The technology and biology of single-cell RNA sequencing.

PubMed

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

2015-05-21

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

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Indigenous and introduced potyviruses of legumes and Passiflora spp. from Australia: biological properties and comparison of coat protein sequences

USDA-ARS?s Scientific Manuscript database

Coat protein sequences of 33 Potyvirus isolates from legume and Passiflora spp. were sequenced to determine the identity of infecting viruses. Phylogenetic analysis of the sequences revealed the presence of seven distinct virus species....

Noncoding sequence classification based on wavelet transform analysis: part II

NASA Astrophysics Data System (ADS)

Paredes, O.; Strojnik, M.; Romo-Vázquez, R.; Vélez-Pérez, H.; Ranta, R.; Garcia-Torales, G.; Scholl, M. K.; Morales, J. A.

2017-09-01

DNA sequences in human genome can be divided into the coding and noncoding ones. We hypothesize that the characteristic periodicities of the noncoding sequences are related to their function. We describe the procedure to identify these characteristic periodicities using the wavelet analysis. Our results show that three groups of noncoding sequences, each one with different biological function, may be differentiated by their wavelet coefficients within specific frequency range.

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing

PubMed Central

2012-01-01

Background RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Results Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. Conclusions This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates. PMID:22985019

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing.

PubMed

Robles, José A; Qureshi, Sumaira E; Stephen, Stuart J; Wilson, Susan R; Burden, Conrad J; Taylor, Jennifer M

2012-09-17

RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates.

Information theory applications for biological sequence analysis.

PubMed

Vinga, Susana

2014-05-01

Information theory (IT) addresses the analysis of communication systems and has been widely applied in molecular biology. In particular, alignment-free sequence analysis and comparison greatly benefited from concepts derived from IT, such as entropy and mutual information. This review covers several aspects of IT applications, ranging from genome global analysis and comparison, including block-entropy estimation and resolution-free metrics based on iterative maps, to local analysis, comprising the classification of motifs, prediction of transcription factor binding sites and sequence characterization based on linguistic complexity and entropic profiles. IT has also been applied to high-level correlations that combine DNA, RNA or protein features with sequence-independent properties, such as gene mapping and phenotype analysis, and has also provided models based on communication systems theory to describe information transmission channels at the cell level and also during evolutionary processes. While not exhaustive, this review attempts to categorize existing methods and to indicate their relation with broader transversal topics such as genomic signatures, data compression and complexity, time series analysis and phylogenetic classification, providing a resource for future developments in this promising area.

Bayesian selection of Markov models for symbol sequences: application to microsaccadic eye movements.

PubMed

Bettenbühl, Mario; Rusconi, Marco; Engbert, Ralf; Holschneider, Matthias

2012-01-01

Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems.

PROFESS: a PROtein Function, Evolution, Structure and Sequence database

PubMed Central

Triplet, Thomas; Shortridge, Matthew D.; Griep, Mark A.; Stark, Jaime L.; Powers, Robert; Revesz, Peter

2010-01-01

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are ∼1100 molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein–protein interaction networks. Database URL: http://cse.unl.edu/∼profess/ PMID:20624718

Applications and Extensions of pClust to Big Microbial Proteomic Data

ERIC Educational Resources Information Center

Lockwood, Svetlana

2016-01-01

The goal of biological sciences is to understand the biomolecular mechanics of living organisms. Proteins serve as the foundation for organisms functional analysis and sequence analysis has shown to be invaluable in answering questions about individual organisms. The first step in any sequence analysis is alignment and it is common that even…

Meta-analysis of RNA-Seq data across cohorts in a multi-season feed efficiency study of crossbred beef steers accounts for biological and technical variability within season

USDA-ARS?s Scientific Manuscript database

High-throughput sequencing is often used for studies of the transcriptome, particularly for comparisons between experimental conditions. Due to sequencing costs, a limited number of biological replicates are typically considered in such experiments, leading to low detection power for differential ex...

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

PubMed

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

PubMed

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Draft sequencing and comparative genomics of Xylella fastidiosa strains reveal novel biological insights.

PubMed

Bhattacharyya, Anamitra; Stilwagen, Stephanie; Reznik, Gary; Feil, Helene; Feil, William S; Anderson, Iain; Bernal, Axel; D'Souza, Mark; Ivanova, Natalia; Kapatral, Vinayak; Larsen, Niels; Los, Tamara; Lykidis, Athanasios; Selkov, Eugene; Walunas, Theresa L; Purcell, Alexander; Edwards, Rob A; Hawkins, Trevor; Haselkorn, Robert; Overbeek, Ross; Kyrpides, Nikos C; Predki, Paul F

2002-10-01

Draft sequencing is a rapid and efficient method for determining the near-complete sequence of microbial genomes. Here we report a comparative analysis of one complete and two draft genome sequences of the phytopathogenic bacterium, Xylella fastidiosa, which causes serious disease in plants, including citrus, almond, and oleander. We present highlights of an in silico analysis based on a comparison of reconstructions of core biological subsystems. Cellular pathway reconstructions have been used to identify a small number of genes, which are likely to reside within the draft genomes but are not captured in the draft assembly. These represented only a small fraction of all genes and were predominantly large and small ribosomal subunit protein components. By using this approach, some of the inherent limitations of draft sequence can be significantly reduced. Despite the incomplete nature of the draft genomes, it is possible to identify several phage-related genes, which appear to be absent from the draft genomes and not the result of insufficient sequence sampling. This region may therefore identify potential host-specific functions. Based on this first functional reconstruction of a phytopathogenic microbe, we spotlight an unusual respiration machinery as a potential target for biological control. We also predicted and developed a new defined growth medium for Xylella.

