eventually enables understanding the pathways from individual genes to physiological functions. Access to this information triggers fundamental questions for doctors and patients alike: what are the chances of an outbreak for a specific disease? Can individual risks be managed and if so how? Which drugs are available and how should they be applied? Could a new drug be tailored to an individual's genetic predisposition fast and in an affordable way? In order to provide answers and real-life value to patients, the rapid evolvement of novel computing approaches for analyzing big data in systems genomics has to be accompanied by an equally strong effort to develop next-generation DNA-sequencing and next-generation drug screening and design platforms. In that context lab-on-a-chip devices utilizing nanopore- and nanochannel based resistive pulse-sensing technology for DNA-sequencing and protein screening applications occupy a key role. This paper describes the status quo of resistive pulse sensing technology for these two application areas with a special focus on current technology trends and challenges ahead.

Statistical mechanics of simple models of protein folding and design.

PubMed Central

Pande, V S; Grosberg, A Y; Tanaka, T

1997-01-01

It is now believed that the primary equilibrium aspects of simple models of protein folding are understood theoretically. However, current theories often resort to rather heavy mathematics to overcome some technical difficulties inherent in the problem or start from a phenomenological model. To this end, we take a new approach in this pedagogical review of the statistical mechanics of protein folding. The benefit of our approach is a drastic mathematical simplification of the theory, without resort to any new approximations or phenomenological prescriptions. Indeed, the results we obtain agree precisely with previous calculations. Because of this simplification, we are able to present here a thorough and self contained treatment of the problem. Topics discussed include the statistical mechanics of the random energy model (REM), tests of the validity of REM as a model for heteropolymer freezing, freezing transition of random sequences, phase diagram of designed ("minimally frustrated") sequences, and the degree to which errors in the interactions employed in simulations of either folding and design can still lead to correct folding behavior. Images FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 6 PMID:9414231

Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome

PubMed Central

Chan, Robin F.; Shabalin, Andrey A.; Xie, Lin Y.; Adkins, Daniel E.; Zhao, Min; Turecki, Gustavo; Clark, Shaunna L.; Aberg, Karolina A.

2017-01-01

Abstract Methylome-wide association studies are typically performed using microarray technologies that only assay a very small fraction of the CG methylome and entirely miss two forms of methylation that are common in brain and likely of particular relevance for neuroscience and psychiatric disorders. The alternative is to use whole genome bisulfite (WGB) sequencing but this approach is not yet practically feasible with sample sizes required for adequate statistical power. We argue for revisiting methylation enrichment methods that, provided optimal protocols are used, enable comprehensive, adequately powered and cost-effective genome-wide investigations of the brain methylome. To support our claim we use data showing that enrichment methods approximate the sensitivity obtained with WGB methods and with slightly better specificity. However, this performance is achieved at <5% of the reagent costs. Furthermore, because many more samples can be sequenced simultaneously, projects can be completed about 15 times faster. Currently the only viable option available for comprehensive brain methylome studies, enrichment methods may be critical for moving the field forward. PMID:28334972

Harnessing mtDNA variation to resolve ambiguity in ‘Redfish’ sold in Europe

PubMed Central

Moore, Lauren; Pampoulie, Christophe; Di Muri, Cristina; Vandamme, Sara; Mariani, Stefano

2017-01-01

Morphology-based identification of North Atlantic Sebastes has long been controversial and misidentification may produce misleading data, with cascading consequences that negatively affect fisheries management and seafood labelling. North Atlantic Sebastes comprises of four species, commonly known as ‘redfish’, but little is known about the number, identity and labelling accuracy of redfish species sold across Europe. We used a molecular approach to identify redfish species from ‘blind’ specimens to evaluate the performance of the Barcode of Life (BOLD) and Genbank databases, as well as carrying out a market product accuracy survey from retailers across Europe. The conventional BOLD approach proved ambiguous, and phylogenetic analysis based on mtDNA control region sequences provided a higher resolution for species identification. By sampling market products from four countries, we found the presence of two species of redfish (S. norvegicus and S. mentella) and one unidentified Pacific rockfish marketed in Europe. Furthermore, public databases revealed the existence of inaccurate reference sequences, likely stemming from species misidentification from previous studies, which currently hinders the efficacy of DNA methods for the identification of Sebastes market samples. PMID:29018597

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

Electrochemical techniques on sequence-specific PCR amplicon detection for point-of-care applications.

