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

PubMed Central

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

2010-01-01

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

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.

PubMed

Nordberg, Henrik; Bhatia, Karan; Wang, Kai; Wang, Zhong

2013-12-01

The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this 'data deluge', here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. We built BioPig on the Apache's Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig's programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis.

Cyclicity in Upper Mississippian Bangor Limestone, Blount County, Alabama

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

Bronner, R.L.

1988-01-01

The Upper Mississippian (Chesterian) Bangor Limestone in Alabama consists of a thick, complex sequence of carbonate platform deposits. A continuous core through the Bangor on Blount Mountain in north-central Alabama provides the opportunity to analyze the unit for cyclicity and to identify controls on vertical facies sequence. Lithologies from the core represent four general environments of deposition: (1) subwave-base, open marine, (2) shoal, (3) lagoon, and (4) peritidal. Analysis of the vertical sequence of lithologies in the core indicates the presence of eight large-scale cycles dominated by subtidal deposits, but defined on the basis of peritidal caps. These large-scale cyclesmore » can be subdivided into 16 small-scale cycles that may be entirely subtidal but illustrate upward shallowing followed by rapid deepening. Large-scale cycles range from 33 to 136 ft thick, averaging 68 ft; small-scale cycles range from 5 to 80 ft thick and average 34 ft. Small-scale cycles have an average duration of approximately 125,000 years, which is compatible with Milankovitch periodicity. The large-scale cycles have an average duration of approximately 250,000 years, which may simply reflect variations in amplitude of sea level fluctuation or the influence of tectonic subsidence along the southeastern margin of the North American craton.« less

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

PubMed Central

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

PubMed

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis.

WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing

PubMed Central

Sharma, Parichit; Mantri, Shrikant S.

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis. PMID:24979410

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

Analysis of genetic diversity using SNP markers in oat

USDA-ARS?s Scientific Manuscript database

A large-scale single nucleotide polymorphism (SNP) discovery was carried out in cultivated oat using Roche 454 sequencing methods. DNA sequences were generated from cDNAs originating from a panel of 20 diverse oat cultivars, and from Diversity Array Technology (DArT) genomic complexity reductions fr...

TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

PubMed

Richard, François D; Kajava, Andrey V

2014-06-01

The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.

BioPig: Developing Cloud Computing Applications for Next-Generation Sequence Analysis

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

Bhatia, Karan; Wang, Zhong

Next Generation sequencing is producing ever larger data sizes with a growth rate outpacing Moore's Law. The data deluge has made many of the current sequenceanalysis tools obsolete because they do not scale with data. Here we present BioPig, a collection of cloud computing tools to scale data analysis and management. Pig is aflexible data scripting language that uses Apache's Hadoop data structure and map reduce framework to process very large data files in parallel and combine the results.BioPig extends Pig with capability with sequence analysis. We will show the performance of BioPig on a variety of bioinformatics tasks, includingmore » screeningsequence contaminants, Illumina QA/QC, and gene discovery from metagenome data sets using the Rumen metagenome as an example.« less

Enabling large-scale next-generation sequence assembly with Blacklight

PubMed Central

Couger, M. Brian; Pipes, Lenore; Squina, Fabio; Prade, Rolf; Siepel, Adam; Palermo, Robert; Katze, Michael G.; Mason, Christopher E.; Blood, Philip D.

2014-01-01

Summary A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly, very large metagenomic sequence assembly, transcriptome assembly, and sequencing error correction. The data sets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, composed of both short-read and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results, initially reported previously at XSEDE13 and expanded here, represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems. PMID:25294974

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

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

Optical mapping and its potential for large-scale sequencing projects.

PubMed

Aston, C; Mishra, B; Schwartz, D C

1999-07-01

Physical mapping has been rediscovered as an important component of large-scale sequencing projects. Restriction maps provide landmark sequences at defined intervals, and high-resolution restriction maps can be assembled from ensembles of single molecules by optical means. Such optical maps can be constructed from both large-insert clones and genomic DNA, and are used as a scaffold for accurately aligning sequence contigs generated by shotgun sequencing.

Comprehensive Analysis of DNA Methylation Data with RnBeads

PubMed Central

Walter, Jörn; Lengauer, Thomas; Bock, Christoph

2014-01-01

RnBeads is a software tool for large-scale analysis and interpretation of DNA methylation data, providing a user-friendly analysis workflow that yields detailed hypertext reports (http://rnbeads.mpi-inf.mpg.de). Supported assays include whole genome bisulfite sequencing, reduced representation bisulfite sequencing, Infinium microarrays, and any other protocol that produces high-resolution DNA methylation data. Important applications of RnBeads include the analysis of epigenome-wide association studies and epigenetic biomarker discovery in cancer cohorts. PMID:25262207

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Selectivity by host plants affects the distribution of arbuscular mycorrhizal fungi: evidence from ITS rDNA sequence metadata.

PubMed

Yang, Haishui; Zang, Yanyan; Yuan, Yongge; Tang, Jianjun; Chen, Xin

2012-04-12

Arbuscular mycorrhizal fungi (AMF) can form obligate symbioses with the vast majority of land plants, and AMF distribution patterns have received increasing attention from researchers. At the local scale, the distribution of AMF is well documented. Studies at large scales, however, are limited because intensive sampling is difficult. Here, we used ITS rDNA sequence metadata obtained from public databases to study the distribution of AMF at continental and global scales. We also used these sequence metadata to investigate whether host plant is the main factor that affects the distribution of AMF at large scales. We defined 305 ITS virtual taxa (ITS-VTs) among all sequences of the Glomeromycota by using a comprehensive maximum likelihood phylogenetic analysis. Each host taxonomic order averaged about 53% specific ITS-VTs, and approximately 60% of the ITS-VTs were host specific. Those ITS-VTs with wide host range showed wide geographic distribution. Most ITS-VTs occurred in only one type of host functional group. The distributions of most ITS-VTs were limited across ecosystem, across continent, across biogeographical realm, and across climatic zone. Non-metric multidimensional scaling analysis (NMDS) showed that AMF community composition differed among functional groups of hosts, and among ecosystem, continent, biogeographical realm, and climatic zone. The Mantel test showed that AMF community composition was significantly correlated with plant community composition among ecosystem, among continent, among biogeographical realm, and among climatic zone. The structural equation modeling (SEM) showed that the effects of ecosystem, continent, biogeographical realm, and climatic zone were mainly indirect on AMF distribution, but plant had strongly direct effects on AMF. The distribution of AMF as indicated by ITS rDNA sequences showed a pattern of high endemism at large scales. This pattern indicates high specificity of AMF for host at different scales (plant taxonomic order and functional group) and high selectivity from host plants for AMF. The effects of ecosystemic, biogeographical, continental and climatic factors on AMF distribution might be mediated by host plants.

RNA sequencing: current and prospective uses in metabolic research.

PubMed

Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay

2014-10-01

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

New Tools For Understanding Microbial Diversity Using High-throughput Sequence Data

NASA Astrophysics Data System (ADS)

Knight, R.; Hamady, M.; Liu, Z.; Lozupone, C.

2007-12-01

High-throughput sequencing techniques such as 454 are straining the limits of tools traditionally used to build trees, choose OTUs, and perform other essential sequencing tasks. We have developed a workflow for phylogenetic analysis of large-scale sequence data sets that combines existing tools, such as the Arb phylogeny package and the NAST multiple sequence alignment tool, with new methods for choosing and clustering OTUs and for performing phylogenetic community analysis with UniFrac. This talk discusses the cyberinfrastructure we are developing to support the human microbiome project, and the application of these workflows to analyze very large data sets that contrast the gut microbiota with a range of physical environments. These tools will ultimately help to define core and peripheral microbiomes in a range of environments, and will allow us to understand the physical and biotic factors that contribute most to differences in microbial diversity.

About TCGA - TCGA

Cancer.gov

Find out about The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

PubMed

Nowrousian, Minou; Würtz, Christian; Pöggeler, Stefanie; Kück, Ulrich

2004-03-01

One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

Home - The Cancer Genome Atlas - Cancer Genome - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

Assembly of 500,000 inter-specific catfish expressed sequence tags and large scale gene-associated marker development for whole genome association studies

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

Catfish Genome Consortium; Wang, Shaolin; Peatman, Eric

2010-03-23

Background-Through the Community Sequencing Program, a catfish EST sequencing project was carried out through a collaboration between the catfish research community and the Department of Energy's Joint Genome Institute. Prior to this project, only a limited EST resource from catfish was available for the purpose of SNP identification. Results-A total of 438,321 quality ESTs were generated from 8 channel catfish (Ictalurus punctatus) and 4 blue catfish (Ictalurus furcatus) libraries, bringing the number of catfish ESTs to nearly 500,000. Assembly of all catfish ESTs resulted in 45,306 contigs and 66,272 singletons. Over 35percent of the unique sequences had significant similarities tomore » known genes, allowing the identification of 14,776 unique genes in catfish. Over 300,000 putative SNPs have been identified, of which approximately 48,000 are high-quality SNPs identified from contigs with at least four sequences and the minor allele presence of at least two sequences in the contig. The EST resource should be valuable for identification of microsatellites, genome annotation, large-scale expression analysis, and comparative genome analysis. Conclusions-This project generated a large EST resource for catfish that captured the majority of the catfish transcriptome. The parallel analysis of ESTs from two closely related Ictalurid catfishes should also provide powerful means for the evaluation of ancient and recent gene duplications, and for the development of high-density microarrays in catfish. The inter- and intra-specific SNPs identified from all catfish EST dataset assembly will greatly benefit the catfish introgression breeding program and whole genome association studies.« less

Identification of tissue-specific, abiotic stress-responsive gene expression patterns in wine grape (Vitis vinifera L.) based on curation and mining of large-scale EST data sets

PubMed Central

2011-01-01

Background Abiotic stresses, such as water deficit and soil salinity, result in changes in physiology, nutrient use, and vegetative growth in vines, and ultimately, yield and flavor in berries of wine grape, Vitis vinifera L. Large-scale expressed sequence tags (ESTs) were generated, curated, and analyzed to identify major genetic determinants responsible for stress-adaptive responses. Although roots serve as the first site of perception and/or injury for many types of abiotic stress, EST sequencing in root tissues of wine grape exposed to abiotic stresses has been extremely limited to date. To overcome this limitation, large-scale EST sequencing was conducted from root tissues exposed to multiple abiotic stresses. Results A total of 62,236 expressed sequence tags (ESTs) were generated from leaf, berry, and root tissues from vines subjected to abiotic stresses and compared with 32,286 ESTs sequenced from 20 public cDNA libraries. Curation to correct annotation errors, clustering and assembly of the berry and leaf ESTs with currently available V. vinifera full-length transcripts and ESTs yielded a total of 13,278 unique sequences, with 2302 singletons and 10,976 mapped to V. vinifera gene models. Of these, 739 transcripts were found to have significant differential expression in stressed leaves and berries including 250 genes not described previously as being abiotic stress responsive. In a second analysis of 16,452 ESTs from a normalized root cDNA library derived from roots exposed to multiple, short-term, abiotic stresses, 135 genes with root-enriched expression patterns were identified on the basis of their relative EST abundance in roots relative to other tissues. Conclusions The large-scale analysis of relative EST frequency counts among a diverse collection of 23 different cDNA libraries from leaf, berry, and root tissues of wine grape exposed to a variety of abiotic stress conditions revealed distinct, tissue-specific expression patterns, previously unrecognized stress-induced genes, and many novel genes with root-enriched mRNA expression for improving our understanding of root biology and manipulation of rootstock traits in wine grape. mRNA abundance estimates based on EST library-enriched expression patterns showed only modest correlations between microarray and quantitative, real-time reverse transcription-polymerase chain reaction (qRT-PCR) methods highlighting the need for deep-sequencing expression profiling methods. PMID:21592389

Transfer of movement sequences: bigger is better.

PubMed

Dean, Noah J; Kovacs, Attila J; Shea, Charles H

2008-02-01

Experiment 1 was conducted to determine if proportional transfer from "small to large" scale movements is as effective as transferring from "large to small." We hypothesize that the learning of larger scale movement will require the participant to learn to manage the generation, storage, and dissipation of forces better than when practicing smaller scale movements. Thus, we predict an advantage for transfer of larger scale movements to smaller scale movements relative to transfer from smaller to larger scale movements. Experiment 2 was conducted to determine if adding a load to a smaller scale movement would enhance later transfer to a larger scale movement sequence. It was hypothesized that the added load would require the participants to consider the dynamics of the movement to a greater extent than without the load. The results replicated earlier findings of effective transfer from large to small movements, but consistent with our hypothesis, transfer was less effective from small to large (Experiment 1). However, when a load was added during acquisition transfer from small to large was enhanced even though the load was removed during the transfer test. These results are consistent with the notion that the transfer asymmetry noted in Experiment 1 was due to factors related to movement dynamics that were enhanced during practice of the larger scale movement sequence, but not during the practice of the smaller scale movement sequence. The findings that the movement structure is unaffected by transfer direction but the movement dynamics are influenced by transfer direction is consistent with hierarchal models of sequence production.

PGen: large-scale genomic variations analysis workflow and browser in SoyKB.

PubMed

Liu, Yang; Khan, Saad M; Wang, Juexin; Rynge, Mats; Zhang, Yuanxun; Zeng, Shuai; Chen, Shiyuan; Maldonado Dos Santos, Joao V; Valliyodan, Babu; Calyam, Prasad P; Merchant, Nirav; Nguyen, Henry T; Xu, Dong; Joshi, Trupti

2016-10-06

With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed "PGen", an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way. We have developed both a Linux version in GitHub ( https://github.com/pegasus-isi/PGen-GenomicVariations-Workflow ) and a web-based implementation of the PGen workflow integrated within the Soybean Knowledge Base (SoyKB), ( http://soykb.org/Pegasus/index.php ). Using PGen, we identified 10,218,140 single-nucleotide polymorphisms (SNPs) and 1,398,982 indels from analysis of 106 soybean lines sequenced at 15X coverage. 297,245 non-synonymous SNPs and 3330 copy number variation (CNV) regions were identified from this analysis. SNPs identified using PGen from additional soybean resequencing projects adding to 500+ soybean germplasm lines in total have been integrated. These SNPs are being utilized for trait improvement using genotype to phenotype prediction approaches developed in-house. In order to browse and access NGS data easily, we have also developed an NGS resequencing data browser ( http://soykb.org/NGS_Resequence/NGS_index.php ) within SoyKB to provide easy access to SNP and downstream analysis results for soybean researchers. PGen workflow has been optimized for the most efficient analysis of soybean data using thorough testing and validation. This research serves as an example of best practices for development of genomics data analysis workflows by integrating remote HPC resources and efficient data management with ease of use for biological users. PGen workflow can also be easily customized for analysis of data in other species.

DNA-encoded chemistry: enabling the deeper sampling of chemical space.

PubMed

Goodnow, Robert A; Dumelin, Christoph E; Keefe, Anthony D

2017-02-01

DNA-encoded chemical library technologies are increasingly being adopted in drug discovery for hit and lead generation. DNA-encoded chemistry enables the exploration of chemical spaces four to five orders of magnitude more deeply than is achievable by traditional high-throughput screening methods. Operation of this technology requires developing a range of capabilities including aqueous synthetic chemistry, building block acquisition, oligonucleotide conjugation, large-scale molecular biological transformations, selection methodologies, PCR, sequencing, sequence data analysis and the analysis of large chemistry spaces. This Review provides an overview of the development and applications of DNA-encoded chemistry, highlighting the challenges and future directions for the use of this technology.

Chromosome evolution in the Thermotogales: large-scale inversions and strain diversification of CRISPR sequences.

PubMed

DeBoy, Robert T; Mongodin, Emmanuel F; Emerson, Joanne B; Nelson, Karen E

2006-04-01

In the present study, the chromosomes of two members of the Thermotogales were compared. A whole-genome alignment of Thermotoga maritima MSB8 and Thermotoga neapolitana NS-E has revealed numerous large-scale DNA rearrangements, most of which are associated with CRISPR DNA repeats and/or tRNA genes. These DNA rearrangements do not include the putative origin of DNA replication but move within the same replichore, i.e., the same replicating half of the chromosome (delimited by the replication origin and terminus). Based on cumulative GC skew analysis, both the T. maritima and T. neapolitana lineages contain one or two major inverted DNA segments. Also, based on PCR amplification and sequence analysis of the DNA joints that are associated with the major rearrangements, the overall chromosome architecture was found to be conserved at most DNA joints for other strains of T. neapolitana. Taken together, the results from this analysis suggest that the observed chromosomal rearrangements in the Thermotogales likely occurred by successive inversions after their divergence from a common ancestor and before strain diversification. Finally, sequence analysis shows that size polymorphisms in the DNA joints associated with CRISPRs can be explained by expansion and possibly contraction of the DNA repeat and spacer unit, providing a tool for discerning the relatedness of strains from different geographic locations.

Lessons learnt on the analysis of large sequence data in animal genomics.

PubMed

Biscarini, F; Cozzi, P; Orozco-Ter Wengel, P

2018-04-06

The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets. © 2018 Stichting International Foundation for Animal Genetics.

Design of DNA pooling to allow incorporation of covariates in rare variants analysis.

PubMed

Guan, Weihua; Li, Chun

2014-01-01

Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect. For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique. Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes. Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.

PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens.

PubMed

Spahn, Philipp N; Bath, Tyler; Weiss, Ryan J; Kim, Jihoon; Esko, Jeffrey D; Lewis, Nathan E; Harismendy, Olivier

2017-11-20

Large-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools have been developed for this purpose, their utility is still hindered either due to limited functionality or the requirement of bioinformatic expertise. To make sequencing data analysis of CRISPR/Cas9 screens more accessible to a wide range of scientists, we developed a Platform-independent Analysis of Pooled Screens using Python (PinAPL-Py), which is operated as an intuitive web-service. PinAPL-Py implements state-of-the-art tools and statistical models, assembled in a comprehensive workflow covering sequence quality control, automated sgRNA sequence extraction, alignment, sgRNA enrichment/depletion analysis and gene ranking. The workflow is set up to use a variety of popular sgRNA libraries as well as custom libraries that can be easily uploaded. Various analysis options are offered, suitable to analyze a large variety of CRISPR/Cas9 screening experiments. Analysis output includes ranked lists of sgRNAs and genes, and publication-ready plots. PinAPL-Py helps to advance genome-wide screening efforts by combining comprehensive functionality with user-friendly implementation. PinAPL-Py is freely accessible at http://pinapl-py.ucsd.edu with instructions and test datasets.

Initial sequencing and comparative analysis of the mouse genome

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

Waterston, Robert H.; Lindblad-Toh, Kerstin; Birney, Ewan

2002-12-15

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of themore » genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.« less

Let them fall where they may: congruence analysis in massive phylogenetically messy data sets.

PubMed

Leigh, Jessica W; Schliep, Klaus; Lopez, Philippe; Bapteste, Eric

2011-10-01

Interest in congruence in phylogenetic data has largely focused on issues affecting multicellular organisms, and animals in particular, in which the level of incongruence is expected to be relatively low. In addition, assessment methods developed in the past have been designed for reasonably small numbers of loci and scale poorly for larger data sets. However, there are currently over a thousand complete genome sequences available and of interest to evolutionary biologists, and these sequences are predominantly from microbial organisms, whose molecular evolution is much less frequently tree-like than that of multicellular life forms. As such, the level of incongruence in these data is expected to be high. We present a congruence method that accommodates both very large numbers of genes and high degrees of incongruence. Our method uses clustering algorithms to identify subsets of genes based on similarity of phylogenetic signal. It involves only a single phylogenetic analysis per gene, and therefore, computation time scales nearly linearly with the number of genes in the data set. We show that our method performs very well with sets of sequence alignments simulated under a wide variety of conditions. In addition, we present an analysis of core genes of prokaryotes, often assumed to have been largely vertically inherited, in which we identify two highly incongruent classes of genes. This result is consistent with the complexity hypothesis.

mySyntenyPortal: an application package to construct websites for synteny block analysis.

PubMed

Lee, Jongin; Lee, Daehwan; Sim, Mikang; Kwon, Daehong; Kim, Juyeon; Ko, Younhee; Kim, Jaebum

2018-06-05

Advances in sequencing technologies have facilitated large-scale comparative genomics based on whole genome sequencing. Constructing and investigating conserved genomic regions among multiple species (called synteny blocks) are essential in the comparative genomics. However, they require significant amounts of computational resources and time in addition to bioinformatics skills. Many web interfaces have been developed to make such tasks easier. However, these web interfaces cannot be customized for users who want to use their own set of genome sequences or definition of synteny blocks. To resolve this limitation, we present mySyntenyPortal, a stand-alone application package to construct websites for synteny block analyses by using users' own genome data. mySyntenyPortal provides both command line and web-based interfaces to build and manage websites for large-scale comparative genomic analyses. The websites can be also easily published and accessed by other users. To demonstrate the usability of mySyntenyPortal, we present an example study for building websites to compare genomes of three mammalian species (human, mouse, and cow) and show how they can be easily utilized to identify potential genes affected by genome rearrangements. mySyntenyPortal will contribute for extended comparative genomic analyses based on large-scale whole genome sequences by providing unique functionality to support the easy creation of interactive websites for synteny block analyses from user's own genome data.

Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

PubMed

Chechetkin, V R; Lobzin, V V

2017-08-07

Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

PubMed

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

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

CoCoNUT: an efficient system for the comparison and analysis of genomes

PubMed Central

2008-01-01

Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477

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

PubMed

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

2018-05-09

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

Search for 5'-leader regulatory RNA structures based on gene annotation aided by the RiboGap database.

PubMed

Naghdi, Mohammad Reza; Smail, Katia; Wang, Joy X; Wade, Fallou; Breaker, Ronald R; Perreault, Jonathan

2017-03-15

The discovery of noncoding RNAs (ncRNAs) and their importance for gene regulation led us to develop bioinformatics tools to pursue the discovery of novel ncRNAs. Finding ncRNAs de novo is challenging, first due to the difficulty of retrieving large numbers of sequences for given gene activities, and second due to exponential demands on calculation needed for comparative genomics on a large scale. Recently, several tools for the prediction of conserved RNA secondary structure were developed, but many of them are not designed to uncover new ncRNAs, or are too slow for conducting analyses on a large scale. Here we present various approaches using the database RiboGap as a primary tool for finding known ncRNAs and for uncovering simple sequence motifs with regulatory roles. This database also can be used to easily extract intergenic sequences of eubacteria and archaea to find conserved RNA structures upstream of given genes. We also show how to extend analysis further to choose the best candidate ncRNAs for experimental validation. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural Analysis of Biodiversity

PubMed Central

Sirovich, Lawrence; Stoeckle, Mark Y.; Zhang, Yu

2010-01-01

Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity. PMID:20195371

Multiple and substitute addictions involving prescription drugs misuse among 12th graders: gateway theory revisited with Market Basket Analysis.

PubMed

Jayawardene, Wasantha Parakrama; YoussefAgha, Ahmed Hassan

2014-01-01

This study aimed to identify the sequential patterns of drug use initiation, which included prescription drugs misuse (PDM), among 12th-grade students in Indiana. The study also tested the suitability of the data mining method Market Basket Analysis (MBA) to detect common drug use initiation sequences in large-scale surveys. Data from 2007 to 2009 Annual Surveys of Alcohol, Tobacco, and Other Drug Use by Indiana Children and Adolescents were used for this study. A close-ended, self-administered questionnaire was used to ask adolescents about the use of 21 substance categories and the age of first use. "Support%" and "confidence%" statistics of Market Basket Analysis detected multiple and substitute addictions, respectively. The lifetime prevalence of using any addictive substance was 73.3%, and it has been decreasing during past few years. Although the lifetime prevalence of PDM was 19.2%, it has been increasing. Males and whites were more likely to use drugs and engage in multiple addictions. Market Basket Analysis identified common drug use initiation sequences that involved 11 drugs. High levels of support existed for associations among alcohol, cigarettes, and marijuana, whereas associations that included prescription drugs had medium levels of support. Market Basket Analysis is useful for the detection of common substance use initiation sequences in large-scale surveys. Before initiation of prescription drugs, physicians should consider the adolescents' risk of addiction. Prevention programs should address multiple addictions, substitute addictions, common sequences in drug use initiation, sex and racial differences in PDM, and normative beliefs of parents and adolescents in relation to PDM.

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread--a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

DOE Joint Genome Institute 2008 Progress Report

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

Gilbert, David

2009-03-12

While initially a virtual institute, the driving force behind the creation of the DOE Joint Genome Institute in Walnut Creek, California in the Fall of 1999 was the Department of Energy's commitment to sequencing the human genome. With the publication in 2004 of a trio of manuscripts describing the finished 'DOE Human Chromosomes', the Institute successfully completed its human genome mission. In the time between the creation of the Department of Energy Joint Genome Institute (DOE JGI) and completion of the Human Genome Project, sequencing and its role in biology spread to fields extending far beyond what could be imaginedmore » when the Human Genome Project first began. Accordingly, the targets of the DOE JGI's sequencing activities changed, moving from a single human genome to the genomes of large numbers of microbes, plants, and other organisms, and the community of users of DOE JGI data similarly expanded and diversified. Transitioning into operating as a user facility, the DOE JGI modeled itself after other DOE user facilities, such as synchrotron light sources and supercomputer facilities, empowering the science of large numbers of investigators working in areas of relevance to energy and the environment. The JGI's approach to being a user facility is based on the concept that by focusing state-of-the-art sequencing and analysis capabilities on the best peer-reviewed ideas drawn from a broad community of scientists, the DOE JGI will effectively encourage creative approaches to DOE mission areas and produce important science. This clearly has occurred, only partially reflected in the fact that the DOE JGI has played a major role in more than 45 papers published in just the past three years alone in Nature and Science. The involvement of a large and engaged community of users working on important problems has helped maximize the impact of JGI science. A seismic technological change is presently underway at the JGI. The Sanger capillary-based sequencing process that dominated how sequencing was done in the last decade is being replaced by a variety of new processes and sequencing instruments. The JGI, with an increasing number of next-generation sequencers, whose throughput is 100- to 1,000-fold greater than the Sanger capillary-based sequencers, is increasingly focused in new directions on projects of scale and complexity not previously attempted. These new directions for the JGI come, in part, from the 2008 National Research Council report on the goals of the National Plant Genome Initiative as well as the 2007 National Research Council report on the New Science of Metagenomics. Both reports outline a crucial need for systematic large-scale surveys of the plant and microbial components of the biosphere as well as an increasing need for large-scale analysis capabilities to meet the challenge of converting sequence data into knowledge. The JGI is extensively discussed in both reports as vital to progress in these fields of major national interest. JGI's future plan for plants and microbes includes a systematic approach for investigation of these organisms at a scale requiring the special capabilities of the JGI to generate, manage, and analyze the datasets. JGI will generate and provide not only community access to these plant and microbial datasets, but also the tools for analyzing them. These activities will produce essential knowledge that will be needed if we are to be able to respond to the world's energy and environmental challenges. As the JGI Plant and Microbial programs advance, the JGI as a user facility is also evolving. The Institute has been highly successful in bending its technical and analytical skills to help users solve large complex problems of major importance, and that effort will continue unabated. The JGI will increasingly move from a central focus on 'one-off' user projects coming from small user communities to much larger scale projects driven by systematic and problem-focused approaches to selection of sequencing targets. Entire communities of scientists working in a particular field, such as feedstock improvement or biomass degradation, will be users of this information. Despite this new emphasis, an investigator-initiated user program will remain. This program in the future will replace small projects that increasingly can be accomplished without the involvement of JGI, with imaginative large-scale 'Grand Challenge' projects of foundational relevance to energy and the environment that require a new scale of sequencing and analysis capabilities. Close interactions with the DOE Bioenergy Research Centers, and with other DOE institutions that may follow, will also play a major role in shaping aspects of how the JGI operates as a user facility. Based on increased availability of high-throughput sequencing, the JGI will increasingly provide to users, in addition to DNA sequencing, an array of both pre- and post-sequencing value-added capabilities to accelerate their science.« less

Application and research of block caving in Pulang copper mine

NASA Astrophysics Data System (ADS)

Ge, Qifa; Fan, Wenlu; Zhu, Weigen; Chen, Xiaowei

2018-01-01

The application of block caving in mines shows significant advantages in large scale, low cost and high efficiency, thus block caving is worth promoting in the mines that meets the requirement of natural caving. Due to large scale of production and low ore grade in Pulang copper mine in China, comprehensive analysis and research were conducted on rock mechanics, mining sequence, undercutting and stability of bottom structure in terms of raising mine benefit and maximizing the recovery mineral resources. Finally this study summarizes that block caving is completely suitable for Pulang copper mine.

Large-scale gene discovery in the pea aphid Acyrthosiphon pisum (Hemiptera)

PubMed Central

Sabater-Muñoz, Beatriz; Legeai, Fabrice; Rispe, Claude; Bonhomme, Joël; Dearden, Peter; Dossat, Carole; Duclert, Aymeric; Gauthier, Jean-Pierre; Ducray, Danièle Giblot; Hunter, Wayne; Dang, Phat; Kambhampati, Srini; Martinez-Torres, David; Cortes, Teresa; Moya, Andrès; Nakabachi, Atsushi; Philippe, Cathy; Prunier-Leterme, Nathalie; Rahbé, Yvan; Simon, Jean-Christophe; Stern, David L; Wincker, Patrick; Tagu, Denis

2006-01-01

Aphids are the leading pests in agricultural crops. A large-scale sequencing of 40,904 ESTs from the pea aphid Acyrthosiphon pisum was carried out to define a catalog of 12,082 unique transcripts. A strong AT bias was found, indicating a compositional shift between Drosophila melanogaster and A. pisum. An in silico profiling analysis characterized 135 transcripts specific to pea-aphid tissues (relating to bacteriocytes and parthenogenetic embryos). This project is the first to address the genetics of the Hemiptera and of a hemimetabolous insect. PMID:16542494

Population-Sequencing as a Biomarker of Burkholderia mallei and Burkholderia pseudomallei Evolution through Microbial Forensic Analysis.

PubMed

Jakupciak, John P; Wells, Jeffrey M; Karalus, Richard J; Pawlowski, David R; Lin, Jeffrey S; Feldman, Andrew B

2013-01-01

Large-scale genomics projects are identifying biomarkers to detect human disease. B. pseudomallei and B. mallei are two closely related select agents that cause melioidosis and glanders. Accurate characterization of metagenomic samples is dependent on accurate measurements of genetic variation between isolates with resolution down to strain level. Often single biomarker sensitivity is augmented by use of multiple or panels of biomarkers. In parallel with single biomarker validation, advances in DNA sequencing enable analysis of entire genomes in a single run: population-sequencing. Potentially, direct sequencing could be used to analyze an entire genome to serve as the biomarker for genome identification. However, genome variation and population diversity complicate use of direct sequencing, as well as differences caused by sample preparation protocols including sequencing artifacts and mistakes. As part of a Department of Homeland Security program in bacterial forensics, we examined how to implement whole genome sequencing (WGS) analysis as a judicially defensible forensic method for attributing microbial sample relatedness; and also to determine the strengths and limitations of whole genome sequence analysis in a forensics context. Herein, we demonstrate use of sequencing to provide genetic characterization of populations: direct sequencing of populations.

Population-Sequencing as a Biomarker of Burkholderia mallei and Burkholderia pseudomallei Evolution through Microbial Forensic Analysis

PubMed Central

Jakupciak, John P.; Wells, Jeffrey M.; Karalus, Richard J.; Pawlowski, David R.; Lin, Jeffrey S.; Feldman, Andrew B.

2013-01-01

Large-scale genomics projects are identifying biomarkers to detect human disease. B. pseudomallei and B. mallei are two closely related select agents that cause melioidosis and glanders. Accurate characterization of metagenomic samples is dependent on accurate measurements of genetic variation between isolates with resolution down to strain level. Often single biomarker sensitivity is augmented by use of multiple or panels of biomarkers. In parallel with single biomarker validation, advances in DNA sequencing enable analysis of entire genomes in a single run: population-sequencing. Potentially, direct sequencing could be used to analyze an entire genome to serve as the biomarker for genome identification. However, genome variation and population diversity complicate use of direct sequencing, as well as differences caused by sample preparation protocols including sequencing artifacts and mistakes. As part of a Department of Homeland Security program in bacterial forensics, we examined how to implement whole genome sequencing (WGS) analysis as a judicially defensible forensic method for attributing microbial sample relatedness; and also to determine the strengths and limitations of whole genome sequence analysis in a forensics context. Herein, we demonstrate use of sequencing to provide genetic characterization of populations: direct sequencing of populations. PMID:24455204

Open Reading Frame Phylogenetic Analysis on the Cloud

PubMed Central

2013-01-01

Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus. PMID:23671843

Atlas2 Cloud: a framework for personal genome analysis in the cloud

PubMed Central

2012-01-01

Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663

Atlas2 Cloud: a framework for personal genome analysis in the cloud.

PubMed

Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli

2012-01-01

Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

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

PubMed

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

2018-05-04

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

Large-scale horizontal flows from SOUP observations of solar granulation

NASA Technical Reports Server (NTRS)

November, L. J.; Simon, G. W.; Tarbell, T. D.; Title, A. M.; Ferguson, S. H.

1987-01-01

Using high resolution time sequence photographs of solar granulation from the SOUP experiment on Spacelab 2, large scale horizontal flows were observed in the solar surface. The measurement method is based upon a local spatial cross correlation analysis. The horizontal motions have amplitudes in the range 300 to 1000 m/s. Radial outflow of granulation from a sunspot penumbra into surrounding photosphere is a striking new discovery. Both the supergranulation pattern and cellular structures having the scale of mesogranulation are seen. The vertical flows that are inferred by continuity of mass from these observed horizontal flows have larger upflow amplitudes in cell centers than downflow amplitudes at cell boundaries.

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.

Next-Generation Sequencing of the Chrysanthemum nankingense (Asteraceae) Transcriptome Permits Large-Scale Unigene Assembly and SSR Marker Discovery

PubMed Central

Wang, Haibin; Jiang, Jiafu; Chen, Sumei; Qi, Xiangyu; Peng, Hui; Li, Pirui; Song, Aiping; Guan, Zhiyong; Fang, Weimin; Liao, Yuan; Chen, Fadi

2013-01-01

Background Simple sequence repeats (SSRs) are ubiquitous in eukaryotic genomes. Chrysanthemum is one of the largest genera in the Asteraceae family. Only few Chrysanthemum expressed sequence tag (EST) sequences have been acquired to date, so the number of available EST-SSR markers is very low. Methodology/Principal Findings Illumina paired-end sequencing technology produced over 53 million sequencing reads from C. nankingense mRNA. The subsequent de novo assembly yielded 70,895 unigenes, of which 45,789 (64.59%) unigenes showed similarity to the sequences in NCBI database. Out of 45,789 sequences, 107 have hits to the Chrysanthemum Nr protein database; 679 and 277 sequences have hits to the database of Helianthus and Lactuca species, respectively. MISA software identified a large number of putative EST-SSRs, allowing 1,788 primer pairs to be designed from the de novo transcriptome sequence and a further 363 from archival EST sequence. Among 100 primer pairs randomly chosen, 81 markers have amplicons and 20 are polymorphic for genotypes analysis in Chrysanthemum. The results showed that most (but not all) of the assays were transferable across species and that they exposed a significant amount of allelic diversity. Conclusions/Significance SSR markers acquired by transcriptome sequencing are potentially useful for marker-assisted breeding and genetic analysis in the genus Chrysanthemum and its related genera. PMID:23626799

Comparisons between Arabidopsis thaliana and Drosophila melanogaster in relation to Coding and Noncoding Sequence Length and Gene Expression

PubMed Central

Caldwell, Rachel; Lin, Yan-Xia; Zhang, Ren

2015-01-01

There is a continuing interest in the analysis of gene architecture and gene expression to determine the relationship that may exist. Advances in high-quality sequencing technologies and large-scale resource datasets have increased the understanding of relationships and cross-referencing of expression data to the large genome data. Although a negative correlation between expression level and gene (especially transcript) length has been generally accepted, there have been some conflicting results arising from the literature concerning the impacts of different regions of genes, and the underlying reason is not well understood. The research aims to apply quantile regression techniques for statistical analysis of coding and noncoding sequence length and gene expression data in the plant, Arabidopsis thaliana, and fruit fly, Drosophila melanogaster, to determine if a relationship exists and if there is any variation or similarities between these species. The quantile regression analysis found that the coding sequence length and gene expression correlations varied, and similarities emerged for the noncoding sequence length (5′ and 3′ UTRs) between animal and plant species. In conclusion, the information described in this study provides the basis for further exploration into gene regulation with regard to coding and noncoding sequence length. PMID:26114098

Development of Low-cost, High Energy-per-unit-area Solar Cell Modules

NASA Technical Reports Server (NTRS)

Jones, G. T.; Chitre, S.; Rhee, S. S.

1978-01-01

The development of two hexagonal solar cell process sequences, a laserscribing process technique for scribing hexagonal and modified hexagonal solar cells, a large through-put diffusion process, and two surface macrostructure processes suitable for large scale production is reported. Experimental analysis was made on automated spin-on anti-reflective coating equipment and high pressure wafer cleaning equipment. Six hexagonal solar cell modules were fabricated. Also covered is a detailed theoretical analysis on the optimum silicon utilization by modified hexagonal solar cells.

Techniques for Large-Scale Bacterial Genome Manipulation and Characterization of the Mutants with Respect to In Silico Metabolic Reconstructions.

PubMed

diCenzo, George C; Finan, Turlough M

2018-01-01

The rate at which all genes within a bacterial genome can be identified far exceeds the ability to characterize these genes. To assist in associating genes with cellular functions, a large-scale bacterial genome deletion approach can be employed to rapidly screen tens to thousands of genes for desired phenotypes. Here, we provide a detailed protocol for the generation of deletions of large segments of bacterial genomes that relies on the activity of a site-specific recombinase. In this procedure, two recombinase recognition target sequences are introduced into known positions of a bacterial genome through single cross-over plasmid integration. Subsequent expression of the site-specific recombinase mediates recombination between the two target sequences, resulting in the excision of the intervening region and its loss from the genome. We further illustrate how this deletion system can be readily adapted to function as a large-scale in vivo cloning procedure, in which the region excised from the genome is captured as a replicative plasmid. We next provide a procedure for the metabolic analysis of bacterial large-scale genome deletion mutants using the Biolog Phenotype MicroArray™ system. Finally, a pipeline is described, and a sample Matlab script is provided, for the integration of the obtained data with a draft metabolic reconstruction for the refinement of the reactions and gene-protein-reaction relationships in a metabolic reconstruction.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

SOBA: sequence ontology bioinformatics analysis.

PubMed

Moore, Barry; Fan, Guozhen; Eilbeck, Karen

2010-07-01

The advent of cheaper, faster sequencing technologies has pushed the task of sequence annotation from the exclusive domain of large-scale multi-national sequencing projects to that of research laboratories and small consortia. The bioinformatics burden placed on these laboratories, some with very little programming experience can be daunting. Fortunately, there exist software libraries and pipelines designed with these groups in mind, to ease the transition from an assembled genome to an annotated and accessible genome resource. We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

Selected Insights from Application of Whole Genome Sequencing for Outbreak Investigations

PubMed Central

Le, Vien Thi Minh; Diep, Binh An

2014-01-01

Purpose of review The advent of high-throughput whole genome sequencing has the potential to revolutionize the conduct of outbreak investigation. Because of its ultimate pathogen strain resolution, whole genome sequencing could augment traditional epidemiologic investigations of infectious disease outbreaks. Recent findings The combination of whole genome sequencing and intensive epidemiologic analysis provided new insights on the sources and transmission dynamics of large-scale epidemics caused by Escherichia coli and Vibrio cholerae, nosocomial outbreaks caused by methicillin-resistant Staphylococcus aureus, Klebsiella pneumonia, and Mycobacterium abscessus, community-centered outbreaks caused by Mycobacterium tuberculosis, and natural disaster-associated outbreak caused by environmentally acquired molds. Summary When combined with traditional epidemiologic investigation, whole genome sequencing has proven useful for elucidating sources and transmission dynamics of disease outbreaks. Development of a fully automated bioinformatics pipeline for analysis of whole genome sequence data is much needed to make this powerful tool more widely accessible. PMID:23856896

Development of self-compressing BLSOM for comprehensive analysis of big sequence data.

PubMed

Kikuchi, Akihito; Ikemura, Toshimichi; Abe, Takashi

2015-01-01

With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM), which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM) for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method's suitability for efficient knowledge discovery from big sequence data.

Successful application of FTA Classic Card technology and use of bacteriophage phi29 DNA polymerase for large-scale field sampling and cloning of complete maize streak virus genomes.

PubMed

Owor, Betty E; Shepherd, Dionne N; Taylor, Nigel J; Edema, Richard; Monjane, Adérito L; Thomson, Jennifer A; Martin, Darren P; Varsani, Arvind

2007-03-01

Leaf samples from 155 maize streak virus (MSV)-infected maize plants were collected from 155 farmers' fields in 23 districts in Uganda in May/June 2005 by leaf-pressing infected samples onto FTA Classic Cards. Viral DNA was successfully extracted from cards stored at room temperature for 9 months. The diversity of 127 MSV isolates was analysed by PCR-generated RFLPs. Six representative isolates having different RFLP patterns and causing either severe, moderate or mild disease symptoms, were chosen for amplification from FTA cards by bacteriophage phi29 DNA polymerase using the TempliPhi system. Full-length genomes were inserted into a cloning vector using a unique restriction enzyme site, and sequenced. The 1.3-kb PCR product amplified directly from FTA-eluted DNA and used for RFLP analysis was also cloned and sequenced. Comparison of cloned whole genome sequences with those of the original PCR products indicated that the correct virus genome had been cloned and that no errors were introduced by the phi29 polymerase. This is the first successful large-scale application of FTA card technology to the field, and illustrates the ease with which large numbers of infected samples can be collected and stored for downstream molecular applications such as diversity analysis and cloning of potentially new virus genomes.

De novo sequencing and characterization of floral transcriptome in two species of buckwheat (Fagopyrum)

PubMed Central

2011-01-01

Background Transcriptome sequencing data has become an integral component of modern genetics, genomics and evolutionary biology. However, despite advances in the technologies of DNA sequencing, such data are lacking for many groups of living organisms, in particular, many plant taxa. We present here the results of transcriptome sequencing for two closely related plant species. These species, Fagopyrum esculentum and F. tataricum, belong to the order Caryophyllales - a large group of flowering plants with uncertain evolutionary relationships. F. esculentum (common buckwheat) is also an important food crop. Despite these practical and evolutionary considerations Fagopyrum species have not been the subject of large-scale sequencing projects. Results Normalized cDNA corresponding to genes expressed in flowers and inflorescences of F. esculentum and F. tataricum was sequenced using the 454 pyrosequencing technology. This resulted in 267 (for F. esculentum) and 229 (F. tataricum) thousands of reads with average length of 341-349 nucleotides. De novo assembly of the reads produced about 25 thousands of contigs for each species, with 7.5-8.2× coverage. Comparative analysis of two transcriptomes demonstrated their overall similarity but also revealed genes that are presumably differentially expressed. Among them are retrotransposon genes and genes involved in sugar biosynthesis and metabolism. Thirteen single-copy genes were used for phylogenetic analysis; the resulting trees are largely consistent with those inferred from multigenic plastid datasets. The sister relationships of the Caryophyllales and asterids now gained high support from nuclear gene sequences. Conclusions 454 transcriptome sequencing and de novo assembly was performed for two congeneric flowering plant species, F. esculentum and F. tataricum. As a result, a large set of cDNA sequences that represent orthologs of known plant genes as well as potential new genes was generated. PMID:21232141

An improved model for whole genome phylogenetic analysis by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees and demonstrates that the improved DFT dissimilarity measure is an efficient and effective similarity measure of DNA sequences. Due to its high efficiency and accuracy, the proposed DFT similarity measure is successfully applied on phylogenetic analysis for individual genes and large whole bacterial genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies

PubMed Central

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets. PMID:25937948

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis

PubMed Central

Yang, Yilong

2017-01-01

Abstract The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Access Array system and 454 sequencing platform. About 24 single-copy or low-copy nuclear genes distributed across the genome were amplified and sequenced from 96 genomic DNA samples representing 16 Fragaria species from diploid (2×) to decaploid (10×), including the most extensive sampling of octoploid taxa yet reported. Individual gene trees were constructed by different tree-building methods. Mosaic genomic structures of diploid Fragaria species consisting of sequences at different phylogenetic positions were observed. Our findings support the presence in octoploid species of genetic signatures from at least five diploid ancestors (F. vesca, F. iinumae, F. bucharica, F. viridis, and at least one additional allele contributor of unknown identity), and questions the extent to which distinct subgenomes are preserved over evolutionary time in the allopolyploid Fragaria species. In addition, our data support divergence between the two wild octoploid species, F. virginiana and F. chiloensis. PMID:29045639

A space-time multifractal analysis on radar rainfall sequences from central Poland

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Deidda, Roberto

2014-05-01

Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).

Revealing Less Derived Nature of Cartilaginous Fish Genomes with Their Evolutionary Time Scale Inferred with Nuclear Genes

PubMed Central

Renz, Adina J.; Meyer, Axel; Kuraku, Shigehiro

2013-01-01

Cartilaginous fishes, divided into Holocephali (chimaeras) and Elasmoblanchii (sharks, rays and skates), occupy a key phylogenetic position among extant vertebrates in reconstructing their evolutionary processes. Their accurate evolutionary time scale is indispensable for better understanding of the relationship between phenotypic and molecular evolution of cartilaginous fishes. However, our current knowledge on the time scale of cartilaginous fish evolution largely relies on estimates using mitochondrial DNA sequences. In this study, making the best use of the still partial, but large-scale sequencing data of cartilaginous fish species, we estimate the divergence times between the major cartilaginous fish lineages employing nuclear genes. By rigorous orthology assessment based on available genomic and transcriptomic sequence resources for cartilaginous fishes, we selected 20 protein-coding genes in the nuclear genome, spanning 2973 amino acid residues. Our analysis based on the Bayesian inference resulted in the mean divergence time of 421 Ma, the late Silurian, for the Holocephali-Elasmobranchii split, and 306 Ma, the late Carboniferous, for the split between sharks and rays/skates. By applying these results and other documented divergence times, we measured the relative evolutionary rate of the Hox A cluster sequences in the cartilaginous fish lineages, which resulted in a lower substitution rate with a factor of at least 2.4 in comparison to tetrapod lineages. The obtained time scale enables mapping phenotypic and molecular changes in a quantitative framework. It is of great interest to corroborate the less derived nature of cartilaginous fish at the molecular level as a genome-wide phenomenon. PMID:23825540

Revealing less derived nature of cartilaginous fish genomes with their evolutionary time scale inferred with nuclear genes.

PubMed

Renz, Adina J; Meyer, Axel; Kuraku, Shigehiro

2013-01-01

Cartilaginous fishes, divided into Holocephali (chimaeras) and Elasmoblanchii (sharks, rays and skates), occupy a key phylogenetic position among extant vertebrates in reconstructing their evolutionary processes. Their accurate evolutionary time scale is indispensable for better understanding of the relationship between phenotypic and molecular evolution of cartilaginous fishes. However, our current knowledge on the time scale of cartilaginous fish evolution largely relies on estimates using mitochondrial DNA sequences. In this study, making the best use of the still partial, but large-scale sequencing data of cartilaginous fish species, we estimate the divergence times between the major cartilaginous fish lineages employing nuclear genes. By rigorous orthology assessment based on available genomic and transcriptomic sequence resources for cartilaginous fishes, we selected 20 protein-coding genes in the nuclear genome, spanning 2973 amino acid residues. Our analysis based on the Bayesian inference resulted in the mean divergence time of 421 Ma, the late Silurian, for the Holocephali-Elasmobranchii split, and 306 Ma, the late Carboniferous, for the split between sharks and rays/skates. By applying these results and other documented divergence times, we measured the relative evolutionary rate of the Hox A cluster sequences in the cartilaginous fish lineages, which resulted in a lower substitution rate with a factor of at least 2.4 in comparison to tetrapod lineages. The obtained time scale enables mapping phenotypic and molecular changes in a quantitative framework. It is of great interest to corroborate the less derived nature of cartilaginous fish at the molecular level as a genome-wide phenomenon.

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.

PubMed

Reid, Jeffrey G; Carroll, Andrew; Veeraraghavan, Narayanan; Dahdouli, Mahmoud; Sundquist, Andreas; English, Adam; Bainbridge, Matthew; White, Simon; Salerno, William; Buhay, Christian; Yu, Fuli; Muzny, Donna; Daly, Richard; Duyk, Geoff; Gibbs, Richard A; Boerwinkle, Eric

2014-01-29

Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.

Large-scale structures of solar wind and dynamics of parameters in them

NASA Astrophysics Data System (ADS)

Yermolaev, Yuri; Lodkina, Irina; Yermolaev, Michael

2017-04-01

On the basis of OMNI dataset and our catalog of large-scale solar wind (SW) phenomena (see web-site ftp://ftp.iki.rssi.ru/pub/omni/ and paper by Yermolaev et al., 2009) we study temporal profile of interplanetary and magnetospheric parameters in following SW phenomena: interplanetary manifestation of coronal mass ejection (ICME) including magnetic cloud (MC) and Ejecta, Sheath—compression region before ICME and corotating interaction region (CIR)—compression region before high-speed stream (HSS) of solar wind. To take into account a possible influence of other SW types, following sequences of phenomena, which include all typical sequences of non-stationary SW events, are analyzed: (1) SW/ CIR/ SW, (2) SW/ IS/ CIR/ SW, (3) SW/ Ejecta/ SW, (4) SW/ Sheath/Ejecta/ SW, (5) SW/ IS/ Sheath/ Ejecta/ SW, (6) SW/ MC/ SW, (7) SW/Sheath/ MC/ SW, (8) SW/ IS/ Sheath/ MC/ SW (where SW is undisturbed solar wind, and IS is interplanetary shock) (Yermolaev et al., 2015) using the method of double superposed epoch analysis for large numbers of events (Yermolaev et al., 2010). Similarities and distinctions of different SW phenomena depending on neighboring SW types and their geoeffectiveness are discussed. The work was supported by the Russian Science Foundation, projects 16-12-10062. References: Yermolaev, Yu. I., N. S. Nikolaeva, I. G. Lodkina, and M. Yu. Yermolaev (2009), Catalog of Large-Scale Solar Wind Phenomena during 1976-2000, Cosmic Research, , Vol. 47, No. 2, pp. 81-94. Yermolaev, Y. I., N. S. Nikolaeva, I. G. Lodkina, and M. Y. Yermolaev (2010), Specific interplanetary conditions for CIR-induced, Sheath-induced, and ICME-induced geomagnetic storms obtained by double superposed epoch analysis, Ann. Geophys., 28, pp. 2177-2186. Yermolaev, Yu. I., I. G. Lodkina, N. S. Nikolaeva, and M. Yu. Yermolaev (2015), Dynamics of large-scale solar wind streams obtained by the double superposed epoch analysis, J. Geophys. Res. Space Physics, 120, doi:10.1002/2015JA021274.

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

Diversity analysis in Cannabis sativa based on large-scale development of expressed sequence tag-derived simple sequence repeat markers.

PubMed

Gao, Chunsheng; Xin, Pengfei; Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis.

Diversity Analysis in Cannabis sativa Based on Large-Scale Development of Expressed Sequence Tag-Derived Simple Sequence Repeat Markers

PubMed Central

Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis. PMID:25329551

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Large-scale horizontal flows from SOUP observations of solar granulation

NASA Astrophysics Data System (ADS)

November, L. J.; Simon, G. W.; Tarbell, T. D.; Title, A. M.; Ferguson, S. H.

1987-09-01

Using high-resolution time-sequence photographs of solar granulation from the SOUP experiment on Spacelab 2 the authors observed large-scale horizontal flows in the solar surface. The measurement method is based upon a local spatial cross correlation analysis. The horizontal motions have amplitudes in the range 300 to 1000 m/s. Radial outflow of granulation from a sunspot penumbra into the surrounding photosphere is a striking new discovery. Both the supergranulation pattern and cellular structures having the scale of mesogranulation are seen. The vertical flows that are inferred by continuity of mass from these observed horizontal flows have larger upflow amplitudes in cell centers than downflow amplitudes at cell boundaries.

A generic, cost-effective, and scalable cell lineage analysis platform

PubMed Central

Biezuner, Tamir; Spiro, Adam; Raz, Ofir; Amir, Shiran; Milo, Lilach; Adar, Rivka; Chapal-Ilani, Noa; Berman, Veronika; Fried, Yael; Ainbinder, Elena; Cohen, Galit; Barr, Haim M.; Halaban, Ruth; Shapiro, Ehud

2016-01-01

Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery. PMID:27558250

Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

USDA-ARS?s Scientific Manuscript database

Copy number variants (CNV) are large scale duplications or deletions of genomic sequence that are caused by a diverse set of molecular phenomena that are distinct from single nucleotide polymorphism (SNP) formation. Due to their different mechanisms of formation, CNVs are often difficult to track us...

Development of 5123 Intron-Length Polymorphic Markers for Large-Scale Genotyping Applications in Foxtail Millet

PubMed Central

Muthamilarasan, Mehanathan; Venkata Suresh, B.; Pandey, Garima; Kumari, Kajal; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

Generating genomic resources in terms of molecular markers is imperative in molecular breeding for crop improvement. Though development and application of microsatellite markers in large-scale was reported in the model crop foxtail millet, no such large-scale study was conducted for intron-length polymorphic (ILP) markers. Considering this, we developed 5123 ILP markers, of which 4049 were physically mapped onto 9 chromosomes of foxtail millet. BLAST analysis of 5123 expressed sequence tags (ESTs) suggested the function for ∼71.5% ESTs and grouped them into 5 different functional categories. About 440 selected primer pairs representing the foxtail millet genome and the different functional groups showed high-level of cross-genera amplification at an average of ∼85% in eight millets and five non-millet species. The efficacy of the ILP markers for distinguishing the foxtail millet is demonstrated by observed heterozygosity (0.20) and Nei's average gene diversity (0.22). In silico comparative mapping of physically mapped ILP markers demonstrated substantial percentage of sequence-based orthology and syntenic relationship between foxtail millet chromosomes and sorghum (∼50%), maize (∼46%), rice (∼21%) and Brachypodium (∼21%) chromosomes. Hence, for the first time, we developed large-scale ILP markers in foxtail millet and demonstrated their utility in germplasm characterization, transferability, phylogenetics and comparative mapping studies in millets and bioenergy grass species. PMID:24086082

Mantis: A Fast, Small, and Exact Large-Scale Sequence-Search Index.

PubMed

Pandey, Prashant; Almodaresi, Fatemeh; Bender, Michael A; Ferdman, Michael; Johnson, Rob; Patro, Rob

2018-06-18

Sequence-level searches on large collections of RNA sequencing experiments, such as the NCBI Sequence Read Archive (SRA), would enable one to ask many questions about the expression or variation of a given transcript in a population. Existing approaches, such as the sequence Bloom tree, suffer from fundamental limitations of the Bloom filter, resulting in slow build and query times, less-than-optimal space usage, and potentially large numbers of false-positives. This paper introduces Mantis, a space-efficient system that uses new data structures to index thousands of raw-read experiments and facilitates large-scale sequence searches. In our evaluation, index construction with Mantis is 6× faster and yields a 20% smaller index than the state-of-the-art split sequence Bloom tree (SSBT). For queries, Mantis is 6-108× faster than SSBT and has no false-positives or -negatives. For example, Mantis was able to search for all 200,400 known human transcripts in an index of 2,652 RNA sequencing experiments in 82 min; SSBT took close to 4 days. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-06-01

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

Lessons learned from implementing a national infrastructure in Sweden for storage and analysis of next-generation sequencing data

PubMed Central

2013-01-01

Analyzing and storing data and results from next-generation sequencing (NGS) experiments is a challenging task, hampered by ever-increasing data volumes and frequent updates of analysis methods and tools. Storage and computation have grown beyond the capacity of personal computers and there is a need for suitable e-infrastructures for processing. Here we describe UPPNEX, an implementation of such an infrastructure, tailored to the needs of data storage and analysis of NGS data in Sweden serving various labs and multiple instruments from the major sequencing technology platforms. UPPNEX comprises resources for high-performance computing, large-scale and high-availability storage, an extensive bioinformatics software suite, up-to-date reference genomes and annotations, a support function with system and application experts as well as a web portal and support ticket system. UPPNEX applications are numerous and diverse, and include whole genome-, de novo- and exome sequencing, targeted resequencing, SNP discovery, RNASeq, and methylation analysis. There are over 300 projects that utilize UPPNEX and include large undertakings such as the sequencing of the flycatcher and Norwegian spruce. We describe the strategic decisions made when investing in hardware, setting up maintenance and support, allocating resources, and illustrate major challenges such as managing data growth. We conclude with summarizing our experiences and observations with UPPNEX to date, providing insights into the successful and less successful decisions made. PMID:23800020

Defining the transcriptome assembly and its use for genome dynamics and transcriptome profiling studies in pigeonpea (Cajanus cajan L.).

PubMed

Dubey, Anuja; Farmer, Andrew; Schlueter, Jessica; Cannon, Steven B; Abernathy, Brian; Tuteja, Reetu; Woodward, Jimmy; Shah, Trushar; Mulasmanovic, Benjamin; Kudapa, Himabindu; Raju, Nikku L; Gothalwal, Ragini; Pande, Suresh; Xiao, Yongli; Town, Chris D; Singh, Nagendra K; May, Gregory D; Jackson, Scott; Varshney, Rajeev K

2011-06-01

This study reports generation of large-scale genomic resources for pigeonpea, a so-called 'orphan crop species' of the semi-arid tropic regions. FLX/454 sequencing carried out on a normalized cDNA pool prepared from 31 tissues produced 494 353 short transcript reads (STRs). Cluster analysis of these STRs, together with 10 817 Sanger ESTs, resulted in a pigeonpea trancriptome assembly (CcTA) comprising of 127 754 tentative unique sequences (TUSs). Functional analysis of these TUSs highlights several active pathways and processes in the sampled tissues. Comparison of the CcTA with the soybean genome showed similarity to 10 857 and 16 367 soybean gene models (depending on alignment methods). Additionally, Illumina 1G sequencing was performed on Fusarium wilt (FW)- and sterility mosaic disease (SMD)-challenged root tissues of 10 resistant and susceptible genotypes. More than 160 million sequence tags were used to identify FW- and SMD-responsive genes. Sequence analysis of CcTA and the Illumina tags identified a large new set of markers for use in genetics and breeding, including 8137 simple sequence repeats, 12 141 single-nucleotide polymorphisms and 5845 intron-spanning regions. Genomic resources developed in this study should be useful for basic and applied research, not only for pigeonpea improvement but also for other related, agronomically important legumes.

Large-scale transcriptome sequencing and gene analyses in the crab-eating macaque (Macaca fascicularis) for biomedical research

PubMed Central

2012-01-01

Background As a human replacement, the crab-eating macaque (Macaca fascicularis) is an invaluable non-human primate model for biomedical research, but the lack of genetic information on this primate has represented a significant obstacle for its broader use. Results Here, we sequenced the transcriptome of 16 tissues originated from two individuals of crab-eating macaque (male and female), and identified genes to resolve the main obstacles for understanding the biological response of the crab-eating macaque. From 4 million reads with 1.4 billion base sequences, 31,786 isotigs containing genes similar to those of humans, 12,672 novel isotigs, and 348,160 singletons were identified using the GS FLX sequencing method. Approximately 86% of human genes were represented among the genes sequenced in this study. Additionally, 175 tissue-specific transcripts were identified, 81 of which were experimentally validated. In total, 4,314 alternative splicing (AS) events were identified and analyzed. Intriguingly, 10.4% of AS events were associated with transposable element (TE) insertions. Finally, investigation of TE exonization events and evolutionary analysis were conducted, revealing interesting phenomena of human-specific amplified trends in TE exonization events. Conclusions This report represents the first large-scale transcriptome sequencing and genetic analyses of M. fascicularis and could contribute to its utility for biomedical research and basic biology. PMID:22554259

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.

Advances in DNA sequencing technologies for high resolution HLA typing.

PubMed

Cereb, Nezih; Kim, Hwa Ran; Ryu, Jaejun; Yang, Soo Young

2015-12-01

This communication describes our experience in large-scale G group-level high resolution HLA typing using three different DNA sequencing platforms - ABI 3730 xl, Illumina MiSeq and PacBio RS II. Recent advances in DNA sequencing technologies, so-called next generation sequencing (NGS), have brought breakthroughs in deciphering the genetic information in all living species at a large scale and at an affordable level. The NGS DNA indexing system allows sequencing multiple genes for large number of individuals in a single run. Our laboratory has adopted and used these technologies for HLA molecular testing services. We found that each sequencing technology has its own strengths and weaknesses, and their sequencing performances complement each other. HLA genes are highly complex and genotyping them is quite challenging. Using these three sequencing platforms, we were able to meet all requirements for G group-level high resolution and high volume HLA typing. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Applications of species accumulation curves in large-scale biological data analysis.

PubMed

Deng, Chao; Daley, Timothy; Smith, Andrew D

2015-09-01

The species accumulation curve, or collector's curve, of a population gives the expected number of observed species or distinct classes as a function of sampling effort. Species accumulation curves allow researchers to assess and compare diversity across populations or to evaluate the benefits of additional sampling. Traditional applications have focused on ecological populations but emerging large-scale applications, for example in DNA sequencing, are orders of magnitude larger and present new challenges. We developed a method to estimate accumulation curves for predicting the complexity of DNA sequencing libraries. This method uses rational function approximations to a classical non-parametric empirical Bayes estimator due to Good and Toulmin [Biometrika, 1956, 43, 45-63]. Here we demonstrate how the same approach can be highly effective in other large-scale applications involving biological data sets. These include estimating microbial species richness, immune repertoire size, and k -mer diversity for genome assembly applications. We show how the method can be modified to address populations containing an effectively infinite number of species where saturation cannot practically be attained. We also introduce a flexible suite of tools implemented as an R package that make these methods broadly accessible.

Applications of species accumulation curves in large-scale biological data analysis

PubMed Central

Deng, Chao; Daley, Timothy; Smith, Andrew D

2016-01-01

The species accumulation curve, or collector’s curve, of a population gives the expected number of observed species or distinct classes as a function of sampling effort. Species accumulation curves allow researchers to assess and compare diversity across populations or to evaluate the benefits of additional sampling. Traditional applications have focused on ecological populations but emerging large-scale applications, for example in DNA sequencing, are orders of magnitude larger and present new challenges. We developed a method to estimate accumulation curves for predicting the complexity of DNA sequencing libraries. This method uses rational function approximations to a classical non-parametric empirical Bayes estimator due to Good and Toulmin [Biometrika, 1956, 43, 45–63]. Here we demonstrate how the same approach can be highly effective in other large-scale applications involving biological data sets. These include estimating microbial species richness, immune repertoire size, and k-mer diversity for genome assembly applications. We show how the method can be modified to address populations containing an effectively infinite number of species where saturation cannot practically be attained. We also introduce a flexible suite of tools implemented as an R package that make these methods broadly accessible. PMID:27252899

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE PAGES

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew; ...

2015-08-13

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

BactoGeNIE: a large-scale comparative genome visualization for big displays

PubMed Central

2015-01-01

Background The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. Results In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. Conclusions BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics. PMID:26329021

BactoGeNIE: A large-scale comparative genome visualization for big displays

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

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

Debugging and Analysis of Large-Scale Parallel Programs

DTIC Science & Technology

1989-09-01

Przybylski, T. Riordan , C. Rowen, and D. Van’t Hof, "A CMOS RISC Processor with Integrated System Functions," In Proc. of the 1986 COMPCON. IEEE, March 1986...Sequencers," Communications of the ACM, 22(2):115-123, 1979. 115 [Richardson, 1988] Rick Richardson, "Dhrystone 2.1 Benchmark," Usenet Distribution

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Global MLST of Salmonella Typhi Revisited in Post-genomic Era: Genetic Conservation, Population Structure, and Comparative Genomics of Rare Sequence Types.

PubMed

Yap, Kien-Pong; Ho, Wing S; Gan, Han M; Chai, Lay C; Thong, Kwai L

2016-01-01

Typhoid fever, caused by Salmonella enterica serovar Typhi, remains an important public health burden in Southeast Asia and other endemic countries. Various genotyping methods have been applied to study the genetic variations of this human-restricted pathogen. Multilocus sequence typing (MLST) is one of the widely accepted methods, and recently, there is a growing interest in the re-application of MLST in the post-genomic era. In this study, we provide the global MLST distribution of S. Typhi utilizing both publicly available 1,826 S. Typhi genome sequences in addition to performing conventional MLST on S. Typhi strains isolated from various endemic regions spanning over a century. Our global MLST analysis confirms the predominance of two sequence types (ST1 and ST2) co-existing in the endemic regions. Interestingly, S. Typhi strains with ST8 are currently confined within the African continent. Comparative genomic analyses of ST8 and other rare STs with genomes of ST1/ST2 revealed unique mutations in important virulence genes such as flhB, sipC, and tviD that may explain the variations that differentiate between seemingly successful (widespread) and unsuccessful (poor dissemination) S. Typhi populations. Large scale whole-genome phylogeny demonstrated evidence of phylogeographical structuring and showed that ST8 may have diverged from the earlier ancestral population of ST1 and ST2, which later lost some of its fitness advantages, leading to poor worldwide dissemination. In response to the unprecedented increase in genomic data, this study demonstrates and highlights the utility of large-scale genome-based MLST as a quick and effective approach to narrow the scope of in-depth comparative genomic analysis and consequently provide new insights into the fine scale of pathogen evolution and population structure.

Translational bioinformatics in the cloud: an affordable alternative

PubMed Central

2010-01-01

With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine. PMID:20691073

Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

PubMed

Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

2016-12-01

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures. © 2016 The Protein Society.

Homology and phylogeny and their automated inference

NASA Astrophysics Data System (ADS)

Fuellen, Georg

2008-06-01

The analysis of the ever-increasing amount of biological and biomedical data can be pushed forward by comparing the data within and among species. For example, an integrative analysis of data from the genome sequencing projects for various species traces the evolution of the genomes and identifies conserved and innovative parts. Here, I review the foundations and advantages of this “historical” approach and evaluate recent attempts at automating such analyses. Biological data is comparable if a common origin exists (homology), as is the case for members of a gene family originating via duplication of an ancestral gene. If the family has relatives in other species, we can assume that the ancestral gene was present in the ancestral species from which all the other species evolved. In particular, describing the relationships among the duplicated biological sequences found in the various species is often possible by a phylogeny, which is more informative than homology statements. Detecting and elaborating on common origins may answer how certain biological sequences developed, and predict what sequences are in a particular species and what their function is. Such knowledge transfer from sequences in one species to the homologous sequences of the other is based on the principle of ‘my closest relative looks and behaves like I do’, often referred to as ‘guilt by association’. To enable knowledge transfer on a large scale, several automated ‘phylogenomics pipelines’ have been developed in recent years, and seven of these will be described and compared. Overall, the examples in this review demonstrate that homology and phylogeny analyses, done on a large (and automated) scale, can give insights into function in biology and biomedicine.

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.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Construction of a plant-transformation-competent BIBAC library and genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.)

PubMed Central

2013-01-01

Background Cotton, one of the world’s leading crops, is important to the world’s textile and energy industries, and is a model species for studies of plant polyploidization, cellulose biosynthesis and cell wall biogenesis. Here, we report the construction of a plant-transformation-competent binary bacterial artificial chromosome (BIBAC) library and comparative genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.) with one of its diploid putative progenitor species, G. raimondii Ulbr. Results We constructed the cotton BIBAC library in a vector competent for high-molecular-weight DNA transformation in different plant species through either Agrobacterium or particle bombardment. The library contains 76,800 clones with an average insert size of 135 kb, providing an approximate 99% probability of obtaining at least one positive clone from the library using a single-copy probe. The quality and utility of the library were verified by identifying BIBACs containing genes important for fiber development, fiber cellulose biosynthesis, seed fatty acid metabolism, cotton-nematode interaction, and bacterial blight resistance. In order to gain an insight into the Upland cotton genome and its relationship with G. raimondii, we sequenced nearly 10,000 BIBAC ends (BESs) randomly selected from the library, generating approximately one BES for every 250 kb along the Upland cotton genome. The retroelement Gypsy/DIRS1 family predominates in the Upland cotton genome, accounting for over 77% of all transposable elements. From the BESs, we identified 1,269 simple sequence repeats (SSRs), of which 1,006 were new, thus providing additional markers for cotton genome research. Surprisingly, comparative sequence analysis showed that Upland cotton is much more diverged from G. raimondii at the genomic sequence level than expected. There seems to be no significant difference between the relationships of the Upland cotton D- and A-subgenomes with the G. raimondii genome, even though G. raimondii contains a D genome (D5). Conclusions The library represents the first BIBAC library in cotton and related species, thus providing tools useful for integrative physical mapping, large-scale genome sequencing and large-scale functional analysis of the Upland cotton genome. Comparative sequence analysis provides insights into the Upland cotton genome, and a possible mechanism underlying the divergence and evolution of polyploid Upland cotton from its diploid putative progenitor species, G. raimondii. PMID:23537070

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System.

PubMed

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-08-18

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

Scaling effects in the impact response of graphite-epoxy composite beams

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.

1989-01-01

In support of crashworthiness studies on composite airframes and substructure, an experimental and analytical study was conducted to characterize size effects in the large deflection response of scale model graphite-epoxy beams subjected to impact. Scale model beams of 1/2, 2/3, 3/4, 5/6, and full scale were constructed of four different laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic. The beam specimens were subjected to eccentric axial impact loads which were scaled to provide homologous beam responses. Comparisons of the load and strain time histories between the scale model beams and the prototype should verify the scale law and demonstrate the use of scale model testing for determining impact behavior of composite structures. The nonlinear structural analysis finite element program DYCAST (DYnamic Crash Analysis of STructures) was used to model the beam response. DYCAST analysis predictions of beam strain response are compared to experimental data and the results are presented.

A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis.

PubMed

Yang, Yilong; Davis, Thomas M

2017-12-01

The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Access Array system and 454 sequencing platform. About 24 single-copy or low-copy nuclear genes distributed across the genome were amplified and sequenced from 96 genomic DNA samples representing 16 Fragaria species from diploid (2×) to decaploid (10×), including the most extensive sampling of octoploid taxa yet reported. Individual gene trees were constructed by different tree-building methods. Mosaic genomic structures of diploid Fragaria species consisting of sequences at different phylogenetic positions were observed. Our findings support the presence in octoploid species of genetic signatures from at least five diploid ancestors (F. vesca, F. iinumae, F. bucharica, F. viridis, and at least one additional allele contributor of unknown identity), and questions the extent to which distinct subgenomes are preserved over evolutionary time in the allopolyploid Fragaria species. In addition, our data support divergence between the two wild octoploid species, F. virginiana and F. chiloensis. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

Preparation of fosmid libraries and functional metagenomic analysis of microbial community DNA.

PubMed

Martínez, Asunción; Osburne, Marcia S

2013-01-01

One of the most important challenges in contemporary microbial ecology is to assign a functional role to the large number of novel genes discovered through large-scale sequencing of natural microbial communities that lack similarity to genes of known function. Functional screening of metagenomic libraries, that is, screening environmental DNA clones for the ability to confer an activity of interest to a heterologous bacterial host, is a promising approach for bridging the gap between metagenomic DNA sequencing and functional characterization. Here, we describe methods for isolating environmental DNA and constructing metagenomic fosmid libraries, as well as methods for designing and implementing successful functional screens of such libraries. © 2013 Elsevier Inc. All rights reserved.

New convergence results for the scaled gradient projection method

NASA Astrophysics Data System (ADS)

Bonettini, S.; Prato, M.

2015-09-01

The aim of this paper is to deepen the convergence analysis of the scaled gradient projection (SGP) method, proposed by Bonettini et al in a recent paper for constrained smooth optimization. The main feature of SGP is the presence of a variable scaling matrix multiplying the gradient, which may change at each iteration. In the last few years, extensive numerical experimentation showed that SGP equipped with a suitable choice of the scaling matrix is a very effective tool for solving large scale variational problems arising in image and signal processing. In spite of the very reliable numerical results observed, only a weak convergence theorem is provided establishing that any limit point of the sequence generated by SGP is stationary. Here, under the only assumption that the objective function is convex and that a solution exists, we prove that the sequence generated by SGP converges to a minimum point, if the scaling matrices sequence satisfies a simple and implementable condition. Moreover, assuming that the gradient of the objective function is Lipschitz continuous, we are also able to prove the {O}(1/k) convergence rate with respect to the objective function values. Finally, we present the results of a numerical experience on some relevant image restoration problems, showing that the proposed scaling matrix selection rule performs well also from the computational point of view.

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data.

PubMed

Devlin, Joseph C; Battaglia, Thomas; Blaser, Martin J; Ruggles, Kelly V

2018-06-25

Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Genomic Sequence around Butterfly Wing Development Genes: Annotation and Comparative Analysis

PubMed Central

Conceição, Inês C.; Long, Anthony D.; Gruber, Jonathan D.; Beldade, Patrícia

2011-01-01

Background Analysis of genomic sequence allows characterization of genome content and organization, and access beyond gene-coding regions for identification of functional elements. BAC libraries, where relatively large genomic regions are made readily available, are especially useful for species without a fully sequenced genome and can increase genomic coverage of phylogenetic and biological diversity. For example, no butterfly genome is yet available despite the unique genetic and biological properties of this group, such as diversified wing color patterns. The evolution and development of these patterns is being studied in a few target species, including Bicyclus anynana, where a whole-genome BAC library allows targeted access to large genomic regions. Methodology/Principal Findings We characterize ∼1.3 Mb of genomic sequence around 11 selected genes expressed in B. anynana developing wings. Extensive manual curation of in silico predictions, also making use of a large dataset of expressed genes for this species, identified repetitive elements and protein coding sequence, and highlighted an expansion of Alcohol dehydrogenase genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations) and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes). Conclusions The general properties and organization of the available B. anynana genomic sequence are similar to the lepidopteran reference, despite the more than 140 MY divergence. Our results lay the groundwork for further studies of new interesting findings in relation to both coding and non-coding sequence: 1) the Alcohol dehydrogenase expansion with higher similarity between the five tandemly-repeated B. anynana paralogs than with the corresponding B. mori orthologs, and 2) the high conservation of non-coding sequence around the genes wingless and Ecdysone receptor, both involved in multiple developmental processes including wing pattern formation. PMID:21909358

Analysis of ERTS-1 imagery and its application to evaluation of Wyoming's natural resources

NASA Technical Reports Server (NTRS)

Houston, R. S. (Principal Investigator); Marrs, R. W.

1973-01-01

The author has identified the following significant results. Significant results of the Wyoming ERTS-1 investigation during the first six months (July-December 1972) included: (1) successful segregation of Precambrian metasedimentary/metavolcanic rocks from igneous rocks, (2) discovery of iron formation within the metasedimentary sequence, (3) mapping of previously unreported tectonic elements of major significance, (4) successful mapping of large scale fracture systems of the Wind River Mountains, (5) successful distinction of some metamorphic, igneous, and sedimentary lithologies by color additive viewing, (6) mapping of large scale glacial features, and (7) development of techniques for mapping small urban areas.

Molecular epidemiology of Oropouche virus, Brazil.

PubMed

Vasconcelos, Helena Baldez; Nunes, Márcio R T; Casseb, Lívia M N; Carvalho, Valéria L; Pinto da Silva, Eliana V; Silva, Mayra; Casseb, Samir M M; Vasconcelos, Pedro F C

2011-05-01

Oropouche virus (OROV) is the causative agent of Oropouche fever, an urban febrile arboviral disease widespread in South America, with >30 epidemics reported in Brazil and other Latin American countries during 1960-2009. To describe the molecular epidemiology of OROV, we analyzed the entire N gene sequences (small RNA) of 66 strains and 35 partial Gn (medium RNA) and large RNA gene sequences. Distinct patterns of OROV strain clustered according to N, Gn, and large gene sequences, which suggests that each RNA segment had a different evolutionary history and that the classification in genotypes must consider the genetic information for all genetic segments. Finally, time-scale analysis based on the N gene showed that OROV emerged in Brazil ≈223 years ago and that genotype I (based on N gene data) was responsible for the emergence of all other genotypes and for virus dispersal.

GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics.

PubMed

Ricke, Darrell O; Shcherbina, Anna; Michaleas, Adam; Fremont-Smith, Philip

2018-04-16

High-throughput sequencing (HTS) of single nucleotide polymorphisms (SNPs) enables additional DNA forensic capabilities not attainable using traditional STR panels. However, the inclusion of sets of loci selected for mixture analysis, extended kinship, phenotype, biogeographic ancestry prediction, etc., can result in large panel sizes that are difficult to analyze in a rapid fashion. GrigoraSNP was developed to address the allele-calling bottleneck that was encountered when analyzing SNP panels with more than 5000 loci using HTS. GrigoraSNPs uses a MapReduce parallel data processing on multiple computational threads plus a novel locus-identification hashing strategy leveraging target sequence tags. This tool optimizes the SNP calling module of the DNA analysis pipeline with runtimes that scale linearly with the number of HTS reads. Results are compared with SNP analysis pipelines implemented with SAMtools and GATK. GrigoraSNPs removes a computational bottleneck for processing forensic samples with large HTS SNP panels. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Analysis and Functional Annotation of an Expressed Sequence Tag Collection for Tropical Crop Sugarcane

PubMed Central

Vettore, André L.; da Silva, Felipe R.; Kemper, Edson L.; Souza, Glaucia M.; da Silva, Aline M.; Ferro, Maria Inês T.; Henrique-Silva, Flavio; Giglioti, Éder A.; Lemos, Manoel V.F.; Coutinho, Luiz L.; Nobrega, Marina P.; Carrer, Helaine; França, Suzelei C.; Bacci, Maurício; Goldman, Maria Helena S.; Gomes, Suely L.; Nunes, Luiz R.; Camargo, Luis E.A.; Siqueira, Walter J.; Van Sluys, Marie-Anne; Thiemann, Otavio H.; Kuramae, Eiko E.; Santelli, Roberto V.; Marino, Celso L.; Targon, Maria L.P.N.; Ferro, Jesus A.; Silveira, Henrique C.S.; Marini, Danyelle C.; Lemos, Eliana G.M.; Monteiro-Vitorello, Claudia B.; Tambor, José H.M.; Carraro, Dirce M.; Roberto, Patrícia G.; Martins, Vanderlei G.; Goldman, Gustavo H.; de Oliveira, Regina C.; Truffi, Daniela; Colombo, Carlos A.; Rossi, Magdalena; de Araujo, Paula G.; Sculaccio, Susana A.; Angella, Aline; Lima, Marleide M.A.; de Rosa, Vicente E.; Siviero, Fábio; Coscrato, Virginia E.; Machado, Marcos A.; Grivet, Laurent; Di Mauro, Sonia M.Z.; Nobrega, Francisco G.; Menck, Carlos F.M.; Braga, Marilia D.V.; Telles, Guilherme P.; Cara, Frank A.A.; Pedrosa, Guilherme; Meidanis, João; Arruda, Paulo

2003-01-01

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged. PMID:14613979

Metasecretome-selective phage display approach for mining the functional potential of a rumen microbial community.

PubMed

Ciric, Milica; Moon, Christina D; Leahy, Sinead C; Creevey, Christopher J; Altermann, Eric; Attwood, Graeme T; Rakonjac, Jasna; Gagic, Dragana

2014-05-12

In silico, secretome proteins can be predicted from completely sequenced genomes using various available algorithms that identify membrane-targeting sequences. For metasecretome (collection of surface, secreted and transmembrane proteins from environmental microbial communities) this approach is impractical, considering that the metasecretome open reading frames (ORFs) comprise only 10% to 30% of total metagenome, and are poorly represented in the dataset due to overall low coverage of metagenomic gene pool, even in large-scale projects. By combining secretome-selective phage display and next-generation sequencing, we focused the sequence analysis of complex rumen microbial community on the metasecretome component of the metagenome. This approach achieved high enrichment (29 fold) of secreted fibrolytic enzymes from the plant-adherent microbial community of the bovine rumen. In particular, we identified hundreds of heretofore rare modules belonging to cellulosomes, cell-surface complexes specialised for recognition and degradation of the plant fibre. As a method, metasecretome phage display combined with next-generation sequencing has a power to sample the diversity of low-abundance surface and secreted proteins that would otherwise require exceptionally large metagenomic sequencing projects. As a resource, metasecretome display library backed by the dataset obtained by next-generation sequencing is ready for i) affinity selection by standard phage display methodology and ii) easy purification of displayed proteins as part of the virion for individual functional analysis.

Sequencing, Analysis, and Annotation of Expressed Sequence Tags for Camelus dromedarius

PubMed Central

Al-Swailem, Abdulaziz M.; Shehata, Maher M.; Abu-Duhier, Faisel M.; Al-Yamani, Essam J.; Al-Busadah, Khalid A.; Al-Arawi, Mohammed S.; Al-Khider, Ali Y.; Al-Muhaimeed, Abdullah N.; Al-Qahtani, Fahad H.; Manee, Manee M.; Al-Shomrani, Badr M.; Al-Qhtani, Saad M.; Al-Harthi, Amer S.; Akdemir, Kadir C.; Otu, Hasan H.

2010-01-01

Despite its economical, cultural, and biological importance, there has not been a large scale sequencing project to date for Camelus dromedarius. With the goal of sequencing complete DNA of the organism, we first established and sequenced camel EST libraries, generating 70,272 reads. Following trimming, chimera check, repeat masking, cluster and assembly, we obtained 23,602 putative gene sequences, out of which over 4,500 potentially novel or fast evolving gene sequences do not carry any homology to other available genomes. Functional annotation of sequences with similarities in nucleotide and protein databases has been obtained using Gene Ontology classification. Comparison to available full length cDNA sequences and Open Reading Frame (ORF) analysis of camel sequences that exhibit homology to known genes show more than 80% of the contigs with an ORF>300 bp and ∼40% hits extending to the start codons of full length cDNAs suggesting successful characterization of camel genes. Similarity analyses are done separately for different organisms including human, mouse, bovine, and rat. Accompanying web portal, CAGBASE (http://camel.kacst.edu.sa/), hosts a relational database containing annotated EST sequences and analysis tools with possibility to add sequences from public domain. We anticipate our results to provide a home base for genomic studies of camel and other comparative studies enabling a starting point for whole genome sequencing of the organism. PMID:20502665

De novo sequencing, assembly and analysis of eight different transcriptomes from the Malayan pangolin

PubMed Central

Mohamed Yusoff, Aini; Tan, Tze King; Hari, Ranjeev; Koepfli, Klaus-Peter; Wee, Wei Yee; Antunes, Agostinho; Sitam, Frankie Thomas; Rovie-Ryan, Jeffrine Japning; Karuppannan, Kayal Vizi; Wong, Guat Jah; Lipovich, Leonard; Warren, Wesley C.; O’Brien, Stephen J.; Choo, Siew Woh

2016-01-01

Pangolins are scale-covered mammals, containing eight endangered species. Maintaining pangolins in captivity is a significant challenge, in part because little is known about their genetics. Here we provide the first large-scale sequencing of the critically endangered Manis javanica transcriptomes from eight different organs using Illumina HiSeq technology, yielding ~75 Giga bases and 89,754 unigenes. We found some unigenes involved in the insect hormone biosynthesis pathway and also 747 lipids metabolism-related unigenes that may be insightful to understand the lipid metabolism system in pangolins. Comparative analysis between M. javanica and other mammals revealed many pangolin-specific genes significantly over-represented in stress-related processes, cell proliferation and external stimulus, probably reflecting the traits and adaptations of the analyzed pregnant female M. javanica. Our study provides an invaluable resource for future functional works that may be highly relevant for the conservation of pangolins. PMID:27618997

Genome-wide association analysis based on multiple imputation with low-depth GBS data: application to biofuel traits in reed canarygrass

USDA-ARS?s Scientific Manuscript database

Genotyping-by-sequencing allows for large-scale genetic analyses in plant species with no reference genome, creating the challenge of sound inference in the presence of uncertain genotypes. Here we report an imputation-based genome-wide association study (GWAS) in reed canarygrass (Phalaris arundina...

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.

Lithofacies control in detrital zircon provenance studies: Insights from the Cretaceous Methow basin, southern Canadian Cordillera

USGS Publications Warehouse

DeGraaff-Surpless, K.; Mahoney, J.B.; Wooden, J.L.; McWilliams, M.O.

2003-01-01

High-frequency sampling for detrital zircon analysis can provide a detailed record of fine-scale basin evolution by revealing the temporal and spatial variability of detrital zircon ages within clastic sedimentary successions. This investigation employed detailed sampling of two sedimentary successions in the Methow/Methow-Tyaughton basin of the southern Canadian Cordillera to characterize the heterogeneity of detrital zircon signatures within single lithofacies and assess the applicability of detrital zircon analysis in distinguishing fine-scale provenance changes not apparent in lithologic analysis of the strata. The Methow/Methow-Tyaughton basin contains two distinct stratigraphic sequences of middle Albian to Santonian clastic sedimentary rocks: submarine-fan deposits of the Harts Pass Formation/Jackass Mountain Group and fluvial deposits of the Winthrop Formation. Although both stratigraphic sequences displayed consistent ranges in detrital zircon ages on a broad scale, detailed sampling within each succession revealed heterogeneity in the detrital zircon age distributions that was systematic and predictable in the turbidite succession but unpredictable in the fluvial succession. These results suggest that a high-density sampling approach permits interpretation of finescale changes within a lithologically uniform turbiditic sedimentary succession, but heterogeneity within fluvial systems may be too large and unpredictable to permit accurate fine-scale characterization of the evolution of source regions. The robust composite detrital zircon age signature developed for these two successions permits comparison of the Methow/Methow-Tyaughton basin age signature with known plutonic source-rock ages from major plutonic belts throughout the Cretaceous North American margin. The Methow/Methow-Tyaughton basin detrital zircon age signature matches best with source regions in the southern Canadian Cordillera, requiring that the basin developed in close proximity to the southern Canadian Cordillera and providing evidence against large-scale dextral translation of the Methow terrane.

Insights from Human/Mouse genome comparisons

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

Pennacchio, Len A.

2003-03-30

Large-scale public genomic sequencing efforts have provided a wealth of vertebrate sequence data poised to provide insights into mammalian biology. These include deep genomic sequence coverage of human, mouse, rat, zebrafish, and two pufferfish (Fugu rubripes and Tetraodon nigroviridis) (Aparicio et al. 2002; Lander et al. 2001; Venter et al. 2001; Waterston et al. 2002). In addition, a high-priority has been placed on determining the genomic sequence of chimpanzee, dog, cow, frog, and chicken (Boguski 2002). While only recently available, whole genome sequence data have provided the unique opportunity to globally compare complete genome contents. Furthermore, the shared evolutionary ancestrymore » of vertebrate species has allowed the development of comparative genomic approaches to identify ancient conserved sequences with functionality. Accordingly, this review focuses on the initial comparison of available mammalian genomes and describes various insights derived from such analysis.« less

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline

PubMed Central

2014-01-01

Background Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. Results To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. Conclusions By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples. PMID:24475911

Wheat EST resources for functional genomics of abiotic stress

PubMed Central

Houde, Mario; Belcaid, Mahdi; Ouellet, François; Danyluk, Jean; Monroy, Antonio F; Dryanova, Ani; Gulick, Patrick; Bergeron, Anne; Laroche, André; Links, Matthew G; MacCarthy, Luke; Crosby, William L; Sarhan, Fathey

2006-01-01

Background Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. Results We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. Conclusion We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals. PMID:16772040

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

A numerical formulation and algorithm for limit and shakedown analysis of large-scale elastoplastic structures

NASA Astrophysics Data System (ADS)

Peng, Heng; Liu, Yinghua; Chen, Haofeng

2018-05-01

In this paper, a novel direct method called the stress compensation method (SCM) is proposed for limit and shakedown analysis of large-scale elastoplastic structures. Without needing to solve the specific mathematical programming problem, the SCM is a two-level iterative procedure based on a sequence of linear elastic finite element solutions where the global stiffness matrix is decomposed only once. In the inner loop, the static admissible residual stress field for shakedown analysis is constructed. In the outer loop, a series of decreasing load multipliers are updated to approach to the shakedown limit multiplier by using an efficient and robust iteration control technique, where the static shakedown theorem is adopted. Three numerical examples up to about 140,000 finite element nodes confirm the applicability and efficiency of this method for two-dimensional and three-dimensional elastoplastic structures, with detailed discussions on the convergence and the accuracy of the proposed algorithm.

CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects

PubMed Central

Ameur, Adam; Bunikis, Ignas; Enroth, Stefan; Gyllensten, Ulf

2014-01-01

CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome- (WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server. Database URL: https://github.com/UppsalaGenomeCenter/CanvasDB PMID:25281234

CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects.

PubMed

Ameur, Adam; Bunikis, Ignas; Enroth, Stefan; Gyllensten, Ulf

2014-01-01

CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome- (WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server. Database URL: https://github.com/UppsalaGenomeCenter/CanvasDB. © The Author(s) 2014. Published by Oxford University Press.

Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

PubMed Central

Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

2015-01-01

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics

PubMed Central

2010-01-01

Background Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. Description An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Conclusions Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms. PMID:21210976

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics.

PubMed

Taylor, Ronald C

2010-12-21

Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms.

Prevalence, Molecular Characterization, and Antibiotic Susceptibility of Cronobacter sakazakii Isolates from Powdered Infant Formula Collected from Chinese Retail Markets

PubMed Central

Fei, Peng; Jiang, Yichao; Jiang, Yan; Yuan, Xiujuan; Yang, Tongxiang; Chen, Junliang; Wang, Ziyuan; Kang, Huaibin; Forsythe, Stephen J.

2017-01-01

Cronobacter sakazakii is an opportunistic pathogen that causes severe infections in neonates and infants through contaminated powdered infant formula (PIF). Therefore, the aim of this study was a large-scale study on determine the prevalence, molecular characterization and antibiotic susceptibility of C. sakazakii isolates from PIF purchased from Chinese retail markets. Two thousand and twenty PIF samples were collected from different institutions. Fifty-six C. sakazakii strains were isolated, and identified using fusA sequencing analysis, giving a contamination rate of 2.8%. Multilocus sequence typing (MLST) was more discriminatory than other genotyping methods. The C. sakazakii isolates were divided into 14 sequence types (STs) by MLST, compared with only seven clusters by ompA and rpoB sequence analysis, and four C. sakazakii serotypes by PCR-based O-antigen serotyping. C. sakazakii ST4 (19/56, 33.9%), ST1 (12/56, 21.4%), and ST64 (11/56, 16.1%) were the dominant sequence types isolated. C. sakazakii serotype O2 (34/56, 60.7%) was the primary serotype, along with ompA6 and rpoB1 as the main allele profiles, respectively. Antibiotic susceptibility testing indicated that all C. sakazakii isolates were susceptible to ampicillin-sulbactam, cefotaxime, ciprofloxacin, meropenem, tetracycline, piperacillin-tazobactam, and trimethoprim-sulfamethoxazole. The majority of C. sakazakii strains were susceptible to chloramphenicol and gentamicin (87.5 and 92.9%, respectively). In contrast, 55.4% C. sakazakii strains were resistant to cephalothin. In conclusion, this large-scale study revealed the prevalence and characteristics of C. sakazakii from PIF in Chinese retail markets, demonstrating a potential risk for neonates and infants, and provide a guided to effective control the contamination of C. sakazakii in production process. PMID:29089940

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

PubMed

Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

2006-03-31

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

ProteinInferencer: Confident protein identification and multiple experiment comparison for large scale proteomics projects.

PubMed

Zhang, Yaoyang; Xu, Tao; Shan, Bing; Hart, Jonathan; Aslanian, Aaron; Han, Xuemei; Zong, Nobel; Li, Haomin; Choi, Howard; Wang, Dong; Acharya, Lipi; Du, Lisa; Vogt, Peter K; Ping, Peipei; Yates, John R

2015-11-03

Shotgun proteomics generates valuable information from large-scale and target protein characterizations, including protein expression, protein quantification, protein post-translational modifications (PTMs), protein localization, and protein-protein interactions. Typically, peptides derived from proteolytic digestion, rather than intact proteins, are analyzed by mass spectrometers because peptides are more readily separated, ionized and fragmented. The amino acid sequences of peptides can be interpreted by matching the observed tandem mass spectra to theoretical spectra derived from a protein sequence database. Identified peptides serve as surrogates for their proteins and are often used to establish what proteins were present in the original mixture and to quantify protein abundance. Two major issues exist for assigning peptides to their originating protein. The first issue is maintaining a desired false discovery rate (FDR) when comparing or combining multiple large datasets generated by shotgun analysis and the second issue is properly assigning peptides to proteins when homologous proteins are present in the database. Herein we demonstrate a new computational tool, ProteinInferencer, which can be used for protein inference with both small- or large-scale data sets to produce a well-controlled protein FDR. In addition, ProteinInferencer introduces confidence scoring for individual proteins, which makes protein identifications evaluable. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

PubMed Central

2011-01-01

Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105

Evolution, substrate specificity and subfamily classification of glycoside hydrolase family 5 (GH5).

PubMed

Aspeborg, Henrik; Coutinho, Pedro M; Wang, Yang; Brumer, Harry; Henrissat, Bernard

2012-09-20

The large Glycoside Hydrolase family 5 (GH5) groups together a wide range of enzymes acting on β-linked oligo- and polysaccharides, and glycoconjugates from a large spectrum of organisms. The long and complex evolution of this family of enzymes and its broad sequence diversity limits functional prediction. With the objective of improving the differentiation of enzyme specificities in a knowledge-based context, and to obtain new evolutionary insights, we present here a new, robust subfamily classification of family GH5. About 80% of the current sequences were assigned into 51 subfamilies in a global analysis of all publicly available GH5 sequences and associated biochemical data. Examination of subfamilies with catalytically-active members revealed that one third are monospecific (containing a single enzyme activity), although new functions may be discovered with biochemical characterization in the future. Furthermore, twenty subfamilies presently have no characterization whatsoever and many others have only limited structural and biochemical data. Mapping of functional knowledge onto the GH5 phylogenetic tree revealed that the sequence space of this historical and industrially important family is far from well dispersed, highlighting targets in need of further study. The analysis also uncovered a number of GH5 proteins which have lost their catalytic machinery, indicating evolution towards novel functions. Overall, the subfamily division of GH5 provides an actively curated resource for large-scale protein sequence annotation for glycogenomics; the subfamily assignments are openly accessible via the Carbohydrate-Active Enzyme database at http://www.cazy.org/GH5.html.

Molecular Epidemiology of Oropouche Virus, Brazil

PubMed Central

Vasconcelos, Helena Baldez; Nunes, Márcio R.T.; Casseb, Lívia M.N.; Carvalho, Valéria L.; Pinto da Silva, Eliana V.; Silva, Mayra; Casseb, Samir M.M.

2011-01-01

Oropouche virus (OROV) is the causative agent of Oropouche fever, an urban febrile arboviral disease widespread in South America, with >30 epidemics reported in Brazil and other Latin American countries during 1960–2009. To describe the molecular epidemiology of OROV, we analyzed the entire N gene sequences (small RNA) of 66 strains and 35 partial Gn (medium RNA) and large RNA gene sequences. Distinct patterns of OROV strain clustered according to N, Gn, and large gene sequences, which suggests that each RNA segment had a different evolutionary history and that the classification in genotypes must consider the genetic information for all genetic segments. Finally, time-scale analysis based on the N gene showed that OROV emerged in Brazil ≈223 years ago and that genotype I (based on N gene data) was responsible for the emergence of all other genotypes and for virus dispersal. PMID:21529387

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

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.

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

Defining the transcriptome assembly and its use for genome dynamics and transcriptome profiling studies in pigeonpea (Cajanus cajan L.)

USDA-ARS?s Scientific Manuscript database

This study reports generation of large-scale genomic resources for pigeonpea, a so-called ‘orphan crop species’ of the semi-arid tropic regions. Roche FLX/454 sequencing was carried out on a normalized cDNA pool prepared from 31 tissues produced 494,353 short transcript reads (STRs). Cluster analysi...

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

PubMed

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

PubMed Central

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-01-01

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems. PMID:27548171

ESTimating plant phylogeny: lessons from partitioning

PubMed Central

de la Torre, Jose EB; Egan, Mary G; Katari, Manpreet S; Brenner, Eric D; Stevenson, Dennis W; Coruzzi, Gloria M; DeSalle, Rob

2006-01-01

Background While Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies. Results A maximum parsimony (MP) analysis resulted in a single tree with relatively high support at all nodes in the tree despite rampant conflict among trees generated from the separate analysis of individual partitions. In a comparison of broader-scale groupings based on cellular compartment (ie: chloroplast, mitochondrial or nuclear) or function, only the nuclear partition tree (based largely on EST data) was found to be topologically identical to the tree based on the simultaneous analysis of all data. Despite topological conflict among the broader-scale groupings examined, only the tree based on morphological data showed statistically significant differences. Conclusion Based on the amount of character support contributed by EST data which make up a majority of the nuclear data set, and the lack of conflict of the nuclear data set with the simultaneous analysis tree, we conclude that the inclusion of EST data does provide a viable and efficient approach to address phylogenetic questions within a parsimony framework on a genomic scale, if problems of orthology determination and potential sequencing errors can be overcome. In addition, approaches that examine conflict and support in a simultaneous analysis framework allow for a more precise understanding of the evolutionary history of individual process partitions and may be a novel way to understand functional aspects of different kinds of cellular classes of gene products. PMID:16776834

A Glance at Microsatellite Motifs from 454 Sequencing Reads of Watermelon Genomic DNA

USDA-ARS?s Scientific Manuscript database

A single 454 (Life Sciences Sequencing Technology) run of Charleston Gray watermelon (Citrullus lanatus var. lanatus) genomic DNA was performed and sequence data were assembled. A large scale identification of simple sequence repeat (SSR) was performed and SSR sequence data were used for the develo...

Genetic diversity of armored scales (Hemiptera: Diaspididae) and soft scales (Hemiptera: Coccidae) in Chile.

PubMed

Amouroux, P; Crochard, D; Germain, J-F; Correa, M; Ampuero, J; Groussier, G; Kreiter, P; Malausa, T; Zaviezo, T

2017-05-17

Scale insects (Sternorrhyncha: Coccoidea) are one of the most invasive and agriculturally damaging insect groups. Their management and the development of new control methods are currently jeopardized by the scarcity of identification data, in particular in regions where no large survey coupling morphological and DNA analyses have been performed. In this study, we sampled 116 populations of armored scales (Hemiptera: Diaspididae) and 112 populations of soft scales (Hemiptera: Coccidae) in Chile, over a latitudinal gradient ranging from 18°S to 41°S, on fruit crops, ornamental plants and trees. We sequenced the COI and 28S genes in each population. In total, 19 Diaspididae species and 11 Coccidae species were identified morphologically. From the 63 COI haplotypes and the 54 28S haplotypes uncovered, and using several DNA data analysis methods (Automatic Barcode Gap Discovery, K2P distance, NJ trees), up to 36 genetic clusters were detected. Morphological and DNA data were congruent, except for three species (Aspidiotus nerii, Hemiberlesia rapax and Coccus hesperidum) in which DNA data revealed highly differentiated lineages. More than 50% of the haplotypes obtained had no high-scoring matches with any of the sequences in the GenBank database. This study provides 63 COI and 54 28S barcode sequences for the identification of Coccoidea from Chile.

A new and fast method for preparing high quality lambda DNA suitable for sequencing.

PubMed Central

Manfioletti, G; Schneider, C

1988-01-01

A method is described for the rapid purification of high quality lambda DNA. The method can be used from either liquid or plate lysates and on a small scale or a large scale. It relies on the preadsobtion of all polyanions present in the lysate to an "insoluble" anion-exchange matrix (DEAE or TEAE). Phage particles are then disrupted by combined treatment with EDTA/proteinase K and the resulting DNA is precipitated by the addition of the cationic detergent cetyl (or hexadecyl)-trimethyl ammonium bromide-CTAB ("soluble" anion-exchange matrix). The precipitated CTAB-DNA complex is then exchanged to Na-DNA and ethanol precipitated. The resultant purified DNA is suitable for enzymatic reactions and provides a high quality template for dideoxy-sequence analysis. Images PMID:2966928

SIMAP--a comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters.