PubMed

Luo, Xiaoteng; Hsing, I-Ming

2009-10-01

Nucleic acid based analysis provides accurate differentiation among closely affiliated species and this species- and sequence-specific detection technique would be particularly useful for point-of-care (POC) testing for prevention and early detection of highly infectious and damaging diseases. Electrochemical (EC) detection and polymerase chain reaction (PCR) are two indispensable steps, in our view, in a nucleic acid based point-of-care testing device as the former, in comparison with the fluorescence counterpart, provides inherent advantages of detection sensitivity, device miniaturization and operation simplicity, and the latter offers an effective way to boost the amount of targets to a detectable quantity. In this mini-review, we will highlight some of the interesting investigations using the combined EC detection and PCR amplification approaches for end-point detection and real-time monitoring. The promise of current approaches and the direction for future investigations will be discussed. It would be our view that the synergistic effect of the combined EC-PCR steps in a portable device provides a promising detection technology platform that will be ready for point-of-care applications in the near future.

The Genome Sequencer FLX System--longer reads, more applications, straight forward bioinformatics and more complete data sets.

PubMed

Droege, Marcus; Hill, Brendon

2008-08-31

The Genome Sequencer FLX System (GS FLX), powered by 454 Sequencing, is a next-generation DNA sequencing technology featuring a unique mix of long reads, exceptional accuracy, and ultra-high throughput. It has been proven to be the most versatile of all currently available next-generation sequencing technologies, supporting many high-profile studies in over seven applications categories. GS FLX users have pursued innovative research in de novo sequencing, re-sequencing of whole genomes and target DNA regions, metagenomics, and RNA analysis. 454 Sequencing is a powerful tool for human genetics research, having recently re-sequenced the genome of an individual human, currently re-sequencing the complete human exome and targeted genomic regions using the NimbleGen sequence capture process, and detected low-frequency somatic mutations linked to cancer.

On the Use of Diversity Measures in Longitudinal Sequencing Studies of Microbial Communities.

PubMed

Wagner, Brandie D; Grunwald, Gary K; Zerbe, Gary O; Mikulich-Gilbertson, Susan K; Robertson, Charles E; Zemanick, Edith T; Harris, J Kirk

2018-01-01

Identification of the majority of organisms present in human-associated microbial communities is feasible with the advent of high throughput sequencing technology. As substantial variability in microbiota communities is seen across subjects, the use of longitudinal study designs is important to better understand variation of the microbiome within individual subjects. Complex study designs with longitudinal sample collection require analytic approaches to account for this additional source of variability. A common approach to assessing community changes is to evaluate the change in alpha diversity (the variety and abundance of organisms in a community) over time. However, there are several commonly used alpha diversity measures and the use of different measures can result in different estimates of magnitude of change and different inferences. It has recently been proposed that diversity profile curves are useful for clarifying these differences, and may provide a more complete picture of the community structure. However, it is unclear how to utilize these curves when interest is in evaluating changes in community structure over time. We propose the use of a bi-exponential function in a longitudinal model that accounts for repeated measures on each subject to compare diversity profiles over time. Furthermore, it is possible that no change in alpha diversity (single community/sample) may be observed despite the presence of a highly divergent community composition. Thus, it is also important to use a beta diversity measure (similarity between multiple communities/samples) that captures changes in community composition. Ecological methods developed to evaluate temporal turnover have currently only been applied to investigate changes of a single community over time. We illustrate the extension of this approach to multiple communities of interest (i.e., subjects) by modeling the beta diversity measure over time. With this approach, a rate of change in community composition is estimated. There is a need for the extension and development of analytic methods for longitudinal microbiota studies. In this paper, we discuss different approaches to model alpha and beta diversity indices in longitudinal microbiota studies and provide both a review of current approaches and a proposal for new methods.

Combining independent de novo assemblies optimizes the coding transcriptome for nonconventional model eukaryotic organisms.