PubMed

Rattei, Thomas; Tischler, Patrick; Götz, Stefan; Jehl, Marc-André; Hoser, Jonathan; Arnold, Roland; Conesa, Ana; Mewes, Hans-Werner

2010-01-01

The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date pre-calculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are pre-calculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).

A Toolkit for bulk PCR-based marker design from next-generation sequence data: application for development of a framework linkage map in bulb onion (Allium cepa L.)

PubMed Central

2012-01-01

Background Although modern sequencing technologies permit the ready detection of numerous DNA sequence variants in any organisms, converting such information to PCR-based genetic markers is hampered by a lack of simple, scalable tools. Onion is an example of an under-researched crop with a complex, heterozygous genome where genome-based research has previously been hindered by limited sequence resources and genetic markers. Results We report the development of generic tools for large-scale web-based PCR-based marker design in the Galaxy bioinformatics framework, and their application for development of next-generation genetics resources in a wide cross of bulb onion (Allium cepa L.). Transcriptome sequence resources were developed for the homozygous doubled-haploid bulb onion line ‘CUDH2150’ and the genetically distant Indian landrace ‘Nasik Red’, using 454™ sequencing of normalised cDNA libraries of leaf and shoot. Read mapping of ‘Nasik Red’ reads onto ‘CUDH2150’ assemblies revealed 16836 indel and SNP polymorphisms that were mined for portable PCR-based marker development. Tools for detection of restriction polymorphisms and primer set design were developed in BioPython and adapted for use in the Galaxy workflow environment, enabling large-scale and targeted assay design. Using PCR-based markers designed with these tools, a framework genetic linkage map of over 800cM spanning all chromosomes was developed in a subset of 93 F2 progeny from a very large F2 family developed from the ‘Nasik Red’ x ‘CUDH2150’ inter-cross. The utility of tools and genetic resources developed was tested by designing markers to transcription factor-like polymorphic sequences. Bin mapping these markers using a subset of 10 progeny confirmed the ability to place markers within 10 cM bins, enabling increased efficiency in marker assignment and targeted map refinement. The major genetic loci conditioning red bulb colour (R) and fructan content (Frc) were located on this map by QTL analysis. Conclusions The generic tools developed for the Galaxy environment enable rapid development of sets of PCR assays targeting sequence variants identified from Illumina and 454 sequence data. They enable non-specialist users to validate and exploit large volumes of next-generation sequence data using basic equipment. PMID:23157543

A toolkit for bulk PCR-based marker design from next-generation sequence data: application for development of a framework linkage map in bulb onion (Allium cepa L.).

PubMed

Baldwin, Samantha; Revanna, Roopashree; Thomson, Susan; Pither-Joyce, Meeghan; Wright, Kathryn; Crowhurst, Ross; Fiers, Mark; Chen, Leshi; Macknight, Richard; McCallum, John A

2012-11-19

Although modern sequencing technologies permit the ready detection of numerous DNA sequence variants in any organisms, converting such information to PCR-based genetic markers is hampered by a lack of simple, scalable tools. Onion is an example of an under-researched crop with a complex, heterozygous genome where genome-based research has previously been hindered by limited sequence resources and genetic markers. We report the development of generic tools for large-scale web-based PCR-based marker design in the Galaxy bioinformatics framework, and their application for development of next-generation genetics resources in a wide cross of bulb onion (Allium cepa L.). Transcriptome sequence resources were developed for the homozygous doubled-haploid bulb onion line 'CUDH2150' and the genetically distant Indian landrace 'Nasik Red', using 454™ sequencing of normalised cDNA libraries of leaf and shoot. Read mapping of 'Nasik Red' reads onto 'CUDH2150' assemblies revealed 16836 indel and SNP polymorphisms that were mined for portable PCR-based marker development. Tools for detection of restriction polymorphisms and primer set design were developed in BioPython and adapted for use in the Galaxy workflow environment, enabling large-scale and targeted assay design. Using PCR-based markers designed with these tools, a framework genetic linkage map of over 800cM spanning all chromosomes was developed in a subset of 93 F(2) progeny from a very large F(2) family developed from the 'Nasik Red' x 'CUDH2150' inter-cross. The utility of tools and genetic resources developed was tested by designing markers to transcription factor-like polymorphic sequences. Bin mapping these markers using a subset of 10 progeny confirmed the ability to place markers within 10 cM bins, enabling increased efficiency in marker assignment and targeted map refinement. The major genetic loci conditioning red bulb colour (R) and fructan content (Frc) were located on this map by QTL analysis. The generic tools developed for the Galaxy environment enable rapid development of sets of PCR assays targeting sequence variants identified from Illumina and 454 sequence data. They enable non-specialist users to validate and exploit large volumes of next-generation sequence data using basic equipment.

MinION Analysis and Reference Consortium: Phase 1 data release and analysis

PubMed Central

Eccles, David A.; Zalunin, Vadim; Urban, John M.; Piazza, Paolo; Bowden, Rory J.; Paten, Benedict; Mwaigwisya, Solomon; Batty, Elizabeth M.; Simpson, Jared T.; Snutch, Terrance P.

2015-01-01

The advent of a miniaturized DNA sequencing device with a high-throughput contextual sequencing capability embodies the next generation of large scale sequencing tools. The MinION™ Access Programme (MAP) was initiated by Oxford Nanopore Technologies™ in April 2014, giving public access to their USB-attached miniature sequencing device. The MinION Analysis and Reference Consortium (MARC) was formed by a subset of MAP participants, with the aim of evaluating and providing standard protocols and reference data to the community. Envisaged as a multi-phased project, this study provides the global community with the Phase 1 data from MARC, where the reproducibility of the performance of the MinION was evaluated at multiple sites. Five laboratories on two continents generated data using a control strain of Escherichia coli K-12, preparing and sequencing samples according to a revised ONT protocol. Here, we provide the details of the protocol used, along with a preliminary analysis of the characteristics of typical runs including the consistency, rate, volume and quality of data produced. Further analysis of the Phase 1 data presented here, and additional experiments in Phase 2 of E. coli from MARC are already underway to identify ways to improve and enhance MinION performance. PMID:26834992

SNP-VISTA: An interactive SNP visualization tool

PubMed Central

Shah, Nameeta; Teplitsky, Michael V; Minovitsky, Simon; Pennacchio, Len A; Hugenholtz, Philip; Hamann, Bernd; Dubchak, Inna L

2005-01-01

Background Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at [1]. Results We have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. Conclusion The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user. PMID:16336665

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

PubMed

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

2014-06-01

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

XS: a FASTQ read simulator.

PubMed

Pratas, Diogo; Pinho, Armando J; Rodrigues, João M O S

2014-01-16

The emerging next-generation sequencing (NGS) is bringing, besides the natural huge amounts of data, an avalanche of new specialized tools (for analysis, compression, alignment, among others) and large public and private network infrastructures. Therefore, a direct necessity of specific simulation tools for testing and benchmarking is rising, such as a flexible and portable FASTQ read simulator, without the need of a reference sequence, yet correctly prepared for producing approximately the same characteristics as real data. We present XS, a skilled FASTQ read simulation tool, flexible, portable (does not need a reference sequence) and tunable in terms of sequence complexity. It has several running modes, depending on the time and memory available, and is aimed at testing computing infrastructures, namely cloud computing of large-scale projects, and testing FASTQ compression algorithms. Moreover, XS offers the possibility of simulating the three main FASTQ components individually (headers, DNA sequences and quality-scores). XS provides an efficient and convenient method for fast simulation of FASTQ files, such as those from Ion Torrent (currently uncovered by other simulators), Roche-454, Illumina and ABI-SOLiD sequencing machines. This tool is publicly available at http://bioinformatics.ua.pt/software/xs/.

Large-scale sequence and structural comparisons of human naive and antigen-experienced antibody repertoires.

PubMed

DeKosky, Brandon J; Lungu, Oana I; Park, Daechan; Johnson, Erik L; Charab, Wissam; Chrysostomou, Constantine; Kuroda, Daisuke; Ellington, Andrew D; Ippolito, Gregory C; Gray, Jeffrey J; Georgiou, George

2016-05-10

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy- and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19(+)CD20(+)CD27(-) IgM-naive B cells, >120,000 antibody clusters from CD19(+)CD20(+)CD27(+) antigen-experienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ-Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease.

A genomic regulatory network for development

NASA Technical Reports Server (NTRS)

Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar;

Memory effect in M ≥ 7 earthquakes of Taiwan

NASA Astrophysics Data System (ADS)

Wang, Jeen-Hwa

2014-07-01

The M ≥ 7 earthquakes that occurred in the Taiwan region during 1906-2006 are taken to study the possibility of memory effect existing in the sequence of those large earthquakes. Those events are all mainshocks. The fluctuation analysis technique is applied to analyze two sequences in terms of earthquake magnitude and inter-event time represented in the natural time domain. For both magnitude and inter-event time, the calculations are made for three data sets, i.e., the original order data, the reverse-order data, and that of the mean values. Calculated results show that the exponents of scaling law of fluctuation versus window length are less than 0.5 for the sequences of both magnitude and inter-event time data. In addition, the phase portraits of two sequent magnitudes and two sequent inter-event times are also applied to explore if large (or small) earthquakes are followed by large (or small) events. Results lead to a negative answer. Together with all types of information in study, we make a conclusion that the earthquake sequence in study is short-term corrected and thus the short-term memory effect would be operative.

Preparation of highly multiplexed small RNA sequencing libraries.

PubMed

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

2017-08-01

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

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.

Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing

PubMed Central

Nunes, José de Ribamar da Silva; Liu, Shikai; Pértille, Fábio; Perazza, Caio Augusto; Villela, Priscilla Marqui Schmidt; de Almeida-Val, Vera Maria Fonseca; Hilsdorf, Alexandre Wagner Silva; Liu, Zhanjiang; Coutinho, Luiz Lehmann

2017-01-01

Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs. PMID:28387238

Efficient population-scale variant analysis and prioritization with VAPr.

PubMed

Birmingham, Amanda; Mark, Adam M; Mazzaferro, Carlo; Xu, Guorong; Fisch, Kathleen M

2018-04-06

With the growing availability of population-scale whole-exome and whole-genome sequencing, demand for reproducible, scalable variant analysis has spread within genomic research communities. To address this need, we introduce the Python package VAPr (Variant Analysis and Prioritization). VAPr leverages existing annotation tools ANNOVAR and MyVariant.info with MongoDB-based flexible storage and filtering functionality. It offers biologists and bioinformatics generalists easy-to-use and scalable analysis and prioritization of genomic variants from large cohort studies. VAPr is developed in Python and is available for free use and extension under the MIT License. An install package is available on PyPi at https://pypi.python.org/pypi/VAPr, while source code and extensive documentation are on GitHub at https://github.com/ucsd-ccbb/VAPr. kfisch@ucsd.edu.

Recent advances in ChIP-seq analysis: from quality management to whole-genome annotation.

PubMed

Nakato, Ryuichiro; Shirahige, Katsuhiko

2017-03-01

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis can detect protein/DNA-binding and histone-modification sites across an entire genome. Recent advances in sequencing technologies and analyses enable us to compare hundreds of samples simultaneously; such large-scale analysis has potential to reveal the high-dimensional interrelationship level for regulatory elements and annotate novel functional genomic regions de novo. Because many experimental considerations are relevant to the choice of a method in a ChIP-seq analysis, the overall design and quality management of the experiment are of critical importance. This review offers guiding principles of computation and sample preparation for ChIP-seq analyses, highlighting the validity and limitations of the state-of-the-art procedures at each step. We also discuss the latest challenges of single-cell analysis that will encourage a new era in this field. © The Author 2016. Published by Oxford University Press.

TaqMan Real-Time PCR Assays To Assess Arbuscular Mycorrhizal Responses to Field Manipulation of Grassland Biodiversity: Effects of Soil Characteristics, Plant Species Richness, and Functional Traits▿ †

PubMed Central

König, Stephan; Wubet, Tesfaye; Dormann, Carsten F.; Hempel, Stefan; Renker, Carsten; Buscot, François

2010-01-01

Large-scale (temporal and/or spatial) molecular investigations of the diversity and distribution of arbuscular mycorrhizal fungi (AMF) require considerable sampling efforts and high-throughput analysis. To facilitate such efforts, we have developed a TaqMan real-time PCR assay to detect and identify AMF in environmental samples. First, we screened the diversity in clone libraries, generated by nested PCR, of the nuclear ribosomal DNA internal transcribed spacer (ITS) of AMF in environmental samples. We then generated probes and forward primers based on the detected sequences, enabling AMF sequence type-specific detection in TaqMan multiplex real-time PCR assays. In comparisons to conventional clone library screening and Sanger sequencing, the TaqMan assay approach provided similar accuracy but higher sensitivity with cost and time savings. The TaqMan assays were applied to analyze the AMF community composition within plots of a large-scale plant biodiversity manipulation experiment, the Jena Experiment, primarily designed to investigate the interactive effects of plant biodiversity on element cycling and trophic interactions. The results show that environmental variables hierarchically shape AMF communities and that the sequence type spectrum is strongly affected by previous land use and disturbance, which appears to favor disturbance-tolerant members of the genus Glomus. The AMF species richness of disturbance-associated communities can be largely explained by richness of plant species and plant functional groups, while plant productivity and soil parameters appear to have only weak effects on the AMF community. PMID:20418424

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

PubMed

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

2014-10-01

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

Large-scale genomic analyses reveal the population structure and evolutionary trends of Streptococcus agalactiae strains in Brazilian fish farms.

PubMed

Barony, Gustavo M; Tavares, Guilherme C; Pereira, Felipe L; Carvalho, Alex F; Dorella, Fernanda A; Leal, Carlos A G; Figueiredo, Henrique C P

2017-10-19

Streptococcus agalactiae is a major pathogen and a hindrance on tilapia farming worldwide. The aims of this work were to analyze the genomic evolution of Brazilian strains of S. agalactiae and to establish spatial and temporal relations between strains isolated from different outbreaks of streptococcosis. A total of 39 strains were obtained from outbreaks and their whole genomes were sequenced and annotated for comparative analysis of multilocus sequence typing, genomic similarity and whole genome multilocus sequence typing (wgMLST). The Brazilian strains presented two sequence types, including a newly described ST, and a non-typeable lineage. The use of wgMLST could differentiate each strain in a single clone and was used to establish temporal and geographical correlations among strains. Bayesian phylogenomic analysis suggests that the studied Brazilian population was co-introduced in the country with their host, approximately 60 years ago. Brazilian strains of S. agalactiae were shown to be heterogeneous in their genome sequences and were distributed in different regions of the country according to their genotype, which allowed the use of wgMLST analysis to track each outbreak event individually.

NCBI prokaryotic genome annotation pipeline.

PubMed

Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

2016-08-19

Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Gold nanoparticles for high-throughput genotyping of long-range haplotypes

NASA Astrophysics Data System (ADS)

Chen, Peng; Pan, Dun; Fan, Chunhai; Chen, Jianhua; Huang, Ke; Wang, Dongfang; Zhang, Honglu; Li, You; Feng, Guoyin; Liang, Peiji; He, Lin; Shi, Yongyong

2011-10-01

Completion of the Human Genome Project and the HapMap Project has led to increasing demands for mapping complex traits in humans to understand the aetiology of diseases. Identifying variations in the DNA sequence, which affect how we develop disease and respond to pathogens and drugs, is important for this purpose, but it is difficult to identify these variations in large sample sets. Here we show that through a combination of capillary sequencing and polymerase chain reaction assisted by gold nanoparticles, it is possible to identify several DNA variations that are associated with age-related macular degeneration and psoriasis on significant regions of human genomic DNA. Our method is accurate and promising for large-scale and high-throughput genetic analysis of susceptibility towards disease and drug resistance.

Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL Cholesterol

PubMed Central

Lange, Leslie A.; Hu, Youna; Zhang, He; Xue, Chenyi; Schmidt, Ellen M.; Tang, Zheng-Zheng; Bizon, Chris; Lange, Ethan M.; Smith, Joshua D.; Turner, Emily H.; Jun, Goo; Kang, Hyun Min; Peloso, Gina; Auer, Paul; Li, Kuo-ping; Flannick, Jason; Zhang, Ji; Fuchsberger, Christian; Gaulton, Kyle; Lindgren, Cecilia; Locke, Adam; Manning, Alisa; Sim, Xueling; Rivas, Manuel A.; Holmen, Oddgeir L.; Gottesman, Omri; Lu, Yingchang; Ruderfer, Douglas; Stahl, Eli A.; Duan, Qing; Li, Yun; Durda, Peter; Jiao, Shuo; Isaacs, Aaron; Hofman, Albert; Bis, Joshua C.; Correa, Adolfo; Griswold, Michael E.; Jakobsdottir, Johanna; Smith, Albert V.; Schreiner, Pamela J.; Feitosa, Mary F.; Zhang, Qunyuan; Huffman, Jennifer E.; Crosby, Jacy; Wassel, Christina L.; Do, Ron; Franceschini, Nora; Martin, Lisa W.; Robinson, Jennifer G.; Assimes, Themistocles L.; Crosslin, David R.; Rosenthal, Elisabeth A.; Tsai, Michael; Rieder, Mark J.; Farlow, Deborah N.; Folsom, Aaron R.; Lumley, Thomas; Fox, Ervin R.; Carlson, Christopher S.; Peters, Ulrike; Jackson, Rebecca D.; van Duijn, Cornelia M.; Uitterlinden, André G.; Levy, Daniel; Rotter, Jerome I.; Taylor, Herman A.; Gudnason, Vilmundur; Siscovick, David S.; Fornage, Myriam; Borecki, Ingrid B.; Hayward, Caroline; Rudan, Igor; Chen, Y. Eugene; Bottinger, Erwin P.; Loos, Ruth J.F.; Sætrom, Pål; Hveem, Kristian; Boehnke, Michael; Groop, Leif; McCarthy, Mark; Meitinger, Thomas; Ballantyne, Christie M.; Gabriel, Stacey B.; O’Donnell, Christopher J.; Post, Wendy S.; North, Kari E.; Reiner, Alexander P.; Boerwinkle, Eric; Psaty, Bruce M.; Altshuler, David; Kathiresan, Sekar; Lin, Dan-Yu; Jarvik, Gail P.; Cupples, L. Adrienne; Kooperberg, Charles; Wilson, James G.; Nickerson, Deborah A.; Abecasis, Goncalo R.; Rich, Stephen S.; Tracy, Russell P.; Willer, Cristen J.; Gabriel, Stacey B.; Altshuler, David M.; Abecasis, Gonçalo R.; Allayee, Hooman; Cresci, Sharon; Daly, Mark J.; de Bakker, Paul I.W.; DePristo, Mark A.; Do, Ron; Donnelly, Peter; Farlow, Deborah N.; Fennell, Tim; Garimella, Kiran; Hazen, Stanley L.; Hu, Youna; Jordan, Daniel M.; Jun, Goo; Kathiresan, Sekar; Kang, Hyun Min; Kiezun, Adam; Lettre, Guillaume; Li, Bingshan; Li, Mingyao; Newton-Cheh, Christopher H.; Padmanabhan, Sandosh; Peloso, Gina; Pulit, Sara; Rader, Daniel J.; Reich, David; Reilly, Muredach P.; Rivas, Manuel A.; Schwartz, Steve; Scott, Laura; Siscovick, David S.; Spertus, John A.; Stitziel, Nathaniel O.; Stoletzki, Nina; Sunyaev, Shamil R.; Voight, Benjamin F.; Willer, Cristen J.; Rich, Stephen S.; Akylbekova, Ermeg; Atwood, Larry D.; Ballantyne, Christie M.; Barbalic, Maja; Barr, R. Graham; Benjamin, Emelia J.; Bis, Joshua; Boerwinkle, Eric; Bowden, Donald W.; Brody, Jennifer; Budoff, Matthew; Burke, Greg; Buxbaum, Sarah; Carr, Jeff; Chen, Donna T.; Chen, Ida Y.; Chen, Wei-Min; Concannon, Pat; Crosby, Jacy; Cupples, L. Adrienne; D’Agostino, Ralph; DeStefano, Anita L.; Dreisbach, Albert; Dupuis, Josée; Durda, J. Peter; Ellis, Jaclyn; Folsom, Aaron R.; Fornage, Myriam; Fox, Caroline S.; Fox, Ervin; Funari, Vincent; Ganesh, Santhi K.; Gardin, Julius; Goff, David; Gordon, Ora; Grody, Wayne; Gross, Myron; Guo, Xiuqing; Hall, Ira M.; Heard-Costa, Nancy L.; Heckbert, Susan R.; Heintz, Nicholas; Herrington, David M.; Hickson, DeMarc; Huang, Jie; Hwang, Shih-Jen; Jacobs, David R.; Jenny, Nancy S.; Johnson, Andrew D.; Johnson, Craig W.; Kawut, Steven; Kronmal, Richard; Kurz, Raluca; Lange, Ethan M.; Lange, Leslie A.; Larson, Martin G.; Lawson, Mark; Lewis, Cora E.; Levy, Daniel; Li, Dalin; Lin, Honghuang; Liu, Chunyu; Liu, Jiankang; Liu, Kiang; Liu, Xiaoming; Liu, Yongmei; Longstreth, William T.; Loria, Cay; Lumley, Thomas; Lunetta, Kathryn; Mackey, Aaron J.; Mackey, Rachel; Manichaikul, Ani; Maxwell, Taylor; McKnight, Barbara; Meigs, James B.; Morrison, Alanna C.; Musani, Solomon K.; Mychaleckyj, Josyf C.; Nettleton, Jennifer A.; North, Kari; O’Donnell, Christopher J.; O’Leary, Daniel; Ong, Frank; Palmas, Walter; Pankow, James S.; Pankratz, Nathan D.; Paul, Shom; Perez, Marco; Person, Sharina D.; Polak, Joseph; Post, Wendy S.; Psaty, Bruce M.; Quinlan, Aaron R.; Raffel, Leslie J.; Ramachandran, Vasan S.; Reiner, Alexander P.; Rice, Kenneth; Rotter, Jerome I.; Sanders, Jill P.; Schreiner, Pamela; Seshadri, Sudha; Shea, Steve; Sidney, Stephen; Silverstein, Kevin; Smith, Nicholas L.; Sotoodehnia, Nona; Srinivasan, Asoke; Taylor, Herman A.; Taylor, Kent; Thomas, Fridtjof; Tracy, Russell P.; Tsai, Michael Y.; Volcik, Kelly A.; Wassel, Chrstina L.; Watson, Karol; Wei, Gina; White, Wendy; Wiggins, Kerri L.; Wilk, Jemma B.; Williams, O. Dale; Wilson, Gregory; Wilson, James G.; Wolf, Phillip; Zakai, Neil A.; Hardy, John; Meschia, James F.; Nalls, Michael; Singleton, Andrew; Worrall, Brad; Bamshad, Michael J.; Barnes, Kathleen C.; Abdulhamid, Ibrahim; Accurso, Frank; Anbar, Ran; Beaty, Terri; Bigham, Abigail; Black, Phillip; Bleecker, Eugene; Buckingham, Kati; Cairns, Anne Marie; Caplan, Daniel; Chatfield, Barbara; Chidekel, Aaron; Cho, Michael; Christiani, David C.; Crapo, James D.; Crouch, Julia; Daley, Denise; Dang, Anthony; Dang, Hong; De Paula, Alicia; DeCelie-Germana, Joan; Drumm, Allen DozorMitch; Dyson, Maynard; Emerson, Julia; Emond, Mary J.; Ferkol, Thomas; Fink, Robert; Foster, Cassandra; Froh, Deborah; Gao, Li; Gershan, William; Gibson, Ronald L.; Godwin, Elizabeth; Gondor, Magdalen; Gutierrez, Hector; Hansel, Nadia N.; Hassoun, Paul M.; Hiatt, Peter; Hokanson, John E.; Howenstine, Michelle; Hummer, Laura K.; Kanga, Jamshed; Kim, Yoonhee; Knowles, Michael R.; Konstan, Michael; Lahiri, Thomas; Laird, Nan; Lange, Christoph; Lin, Lin; Lin, Xihong; Louie, Tin L.; Lynch, David; Make, Barry; Martin, Thomas R.; Mathai, Steve C.; Mathias, Rasika A.; McNamara, John; McNamara, Sharon; Meyers, Deborah; Millard, Susan; Mogayzel, Peter; Moss, Richard; Murray, Tanda; Nielson, Dennis; Noyes, Blakeslee; O’Neal, Wanda; Orenstein, David; O’Sullivan, Brian; Pace, Rhonda; Pare, Peter; Parker, H. Worth; Passero, Mary Ann; Perkett, Elizabeth; Prestridge, Adrienne; Rafaels, Nicholas M.; Ramsey, Bonnie; Regan, Elizabeth; Ren, Clement; Retsch-Bogart, George; Rock, Michael; Rosen, Antony; Rosenfeld, Margaret; Ruczinski, Ingo; Sanford, Andrew; Schaeffer, David; Sell, Cindy; Sheehan, Daniel; Silverman, Edwin K.; Sin, Don; Spencer, Terry; Stonebraker, Jackie; Tabor, Holly K.; Varlotta, Laurie; Vergara, Candelaria I.; Weiss, Robert; Wigley, Fred; Wise, Robert A.; Wright, Fred A.; Wurfel, Mark M.; Zanni, Robert; Zou, Fei; Nickerson, Deborah A.; Rieder, Mark J.; Green, Phil; Shendure, Jay; Akey, Joshua M.; Bustamante, Carlos D.; Crosslin, David R.; Eichler, Evan E.; Fox, P. Keolu; Fu, Wenqing; Gordon, Adam; Gravel, Simon; Jarvik, Gail P.; Johnsen, Jill M.; Kan, Mengyuan; Kenny, Eimear E.; Kidd, Jeffrey M.; Lara-Garduno, Fremiet; Leal, Suzanne M.; Liu, Dajiang J.; McGee, Sean; O’Connor, Timothy D.; Paeper, Bryan; Robertson, Peggy D.; Smith, Joshua D.; Staples, Jeffrey C.; Tennessen, Jacob A.; Turner, Emily H.; Wang, Gao; Yi, Qian; Jackson, Rebecca; Peters, Ulrike; Carlson, Christopher S.; Anderson, Garnet; Anton-Culver, Hoda; Assimes, Themistocles L.; Auer, Paul L.; Beresford, Shirley; Bizon, Chris; Black, Henry; Brunner, Robert; Brzyski, Robert; Burwen, Dale; Caan, Bette; Carty, Cara L.; Chlebowski, Rowan; Cummings, Steven; Curb, J. David; Eaton, Charles B.; Ford, Leslie; Franceschini, Nora; Fullerton, Stephanie M.; Gass, Margery; Geller, Nancy; Heiss, Gerardo; Howard, Barbara V.; Hsu, Li; Hutter, Carolyn M.; Ioannidis, John; Jiao, Shuo; Johnson, Karen C.; Kooperberg, Charles; Kuller, Lewis; LaCroix, Andrea; Lakshminarayan, Kamakshi; Lane, Dorothy; Lasser, Norman; LeBlanc, Erin; Li, Kuo-Ping; Limacher, Marian; Lin, Dan-Yu; Logsdon, Benjamin A.; Ludlam, Shari; Manson, JoAnn E.; Margolis, Karen; Martin, Lisa; McGowan, Joan; Monda, Keri L.; Kotchen, Jane Morley; Nathan, Lauren; Ockene, Judith; O’Sullivan, Mary Jo; Phillips, Lawrence S.; Prentice, Ross L.; Robbins, John; Robinson, Jennifer G.; Rossouw, Jacques E.; Sangi-Haghpeykar, Haleh; Sarto, Gloria E.; Shumaker, Sally; Simon, Michael S.; Stefanick, Marcia L.; Stein, Evan; Tang, Hua; Taylor, Kira C.; Thomson, Cynthia A.; Thornton, Timothy A.; Van Horn, Linda; Vitolins, Mara; Wactawski-Wende, Jean; Wallace, Robert; Wassertheil-Smoller, Sylvia; Zeng, Donglin; Applebaum-Bowden, Deborah; Feolo, Michael; Gan, Weiniu; Paltoo, Dina N.; Sholinsky, Phyliss; Sturcke, Anne

2014-01-01

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98th or <2nd percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments. PMID:24507775

Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.

PubMed

Lange, Leslie A; Hu, Youna; Zhang, He; Xue, Chenyi; Schmidt, Ellen M; Tang, Zheng-Zheng; Bizon, Chris; Lange, Ethan M; Smith, Joshua D; Turner, Emily H; Jun, Goo; Kang, Hyun Min; Peloso, Gina; Auer, Paul; Li, Kuo-Ping; Flannick, Jason; Zhang, Ji; Fuchsberger, Christian; Gaulton, Kyle; Lindgren, Cecilia; Locke, Adam; Manning, Alisa; Sim, Xueling; Rivas, Manuel A; Holmen, Oddgeir L; Gottesman, Omri; Lu, Yingchang; Ruderfer, Douglas; Stahl, Eli A; Duan, Qing; Li, Yun; Durda, Peter; Jiao, Shuo; Isaacs, Aaron; Hofman, Albert; Bis, Joshua C; Correa, Adolfo; Griswold, Michael E; Jakobsdottir, Johanna; Smith, Albert V; Schreiner, Pamela J; Feitosa, Mary F; Zhang, Qunyuan; Huffman, Jennifer E; Crosby, Jacy; Wassel, Christina L; Do, Ron; Franceschini, Nora; Martin, Lisa W; Robinson, Jennifer G; Assimes, Themistocles L; Crosslin, David R; Rosenthal, Elisabeth A; Tsai, Michael; Rieder, Mark J; Farlow, Deborah N; Folsom, Aaron R; Lumley, Thomas; Fox, Ervin R; Carlson, Christopher S; Peters, Ulrike; Jackson, Rebecca D; van Duijn, Cornelia M; Uitterlinden, André G; Levy, Daniel; Rotter, Jerome I; Taylor, Herman A; Gudnason, Vilmundur; Siscovick, David S; Fornage, Myriam; Borecki, Ingrid B; Hayward, Caroline; Rudan, Igor; Chen, Y Eugene; Bottinger, Erwin P; Loos, Ruth J F; Sætrom, Pål; Hveem, Kristian; Boehnke, Michael; Groop, Leif; McCarthy, Mark; Meitinger, Thomas; Ballantyne, Christie M; Gabriel, Stacey B; O'Donnell, Christopher J; Post, Wendy S; North, Kari E; Reiner, Alexander P; Boerwinkle, Eric; Psaty, Bruce M; Altshuler, David; Kathiresan, Sekar; Lin, Dan-Yu; Jarvik, Gail P; Cupples, L Adrienne; Kooperberg, Charles; Wilson, James G; Nickerson, Deborah A; Abecasis, Goncalo R; Rich, Stephen S; Tracy, Russell P; Willer, Cristen J

2014-02-06

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

InterProScan 5: genome-scale protein function classification

PubMed Central

Jones, Philip; Binns, David; Chang, Hsin-Yu; Fraser, Matthew; Li, Weizhong; McAnulla, Craig; McWilliam, Hamish; Maslen, John; Mitchell, Alex; Nuka, Gift; Pesseat, Sebastien; Quinn, Antony F.; Sangrador-Vegas, Amaia; Scheremetjew, Maxim; Yong, Siew-Yit; Lopez, Rodrigo; Hunter, Sarah

2014-01-01

Motivation: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of sequences. Here, we describe a new Java-based architecture for the widely used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete reimplementation of the software framework, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the open source code is hosted at Google Code. Availability and implementation: InterProScan is distributed via FTP at ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/ and the source code is available from http://code.google.com/p/interproscan/. Contact: http://www.ebi.ac.uk/support or interhelp@ebi.ac.uk or mitchell@ebi.ac.uk PMID:24451626

Bacterial discrimination by means of a universal array approach mediated by LDR (ligase detection reaction)

PubMed Central

Busti, Elena; Bordoni, Roberta; Castiglioni, Bianca; Monciardini, Paolo; Sosio, Margherita; Donadio, Stefano; Consolandi, Clarissa; Rossi Bernardi, Luigi; Battaglia, Cristina; De Bellis, Gianluca

2002-01-01

Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode) which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene) contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria. PMID:12243651

A reference guide for tree analysis and visualization

PubMed Central

2010-01-01

The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are becoming vast. Sequencing technologies become cheaper and easier to use and, thus, large-scale evolutionary studies towards the origins of life for all species and their evolution becomes more and more challenging. Databases holding information about how data are related and how they are hierarchically organized expand rapidly. Clustering analysis is becoming more and more difficult to be applied on very large amounts of data since the results of these algorithms cannot be efficiently visualized. Most of the available visualization tools that are able to represent such hierarchies, project data in 2D and are lacking often the necessary user friendliness and interactivity. For example, the current phylogenetic tree visualization tools are not able to display easy to understand large scale trees with more than a few thousand nodes. In this study, we review tools that are currently available for the visualization of biological trees and analysis, mainly developed during the last decade. We describe the uniform and standard computer readable formats to represent tree hierarchies and we comment on the functionality and the limitations of these tools. We also discuss on how these tools can be developed further and should become integrated with various data sources. Here we focus on freely available software that offers to the users various tree-representation methodologies for biological data analysis. PMID:20175922

Scalable and cost-effective NGS genotyping in the cloud.

PubMed

Souilmi, Yassine; Lancaster, Alex K; Jung, Jae-Yoon; Rizzo, Ettore; Hawkins, Jared B; Powles, Ryan; Amzazi, Saaïd; Ghazal, Hassan; Tonellato, Peter J; Wall, Dennis P

2015-10-15

While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.

Genomic analysis of expressed sequence tags in American black bear Ursus americanus

PubMed Central

2010-01-01

Background Species of the bear family (Ursidae) are important organisms for research in molecular evolution, comparative physiology and conservation biology, but relatively little genetic sequence information is available for this group. Here we report the development and analyses of the first large scale Expressed Sequence Tag (EST) resource for the American black bear (Ursus americanus). Results Comprehensive analyses of molecular functions, alternative splicing, and tissue-specific expression of 38,757 black bear EST sequences were conducted using the dog genome as a reference. We identified 18 genes, involved in functions such as lipid catabolism, cell cycle, and vesicle-mediated transport, that are showing rapid evolution in the bear lineage Three genes, Phospholamban (PLN), cysteine glycine-rich protein 3 (CSRP3) and Troponin I type 3 (TNNI3), are related to heart contraction, and defects in these genes in humans lead to heart disease. Two genes, biphenyl hydrolase-like (BPHL) and CSRP3, contain positively selected sites in bear. Global analysis of evolution rates of hibernation-related genes in bear showed that they are largely conserved and slowly evolving genes, rather than novel and fast-evolving genes. Conclusion We provide a genomic resource for an important mammalian organism and our study sheds new light on the possible functions and evolution of bear genes. PMID:20338065

Genomic analysis of expressed sequence tags in American black bear Ursus americanus.

PubMed

Zhao, Sen; Shao, Chunxuan; Goropashnaya, Anna V; Stewart, Nathan C; Xu, Yichi; Tøien, Øivind; Barnes, Brian M; Fedorov, Vadim B; Yan, Jun

2010-03-26

Species of the bear family (Ursidae) are important organisms for research in molecular evolution, comparative physiology and conservation biology, but relatively little genetic sequence information is available for this group. Here we report the development and analyses of the first large scale Expressed Sequence Tag (EST) resource for the American black bear (Ursus americanus). Comprehensive analyses of molecular functions, alternative splicing, and tissue-specific expression of 38,757 black bear EST sequences were conducted using the dog genome as a reference. We identified 18 genes, involved in functions such as lipid catabolism, cell cycle, and vesicle-mediated transport, that are showing rapid evolution in the bear lineage Three genes, Phospholamban (PLN), cysteine glycine-rich protein 3 (CSRP3) and Troponin I type 3 (TNNI3), are related to heart contraction, and defects in these genes in humans lead to heart disease. Two genes, biphenyl hydrolase-like (BPHL) and CSRP3, contain positively selected sites in bear. Global analysis of evolution rates of hibernation-related genes in bear showed that they are largely conserved and slowly evolving genes, rather than novel and fast-evolving genes. We provide a genomic resource for an important mammalian organism and our study sheds new light on the possible functions and evolution of bear genes.

HASP server: a database and structural visualization platform for comparative models of influenza A hemagglutinin proteins.

PubMed

Ambroggio, Xavier I; Dommer, Jennifer; Gopalan, Vivek; Dunham, Eleca J; Taubenberger, Jeffery K; Hurt, Darrell E

2013-06-18

Influenza A viruses possess RNA genomes that mutate frequently in response to immune pressures. The mutations in the hemagglutinin genes are particularly significant, as the hemagglutinin proteins mediate attachment and fusion to host cells, thereby influencing viral pathogenicity and species specificity. Large-scale influenza A genome sequencing efforts have been ongoing to understand past epidemics and pandemics and anticipate future outbreaks. Sequencing efforts thus far have generated nearly 9,000 distinct hemagglutinin amino acid sequences. Comparative models for all publicly available influenza A hemagglutinin protein sequences (8,769 to date) were generated using the Rosetta modeling suite. The C-alpha root mean square deviations between a randomly chosen test set of models and their crystallographic templates were less than 2 Å, suggesting that the modeling protocols yielded high-quality results. The models were compiled into an online resource, the Hemagglutinin Structure Prediction (HASP) server. The HASP server was designed as a scientific tool for researchers to visualize hemagglutinin protein sequences of interest in a three-dimensional context. With a built-in molecular viewer, hemagglutinin models can be compared side-by-side and navigated by a corresponding sequence alignment. The models and alignments can be downloaded for offline use and further analysis. The modeling protocols used in the HASP server scale well for large amounts of sequences and will keep pace with expanded sequencing efforts. The conservative approach to modeling and the intuitive search and visualization interfaces allow researchers to quickly analyze hemagglutinin sequences of interest in the context of the most highly related experimental structures, and allow them to directly compare hemagglutinin sequences to each other simultaneously in their two- and three-dimensional contexts. The models and methodology have shown utility in current research efforts and the ongoing aim of the HASP server is to continue to accelerate influenza A research and have a positive impact on global public health.

Human structural variation: mechanisms of chromosome rearrangements

PubMed Central

Weckselblatt, Brooke; Rudd, M. Katharine

2015-01-01

Chromosome structural variation (SV) is a normal part of variation in the human genome, but some classes of SV can cause neurodevelopmental disorders. Analysis of the DNA sequence at SV breakpoints can reveal mutational mechanisms and risk factors for chromosome rearrangement. Large-scale SV breakpoint studies have become possible recently owing to advances in next-generation sequencing (NGS) including whole-genome sequencing (WGS). These findings have shed light on complex forms of SV such as triplications, inverted duplications, insertional translocations, and chromothripsis. Sequence-level breakpoint data resolve SV structure and determine how genes are disrupted, fused, and/or misregulated by breakpoints. Recent improvements in breakpoint sequencing have also revealed non-allelic homologous recombination (NAHR) between paralogous long interspersed nuclear element (LINE) or human endogenous retrovirus (HERV) repeats as a cause of deletions, duplications, and translocations. This review covers the genomic organization of simple and complex constitutional SVs, as well as the molecular mechanisms of their formation. PMID:26209074

GenBank

PubMed Central

Benson, Dennis A.; Karsch-Mizrachi, Ilene; Lipman, David J.; Ostell, James; Wheeler, David L.

2007-01-01

GenBank (R) is a comprehensive database that contains publicly available nucleotide sequences for more than 240 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage (). PMID:17202161

A resource of large-scale molecular markers for monitoring Agropyron cristatum chromatin introgression in wheat background based on transcriptome sequences.

PubMed

Zhang, Jinpeng; Liu, Weihua; Lu, Yuqing; Liu, Qunxing; Yang, Xinming; Li, Xiuquan; Li, Lihui

2017-09-20

Agropyron cristatum is a wild grass of the tribe Triticeae and serves as a gene donor for wheat improvement. However, very few markers can be used to monitor A. cristatum chromatin introgressions in wheat. Here, we reported a resource of large-scale molecular markers for tracking alien introgressions in wheat based on transcriptome sequences. By aligning A. cristatum unigenes with the Chinese Spring reference genome sequences, we designed 9602 A. cristatum expressed sequence tag-sequence-tagged site (EST-STS) markers for PCR amplification and experimental screening. As a result, 6063 polymorphic EST-STS markers were specific for the A. cristatum P genome in the single-receipt wheat background. A total of 4956 randomly selected polymorphic EST-STS markers were further tested in eight wheat variety backgrounds, and 3070 markers displaying stable and polymorphic amplification were validated. These markers covered more than 98% of the A. cristatum genome, and the marker distribution density was approximately 1.28 cM. An application case of all EST-STS markers was validated on the A. cristatum 6 P chromosome. These markers were successfully applied in the tracking of alien A. cristatum chromatin. Altogether, this study provided a universal method of large-scale molecular marker development to monitor wild relative chromatin in wheat.

PRADA: pipeline for RNA sequencing data analysis.

PubMed

Torres-García, Wandaliz; Zheng, Siyuan; Sivachenko, Andrey; Vegesna, Rahulsimham; Wang, Qianghu; Yao, Rong; Berger, Michael F; Weinstein, John N; Getz, Gad; Verhaak, Roel G W

2014-08-01

Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program.  http://sourceforge.net/projects/prada/  gadgetz@broadinstitute.org or rverhaak@mdanderson.org  Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Extreme-Scale De Novo Genome Assembly

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

Georganas, Evangelos; Hofmeyr, Steven; Egan, Rob

De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMER, a high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. Genome assembly software has many components, each of which stresses different components of a computer system. This chapter explains the computational challenges involved in each step of the HipMer pipeline, the key distributed data structures, and communication costs in detail. We present performance results of assembling the human genome and themore » large hexaploid wheat genome on large supercomputers up to tens of thousands of cores.« less

Computational solutions to large-scale data management and analysis

PubMed Central

Schadt, Eric E.; Linderman, Michael D.; Sorenson, Jon; Lee, Lawrence; Nolan, Garry P.

2011-01-01

Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist — such as cloud and heterogeneous computing — to successfully tackle our big data problems. PMID:20717155

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

PubMed

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

2014-10-01

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

Elimination sequence optimization for SPAR

NASA Technical Reports Server (NTRS)

Hogan, Harry A.

1986-01-01

SPAR is a large-scale computer program for finite element structural analysis. The program allows user specification of the order in which the joints of a structure are to be eliminated since this order can have significant influence over solution performance, in terms of both storage requirements and computer time. An efficient elimination sequence can improve performance by over 50% for some problems. Obtaining such sequences, however, requires the expertise of an experienced user and can take hours of tedious effort to affect. Thus, an automatic elimination sequence optimizer would enhance productivity by reducing the analysts' problem definition time and by lowering computer costs. Two possible methods for automating the elimination sequence specifications were examined. Several algorithms based on the graph theory representations of sparse matrices were studied with mixed results. Significant improvement in the program performance was achieved, but sequencing by an experienced user still yields substantially better results. The initial results provide encouraging evidence that the potential benefits of such an automatic sequencer would be well worth the effort.

Sequence stratigraphy and sedimentary study on Mishrif formation of Fauqi Oilfield of Missan in south east Iraq

NASA Astrophysics Data System (ADS)

Sang, Hua; Lin, Changsong; Jiang, Yiming

2017-05-01

The reservoir of Mishrif formation has a large scale distribution of marine facies carbonate sediments in great thickness in central and south east Iraq. Rudist reef and shoal facies limestones of the Mishrif Formation (Late Cenomanian - Middle Turonian) form a great potential reservoir rocks at oilfields and structures of Iraq. Facies modelling was applied to predict the relationship between facies distribution and reservoir characteristics to construct a predictive geologic model which will assist future exploration and development in south east Iraq. Microfacies analysis and electrofacies identification and correlations indicate that the limestone of the Mishrif Formation were mainly deposited in open platform setting. Sequence stratigraphic analyses of the Mishrif Formation indicate 3 third order depositional sequences.

Genomic analysis of organismal complexity in the multicellular green alga Volvox carteri

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

Prochnik, Simon E.; Umen, James; Nedelcu, Aurora

2010-07-01

Analysis of the Volvox carteri genome reveals that this green alga's increased organismal complexity and multicellularity are associated with modifications in protein families shared with its unicellular ancestor, and not with large-scale innovations in protein coding capacity. The multicellular green alga Volvox carteri and its morphologically diverse close relatives (the volvocine algae) are uniquely suited for investigating the evolution of multicellularity and development. We sequenced the 138 Mb genome of V. carteri and compared its {approx}14,500 predicted proteins to those of its unicellular relative, Chlamydomonas reinhardtii. Despite fundamental differences in organismal complexity and life history, the two species have similarmore » protein-coding potentials, and few species-specific protein-coding gene predictions. Interestingly, volvocine algal-specific proteins are enriched in Volvox, including those associated with an expanded and highly compartmentalized extracellular matrix. Our analysis shows that increases in organismal complexity can be associated with modifications of lineage-specific proteins rather than large-scale invention of protein-coding capacity.« less

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

CLAST: CUDA implemented large-scale alignment search tool.

PubMed

Yano, Masahiro; Mori, Hiroshi; Akiyama, Yutaka; Yamada, Takuji; Kurokawa, Ken

2014-12-11

Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets. We developed a tool, which we named CLAST (CUDA implemented large-scale alignment search tool), that enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. CLAST has four main advantages over existing alignment tools. First, CLAST was capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy. Third, CLAST does not need a preprocessed sequence database like Burrows-Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases. Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node. CLAST achieved very high speed (similar to the Burrows-Wheeler Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, and FR-HIT) without the need for extensive database preprocessing or a specialized computing platform. Our results demonstrate that CLAST has the potential to be one of the most powerful and realistic approaches to analyze the massive amount of sequence data from next-generation sequencing technologies.

Quantitative phenotyping via deep barcode sequencing.

PubMed

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

2009-10-01

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

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals

PubMed Central

Knoll-Gellida, Anja; André, Michèle; Gattegno, Tamar; Forgue, Jean; Admon, Arie; Babin, Patrick J

2006-01-01

Background The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases. Results Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin. Conclusion This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development. PMID:16526958

Relative role of transfer zones in controlling sequence stacking patterns and facies distribution: insights from the Fushan Depression, South China Sea

NASA Astrophysics Data System (ADS)

Liu, Entao; Wang, Hua; Li, Yuan; Huang, Chuanyan

2015-04-01

In sedimentary basins, a transfer zone can be defined as a coordinated system of deformational features which has good prospects for hydrocarbon exploration. Although the term 'transfer zone' has been widely applied to the study of extensional basins, little attention has been paid to its controlling effect on sequence tracking pattern and depositional facies distribution. Fushan Depression is a half-graben rift sub-basin, located in the southeast of the Beibuwan Basin, South China Sea. In this study, comparative analysis of seismic reflection, palaeogeomorphology, fault activity and depositional facies distribution in the southern slope indicates that three different types of sequence stacking patterns (i.e. multi-level step-fault belt in the western area, flexure slope belt in the central area, gentle slope belt in the eastern area) were developed along the southern slope, together with a large-scale transfer zone in the central area, at the intersection of the western and eastern fault systems. Further analysis shows that the transfer zone played an important role in the diversity of sequence stacking patterns in the southern slope by dividing the Fushan Depression into two non-interfering tectonic systems forming different sequence patterns, and leading to the formation of the flexure slope belt in the central area. The transfer zone had an important controlling effect on not only the diversity of sequence tracking patterns, but also the facies distribution on the relay ramp. During the high-stand stage, under the controlling effect of the transfer zone, the sediments contain a significant proportion of coarser material accumulated and distributed along the ramp axis. By contrast, during the low-stand stage, the transfer zone did not seem to contribute significantly to the low-stand fan distribution which was mainly controlled by the slope gradient (palaeogeomorphology). Therefore, analysis of the transfer zone can provide a new perspective for basin analysis. In addition, the transfer zone area demonstrated unique hydrocarbon accumulation models different from the western and eastern areas. It was not only a structural high combined with sufficient coarse-grained reservoir quality sands, but was also associated with large-scale sublacustrine fan deposits with high quality reservoirs, indicating that the recognition of transfer zones can improve the prediction of hydrocarbon occurrences in similar settings.

Functional annotation of HOT regions in the human genome: implications for human disease and cancer

PubMed Central

Li, Hao; Chen, Hebing; Liu, Feng; Ren, Chao; Wang, Shengqi; Bo, Xiaochen; Shu, Wenjie

2015-01-01

Advances in genome-wide association studies (GWAS) and large-scale sequencing studies have resulted in an impressive and growing list of disease- and trait-associated genetic variants. Most studies have emphasised the discovery of genetic variation in coding sequences, however, the noncoding regulatory effects responsible for human disease and cancer biology have been substantially understudied. To better characterise the cis-regulatory effects of noncoding variation, we performed a comprehensive analysis of the genetic variants in HOT (high-occupancy target) regions, which are considered to be one of the most intriguing findings of recent large-scale sequencing studies. We observed that GWAS variants that map to HOT regions undergo a substantial net decrease and illustrate development-specific localisation during haematopoiesis. Additionally, genetic risk variants are disproportionally enriched in HOT regions compared with LOT (low-occupancy target) regions in both disease-relevant and cancer cells. Importantly, this enrichment is biased toward disease- or cancer-specific cell types. Furthermore, we observed that cancer cells generally acquire cancer-specific HOT regions at oncogenes through diverse mechanisms of cancer pathogenesis. Collectively, our findings demonstrate the key roles of HOT regions in human disease and cancer and represent a critical step toward further understanding disease biology, diagnosis, and therapy. PMID:26113264

Functional annotation of HOT regions in the human genome: implications for human disease and cancer.

PubMed

Li, Hao; Chen, Hebing; Liu, Feng; Ren, Chao; Wang, Shengqi; Bo, Xiaochen; Shu, Wenjie

2015-06-26

Advances in genome-wide association studies (GWAS) and large-scale sequencing studies have resulted in an impressive and growing list of disease- and trait-associated genetic variants. Most studies have emphasised the discovery of genetic variation in coding sequences, however, the noncoding regulatory effects responsible for human disease and cancer biology have been substantially understudied. To better characterise the cis-regulatory effects of noncoding variation, we performed a comprehensive analysis of the genetic variants in HOT (high-occupancy target) regions, which are considered to be one of the most intriguing findings of recent large-scale sequencing studies. We observed that GWAS variants that map to HOT regions undergo a substantial net decrease and illustrate development-specific localisation during haematopoiesis. Additionally, genetic risk variants are disproportionally enriched in HOT regions compared with LOT (low-occupancy target) regions in both disease-relevant and cancer cells. Importantly, this enrichment is biased toward disease- or cancer-specific cell types. Furthermore, we observed that cancer cells generally acquire cancer-specific HOT regions at oncogenes through diverse mechanisms of cancer pathogenesis. Collectively, our findings demonstrate the key roles of HOT regions in human disease and cancer and represent a critical step toward further understanding disease biology, diagnosis, and therapy.

An efficient procedure for the expression and purification of HIV-1 protease from inclusion bodies.

PubMed

Nguyen, Hong-Loan Thi; Nguyen, Thuy Thi; Vu, Quy Thi; Le, Hang Thi; Pham, Yen; Trinh, Phuong Le; Bui, Thuan Phuong; Phan, Tuan-Nghia

2015-12-01

Several studies have focused on HIV-1 protease for developing drugs for treating AIDS. Recombinant HIV-1 protease is used to screen new drugs from synthetic compounds or natural substances. However, large-scale expression and purification of this enzyme is difficult mainly because of its low expression and solubility. In this study, we constructed 9 recombinant plasmids containing a sequence encoding HIV-1 protease along with different fusion tags and examined the expression of the enzyme from these plasmids. Of the 9 plasmids, pET32a(+) plasmid containing the HIV-1 protease-encoding sequence along with sequences encoding an autocleavage site GTVSFNF at the N-terminus and TEV plus 6× His tag at the C-terminus showed the highest expression of the enzyme and was selected for further analysis. The recombinant protein was isolated from inclusion bodies by using 2 tandem Q- and Ni-Sepharose columns. SDS-PAGE of the obtained HIV-1 protease produced a single band of approximately 13 kDa. The enzyme was recovered efficiently (4 mg protein/L of cell culture) and had high specific activity of 1190 nmol min(-1) mg(-1) at an optimal pH of 4.7 and optimal temperature of 37 °C. This procedure for expressing and purifying HIV-1 protease is now being scaled up to produce the enzyme on a large scale for its application. Copyright © 2015 Elsevier Inc. All rights reserved.

Universal sequence map (USM) of arbitrary discrete sequences

PubMed Central

2002-01-01

Background For over a decade the idea of representing biological sequences in a continuous coordinate space has maintained its appeal but not been fully realized. The basic idea is that any sequence of symbols may define trajectories in the continuous space conserving all its statistical properties. Ideally, such a representation would allow scale independent sequence analysis – without the context of fixed memory length. A simple example would consist on being able to infer the homology between two sequences solely by comparing the coordinates of any two homologous units. Results We have successfully identified such an iterative function for bijective mappingψ of discrete sequences into objects of continuous state space that enable scale-independent sequence analysis. The technique, named Universal Sequence Mapping (USM), is applicable to sequences with an arbitrary length and arbitrary number of unique units and generates a representation where map distance estimates sequence similarity. The novel USM procedure is based on earlier work by these and other authors on the properties of Chaos Game Representation (CGR). The latter enables the representation of 4 unit type sequences (like DNA) as an order free Markov Chain transition table. The properties of USM are illustrated with test data and can be verified for other data by using the accompanying web-based tool:http://bioinformatics.musc.edu/~jonas/usm/. Conclusions USM is shown to enable a statistical mechanics approach to sequence analysis. The scale independent representation frees sequence analysis from the need to assume a memory length in the investigation of syntactic rules. PMID:11895567

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

DOE PAGES

Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; ...

2015-06-01

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

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

USDA-ARS?s Scientific Manuscript database

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

In silico prediction of splice-altering single nucleotide variants in the human genome.

PubMed

Jian, Xueqiu; Boerwinkle, Eric; Liu, Xiaoming

2014-12-16

In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools only predict potential splice sites given a DNA sequence without measuring splicing signal changes caused by a variant. Another limitation is the lack of large-scale evaluation studies of these tools. We compared eight in silico tools on 2959 single nucleotide variants within splicing consensus regions (scSNVs) using receiver operating characteristic analysis. The Position Weight Matrix model and MaxEntScan outperformed other methods. Two ensemble learning methods, adaptive boosting and random forests, were used to construct models that take advantage of individual methods. Both models further improved prediction, with outputs of directly interpretable prediction scores. We applied our ensemble scores to scSNVs from the Catalogue of Somatic Mutations in Cancer database. Analysis showed that predicted splice-altering scSNVs are enriched in recurrent scSNVs and known cancer genes. We pre-computed our ensemble scores for all potential scSNVs across the human genome, providing a whole genome level resource for identifying splice-altering scSNVs discovered from large-scale sequencing studies.

BRepertoire: a user-friendly web server for analysing antibody repertoire data.

PubMed

Margreitter, Christian; Lu, Hui-Chun; Townsend, Catherine; Stewart, Alexander; Dunn-Walters, Deborah K; Fraternali, Franca

2018-04-14

Antibody repertoire analysis by high throughput sequencing is now widely used, but a persisting challenge is enabling immunologists to explore their data to discover discriminating repertoire features for their own particular investigations. Computational methods are necessary for large-scale evaluation of antibody properties. We have developed BRepertoire, a suite of user-friendly web-based software tools for large-scale statistical analyses of repertoire data. The software is able to use data preprocessed by IMGT, and performs statistical and comparative analyses with versatile plotting options. BRepertoire has been designed to operate in various modes, for example analysing sequence-specific V(D)J gene usage, discerning physico-chemical properties of the CDR regions and clustering of clonotypes. Those analyses are performed on the fly by a number of R packages and are deployed by a shiny web platform. The user can download the analysed data in different table formats and save the generated plots as image files ready for publication. We believe BRepertoire to be a versatile analytical tool that complements experimental studies of immune repertoires. To illustrate the server's functionality, we show use cases including differential gene usage in a vaccination dataset and analysis of CDR3H properties in old and young individuals. The server is accessible under http://mabra.biomed.kcl.ac.uk/BRepertoire.

Targeted enrichment strategies for next-generation plant biology

Treesearch

Richard Cronn; Brian J. Knaus; Aaron Liston; Peter J. Maughan; Matthew Parks; John V. Syring; Joshua Udall

2012-01-01

The dramatic advances offered by modem DNA sequencers continue to redefine the limits of what can be accomplished in comparative plant biology. Even with recent achievements, however, plant genomes present obstacles that can make it difficult to execute large-scale population and phylogenetic studies on next-generation sequencing platforms. Factors like large genome...

Increased Sensitivity of Diagnostic Mutation Detection by Re-analysis Incorporating Local Reassembly of Sequence Reads.

PubMed

Watson, Christopher M; Camm, Nick; Crinnion, Laura A; Clokie, Samuel; Robinson, Rachel L; Adlard, Julian; Charlton, Ruth; Markham, Alexander F; Carr, Ian M; Bonthron, David T

2017-12-01

Diagnostic genetic testing programmes based on next-generation DNA sequencing have resulted in the accrual of large datasets of targeted raw sequence data. Most diagnostic laboratories process these data through an automated variant-calling pipeline. Validation of the chosen analytical methods typically depends on confirming the detection of known sequence variants. Despite improvements in short-read alignment methods, current pipelines are known to be comparatively poor at detecting large insertion/deletion mutations. We performed clinical validation of a local reassembly tool, ABRA (assembly-based realigner), through retrospective reanalysis of a cohort of more than 2000 hereditary cancer cases. ABRA enabled detection of a 96-bp deletion, 4-bp insertion mutation in PMS2 that had been initially identified using a comparative read-depth approach. We applied an updated pipeline incorporating ABRA to the entire cohort of 2000 cases and identified one previously undetected pathogenic variant, a 23-bp duplication in PTEN. We demonstrate the effect of read length on the ability to detect insertion/deletion variants by comparing HiSeq2500 (2 × 101-bp) and NextSeq500 (2 × 151-bp) sequence data for a range of variants and thereby show that the limitations of shorter read lengths can be mitigated using appropriate informatics tools. This work highlights the need for ongoing development of diagnostic pipelines to maximize test sensitivity. We also draw attention to the large differences in computational infrastructure required to perform day-to-day versus large-scale reprocessing tasks.

GAP Final Technical Report 12-14-04

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

Andrew J. Bordner, PhD, Senior Research Scientist

2004-12-14

The Genomics Annotation Platform (GAP) was designed to develop new tools for high throughput functional annotation and characterization of protein sequences and structures resulting from genomics and structural proteomics, benchmarking and application of those tools. Furthermore, this platform integrated the genomic scale sequence and structural analysis and prediction tools with the advanced structure prediction and bioinformatics environment of ICM. The development of GAP was primarily oriented towards the annotation of new biomolecular structures using both structural and sequence data. Even though the amount of protein X-ray crystal data is growing exponentially, the volume of sequence data is growing even moremore » rapidly. This trend was exploited by leveraging the wealth of sequence data to provide functional annotation for protein structures. The additional information provided by GAP is expected to assist the majority of the commercial users of ICM, who are involved in drug discovery, in identifying promising drug targets as well in devising strategies for the rational design of therapeutics directed at the protein of interest. The GAP also provided valuable tools for biochemistry education, and structural genomics centers. In addition, GAP incorporates many novel prediction and analysis methods not available in other molecular modeling packages. This development led to signing the first Molsoft agreement in the structural genomics annotation area with the University of oxford Structural Genomics Center. This commercial agreement validated the Molsoft efforts under the GAP project and provided the basis for further development of the large scale functional annotation platform.« less

PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

PubMed

Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

2017-01-04

The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Large-scale sequence and structural comparisons of human naive and antigen-experienced antibody repertoires

PubMed Central

DeKosky, Brandon J.; Lungu, Oana I.; Park, Daechan; Johnson, Erik L.; Charab, Wissam; Chrysostomou, Constantine; Kuroda, Daisuke; Ellington, Andrew D.; Ippolito, Gregory C.; Gray, Jeffrey J.; Georgiou, George

2016-01-01

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy- and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19+CD20+CD27− IgM-naive B cells, >120,000 antibody clusters from CD19+CD20+CD27+ antigen–experienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ–Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease. PMID:27114511

Large scale wind tunnel investigation of a folding tilt rotor

NASA Technical Reports Server (NTRS)

1972-01-01

A twenty-five foot diameter folding tilt rotor was tested in a large scale wind tunnel to determine its aerodynamic characteristics in unfolded, partially folded, and fully folded configurations. During the tests, the rotor completed over forty start/stop sequences. After completing the sequences in a stepwise manner, smooth start/stop transitions were made in approximately two seconds. Wind tunnel speeds up through seventy-five knots were used, at which point the rotor mast angle was increased to four degrees, corresponding to a maneuver condition of one and one-half g.

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies.

PubMed

Furnham, Nicholas; Dawson, Natalie L; Rahman, Syed A; Thornton, Janet M; Orengo, Christine A

2016-01-29

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mobile element biology – new possibilities with high-throughput sequencing

PubMed Central

Xing, Jinchuan; Witherspoon, David J.; Jorde, Lynn B.

2014-01-01

Mobile elements compose more than half of the human genome, but until recently their large-scale detection was time-consuming and challenging. With the development of new high-throughput sequencing technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. We review several high-throughput methods, with an emphasis on techniques that specifically target mobile element insertions in humans, and we highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human cancers. PMID:23312846

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Wheeler, David L

2008-01-01

GenBank (R) is a comprehensive database that contains publicly available nucleotide sequences for more than 260 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.

GenBank

PubMed Central

Benson, Dennis A.; Karsch-Mizrachi, Ilene; Lipman, David J.; Ostell, James; Wheeler, David L.

2008-01-01

GenBank (R) is a comprehensive database that contains publicly available nucleotide sequences for more than 260 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov PMID:18073190

Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS.

PubMed

Warris, Sven; Yalcin, Feyruz; Jackson, Katherine J L; Nap, Jan Peter

2015-01-01

To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis. With the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation.

Characterization and prediction of residues determining protein functional specificity.

PubMed

Capra, John A; Singh, Mona

2008-07-01

Within a homologous protein family, proteins may be grouped into subtypes that share specific functions that are not common to the entire family. Often, the amino acids present in a small number of sequence positions determine each protein's particular functional specificity. Knowledge of these specificity determining positions (SDPs) aids in protein function prediction, drug design and experimental analysis. A number of sequence-based computational methods have been introduced for identifying SDPs; however, their further development and evaluation have been hindered by the limited number of known experimentally determined SDPs. We combine several bioinformatics resources to automate a process, typically undertaken manually, to build a dataset of SDPs. The resulting large dataset, which consists of SDPs in enzymes, enables us to characterize SDPs in terms of their physicochemical and evolutionary properties. It also facilitates the large-scale evaluation of sequence-based SDP prediction methods. We present a simple sequence-based SDP prediction method, GroupSim, and show that, surprisingly, it is competitive with a representative set of current methods. We also describe ConsWin, a heuristic that considers sequence conservation of neighboring amino acids, and demonstrate that it improves the performance of all methods tested on our large dataset of enzyme SDPs. Datasets and GroupSim code are available online at http://compbio.cs.princeton.edu/specificity/. Supplementary data are available at Bioinformatics online.

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics

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

Taylor, Ronald C.

Bioinformatics researchers are increasingly confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBasemore » project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date.« less

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

PubMed

Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

2012-01-01

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

Development of renormalization group analysis of turbulence

NASA Technical Reports Server (NTRS)

Smith, L. M.

1990-01-01

The renormalization group (RG) procedure for nonlinear, dissipative systems is now quite standard, and its applications to the problem of hydrodynamic turbulence are becoming well known. In summary, the RG method isolates self similar behavior and provides a systematic procedure to describe scale invariant dynamics in terms of large scale variables only. The parameterization of the small scales in a self consistent manner has important implications for sub-grid modeling. This paper develops the homogeneous, isotropic turbulence and addresses the meaning and consequence of epsilon-expansion. The theory is then extended to include a weak mean flow and application of the RG method to a sequence of models is shown to converge to the Navier-Stokes equations.

Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency.

PubMed

Aniceto, Rodrigo; Xavier, Rene; Guimarães, Valeria; Hondo, Fernanda; Holanda, Maristela; Walter, Maria Emilia; Lifschitz, Sérgio

2015-01-01

Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB.

'Big data', Hadoop and cloud computing in genomics.

PubMed

O'Driscoll, Aisling; Daugelaite, Jurate; Sleator, Roy D

2013-10-01

Since the completion of the Human Genome project at the turn of the Century, there has been an unprecedented proliferation of genomic sequence data. A consequence of this is that the medical discoveries of the future will largely depend on our ability to process and analyse large genomic data sets, which continue to expand as the cost of sequencing decreases. Herein, we provide an overview of cloud computing and big data technologies, and discuss how such expertise can be used to deal with biology's big data sets. In particular, big data technologies such as the Apache Hadoop project, which provides distributed and parallelised data processing and analysis of petabyte (PB) scale data sets will be discussed, together with an overview of the current usage of Hadoop within the bioinformatics community. Copyright © 2013 Elsevier Inc. All rights reserved.

Legume genome evolution viewed through the Medicago truncatula and Lotus japonicus genomes

PubMed Central

Cannon, Steven B.; Sterck, Lieven; Rombauts, Stephane; Sato, Shusei; Cheung, Foo; Gouzy, Jérôme; Wang, Xiaohong; Mudge, Joann; Vasdewani, Jayprakash; Schiex, Thomas; Spannagl, Manuel; Monaghan, Erin; Nicholson, Christine; Humphray, Sean J.; Schoof, Heiko; Mayer, Klaus F. X.; Rogers, Jane; Quétier, Francis; Oldroyd, Giles E.; Debellé, Frédéric; Cook, Douglas R.; Retzel, Ernest F.; Roe, Bruce A.; Town, Christopher D.; Tabata, Satoshi; Van de Peer, Yves; Young, Nevin D.

2006-01-01

Genome sequencing of the model legumes, Medicago truncatula and Lotus japonicus, provides an opportunity for large-scale sequence-based comparison of two genomes in the same plant family. Here we report synteny comparisons between these species, including details about chromosome relationships, large-scale synteny blocks, microsynteny within blocks, and genome regions lacking clear correspondence. The Lotus and Medicago genomes share a minimum of 10 large-scale synteny blocks, each with substantial collinearity and frequently extending the length of whole chromosome arms. The proportion of genes syntenic and collinear within each synteny block is relatively homogeneous. Medicago–Lotus comparisons also indicate similar and largely homogeneous gene densities, although gene-containing regions in Mt occupy 20–30% more space than Lj counterparts, primarily because of larger numbers of Mt retrotransposons. Because the interpretation of genome comparisons is complicated by large-scale genome duplications, we describe synteny, synonymous substitutions and phylogenetic analyses to identify and date a probable whole-genome duplication event. There is no direct evidence for any recent large-scale genome duplication in either Medicago or Lotus but instead a duplication predating speciation. Phylogenetic comparisons place this duplication within the Rosid I clade, clearly after the split between legumes and Salicaceae (poplar). PMID:17003129

Delimiting Coalescence Genes (C-Genes) in Phylogenomic Data Sets.

PubMed

Springer, Mark S; Gatesy, John

2018-02-26

coalescence methods have emerged as a popular alternative for inferring species trees with large genomic datasets, because these methods explicitly account for incomplete lineage sorting. However, statistical consistency of summary coalescence methods is not guaranteed unless several model assumptions are true, including the critical assumption that recombination occurs freely among but not within coalescence genes (c-genes), which are the fundamental units of analysis for these methods. Each c-gene has a single branching history, and large sets of these independent gene histories should be the input for genome-scale coalescence estimates of phylogeny. By contrast, numerous studies have reported the results of coalescence analyses in which complete protein-coding sequences are treated as c-genes even though exons for these loci can span more than a megabase of DNA. Empirical estimates of recombination breakpoints suggest that c-genes may be much shorter, especially when large clades with many species are the focus of analysis. Although this idea has been challenged recently in the literature, the inverse relationship between c-gene size and increased taxon sampling in a dataset-the 'recombination ratchet'-is a fundamental property of c-genes. For taxonomic groups characterized by genes with long intron sequences, complete protein-coding sequences are likely not valid c-genes and are inappropriate units of analysis for summary coalescence methods unless they occur in recombination deserts that are devoid of incomplete lineage sorting (ILS). Finally, it has been argued that coalescence methods are robust when the no-recombination within loci assumption is violated, but recombination must matter at some scale because ILS, a by-product of recombination, is the raison d'etre for coalescence methods. That is, extensive recombination is required to yield the large number of independently segregating c-genes used to infer a species tree. If coalescent methods are powerful enough to infer the correct species tree for difficult phylogenetic problems in the anomaly zone, where concatenation is expected to fail because of ILS, then there should be a decreasing probability of inferring the correct species tree using longer loci with many intralocus recombination breakpoints (i.e., increased levels of concatenation).

Delimiting Coalescence Genes (C-Genes) in Phylogenomic Data Sets

PubMed Central

Springer, Mark S.; Gatesy, John

2018-01-01

Summary coalescence methods have emerged as a popular alternative for inferring species trees with large genomic datasets, because these methods explicitly account for incomplete lineage sorting. However, statistical consistency of summary coalescence methods is not guaranteed unless several model assumptions are true, including the critical assumption that recombination occurs freely among but not within coalescence genes (c-genes), which are the fundamental units of analysis for these methods. Each c-gene has a single branching history, and large sets of these independent gene histories should be the input for genome-scale coalescence estimates of phylogeny. By contrast, numerous studies have reported the results of coalescence analyses in which complete protein-coding sequences are treated as c-genes even though exons for these loci can span more than a megabase of DNA. Empirical estimates of recombination breakpoints suggest that c-genes may be much shorter, especially when large clades with many species are the focus of analysis. Although this idea has been challenged recently in the literature, the inverse relationship between c-gene size and increased taxon sampling in a dataset—the ‘recombination ratchet’—is a fundamental property of c-genes. For taxonomic groups characterized by genes with long intron sequences, complete protein-coding sequences are likely not valid c-genes and are inappropriate units of analysis for summary coalescence methods unless they occur in recombination deserts that are devoid of incomplete lineage sorting (ILS). Finally, it has been argued that coalescence methods are robust when the no-recombination within loci assumption is violated, but recombination must matter at some scale because ILS, a by-product of recombination, is the raison d’etre for coalescence methods. That is, extensive recombination is required to yield the large number of independently segregating c-genes used to infer a species tree. If coalescent methods are powerful enough to infer the correct species tree for difficult phylogenetic problems in the anomaly zone, where concatenation is expected to fail because of ILS, then there should be a decreasing probability of inferring the correct species tree using longer loci with many intralocus recombination breakpoints (i.e., increased levels of concatenation). PMID:29495400

Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns.

PubMed

Shen, Hui; Jin, Dongmei; Shu, Jiang-Ping; Zhou, Xi-Le; Lei, Ming; Wei, Ran; Shang, Hui; Wei, Hong-Jin; Zhang, Rui; Liu, Li; Gu, Yu-Feng; Zhang, Xian-Chun; Yan, Yue-Hong

2018-02-01

Ferns, originated about 360 million years ago, are the sister group of seed plants. Despite the remarkable progress in our understanding of fern phylogeny, with conflicting molecular evidence and different morphological interpretations, relationships among major fern lineages remain controversial. With the aim to obtain a robust fern phylogeny, we carried out a large-scale phylogenomic analysis using high-quality transcriptome sequencing data, which covered 69 fern species from 38 families and 11 orders. Both coalescent-based and concatenation-based methods were applied to both nucleotide and amino acid sequences in species tree estimation. The resulting topologies are largely congruent with each other, except for the placement of Angiopteris fokiensis, Cheiropleuria bicuspis, Diplaziopsis brunoniana, Matteuccia struthiopteris, Elaphoglossum mcclurei, and Tectaria subpedata. Our result confirmed that Equisetales is sister to the rest of ferns, and Dennstaedtiaceae is sister to eupolypods. Moreover, our result strongly supported some relationships different from the current view of fern phylogeny, including that Marattiaceae may be sister to the monophyletic clade of Psilotaceae and Ophioglossaceae; that Gleicheniaceae and Hymenophyllaceae form a monophyletic clade sister to Dipteridaceae; and that Aspleniaceae is sister to the rest of the groups in eupolypods II. These results were interpreted with morphological traits, especially sporangia characters, and a new evolutionary route of sporangial annulus in ferns was suggested. This backbone phylogeny in ferns sets a foundation for further studies in biology and evolution in ferns, and therefore in plants. © The Authors 2017. Published by Oxford University Press.

Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns

PubMed Central

Shen, Hui; Jin, Dongmei; Shu, Jiang-Ping; Zhou, Xi-Le; Lei, Ming; Wei, Ran; Shang, Hui; Wei, Hong-Jin; Zhang, Rui; Liu, Li; Gu, Yu-Feng; Zhang, Xian-Chun; Yan, Yue-Hong

2018-01-01

Abstract Background Ferns, originated about 360 million years ago, are the sister group of seed plants. Despite the remarkable progress in our understanding of fern phylogeny, with conflicting molecular evidence and different morphological interpretations, relationships among major fern lineages remain controversial. Results With the aim to obtain a robust fern phylogeny, we carried out a large-scale phylogenomic analysis using high-quality transcriptome sequencing data, which covered 69 fern species from 38 families and 11 orders. Both coalescent-based and concatenation-based methods were applied to both nucleotide and amino acid sequences in species tree estimation. The resulting topologies are largely congruent with each other, except for the placement of Angiopteris fokiensis, Cheiropleuria bicuspis, Diplaziopsis brunoniana, Matteuccia struthiopteris, Elaphoglossum mcclurei, and Tectaria subpedata. Conclusions Our result confirmed that Equisetales is sister to the rest of ferns, and Dennstaedtiaceae is sister to eupolypods. Moreover, our result strongly supported some relationships different from the current view of fern phylogeny, including that Marattiaceae may be sister to the monophyletic clade of Psilotaceae and Ophioglossaceae; that Gleicheniaceae and Hymenophyllaceae form a monophyletic clade sister to Dipteridaceae; and that Aspleniaceae is sister to the rest of the groups in eupolypods II. These results were interpreted with morphological traits, especially sporangia characters, and a new evolutionary route of sporangial annulus in ferns was suggested. This backbone phylogeny in ferns sets a foundation for further studies in biology and evolution in ferns, and therefore in plants. PMID:29186447

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

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

XLID-Causing Mutations and Associated Genes Challenged in Light of Data From Large-Scale Human Exome Sequencing

PubMed Central

Piton, Amélie; Redin, Claire; Mandel, Jean-Louis

2013-01-01

Because of the unbalanced sex ratio (1.3–1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases. PMID:23871722

Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection.

PubMed

Wang, Kai; Zhang, Xianmin; Ota, Jun; Huang, Yanjiang

2018-02-24

This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods.

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

PubMed Central

2013-01-01

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

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

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

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

Quantitative phenotyping via deep barcode sequencing

PubMed Central

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

2009-01-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or “Bar-seq,” outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that ∼20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene–environment interactions on a genome-wide scale. PMID:19622793

Overcoming Sequence Misalignments with Weighted Structural Superposition

PubMed Central

Khazanov, Nickolay A.; Damm-Ganamet, Kelly L.; Quang, Daniel X.; Carlson, Heather A.

2012-01-01

An appropriate structural superposition identifies similarities and differences between homologous proteins that are not evident from sequence alignments alone. We have coupled our Gaussian-weighted RMSD (wRMSD) tool with a sequence aligner and seed extension (SE) algorithm to create a robust technique for overlaying structures and aligning sequences of homologous proteins (HwRMSD). HwRMSD overcomes errors in the initial sequence alignment that would normally propagate into a standard RMSD overlay. SE can generate a corrected sequence alignment from the improved structural superposition obtained by wRMSD. HwRMSD’s robust performance and its superiority over standard RMSD are demonstrated over a range of homologous proteins. Its better overlay results in corrected sequence alignments with good agreement to HOMSTRAD. Finally, HwRMSD is compared to established structural alignment methods: FATCAT, SSM, CE, and Dalilite. Most methods are comparable at placing residue pairs within 2 Å, but HwRMSD places many more residue pairs within 1 Å, providing a clear advantage. Such high accuracy is essential in drug design, where small distances can have a large impact on computational predictions. This level of accuracy is also needed to correct sequence alignments in an automated fashion, especially for omics-scale analysis. HwRMSD can align homologs with low sequence identity and large conformational differences, cases where both sequence-based and structural-based methods may fail. The HwRMSD pipeline overcomes the dependency of structural overlays on initial sequence pairing and removes the need to determine the best sequence-alignment method, substitution matrix, and gap parameters for each unique pair of homologs. PMID:22733542

MytiBase: a knowledgebase of mussel (M. galloprovincialis) transcribed sequences

PubMed Central

Venier, Paola; De Pittà, Cristiano; Bernante, Filippo; Varotto, Laura; De Nardi, Barbara; Bovo, Giuseppe; Roch, Philippe; Novoa, Beatriz; Figueras, Antonio; Pallavicini, Alberto; Lanfranchi, Gerolamo

2009-01-01

Background Although Bivalves are among the most studied marine organisms due to their ecological role, economic importance and use in pollution biomonitoring, very little information is available on the genome sequences of mussels. This study reports the functional analysis of a large-scale Expressed Sequence Tag (EST) sequencing from different tissues of Mytilus galloprovincialis (the Mediterranean mussel) challenged with toxic pollutants, temperature and potentially pathogenic bacteria. Results We have constructed and sequenced seventeen cDNA libraries from different Mediterranean mussel tissues: gills, digestive gland, foot, anterior and posterior adductor muscle, mantle and haemocytes. A total of 24,939 clones were sequenced from these libraries generating 18,788 high-quality ESTs which were assembled into 2,446 overlapping clusters and 4,666 singletons resulting in a total of 7,112 non-redundant sequences. In particular, a high-quality normalized cDNA library (Nor01) was constructed as determined by the high rate of gene discovery (65.6%). Bioinformatic screening of the non-redundant M. galloprovincialis sequences identified 159 microsatellite-containing ESTs. Clusters, consensuses, related similarities and gene ontology searches have been organized in a dedicated, searchable database . Conclusion We defined the first species-specific catalogue of M. galloprovincialis ESTs including 7,112 unique transcribed sequences. Putative microsatellite markers were identified. This annotated catalogue represents a valuable platform for expression studies, marker validation and genetic linkage analysis for investigations in the biology of Mediterranean mussels. PMID:19203376

Pipeline for large-scale microdroplet bisulfite PCR-based sequencing allows the tracking of hepitype evolution in tumors.

PubMed

Herrmann, Alexander; Haake, Andrea; Ammerpohl, Ole; Martin-Guerrero, Idoia; Szafranski, Karol; Stemshorn, Kathryn; Nothnagel, Michael; Kotsopoulos, Steve K; Richter, Julia; Warner, Jason; Olson, Jeff; Link, Darren R; Schreiber, Stefan; Krawczak, Michael; Platzer, Matthias; Nürnberg, Peter; Siebert, Reiner; Hampe, Jochen

2011-01-01

Cytosine methylation provides an epigenetic level of cellular plasticity that is important for development, differentiation and cancerogenesis. We adopted microdroplet PCR to bisulfite treated target DNA in combination with second generation sequencing to simultaneously assess DNA sequence and methylation. We show measurement of methylation status in a wide range of target sequences (total 34 kb) with an average coverage of 95% (median 100%) and good correlation to the opposite strand (rho = 0.96) and to pyrosequencing (rho = 0.87). Data from lymphoma and colorectal cancer samples for SNRPN (imprinted gene), FGF6 (demethylated in the cancer samples) and HS3ST2 (methylated in the cancer samples) serve as a proof of principle showing the integration of SNP data and phased DNA-methylation information into "hepitypes" and thus the analysis of DNA methylation phylogeny in the somatic evolution of cancer.

Rapid protein alignment in the cloud: HAMOND combines fast DIAMOND alignments with Hadoop parallelism.

PubMed

Yu, Jia; Blom, Jochen; Sczyrba, Alexander; Goesmann, Alexander

2017-09-10

The introduction of next generation sequencing has caused a steady increase in the amounts of data that have to be processed in modern life science. Sequence alignment plays a key role in the analysis of sequencing data e.g. within whole genome sequencing or metagenome projects. BLAST is a commonly used alignment tool that was the standard approach for more than two decades, but in the last years faster alternatives have been proposed including RapSearch, GHOSTX, and DIAMOND. Here we introduce HAMOND, an application that uses Apache Hadoop to parallelize DIAMOND computation in order to scale-out the calculation of alignments. HAMOND is fault tolerant and scalable by utilizing large cloud computing infrastructures like Amazon Web Services. HAMOND has been tested in comparative genomics analyses and showed promising results both in efficiency and accuracy. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Mercury BLASTP: Accelerating Protein Sequence Alignment

PubMed Central

Jacob, Arpith; Lancaster, Joseph; Buhler, Jeremy; Harris, Brandon; Chamberlain, Roger D.

2008-01-01

Large-scale protein sequence comparison is an important but compute-intensive task in molecular biology. BLASTP is the most popular tool for comparative analysis of protein sequences. In recent years, an exponential increase in the size of protein sequence databases has required either exponentially more running time or a cluster of machines to keep pace. To address this problem, we have designed and built a high-performance FPGA-accelerated version of BLASTP, Mercury BLASTP. In this paper, we describe the architecture of the portions of the application that are accelerated in the FPGA, and we also describe the integration of these FPGA-accelerated portions with the existing BLASTP software. We have implemented Mercury BLASTP on a commodity workstation with two Xilinx Virtex-II 6000 FPGAs. We show that the new design runs 11-15 times faster than software BLASTP on a modern CPU while delivering close to 99% identical results. PMID:19492068

From the genome sequence to the protein inventory of Bacillus subtilis.

PubMed

Becher, Dörte; Büttner, Knut; Moche, Martin; Hessling, Bernd; Hecker, Michael

2011-08-01

Owing to the low number of proteins necessary to render a bacterial cell viable, bacteria are extremely attractive model systems to understand how the genome sequence is translated into actual life processes. One of the most intensively investigated model organisms is Bacillus subtilis. It has attracted world-wide research interest, addressing cell differentiation and adaptation on a molecular scale as well as biotechnological production processes. Meanwhile, we are looking back on more than 25 years of B. subtilis proteomics. A wide range of methods have been developed during this period for the large-scale qualitative and quantitative proteome analysis. Currently, it is possible to identify and quantify more than 50% of the predicted proteome in different cellular subfractions. In this review, we summarize the development of B. subtilis proteomics during the past 25 years. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

USGS Publications Warehouse

Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.

2017-01-01

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

PubMed Central

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

2013-01-01

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

Integration, warehousing, and analysis strategies of Omics data.

PubMed

Gedela, Srinubabu

2011-01-01

"-Omics" is a current suffix for numerous types of large-scale biological data generation procedures, which naturally demand the development of novel algorithms for data storage and analysis. With next generation genome sequencing burgeoning, it is pivotal to decipher a coding site on the genome, a gene's function, and information on transcripts next to the pure availability of sequence information. To explore a genome and downstream molecular processes, we need umpteen results at the various levels of cellular organization by utilizing different experimental designs, data analysis strategies and methodologies. Here comes the need for controlled vocabularies and data integration to annotate, store, and update the flow of experimental data. This chapter explores key methodologies to merge Omics data by semantic data carriers, discusses controlled vocabularies as eXtensible Markup Languages (XML), and provides practical guidance, databases, and software links supporting the integration of Omics data.

[Isolation and function of genes regulating aphB expression in Vibrio cholerae].

PubMed

Chen, Haili; Zhu, Zhaoqin; Zhong, Zengtao; Zhu, Jun; Kan, Biao

2012-02-04

We identified genes that regulate the expression of aphB, the gene encoding a key virulence regulator in Vibrio cholerae O1 E1 Tor C6706(-). We constructed a transposon library in V. cholerae C6706 strain containing a P(aphB)-luxCDABE and P(aphB)-lacZ transcriptional reporter plasmids. Using a chemiluminescence imager system, we rapidly detected aphB promoter expression level at a large scale. We then sequenced the transposon insertion sites by arbitrary PCR and sequencing analysis. We obtained two candidate mutants T1 and T2 which displayed reduced aphB expression from approximately 40,000 transposon insertion mutants. Sequencing analysis shows that Tn inserted in vc1585 reading frame in the T1 mutant and Tn inserted in the end of coding sequence of vc1602 in the T2 mutant. By using a genetic screen, we identified two potential genes that may involve in regulation of the expression of the key virulence regulator AphB. This study sheds light on our further investigation to fully understand V. cholerae virulence gene regulatory cascades.

Indel variant analysis of short-read sequencing data with Scalpel

PubMed Central

Fang, Han; Bergmann, Ewa A; Arora, Kanika; Vacic, Vladimir; Zody, Michael C; Iossifov, Ivan; O’Rawe, Jason A; Wu, Yiyang; Barron, Laura T Jimenez; Rosenbaum, Julie; Ronemus, Michael; Lee, Yoon-ha; Wang, Zihua; Dikoglu, Esra; Jobanputra, Vaidehi; Lyon, Gholson J; Wigler, Michael; Schatz, Michael C; Narzisi, Giuseppe

2017-01-01

As the second most common type of variation in the human genome, insertions and deletions (indels) have been linked to many diseases, but the discovery of indels of more than a few bases in size from short-read sequencing data remains challenging. Scalpel (http://scalpel.sourceforge.net) is an open-source software for reliable indel detection based on the microassembly technique. It has been successfully used to discover mutations in novel candidate genes for autism, and it is extensively used in other large-scale studies of human diseases. This protocol gives an overview of the algorithm and describes how to use Scalpel to perform highly accurate indel calling from whole-genome and whole-exome sequencing data. We provide detailed instructions for an exemplary family-based de novo study, but we also characterize the other two supported modes of operation: single-sample and somatic analysis. Indel normalization, visualization and annotation of the mutations are also illustrated. Using a standard server, indel discovery and characterization in the exonic regions of the example sequencing data can be completed in ~5 h after read mapping. PMID:27854363

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

PubMed

Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

Genome resequencing in Populus: Revealing large-scale genome variation and implications on specialized-trait genomics

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

Muchero, Wellington; Labbe, Jessy L; Priya, Ranjan

2014-01-01

To date, Populus ranks among a few plant species with a complete genome sequence and other highly developed genomic resources. With the first genome sequence among all tree species, Populus has been adopted as a suitable model organism for genomic studies in trees. However, far from being just a model species, Populus is a key renewable economic resource that plays a significant role in providing raw materials for the biofuel and pulp and paper industries. Therefore, aside from leading frontiers of basic tree molecular biology and ecological research, Populus leads frontiers in addressing global economic challenges related to fuel andmore » fiber production. The latter fact suggests that research aimed at improving quality and quantity of Populus as a raw material will likely drive the pursuit of more targeted and deeper research in order to unlock the economic potential tied in molecular biology processes that drive this tree species. Advances in genome sequence-driven technologies, such as resequencing individual genotypes, which in turn facilitates large scale SNP discovery and identification of large scale polymorphisms are key determinants of future success in these initiatives. In this treatise we discuss implications of genome sequence-enable technologies on Populus genomic and genetic studies of complex and specialized-traits.« less

Scale and time dependence of serial correlations in word-length time series of written texts

NASA Astrophysics Data System (ADS)

Rodriguez, E.; Aguilar-Cornejo, M.; Femat, R.; Alvarez-Ramirez, J.

2014-11-01

This work considered the quantitative analysis of large written texts. To this end, the text was converted into a time series by taking the sequence of word lengths. The detrended fluctuation analysis (DFA) was used for characterizing long-range serial correlations of the time series. To this end, the DFA was implemented within a rolling window framework for estimating the variations of correlations, quantified in terms of the scaling exponent, strength along the text. Also, a filtering derivative was used to compute the dependence of the scaling exponent relative to the scale. The analysis was applied to three famous English-written literary narrations; namely, Alice in Wonderland (by Lewis Carrol), Dracula (by Bram Stoker) and Sense and Sensibility (by Jane Austen). The results showed that high correlations appear for scales of about 50-200 words, suggesting that at these scales the text contains the stronger coherence. The scaling exponent was not constant along the text, showing important variations with apparent cyclical behavior. An interesting coincidence between the scaling exponent variations and changes in narrative units (e.g., chapters) was found. This suggests that the scaling exponent obtained from the DFA is able to detect changes in narration structure as expressed by the usage of words of different lengths.

Memory effect in M ≥ 6 earthquakes of South-North Seismic Belt, Mainland China

NASA Astrophysics Data System (ADS)

Wang, Jeen-Hwa

2013-07-01

The M ≥ 6 earthquakes occurred in the South-North Seismic Belt, Mainland China, during 1901-2008 are taken to study the possible existence of memory effect in large earthquakes. The fluctuation analysis technique is applied to analyze the sequences of earthquake magnitude and inter-event time represented in the natural time domain. Calculated results show that the exponents of scaling law of fluctuation versus window length are less than 0.5 for the sequences of earthquake magnitude and inter-event time. The migration of earthquakes in study is taken to discuss the possible correlation between events. The phase portraits of two sequent magnitudes and two sequent inter-event times are also applied to explore if large (or small) earthquakes are followed by large (or small) events. Together with all kinds of given information, we conclude that the earthquakes in study is short-term correlated and thus the short-term memory effect would be operative.

Characteristics of the Lotus japonicus gene repertoire deduced from large-scale expressed sequence tag (EST) analysis.

PubMed

Asamizu, Erika; Nakamura, Yasukazu; Sato, Shusei; Tabata, Satoshi

2004-02-01

To perform a comprehensive analysis of genes expressed in a model legume, Lotus japonicus, a total of 74472 3'-end expressed sequence tags (EST) were generated from cDNA libraries produced from six different organs. Clustering of sequences was performed with an identity criterion of 95% for 50 bases, and a total of 20457 non-redundant sequences, 8503 contigs and 11954 singletons were generated. EST sequence coverage was analyzed by using the annotated L. japonicus genomic sequence and 1093 of the 1889 predicted protein-encoding genes (57.9%) were hit by the EST sequence(s). Gene content was compared to several plant species. Among the 8503 contigs, 471 were identified as sequences conserved only in leguminous species and these included several disease resistance-related genes. This suggested that in legumes, these genes may have evolved specifically to resist pathogen attack. The rate of gene sequence divergence was assessed by comparing similarity level and functional category based on the Gene Ontology (GO) annotation of Arabidopsis genes. This revealed that genes encoding ribosomal proteins, as well as those related to translation, photosynthesis, and cellular structure were more abundantly represented in the highly conserved class, and that genes encoding transcription factors and receptor protein kinases were abundantly represented in the less conserved class. To make the sequence information and the cDNA clones available to the research community, a Web database with useful services was created at http://www.kazusa.or.jp/en/plant/lotus/EST/.

Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

PubMed

Warris, Sven; Boymans, Sander; Muiser, Iwe; Noback, Michiel; Krijnen, Wim; Nap, Jan-Peter

2014-01-13

Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.

Estimation of pairwise sequence similarity of mammalian enhancers with word neighbourhood counts.

PubMed

Göke, Jonathan; Schulz, Marcel H; Lasserre, Julia; Vingron, Martin

2012-03-01

The identity of cells and tissues is to a large degree governed by transcriptional regulation. A major part is accomplished by the combinatorial binding of transcription factors at regulatory sequences, such as enhancers. Even though binding of transcription factors is sequence-specific, estimating the sequence similarity of two functionally similar enhancers is very difficult. However, a similarity measure for regulatory sequences is crucial to detect and understand functional similarities between two enhancers and will facilitate large-scale analyses like clustering, prediction and classification of genome-wide datasets. We present the standardized alignment-free sequence similarity measure N2, a flexible framework that is defined for word neighbourhoods. We explore the usefulness of adding reverse complement words as well as words including mismatches into the neighbourhood. On simulated enhancer sequences as well as functional enhancers in mouse development, N2 is shown to outperform previous alignment-free measures. N2 is flexible, faster than competing methods and less susceptible to single sequence noise and the occurrence of repetitive sequences. Experiments on the mouse enhancers reveal that enhancers active in different tissues can be separated by pairwise comparison using N2. N2 represents an improvement over previous alignment-free similarity measures without compromising speed, which makes it a good candidate for large-scale sequence comparison of regulatory sequences. The software is part of the open-source C++ library SeqAn (www.seqan.de) and a compiled version can be downloaded at http://www.seqan.de/projects/alf.html. Supplementary data are available at Bioinformatics online.

Shallowing-upward cyclic patterns within larger-scale transgressive-regressive (T-R) sedimentary sequences, St. Peter through Decorah Formations, Ordovician, Iowa area

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

Witzke, B.J.

1993-03-01

Four large-scale (2--8 Ma) T-R sedimentary sequences of M. Ord. age (late Chaz.-Sherm.) were delimited by Witzke Kolata (1980) in the Iowa area, each bounded by local to regional unconformity/disconformity surfaces. These encompass both siliciclastic and carbonate intervals, in ascending order: (1) St. Peter-Glenwood fms., (2) Platteville Fm., (3) Decorah Fm., (4) Dunleith/upper Decorah fms. Finer-scale resolution of depth-related depositional features has led to regional recognition of smaller-scale shallowing-upward cyclicity contained within each large-scale sequence. Such smaller-scale cyclicity encompasses stratigraphic intervals of 1--10 m thickness, with estimated durations of 0.5--1.5 Ma. The St. Peter Sandst. has long been regarded asmore » a classic transgressive sheet sand. However, four discrete shallowing-upward packages characterize the St. Peter-Glenwood interval regionally (IA, MN, NB, KS), including western facies displaying coarsening-upward sandstone packages with condensed conodont-rich brown shale and phosphatic sediments in their lower part (local oolitic ironstone), commonly above pyritic hardgrounds. Regional continuity of small-scale cyclic patterns in M. Ord. strata of the Iowa area may suggest eustatic controls; this can be tested through inter-regional comparisons.« less

Effect of extreme data loss on heart rate signals quantified by entropy analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Wang, Jun; Li, Jin; Liu, Dazhao

2015-02-01

The phenomenon of data loss always occurs in the analysis of large databases. Maintaining the stability of analysis results in the event of data loss is very important. In this paper, we used a segmentation approach to generate a synthetic signal that is randomly wiped from data according to the Gaussian distribution and the exponential distribution of the original signal. Then, the logistic map is used as verification. Finally, two methods of measuring entropy-base-scale entropy and approximate entropy-are comparatively analyzed. Our results show the following: (1) Two key parameters-the percentage and the average length of removed data segments-can change the sequence complexity according to logistic map testing. (2) The calculation results have preferable stability for base-scale entropy analysis, which is not sensitive to data loss. (3) The loss percentage of HRV signals should be controlled below the range (p = 30 %), which can provide useful information in clinical applications.

Imaging different components of a tectonic tremor sequence in southwestern Japan using an automatic statistical detection and location method

NASA Astrophysics Data System (ADS)

Poiata, Natalia; Vilotte, Jean-Pierre; Bernard, Pascal; Satriano, Claudio; Obara, Kazushige

2018-02-01

In this study, we demonstrate the capability of an automatic network-based detection and location method to extract and analyse different components of tectonic tremor activity by analysing a 9-day energetic tectonic tremor sequence occurring at the down-dip extension of the subducting slab in southwestern Japan. The applied method exploits the coherency of multi-scale, frequency-selective characteristics of non-stationary signals recorded across the seismic network. Use of different characteristic functions, in the signal processing step of the method, allows to extract and locate the sources of short-duration impulsive signal transients associated with low-frequency earthquakes and of longer-duration energy transients during the tectonic tremor sequence. Frequency-dependent characteristic functions, based on higher-order statistics' properties of the seismic signals, are used for the detection and location of low-frequency earthquakes. This allows extracting a more complete (˜6.5 times more events) and time-resolved catalogue of low-frequency earthquakes than the routine catalogue provided by the Japan Meteorological Agency. As such, this catalogue allows resolving the space-time evolution of the low-frequency earthquakes activity in great detail, unravelling spatial and temporal clustering, modulation in response to tide, and different scales of space-time migration patterns. In the second part of the study, the detection and source location of longer-duration signal energy transients within the tectonic tremor sequence is performed using characteristic functions built from smoothed frequency-dependent energy envelopes. This leads to a catalogue of longer-duration energy sources during the tectonic tremor sequence, characterized by their durations and 3-D spatial likelihood maps of the energy-release source regions. The summary 3-D likelihood map for the 9-day tectonic tremor sequence, built from this catalogue, exhibits an along-strike spatial segmentation of the long-duration energy-release regions, matching the large-scale clustering features evidenced from the low-frequency earthquake's activity analysis. Further examination of the two catalogues showed that the extracted short-duration low-frequency earthquakes activity coincides in space, within about 10-15 km distance, with the longer-duration energy sources during the tectonic tremor sequence. This observation provides a potential constraint on the size of the longer-duration energy-radiating source region in relation with the clustering of low-frequency earthquakes activity during the analysed tectonic tremor sequence. We show that advanced statistical network-based methods offer new capabilities for automatic high-resolution detection, location and monitoring of different scale-components of tectonic tremor activity, enriching existing slow earthquakes catalogues. Systematic application of such methods to large continuous data sets will allow imaging the slow transient seismic energy-release activity at higher resolution, and therefore, provide new insights into the underlying multi-scale mechanisms of slow earthquakes generation.

Analysis of protein-coding genetic variation in 60,706 humans.

PubMed

Lek, Monkol; Karczewski, Konrad J; Minikel, Eric V; Samocha, Kaitlin E; Banks, Eric; Fennell, Timothy; O'Donnell-Luria, Anne H; Ware, James S; Hill, Andrew J; Cummings, Beryl B; Tukiainen, Taru; Birnbaum, Daniel P; Kosmicki, Jack A; Duncan, Laramie E; Estrada, Karol; Zhao, Fengmei; Zou, James; Pierce-Hoffman, Emma; Berghout, Joanne; Cooper, David N; Deflaux, Nicole; DePristo, Mark; Do, Ron; Flannick, Jason; Fromer, Menachem; Gauthier, Laura; Goldstein, Jackie; Gupta, Namrata; Howrigan, Daniel; Kiezun, Adam; Kurki, Mitja I; Moonshine, Ami Levy; Natarajan, Pradeep; Orozco, Lorena; Peloso, Gina M; Poplin, Ryan; Rivas, Manuel A; Ruano-Rubio, Valentin; Rose, Samuel A; Ruderfer, Douglas M; Shakir, Khalid; Stenson, Peter D; Stevens, Christine; Thomas, Brett P; Tiao, Grace; Tusie-Luna, Maria T; Weisburd, Ben; Won, Hong-Hee; Yu, Dongmei; Altshuler, David M; Ardissino, Diego; Boehnke, Michael; Danesh, John; Donnelly, Stacey; Elosua, Roberto; Florez, Jose C; Gabriel, Stacey B; Getz, Gad; Glatt, Stephen J; Hultman, Christina M; Kathiresan, Sekar; Laakso, Markku; McCarroll, Steven; McCarthy, Mark I; McGovern, Dermot; McPherson, Ruth; Neale, Benjamin M; Palotie, Aarno; Purcell, Shaun M; Saleheen, Danish; Scharf, Jeremiah M; Sklar, Pamela; Sullivan, Patrick F; Tuomilehto, Jaakko; Tsuang, Ming T; Watkins, Hugh C; Wilson, James G; Daly, Mark J; MacArthur, Daniel G

2016-08-18

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Sequence and Analysis of the Tomato JOINTLESS Locus1

PubMed Central

Mao, Long; Begum, Dilara; Goff, Stephen A.; Wing, Rod A.