PubMed

Cerveau, Nicolas; Jackson, Daniel J

2016-12-09

Next-generation sequencing (NGS) technologies are arguably the most revolutionary technical development to join the list of tools available to molecular biologists since PCR. For researchers working with nonconventional model organisms one major problem with the currently dominant NGS platform (Illumina) stems from the obligatory fragmentation of nucleic acid material that occurs prior to sequencing during library preparation. This step creates a significant bioinformatic challenge for accurate de novo assembly of novel transcriptome data. This challenge becomes apparent when a variety of modern assembly tools (of which there is no shortage) are applied to the same raw NGS dataset. With the same assembly parameters these tools can generate markedly different assembly outputs. In this study we present an approach that generates an optimized consensus de novo assembly of eukaryotic coding transcriptomes. This approach does not represent a new assembler, rather it combines the outputs of a variety of established assembly packages, and removes redundancy via a series of clustering steps. We test and validate our approach using Illumina datasets from six phylogenetically diverse eukaryotes (three metazoans, two plants and a yeast) and two simulated datasets derived from metazoan reference genome annotations. All of these datasets were assembled using three currently popular assembly packages (CLC, Trinity and IDBA-tran). In addition, we experimentally demonstrate that transcripts unique to one particular assembly package are likely to be bioinformatic artefacts. For all eight datasets our pipeline generates more concise transcriptomes that in fact possess more unique annotatable protein domains than any of the three individual assemblers we employed. Another measure of assembly completeness (using the purpose built BUSCO databases) also confirmed that our approach yields more information. Our approach yields coding transcriptome assemblies that are more likely to be closer to biological reality than any of the three individual assembly packages we investigated. This approach (freely available as a simple perl script) will be of use to researchers working with species for which there is little or no reference data against which the assembly of a transcriptome can be performed.

On the Use of Diversity Measures in Longitudinal Sequencing Studies of Microbial Communities

PubMed Central

Wagner, Brandie D.; Grunwald, Gary K.; Zerbe, Gary O.; Mikulich-Gilbertson, Susan K.; Robertson, Charles E.; Zemanick, Edith T.; Harris, J. Kirk

2018-01-01

Identification of the majority of organisms present in human-associated microbial communities is feasible with the advent of high throughput sequencing technology. As substantial variability in microbiota communities is seen across subjects, the use of longitudinal study designs is important to better understand variation of the microbiome within individual subjects. Complex study designs with longitudinal sample collection require analytic approaches to account for this additional source of variability. A common approach to assessing community changes is to evaluate the change in alpha diversity (the variety and abundance of organisms in a community) over time. However, there are several commonly used alpha diversity measures and the use of different measures can result in different estimates of magnitude of change and different inferences. It has recently been proposed that diversity profile curves are useful for clarifying these differences, and may provide a more complete picture of the community structure. However, it is unclear how to utilize these curves when interest is in evaluating changes in community structure over time. We propose the use of a bi-exponential function in a longitudinal model that accounts for repeated measures on each subject to compare diversity profiles over time. Furthermore, it is possible that no change in alpha diversity (single community/sample) may be observed despite the presence of a highly divergent community composition. Thus, it is also important to use a beta diversity measure (similarity between multiple communities/samples) that captures changes in community composition. Ecological methods developed to evaluate temporal turnover have currently only been applied to investigate changes of a single community over time. We illustrate the extension of this approach to multiple communities of interest (i.e., subjects) by modeling the beta diversity measure over time. With this approach, a rate of change in community composition is estimated. There is a need for the extension and development of analytic methods for longitudinal microbiota studies. In this paper, we discuss different approaches to model alpha and beta diversity indices in longitudinal microbiota studies and provide both a review of current approaches and a proposal for new methods. PMID:29872428

Identifying micro-inversions using high-throughput sequencing reads.