2001-01-01

A 119-kb bacterial artificial chromosome from the JOINTLESS locus on the tomato (Lycopersicon esculentum) chromosome 11 contained 15 putative genes. Repetitive sequences in this region include one copia-like LTR retrotransposon, 13 simple sequence repeats, three copies of a novel type III foldback transposon, and four putative short DNA repeats. Database searches showed that the foldback transposon and the short DNA repeats seemed to be associated preferably with genes. The predicted tomato genes were compared with the complete Arabidopsis genome. Eleven out of 15 tomato open reading frames were found to be colinear with segments on five Arabidopsis bacterial artificial chromosome/P1-derived artificial chromosome clones. The synteny patterns, however, did not reveal duplicated segments in Arabidopsis, where over half of the genome is duplicated. Our analysis indicated that the microsynteny between the tomato and Arabidopsis genomes was still conserved at a very small scale but was complicated by the large number of gene families in the Arabidopsis genome. PMID:11457984

Transcriptomic analysis of grain amaranth (Amaranthus hypochondriacus) using 454 pyrosequencing: comparison with A. tuberculatus, expression profiling in stems and in response to biotic and abiotic stress

PubMed Central

2011-01-01

Background Amaranthus hypochondriacus, a grain amaranth, is a C4 plant noted by its ability to tolerate stressful conditions and produce highly nutritious seeds. These possess an optimal amino acid balance and constitute a rich source of health-promoting peptides. Although several recent studies, mostly involving subtractive hybridization strategies, have contributed to increase the relatively low number of grain amaranth expressed sequence tags (ESTs), transcriptomic information of this species remains limited, particularly regarding tissue-specific and biotic stress-related genes. Thus, a large scale transcriptome analysis was performed to generate stem- and (a)biotic stress-responsive gene expression profiles in grain amaranth. Results A total of 2,700,168 raw reads were obtained from six 454 pyrosequencing runs, which were assembled into 21,207 high quality sequences (20,408 isotigs + 799 contigs). The average sequence length was 1,064 bp and 930 bp for isotigs and contigs, respectively. Only 5,113 singletons were recovered after quality control. Contigs/isotigs were further incorporated into 15,667 isogroups. All unique sequences were queried against the nr, TAIR, UniRef100, UniRef50 and Amaranthaceae EST databases for annotation. Functional GO annotation was performed with all contigs/isotigs that produced significant hits with the TAIR database. Only 8,260 sequences were found to be homologous when the transcriptomes of A. tuberculatus and A. hypochondriacus were compared, most of which were associated with basic house-keeping processes. Digital expression analysis identified 1,971 differentially expressed genes in response to at least one of four stress treatments tested. These included several multiple-stress-inducible genes that could represent potential candidates for use in the engineering of stress-resistant plants. The transcriptomic data generated from pigmented stems shared similarity with findings reported in developing stems of Arabidopsis and black cottonwood (Populus trichocarpa). Conclusions This study represents the first large-scale transcriptomic analysis of A. hypochondriacus, considered to be a highly nutritious and stress-tolerant crop. Numerous genes were found to be induced in response to (a)biotic stress, many of which could further the understanding of the mechanisms that contribute to multiple stress-resistance in plants, a trait that has potential biotechnological applications in agriculture. PMID:21752295

The Human EST Ontology Explorer: a tissue-oriented visualization system for ontologies distribution in human EST collections.

PubMed

Merelli, Ivan; Caprera, Andrea; Stella, Alessandra; Del Corvo, Marcello; Milanesi, Luciano; Lazzari, Barbara

2009-10-15

The NCBI dbEST currently contains more than eight million human Expressed Sequenced Tags (ESTs). This wide collection represents an important source of information for gene expression studies, provided it can be inspected according to biologically relevant criteria. EST data can be browsed using different dedicated web resources, which allow to investigate library specific gene expression levels and to make comparisons among libraries, highlighting significant differences in gene expression. Nonetheless, no tool is available to examine distributions of quantitative EST collections in Gene Ontology (GO) categories, nor to retrieve information concerning library-dependent EST involvement in metabolic pathways. In this work we present the Human EST Ontology Explorer (HEOE) http://www.itb.cnr.it/ptp/human_est_explorer, a web facility for comparison of expression levels among libraries from several healthy and diseased tissues. The HEOE provides library-dependent statistics on the distribution of sequences in the GO Direct Acyclic Graph (DAG) that can be browsed at each GO hierarchical level. The tool is based on large-scale BLAST annotation of EST sequences. Due to the huge number of input sequences, this BLAST analysis was performed with the aid of grid computing technology, which is particularly suitable to address data parallel task. Relying on the achieved annotation, library-specific distributions of ESTs in the GO Graph were inferred. A pathway-based search interface was also implemented, for a quick evaluation of the representation of libraries in metabolic pathways. EST processing steps were integrated in a semi-automatic procedure that relies on Perl scripts and stores results in a MySQL database. A PHP-based web interface offers the possibility to simultaneously visualize, retrieve and compare data from the different libraries. Statistically significant differences in GO categories among user selected libraries can also be computed. The HEOE provides an alternative and complementary way to inspect EST expression levels with respect to approaches currently offered by other resources. Furthermore, BLAST computation on the whole human EST dataset was a suitable test of grid scalability in the context of large-scale bioinformatics analysis. The HEOE currently comprises sequence analysis from 70 non-normalized libraries, representing a comprehensive overview on healthy and unhealthy tissues. As the analysis procedure can be easily applied to other libraries, the number of represented tissues is intended to increase.

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Wheeler, David L

2007-01-01

GenBank (R) is a comprehensive database that contains publicly available nucleotide sequences for more than 240 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage (www.ncbi.nlm.nih.gov).

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Wheeler, David L

2005-01-01

GenBank is a comprehensive database that contains publicly available DNA sequences for more than 165,000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in the UK and the DNA Data Bank of Japan helps to ensure worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, go to the NCBI Homepage at http://www.ncbi.nlm.nih.gov.

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Wheeler, David L

2006-01-01

GenBank (R) is a comprehensive database that contains publicly available DNA sequences for more than 205 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the Web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the EMBL Data Library in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, go to the NCBI Homepage at www.ncbi.nlm.nih.gov.

Self-Organizing Hidden Markov Model Map (SOHMMM).

PubMed

Ferles, Christos; Stafylopatis, Andreas

2013-12-01

A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Distinct retroelement classes define evolutionary breakpoints demarcating sites of evolutionary novelty

PubMed Central

Longo, Mark S; Carone, Dawn M; Green, Eric D; O'Neill, Michael J; O'Neill, Rachel J

2009-01-01

Background Large-scale genome rearrangements brought about by chromosome breaks underlie numerous inherited diseases, initiate or promote many cancers and are also associated with karyotype diversification during species evolution. Recent research has shown that these breakpoints are nonrandomly distributed throughout the mammalian genome and many, termed "evolutionary breakpoints" (EB), are specific genomic locations that are "reused" during karyotypic evolution. When the phylogenetic trajectory of orthologous chromosome segments is considered, many of these EB are coincident with ancient centromere activity as well as new centromere formation. While EB have been characterized as repeat-rich regions, it has not been determined whether specific sequences have been retained during evolution that would indicate previous centromere activity or a propensity for new centromere formation. Likewise, the conservation of specific sequence motifs or classes at EBs among divergent mammalian taxa has not been determined. Results To define conserved sequence features of EBs associated with centromere evolution, we performed comparative sequence analysis of more than 4.8 Mb within the tammar wallaby, Macropus eugenii, derived from centromeric regions (CEN), euchromatic regions (EU), and an evolutionary breakpoint (EB) that has undergone convergent breakpoint reuse and past centromere activity in marsupials. We found a dramatic enrichment for long interspersed nucleotide elements (LINE1s) and endogenous retroviruses (ERVs) and a depletion of short interspersed nucleotide elements (SINEs) shared between CEN and EBs. We analyzed the orthologous human EB (14q32.33), known to be associated with translocations in many cancers including multiple myelomas and plasma cell leukemias, and found a conserved distribution of similar repetitive elements. Conclusion Our data indicate that EBs tracked within the class Mammalia harbor sequence features retained since the divergence of marsupials and eutherians that may have predisposed these genomic regions to large-scale chromosomal instability. PMID:19630942

TIMPs of parasitic helminths - a large-scale analysis of high-throughput sequence datasets.

PubMed

Cantacessi, Cinzia; Hofmann, Andreas; Pickering, Darren; Navarro, Severine; Mitreva, Makedonka; Loukas, Alex

2013-05-30

Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. In parasitic helminths, such as hookworms, TIMPs have been proposed to play key roles in the host-parasite interplay, including invasion of and establishment in the vertebrate animal hosts. Currently, knowledge of helminth TIMPs is limited to a small number of studies on canine hookworms, whereas no information is available on the occurrence of TIMPs in other parasitic helminths causing neglected diseases. In the present study, we conducted a large-scale investigation of TIMP proteins of a range of neglected human parasites including the hookworm Necator americanus, the roundworm Ascaris suum, the liver flukes Clonorchis sinensis and Opisthorchis viverrini, as well as the schistosome blood flukes. This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum, N. americanus and Schistosoma haematobium which infect the mammalian hosts. A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses. Supported by the availability of gene manipulation technologies such as RNA interference and/or transgenesis, this work provides a basis for future functional explorations of helminth TIMPs and, in particular, of their role/s in fundamental biological pathways linked to long-term establishment in the vertebrate hosts, with a view towards the development of novel approaches for the control of neglected helminthiases.

TIMPs of parasitic helminths – a large-scale analysis of high-throughput sequence datasets

PubMed Central

2013-01-01

Background Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. In parasitic helminths, such as hookworms, TIMPs have been proposed to play key roles in the host-parasite interplay, including invasion of and establishment in the vertebrate animal hosts. Currently, knowledge of helminth TIMPs is limited to a small number of studies on canine hookworms, whereas no information is available on the occurrence of TIMPs in other parasitic helminths causing neglected diseases. Methods In the present study, we conducted a large-scale investigation of TIMP proteins of a range of neglected human parasites including the hookworm Necator americanus, the roundworm Ascaris suum, the liver flukes Clonorchis sinensis and Opisthorchis viverrini, as well as the schistosome blood flukes. This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum, N. americanus and Schistosoma haematobium which infect the mammalian hosts. Results A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses. Conclusions Supported by the availability of gene manipulation technologies such as RNA interference and/or transgenesis, this work provides a basis for future functional explorations of helminth TIMPs and, in particular, of their role/s in fundamental biological pathways linked to long-term establishment in the vertebrate hosts, with a view towards the development of novel approaches for the control of neglected helminthiases. PMID:23721526

Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis.

PubMed

Faya, Ngonidzashe; Penkler, David L; Tastan Bishop, Özlem

2015-01-01

The treatment of protozoan parasitic diseases is challenging, and thus identification and analysis of new drug targets is important. Parasites survive within host organisms, and some need intermediate hosts to complete their life cycle. Changing host environment puts stress on parasites, and often adaptation is accompanied by the expression of large amounts of heat shock proteins (Hsps). Among Hsps, Hsp90 proteins play an important role in stress environments. Yet, there has been little computational research on Hsp90 proteins to analyze them comparatively as potential parasitic drug targets. Here, an attempt was made to gain detailed insights into the differences between host, vector and parasitic Hsp90 proteins by large-scale bioinformatics analysis. A total of 104 Hsp90 sequences were divided into three groups based on their cellular localizations; namely cytosolic, mitochondrial and endoplasmic reticulum (ER). Further, the parasitic proteins were divided according to the type of parasite (protozoa, helminth and ectoparasite). Primary sequence analysis, phylogenetic tree calculations, motif analysis and physicochemical properties of Hsp90 proteins suggested that despite the overall structural conservation of these proteins, parasitic Hsp90 proteins have unique features which differentiate them from human ones, thus encouraging the idea that protozoan Hsp90 proteins should be further analyzed as potential drug targets.

Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency

PubMed Central

Aniceto, Rodrigo; Xavier, Rene; Guimarães, Valeria; Hondo, Fernanda; Holanda, Maristela; Walter, Maria Emilia; Lifschitz, Sérgio

2015-01-01

Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB. PMID:26558254

De Novo Transcriptome Sequencing Analysis of cDNA Library and Large-Scale Unigene Assembly in Japanese Red Pine (Pinus densiflora)

PubMed Central

Liu, Le; Zhang, Shijie; Lian, Chunlan

2015-01-01

Japanese red pine (Pinus densiflora) is extensively cultivated in Japan, Korea, China, and Russia and is harvested for timber, pulpwood, garden, and paper markets. However, genetic information and molecular markers were very scarce for this species. In this study, over 51 million sequencing clean reads from P. densiflora mRNA were produced using Illumina paired-end sequencing technology. It yielded 83,913 unigenes with a mean length of 751 bp, of which 54,530 (64.98%) unigenes showed similarity to sequences in the NCBI database. Among which the best matches in the NCBI Nr database were Picea sitchensis (41.60%), Amborella trichopoda (9.83%), and Pinus taeda (4.15%). A total of 1953 putative microsatellites were identified in 1784 unigenes using MISA (MicroSAtellite) software, of which the tri-nucleotide repeats were most abundant (50.18%) and 629 EST-SSR (expressed sequence tag- simple sequence repeats) primer pairs were successfully designed. Among 20 EST-SSR primer pairs randomly chosen, 17 markers yielded amplification products of the expected size in P. densiflora. Our results will provide a valuable resource for gene-function analysis, germplasm identification, molecular marker-assisted breeding and resistance-related gene(s) mapping for pine for P. densiflora. PMID:26690126

G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies

PubMed Central

Wang, Miaoyan; Jakobsdottir, Johanna; Smith, Albert V.; McPeek, Mary Sara

2017-01-01

In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study’s sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly already sequenced, and one wants to choose an additional fixed-size subset of individuals to sequence in such a way that the power to detect association is maximized. When the phenotyped sample includes related individuals, power for association can be gained by including partial information, such as phenotype data of ungenotyped relatives, in the analysis, and this should be taken into account when assessing whom to sequence. We propose G-STRATEGY, which uses simulated annealing to choose a subset of individuals for sequencing that maximizes the expected power for association. In simulations, G-STRATEGY performs extremely well for a range of complex disease models and outperforms other strategies with, in many cases, relative power increases of 20–40% over the next best strategy, while maintaining correct type 1 error. G-STRATEGY is computationally feasible even for large datasets and complex pedigrees. We apply G-STRATEGY to data on HDL and LDL from the AGES-Reykjavik and REFINE-Reykjavik studies, in which G-STRATEGY is able to closely-approximate the power of sequencing the full sample by selecting for sequencing a only small subset of the individuals. PMID:27256766

D-Light on promoters: a client-server system for the analysis and visualization of cis-regulatory elements

PubMed Central

2013-01-01

Background The binding of transcription factors to DNA plays an essential role in the regulation of gene expression. Numerous experiments elucidated binding sequences which subsequently have been used to derive statistical models for predicting potential transcription factor binding sites (TFBS). The rapidly increasing number of genome sequence data requires sophisticated computational approaches to manage and query experimental and predicted TFBS data in the context of other epigenetic factors and across different organisms. Results We have developed D-Light, a novel client-server software package to store and query large amounts of TFBS data for any number of genomes. Users can add small-scale data to the server database and query them in a large scale, genome-wide promoter context. The client is implemented in Java and provides simple graphical user interfaces and data visualization. Here we also performed a statistical analysis showing what a user can expect for certain parameter settings and we illustrate the usage of D-Light with the help of a microarray data set. Conclusions D-Light is an easy to use software tool to integrate, store and query annotation data for promoters. A public D-Light server, the client and server software for local installation and the source code under GNU GPL license are available at http://biwww.che.sbg.ac.at/dlight. PMID:23617301

Defining precision: The precision medicine initiative trials NCI-MPACT and NCI-MATCH.

PubMed

Coyne, Geraldine O'Sullivan; Takebe, Naoko; Chen, Alice P

"Precision" trials, using rationally incorporated biomarker targets and molecularly selective anticancer agents, have become of great interest to both patients and their physicians. In the endeavor to test the cornerstone premise of precision oncotherapy, that is, determining if modulating a specific molecular aberration in a patient's tumor with a correspondingly specific therapeutic agent improves clinical outcomes, the design of clinical trials with embedded genomic characterization platforms which guide therapy are an increasing challenge. The National Cancer Institute Precision Medicine Initiative is an unprecedented large interdisciplinary collaborative effort to conceptualize and test the feasibility of trials incorporating sequencing platforms and large-scale bioinformatics processing that are not currently uniformly available to patients. National Cancer Institute-Molecular Profiling-based Assignment of Cancer Therapy and National Cancer Institute-Molecular Analysis for Therapy Choice are 2 genomic to phenotypic trials under this National Cancer Institute initiative, where treatment is selected according to predetermined genetic alterations detected using next-generation sequencing technology across a broad range of tumor types. In this article, we discuss the objectives and trial designs that have enabled the public-private partnerships required to complete the scale of both trials, as well as interim trial updates and strategic considerations that have driven data analysis and targeted therapy assignment, with the intent of elucidating further the benefits of this treatment approach for patients. Copyright © 2017. Published by Elsevier Inc.

GLAD: a system for developing and deploying large-scale bioinformatics grid.

PubMed

Teo, Yong-Meng; Wang, Xianbing; Ng, Yew-Kwong

2005-03-01

Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid. GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.

A hybrid computational strategy to address WGS variant analysis in >5000 samples.

PubMed

Huang, Zhuoyi; Rustagi, Navin; Veeraraghavan, Narayanan; Carroll, Andrew; Gibbs, Richard; Boerwinkle, Eric; Venkata, Manjunath Gorentla; Yu, Fuli

2016-09-10

The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

A rapid and cost-effective method for sequencing pooled cDNA clones by using a combination of transposon insertion and Gateway technology.

PubMed

Morozumi, Takeya; Toki, Daisuke; Eguchi-Ogawa, Tomoko; Uenishi, Hirohide

2011-09-01

Large-scale cDNA-sequencing projects require an efficient strategy for mass sequencing. Here we describe a method for sequencing pooled cDNA clones using a combination of transposon insertion and Gateway technology. Our method reduces the number of shotgun clones that are unsuitable for reconstruction of cDNA sequences, and has the advantage of reducing the total costs of the sequencing project.

Hadoop-BAM: directly manipulating next generation sequencing data in the cloud.

PubMed

Niemenmaa, Matti; Kallio, Aleksi; Schumacher, André; Klemelä, Petri; Korpelainen, Eija; Heljanko, Keijo

2012-03-15

Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps.

Exome Pool-Seq in neurodevelopmental disorders.

PubMed

Popp, Bernt; Ekici, Arif B; Thiel, Christian T; Hoyer, Juliane; Wiesener, Antje; Kraus, Cornelia; Reis, André; Zweier, Christiane

2017-12-01

High throughput sequencing has greatly advanced disease gene identification, especially in heterogeneous entities. Despite falling costs this is still an expensive and laborious technique, particularly when studying large cohorts. To address this problem we applied Exome Pool-Seq as an economic and fast screening technology in neurodevelopmental disorders (NDDs). Sequencing of 96 individuals can be performed in eight pools of 12 samples on less than one Illumina sequencer lane. In a pilot study with 96 cases we identified 27 variants, likely or possibly affecting function. Twenty five of these were identified in 923 established NDD genes (based on SysID database, status November 2016) (ACTB, AHDC1, ANKRD11, ATP6V1B2, ATRX, CASK, CHD8, GNAS, IFIH1, KCNQ2, KMT2A, KRAS, MAOA, MED12, MED13L, RIT1, SETD5, SIN3A, TCF4, TRAPPC11, TUBA1A, WAC, ZBTB18, ZMYND11), two in 543 (SysID) candidate genes (ZNF292, BPTF), and additionally a de novo loss-of-function variant in LRRC7, not previously implicated in NDDs. Most of them were confirmed to be de novo, but we also identified X-linked or autosomal-dominantly or autosomal-recessively inherited variants. With a detection rate of 28%, Exome Pool-Seq achieves comparable results to individual exome analyses but reduces costs by >85%. Compared with other large scale approaches using Molecular Inversion Probes (MIP) or gene panels, it allows flexible re-analysis of data. Exome Pool-Seq is thus well suited for large-scale, cost-efficient and flexible screening in characterized but heterogeneous entities like NDDs.

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.

Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

PubMed

Wu, Tiee-Jian; Huang, Ying-Hsueh; Li, Lung-An

2005-11-15

Several measures of DNA sequence dissimilarity have been developed. The purpose of this paper is 3-fold. Firstly, we compare the performance of several word-based or alignment-based methods. Secondly, we give a general guideline for choosing the window size and determining the optimal word sizes for several word-based measures at different window sizes. Thirdly, we use a large-scale simulation method to simulate data from the distribution of SK-LD (symmetric Kullback-Leibler discrepancy). These simulated data can be used to estimate the degree of dissimilarity beta between any pair of DNA sequences. Our study shows (1) for whole sequence similiarity/dissimilarity identification the window size taken should be as large as possible, but probably not >3000, as restricted by CPU time in practice, (2) for each measure the optimal word size increases with window size, (3) when the optimal word size is used, SK-LD performance is superior in both simulation and real data analysis, (4) the estimate beta of beta based on SK-LD can be used to filter out quickly a large number of dissimilar sequences and speed alignment-based database search for similar sequences and (5) beta is also applicable in local similarity comparison situations. For example, it can help in selecting oligo probes with high specificity and, therefore, has potential in probe design for microarrays. The algorithm SK-LD, estimate beta and simulation software are implemented in MATLAB code, and are available at http://www.stat.ncku.edu.tw/tjwu

Genomic analysis of NAC transcription factors in banana (Musa acuminata) and definition of NAC orthologous groups for monocots and dicots.

PubMed

Cenci, Albero; Guignon, Valentin; Roux, Nicolas; Rouard, Mathieu

2014-05-01

Identifying the molecular mechanisms underlying tolerance to abiotic stresses is important in crop breeding. A comprehensive understanding of the gene families associated with drought tolerance is therefore highly relevant. NAC transcription factors form a large plant-specific gene family involved in the regulation of tissue development and responses to biotic and abiotic stresses. The main goal of this study was to set up a framework of orthologous groups determined by an expert sequence comparison of NAC genes from both monocots and dicots. In order to clarify the orthologous relationships among NAC genes of different species, we performed an in-depth comparative study of four divergent taxa, in dicots and monocots, whose genomes have already been completely sequenced: Arabidopsis thaliana, Vitis vinifera, Musa acuminata and Oryza sativa. Due to independent evolution, NAC copy number is highly variable in these plant genomes. Based on an expert NAC sequence comparison, we propose forty orthologous groups of NAC sequences that were probably derived from an ancestor gene present in the most recent common ancestor of dicots and monocots. These orthologous groups provide a curated resource for large-scale protein sequence annotation of NAC transcription factors. The established orthology relationships also provide a useful reference for NAC function studies in newly sequenced genomes such as M. acuminata and other plant species.

Inexpensive and Highly Reproducible Cloud-Based Variant Calling of 2,535 Human Genomes

PubMed Central

Shringarpure, Suyash S.; Carroll, Andrew; De La Vega, Francisco M.; Bustamante, Carlos D.

2015-01-01

Population scale sequencing of whole human genomes is becoming economically feasible; however, data management and analysis remains a formidable challenge for many research groups. Large sequencing studies, like the 1000 Genomes Project, have improved our understanding of human demography and the effect of rare genetic variation in disease. Variant calling on datasets of hundreds or thousands of genomes is time-consuming, expensive, and not easily reproducible given the myriad components of a variant calling pipeline. Here, we describe a cloud-based pipeline for joint variant calling in large samples using the Real Time Genomics population caller. We deployed the population caller on the Amazon cloud with the DNAnexus platform in order to achieve low-cost variant calling. Using our pipeline, we were able to identify 68.3 million variants in 2,535 samples from Phase 3 of the 1000 Genomes Project. By performing the variant calling in a parallel manner, the data was processed within 5 days at a compute cost of $7.33 per sample (a total cost of $18,590 for completed jobs and $21,805 for all jobs). Analysis of cost dependence and running time on the data size suggests that, given near linear scalability, cloud computing can be a cheap and efficient platform for analyzing even larger sequencing studies in the future. PMID:26110529

Digital Marine Bioprospecting: Mining New Neurotoxin Drug Candidates from the Transcriptomes of Cold-Water Sea Anemones

PubMed Central

Urbarova, Ilona; Karlsen, Bård Ove; Okkenhaug, Siri; Seternes, Ole Morten; Johansen, Steinar D.; Emblem, Åse

2012-01-01

Marine bioprospecting is the search for new marine bioactive compounds and large-scale screening in extracts represents the traditional approach. Here, we report an alternative complementary protocol, called digital marine bioprospecting, based on deep sequencing of transcriptomes. We sequenced the transcriptomes from the adult polyp stage of two cold-water sea anemones, Bolocera tuediae and Hormathia digitata. We generated approximately 1.1 million quality-filtered sequencing reads by 454 pyrosequencing, which were assembled into approximately 120,000 contigs and 220,000 single reads. Based on annotation and gene ontology analysis we profiled the expressed mRNA transcripts according to known biological processes. As a proof-of-concept we identified polypeptide toxins with a potential blocking activity on sodium and potassium voltage-gated channels from digital transcriptome libraries. PMID:23170083

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

PubMed

Thorsen, Jonathan; Brejnrod, Asker; Mortensen, Martin; Rasmussen, Morten A; Stokholm, Jakob; Al-Soud, Waleed Abu; Sørensen, Søren; Bisgaard, Hans; Waage, Johannes

2016-11-25

There is an immense scientific interest in the human microbiome and its effects on human physiology, health, and disease. A common approach for examining bacterial communities is high-throughput sequencing of 16S rRNA gene hypervariable regions, aggregating sequence-similar amplicons into operational taxonomic units (OTUs). Strategies for detecting differential relative abundance of OTUs between sample conditions include classical statistical approaches as well as a plethora of newer methods, many borrowing from the related field of RNA-seq analysis. This effort is complicated by unique data characteristics, including sparsity, sequencing depth variation, and nonconformity of read counts to theoretical distributions, which is often exacerbated by exploratory and/or unbalanced study designs. Here, we assess the robustness of available methods for (1) inference in differential relative abundance analysis and (2) beta-diversity-based sample separation, using a rigorous benchmarking framework based on large clinical 16S microbiome datasets from different sources. Running more than 380,000 full differential relative abundance tests on real datasets with permuted case/control assignments and in silico-spiked OTUs, we identify large differences in method performance on a range of parameters, including false positive rates, sensitivity to sparsity and case/control balances, and spike-in retrieval rate. In large datasets, methods with the highest false positive rates also tend to have the best detection power. For beta-diversity-based sample separation, we show that library size normalization has very little effect and that the distance metric is the most important factor in terms of separation power. Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes and case/control proportions, and have low sparsity bias. Result output from some commonly used methods should be interpreted with caution. We provide an easily extensible framework for benchmarking of new methods and future microbiome datasets.

Analysis of transcriptome in hickory (Carya cathayensis), and uncover the dynamics in the hormonal signaling pathway during graft process.

PubMed

Qiu, Lingling; Jiang, Bo; Fang, Jia; Shen, Yike; Fang, Zhongxiang; Rm, Saravana Kumar; Yi, Keke; Shen, Chenjia; Yan, Daoliang; Zheng, Bingsong

2016-11-17

Hickory (Carya cathayensis), a woody plant with high nutritional and economic value, is widely planted in China. Due to its long juvenile phase, grafting is a useful technique for large-scale cultivation of hickory. To reveal the molecular mechanism during the graft process, we sequenced the transcriptomes of graft union in hickory. In our study, six RNA-seq libraries yielded a total of 83,676,860 clean short reads comprising 4.19 Gb of sequence data. A large number of differentially expressed genes (DEGs) at three time points during the graft process were identified. In detail, 777 DEGs in the 7 d vs 0 d (day after grafting) comparison were classified into 11 enriched Gene Ontology (GO) categories, and 262 DEGs in the 14 d vs 0 d comparison were classified into 15 enriched GO categories. Furthermore, an overview of the PPI network was constructed by these DEGs. In addition, 20 genes related to the auxin-and cytokinin-signaling pathways were identified, and some were validated by qRT-PCR analysis. Our comprehensive analysis provides basic information on the candidate genes and hormone signaling pathways involved in the graft process in hickory and other woody plants.

Epigenetics of prostate cancer.

PubMed

McKee, Tawnya C; Tricoli, James V

2015-01-01

The introduction of novel technologies that can be applied to the investigation of the molecular underpinnings of human cancer has allowed for new insights into the mechanisms associated with tumor development and progression. They have also advanced the diagnosis, prognosis and treatment of cancer. These technologies include microarray and other analysis methods for the generation of large-scale gene expression data on both mRNA and miRNA, next-generation DNA sequencing technologies utilizing a number of platforms to perform whole genome, whole exome, or targeted DNA sequencing to determine somatic mutational differences and gene rearrangements, and a variety of proteomic analysis platforms including liquid chromatography/mass spectrometry (LC/MS) analysis to survey alterations in protein profiles in tumors. One other important advancement has been our current ability to survey the methylome of human tumors in a comprehensive fashion through the use of sequence-based and array-based methylation analysis (Bock et al., Nat Biotechnol 28:1106-1114, 2010; Harris et al., Nat Biotechnol 28:1097-1105, 2010). The focus of this chapter is to present and discuss the evidence for key genes involved in prostate tumor development, progression, or resistance to therapy that are regulated by methylation-induced silencing.

De novo Assembly of the Indo-Pacific Humpback Dolphin Leucocyte Transcriptome to Identify Putative Genes Involved in the Aquatic Adaptation and Immune Response

PubMed Central

Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

Background The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. Principal Findings We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10−5), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. Conclusion This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers. PMID:24015242

De novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome to identify putative genes involved in the aquatic adaptation and immune response.

PubMed

Gui, Duan; Jia, Kuntong; Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10(-5)), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers.

Generation and analysis of expressed sequence tags from the bone marrow of Chinese Sika deer.

PubMed

Yao, Baojin; Zhao, Yu; Zhang, Mei; Li, Juan

2012-03-01

Sika deer is one of the best-known and highly valued animals of China. Despite its economic, cultural, and biological importance, there has not been a large-scale sequencing project for Sika deer to date. With the ultimate goal of sequencing the complete genome of this organism, we first established a bone marrow cDNA library for Sika deer and generated a total of 2,025 reads. After processing the sequences, 2,017 high-quality expressed sequence tags (ESTs) were obtained. These ESTs were assembled into 1,157 unigenes, including 238 contigs and 919 singletons. Comparative analyses indicated that 888 (76.75%) of the unigenes had significant matches to sequences in the non-redundant protein database, In addition to highly expressed genes, such as stearoyl-CoA desaturase, cytochrome c oxidase, adipocyte-type fatty acid-binding protein, adiponectin and thymosin beta-4, we also obtained vascular endothelial growth factor-A and heparin-binding growth-associated molecule, both of which are of great importance for angiogenesis research. There were 244 (21.09%) unigenes with no significant match to any sequence in current protein or nucleotide databases, and these sequences may represent genes with unknown function in Sika deer. Open reading frame analysis of the sequences was performed using the getorf program. In addition, the sequences were functionally classified using the gene ontology hierarchy, clusters of orthologous groups of proteins and Kyoto encyclopedia of genes and genomes databases. Analysis of ESTs described in this paper provides an important resource for the transcriptome exploration of Sika deer, and will also facilitate further studies on functional genomics, gene discovery and genome annotation of Sika deer.

Punctuated Evolution of Influenza Virus Neuraminidase (A/H1N1) under Opposing Migration and Vaccination Pressures

PubMed Central

Phillips, J. C.

2014-01-01

Influenza virus contains two highly variable envelope glycoproteins, hemagglutinin (HA) and neuraminidase (NA). The structure and properties of HA, which is responsible for binding the virus to the cell that is being infected, change significantly when the virus is transmitted from avian or swine species to humans. Here we focus first on the simpler problem of the much smaller human individual evolutionary amino acid mutational changes in NA, which cleaves sialic acid groups and is required for influenza virus replication. Our thermodynamic panorama shows that very small amino acid changes can be monitored very accurately across many historic (1945–2011) Uniprot and NCBI strains using hydropathicity scales to quantify the roughness of water film packages. Quantitative sequential analysis is most effective with the fractal differential hydropathicity scale based on protein self-organized criticality (SOC). Our analysis shows that large-scale vaccination programs have been responsible for a very large convergent reduction in common influenza severity in the last century. Hydropathic analysis is capable of interpreting and even predicting trends of functional changes in mutation prolific viruses directly from amino acid sequences alone. An engineered strain of NA1 is described which could well be significantly less virulent than current circulating strains. PMID:25143953

Development of an Expressed Sequence Tag (EST) Resource for Wheat (Triticum aestivum L.)

PubMed Central

Lazo, G. R.; Chao, S.; Hummel, D. D.; Edwards, H.; Crossman, C. C.; Lui, N.; Matthews, D. E.; Carollo, V. L.; Hane, D. L.; You, F. M.; Butler, G. E.; Miller, R. E.; Close, T. J.; Peng, J. H.; Lapitan, N. L. V.; Gustafson, J. P.; Qi, L. L.; Echalier, B.; Gill, B. S.; Dilbirligi, M.; Randhawa, H. S.; Gill, K. S.; Greene, R. A.; Sorrells, M. E.; Akhunov, E. D.; Dvořák, J.; Linkiewicz, A. M.; Dubcovsky, J.; Hossain, K. G.; Kalavacharla, V.; Kianian, S. F.; Mahmoud, A. A.; Miftahudin; Ma, X.-F.; Conley, E. J.; Anderson, J. A.; Pathan, M. S.; Nguyen, H. T.; McGuire, P. E.; Qualset, C. O.; Anderson, O. D.

2004-01-01

This report describes the rationale, approaches, organization, and resource development leading to a large-scale deletion bin map of the hexaploid (2n = 6x = 42) wheat genome (Triticum aestivum L.). Accompanying reports in this issue detail results from chromosome bin-mapping of expressed sequence tags (ESTs) representing genes onto the seven homoeologous chromosome groups and a global analysis of the entire mapped wheat EST data set. Among the resources developed were the first extensive public wheat EST collection (113,220 ESTs). Described are protocols for sequencing, sequence processing, EST nomenclature, and the assembly of ESTs into contigs. These contigs plus singletons (unassembled ESTs) were used for selection of distinct sequence motif unigenes. Selected ESTs were rearrayed, validated by 5′ and 3′ sequencing, and amplified for probing a series of wheat aneuploid and deletion stocks. Images and data for all Southern hybridizations were deposited in databases and were used by the coordinators for each of the seven homoeologous chromosome groups to validate the mapping results. Results from this project have established the foundation for future developments in wheat genomics. PMID:15514037

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Sayers, Eric W

2010-01-01

GenBank is a comprehensive database that contains publicly available nucleotide sequences for more than 300,000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bi-monthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI homepage: www.ncbi.nlm.nih.gov.

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Sayers, Eric W

2009-01-01

GenBank is a comprehensive database that contains publicly available nucleotide sequences for more than 300,000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank(R) staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the National Center for Biotechnology Information (NCBI) Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.

The evolution of surface magnetic fields in young solar-type stars II: the early main sequence (250-650 Myr)

NASA Astrophysics Data System (ADS)

Folsom, C. P.; Bouvier, J.; Petit, P.; Lèbre, A.; Amard, L.; Palacios, A.; Morin, J.; Donati, J.-F.; Vidotto, A. A.

2018-03-01

There is a large change in surface rotation rates of sun-like stars on the pre-main sequence and early main sequence. Since these stars have dynamo-driven magnetic fields, this implies a strong evolution of their magnetic properties over this time period. The spin-down of these stars is controlled by interactions between stellar and magnetic fields, thus magnetic evolution in turn plays an important role in rotational evolution. We present here the second part of a study investigating the evolution of large-scale surface magnetic fields in this critical time period. We observed stars in open clusters and stellar associations with known ages between 120 and 650 Myr, and used spectropolarimetry and Zeeman Doppler Imaging to characterize their large-scale magnetic field strength and geometry. We report 15 stars with magnetic detections here. These stars have masses from 0.8 to 0.95 M⊙, rotation periods from 0.326 to 10.6 d, and we find large-scale magnetic field strengths from 8.5 to 195 G with a wide range of geometries. We find a clear trend towards decreasing magnetic field strength with age, and a power law decrease in magnetic field strength with Rossby number. There is some tentative evidence for saturation of the large-scale magnetic field strength at Rossby numbers below 0.1, although the saturation point is not yet well defined. Comparing to younger classical T Tauri stars, we support the hypothesis that differences in internal structure produce large differences in observed magnetic fields, however for weak-lined T Tauri stars this is less clear.

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

Living laboratory: whole-genome sequencing as a learning healthcare enterprise.

PubMed

Angrist, M; Jamal, L

2015-04-01

With the proliferation of affordable large-scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large-scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype-phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta-analyses, we propose leveraging nascent clinical-research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real-life challenges posed by whole-genome sequencing, such as establishing the clinical actionability of genetic variants, returning 'off-target' results to families, developing effective service delivery models and monitoring long-term outcomes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Phylogenomic Reconstruction of the Oomycete Phylogeny Derived from 37 Genomes

PubMed Central

McCarthy, Charley G. P.

2017-01-01

ABSTRACT The oomycetes are a class of microscopic, filamentous eukaryotes within the Stramenopiles-Alveolata-Rhizaria (SAR) supergroup which includes ecologically significant animal and plant pathogens, most infamously the causative agent of potato blight Phytophthora infestans. Single-gene and concatenated phylogenetic studies both of individual oomycete genera and of members of the larger class have resulted in conflicting conclusions concerning species phylogenies within the oomycetes, particularly for the large Phytophthora genus. Genome-scale phylogenetic studies have successfully resolved many eukaryotic relationships by using supertree methods, which combine large numbers of potentially disparate trees to determine evolutionary relationships that cannot be inferred from individual phylogenies alone. With a sufficient amount of genomic data now available, we have undertaken the first whole-genome phylogenetic analysis of the oomycetes using data from 37 oomycete species and 6 SAR species. In our analysis, we used established supertree methods to generate phylogenies from 8,355 homologous oomycete and SAR gene families and have complemented those analyses with both phylogenomic network and concatenated supermatrix analyses. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and individual clades within the problematic Phytophthora genus. Support for the resolution of the inferred relationships between individual Phytophthora clades varies depending on the methodology used. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. IMPORTANCE The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. PMID:28435885

Transcriptome characterisation of Pinus tabuliformis and evolution of genes in the Pinus phylogeny

PubMed Central

2013-01-01

Background The Chinese pine (Pinus tabuliformis) is an indigenous conifer species in northern China but is relatively underdeveloped as a genomic resource; thus, limiting gene discovery and breeding. Large-scale transcriptome data were obtained using a next-generation sequencing platform to compensate for the lack of P. tabuliformis genomic information. Results The increasing amount of transcriptome data on Pinus provides an excellent resource for multi-gene phylogenetic analysis and studies on how conserved genes and functions are maintained in the face of species divergence. The first P. tabuliformis transcriptome from a normalised cDNA library of multiple tissues and individuals was sequenced in a full 454 GS-FLX run, producing 911,302 sequencing reads. The high quality overlapping expressed sequence tags (ESTs) were assembled into 46,584 putative transcripts, and more than 700 SSRs and 92,000 SNPs/InDels were characterised. Comparative analysis of the transcriptome of six conifer species yielded 191 orthologues, from which we inferred a phylogenetic tree, evolutionary patterns and calculated rates of gene diversion. We also identified 938 fast evolving sequences that may be useful for identifying genes that perhaps evolved in response to positive selection and might be responsible for speciation in the Pinus lineage. Conclusions A large collection of high-quality ESTs was obtained, de novo assembled and characterised, which represents a dramatic expansion of the current transcript catalogues of P. tabuliformis and which will gradually be applied in breeding programs of P. tabuliformis. Furthermore, these data will facilitate future studies of the comparative genomics of P. tabuliformis and other related species. PMID:23597112

Identification of human-to-human transmissibility factors in PB2 proteins of influenza A by large-scale mutual information analysis

PubMed Central

Miotto, Olivo; Heiny, AT; Tan, Tin Wee; August, J Thomas; Brusic, Vladimir

2008-01-01

Background The identification of mutations that confer unique properties to a pathogen, such as host range, is of fundamental importance in the fight against disease. This paper describes a novel method for identifying amino acid sites that distinguish specific sets of protein sequences, by comparative analysis of matched alignments. The use of mutual information to identify distinctive residues responsible for functional variants makes this approach highly suitable for analyzing large sets of sequences. To support mutual information analysis, we developed the AVANA software, which utilizes sequence annotations to select sets for comparison, according to user-specified criteria. The method presented was applied to an analysis of influenza A PB2 protein sequences, with the objective of identifying the components of adaptation to human-to-human transmission, and reconstructing the mutation history of these components. Results We compared over 3,000 PB2 protein sequences of human-transmissible and avian isolates, to produce a catalogue of sites involved in adaptation to human-to-human transmission. This analysis identified 17 characteristic sites, five of which have been present in human-transmissible strains since the 1918 Spanish flu pandemic. Sixteen of these sites are located in functional domains, suggesting they may play functional roles in host-range specificity. The catalogue of characteristic sites was used to derive sequence signatures from historical isolates. These signatures, arranged in chronological order, reveal an evolutionary timeline for the adaptation of the PB2 protein to human hosts. Conclusion By providing the most complete elucidation to date of the functional components participating in PB2 protein adaptation to humans, this study demonstrates that mutual information is a powerful tool for comparative characterization of sequence sets. In addition to confirming previously reported findings, several novel characteristic sites within PB2 are reported. Sequence signatures generated using the characteristic sites catalogue characterize concisely the adaptation characteristics of individual isolates. Evolutionary timelines derived from signatures of early human influenza isolates suggest that characteristic variants emerged rapidly, and remained remarkably stable through subsequent pandemics. In addition, the signatures of human-infecting H5N1 isolates suggest that this avian subtype has low pandemic potential at present, although it presents more human adaptation components than most avian subtypes. PMID:18315849

BrEPS 2.0: Optimization of sequence pattern prediction for enzyme annotation.

PubMed

Dudek, Christian-Alexander; Dannheim, Henning; Schomburg, Dietmar

2017-01-01

The prediction of gene functions is crucial for a large number of different life science areas. Faster high throughput sequencing techniques generate more and larger datasets. The manual annotation by classical wet-lab experiments is not suitable for these large amounts of data. We showed earlier that the automatic sequence pattern-based BrEPS protocol, based on manually curated sequences, can be used for the prediction of enzymatic functions of genes. The growing sequence databases provide the opportunity for more reliable patterns, but are also a challenge for the implementation of automatic protocols. We reimplemented and optimized the BrEPS pattern generation to be applicable for larger datasets in an acceptable timescale. Primary improvement of the new BrEPS protocol is the enhanced data selection step. Manually curated annotations from Swiss-Prot are used as reliable source for function prediction of enzymes observed on protein level. The pool of sequences is extended by highly similar sequences from TrEMBL and SwissProt. This allows us to restrict the selection of Swiss-Prot entries, without losing the diversity of sequences needed to generate significant patterns. Additionally, a supporting pattern type was introduced by extending the patterns at semi-conserved positions with highly similar amino acids. Extended patterns have an increased complexity, increasing the chance to match more sequences, without losing the essential structural information of the pattern. To enhance the usability of the database, we introduced enzyme function prediction based on consensus EC numbers and IUBMB enzyme nomenclature. BrEPS is part of the Braunschweig Enzyme Database (BRENDA) and is available on a completely redesigned website and as download. The database can be downloaded and used with the BrEPScmd command line tool for large scale sequence analysis. The BrEPS website and downloads for the database creation tool, command line tool and database are freely accessible at http://breps.tu-bs.de.

BrEPS 2.0: Optimization of sequence pattern prediction for enzyme annotation

PubMed Central

Schomburg, Dietmar

2017-01-01

The prediction of gene functions is crucial for a large number of different life science areas. Faster high throughput sequencing techniques generate more and larger datasets. The manual annotation by classical wet-lab experiments is not suitable for these large amounts of data. We showed earlier that the automatic sequence pattern-based BrEPS protocol, based on manually curated sequences, can be used for the prediction of enzymatic functions of genes. The growing sequence databases provide the opportunity for more reliable patterns, but are also a challenge for the implementation of automatic protocols. We reimplemented and optimized the BrEPS pattern generation to be applicable for larger datasets in an acceptable timescale. Primary improvement of the new BrEPS protocol is the enhanced data selection step. Manually curated annotations from Swiss-Prot are used as reliable source for function prediction of enzymes observed on protein level. The pool of sequences is extended by highly similar sequences from TrEMBL and SwissProt. This allows us to restrict the selection of Swiss-Prot entries, without losing the diversity of sequences needed to generate significant patterns. Additionally, a supporting pattern type was introduced by extending the patterns at semi-conserved positions with highly similar amino acids. Extended patterns have an increased complexity, increasing the chance to match more sequences, without losing the essential structural information of the pattern. To enhance the usability of the database, we introduced enzyme function prediction based on consensus EC numbers and IUBMB enzyme nomenclature. BrEPS is part of the Braunschweig Enzyme Database (BRENDA) and is available on a completely redesigned website and as download. The database can be downloaded and used with the BrEPScmd command line tool for large scale sequence analysis. The BrEPS website and downloads for the database creation tool, command line tool and database are freely accessible at http://breps.tu-bs.de. PMID:28750104

Rapid DNA extraction protocol for detection of alpha-1 antitrypsin deficiency from dried blood spots by real-time PCR.

PubMed

Struniawski, R; Szpechcinski, A; Poplawska, B; Skronski, M; Chorostowska-Wynimko, J

2013-01-01

The dried blood spot (DBS) specimens have been successfully employed for the large-scale diagnostics of α1-antitrypsin (AAT) deficiency as an easy to collect and transport alternative to plasma/serum. In the present study we propose a fast, efficient, and cost effective protocol of DNA extraction from dried blood spot (DBS) samples that provides sufficient quantity and quality of DNA and effectively eliminates any natural PCR inhibitors, allowing for successful AAT genotyping by real-time PCR and direct sequencing. DNA extracted from 84 DBS samples from chronic obstructive pulmonary disease patients was genotyped for AAT deficiency variants by real-time PCR. The results of DBS AAT genotyping were validated by serum IEF phenotyping and AAT concentration measurement. The proposed protocol allowed successful DNA extraction from all analyzed DBS samples. Both quantity and quality of DNA were sufficient for further real-time PCR and, if necessary, for genetic sequence analysis. A 100% concordance between AAT DBS genotypes and serum phenotypes in positive detection of two major deficiency S- and Z- alleles was achieved. Both assays, DBS AAT genotyping by real-time PCR and serum AAT phenotyping by IEF, positively identified PI*S and PI*Z allele in 8 out of the 84 (9.5%) and 16 out of 84 (19.0%) patients, respectively. In conclusion, the proposed protocol noticeably reduces the costs and the hand-on-time of DBS samples preparation providing genomic DNA of sufficient quantity and quality for further real-time PCR or genetic sequence analysis. Consequently, it is ideally suited for large-scale AAT deficiency screening programs and should be method of choice.

Conservation and variability of West Nile virus proteins.

PubMed

Koo, Qi Ying; Khan, Asif M; Jung, Keun-Ok; Ramdas, Shweta; Miotto, Olivo; Tan, Tin Wee; Brusic, Vladimir; Salmon, Jerome; August, J Thomas

2009-01-01

West Nile virus (WNV) has emerged globally as an increasingly important pathogen for humans and domestic animals. Studies of the evolutionary diversity of the virus over its known history will help to elucidate conserved sites, and characterize their correspondence to other pathogens and their relevance to the immune system. We describe a large-scale analysis of the entire WNV proteome, aimed at identifying and characterizing evolutionarily conserved amino acid sequences. This study, which used 2,746 WNV protein sequences collected from the NCBI GenPept database, focused on analysis of peptides of length 9 amino acids or more, which are immunologically relevant as potential T-cell epitopes. Entropy-based analysis of the diversity of WNV sequences, revealed the presence of numerous evolutionarily stable nonamer positions across the proteome (entropy value of < or = 1). The representation (frequency) of nonamers variant to the predominant peptide at these stable positions was, generally, low (< or = 10% of the WNV sequences analyzed). Eighty-eight fragments of length 9-29 amino acids, representing approximately 34% of the WNV polyprotein length, were identified to be identical and evolutionarily stable in all analyzed WNV sequences. Of the 88 completely conserved sequences, 67 are also present in other flaviviruses, and several have been associated with the functional and structural properties of viral proteins. Immunoinformatic analysis revealed that the majority (78/88) of conserved sequences are potentially immunogenic, while 44 contained experimentally confirmed human T-cell epitopes. This study identified a comprehensive catalogue of completely conserved WNV sequences, many of which are shared by other flaviviruses, and majority are potential epitopes. The complete conservation of these immunologically relevant sequences through the entire recorded WNV history suggests they will be valuable as components of peptide-specific vaccines or other therapeutic applications, for sequence-specific diagnosis of a wide-range of Flavivirus infections, and for studies of homologous sequences among other flaviviruses.

Identification of differentially methylated sites with weak methylation effect

USDA-ARS?s Scientific Manuscript database

DNA methylation is an epigenetic alteration crucial for regulating stress responses. Identifying large-scale DNA methylation at single nucleotide resolution is made possible by whole genome bisulfite sequencing. An essential task following the generation of bisulfite sequencing data is to detect dif...

Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences

PubMed Central

2014-01-01

Background Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Results Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. Conclusion The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification. PMID:24418292

Exploring root symbiotic programs in the model legume Medicago truncatula using EST analysis.

PubMed

Journet, Etienne-Pascal; van Tuinen, Diederik; Gouzy, Jérome; Crespeau, Hervé; Carreau, Véronique; Farmer, Mary-Jo; Niebel, Andreas; Schiex, Thomas; Jaillon, Olivier; Chatagnier, Odile; Godiard, Laurence; Micheli, Fabienne; Kahn, Daniel; Gianinazzi-Pearson, Vivienne; Gamas, Pascal

2002-12-15

We report on a large-scale expressed sequence tag (EST) sequencing and analysis program aimed at characterizing the sets of genes expressed in roots of the model legume Medicago truncatula during interactions with either of two microsymbionts, the nitrogen-fixing bacterium Sinorhizobium meliloti or the arbuscular mycorrhizal fungus Glomus intraradices. We have designed specific tools for in silico analysis of EST data, in relation to chimeric cDNA detection, EST clustering, encoded protein prediction, and detection of differential expression. Our 21 473 5'- and 3'-ESTs could be grouped into 6359 EST clusters, corresponding to distinct virtual genes, along with 52 498 other M.truncatula ESTs available in the dbEST (NCBI) database that were recruited in the process. These clusters were manually annotated, using a specifically developed annotation interface. Analysis of EST cluster distribution in various M.truncatula cDNA libraries, supported by a refined R test to evaluate statistical significance and by 'electronic northern' representation, enabled us to identify a large number of novel genes predicted to be up- or down-regulated during either symbiotic root interaction. These in silico analyses provide a first global view of the genetic programs for root symbioses in M.truncatula. A searchable database has been built and can be accessed through a public interface.

Genomic insights into the taxonomic status of the Bacillus cereus group

PubMed Central

Liu, Yang; Lai, Qiliang; Göker, Markus; Meier-Kolthoff, Jan P.; Wang, Meng; Sun, Yamin; Wang, Lei; Shao, Zongze

2015-01-01

The identification and phylogenetic relationships of bacteria within the Bacillus cereus group are controversial. This study aimed at determining the taxonomic affiliations of these strains using the whole-genome sequence-based Genome BLAST Distance Phylogeny (GBDP) approach. The GBDP analysis clearly separated 224 strains into 30 clusters, representing eleven known, partially merged species and accordingly 19–20 putative novel species. Additionally, 16S rRNA gene analysis, a novel variant of multi-locus sequence analysis (nMLSA) and screening of virulence genes were performed. The 16S rRNA gene sequence was not sufficient to differentiate the bacteria within this group due to its high conservation. The nMLSA results were consistent with GBDP. Moreover, a fast typing method was proposed using the pycA gene, and where necessary, the ccpA gene. The pXO plasmids and cry genes were widely distributed, suggesting little correlation with the phylogenetic positions of the host bacteria. This might explain why classifications based on virulence characteristics proved unsatisfactory in the past. In summary, this is the first large-scale and systematic study of the taxonomic status of the bacteria within the B. cereus group using whole-genome sequences, and is likely to contribute to further insights into their pathogenicity, phylogeny and adaptation to diverse environments. PMID:26373441

Functional sequencing read annotation for high precision microbiome analysis

PubMed Central

Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani; Vaysberg, Pavel; Rühlemann, Malte C; Wu, Guojun; Heinsen, Femke-Anouska; Tempel, Marie; Zhao, Liping; Lieb, Wolfgang; Franke, Andre; Bromberg, Yana

2018-01-01

Abstract The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it. PMID:29194524

Large-Scale Interaction Profiling of Protein Domains Through Proteomic Peptide-Phage Display Using Custom Peptidomes.

PubMed

Seo, Moon-Hyeong; Nim, Satra; Jeon, Jouhyun; Kim, Philip M

2017-01-01

Protein-protein interactions are essential to cellular functions and signaling pathways. We recently combined bioinformatics and custom oligonucleotide arrays to construct custom-made peptide-phage libraries for screening peptide-protein interactions, an approach we call proteomic peptide-phage display (ProP-PD). In this chapter, we describe protocols for phage display for the identification of natural peptide binders for a given protein. We finally describe deep sequencing for the analysis of the proteomic peptide-phage display.

Dichlorvos Exposure Results in Large Scale Disruption of Energy Metabolism in the Liver of the Zebra Fish, Danio Rerio

DTIC Science & Technology

2015-10-24

zebrafish reference genome sequence and its relationship to the human genome . Nature. 2013;496(7446):498–503. 21. Linney E, Upchurch L, Donerly S. Zebrafish...To obtain a broader understanding of the effects of dichlorvos on liver metabolism, we per- formed a genome -wide analysis of gene expression in the ...condition) for whole genome transcript ana- lysis, and fixed another set of fish for histological evaluation (n = 5/condition). We determined the target

Front-End Electron Transfer Dissociation Coupled to a 21 Tesla FT-ICR Mass Spectrometer for Intact Protein Sequence Analysis

NASA Astrophysics Data System (ADS)

Weisbrod, Chad R.; Kaiser, Nathan K.; Syka, John E. P.; Early, Lee; Mullen, Christopher; Dunyach, Jean-Jacques; English, A. Michelle; Anderson, Lissa C.; Blakney, Greg T.; Shabanowitz, Jeffrey; Hendrickson, Christopher L.; Marshall, Alan G.; Hunt, Donald F.

2017-09-01

High resolution mass spectrometry is a key technology for in-depth protein characterization. High-field Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) enables high-level interrogation of intact proteins in the most detail to date. However, an appropriate complement of fragmentation technologies must be paired with FTMS to provide comprehensive sequence coverage, as well as characterization of sequence variants, and post-translational modifications. Here we describe the integration of front-end electron transfer dissociation (FETD) with a custom-built 21 tesla FT-ICR mass spectrometer, which yields unprecedented sequence coverage for proteins ranging from 2.8 to 29 kDa, without the need for extensive spectral averaging (e.g., 60% sequence coverage for apo-myoglobin with four averaged acquisitions). The system is equipped with a multipole storage device separate from the ETD reaction device, which allows accumulation of multiple ETD fragment ion fills. Consequently, an optimally large product ion population is accumulated prior to transfer to the ICR cell for mass analysis, which improves mass spectral signal-to-noise ratio, dynamic range, and scan rate. We find a linear relationship between protein molecular weight and minimum number of ETD reaction fills to achieve optimum sequence coverage, thereby enabling more efficient use of instrument data acquisition time. Finally, real-time scaling of the number of ETD reactions fills during method-based acquisition is shown, and the implications for LC-MS/MS top-down analysis are discussed. [Figure not available: see fulltext.

pico-PLAZA, a genome database of microbial photosynthetic eukaryotes.

PubMed

Vandepoele, Klaas; Van Bel, Michiel; Richard, Guilhem; Van Landeghem, Sofie; Verhelst, Bram; Moreau, Hervé; Van de Peer, Yves; Grimsley, Nigel; Piganeau, Gwenael

2013-08-01

With the advent of next generation genome sequencing, the number of sequenced algal genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse individual genome sequences, exploring complete genome information from multiple species for the analysis of user-defined sequences or gene lists remains a major challenge. pico-PLAZA is a web-based resource (http://bioinformatics.psb.ugent.be/pico-plaza/) for algal genomics that combines different data types with intuitive tools to explore genomic diversity, perform integrative evolutionary sequence analysis and study gene functions. Apart from homologous gene families, multiple sequence alignments, phylogenetic trees, Gene Ontology, InterPro and text-mining functional annotations, different interactive viewers are available to study genome organization using gene collinearity and synteny information. Different search functions, documentation pages, export functions and an extensive glossary are available to guide non-expert scientists. To illustrate the versatility of the platform, different case studies are presented demonstrating how pico-PLAZA can be used to functionally characterize large-scale EST/RNA-Seq data sets and to perform environmental genomics. Functional enrichments analysis of 16 Phaeodactylum tricornutum transcriptome libraries offers a molecular view on diatom adaptation to different environments of ecological relevance. Furthermore, we show how complementary genomic data sources can easily be combined to identify marker genes to study the diversity and distribution of algal species, for example in metagenomes, or to quantify intraspecific diversity from environmental strains. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Molecular Cytogenetics Guides Massively Parallel Sequencing of a Radiation-Induced Chromosome Translocation in Human Cells.

PubMed

Cornforth, Michael N; Anur, Pavana; Wang, Nicholas; Robinson, Erin; Ray, F Andrew; Bedford, Joel S; Loucas, Bradford D; Williams, Eli S; Peto, Myron; Spellman, Paul; Kollipara, Rahul; Kittler, Ralf; Gray, Joe W; Bailey, Susan M

2018-05-11

Chromosome rearrangements are large-scale structural variants that are recognized drivers of oncogenic events in cancers of all types. Cytogenetics allows for their rapid, genome-wide detection, but does not provide gene-level resolution. Massively parallel sequencing (MPS) promises DNA sequence-level characterization of the specific breakpoints involved, but is strongly influenced by bioinformatics filters that affect detection efficiency. We sought to characterize the breakpoint junctions of chromosomal translocations and inversions in the clonal derivatives of human cells exposed to ionizing radiation. Here, we describe the first successful use of DNA paired-end analysis to locate and sequence across the breakpoint junctions of a radiation-induced reciprocal translocation. The analyses employed, with varying degrees of success, several well-known bioinformatics algorithms, a task made difficult by the involvement of repetitive DNA sequences. As for underlying mechanisms, the results of Sanger sequencing suggested that the translocation in question was likely formed via microhomology-mediated non-homologous end joining (mmNHEJ). To our knowledge, this represents the first use of MPS to characterize the breakpoint junctions of a radiation-induced chromosomal translocation in human cells. Curiously, these same approaches were unsuccessful when applied to the analysis of inversions previously identified by directional genomic hybridization (dGH). We conclude that molecular cytogenetics continues to provide critical guidance for structural variant discovery, validation and in "tuning" analysis filters to enable robust breakpoint identification at the base pair level.

Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens.

PubMed

Lyons, Eli; Sheridan, Paul; Tremmel, Georg; Miyano, Satoru; Sugano, Sumio

2017-10-24

High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

CANEapp: a user-friendly application for automated next generation transcriptomic data analysis.

PubMed

Velmeshev, Dmitry; Lally, Patrick; Magistri, Marco; Faghihi, Mohammad Ali

2016-01-13

Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers. To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app . We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups.

DAMe: a toolkit for the initial processing of datasets with PCR replicates of double-tagged amplicons for DNA metabarcoding analyses.

PubMed

Zepeda-Mendoza, Marie Lisandra; Bohmann, Kristine; Carmona Baez, Aldo; Gilbert, M Thomas P

2016-05-03

DNA metabarcoding is an approach for identifying multiple taxa in an environmental sample using specific genetic loci and taxa-specific primers. When combined with high-throughput sequencing it enables the taxonomic characterization of large numbers of samples in a relatively time- and cost-efficient manner. One recent laboratory development is the addition of 5'-nucleotide tags to both primers producing double-tagged amplicons and the use of multiple PCR replicates to filter erroneous sequences. However, there is currently no available toolkit for the straightforward analysis of datasets produced in this way. We present DAMe, a toolkit for the processing of datasets generated by double-tagged amplicons from multiple PCR replicates derived from an unlimited number of samples. Specifically, DAMe can be used to (i) sort amplicons by tag combination, (ii) evaluate PCR replicates dissimilarity, and (iii) filter sequences derived from sequencing/PCR errors, chimeras, and contamination. This is attained by calculating the following parameters: (i) sequence content similarity between the PCR replicates from each sample, (ii) reproducibility of each unique sequence across the PCR replicates, and (iii) copy number of the unique sequences in each PCR replicate. We showcase the insights that can be obtained using DAMe prior to taxonomic assignment, by applying it to two real datasets that vary in their complexity regarding number of samples, sequencing libraries, PCR replicates, and used tag combinations. Finally, we use a third mock dataset to demonstrate the impact and importance of filtering the sequences with DAMe. DAMe allows the user-friendly manipulation of amplicons derived from multiple samples with PCR replicates built in a single or multiple sequencing libraries. It allows the user to: (i) collapse amplicons into unique sequences and sort them by tag combination while retaining the sample identifier and copy number information, (ii) identify sequences carrying unused tag combinations, (iii) evaluate the comparability of PCR replicates of the same sample, and (iv) filter tagged amplicons from a number of PCR replicates using parameters of minimum length, copy number, and reproducibility across the PCR replicates. This enables an efficient analysis of complex datasets, and ultimately increases the ease of handling datasets from large-scale studies.

XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing.

PubMed

Piton, Amélie; Redin, Claire; Mandel, Jean-Louis

2013-08-08

Because of the unbalanced sex ratio (1.3-1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

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

Chen, I-Min; Chu, Ken; Ratner, Anna

2014-10-28

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorwaymore » to a new era in the discovery of novel molecules.« less

Large-scale purification and biochemical characterization of crystallization-grade porin protein P from Pseudomonas aeruginosa.

PubMed

Worobec, E A; Martin, N L; McCubbin, W D; Kay, C M; Brayer, G D; Hancock, R E

1988-04-07

A large-scale purification scheme was developed for lipopolysaccharide-free protein P, the phosphate-starvation-inducible outer-membrane porin from Pseudomonas aeruginosa. This highly purified protein P was used to successfully form hexagonal crystals in the presence of n-octyl-beta-glucopyranoside. Amino-acid analysis indicated that protein P had a similar composition to other bacterial outer membrane proteins, containing a high percentage (50%) of hydrophilic residues. The amino-terminal sequence of this protein, although not homologous to either outer membrane protein, PhoE or OmpF, of Escherichia coli, was found to have an analogous protein-folding pattern. Protein P in the native trimer form was capable of maintaining a stable functional trimer after proteinase cleavage. This suggested the existence of a strongly associated tertiary and quaternary structure. Circular dichroism studies confirmed these results in that a large proportion of the protein structure was determined to be beta-sheet and resistant to acid pH and heating in 0.1% sodium dodecyl sulphate.

Nanowire-nanopore transistor sensor for DNA detection during translocation

NASA Astrophysics Data System (ADS)

Xie, Ping; Xiong, Qihua; Fang, Ying; Qing, Quan; Lieber, Charles

2011-03-01

Nanopore sequencing, as a promising low cost, high throughput sequencing technique, has been proposed more than a decade ago. Due to the incompatibility between small ionic current signal and fast translocation speed and the technical difficulties on large scale integration of nanopore for direct ionic current sequencing, alternative methods rely on integrated DNA sensors have been proposed, such as using capacitive coupling or tunnelling current etc. But none of them have been experimentally demonstrated yet. Here we show that for the first time an amplified sensor signal has been experimentally recorded from a nanowire-nanopore field effect transistor sensor during DNA translocation. Independent multi-channel recording was also demonstrated for the first time. Our results suggest that the signal is from highly localized potential change caused by DNA translocation in none-balanced buffer condition. Given this method may produce larger signal for smaller nanopores, we hope our experiment can be a starting point for a new generation of nanopore sequencing devices with larger signal, higher bandwidth and large-scale multiplexing capability and finally realize the ultimate goal of low cost high throughput sequencing.

Phylogenetic characterization of a biogas plant microbial community integrating clone library 16S-rDNA sequences and metagenome sequence data obtained by 454-pyrosequencing.

PubMed

Kröber, Magdalena; Bekel, Thomas; Diaz, Naryttza N; Goesmann, Alexander; Jaenicke, Sebastian; Krause, Lutz; Miller, Dimitri; Runte, Kai J; Viehöver, Prisca; Pühler, Alfred; Schlüter, Andreas

2009-06-01

The phylogenetic structure of the microbial community residing in a fermentation sample from a production-scale biogas plant fed with maize silage, green rye and liquid manure was analysed by an integrated approach using clone library sequences and metagenome sequence data obtained by 454-pyrosequencing. Sequencing of 109 clones from a bacterial and an archaeal 16S-rDNA amplicon library revealed that the obtained nucleotide sequences are similar but not identical to 16S-rDNA database sequences derived from different anaerobic environments including digestors and bioreactors. Most of the bacterial 16S-rDNA sequences could be assigned to the phylum Firmicutes with the most abundant class Clostridia and to the class Bacteroidetes, whereas most archaeal 16S-rDNA sequences cluster close to the methanogen Methanoculleus bourgensis. Further sequences of the archaeal library most probably represent so far non-characterised species within the genus Methanoculleus. A similar result derived from phylogenetic analysis of mcrA clone sequences. The mcrA gene product encodes the alpha-subunit of methyl-coenzyme-M reductase involved in the final step of methanogenesis. BLASTn analysis applying stringent settings resulted in assignment of 16S-rDNA metagenome sequence reads to 62 16S-rDNA amplicon sequences thus enabling frequency of abundance estimations for 16S-rDNA clone library sequences. Ribosomal Database Project (RDP) Classifier processing of metagenome 16S-rDNA reads revealed abundance of the phyla Firmicutes, Bacteroidetes and Euryarchaeota and the orders Clostridiales, Bacteroidales and Methanomicrobiales. Moreover, a large fraction of 16S-rDNA metagenome reads could not be assigned to lower taxonomic ranks, demonstrating that numerous microorganisms in the analysed fermentation sample of the biogas plant are still unclassified or unknown.

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

PubMed Central

Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

2013-01-01

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765

Resources and costs for microbial sequence analysis evaluated using virtual machines and cloud computing.

PubMed

Angiuoli, Samuel V; White, James R; Matalka, Malcolm; White, Owen; Fricke, W Florian

2011-01-01

The widespread popularity of genomic applications is threatened by the "bioinformatics bottleneck" resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly. We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers. Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S rRNA amplicon sequencing, microbial single-genome and metagenomics WGS projects can achieve cost-efficient bioinformatics support using CloVR in combination with Amazon EC2 as an alternative to local computing centers.

Resources and Costs for Microbial Sequence Analysis Evaluated Using Virtual Machines and Cloud Computing

PubMed Central

Angiuoli, Samuel V.; White, James R.; Matalka, Malcolm; White, Owen; Fricke, W. Florian

2011-01-01

Background The widespread popularity of genomic applications is threatened by the “bioinformatics bottleneck” resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly. Results We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers. Conclusions Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S rRNA amplicon sequencing, microbial single-genome and metagenomics WGS projects can achieve cost-efficient bioinformatics support using CloVR in combination with Amazon EC2 as an alternative to local computing centers. PMID:22028928

Are Clay Minerals a Climate Constraint? A Review of Prior Data and New Insights on Martian "Weathering Sequences"

NASA Astrophysics Data System (ADS)

Ehlmann, B. L.; Dundar, M.

2016-12-01

Most clay minerals on Mars are Fe/Mg smectites or chlorites, which typically form from mafic protoliths in aqueous chemical systems that are relatively closed and thus require liquid water but not large amounts of water throughput and large-scale chemical leaching. They may thus form either in the subsurface or under select conditions at the surface. However, Al clay minerals, discovered in multiple locations on Mars (Arabia Terra, Northeast Syrtis, Libya Montes Terra Sirenum, Eridania, circum-Hellas, Valles Marineris) may provide evidence of substantial water throughput, if their protolith materials were basaltic. This is because formation of Al clays from a mafic protolith requires removal of Mg and either formation of accompanying Fe oxides or removal of Fe. Thus, the observed sequences of Al clays atop Fe/Mg clays were proposed to represent open system weathering and possibly a late climate optimum around the late Noachian/early Hesperian [1]. Later, they were comprehensively cataloged and reported to represent "weathering sequences" similar to those in terrestrial tropical environments [2]. However, key questions remain; in particular, how much water throughput over what time scale is required? The answer to this question has substantial bearing on the climate of early Mars. Recently, we employed a newly developed, non-parametric Bayesian algorithm [3,4] for semi-automatic identification of rare spectral classes on 139 CRISM images in areas with reported regional-scale occurrences of Al clays. Dozens of detections of the minerals alunite and jarosite were made with the algorithm and then verified by manual analysis. These sulfate hydroxides form only at low pHs, and thus their presence tightly constrains water chemistry. Here, we discuss the evidence for low pH surface waters associated with the weathering sequences and their implications for the cumulative duration of surface weathering. [1] Ehlmann et al., 2011, Nature | [2] Carter et al., 2015, Icarus | [3] Dundar et al., 2016, IEEE WHISPERS proceedings | [4] Ehlmann & Dundar, submitted

Implications of Secondary Aftershocks for Failure Processes

NASA Astrophysics Data System (ADS)

Gross, S. J.

2001-12-01

When a seismic sequence with more than one mainshock or an unusually large aftershock occurs, there is a compound aftershock sequence. The secondary aftershocks need not have exactly the same decay as the primary sequence, with the differences having implications for the failure process. When the stress step from the secondary mainshock is positive but not large enough to cause immediate failure of all the remaining primary aftershocks, failure processes which involve accelerating slip will produce secondary aftershocks that decay more rapidly than primary aftershocks. This is because the primary aftershocks are an accelerated version of the background seismicity, and secondary aftershocks are an accelerated version of the primary aftershocks. Real stress perturbations may be negative, and heterogeneities in mainshock stress fields mean that the real world situation is quite complicated. I will first describe and verify my picture of secondary aftershock decay with reference to a simple numerical model of slipping faults which obeys rate and state dependent friction and lacks stress heterogeneity. With such a model, it is possible to generate secondary aftershock sequences with perturbed decay patterns, quantify those patterns, and develop an analysis technique capable of correcting for the effect in real data. The secondary aftershocks are defined in terms of frequency linearized time s(T), which is equal to the number of primary aftershocks expected by a time T, $ s ≡ ∫ t=0T n(t) dt, where the start time t=0 is the time of the primary aftershock, and the primary aftershock decay function n(t) is extrapolated forward to the times of the secondary aftershocks. In the absence of secondary sequences the function s(T)$ re-scales the time so that approximately one event occurs per new time unit; the aftershock sequence is gone. If this rescaling is applied in the presence of a secondary sequence, the secondary sequence is shaped like a primary aftershock sequence, and can be fit by the same modeling techniques applied to simple sequences. The later part of the presentation will concern the decay of Hector Mine aftershocks as influenced by the Landers aftershocks. Although attempts to predict the abundance of Hector aftershocks based on stress overlap analysis are not very successful, the analysis does do a good job fitting the decay of secondary sequences.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology.

PubMed

Cock, Peter J A; Grüning, Björn A; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of "effector" proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen's predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

Component identification of electron transport chains in curdlan-producing Agrobacterium sp. ATCC 31749 and its genome-specific prediction using comparative genome and phylogenetic trees analysis.

PubMed

Zhang, Hongtao; Setubal, Joao Carlos; Zhan, Xiaobei; Zheng, Zhiyong; Yu, Lijun; Wu, Jianrong; Chen, Dingqiang

2011-06-01

Agrobacterium sp. ATCC 31749 (formerly named Alcaligenes faecalis var. myxogenes) is a non-pathogenic aerobic soil bacterium used in large scale biotechnological production of curdlan. However, little is known about its genomic information. DNA partial sequence of electron transport chains (ETCs) protein genes were obtained in order to understand the components of ETC and genomic-specificity in Agrobacterium sp. ATCC 31749. Degenerate primers were designed according to ETC conserved sequences in other reported species. DNA partial sequences of ETC genes in Agrobacterium sp. ATCC 31749 were cloned by the PCR method using degenerate primers. Based on comparative genomic analysis, nine electron transport elements were ascertained, including NADH ubiquinone oxidoreductase, succinate dehydrogenase complex II, complex III, cytochrome c, ubiquinone biosynthesis protein ubiB, cytochrome d terminal oxidase, cytochrome bo terminal oxidase, cytochrome cbb (3)-type terminal oxidase and cytochrome caa (3)-type terminal oxidase. Similarity and phylogenetic analyses of these genes revealed that among fully sequenced Agrobacterium species, Agrobacterium sp. ATCC 31749 is closest to Agrobacterium tumefaciens C58. Based on these results a comprehensive ETC model for Agrobacterium sp. ATCC 31749 is proposed.

A large scale analysis of cDNA in Arabidopsis thaliana: generation of 12,028 non-redundant expressed sequence tags from normalized and size-selected cDNA libraries.

PubMed

Asamizu, E; Nakamura, Y; Sato, S; Tabata, S

2000-06-30

For comprehensive analysis of genes expressed in the model dicotyledonous plant, Arabidopsis thaliana, expressed sequence tags (ESTs) were accumulated. Normalized and size-selected cDNA libraries were constructed from aboveground organs, flower buds, roots, green siliques and liquid-cultured seedlings, respectively, and a total of 14,026 5'-end ESTs and 39,207 3'-end ESTs were obtained. The 3'-end ESTs could be clustered into 12,028 non-redundant groups. Similarity search of the non-redundant ESTs against the public non-redundant protein database indicated that 4816 groups show similarity to genes of known function, 1864 to hypothetical genes, and the remaining 5348 are novel sequences. Gene coverage by the non-redundant ESTs was analyzed using the annotated genomic sequences of approximately 10 Mb on chromosomes 3 and 5. A total of 923 regions were hit by at least one EST, among which only 499 regions were hit by the ESTs deposited in the public database. The result indicates that the EST source generated in this project complements the EST data in the public database and facilitates new gene discovery.

Concept For Generation Of Long Pseudorandom Sequences

NASA Technical Reports Server (NTRS)

Wang, C. C.

1990-01-01

Conceptual very-large-scale integrated (VLSI) digital circuit performs exponentiation in finite field. Algorithm that generates unusually long sequences of pseudorandom numbers executed by digital processor that includes such circuits. Concepts particularly advantageous for such applications as spread-spectrum communications, cryptography, and generation of ranging codes, synthetic noise, and test data, where usually desirable to make pseudorandom sequences as long as possible.

SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

PubMed Central

Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

2001-01-01

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

ocsESTdb: a database of oil crop seed EST sequences for comparative analysis and investigation of a global metabolic network and oil accumulation metabolism.

PubMed

Ke, Tao; Yu, Jingyin; Dong, Caihua; Mao, Han; Hua, Wei; Liu, Shengyi

2015-01-21

Oil crop seeds are important sources of fatty acids (FAs) for human and animal nutrition. Despite their importance, there is a lack of an essential bioinformatics resource on gene transcription of oil crops from a comparative perspective. In this study, we developed ocsESTdb, the first database of expressed sequence tag (EST) information on seeds of four large-scale oil crops with an emphasis on global metabolic networks and oil accumulation metabolism that target the involved unigenes. A total of 248,522 ESTs and 106,835 unigenes were collected from the cDNA libraries of rapeseed (Brassica napus), soybean (Glycine max), sesame (Sesamum indicum) and peanut (Arachis hypogaea). These unigenes were annotated by a sequence similarity search against databases including TAIR, NR protein database, Gene Ontology, COG, Swiss-Prot, TrEMBL and Kyoto Encyclopedia of Genes and Genomes (KEGG). Five genome-scale metabolic networks that contain different numbers of metabolites and gene-enzyme reaction-association entries were analysed and constructed using Cytoscape and yEd programs. Details of unigene entries, deduced amino acid sequences and putative annotation are available from our database to browse, search and download. Intuitive and graphical representations of EST/unigene sequences, functional annotations, metabolic pathways and metabolic networks are also available. ocsESTdb will be updated regularly and can be freely accessed at http://ocri-genomics.org/ocsESTdb/ . ocsESTdb may serve as a valuable and unique resource for comparative analysis of acyl lipid synthesis and metabolism in oilseed plants. It also may provide vital insights into improving oil content in seeds of oil crop species by transcriptional reconstruction of the metabolic network.

An evaluation of the accuracy and speed of metagenome analysis tools

PubMed Central

Lindgreen, Stinus; Adair, Karen L.; Gardner, Paul P.

2016-01-01

Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html PMID:26778510

Ancient DNA studies: new perspectives on old samples

PubMed Central

2012-01-01

In spite of past controversies, the field of ancient DNA is now a reliable research area due to recent methodological improvements. A series of recent large-scale studies have revealed the true potential of ancient DNA samples to study the processes of evolution and to test models and assumptions commonly used to reconstruct patterns of evolution and to analyze population genetics and palaeoecological changes. Recent advances in DNA technologies, such as next-generation sequencing make it possible to recover DNA information from archaeological and paleontological remains allowing us to go back in time and study the genetic relationships between extinct organisms and their contemporary relatives. With the next-generation sequencing methodologies, DNA sequences can be retrieved even from samples (for example human remains) for which the technical pitfalls of classical methodologies required stringent criteria to guaranty the reliability of the results. In this paper, we review the methodologies applied to ancient DNA analysis and the perspectives that next-generation sequencing applications provide in this field. PMID:22697611

Management of familial cancer: sequencing, surveillance and society.

PubMed

Samuel, Nardin; Villani, Anita; Fernandez, Conrad V; Malkin, David

2014-12-01

The clinical management of familial cancer begins with recognition of patterns of cancer occurrence suggestive of genetic susceptibility in a proband or pedigree, to enable subsequent investigation of the underlying DNA mutations. In this regard, next-generation sequencing of DNA continues to transform cancer diagnostics, by enabling screening for cancer-susceptibility genes in the context of known and emerging familial cancer syndromes. Increasingly, not only are candidate cancer genes sequenced, but also entire 'healthy' genomes are mapped in children with cancer and their family members. Although large-scale genomic analysis is considered intrinsic to the success of cancer research and discovery, a number of accompanying ethical and technical issues must be addressed before this approach can be adopted widely in personalized therapy. In this Perspectives article, we describe our views on how the emergence of new sequencing technologies and cancer surveillance strategies is altering the framework for the clinical management of hereditary cancer. Genetic counselling and disclosure issues are discussed, and strategies for approaching ethical dilemmas are proposed.

Survey of MapReduce frame operation in bioinformatics.

PubMed

Zou, Quan; Li, Xu-Bin; Jiang, Wen-Rui; Lin, Zi-Yu; Li, Gui-Lin; Chen, Ke

2014-07-01

Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Genome sequencing in microfabricated high-density picolitre reactors.

PubMed

Margulies, Marcel; Egholm, Michael; Altman, William E; Attiya, Said; Bader, Joel S; Bemben, Lisa A; Berka, Jan; Braverman, Michael S; Chen, Yi-Ju; Chen, Zhoutao; Dewell, Scott B; Du, Lei; Fierro, Joseph M; Gomes, Xavier V; Godwin, Brian C; He, Wen; Helgesen, Scott; Ho, Chun Heen; Ho, Chun He; Irzyk, Gerard P; Jando, Szilveszter C; Alenquer, Maria L I; Jarvie, Thomas P; Jirage, Kshama B; Kim, Jong-Bum; Knight, James R; Lanza, Janna R; Leamon, John H; Lefkowitz, Steven M; Lei, Ming; Li, Jing; Lohman, Kenton L; Lu, Hong; Makhijani, Vinod B; McDade, Keith E; McKenna, Michael P; Myers, Eugene W; Nickerson, Elizabeth; Nobile, John R; Plant, Ramona; Puc, Bernard P; Ronan, Michael T; Roth, George T; Sarkis, Gary J; Simons, Jan Fredrik; Simpson, John W; Srinivasan, Maithreyan; Tartaro, Karrie R; Tomasz, Alexander; Vogt, Kari A; Volkmer, Greg A; Wang, Shally H; Wang, Yong; Weiner, Michael P; Yu, Pengguang; Begley, Richard F; Rothberg, Jonathan M

2005-09-15

The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments. The apparatus uses a novel fibre-optic slide of individual wells and is able to sequence 25 million bases, at 99% or better accuracy, in one four-hour run. To achieve an approximately 100-fold increase in throughput over current Sanger sequencing technology, we have developed an emulsion method for DNA amplification and an instrument for sequencing by synthesis using a pyrosequencing protocol optimized for solid support and picolitre-scale volumes. Here we show the utility, throughput, accuracy and robustness of this system by shotgun sequencing and de novo assembly of the Mycoplasma genitalium genome with 96% coverage at 99.96% accuracy in one run of the machine.

Large-scale photospheric motions determined from granule tracking and helioseismology from SDO/HMI data

NASA Astrophysics Data System (ADS)

Roudier, Th.; Švanda, M.; Ballot, J.; Malherbe, J. M.; Rieutord, M.

2018-04-01

Context. Large-scale flows in the Sun play an important role in the dynamo process linked to the solar cycle. The important large-scale flows are the differential rotation and the meridional circulation with an amplitude of km s-1 and few m s-1, respectively. These flows also have a cycle-related components, namely the torsional oscillations. Aim. Our attempt is to determine large-scale plasma flows on the solar surface by deriving horizontal flow velocities using the techniques of solar granule tracking, dopplergrams, and time-distance helioseismology. Methods: Coherent structure tracking (CST) and time-distance helioseismology were used to investigate the solar differential rotation and meridional circulation at the solar surface on a 30-day HMI/SDO sequence. The influence of a large sunspot on these large-scale flows with a specific 7-day HMI/SDO sequence has been also studied. Results: The large-scale flows measured by the CST on the solar surface and the same flow determined from the same data with the helioseismology in the first 1 Mm below the surface are in good agreement in amplitude and direction. The torsional waves are also located at the same latitudes with amplitude of the same order. We are able to measure the meridional circulation correctly using the CST method with only 3 days of data and after averaging between ± 15° in longitude. Conclusions: We conclude that the combination of CST and Doppler velocities allows us to detect properly the differential solar rotation and also smaller amplitude flows such as the meridional circulation and torsional waves. The results of our methods are in good agreement with helioseismic measurements.

Sequencing of Seven Haloarchaeal Genomes Reveals Patterns of Genomic Flux

PubMed Central

Lynch, Erin A.; Langille, Morgan G. I.; Darling, Aaron; Wilbanks, Elizabeth G.; Haltiner, Caitlin; Shao, Katie S. Y.; Starr, Michael O.; Teiling, Clotilde; Harkins, Timothy T.; Edwards, Robert A.; Eisen, Jonathan A.; Facciotti, Marc T.

2012-01-01

We report the sequencing of seven genomes from two haloarchaeal genera, Haloferax and Haloarcula. Ease of cultivation and the existence of well-developed genetic and biochemical tools for several diverse haloarchaeal species make haloarchaea a model group for the study of archaeal biology. The unique physiological properties of these organisms also make them good candidates for novel enzyme discovery for biotechnological applications. Seven genomes were sequenced to ∼20×coverage and assembled to an average of 50 contigs (range 5 scaffolds - 168 contigs). Comparisons of protein-coding gene compliments revealed large-scale differences in COG functional group enrichment between these genera. Analysis of genes encoding machinery for DNA metabolism reveals genera-specific expansions of the general transcription factor TATA binding protein as well as a history of extensive duplication and horizontal transfer of the proliferating cell nuclear antigen. Insights gained from this study emphasize the importance of haloarchaea for investigation of archaeal biology. PMID:22848480

EUPAN enables pan-genome studies of a large number of eukaryotic genomes.

PubMed

Hu, Zhiqiang; Sun, Chen; Lu, Kuang-Chen; Chu, Xixia; Zhao, Yue; Lu, Jinyuan; Shi, Jianxin; Wei, Chaochun

2017-08-01

Pan-genome analyses are routinely carried out for bacteria to interpret the within-species gene presence/absence variations (PAVs). However, pan-genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan-genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re-sequencing projects primarily focusing on single nucleotide polymorphisms. EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non-commercial use (CC BY-NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html . ccwei@sjtu.edu.cn or jianxin.shi@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fine-scale patterns of population stratification confound rare variant association tests.

PubMed

O'Connor, Timothy D; Kiezun, Adam; Bamshad, Michael; Rich, Stephen S; Smith, Joshua D; Turner, Emily; Leal, Suzanne M; Akey, Joshua M

2013-01-01

Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant association methods remains poorly understood. Here, we performed exhaustive coalescent simulations with demographic parameters calibrated from exome sequence data to evaluate the performance of nine rare variant association methods in the presence of fine-scale population structure. We find that all methods have an inflated spurious association rate for parameter values that are consistent with levels of differentiation typical of European populations. For example, at a nominal significance level of 5%, some test statistics have a spurious association rate as high as 40%. Finally, we empirically assess the impact of population stratification in a large data set of 4,298 European American exomes. Our results have important implications for the design, analysis, and interpretation of rare variant genome-wide association studies.

Understanding continental megathrust earthquake potential through geological mountain building processes: an example in Nepal Himalaya

NASA Astrophysics Data System (ADS)

Zhang, Huai; Zhang, Zhen; Wang, Liangshu; Leroy, Yves; shi, Yaolin

2017-04-01

How to reconcile continent megathrust earthquake characteristics, for instances, mapping the large-great earthquake sequences into geological mountain building process, as well as partitioning the seismic-aseismic slips, is fundamental and unclear. Here, we scope these issues by focusing a typical continental collisional belt, the great Nepal Himalaya. We first prove that refined Nepal Himalaya thrusting sequences, with accurately defining of large earthquake cycle scale, provide new geodynamical hints on long-term earthquake potential in association with, either seismic-aseismic slip partition up to the interpretation of the binary interseismic coupling pattern on the Main Himalayan Thrust (MHT), or the large-great earthquake classification via seismic cycle patterns on MHT. Subsequently, sequential limit analysis is adopted to retrieve the detailed thrusting sequences of Nepal Himalaya mountain wedge. Our model results exhibit apparent thrusting concentration phenomenon with four thrusting clusters, entitled as thrusting 'families', to facilitate the development of sub-structural regions respectively. Within the hinterland thrusting family, the total aseismic shortening and the corresponding spatio-temporal release pattern are revealed by mapping projection. Whereas, in the other three families, mapping projection delivers long-term large (M<8)-great (M>8) earthquake recurrence information, including total lifespans, frequencies and large-great earthquake alternation information by identifying rupture distances along the MHT. In addition, this partition has universality in continental-continental collisional orogenic belt with identified interseismic coupling pattern, while not applicable in continental-oceanic megathrust context.

Noninvasive prenatal diagnosis of common aneuploidies by semiconductor sequencing

PubMed Central

Liao, Can; Yin, Ai-hua; Peng, Chun-fang; Fu, Fang; Yang, Jie-xia; Li, Ru; Chen, Yang-yi; Luo, Dong-hong; Zhang, Yong-ling; Ou, Yan-mei; Li, Jian; Wu, Jing; Mai, Ming-qin; Hou, Rui; Wu, Frances; Luo, Hongrong; Li, Dong-zhi; Liu, Hai-liang; Zhang, Xiao-zhuang; Zhang, Kang

2014-01-01

Massively parallel sequencing (MPS) of cell-free fetal DNA from maternal plasma has revolutionized our ability to perform noninvasive prenatal diagnosis. This approach avoids the risk of fetal loss associated with more invasive diagnostic procedures. The present study developed an effective method for noninvasive prenatal diagnosis of common chromosomal aneuploidies using a benchtop semiconductor sequencing platform (SSP), which relies on the MPS platform but offers advantages over existing noninvasive screening techniques. A total of 2,275 pregnant subjects was included in the study; of these, 515 subjects who had full karyotyping results were used in a retrospective analysis, and 1,760 subjects without karyotyping were analyzed in a prospective study. In the retrospective study, all 55 fetal trisomy 21 cases were identified using the SSP with a sensitivity and specificity of 99.94% and 99.46%, respectively. The SSP also detected 16 trisomy 18 cases with 100% sensitivity and 99.24% specificity and 3 trisomy 13 cases with 100% sensitivity and 100% specificity. Furthermore, 15 fetuses with sex chromosome aneuploidies (10 45,X, 2 47,XYY, 2 47,XXX, and 1 47,XXY) were detected. In the prospective study, nine fetuses with trisomy 21, three with trisomy 18, three with trisomy 13, and one with 45,X were detected. To our knowledge, this is the first large-scale clinical study to systematically identify chromosomal aneuploidies based on cell-free fetal DNA using the SSP and provides an effective strategy for large-scale noninvasive screening for chromosomal aneuploidies in a clinical setting. PMID:24799683

The effect of curriculum changes and instructional techniques on science-reasoning skills among high school students

NASA Astrophysics Data System (ADS)

Newman, Joan T.

Any change, particularly on a large scale like a sequence change in a district with 75,000 students, is difficult. However, with the advent of the new TAKS science test and the new requirements for high school graduation in the state of Texas, educators and students alike are engaged in innovative educational approaches to meet these requirements. This study investigated a different, non-traditional science sequence to investigate relationships among secondary core-science course sequencing, student science-reasoning performance, and classroom pedagogy. The methodology adopted in the study led to a deeper understanding of the successes and challenges faced by teachers in teaching conceptual physics and chemistry to 8 th and 9th grade students. The qualitative analysis suggested a difference in pedagogy employed by middle and high school science teachers and a need for secondary science teachers to enhance their content knowledge and pedagogical skills, as well as change their underlying attitudes and beliefs about the abilities of students. The study examined scores of 495 randomly chosen students following three different matriculation patterns within one large independent school district. The study indicated that students who follow a sequence with 9th grade IPC generally increase their science-reasoning skills as demonstrated on the 10th grade TAKS science test when these scores are compared with those of students who do not have 9th grade IPC in the science sequence.

DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

PubMed

You, Ronghui; Huang, Xiaodi; Zhu, Shanfeng

2018-06-06

As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to reduce this huge gap becomes increasingly important. The previous studies conclude that sequence homology based methods are highly effective in AFP. In addition, mining motif, domain, and functional information from protein sequences has been found very helpful for AFP. Other than sequences, alternative information sources such as text, however, may be useful for AFP as well. Instead of using BOW (bag of words) representation in traditional text-based AFP, we propose a new method called DeepText2GO that relies on deep semantic text representation, together with different kinds of available protein information such as sequence homology, families, domains, and motifs, to improve large-scale AFP. Furthermore, DeepText2GO integrates text-based methods with sequence-based ones by means of a consensus approach. Extensive experiments on the benchmark dataset extracted from UniProt/SwissProt have demonstrated that DeepText2GO significantly outperformed both text-based and sequence-based methods, validating its superiority. Copyright © 2018 Elsevier Inc. 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.

Insights into Hox protein function from a large scale combinatorial analysis of protein domains.

PubMed

Merabet, Samir; Litim-Mecheri, Isma; Karlsson, Daniel; Dixit, Richa; Saadaoui, Mehdi; Monier, Bruno; Brun, Christine; Thor, Stefan; Vijayraghavan, K; Perrin, Laurent; Pradel, Jacques; Graba, Yacine

2011-10-01

Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA), we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences.

Insights into Hox Protein Function from a Large Scale Combinatorial Analysis of Protein Domains

PubMed Central

Karlsson, Daniel; Dixit, Richa; Saadaoui, Mehdi; Monier, Bruno; Brun, Christine; Thor, Stefan; Vijayraghavan, K.; Perrin, Laurent; Pradel, Jacques; Graba, Yacine

2011-01-01

Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA), we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences. PMID:22046139

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

A confidence interval analysis of sampling effort, sequencing depth, and taxonomic resolution of fungal community ecology in the era of high-throughput sequencing.

PubMed

Oono, Ryoko

2017-01-01

High-throughput sequencing technology has helped microbial community ecologists explore ecological and evolutionary patterns at unprecedented scales. The benefits of a large sample size still typically outweigh that of greater sequencing depths per sample for accurate estimations of ecological inferences. However, excluding or not sequencing rare taxa may mislead the answers to the questions 'how and why are communities different?' This study evaluates the confidence intervals of ecological inferences from high-throughput sequencing data of foliar fungal endophytes as case studies through a range of sampling efforts, sequencing depths, and taxonomic resolutions to understand how technical and analytical practices may affect our interpretations. Increasing sampling size reliably decreased confidence intervals across multiple community comparisons. However, the effects of sequencing depths on confidence intervals depended on how rare taxa influenced the dissimilarity estimates among communities and did not significantly decrease confidence intervals for all community comparisons. A comparison of simulated communities under random drift suggests that sequencing depths are important in estimating dissimilarities between microbial communities under neutral selective processes. Confidence interval analyses reveal important biases as well as biological trends in microbial community studies that otherwise may be ignored when communities are only compared for statistically significant differences.

A confidence interval analysis of sampling effort, sequencing depth, and taxonomic resolution of fungal community ecology in the era of high-throughput sequencing

PubMed Central

2017-01-01

High-throughput sequencing technology has helped microbial community ecologists explore ecological and evolutionary patterns at unprecedented scales. The benefits of a large sample size still typically outweigh that of greater sequencing depths per sample for accurate estimations of ecological inferences. However, excluding or not sequencing rare taxa may mislead the answers to the questions ‘how and why are communities different?’ This study evaluates the confidence intervals of ecological inferences from high-throughput sequencing data of foliar fungal endophytes as case studies through a range of sampling efforts, sequencing depths, and taxonomic resolutions to understand how technical and analytical practices may affect our interpretations. Increasing sampling size reliably decreased confidence intervals across multiple community comparisons. However, the effects of sequencing depths on confidence intervals depended on how rare taxa influenced the dissimilarity estimates among communities and did not significantly decrease confidence intervals for all community comparisons. A comparison of simulated communities under random drift suggests that sequencing depths are important in estimating dissimilarities between microbial communities under neutral selective processes. Confidence interval analyses reveal important biases as well as biological trends in microbial community studies that otherwise may be ignored when communities are only compared for statistically significant differences. PMID:29253889

Diversity of Functionally Permissive Sequences in the Receptor-Binding Site of Influenza Hemagglutinin.

PubMed

Wu, Nicholas C; Xie, Jia; Zheng, Tianqing; Nycholat, Corwin M; Grande, Geramie; Paulson, James C; Lerner, Richard A; Wilson, Ian A

2017-06-14

Influenza A virus hemagglutinin (HA) initiates viral entry by engaging host receptor sialylated glycans via its receptor-binding site (RBS). The amino acid sequence of the RBS naturally varies across avian and human influenza virus subtypes and is also evolvable. However, functional sequence diversity in the RBS has not been fully explored. Here, we performed a large-scale mutational analysis of the RBS of A/WSN/33 (H1N1) and A/Hong Kong/1/1968 (H3N2) HAs. Many replication-competent mutants not yet observed in nature were identified, including some that could escape from an RBS-targeted broadly neutralizing antibody. This functional sequence diversity is made possible by pervasive epistasis in the RBS 220-loop and can be buffered by avidity in viral receptor binding. Overall, our study reveals that the HA RBS can accommodate a much greater range of sequence diversity than previously thought, which has significant implications for the complex evolutionary interrelationships between receptor specificity and immune escape. Copyright © 2017 Elsevier Inc. All rights reserved.

Using GenBank.

PubMed

Wheeler, David

2007-01-01

GenBank(R) is a comprehensive database of publicly available DNA sequences for more than 205,000 named organisms and for more than 60,000 within the embryophyta, obtained through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Daily data exchange with the European Molecular Biology Laboratory (EMBL) in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the National Center for Biotechnology Information (NCBI) retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases with taxonomy, genome, mapping, protein structure, and domain information and the biomedical journal literature through PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available through FTP. GenBank usage scenarios ranging from local analyses of the data available through FTP to online analyses supported by the NCBI Web-based tools are discussed. To access GenBank and its related retrieval and analysis services, go to the NCBI Homepage at http://www.ncbi.nlm.nih.gov.

GenBank.

PubMed

Benson, Dennis A; Karsch-Mizrachi, Ilene; Lipman, David J; Ostell, James; Sayers, Eric W

2011-01-01

GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 380,000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system that integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.

Scaling effects in the static and dynamic response of graphite-epoxy beam-columns. Ph.D. Thesis - Virginia Polytechnic Inst. and State Univ.

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

1990-01-01

Scale model technology represents one method of investigating the behavior of advanced, weight-efficient composite structures under a variety of loading conditions. It is necessary, however, to understand the limitations involved in testing scale model structures before the technique can be fully utilized. These limitations, or scaling effects, are characterized. in the large deflection response and failure of composite beams. Scale model beams were loaded with an eccentric axial compressive load designed to produce large bending deflections and global failure. A dimensional analysis was performed on the composite beam-column loading configuration to determine a model law governing the system response. An experimental program was developed to validate the model law under both static and dynamic loading conditions. Laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic were tested to examine a diversity of composite response and failure modes. The model beams were loaded under scaled test conditions until catastrophic failure. A large deflection beam solution was developed to compare with the static experimental results and to analyze beam failure. Also, the finite element code DYCAST (DYnamic Crash Analysis of STructure) was used to model both the static and impulsive beam response. Static test results indicate that the unidirectional and cross ply beam responses scale as predicted by the model law, even under severe deformations. In general, failure modes were consistent between scale models within a laminate family; however, a significant scale effect was observed in strength. The scale effect in strength which was evident in the static tests was also observed in the dynamic tests. Scaling of load and strain time histories between the scale model beams and the prototypes was excellent for the unidirectional beams, but inconsistent results were obtained for the angle ply, cross ply, and quasi-isotropic beams. Results show that valuable information can be obtained from testing on scale model composite structures, especially in the linear elastic response region. However, due to scaling effects in the strength behavior of composite laminates, caution must be used in extrapolating data taken from a scale model test when that test involves failure of the structure.

Transcriptome Analysis of the Differentially Expressed Genes in the Male and Female Shrub Willows (Salix suchowensis)

PubMed Central

Liu, Jingjing; Yin, Tongming; Ye, Ning; Chen, Yingnan; Yin, Tingting; Liu, Min; Hassani, Danial

2013-01-01

Background The dioecious system is relatively rare in plants. Shrub willow is an annual flowering dioecious woody plant, and possesses many characteristics that lend it as a great model for tracking the missing pieces of sex determination evolution. To gain a global view of the genes differentially expressed in the male and female shrub willows and to develop a database for further studies, we performed a large-scale transcriptome sequencing of flower buds which were separately collected from two types of sexes. Results Totally, 1,201,931 high quality reads were obtained, with an average length of 389 bp and a total length of 467.96 Mb. The ESTs were assembled into 29,048 contigs, and 132,709 singletons. These unigenes were further functionally annotated by comparing their sequences to different proteins and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 291 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified 806 differentially expressed genes between the male and female flower buds. And 33 of them located on the incipient sex chromosome of Salicaceae, among which, 12 genes might involve in plant sex determination empirically. These genes were worthy of special notification in future studies. Conclusions In this study, a large number of EST sequences were generated from the flower buds of a male and a female shrub willow. We also reported the differentially expressed genes between the two sex-type flowers. This work provides valuable information and sequence resources for uncovering the sex determining genes and for future functional genomics analysis of Salicaceae spp. PMID:23560075

Phase stability analysis of chirp evoked auditory brainstem responses by Gabor frame operators.

PubMed

Corona-Strauss, Farah I; Delb, Wolfgang; Schick, Bernhard; Strauss, Daniel J

2009-12-01

We have recently shown that click evoked auditory brainstem responses (ABRs) can be efficiently processed using a novelty detection paradigm. Here, ABRs as a large-scale reflection of a stimulus locked neuronal group synchronization at the brainstem level are detected as novel instance-novel as compared to the spontaneous activity which does not exhibit a regular stimulus locked synchronization. In this paper we propose for the first time Gabor frame operators as an efficient feature extraction technique for ABR single sweep sequences that is in line with this paradigm. In particular, we use this decomposition technique to derive the Gabor frame phase stability (GFPS) of sweep sequences of click and chirp evoked ABRs. We show that the GFPS of chirp evoked ABRs provides a stable discrimination of the spontaneous activity from stimulations above the hearing threshold with a small number of sweeps, even at low stimulation intensities. It is concluded that the GFPS analysis represents a robust feature extraction method for ABR single sweep sequences. Further studies are necessary to evaluate the value of the presented approach for clinical applications.