PubMed

He, Feifei; Li, Yang; Tang, Yu-Hang; Ma, Jian; Zhu, Huaiqiu

2016-01-11

The identification of inversions of DNA segments shorter than read length (e.g., 100 bp), defined as micro-inversions (MIs), remains challenging for next-generation sequencing reads. It is acknowledged that MIs are important genomic variation and may play roles in causing genetic disease. However, current alignment methods are generally insensitive to detect MIs. Here we develop a novel tool, MID (Micro-Inversion Detector), to identify MIs in human genomes using next-generation sequencing reads. The algorithm of MID is designed based on a dynamic programming path-finding approach. What makes MID different from other variant detection tools is that MID can handle small MIs and multiple breakpoints within an unmapped read. Moreover, MID improves reliability in low coverage data by integrating multiple samples. Our evaluation demonstrated that MID outperforms Gustaf, which can currently detect inversions from 30 bp to 500 bp. To our knowledge, MID is the first method that can efficiently and reliably identify MIs from unmapped short next-generation sequencing reads. MID is reliable on low coverage data, which is suitable for large-scale projects such as the 1000 Genomes Project (1KGP). MID identified previously unknown MIs from the 1KGP that overlap with genes and regulatory elements in the human genome. We also identified MIs in cancer cell lines from Cancer Cell Line Encyclopedia (CCLE). Therefore our tool is expected to be useful to improve the study of MIs as a type of genetic variant in the human genome. The source code can be downloaded from: http://cqb.pku.edu.cn/ZhuLab/MID .

A new era in clinical genetic testing for hypertrophic cardiomyopathy.

PubMed

Wheeler, Matthew; Pavlovic, Aleksandra; DeGoma, Emil; Salisbury, Heidi; Brown, Colleen; Ashley, Euan A

2009-12-01

Building on seminal studies of the last 20 years, genetic testing for hypertrophic cardiomyopathy (HCM) has become a clinical reality in the form of targeted exonic sequencing of known disease-causing genes. This has been driven primarily by the decreasing cost of sequencing, but the high profile of genome-wide association studies, the launch of direct-to-consumer genetic testing, and new legislative protection have also played important roles. In the clinical management of hypertrophic cardiomyopathy, genetic testing is primarily used for family screening. An increasing role is recognized, however, in diagnostic settings: in the differential diagnosis of HCM; in the differentiation of HCM from hypertensive or athlete's heart; and more rarely in preimplantation genetic diagnosis. Aside from diagnostic clarification and family screening, use of the genetic test for guiding therapy remains controversial, with data currently too limited to derive a reliable mutation risk prediction from within the phenotypic noise of different modifying genomes. Meanwhile, the power of genetic testing derives from the confidence with which a mutation can be called present or absent in a given individual. This confidence contrasts with our more limited ability to judge the significance of mutations for which co-segregation has not been demonstrated. These variants of "unknown" significance represent the greatest challenge to the wider adoption of genetic testing in HCM. Looking forward, next-generation sequencing technologies promise to revolutionize the current approach as whole genome sequencing will soon be available for the cost of today's targeted panel. In summary, our future will be characterized not by lack of genetic information but by our ability to effectively parse it.

Current whole-body MRI applications in the neurofibromatoses

PubMed Central

Fayad, Laura M.; Khan, Muhammad Shayan; Bredella, Miriam A.; Harris, Gordon J.; Evans, D. Gareth; Farschtschi, Said; Jacobs, Michael A.; Chhabra, Avneesh; Salamon, Johannes M.; Wenzel, Ralph; Mautner, Victor F.; Dombi, Eva; Cai, Wenli; Plotkin, Scott R.; Blakeley, Jaishri O.

2016-01-01

Objectives: The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. Methods: A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. Results: WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. Conclusions: WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. PMID:27527647

Detection of Cytosine methylation in ancient DNA from five native american populations using bisulfite sequencing.

PubMed

Smith, Rick W A; Monroe, Cara; Bolnick, Deborah A

2015-01-01

While cytosine methylation has been widely studied in extant populations, relatively few studies have analyzed methylation in ancient DNA. Most existing studies of epigenetic marks in ancient DNA have inferred patterns of methylation in highly degraded samples using post-mortem damage to cytosines as a proxy for cytosine methylation levels. However, this approach limits the inference of methylation compared with direct bisulfite sequencing, the current gold standard for analyzing cytosine methylation at single nucleotide resolution. In this study, we used direct bisulfite sequencing to assess cytosine methylation in ancient DNA from the skeletal remains of 30 Native Americans ranging in age from approximately 230 to 4500 years before present. Unmethylated cytosines were converted to uracils by treatment with sodium bisulfite, bisulfite products of a CpG-rich retrotransposon were pyrosequenced, and C-to-T ratios were quantified for a single CpG position. We found that cytosine methylation is readily recoverable from most samples, given adequate preservation of endogenous nuclear DNA. In addition, our results indicate that the precision of cytosine methylation estimates is inversely correlated with aDNA preservation, such that samples of low DNA concentration show higher variability in measures of percent methylation than samples of high DNA concentration. In particular, samples in this study with a DNA concentration above 0.015 ng/μL generated the most consistent measures of cytosine methylation. This study presents evidence of cytosine methylation in a large collection of ancient human remains, and indicates that it is possible to analyze epigenetic patterns in ancient populations using direct bisulfite sequencing approaches.