Genes mirror geography in Daphnia magna.

PubMed

Fields, Peter D; Reisser, Céline; Dukić, Marinela; Haag, Christoph R; Ebert, Dieter

2015-09-01

Identifying the presence and magnitude of population genetic structure remains a major consideration in evolutionary biology as doing so allows one to understand the demographic history of a species as well as make predictions of how the evolutionary process will proceed. Next-generation sequencing methods allow us to reconsider previous ideas and conclusions concerning the distribution of genetic variation, and what this distribution implies about a given species evolutionary history. A previous phylogeographic study of the crustacean Daphnia magna suggested that, despite strong genetic differentiation among populations at a local scale, the species shows only moderate genetic structure across its European range, with a spatially patchy occurrence of individual lineages. We apply RAD sequencing to a sample of D. magna collected across a wide swath of the species' Eurasian range and analyse the data using principle component analysis (PCA) of genetic variation and Procrustes analytical approaches, to quantify spatial genetic structure. We find remarkable consistency between the first two PCA axes and the geographic coordinates of individual sampling points, suggesting that, on a continent-wide scale, genetic differentiation is driven to a large extent by geographic distance. The observed pattern is consistent with unimpeded (i.e. no barriers, landscape or otherwise) migration at large spatial scales, despite the fragmented and patchy nature of favourable habitats at local scales. With high-resolution genetic data similar patterns may be uncovered for other species with wide geographic distributions, allowing an increased understanding of how genetic drift and selection have shaped their evolutionary history. © 2015 John Wiley & Sons Ltd.

Transcriptome sequencing and annotation of the halophytic microalga Dunaliella salina * #

PubMed Central

Hong, Ling; Liu, Jun-li; Midoun, Samira Z.; Miller, Philip C.

2017-01-01

The unicellular green alga Dunaliella salina is well adapted to salt stress and contains compounds (including β-carotene and vitamins) with potential commercial value. A large transcriptome database of D. salina during the adjustment, exponential and stationary growth phases was generated using a high throughput sequencing platform. We characterized the metabolic processes in D. salina with a focus on valuable metabolites, with the aim of manipulating D. salina to achieve greater economic value in large-scale production through a bioengineering strategy. Gene expression profiles under salt stress verified using quantitative polymerase chain reaction (qPCR) implied that salt can regulate the expression of key genes. This study generated a substantial fraction of D. salina transcriptional sequences for the entire growth cycle, providing a basis for the discovery of novel genes. This first full-scale transcriptome study of D. salina establishes a foundation for further comparative genomic studies. PMID:28990374

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

A pipeline for the de novo assembly of the Themira biloba (Sepsidae: Diptera) transcriptome using a multiple k-mer length approach.

PubMed

Melicher, Dacotah; Torson, Alex S; Dworkin, Ian; Bowsher, Julia H

2014-03-12

The Sepsidae family of flies is a model for investigating how sexual selection shapes courtship and sexual dimorphism in a comparative framework. However, like many non-model systems, there are few molecular resources available. Large-scale sequencing and assembly have not been performed in any sepsid, and the lack of a closely related genome makes investigation of gene expression challenging. Our goal was to develop an automated pipeline for de novo transcriptome assembly, and to use that pipeline to assemble and analyze the transcriptome of the sepsid Themira biloba. Our bioinformatics pipeline uses cloud computing services to assemble and analyze the transcriptome with off-site data management, processing, and backup. It uses a multiple k-mer length approach combined with a second meta-assembly to extend transcripts and recover more bases of transcript sequences than standard single k-mer assembly. We used 454 sequencing to generate 1.48 million reads from cDNA generated from embryo, larva, and pupae of T. biloba and assembled a transcriptome consisting of 24,495 contigs. Annotation identified 16,705 transcripts, including those involved in embryogenesis and limb patterning. We assembled transcriptomes from an additional three non-model organisms to demonstrate that our pipeline assembled a higher-quality transcriptome than single k-mer approaches across multiple species. The pipeline we have developed for assembly and analysis increases contig length, recovers unique transcripts, and assembles more base pairs than other methods through the use of a meta-assembly. The T. biloba transcriptome is a critical resource for performing large-scale RNA-Seq investigations of gene expression patterns, and is the first transcriptome sequenced in this Dipteran family.

The autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders.

PubMed

Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Lehner, Thomas; Roeder, Kathryn; State, Matthew W

2012-12-20

Research during the past decade has seen significant progress in the understanding of the genetic architecture of autism spectrum disorders (ASDs), with gene discovery accelerating as the characterization of genomic variation has become increasingly comprehensive. At the same time, this research has highlighted ongoing challenges. Here we address the enormous impact of high-throughput sequencing (HTS) on ASD gene discovery, outline a consensus view for leveraging this technology, and describe a large multisite collaboration developed to accomplish these goals. Similar approaches could prove effective for severe neurodevelopmental disorders more broadly. Copyright © 2012 Elsevier Inc. All rights reserved.

(New hosts and vectors for genome cloning)

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

Not Available

The main goal of our project remains the development of new bacterial hosts and vectors for the stable propagation of human DNA clones in E. coli. During the past six months of our current budget period, we have (1) continued to develop new hosts that permit the stable maintenance of unstable features of human DNA, and (2) developed a series of vectors for (a) cloning large DNA inserts, (b) assessing the frequency of human sequences that are lethal to the growth of E. coli, and (c) assessing the stability of human sequences cloned in M13 for large-scale sequencing projects.

[New hosts and vectors for genome cloning]. Progress report

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

Not Available

The main goal of our project remains the development of new bacterial hosts and vectors for the stable propagation of human DNA clones in E. coli. During the past six months of our current budget period, we have (1) continued to develop new hosts that permit the stable maintenance of unstable features of human DNA, and (2) developed a series of vectors for (a) cloning large DNA inserts, (b) assessing the frequency of human sequences that are lethal to the growth of E. coli, and (c) assessing the stability of human sequences cloned in M13 for large-scale sequencing projects.

MEMOSys: Bioinformatics platform for genome-scale metabolic models

PubMed Central

2011-01-01

Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys. PMID:21276275

Transcriptome analysis of carnation (Dianthus caryophyllus L.) based on next-generation sequencing technology.

PubMed

Tanase, Koji; Nishitani, Chikako; Hirakawa, Hideki; Isobe, Sachiko; Tabata, Satoshi; Ohmiya, Akemi; Onozaki, Takashi

2012-07-02

Carnation (Dianthus caryophyllus L.), in the family Caryophyllaceae, can be found in a wide range of colors and is a model system for studies of flower senescence. In addition, it is one of the most important flowers in the global floriculture industry. However, few genomics resources, such as sequences and markers are available for carnation or other members of the Caryophyllaceae. To increase our understanding of the genetic control of important characters in carnation, we generated an expressed sequence tag (EST) database for a carnation cultivar important in horticulture by high-throughput sequencing using 454 pyrosequencing technology. We constructed a normalized cDNA library and a 3'-UTR library of carnation, obtaining a total of 1,162,126 high-quality reads. These reads were assembled into 300,740 unigenes consisting of 37,844 contigs and 262,896 singlets. The contigs were searched against an Arabidopsis sequence database, and 61.8% (23,380) of them had at least one BLASTX hit. These contigs were also annotated with Gene Ontology (GO) and were found to cover a broad range of GO categories. Furthermore, we identified 17,362 potential simple sequence repeats (SSRs) in 14,291 of the unigenes. We focused on gene discovery in the areas of flower color and ethylene biosynthesis. Transcripts were identified for almost every gene involved in flower chlorophyll and carotenoid metabolism and in anthocyanin biosynthesis. Transcripts were also identified for every step in the ethylene biosynthesis pathway. We present the first large-scale sequence data set for carnation, generated using next-generation sequencing technology. The large EST database generated from these sequences is an informative resource for identifying genes involved in various biological processes in carnation and provides an EST resource for understanding the genetic diversity of this plant.

Transcriptome analysis of carnation (Dianthus caryophyllus L.) based on next-generation sequencing technology

PubMed Central

2012-01-01

Background Carnation (Dianthus caryophyllus L.), in the family Caryophyllaceae, can be found in a wide range of colors and is a model system for studies of flower senescence. In addition, it is one of the most important flowers in the global floriculture industry. However, few genomics resources, such as sequences and markers are available for carnation or other members of the Caryophyllaceae. To increase our understanding of the genetic control of important characters in carnation, we generated an expressed sequence tag (EST) database for a carnation cultivar important in horticulture by high-throughput sequencing using 454 pyrosequencing technology. Results We constructed a normalized cDNA library and a 3’-UTR library of carnation, obtaining a total of 1,162,126 high-quality reads. These reads were assembled into 300,740 unigenes consisting of 37,844 contigs and 262,896 singlets. The contigs were searched against an Arabidopsis sequence database, and 61.8% (23,380) of them had at least one BLASTX hit. These contigs were also annotated with Gene Ontology (GO) and were found to cover a broad range of GO categories. Furthermore, we identified 17,362 potential simple sequence repeats (SSRs) in 14,291 of the unigenes. We focused on gene discovery in the areas of flower color and ethylene biosynthesis. Transcripts were identified for almost every gene involved in flower chlorophyll and carotenoid metabolism and in anthocyanin biosynthesis. Transcripts were also identified for every step in the ethylene biosynthesis pathway. Conclusions We present the first large-scale sequence data set for carnation, generated using next-generation sequencing technology. The large EST database generated from these sequences is an informative resource for identifying genes involved in various biological processes in carnation and provides an EST resource for understanding the genetic diversity of this plant. PMID:22747974

Visual management of large scale data mining projects.

PubMed

Shah, I; Hunter, L

2000-01-01

This paper describes a unified framework for visualizing the preparations for, and results of, hundreds of machine learning experiments. These experiments were designed to improve the accuracy of enzyme functional predictions from sequence, and in many cases were successful. Our system provides graphical user interfaces for defining and exploring training datasets and various representational alternatives, for inspecting the hypotheses induced by various types of learning algorithms, for visualizing the global results, and for inspecting in detail results for specific training sets (functions) and examples (proteins). The visualization tools serve as a navigational aid through a large amount of sequence data and induced knowledge. They provided significant help in understanding both the significance and the underlying biological explanations of our successes and failures. Using these visualizations it was possible to efficiently identify weaknesses of the modular sequence representations and induction algorithms which suggest better learning strategies. The context in which our data mining visualization toolkit was developed was the problem of accurately predicting enzyme function from protein sequence data. Previous work demonstrated that approximately 6% of enzyme protein sequences are likely to be assigned incorrect functions on the basis of sequence similarity alone. In order to test the hypothesis that more detailed sequence analysis using machine learning techniques and modular domain representations could address many of these failures, we designed a series of more than 250 experiments using information-theoretic decision tree induction and naive Bayesian learning on local sequence domain representations of problematic enzyme function classes. In more than half of these cases, our methods were able to perfectly discriminate among various possible functions of similar sequences. We developed and tested our visualization techniques on this application.

[Genome-scale sequence data processing and epigenetic analysis of DNA methylation].

PubMed

Wang, Ting-Zhang; Shan, Gao; Xu, Jian-Hong; Xue, Qing-Zhong

2013-06-01

A new approach recently developed for detecting cytosine DNA methylation (mC) and analyzing the genome-scale DNA methylation profiling, is called BS-Seq which is based on bisulfite conversion of genomic DNA combined with next-generation sequencing. The method can not only provide an insight into the difference of genome-scale DNA methylation among different organisms, but also reveal the conservation of DNA methylation in all contexts and nucleotide preference for different genomic regions, including genes, exons, and repetitive DNA sequences. It will be helpful to under-stand the epigenetic impacts of cytosine DNA methylation on the regulation of gene expression and maintaining silence of repetitive sequences, such as transposable elements. In this paper, we introduce the preprocessing steps of DNA methylation data, by which cytosine (C) and guanine (G) in the reference sequence are transferred to thymine (T) and adenine (A), and cytosine in reads is transferred to thymine, respectively. We also comprehensively review the main content of the DNA methylation analysis on the genomic scale: (1) the cytosine methylation under the context of different sequences; (2) the distribution of genomic methylcytosine; (3) DNA methylation context and the preference for the nucleotides; (4) DNA- protein interaction sites of DNA methylation; (5) degree of methylation of cytosine in the different structural elements of genes. DNA methylation analysis technique provides a powerful tool for the epigenome study in human and other species, and genes and environment interaction, and founds the theoretical basis for further development of disease diagnostics and therapeutics in human.

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

PubMed Central

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

2015-01-01

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

Resources for Genetic and Genomic Analysis of Emerging Pathogen Acinetobacter baumannii

PubMed Central

Ramage, Elizabeth; Weiss, Eli J.; Radey, Matthew; Hayden, Hillary S.; Held, Kiara G.; Huse, Holly K.; Zurawski, Daniel V.; Brittnacher, Mitchell J.; Manoil, Colin

2015-01-01

ABSTRACT Acinetobacter baumannii is a Gram-negative bacterial pathogen notorious for causing serious nosocomial infections that resist antibiotic therapy. Research to identify factors responsible for the pathogen's success has been limited by the resources available for genome-scale experimental studies. This report describes the development of several such resources for A. baumannii strain AB5075, a recently characterized wound isolate that is multidrug resistant and displays robust virulence in animal models. We report the completion and annotation of the genome sequence, the construction of a comprehensive ordered transposon mutant library, the extension of high-coverage transposon mutant pool sequencing (Tn-seq) to the strain, and the identification of the genes essential for growth on nutrient-rich agar. These resources should facilitate large-scale genetic analysis of virulence, resistance, and other clinically relevant traits that make A. baumannii a formidable public health threat. IMPORTANCE Acinetobacter baumannii is one of six bacterial pathogens primarily responsible for antibiotic-resistant infections that have become the scourge of health care facilities worldwide. Eliminating such infections requires a deeper understanding of the factors that enable the pathogen to persist in hospital environments, establish infections, and resist antibiotics. We present a set of resources that should accelerate genome-scale genetic characterization of these traits for a reference isolate of A. baumannii that is highly virulent and representative of current outbreak strains. PMID:25845845

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects.

PubMed

Dereeper, Alexis; Nicolas, Stéphane; Le Cunff, Loïc; Bacilieri, Roberto; Doligez, Agnès; Peros, Jean-Pierre; Ruiz, Manuel; This, Patrice

2011-05-05

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data. In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats. Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.SNiPlay is available at: http://sniplay.cirad.fr/.

Network Analysis of Sequence-Function Relationships and Exploration of Sequence Space of TEM β-Lactamases.

PubMed

Zeil, Catharina; Widmann, Michael; Fademrecht, Silvia; Vogel, Constantin; Pleiss, Jürgen

2016-05-01

The Lactamase Engineering Database (www.LacED.uni-stuttgart.de) was developed to facilitate the classification and analysis of TEM β-lactamases. The current version contains 474 TEM variants. Two hundred fifty-nine variants form a large scale-free network of highly connected point mutants. The network was divided into three subnetworks which were enriched by single phenotypes: one network with predominantly 2be and two networks with 2br phenotypes. Fifteen positions were found to be highly variable, contributing to the majority of the observed variants. Since it is expected that a considerable fraction of the theoretical sequence space is functional, the currently sequenced 474 variants represent only the tip of the iceberg of functional TEM β-lactamase variants which form a huge natural reservoir of highly interconnected variants. Almost 50% of the variants are part of a quartet. Thus, two single mutations that result in functional enzymes can be combined into a functional protein. Most of these quartets consist of the same phenotype, or the mutations are additive with respect to the phenotype. By predicting quartets from triplets, 3,916 unknown variants were constructed. Eighty-seven variants complement multiple quartets and therefore have a high probability of being functional. The construction of a TEM β-lactamase network and subsequent analyses by clustering and quartet prediction are valuable tools to gain new insights into the viable sequence space of TEM β-lactamases and to predict their phenotype. The highly connected sequence space of TEM β-lactamases is ideally suited to network analysis and demonstrates the strengths of network analysis over tree reconstruction methods. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.

PubMed

Crow, Megan; Paul, Anirban; Ballouz, Sara; Huang, Z Josh; Gillis, Jesse

2018-02-28

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.

Googling DNA sequences on the World Wide Web.

PubMed

Hajibabaei, Mehrdad; Singer, Gregory A C

2009-11-10

New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available for analyzing DNA sequence information, conventional web-based tools have not been utilized for bioinformatics applications. We have developed a novel algorithm and implemented it for searching species-specific genomic sequences, DNA barcodes, by using popular web-based methods such as Google. We developed an alignment independent character based algorithm based on dividing a sequence library (DNA barcodes) and query sequence to words. The actual search is conducted by conventional search tools such as freely available Google Desktop Search. We implemented our algorithm in two exemplar packages. We developed pre and post-processing software to provide customized input and output services, respectively. Our analysis of all publicly available DNA barcode sequences shows a high accuracy as well as rapid results. Our method makes use of conventional web-based technologies for specialized genetic data. It provides a robust and efficient solution for sequence search on the web. The integration of our search method for large-scale sequence libraries such as DNA barcodes provides an excellent web-based tool for accessing this information and linking it to other available categories of information on the web.

NG6: Integrated next generation sequencing storage and processing environment.

PubMed

Mariette, Jérôme; Escudié, Frédéric; Allias, Nicolas; Salin, Gérald; Noirot, Céline; Thomas, Sylvain; Klopp, Christophe

2012-09-09

Next generation sequencing platforms are now well implanted in sequencing centres and some laboratories. Upcoming smaller scale machines such as the 454 junior from Roche or the MiSeq from Illumina will increase the number of laboratories hosting a sequencer. In such a context, it is important to provide these teams with an easily manageable environment to store and process the produced reads. We describe a user-friendly information system able to manage large sets of sequencing data. It includes, on one hand, a workflow environment already containing pipelines adapted to different input formats (sff, fasta, fastq and qseq), different sequencers (Roche 454, Illumina HiSeq) and various analyses (quality control, assembly, alignment, diversity studies,…) and, on the other hand, a secured web site giving access to the results. The connected user will be able to download raw and processed data and browse through the analysis result statistics. The provided workflows can easily be modified or extended and new ones can be added. Ergatis is used as a workflow building, running and monitoring system. The analyses can be run locally or in a cluster environment using Sun Grid Engine. NG6 is a complete information system designed to answer the needs of a sequencing platform. It provides a user-friendly interface to process, store and download high-throughput sequencing data.

Sequence stratigraphic analysis of Cenomanian greenhouse palaeosols: A case study from southern Patagonia, Argentina

NASA Astrophysics Data System (ADS)

Varela, Augusto N.; Veiga, Gonzalo D.; Poiré, Daniel G.

2012-10-01

The aim of this contribution is to analyse extrinsic (i.e., tectonics, climate and eustasy) and intrinsic (i.e., palaeotopography, palaeodrainage and relative sedimentation rates) factors that controlled palaeosol development in the Cenomanian Mata Amarilla Formation (Austral foreland basin, southwestern Patagonia, Argentina). Detailed sedimentological logs, facies analysis, pedofeatures and palaeosol horizon identification led to the definition of six pedotypes, which represent Histosols, acid sulphate Histosols, Vertisols, hydromorphic Vertisols, Inceptisols and vertic Alfisols. Small- and large-scale changes in palaeosol development were recognised throughout the units. Small-scale or high-frequency variations, identified within the middle section are represented by the lateral and vertical superimposition of Inceptisols, Vertisols and hydromorphic Vertisols. Lateral changes are interpreted as the result of intrinsic factors to the depositional systems, such as the relative position within the floodplain and the distance from the main channels, that condition the nature of parent material, the sedimentation rate and eventually the palaeotopographic position. Vertical stacking of different soil types is linked to avulsion processes and the relatively abrupt change in the distance to main channels as the system aggraded. The large-scale or low-frequency vertical variations in palaeosol type occurring in the Mata Amarilla Formation are related to long-term changes in depositional environments. The lower and upper sections of the studied logs are characterised by Histosols and acid sulphate Histosols, and few hydromorphic Vertisols associated with low-gradient coastal environments (i.e., lagoons, estuaries and distal fluvial systems). At the lower boundary of the middle section, a thick palaeosol succession composed of vertic Alfisols occurs. The rest of the middle section is characterised by Vertisols, hydromorphic Vertisols and Inceptisols occurring on distal and proximal fluvial floodplains, respectively. The palaeosol succession for the Mata Amarilla Formation can be analysed within a sequence stratigraphic scheme considering changes in depositional environments in relation to accommodation/supply conditions. The results contrast with classical models, mainly in that the palaeosols of the Mata Amarilla Formation are relatively well-developed throughout the whole sequence, including transgressive periods of relatively high aggradation rate. Also, even when during regressive episodes, when a thick palaeosol succession that marks the sequence boundary is developed in the classical models, the lack of incised valleys in this succession led to the preservation of thick palaeosol successions during lowstand conditions. The vertical and lateral palaeosol distribution identified in the Mata Amarilla Formation could be eventually extrapolated to other sequences deposited during climate optimums.

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

PubMed Central

Etheridge, Alton; Sakhanenko, Nikita; Galas, David

2017-01-01

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

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

PubMed

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

2016-01-01

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

Sequence Determines Degree of Knottedness in a Coarse-Grained Protein Model

NASA Astrophysics Data System (ADS)

Wüst, Thomas; Reith, Daniel; Virnau, Peter

2015-01-01

Knots are abundant in globular homopolymers but rare in globular proteins. To shed new light on this long-standing conundrum, we study the influence of sequence on the formation of knots in proteins under native conditions within the framework of the hydrophobic-polar lattice protein model. By employing large-scale Wang-Landau simulations combined with suitable Monte Carlo trial moves we show that even though knots are still abundant on average, sequence introduces large variability in the degree of self-entanglements. Moreover, we are able to design sequences which are either almost always or almost never knotted. Our findings serve as proof of concept that the introduction of just one additional degree of freedom per monomer (in our case sequence) facilitates evolution towards a protein universe in which knots are rare.

Newborn Sequencing in Genomic Medicine and Public Health

PubMed Central

Agrawal, Pankaj B.; Bailey, Donald B.; Beggs, Alan H.; Brenner, Steven E.; Brower, Amy M.; Cakici, Julie A.; Ceyhan-Birsoy, Ozge; Chan, Kee; Chen, Flavia; Currier, Robert J.; Dukhovny, Dmitry; Green, Robert C.; Harris-Wai, Julie; Holm, Ingrid A.; Iglesias, Brenda; Joseph, Galen; Kingsmore, Stephen F.; Koenig, Barbara A.; Kwok, Pui-Yan; Lantos, John; Leeder, Steven J.; Lewis, Megan A.; McGuire, Amy L.; Milko, Laura V.; Mooney, Sean D.; Parad, Richard B.; Pereira, Stacey; Petrikin, Joshua; Powell, Bradford C.; Powell, Cynthia M.; Puck, Jennifer M.; Rehm, Heidi L.; Risch, Neil; Roche, Myra; Shieh, Joseph T.; Veeraraghavan, Narayanan; Watson, Michael S.; Willig, Laurel; Yu, Timothy W.; Urv, Tiina; Wise, Anastasia L.

2017-01-01

The rapid development of genomic sequencing technologies has decreased the cost of genetic analysis to the extent that it seems plausible that genome-scale sequencing could have widespread availability in pediatric care. Genomic sequencing provides a powerful diagnostic modality for patients who manifest symptoms of monogenic disease and an opportunity to detect health conditions before their development. However, many technical, clinical, ethical, and societal challenges should be addressed before such technology is widely deployed in pediatric practice. This article provides an overview of the Newborn Sequencing in Genomic Medicine and Public Health Consortium, which is investigating the application of genome-scale sequencing in newborns for both diagnosis and screening. PMID:28096516

RNA sequencing demonstrates large-scale temporal dysregulation of gene expression in stimulated macrophages derived from MHC-defined chicken haplotypes.

PubMed

Irizarry, Kristopher J L; Downs, Eileen; Bryden, Randall; Clark, Jory; Griggs, Lisa; Kopulos, Renee; Boettger, Cynthia M; Carr, Thomas J; Keeler, Calvin L; Collisson, Ellen; Drechsler, Yvonne

2017-01-01

Discovering genetic biomarkers associated with disease resistance and enhanced immunity is critical to developing advanced strategies for controlling viral and bacterial infections in different species. Macrophages, important cells of innate immunity, are directly involved in cellular interactions with pathogens, the release of cytokines activating other immune cells and antigen presentation to cells of the adaptive immune response. IFNγ is a potent activator of macrophages and increased production has been associated with disease resistance in several species. This study characterizes the molecular basis for dramatically different nitric oxide production and immune function between the B2 and the B19 haplotype chicken macrophages.A large-scale RNA sequencing approach was employed to sequence the RNA of purified macrophages from each haplotype group (B2 vs. B19) during differentiation and after stimulation. Our results demonstrate that a large number of genes exhibit divergent expression between B2 and B19 haplotype cells both prior and after stimulation. These differences in gene expression appear to be regulated by complex epigenetic mechanisms that need further investigation.

Environmental DNA sequencing primers for eutardigrades and bdelloid rotifers

PubMed Central

2009-01-01

Background The time it takes to isolate individuals from environmental samples and then extract DNA from each individual is one of the problems with generating molecular data from meiofauna such as eutardigrades and bdelloid rotifers. The lack of consistent morphological information and the extreme abundance of these classes makes morphological identification of rare, or even common cryptic taxa a large and unwieldy task. This limits the ability to perform large-scale surveys of the diversity of these organisms. Here we demonstrate a culture-independent molecular survey approach that enables the generation of large amounts of eutardigrade and bdelloid rotifer sequence data directly from soil. Our PCR primers, specific to the 18s small-subunit rRNA gene, were developed for both eutardigrades and bdelloid rotifers. Results The developed primers successfully amplified DNA of their target organism from various soil DNA extracts. This was confirmed by both the BLAST similarity searches and phylogenetic analyses. Tardigrades showed much better phylogenetic resolution than bdelloids. Both groups of organisms exhibited varying levels of endemism. Conclusion The development of clade-specific primers for characterizing eutardigrades and bdelloid rotifers from environmental samples should greatly increase our ability to characterize the composition of these taxa in environmental samples. Environmental sequencing as shown here differs from other molecular survey methods in that there is no need to pre-isolate the organisms of interest from soil in order to amplify their DNA. The DNA sequences obtained from methods that do not require culturing can be identified post-hoc and placed phylogenetically as additional closely related sequences are obtained from morphologically identified conspecifics. Our non-cultured environmental sequence based approach will be able to provide a rapid and large-scale screening of the presence, absence and diversity of Bdelloidea and Eutardigrada in a variety of soils. PMID:20003362

Cloud-based interactive analytics for terabytes of genomic variants data.

PubMed

Pan, Cuiping; McInnes, Gregory; Deflaux, Nicole; Snyder, Michael; Bingham, Jonathan; Datta, Somalee; Tsao, Philip S

2017-12-01

Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. cuiping@stanford.edu or ptsao@stanford.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

Cloud-based interactive analytics for terabytes of genomic variants data

PubMed Central

Pan, Cuiping; McInnes, Gregory; Deflaux, Nicole; Snyder, Michael; Bingham, Jonathan; Datta, Somalee; Tsao, Philip S

2017-01-01

Abstract Motivation Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. Results We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. Availability and implementation Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. Contact cuiping@stanford.edu or ptsao@stanford.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28961771

Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space

PubMed Central

2014-01-01

Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993

Characterization of the Kenaf (Hibiscus cannabinus) Global Transcriptome Using Illumina Paired-End Sequencing and Development of EST-SSR Markers

PubMed Central

Li, Hui; Li, Defang; Chen, Anguo; Tang, Huijuan; Li, Jianjun; Huang, Siqi

2016-01-01

Kenaf (Hibiscus cannabinus L.) is an economically important natural fiber crop grown worldwide. However, only 20 expressed tag sequences (ESTs) for kenaf are available in public databases. The aim of this study was to develop large-scale simple sequence repeat (SSR) markers to lay a solid foundation for the construction of genetic linkage maps and marker-assisted breeding in kenaf. We used Illumina paired-end sequencing technology to generate new EST-simple sequences and MISA software to mine SSR markers. We identified 71,318 unigenes with an average length of 1143 nt and annotated these unigenes using four different protein databases. Overall, 9324 complementary pairs were designated as EST-SSR markers, and their quality was validated using 100 randomly selected SSR markers. In total, 72 primer pairs reproducibly amplified target amplicons, and 61 of these primer pairs detected significant polymorphism among 28 kenaf accessions. Thus, in this study, we have developed large-scale SSR markers for kenaf, and this new resource will facilitate construction of genetic linkage maps, investigation of fiber growth and development in kenaf, and also be of value to novel gene discovery and functional genomic studies. PMID:26960153

Characterization of Integrons and Resistance Genes in Salmonella Isolates from Farm Animals in Shandong Province, China

PubMed Central

Zhao, Xiaonan; Yang, Jie; Zhang, Baozhen; Sun, Shuhong; Chang, Weishan

2017-01-01

A total of 154 non-duplicate Salmonella isolates were recovered from 1,105 rectal swabs collected from three large-scale chicken farms (78/325, 24.0%), three large-scale duck farms (56/600, 9.3%) and three large-scale pig farms (20/180, 11.1%) between April and July 2016. Seven serotypes were identified among the 154 isolates, with the most common serotype in chickens and ducks being Salmonella enteritidis and in pigs Salmonella typhimurium. Antimicrobial susceptibility testing revealed that high antimicrobial resistance rates were observed for tetracycline (72.0%) and ampicillin (69.4%) in all sources. Class 1 integrons were detected in 16.9% (26/154) of these isolates and contained gene cassettes aadA2, aadA1, drfA1-aadA1, drfA12-aadA2, and drfA17-aadA5. Three β-lactamase genes were detected among the 154 isolates, and most of the isolates carried blaTEM−1(55/154), followed by blaPSE−1(14/154) and blaCTX−M−55 (11/154). Three plasmid-mediated quinolone resistance genes were detected among the 154 isolates, and most of the isolates carried qnrA (113/154), followed by qnrB (99/154) and qnrS (10/154). Fifty-four isolates carried floR among the 154 isolates. Multilocus sequence typing (MLST) analysis showed that nine sequence types (STs) were identified; ST11 was the most frequent genotype in chickens and ducks, and ST19 was identified in pigs. Our findings indicated that Salmonella was widespread, and the overuse of antibiotics in animals should be reduced considerably in developing countries. PMID:28747906

Consolidation of glycosyl hydrolase family 30 : a dual domain 4/7 hydrolase family consisting of two structurally distinct groups

Treesearch

Franz J. St John; Javier M. Gonzalez; Edwin Pozharski

2010-01-01

In this work glycosyl hydrolase (GH) family 30 (GH30) is analyzed and shown to consist of its currently classified member sequences as well as several homologous sequence groups currently assigned within family GH5. A large scale amino acid sequence alignment and a phylogenetic tree were generated and GH30 groups and subgroups were designated. A partial rearrangement...

Draft Genome Sequences of 510 Listeria monocytogenes Strains from Food Isolates and Human Listeriosis Cases from Northern Italy.

PubMed

Lomonaco, Sara; Gallina, Silvia; Filipello, Virginia; Sanchez Leon, Maria; Kastanis, George John; Allard, Marc; Brown, Eric; Amato, Ettore; Pontello, Mirella; Decastelli, Lucia

2018-01-18

Listeriosis outbreaks are frequently multistate/multicountry outbreaks, underlining the importance of molecular typing data for several diverse and well-characterized isolates. Large-scale whole-genome sequencing studies on Listeria monocytogenes isolates from non-U.S. locations have been limited. Herein, we describe the draft genome sequences of 510 L. monocytogenes isolates from northern Italy from different sources.

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

OF THE PROBLEM AND CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0... DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 9 Figure 5: The flow of data in a DNA analysis system based on an...logarithmic scale and a linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits

XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.

PubMed

Yu, Yao; Hu, Hao; Bohlender, Ryan J; Hu, Fulan; Chen, Jiun-Sheng; Holt, Carson; Fowler, Jerry; Guthery, Stephen L; Scheet, Paul; Hildebrandt, Michelle A T; Yandell, Mark; Huff, Chad D

2018-04-06

High-throughput sequencing data are increasingly being made available to the research community for secondary analyses, providing new opportunities for large-scale association studies. However, heterogeneity in target capture and sequencing technologies often introduce strong technological stratification biases that overwhelm subtle signals of association in studies of complex traits. Here, we introduce the Cross-Platform Association Toolkit, XPAT, which provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets. XPAT includes tools to support cross-platform aware variant calling, quality control filtering, gene-based association testing and rare variant effect size estimation. To evaluate the performance of XPAT, we conducted case-control association studies for three diseases, including 783 breast cancer cases, 272 ovarian cancer cases, 205 Crohn disease cases and 3507 shared controls (including 1722 females) using sequencing data from multiple sources. XPAT greatly reduced Type I error inflation in the case-control analyses, while replicating many previously identified disease-gene associations. We also show that association tests conducted with XPAT using cross-platform data have comparable performance to tests using matched platform data. XPAT enables new association studies that combine existing sequencing datasets to identify genetic loci associated with common diseases and other complex traits.

Three-dimensional displays for natural hazards analysis, using classified Landsat Thematic Mapper digital data and large-scale digital elevation models

NASA Technical Reports Server (NTRS)

Butler, David R.; Walsh, Stephen J.; Brown, Daniel G.

1991-01-01

Methods are described for using Landsat Thematic Mapper digital data and digital elevation models for the display of natural hazard sites in a mountainous region of northwestern Montana, USA. Hazard zones can be easily identified on the three-dimensional images. Proximity of facilities such as highways and building locations to hazard sites can also be easily displayed. A temporal sequence of Landsat TM (or similar) satellite data sets could also be used to display landscape changes associated with dynamic natural hazard processes.

Regulatory sequence analysis tools.

PubMed

van Helden, Jacques

2003-07-01

The web resource Regulatory Sequence Analysis Tools (RSAT) (http://rsat.ulb.ac.be/rsat) offers a collection of software tools dedicated to the prediction of regulatory sites in non-coding DNA sequences. These tools include sequence retrieval, pattern discovery, pattern matching, genome-scale pattern matching, feature-map drawing, random sequence generation and other utilities. Alternative formats are supported for the representation of regulatory motifs (strings or position-specific scoring matrices) and several algorithms are proposed for pattern discovery. RSAT currently holds >100 fully sequenced genomes and these data are regularly updated from GenBank.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets.

PubMed

Shrimankar, D D; Sathe, S R

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today's supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets

PubMed Central

Shrimankar, D. D.; Sathe, S. R.

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today’s supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures. PMID:27932868

Low Cost, Scalable Proteomics Data Analysis Using Amazon's Cloud Computing Services and Open Source Search Algorithms

PubMed Central

Halligan, Brian D.; Geiger, Joey F.; Vallejos, Andrew K.; Greene, Andrew S.; Twigger, Simon N.

2009-01-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step by step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center website (http://proteomics.mcw.edu/vipdac). PMID:19358578

Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

PubMed

Halligan, Brian D; Geiger, Joey F; Vallejos, Andrew K; Greene, Andrew S; Twigger, Simon N

2009-06-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

An exploration of the sequence of a 2.9-Mb region of the genome of Drosophila melanogaster: the Adh region.

PubMed Central

Ashburner, M; Misra, S; Roote, J; Lewis, S E; Blazej, R; Davis, T; Doyle, C; Galle, R; George, R; Harris, N; Hartzell, G; Harvey, D; Hong, L; Houston, K; Hoskins, R; Johnson, G; Martin, C; Moshrefi, A; Palazzolo, M; Reese, M G; Spradling, A; Tsang, G; Wan, K; Whitelaw, K; Celniker, S

1999-01-01

A contiguous sequence of nearly 3 Mb from the genome of Drosophila melanogaster has been sequenced from a series of overlapping P1 and BAC clones. This region covers 69 chromosome polytene bands on chromosome arm 2L, including the genetically well-characterized "Adh region." A computational analysis of the sequence predicts 218 protein-coding genes, 11 tRNAs, and 17 transposable element sequences. At least 38 of the protein-coding genes are arranged in clusters of from 2 to 6 closely related genes, suggesting extensive tandem duplication. The gene density is one protein-coding gene every 13 kb; the transposable element density is one element every 171 kb. Of 73 genes in this region identified by genetic analysis, 49 have been located on the sequence; P-element insertions have been mapped to 43 genes. Ninety-five (44%) of the known and predicted genes match a Drosophila EST, and 144 (66%) have clear similarities to proteins in other organisms. Genes known to have mutant phenotypes are more likely to be represented in cDNA libraries, and far more likely to have products similar to proteins of other organisms, than are genes with no known mutant phenotype. Over 650 chromosome aberration breakpoints map to this chromosome region, and their nonrandom distribution on the genetic map reflects variation in gene spacing on the DNA. This is the first large-scale analysis of the genome of D. melanogaster at the sequence level. In addition to the direct results obtained, this analysis has allowed us to develop and test methods that will be needed to interpret the complete sequence of the genome of this species.Before beginning a Hunt, it is wise to ask someone what you are looking for before you begin looking for it. Milne 1926 PMID:10471707

Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing

PubMed Central

Hykin, Sarah M.; Bi, Ke; McGuire, Jimmy A.

2015-01-01

For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles), attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens—particularly for use in phylogenetic analyses—has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp). We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens available for genetic analysis. PMID:26505622

Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing.

PubMed

Hykin, Sarah M; Bi, Ke; McGuire, Jimmy A

2015-01-01

For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles), attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens-particularly for use in phylogenetic analyses-has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp). We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens available for genetic analysis.

A private DNA motif finding algorithm.

PubMed

Chen, Rui; Peng, Yun; Choi, Byron; Xu, Jianliang; Hu, Haibo

2014-08-01

With the increasing availability of genomic sequence data, numerous methods have been proposed for finding DNA motifs. The discovery of DNA motifs serves a critical step in many biological applications. However, the privacy implication of DNA analysis is normally neglected in the existing methods. In this work, we propose a private DNA motif finding algorithm in which a DNA owner's privacy is protected by a rigorous privacy model, known as ∊-differential privacy. It provides provable privacy guarantees that are independent of adversaries' background knowledge. Our algorithm makes use of the n-gram model and is optimized for processing large-scale DNA sequences. We evaluate the performance of our algorithm over real-life genomic data and demonstrate the promise of integrating privacy into DNA motif finding. Copyright © 2014 Elsevier Inc. All rights reserved.

Targeted Capture and High-Throughput Sequencing Using Molecular Inversion Probes (MIPs).

PubMed

Cantsilieris, Stuart; Stessman, Holly A; Shendure, Jay; Eichler, Evan E

2017-01-01

Molecular inversion probes (MIPs) in combination with massively parallel DNA sequencing represent a versatile, yet economical tool for targeted sequencing of genomic DNA. Several thousand genomic targets can be selectively captured using long oligonucleotides containing unique targeting arms and universal linkers. The ability to append sequencing adaptors and sample-specific barcodes allows large-scale pooling and subsequent high-throughput sequencing at relatively low cost per sample. Here, we describe a "wet bench" protocol detailing the capture and subsequent sequencing of >2000 genomic targets from 192 samples, representative of a single lane on the Illumina HiSeq 2000 platform.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

An investigation of Hebbian phase sequences as assembly graphs

PubMed Central

Almeida-Filho, Daniel G.; Lopes-dos-Santos, Vitor; Vasconcelos, Nivaldo A. P.; Miranda, José G. V.; Tort, Adriano B. L.; Ribeiro, Sidarta

2014-01-01

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition. PMID:24782715

Large-scale exploratory genetic analysis of cognitive impairment in Parkinson's disease.

PubMed

Mata, Ignacio F; Johnson, Catherine O; Leverenz, James B; Weintraub, Daniel; Trojanowski, John Q; Van Deerlin, Vivianna M; Ritz, Beate; Rausch, Rebecca; Factor, Stewart A; Wood-Siverio, Cathy; Quinn, Joseph F; Chung, Kathryn A; Peterson-Hiller, Amie L; Espay, Alberto J; Revilla, Fredy J; Devoto, Johnna; Yearout, Dora; Hu, Shu-Ching; Cholerton, Brenna A; Montine, Thomas J; Edwards, Karen L; Zabetian, Cyrus P

2017-08-01

Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We genotyped 1105 PD patients from the PD Cognitive Genetics Consortium for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). For common variants, we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate-corrected p-value (P FDR ) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; P FDR  = 2.7 × 10 -4 ) for JoLO, PARP4 rs9318600 (P FDR  = 0.006), and rs9581094 (P FDR  = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (P FDR  = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts. Published by Elsevier Inc.

Spencermartinsiella europaea gen. nov., sp. nov., a new member of the family Trichomonascaceae

USDA-ARS?s Scientific Manuscript database

Ten strains of a novel heterothallic yeast species were isolated from rotten wood collected at different locations in Hungary. Analysis of gene sequences for the D1/D2 domain of the large subunit ribosomal RNA, as well as analysis of concatenated gene sequences for the nearly complete nuclear large...

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/.

Fungal Genomics Program

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

Grigoriev, Igor

The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scalemore » genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.« less

VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

PubMed Central

Jia, Peilin; Zhao, Zhongming

2014-01-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data. PMID:24516372

VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

PubMed

Jia, Peilin; Zhao, Zhongming

2014-02-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

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.

Interaction chromatography for characterization and large-scale fractionation of chemically heterogeneous copolymers

NASA Astrophysics Data System (ADS)

Han, Junwon

The remarkable development of polymer synthesis techniques to make complex polymers with controlled chain architectures has inevitably demanded the advancement of polymer characterization tools to analyze the molecular dispersity in polymeric materials beyond size exclusion chromatography (SEC). In particular, man-made synthetic copolymers that consist of more than one monomer type are disperse mixtures of polymer chains that have distributions in terms of both chemical heterogeneity and chain length (molar mass). While the molecular weight distribution has been quite reliably estimated by the SEC, it is still challenging to properly characterize the chemical composition distribution in the copolymers. Here, I have developed and applied adsorption-based interaction chromatography (IC) techniques as a promising tool to characterize and fractionate polystyrene-based block, random and branched copolymers in terms of their chemical heterogeneity. The first part of this thesis is focused on the adsorption-desorption based purification of PS-b-PMMA diblock copolymers using nanoporous silica. The liquid chromatography analysis and large scale purification are discussed for the PS-b-PMMA block copolymers that have been synthesized by sequential anionic polymerization. SEC and IC are compared to critically analyze the contents of PS homopolymers in the as-synthesized block copolymers. In addition, I have developed an IC technique to provide faster and more reliable information on the chemical heterogeneity in the as-synthesized block copolymers. Finally, a large scale (multi-gram) separation technique is developed to obtain "homopolymer-free" block copolymers via a simple chromatographic filtration technique. By taking advantage of the large specific surface area of nanoporous silica (≈300m 2/g), large scale purification of neat PS-b-PMMA has successfully been achieved by controlling adsorption and desorption of the block copolymers on the silica gel surface using a gravity column. The second part of this thesis is focused on the liquid chromatography analysis and fractionation of RAFT-polymerized PS-b -PMMA diblock copolymers and AFM studies. In this study, PS- b-PMMA block copolymers were synthesized by a RAFT free radical polymerization process---the PMMA block with a phenyldithiobenzoate end group was synthesized first. The contents of unreacted PS and PMMA homopolymers in as-synthesized PS-b-PMMA block copolymers were quantitatively analyzed by solvent gradient interaction chromatography (SGIC) technique employing bare silica and C18-bonded silica columns, respectively. In addition, by 2-dimensional large-scale IC fractionation method, atomic force microscopy (AFM) study of these fractionated samples revealed various morphologies with respect to the chemical composition of each fraction. The third part of this thesis is to analyze random copolymers with tunable monomer sequence distributions using interaction chromatography. Here, IC was used for characterizing the composition and monomer sequence distribution in statistical copolymers of poly(styrene-co-4-bromostyrene) (PBrxS). The PBrS copolymers were synthesized by the bromination of monodisperse polystyrenes; the degree of bromination (x) and the sequence distribution were adjusted by varying the bromination time and the solvent quality, respectively. Both normal-phase (bare silica) and reversed-phase (C18-bonded silica) columns were used at different combinations of solvents and non-solvents to monitor the content of the 4-bromostyrene units in the copolymer and their average monomer sequence distribution. The fourth part of this thesis is to analyze and fractionate highly branched polymers such as dendronized polymers and star-shaped homo and copolymers. I have developed an interaction chromatography technique to separate polymers with nonlinear chain architecture. Specifically, the IC technique has been used to separate dendronized polymers and PS-based highly branched copolymers and to ultimately obtain well-defined dendronized or branched copolymers with a low polydispersity. The effects of excess arm-polymers on (1) the micellar self-assembly of dendronized polymers and (2) the regularity of the pore morphology in the low-k applications by the sol-gel process have been studied.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

PubMed Central

Grüning, Björn A.; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of “effector” proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen’s predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu). PMID:24109552

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

Beyond Linear Sequence Comparisons: The use of genome-levelcharacters for phylogenetic reconstruction

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

Boore, Jeffrey L.

2004-11-27

Although the phylogenetic relationships of many organisms have been convincingly resolved by the comparisons of nucleotide or amino acid sequences, others have remained equivocal despite great effort. Now that large-scale genome sequencing projects are sampling many lineages, it is becoming feasible to compare large data sets of genome-level features and to develop this as a tool for phylogenetic reconstruction that has advantages over conventional sequence comparisons. Although it is unlikely that these will address a large number of evolutionary branch points across the broad tree of life due to the infeasibility of such sampling, they have great potential for convincinglymore » resolving many critical, contested relationships for which no other data seems promising. However, it is important that we recognize potential pitfalls, establish reasonable standards for acceptance, and employ rigorous methodology to guard against a return to earlier days of scenario-driven evolutionary reconstructions.« less

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome

PubMed Central

2013-01-01

Background Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear. Results We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M. Conclusions Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13. PMID:23834397

[New hosts and vectors for genome cloning]. Progress report, 1990--1991

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

Not Available

The main goal of our project remains the development of new bacterial hosts and vectors for the stable propagation of human DNA clones in E. coli. During the past six months of our current budget period, we have (1) continued to develop new hosts that permit the stable maintenance of unstable features of human DNA, and (2) developed a series of vectors for (a) cloning large DNA inserts, (b) assessing the frequency of human sequences that are lethal to the growth of E. coli, and (c) assessing the stability of human sequences cloned in M13 for large-scale sequencing projects.

The sequence of sequencers: The history of sequencing DNA

PubMed Central

Heather, James M.; Chain, Benjamin

2016-01-01

Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way. PMID:26554401

Using the Saccharomyces Genome Database (SGD) for analysis of genomic information

PubMed Central

Skrzypek, Marek S.; Hirschman, Jodi

2011-01-01

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets. PMID:21901739

Sequence-dependent DNA deformability studied using molecular dynamics simulations.

PubMed

Fujii, Satoshi; Kono, Hidetoshi; Takenaka, Shigeori; Go, Nobuhiro; Sarai, Akinori

2007-01-01

Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein-DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein-DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids.

Missing Data and Influential Sites: Choice of Sites for Phylogenetic Analysis Can Be As Important As Taxon Sampling and Model Choice

PubMed Central

Shavit Grievink, Liat; Penny, David; Holland, Barbara R.

2013-01-01

Phylogenetic studies based on molecular sequence alignments are expected to become more accurate as the number of sites in the alignments increases. With the advent of genomic-scale data, where alignments have very large numbers of sites, bootstrap values close to 100% and posterior probabilities close to 1 are the norm, suggesting that the number of sites is now seldom a limiting factor on phylogenetic accuracy. This provokes the question, should we be fussy about the sites we choose to include in a genomic-scale phylogenetic analysis? If some sites contain missing data, ambiguous character states, or gaps, then why not just throw them away before conducting the phylogenetic analysis? Indeed, this is exactly the approach taken in many phylogenetic studies. Here, we present an example where the decision on how to treat sites with missing data is of equal importance to decisions on taxon sampling and model choice, and we introduce a graphical method for illustrating this. PMID:23471508

MEGANTE: A Web-Based System for Integrated Plant Genome Annotation

PubMed Central

Numa, Hisataka; Itoh, Takeshi

2014-01-01

The recent advancement of high-throughput genome sequencing technologies has resulted in a considerable increase in demands for large-scale genome annotation. While annotation is a crucial step for downstream data analyses and experimental studies, this process requires substantial expertise and knowledge of bioinformatics. Here we present MEGANTE, a web-based annotation system that makes plant genome annotation easy for researchers unfamiliar with bioinformatics. Without any complicated configuration, users can perform genomic sequence annotations simply by uploading a sequence and selecting the species to query. MEGANTE automatically runs several analysis programs and integrates the results to select the appropriate consensus exon–intron structures and to predict open reading frames (ORFs) at each locus. Functional annotation, including a similarity search against known proteins and a functional domain search, are also performed for the predicted ORFs. The resultant annotation information is visualized with a widely used genome browser, GBrowse. For ease of analysis, the results can be downloaded in Microsoft Excel format. All of the query sequences and annotation results are stored on the server side so that users can access their own data from virtually anywhere on the web. The current release of MEGANTE targets 24 plant species from the Brassicaceae, Fabaceae, Musaceae, Poaceae, Salicaceae, Solanaceae, Rosaceae and Vitaceae families, and it allows users to submit a sequence up to 10 Mb in length and to save up to 100 sequences with the annotation information on the server. The MEGANTE web service is available at https://megante.dna.affrc.go.jp/. PMID:24253915

Highly specific gene silencing in a monocot species by artificial microRNAs derived from chimeric miRNA precursors

DOE PAGES

Carbonell, Alberto; Fahlgren, Noah; Mitchell, Skyler; ...

2015-05-20

Artificial microRNAs (amiRNAs) are used for selective gene silencing in plants. However, current methods to produce amiRNA constructs for silencing transcripts in monocot species are not suitable for simple, cost-effective and large-scale synthesis. Here, a series of expression vectors based on Oryza sativa MIR390 (OsMIR390) precursor was developed for high-throughput cloning and high expression of amiRNAs in monocots. Four different amiRNA sequences designed to target specifically endogenous genes and expressed from OsMIR390-based vectors were validated in transgenic Brachypodium distachyon plants. Surprisingly, amiRNAs accumulated to higher levels and were processed more accurately when expressed from chimeric OsMIR390-based precursors that include distalmore » stem-loop sequences from Arabidopsis thaliana MIR390a (AtMIR390a). In all cases, transgenic plants displayed the predicted phenotypes induced by target gene repression, and accumulated high levels of amiRNAs and low levels of the corresponding target transcripts. Genome-wide transcriptome profiling combined with 5-RLM-RACE analysis in transgenic plants confirmed that amiRNAs were highly specific. Finally, significance Statement A series of amiRNA vectors based on Oryza sativa MIR390 (OsMIR390) precursor were developed for simple, cost-effective and large-scale synthesis of amiRNA constructs to silence genes in monocots. Unexpectedly, amiRNAs produced from chimeric OsMIR390-based precursors including Arabidopsis thaliana MIR390a distal stem-loop sequences accumulated elevated levels of highly effective and specific amiRNAs in transgenic Brachypodium distachyon plants.« less

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

PubMed

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world. Copyright © 2015 Hadjithomas et al.

Newborn Sequencing in Genomic Medicine and Public Health.

PubMed

Berg, Jonathan S; Agrawal, Pankaj B; Bailey, Donald B; Beggs, Alan H; Brenner, Steven E; Brower, Amy M; Cakici, Julie A; Ceyhan-Birsoy, Ozge; Chan, Kee; Chen, Flavia; Currier, Robert J; Dukhovny, Dmitry; Green, Robert C; Harris-Wai, Julie; Holm, Ingrid A; Iglesias, Brenda; Joseph, Galen; Kingsmore, Stephen F; Koenig, Barbara A; Kwok, Pui-Yan; Lantos, John; Leeder, Steven J; Lewis, Megan A; McGuire, Amy L; Milko, Laura V; Mooney, Sean D; Parad, Richard B; Pereira, Stacey; Petrikin, Joshua; Powell, Bradford C; Powell, Cynthia M; Puck, Jennifer M; Rehm, Heidi L; Risch, Neil; Roche, Myra; Shieh, Joseph T; Veeraraghavan, Narayanan; Watson, Michael S; Willig, Laurel; Yu, Timothy W; Urv, Tiina; Wise, Anastasia L

2017-02-01

The rapid development of genomic sequencing technologies has decreased the cost of genetic analysis to the extent that it seems plausible that genome-scale sequencing could have widespread availability in pediatric care. Genomic sequencing provides a powerful diagnostic modality for patients who manifest symptoms of monogenic disease and an opportunity to detect health conditions before their development. However, many technical, clinical, ethical, and societal challenges should be addressed before such technology is widely deployed in pediatric practice. This article provides an overview of the Newborn Sequencing in Genomic Medicine and Public Health Consortium, which is investigating the application of genome-scale sequencing in newborns for both diagnosis and screening. Copyright © 2017 by the American Academy of Pediatrics.

Reference-guided assembly of four diverse Arabidopsis thaliana genomes

PubMed Central

Schneeberger, Korbinian; Ossowski, Stephan; Ott, Felix; Klein, Juliane D.; Wang, Xi; Lanz, Christa; Smith, Lisa M.; Cao, Jun; Fitz, Joffrey; Warthmann, Norman; Henz, Stefan R.; Huson, Daniel H.; Weigel, Detlef

2011-01-01

We present whole-genome assemblies of four divergent Arabidopsis thaliana strains that complement the 125-Mb reference genome sequence released a decade ago. Using a newly developed reference-guided approach, we assembled large contigs from 9 to 42 Gb of Illumina short-read data from the Landsberg erecta (Ler-1), C24, Bur-0, and Kro-0 strains, which have been sequenced as part of the 1,001 Genomes Project for this species. Using alignments against the reference sequence, we first reduced the complexity of the de novo assembly and later integrated reads without similarity to the reference sequence. As an example, half of the noncentromeric C24 genome was covered by scaffolds that are longer than 260 kb, with a maximum of 2.2 Mb. Moreover, over 96% of the reference genome was covered by the reference-guided assembly, compared with only 87% with a complete de novo assembly. Comparisons with 2 Mb of dideoxy sequence reveal that the per-base error rate of the reference-guided assemblies was below 1 in 10,000. Our assemblies provide a detailed, genomewide picture of large-scale differences between A. thaliana individuals, most of which are difficult to access with alignment-consensus methods only. We demonstrate their practical relevance in studying the expression differences of polymorphic genes and show how the analysis of sRNA sequencing data can lead to erroneous conclusions if aligned against the reference genome alone. Genome assemblies, raw reads, and further information are accessible through http://1001genomes.org/projects/assemblies.html. PMID:21646520

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…

Cell-free translational screening of an expression sequence tag library of Clonorchis sinensis for novel antigen discovery.

PubMed

Kasi, Devi; Catherine, Christy; Lee, Seung-Won; Lee, Kyung-Ho; Kim, Yu Jung; Ro Lee, Myeong; Ju, Jung Won; Kim, Dong-Myung

2017-05-01

The rapidly evolving cloning and sequencing technologies have enabled understanding of genomic structure of parasite genomes, opening up new ways of combatting parasite-related diseases. To make the most of the exponentially accumulating genomic data, however, it is crucial to analyze the proteins encoded by these genomic sequences. In this study, we adopted an engineered cell-free protein synthesis system for large-scale expression screening of an expression sequence tag (EST) library of Clonorchis sinensis to identify potential antigens that can be used for diagnosis and treatment of clonorchiasis. To allow high-throughput expression and identification of individual genes comprising the library, a cell-free synthesis reaction was designed such that both the template DNA and the expressed proteins were co-immobilized on the same microbeads, leading to microbead-based linkage of the genotype and phenotype. This reaction configuration allowed streamlined expression, recovery, and analysis of proteins. This approach enabled us to identify 21 antigenic proteins. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:832-837, 2017. © 2017 American Institute of Chemical Engineers.

Sequence and analysis of chromosome 2 of the plant Arabidopsis thaliana.

PubMed

Lin, X; Kaul, S; Rounsley, S; Shea, T P; Benito, M I; Town, C D; Fujii, C Y; Mason, T; Bowman, C L; Barnstead, M; Feldblyum, T V; Buell, C R; Ketchum, K A; Lee, J; Ronning, C M; Koo, H L; Moffat, K S; Cronin, L A; Shen, M; Pai, G; Van Aken, S; Umayam, L; Tallon, L J; Gill, J E; Adams, M D; Carrera, A J; Creasy, T H; Goodman, H M; Somerville, C R; Copenhaver, G P; Preuss, D; Nierman, W C; White, O; Eisen, J A; Salzberg, S L; Fraser, C M; Venter, J C

1999-12-16

Arabidopsis thaliana (Arabidopsis) is unique among plant model organisms in having a small genome (130-140 Mb), excellent physical and genetic maps, and little repetitive DNA. Here we report the sequence of chromosome 2 from the Columbia ecotype in two gap-free assemblies (contigs) of 3.6 and 16 megabases (Mb). The latter represents the longest published stretch of uninterrupted DNA sequence assembled from any organism to date. Chromosome 2 represents 15% of the genome and encodes 4,037 genes, 49% of which have no predicted function. Roughly 250 tandem gene duplications were found in addition to large-scale duplications of about 0.5 and 4.5 Mb between chromosomes 2 and 1 and between chromosomes 2 and 4, respectively. Sequencing of nearly 2 Mb within the genetically defined centromere revealed a low density of recognizable genes, and a high density and diverse range of vestigial and presumably inactive mobile elements. More unexpected is what appears to be a recent insertion of a continuous stretch of 75% of the mitochondrial genome into chromosome 2.

Needles in the EST Haystack: Large-Scale Identification and Analysis of Excretory-Secretory (ES) Proteins in Parasitic Nematodes Using Expressed Sequence Tags (ESTs)

PubMed Central

Nagaraj, Shivashankar H.; Gasser, Robin B.; Ranganathan, Shoba

2008-01-01

Background Parasitic nematodes of humans, other animals and plants continue to impose a significant public health and economic burden worldwide, due to the diseases they cause. Promising antiparasitic drug and vaccine candidates have been discovered from excreted or secreted (ES) proteins released from the parasite and exposed to the immune system of the host. Mining the entire expressed sequence tag (EST) data available from parasitic nematodes represents an approach to discover such ES targets. Methods and Findings In this study, we predicted, using EST2Secretome, a novel, high-throughput, computational workflow system, 4,710 ES proteins from 452,134 ESTs derived from 39 different species of nematodes, parasitic in animals (including humans) or plants. In total, 2,632, 786, and 1,292 ES proteins were predicted for animal-, human-, and plant-parasitic nematodes. Subsequently, we systematically analysed ES proteins using computational methods. Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases. Of the C. elegans homologues, 267 had strong “loss-of-function” phenotypes by RNA interference (RNAi) in this nematode. We could functionally classify 1,948 (41.3%) sequences using the Gene Ontology (GO) terms, establish pathway associations for 573 (12.2%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG), and identify protein interaction partners for 1,774 (37.6%) molecules. We also mapped 758 (16.1%) proteins to protein domains including the nematode-specific protein family “transthyretin-like” and “chromadorea ALT,” considered as vaccine candidates against filariasis in humans. Conclusions We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes. This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control. PMID:18820748

Scaling in nature: From DNA through heartbeats to weather

NASA Astrophysics Data System (ADS)

Havlin, S.; Buldyrev, S. V.; Bunde, A.; Goldberger, A. L.; Ivanov, P. Ch.; Peng, C.-K.; Stanley, H. E.

1999-12-01

The purpose of this talk is to describe some recent progress in applying scaling concepts to various systems in nature. We review several systems characterized by scaling laws such as DNA sequences, heartbeat rates and weather variations. We discuss the finding that the exponent α quantifying the scaling in DNA in smaller for coding than for noncoding sequences. We also discuss the application of fractal scaling analysis to the dynamics of heartbeat regulation, and report the recent finding that the scaling exponent α is smaller during sleep periods compared to wake periods. We also discuss the recent findings that suggest a universal scaling exponent characterizing the weather fluctuations.

Scaling in nature: from DNA through heartbeats to weather

NASA Technical Reports Server (NTRS)

Havlin, S.; Buldyrev, S. V.; Bunde, A.; Goldberger, A. L.; Peng, C. K.; Stanley, H. E.

1999-01-01

The purpose of this report is to describe some recent progress in applying scaling concepts to various systems in nature. We review several systems characterized by scaling laws such as DNA sequences, heartbeat rates and weather variations. We discuss the finding that the exponent alpha quantifying the scaling in DNA in smaller for coding than for noncoding sequences. We also discuss the application of fractal scaling analysis to the dynamics of heartbeat regulation, and report the recent finding that the scaling exponent alpha is smaller during sleep periods compared to wake periods. We also discuss the recent findings that suggest a universal scaling exponent characterizing the weather fluctuations.

Gene expression analysis of flax seed development

PubMed Central

2011-01-01

Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise even low-expressed genes such as those encoding transcription factors. This has allowed us to delineate the spatio-temporal aspects of gene expression underlying the biosynthesis of a number of important seed constituents in flax. Flax belongs to a taxonomic group of diverse plants and the large sequence database will allow for evolutionary studies as well. PMID:21529361

Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features

PubMed Central

Mohammad-Noori, Morteza; Beer, Michael A.

2014-01-01

Abstract Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem. PMID:25033408

Enhanced regulatory sequence prediction using gapped k-mer features.

PubMed

Ghandi, Mahmoud; Lee, Dongwon; Mohammad-Noori, Morteza; Beer, Michael A

2014-07-01

Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.

Detection of large-scale concentric gravity waves from a Chinese airglow imager network

NASA Astrophysics Data System (ADS)

Lai, Chang; Yue, Jia; Xu, Jiyao; Yuan, Wei; Li, Qinzeng; Liu, Xiao

2018-06-01

Concentric gravity waves (CGWs) contain a broad spectrum of horizontal wavelengths and periods due to their instantaneous localized sources (e.g., deep convection, volcanic eruptions, or earthquake, etc.). However, it is difficult to observe large-scale gravity waves of >100 km wavelength from the ground for the limited field of view of a single camera and local bad weather. Previously, complete large-scale CGW imagery could only be captured by satellite observations. In the present study, we developed a novel method that uses assembling separate images and applying low-pass filtering to obtain temporal and spatial information about complete large-scale CGWs from a network of all-sky airglow imagers. Coordinated observations from five all-sky airglow imagers in Northern China were assembled and processed to study large-scale CGWs over a wide area (1800 km × 1 400 km), focusing on the same two CGW events as Xu et al. (2015). Our algorithms yielded images of large-scale CGWs by filtering out the small-scale CGWs. The wavelengths, wave speeds, and periods of CGWs were measured from a sequence of consecutive assembled images. Overall, the assembling and low-pass filtering algorithms can expand the airglow imager network to its full capacity regarding the detection of large-scale gravity waves.

Discovery, genotyping and characterization of structural variation and novel sequence at single nucleotide resolution from de novo genome assemblies on a population scale.

PubMed

Liu, Siyang; Huang, Shujia; Rao, Junhua; Ye, Weijian; Krogh, Anders; Wang, Jun

2015-01-01

Comprehensive recognition of genomic variation in one individual is important for understanding disease and developing personalized medication and treatment. Many tools based on DNA re-sequencing exist for identification of single nucleotide polymorphisms, small insertions and deletions (indels) as well as large deletions. However, these approaches consistently display a substantial bias against the recovery of complex structural variants and novel sequence in individual genomes and do not provide interpretation information such as the annotation of ancestral state and formation mechanism. We present a novel approach implemented in a single software package, AsmVar, to discover, genotype and characterize different forms of structural variation and novel sequence from population-scale de novo genome assemblies up to nucleotide resolution. Application of AsmVar to several human de novo genome assemblies captures a wide spectrum of structural variants and novel sequences present in the human population in high sensitivity and specificity. Our method provides a direct solution for investigating structural variants and novel sequences from de novo genome assemblies, facilitating the construction of population-scale pan-genomes. Our study also highlights the usefulness of the de novo assembly strategy for definition of genome structure.

Closha: bioinformatics workflow system for the analysis of massive sequencing data.

PubMed

Ko, GunHwan; Kim, Pan-Gyu; Yoon, Jongcheol; Han, Gukhee; Park, Seong-Jin; Song, Wangho; Lee, Byungwook

2018-02-19

While next-generation sequencing (NGS) costs have fallen in recent years, the cost and complexity of computation remain substantial obstacles to the use of NGS in bio-medical care and genomic research. The rapidly increasing amounts of data available from the new high-throughput methods have made data processing infeasible without automated pipelines. The integration of data and analytic resources into workflow systems provides a solution to the problem by simplifying the task of data analysis. To address this challenge, we developed a cloud-based workflow management system, Closha, to provide fast and cost-effective analysis of massive genomic data. We implemented complex workflows making optimal use of high-performance computing clusters. Closha allows users to create multi-step analyses using drag and drop functionality and to modify the parameters of pipeline tools. Users can also import the Galaxy pipelines into Closha. Closha is a hybrid system that enables users to use both analysis programs providing traditional tools and MapReduce-based big data analysis programs simultaneously in a single pipeline. Thus, the execution of analytics algorithms can be parallelized, speeding up the whole process. We also developed a high-speed data transmission solution, KoDS, to transmit a large amount of data at a fast rate. KoDS has a file transfer speed of up to 10 times that of normal FTP and HTTP. The computer hardware for Closha is 660 CPU cores and 800 TB of disk storage, enabling 500 jobs to run at the same time. Closha is a scalable, cost-effective, and publicly available web service for large-scale genomic data analysis. Closha supports the reliable and highly scalable execution of sequencing analysis workflows in a fully automated manner. Closha provides a user-friendly interface to all genomic scientists to try to derive accurate results from NGS platform data. The Closha cloud server is freely available for use from http://closha.kobic.re.kr/ .

Multi-Genetic Marker Approach and Spatio-Temporal Analysis Suggest There Is a Single Panmictic Population of Swordfish Xiphias gladius in the Indian Ocean

PubMed Central

Muths, Delphine; Le Couls, Sarah; Evano, Hugues; Grewe, Peter; Bourjea, Jerome

2013-01-01

Genetic population structure of swordfish Xiphias gladius was examined based on 2231 individual samples, collected mainly between 2009 and 2010, among three major sampling areas within the Indian Ocean (IO; twelve distinct sites), Atlantic (two sites) and Pacific (one site) Oceans using analysis of nineteen microsatellite loci (n = 2146) and mitochondrial ND2 sequences (n = 2001) data. Sample collection was stratified in time and space in order to investigate the stability of the genetic structure observed with a special focus on the South West Indian Ocean. Significant AMOVA variance was observed for both markers indicating genetic population subdivision was present between oceans. Overall value of F-statistics for ND2 sequences confirmed that Atlantic and Indian Oceans swordfish represent two distinct genetic stocks. Indo-Pacific differentiation was also significant but lower than that observed between Atlantic and Indian Oceans. However, microsatellite F-statistics failed to reveal structure even at the inter-oceanic scale, indicating that resolving power of our microsatellite loci was insufficient for detecting population subdivision. At the scale of the Indian Ocean, results obtained from both markers are consistent with swordfish belonging to a single unique panmictic population. Analyses partitioned by sampling area, season, or sex also failed to identify any clear structure within this ocean. Such large spatial and temporal homogeneity of genetic structure, observed for such a large highly mobile pelagic species, suggests as satisfactory to consider swordfish as a single panmictic population in the Indian Ocean. PMID:23717447

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing

PubMed Central

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; Martínez de la Vega, Octavio; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C.; Vielle-Calzada, Jean-Philippe

2012-01-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies. PMID:22442422

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing.

PubMed

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; de la Vega, Octavio Martínez; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C; Vielle-Calzada, Jean-Philippe

2012-06-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies.

Genome-wide association study based on multiple imputation with low-depth sequencing data: application to biofuel traits in reed canarygrass

USDA-ARS?s Scientific Manuscript database

Genotyping by sequencing allows for large-scale genetic analyses in plant species with no reference genome, but sets the challenge of sound inference in presence of uncertain genotypes. We report an imputation-based genome-wide association study (GWAS) in reed canarygrass (Phalaris arundinacea L., P...

Phylogenetics.

PubMed

Sleator, Roy D

2011-04-01

The recent rapid expansion in the DNA and protein databases, arising from large-scale genomic and metagenomic sequence projects, has forced significant development in the field of phylogenetics: the study of the evolutionary relatedness of the planet's inhabitants. Advances in phylogenetic analysis have greatly transformed our view of the landscape of evolutionary biology, transcending the view of the tree of life that has shaped evolutionary theory since Darwinian times. Indeed, modern phylogenetic analysis no longer focuses on the restricted Darwinian-Mendelian model of vertical gene transfer, but must also consider the significant degree of lateral gene transfer, which connects and shapes almost all living things. Herein, I review the major tree-building methods, their strengths, weaknesses and future prospects.

Global investigation of protein-protein interactions in yeast Saccharomyces cerevisiae using re-occurring short polypeptide sequences.

PubMed

Pitre, S; North, C; Alamgir, M; Jessulat, M; Chan, A; Luo, X; Green, J R; Dumontier, M; Dehne, F; Golshani, A

2008-08-01

Protein-protein interaction (PPI) maps provide insight into cellular biology and have received considerable attention in the post-genomic era. While large-scale experimental approaches have generated large collections of experimentally determined PPIs, technical limitations preclude certain PPIs from detection. Recently, we demonstrated that yeast PPIs can be computationally predicted using re-occurring short polypeptide sequences between known interacting protein pairs. However, the computational requirements and low specificity made this method unsuitable for large-scale investigations. Here, we report an improved approach, which exhibits a specificity of approximately 99.95% and executes 16,000 times faster. Importantly, we report the first all-to-all sequence-based computational screen of PPIs in yeast, Saccharomyces cerevisiae in which we identify 29,589 high confidence interactions of approximately 2 x 10(7) possible pairs. Of these, 14,438 PPIs have not been previously reported and may represent novel interactions. In particular, these results reveal a richer set of membrane protein interactions, not readily amenable to experimental investigations. From the novel PPIs, a novel putative protein complex comprised largely of membrane proteins was revealed. In addition, two novel gene functions were predicted and experimentally confirmed to affect the efficiency of non-homologous end-joining, providing further support for the usefulness of the identified PPIs in biological investigations.

Possible roles for fronto-striatal circuits in reading disorder

PubMed Central

Hancock, Roeland; Richlan, Fabio; Hoeft, Fumiko

2016-01-01

Several studies have reported hyperactivation in frontal and striatal regions in individuals with reading disorder (RD) during reading-related tasks. Hyperactivation in these regions is typically interpreted as a form of neural compensation and related to articulatory processing. Fronto-striatal hyperactivation in RD can however, also arise from fundamental impairment in reading related processes, such as phonological processing and implicit sequence learning relevant to early language acquisition. We review current evidence for the compensation hypothesis in RD and apply large-scale reverse inference to investigate anatomical overlap between hyperactivation regions and neural systems for articulation, phonological processing, implicit sequence learning. We found anatomical convergence between hyperactivation regions and regions supporting articulation, consistent with the proposed compensatory role of these regions, and low convergence with phonological and implicit sequence learning regions. Although the application of large-scale reverse inference to decode function in a clinical population should be interpreted cautiously, our findings suggest future lines of research that may clarify the functional significance of hyperactivation in RD. PMID:27826071

Hadoop-BAM: directly manipulating next generation sequencing data in the cloud

PubMed Central

Niemenmaa, Matti; Kallio, Aleksi; Schumacher, André; Klemelä, Petri; Korpelainen, Eija; Heljanko, Keijo

2012-01-01

Summary: Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps. Availability: Available under the open-source MIT license at http://sourceforge.net/projects/hadoop-bam/ Contact: matti.niemenmaa@aalto.fi Supplementary information: Supplementary material is available at Bioinformatics online. PMID:22302568

Shedding new light on opsin evolution

PubMed Central

Porter, Megan L.; Blasic, Joseph R.; Bok, Michael J.; Cameron, Evan G.; Pringle, Thomas; Cronin, Thomas W.; Robinson, Phyllis R.

2012-01-01

Opsin proteins are essential molecules in mediating the ability of animals to detect and use light for diverse biological functions. Therefore, understanding the evolutionary history of opsins is key to understanding the evolution of light detection and photoreception in animals. As genomic data have appeared and rapidly expanded in quantity, it has become possible to analyse opsins that functionally and histologically are less well characterized, and thus to examine opsin evolution strictly from a genetic perspective. We have incorporated these new data into a large-scale, genome-based analysis of opsin evolution. We use an extensive phylogeny of currently known opsin sequence diversity as a foundation for examining the evolutionary distributions of key functional features within the opsin clade. This new analysis illustrates the lability of opsin protein-expression patterns, site-specific functionality (i.e. counterion position) and G-protein binding interactions. Further, it demonstrates the limitations of current model organisms, and highlights the need for further characterization of many of the opsin sequence groups with unknown function. PMID:22012981

G2S: a web-service for annotating genomic variants on 3D protein structures.

PubMed

Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-06-01

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that supports programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online.

From genes to genomes: a new paradigm for studying fungal pathogenesis in Magnaporthe oryzae.

PubMed

Xu, Jin-Rong; Zhao, Xinhua; Dean, Ralph A

2007-01-01

Magnaporthe oryzae is the most destructive fungal pathogen of rice worldwide and because of its amenability to classical and molecular genetic manipulation, availability of a genome sequence, and other resources it has emerged as a leading model system to study host-pathogen interactions. This chapter reviews recent progress toward elucidation of the molecular basis of infection-related morphogenesis, host penetration, invasive growth, and host-pathogen interactions. Related information on genome analysis and genomic studies of plant infection processes is summarized under specific topics where appropriate. Particular emphasis is placed on the role of MAP kinase and cAMP signal transduction pathways and unique features in the genome such as repetitive sequences and expanded gene families. Emerging developments in functional genome analysis through large-scale insertional mutagenesis and gene expression profiling are detailed. The chapter concludes with new prospects in the area of systems biology, such as protein expression profiling, and highlighting remaining crucial information needed to fully appreciate host-pathogen interactions.

A Continental-Wide Perspective: The Genepool of Nuclear Encoded Ribosomal DNA and Single-Copy Gene Sequences in North American Boechera (Brassicaceae)

PubMed Central

Kiefer, Christiane; Koch, Marcus A.

2012-01-01

74 of the currently accepted 111 taxa of the North American genus Boechera (Brassicaceae) were subject to pyhlogenetic reconstruction and network analysis. The dataset comprised 911 accessions for which ITS sequences were analyzed. Phylogenetic analyses yielded largely unresolved trees. Together with the network analysis confirming this result this can be interpreted as an indication for multiple, independent, and rapid diversification events. Network analyses were superimposed with datasets describing i) geographical distribution, ii) taxonomy, iii) reproductive mode, and iv) distribution history based on phylogeographic evidence. Our results provide first direct evidence for enormous reticulate evolution in the entire genus and give further insights into the evolutionary history of this complex genus on a continental scale. In addition two novel single-copy gene markers, orthologues of the Arabidopsis thaliana genes At2g25920 and At3g18900, were analyzed for subsets of taxa and confirmed the findings obtained through the ITS data. PMID:22606266

Precise excision and self-integration of a composite transposon as a model for spontaneous large-scale chromosome inversion/deletion of the Staphylococcus haemolyticus clinical strain JCSC1435.

PubMed

Watanabe, Shinya; Ito, Teruyo; Morimoto, Yuh; Takeuchi, Fumihiko; Hiramatsu, Keiichi

2007-04-01

Large-scale chromosomal inversions (455 to 535 kbp) or deletions (266 to 320 kbp) were found to accompany spontaneous loss of beta-lactam resistance during drug-free passage of the multiresistant Staphylococcus haemolyticus clinical strain JCSC1435. Identification and sequencing of the rearranged chromosomal loci revealed that ISSha1 of S. haemolyticus is responsible for the chromosome rearrangements.

Lateral fluid flow in a compacting sand-shale sequence: South Caspian basin.

USGS Publications Warehouse

Bredehoeft, J.D.; Djevanshir, R.D.; Belitz, K.R.

1988-01-01

The South Caspian basin contains both sands and shales that have pore-fluid pressures substantially in excess of hydrostatic fluid pressure. Pore-pressure data from the South Caspian basin demonstrate that large differences in excess hydraulic head exist between sand and shale. The data indicate that sands are acting as drains for overlying and underlying compacting shales and that fluid flows laterally through the sand on a regional scale from the basin interior northward to points of discharge. The major driving force for the fluid movement is shale compaction. We present a first- order mathematical analysis in an effort to test if the permeability of the sands required to support a regional flow system is reasonable. The results of the analysis suggest regional sand permeabilities ranging from 1 to 30 md; a range that seems reasonable. This result supports the thesis that lateral fluid flow is occurring on a regional scale within the South Caspian basin. If vertical conduits for flow exist within the basin, they are sufficiently impermeable and do not provide a major outlet for the regional flow system. The lateral fluid flow within the sands implies that the stratigraphic sequence is divided into horizontal units that are hydraulically isolated from one another, a conclusion that has important implications for oil and gas migration.-Authors

Prediction of protein tertiary structure from sequences using a very large back-propagation neural network

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

Liu, X.; Wilcox, G.L.

1993-12-31

We have implemented large scale back-propagation neural networks on a 544 node Connection Machine, CM-5, using the C language in MIMD mode. The program running on 512 processors performs backpropagation learning at 0.53 Gflops, which provides 76 million connection updates per second. We have applied the network to the prediction of protein tertiary structure from sequence information alone. A neural network with one hidden layer and 40 million connections is trained to learn the relationship between sequence and tertiary structure. The trained network yields predicted structures of some proteins on which it has not been trained given only their sequences.more » Presentation of the Fourier transform of the sequences accentuates periodicity in the sequence and yields good generalization with greatly increased training efficiency. Training simulations with a large, heterologous set of protein structures (111 proteins from CM-5 time) to solutions with under 2% RMS residual error within the training set (random responses give an RMS error of about 20%). Presentation of 15 sequences of related proteins in a testing set of 24 proteins yields predicted structures with less than 8% RMS residual error, indicating good apparent generalization.« less

An integrated semiconductor device enabling non-optical genome sequencing.

PubMed

Rothberg, Jonathan M; Hinz, Wolfgang; Rearick, Todd M; Schultz, Jonathan; Mileski, William; Davey, Mel; Leamon, John H; Johnson, Kim; Milgrew, Mark J; Edwards, Matthew; Hoon, Jeremy; Simons, Jan F; Marran, David; Myers, Jason W; Davidson, John F; Branting, Annika; Nobile, John R; Puc, Bernard P; Light, David; Clark, Travis A; Huber, Martin; Branciforte, Jeffrey T; Stoner, Isaac B; Cawley, Simon E; Lyons, Michael; Fu, Yutao; Homer, Nils; Sedova, Marina; Miao, Xin; Reed, Brian; Sabina, Jeffrey; Feierstein, Erika; Schorn, Michelle; Alanjary, Mohammad; Dimalanta, Eileen; Dressman, Devin; Kasinskas, Rachel; Sokolsky, Tanya; Fidanza, Jacqueline A; Namsaraev, Eugeni; McKernan, Kevin J; Williams, Alan; Roth, G Thomas; Bustillo, James

2011-07-20

The seminal importance of DNA sequencing to the life sciences, biotechnology and medicine has driven the search for more scalable and lower-cost solutions. Here we describe a DNA sequencing technology in which scalable, low-cost semiconductor manufacturing techniques are used to make an integrated circuit able to directly perform non-optical DNA sequencing of genomes. Sequence data are obtained by directly sensing the ions produced by template-directed DNA polymerase synthesis using all-natural nucleotides on this massively parallel semiconductor-sensing device or ion chip. The ion chip contains ion-sensitive, field-effect transistor-based sensors in perfect register with 1.2 million wells, which provide confinement and allow parallel, simultaneous detection of independent sequencing reactions. Use of the most widely used technology for constructing integrated circuits, the complementary metal-oxide semiconductor (CMOS) process, allows for low-cost, large-scale production and scaling of the device to higher densities and larger array sizes. We show the performance of the system by sequencing three bacterial genomes, its robustness and scalability by producing ion chips with up to 10 times as many sensors and sequencing a human genome.

Phylogenomics of nonavian reptiles and the structure of the ancestral amniote genome

PubMed Central

Shedlock, Andrew M.; Botka, Christopher W.; Zhao, Shaying; Shetty, Jyoti; Zhang, Tingting; Liu, Jun S.; Deschavanne, Patrick J.; Edwards, Scott V.

2007-01-01

We report results of a megabase-scale phylogenomic analysis of the Reptilia, the sister group of mammals. Large-scale end-sequence scanning of genomic clones of a turtle, alligator, and lizard reveals diverse, mammal-like landscapes of retroelements and simple sequence repeats (SSRs) not found in the chicken. Several global genomic traits, including distinctive phylogenetic lineages of CR1-like long interspersed elements (LINEs) and a paucity of A-T rich SSRs, characterize turtles and archosaur genomes, whereas higher frequencies of tandem repeats and a lower global GC content reveal mammal-like features in Anolis. Nonavian reptile genomes also possess a high frequency of diverse and novel 50-bp unit tandem duplications not found in chicken or mammals. The frequency distributions of ≈65,000 8-mer oligonucleotides suggest that rates of DNA-word frequency change are an order of magnitude slower in reptiles than in mammals. These results suggest a diverse array of interspersed and SSRs in the common ancestor of amniotes and a genomic conservatism and gradual loss of retroelements in reptiles that culminated in the minimalist chicken genome. PMID:17307883

Scaling exponents for ordered maxima

DOE PAGES

Ben-Naim, E.; Krapivsky, P. L.; Lemons, N. W.

2015-12-22

We study extreme value statistics of multiple sequences of random variables. For each sequence with N variables, independently drawn from the same distribution, the running maximum is defined as the largest variable to date. We compare the running maxima of m independent sequences and investigate the probability S N that the maxima are perfectly ordered, that is, the running maximum of the first sequence is always larger than that of the second sequence, which is always larger than the running maximum of the third sequence, and so on. The probability S N is universal: it does not depend on themore » distribution from which the random variables are drawn. For two sequences, S N~N –1/2, and in general, the decay is algebraic, S N~N –σm, for large N. We analytically obtain the exponent σ 3≅1.302931 as root of a transcendental equation. Moreover, the exponents σ m grow with m, and we show that σ m~m for large m.« less

FOUNTAIN: A JAVA open-source package to assist large sequencing projects

PubMed Central

Buerstedde, Jean-Marie; Prill, Florian

2001-01-01

Background Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences. Results We describe here a new program, named FOUNTAIN, for the management of large sequencing projects . FOUNTAIN uses the JAVA computer language and data storage in a relational database. Starting with a collection of sequencing objects (clones), the program generates and stores information related to the different stages of the sequencing project using a web browser interface for user input. The generated sequences are subsequently imported and annotated based on BLAST searches against the public databases. In addition, simple algorithms to cluster sequences and determine putative polymorphic positions are implemented. Conclusions A simple, but flexible and scalable software package is presented to facilitate data generation and storage for large sequencing projects. Open source and largely platform and database independent, we wish FOUNTAIN to be improved and extended in a community effort. PMID:11591214

Clustalnet: the joining of Clustal and CORBA.

PubMed

Campagne, F

2000-07-01

Performing sequence alignment operations from a different program than the original sequence alignment code, and/or through a network connection, is often required. Interactive alignment editors and large-scale biological data analysis are common examples where such a flexibility is important. Interoperability between the alignment engine and the client should be obtained regardless of the architectures and programming languages of the server and client. Clustalnet, a Clustal alignment CORBA server is described, which was developed on the basis of Clustalw. This server brings the robustness of the algorithms and implementations of Clustal to a new level of reuse. A Clustalnet server object can be accessed from a program, transparently through the network. We present interfaces to perform the alignment operations and to control these operations via immutable contexts. The interfaces that select the contexts do not depend on the nature of the operation to be performed, making the design modular. The IDL interfaces presented here are not specific to Clustal and can be implemented on top of different sequence alignment algorithm implementations.

In vivo insertion pool sequencing identifies virulence factors in a complex fungal–host interaction

PubMed Central

Uhse, Simon; Pflug, Florian G.; Stirnberg, Alexandra; Ehrlinger, Klaus; von Haeseler, Arndt

2018-01-01

Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U. maydis. iPool-Seq features tagmentation, unique molecular barcodes, and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues. In a proof of concept using iPool-Seq, we identified 28 virulence factors, including 23 that were previously uncharacterized, from an initial pool of 195 candidate effector mutants. Because of its sensitivity and quantitative nature, iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts. PMID:29684023

Exploring bacterial epigenomics in the next-generation sequencing era: a new approach for an emerging frontier.

PubMed

Chen, Poyin; Jeannotte, Richard; Weimer, Bart C

2014-05-01

Epigenetics has an important role for the success of foodborne pathogen persistence in diverse host niches. Substantial challenges exist in determining DNA methylation to situation-specific phenotypic traits. DNA modification, mediated by restriction-modification systems, functions as an immune response against antagonistic external DNA, and bacteriophage-acquired methyltransferases (MTase) and orphan MTases - those lacking the cognate restriction endonuclease - facilitate evolution of new phenotypes via gene expression modulation via DNA and RNA modifications, including methylation and phosphorothioation. Recent establishment of large-scale genome sequencing projects will result in a significant increase in genome availability that will lead to new demands for data analysis including new predictive bioinformatics approaches that can be verified with traditional scientific rigor. Sequencing technologies that detect modification coupled with mass spectrometry to discover new adducts is a powerful tactic to study bacterial epigenetics, which is poised to make novel and far-reaching discoveries that link biological significance and the bacterial epigenome. Copyright © 2014 Elsevier Ltd. All rights reserved.

Physical Model of the Genotype-to-Phenotype Map of Proteins

NASA Astrophysics Data System (ADS)

Tlusty, Tsvi; Libchaber, Albert; Eckmann, Jean-Pierre

2017-04-01

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to function. We therefore treat protein as learning amorphous matter that evolves towards such a mechanical function: Genes are binary sequences that encode the connectivity of the amino acid network that makes a protein. The gene is evolved until the network forms a shear band across the protein, which allows for long-range, soft modes required for protein function. The evolution reduces the high-dimensional sequence space to a low-dimensional space of mechanical modes, in accord with the observed dimensional reduction between genotype and phenotype of proteins. Spectral analysis of the space of 1 06 solutions shows a strong correspondence between localization around the shear band of both mechanical modes and the sequence structure. Specifically, our model shows how mutations are correlated among amino acids whose interactions determine the functional mode.

Chromosome evolution with naked eye: Palindromic context of the life origin

NASA Astrophysics Data System (ADS)

Larionov, Sergei; Loskutov, Alexander; Ryadchenko, Eugeny

2008-03-01

Based on the representation of the DNA sequence as a two-dimensional (2D) plane walk, we consider the problem of identification and comparison of functional and structural organizations of chromosomes of different organisms. According to the characteristic design of 2D walks we identify telomere sites, palindromes of various sizes and complexity, areas of ribosomal RNA, transposons, as well as diverse satellite sequences. As an interesting result of the application of the 2D walk method, a new duplicated gigantic palindrome in the X human chromosome is detected. A schematic mechanism leading to the formation of such a duplicated palindrome is proposed. Analysis of a large number of the different genomes shows that some chromosomes (or their fragments) of various species appear as imperfect gigantic palindromes, which are disintegrated by many inversions and the mutation drift on different scales. A spread occurrence of these types of sequences in the numerous chromosomes allows us to develop a new insight of some accepted points of the genome evolution in the prebiotic phase.

A DNA 'barcode blitz': rapid digitization and sequencing of a natural history collection.

PubMed

Hebert, Paul D N; Dewaard, Jeremy R; Zakharov, Evgeny V; Prosser, Sean W J; Sones, Jayme E; McKeown, Jaclyn T A; Mantle, Beth; La Salle, John

2013-01-01

DNA barcoding protocols require the linkage of each sequence record to a voucher specimen that has, whenever possible, been authoritatively identified. Natural history collections would seem an ideal resource for barcode library construction, but they have never seen large-scale analysis because of concerns linked to DNA degradation. The present study examines the strength of this barrier, carrying out a comprehensive analysis of moth and butterfly (Lepidoptera) species in the Australian National Insect Collection. Protocols were developed that enabled tissue samples, specimen data, and images to be assembled rapidly. Using these methods, a five-person team processed 41,650 specimens representing 12,699 species in 14 weeks. Subsequent molecular analysis took about six months, reflecting the need for multiple rounds of PCR as sequence recovery was impacted by age, body size, and collection protocols. Despite these variables and the fact that specimens averaged 30.4 years old, barcode records were obtained from 86% of the species. In fact, one or more barcode compliant sequences (>487 bp) were recovered from virtually all species represented by five or more individuals, even when the youngest was 50 years old. By assembling specimen images, distributional data, and DNA barcode sequences on a web-accessible informatics platform, this study has greatly advanced accessibility to information on thousands of species. Moreover, much of the specimen data became publically accessible within days of its acquisition, while most sequence results saw release within three months. As such, this study reveals the speed with which DNA barcode workflows can mobilize biodiversity data, often providing the first web-accessible information for a species. These results further suggest that existing collections can enable the rapid development of a comprehensive DNA barcode library for the most diverse compartment of terrestrial biodiversity - insects.

MACSIMS : multiple alignment of complete sequences information management system

PubMed Central

Thompson, Julie D; Muller, Arnaud; Waterhouse, Andrew; Procter, Jim; Barton, Geoffrey J; Plewniak, Frédéric; Poch, Olivier

2006-01-01

Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at . PMID:16792820

The DNA Methylome of Human Peripheral Blood Mononuclear Cells

PubMed Central

Ye, Mingzhi; Zheng, Hancheng; Yu, Jian; Wu, Honglong; Sun, Jihua; Zhang, Hongyu; Chen, Quan; Luo, Ruibang; Chen, Minfeng; He, Yinghua; Jin, Xin; Zhang, Qinghui; Yu, Chang; Zhou, Guangyu; Sun, Jinfeng; Huang, Yebo; Zheng, Huisong; Cao, Hongzhi; Zhou, Xiaoyu; Guo, Shicheng; Hu, Xueda; Li, Xin; Kristiansen, Karsten; Bolund, Lars; Xu, Jiujin; Wang, Wen; Yang, Huanming; Wang, Jian; Li, Ruiqiang; Beck, Stephan; Wang, Jun; Zhang, Xiuqing

2010-01-01

DNA methylation plays an important role in biological processes in human health and disease. Recent technological advances allow unbiased whole-genome DNA methylation (methylome) analysis to be carried out on human cells. Using whole-genome bisulfite sequencing at 24.7-fold coverage (12.3-fold per strand), we report a comprehensive (92.62%) methylome and analysis of the unique sequences in human peripheral blood mononuclear cells (PBMC) from the same Asian individual whose genome was deciphered in the YH project. PBMC constitute an important source for clinical blood tests world-wide. We found that 68.4% of CpG sites and <0.2% of non-CpG sites were methylated, demonstrating that non-CpG cytosine methylation is minor in human PBMC. Analysis of the PBMC methylome revealed a rich epigenomic landscape for 20 distinct genomic features, including regulatory, protein-coding, non-coding, RNA-coding, and repeat sequences. Integration of our methylome data with the YH genome sequence enabled a first comprehensive assessment of allele-specific methylation (ASM) between the two haploid methylomes of any individual and allowed the identification of 599 haploid differentially methylated regions (hDMRs) covering 287 genes. Of these, 76 genes had hDMRs within 2 kb of their transcriptional start sites of which >80% displayed allele-specific expression (ASE). These data demonstrate that ASM is a recurrent phenomenon and is highly correlated with ASE in human PBMCs. Together with recently reported similar studies, our study provides a comprehensive resource for future epigenomic research and confirms new sequencing technology as a paradigm for large-scale epigenomics studies. PMID:21085693

Microfluidic single-cell whole-transcriptome sequencing.

PubMed

Streets, Aaron M; Zhang, Xiannian; Cao, Chen; Pang, Yuhong; Wu, Xinglong; Xiong, Liang; Yang, Lu; Fu, Yusi; Zhao, Liang; Tang, Fuchou; Huang, Yanyi

2014-05-13

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

Transposon diversity in Arabidopsis thaliana

PubMed Central

Le, Quang Hien; Wright, Stephen; Yu, Zhihui; Bureau, Thomas

2000-01-01

Recent availability of extensive genome sequence information offers new opportunities to analyze genome organization, including transposon diversity and accumulation, at a level of resolution that was previously unattainable. In this report, we used sequence similarity search and analysis protocols to perform a fine-scale analysis of a large sample (≈17.2 Mb) of the Arabidopsis thaliana (Columbia) genome for transposons. Consistent with previous studies, we report that the A. thaliana genome harbors diverse representatives of most known superfamilies of transposons. However, our survey reveals a higher density of transposons of which over one-fourth could be classified into a single novel transposon family designated as Basho, which appears unrelated to any previously known superfamily. We have also identified putative transposase-coding ORFs for miniature inverted-repeat transposable elements (MITEs), providing clues into the mechanism of mobility and origins of the most abundant transposons associated with plant genes. In addition, we provide evidence that most mined transposons have a clear distribution preference for A + T-rich sequences and show that structural variation for many mined transposons is partly due to interelement recombination. Taken together, these findings further underscore the complexity of transposons within the compact genome of A. thaliana. PMID:10861007

SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

PubMed

Brannan, Kristopher W; Jin, Wenhao; Huelga, Stephanie C; Banks, Charles A S; Gilmore, Joshua M; Florens, Laurence; Washburn, Michael P; Van Nostrand, Eric L; Pratt, Gabriel A; Schwinn, Marie K; Daniels, Danette L; Yeo, Gene W

2016-10-20

RNA metabolism is controlled by an expanding, yet incomplete, catalog of RNA-binding proteins (RBPs), many of which lack characterized RNA binding domains. Approaches to expand the RBP repertoire to discover non-canonical RBPs are currently needed. Here, HaloTag fusion pull down of 12 nuclear and cytoplasmic RBPs followed by quantitative mass spectrometry (MS) demonstrates that proteins interacting with multiple RBPs in an RNA-dependent manner are enriched for RBPs. This motivated SONAR, a computational approach that predicts RNA binding activity by analyzing large-scale affinity precipitation-MS protein-protein interactomes. Without relying on sequence or structure information, SONAR identifies 1,923 human, 489 fly, and 745 yeast RBPs, including over 100 human candidate RBPs that contain zinc finger domains. Enhanced CLIP confirms RNA binding activity and identifies transcriptome-wide RNA binding sites for SONAR-predicted RBPs, revealing unexpected RNA binding activity for disease-relevant proteins and DNA binding proteins. Copyright © 2016 Elsevier Inc. All rights reserved.

aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity.

PubMed

Kuraku, Shigehiro; Zmasek, Christian M; Nishimura, Osamu; Katoh, Kazutaka

2013-07-01

We report a new web server, aLeaves (http://aleaves.cdb.riken.jp/), for homologue collection from diverse animal genomes. In molecular comparative studies involving multiple species, orthology identification is the basis on which most subsequent biological analyses rely. It can be achieved most accurately by explicit phylogenetic inference. More and more species are subjected to large-scale sequencing, but the resultant resources are scattered in independent project-based, and multi-species, but separate, web sites. This complicates data access and is becoming a serious barrier to the comprehensiveness of molecular phylogenetic analysis. aLeaves, launched to overcome this difficulty, collects sequences similar to an input query sequence from various data sources. The collected sequences can be passed on to the MAFFT sequence alignment server (http://mafft.cbrc.jp/alignment/server/), which has been significantly improved in interactivity. This update enables to switch between (i) sequence selection using the Archaeopteryx tree viewer, (ii) multiple sequence alignment and (iii) tree inference. This can be performed as a loop until one reaches a sensible data set, which minimizes redundancy for better visibility and handling in phylogenetic inference while covering relevant taxa. The work flow achieved by the seamless link between aLeaves and MAFFT provides a convenient online platform to address various questions in zoology and evolutionary biology.

Large-scale contamination of microbial isolate genomes by Illumina PhiX control.

PubMed

Mukherjee, Supratim; Huntemann, Marcel; Ivanova, Natalia; Kyrpides, Nikos C; Pati, Amrita

2015-01-01

With the rapid growth and development of sequencing technologies, genomes have become the new go-to for exploring solutions to some of the world's biggest challenges such as searching for alternative energy sources and exploration of genomic dark matter. However, progress in sequencing has been accompanied by its share of errors that can occur during template or library preparation, sequencing, imaging or data analysis. In this study we screened over 18,000 publicly available microbial isolate genome sequences in the Integrated Microbial Genomes database and identified more than 1000 genomes that are contaminated with PhiX, a control frequently used during Illumina sequencing runs. Approximately 10% of these genomes have been published in literature and 129 contaminated genomes were sequenced under the Human Microbiome Project. Raw sequence reads are prone to contamination from various sources and are usually eliminated during downstream quality control steps. Detection of PhiX contaminated genomes indicates a lapse in either the application or effectiveness of proper quality control measures. The presence of PhiX contamination in several publicly available isolate genomes can result in additional errors when such data are used in comparative genomics analyses. Such contamination of public databases have far-reaching consequences in the form of erroneous data interpretation and analyses, and necessitates better measures to proofread raw sequences before releasing them to the broader scientific community.

aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity

PubMed Central

Kuraku, Shigehiro; Zmasek, Christian M.; Nishimura, Osamu; Katoh, Kazutaka

2013-01-01

We report a new web server, aLeaves (http://aleaves.cdb.riken.jp/), for homologue collection from diverse animal genomes. In molecular comparative studies involving multiple species, orthology identification is the basis on which most subsequent biological analyses rely. It can be achieved most accurately by explicit phylogenetic inference. More and more species are subjected to large-scale sequencing, but the resultant resources are scattered in independent project-based, and multi-species, but separate, web sites. This complicates data access and is becoming a serious barrier to the comprehensiveness of molecular phylogenetic analysis. aLeaves, launched to overcome this difficulty, collects sequences similar to an input query sequence from various data sources. The collected sequences can be passed on to the MAFFT sequence alignment server (http://mafft.cbrc.jp/alignment/server/), which has been significantly improved in interactivity. This update enables to switch between (i) sequence selection using the Archaeopteryx tree viewer, (ii) multiple sequence alignment and (iii) tree inference. This can be performed as a loop until one reaches a sensible data set, which minimizes redundancy for better visibility and handling in phylogenetic inference while covering relevant taxa. The work flow achieved by the seamless link between aLeaves and MAFFT provides a convenient online platform to address various questions in zoology and evolutionary biology. PMID:23677614

The sequence of sequencers: The history of sequencing DNA.

PubMed

Heather, James M; Chain, Benjamin

2016-01-01

Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

BAC-pool sequencing and analysis of large segments of A12 and D12 homoeologous chromosomes in Upland cotton

USDA-ARS?s Scientific Manuscript database

New and emerging next generation sequencing technologies have reduced sequencing costs, but there is room for additional approaches that can be applied to complex polyploid plant genomes. Large (about 2.5GB) and highly repetitive tetraploid genome of G. hirsutum is still cost-intensive with traditi...

Whole Genome Amplification and Reduced-Representation Genome Sequencing of Schistosoma japonicum Miracidia.

PubMed

Shortt, Jonathan A; Card, Daren C; Schield, Drew R; Liu, Yang; Zhong, Bo; Castoe, Todd A; Carlton, Elizabeth J; Pollock, David D

2017-01-01

In areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies. We applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample. This high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes.

A Web-Hosted R Workflow to Simplify and Automate the Analysis of 16S NGS Data

EPA Science Inventory

Next-Generation Sequencing (NGS) produces large data sets that include tens-of-thousands of sequence reads per sample. For analysis of bacterial diversity, 16S NGS sequences are typically analyzed in a workflow that containing best-of-breed bioinformatics packages that may levera...