Challenging a bioinformatic tool's ability to detect microbial contaminants using in silico whole genome sequencing data.

PubMed

Olson, Nathan D; Zook, Justin M; Morrow, Jayne B; Lin, Nancy J

2017-01-01

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus , Escherichia , and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

PubMed

Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

2016-09-01

S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.

Evaluating multiplexed next-generation sequencing as a method in palynology for mixed pollen samples.

PubMed

Keller, A; Danner, N; Grimmer, G; Ankenbrand, M; von der Ohe, K; von der Ohe, W; Rost, S; Härtel, S; Steffan-Dewenter, I

2015-03-01

The identification of pollen plays an important role in ecology, palaeo-climatology, honey quality control and other areas. Currently, expert knowledge and reference collections are essential to identify pollen origin through light microscopy. Pollen identification through molecular sequencing and DNA barcoding has been proposed as an alternative approach, but the assessment of mixed pollen samples originating from multiple plant species is still a tedious and error-prone task. Next-generation sequencing has been proposed to avoid this hindrance. In this study we assessed mixed pollen probes through next-generation sequencing of amplicons from the highly variable, species-specific internal transcribed spacer 2 region of nuclear ribosomal DNA. Further, we developed a bioinformatic workflow to analyse these high-throughput data with a newly created reference database. To evaluate the feasibility, we compared results from classical identification based on light microscopy from the same samples with our sequencing results. We assessed in total 16 mixed pollen samples, 14 originated from honeybee colonies and two from solitary bee nests. The sequencing technique resulted in higher taxon richness (deeper assignments and more identified taxa) compared to light microscopy. Abundance estimations from sequencing data were significantly correlated with counted abundances through light microscopy. Simulation analyses of taxon specificity and sensitivity indicate that 96% of taxa present in the database are correctly identifiable at the genus level and 70% at the species level. Next-generation sequencing thus presents a useful and efficient workflow to identify pollen at the genus and species level without requiring specialised palynological expert knowledge. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Biological nanopore MspA for DNA sequencing

NASA Astrophysics Data System (ADS)

Manrao, Elizabeth A.

Unlocking the information hidden in the human genome provides insight into the inner workings of complex biological systems and can be used to greatly improve health-care. In order to allow for widespread sequencing, new technologies are required that provide fast and inexpensive readings of DNA. Nanopore sequencing is a third generation DNA sequencing technology that is currently being developed to fulfill this need. In nanopore sequencing, a voltage is applied across a small pore in an electrolyte solution and the resulting ionic current is recorded. When DNA passes through the channel, the ionic current is partially blocked. If the DNA bases uniquely modulate the ionic current flowing through the channel, the time trace of the current can be related to the sequence of DNA passing through the pore. There are two main challenges to realizing nanopore sequencing: identifying a pore with sensitivity to single nucleotides and controlling the translocation of DNA through the pore so that the small single nucleotide current signatures are distinguishable from background noise. In this dissertation, I explore the use of Mycobacterium smegmatis porin A (MspA) for nanopore sequencing. In order to determine MspA's sensitivity to single nucleotides, DNA strands of various compositions are held in the pore as the resulting ionic current is measured. DNA is immobilized in MspA by attaching it to a large molecule which acts as an anchor. This technique confirms the single nucleotide resolution of the pore and additionally shows that MspA is sensitive to epigenetic modifications and single nucleotide polymorphisms. The forces from the electric field within MspA, the effective charge of nucleotides, and elasticity of DNA are estimated using a Freely Jointed Chain model of single stranded DNA. These results offer insight into the interactions of DNA within the pore. With the nucleotide sensitivity of MspA confirmed, a method is introduced to controllably pass DNA through the pore. Using a DNA polymerase, DNA strands are stepped through MspA one nucleotide at a time. The steps are observable as distinct levels on the ionic-current time-trace and are related to the DNA sequence. These experiments overcome the two fundamental challenges to realizing MspA nanopore sequencing and pave the way to the development of a commercial technology.