Joint analysis of bacterial DNA methylation, predicted promoter and regulation motifs for biological significance

USDA-ARS?s Scientific Manuscript database

Advances in long-read, single molecule real-time sequencing technology and analysis software over the last two years has enabled the efficient production of closed bacterial genome sequences. However, consistent annotation of these genomes has lagged behind the ability to create them, while the avai...

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.

Next Generation Sequencing Technology and Genomewide Data Analysis: Perspectives for Retinal Research

PubMed Central

Chaitankar, Vijender; Karakülah, Gökhan; Ratnapriya, Rinki; Giuste, Felipe O.; Brooks, Matthew J.; Swaroop, Anand

2016-01-01

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well. PMID:27297499

Object-oriented parsing of biological databases with Python.

PubMed

Ramu, C; Gemünd, C; Gibson, T J

2000-07-01

While database activities in the biological area are increasing rapidly, rather little is done in the area of parsing them in a simple and object-oriented way. We present here an elegant, simple yet powerful way of parsing biological flat-file databases. We have taken EMBL, SWISSPROT and GENBANK as examples. EMBL and SWISS-PROT do not differ much in the format structure. GENBANK has a very different format structure than EMBL and SWISS-PROT. Extracting the desired fields in an entry (for example a sub-sequence with an associated feature) for later analysis is a constant need in the biological sequence-analysis community: this is illustrated with tools to make new splice-site databases. The interface to the parser is abstract in the sense that the access to all the databases is independent from their different formats, since parsing instructions are hidden.

Single Cell Analysis: From Technology to Biology and Medicine.

PubMed

Pan, Xinghua

2014-01-01

Single-cell analysis heralds a new era that allows "omics" analysis, notably genomics, transcriptomics, epigenomics and proteomics at the single-cell level. It enables the identification of the minor subpopulations that may play a critical role in a biological process of a population of cells, which conventionally are regarded as homogeneous. It provides an ultra-sensitive tool to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. It also facilitates the clinical investigation of patients when a very low quantity or a single cell is available for analysis, such as noninvasive prenatal diagnosis and cancer screening, and genetic evaluation for in vitro fertilization. Within a few short years, single-cell analysis, especially whole genomic sequencing and transcriptomic sequencing, is becoming robust and broadly accessible, although not yet a routine practice. Here, with single cell RNA-seq emphasized, an overview of the discipline, progresses, and prospects of single-cell analysis and its applications in biology and medicine are given with a series of logic and theoretical considerations.

A comparison of students' achievement and attitude as a function of lecture/lab sequencing in a non-science majors introductory biology course

NASA Astrophysics Data System (ADS)

Hurst March, Robin Denise

This investigation compared student achievement and attitudes toward science from three different sequencing approaches used in teaching biology to nonscience students. The three sequencing approaches were the lecture course only, lecture/laboratory courses taken together, and laboratory with previously taken lecture approach. The purposes of this study were to determine if (1) a relationship exists between the Attitude Towards Science in School Assessment (ATSSA) scores (Germann, 1988) and biology achievement, (2) a difference exists among the ATSSA scores and sequencing, (3) a difference exists among the biology achievement scores and sequencing, and (4) the ATSSA is a reliable instrument of science attitude assessment for the undergraduate students in an introductory biology nonmajors laboratory and lecture courses at a research I institution during the fall semester 1996. Fifty-four students comprised the lecture only group, 90 students comprised the lecture and laboratory taken together approach, and 23 students comprised the laboratory only approach. Research questions addressed were (1) What are the differences in student biology achievement as a function of the three different methods of instruction? (2) What are the differences in student attitude towards science as a function of the three different methods of instruction? (3) What is the relationship between post-attitude (ATSSA) and biology achievement for each of the three methods of instruction? An analysis of variance utilized the mean posttest scores on the ATSSA and mean achievement scores as the dependent variables. The independent variables were the three different sequences of enrollment in introductory biology. At the.05 level of significance, it was found that no significant difference existed between the ATTS and laboratory/lecture sequence. At the.05 level of significance, it was found that no significant difference existed between achievement and laboratory/lecture sequence. A Pearson product moment correlation was used to see if a relationship existed between posttest ATSSA scores and achievement totals in each sequence. A significant relationship was noted between the ATSSA and achievement in each sequence that involved a laboratory component.

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

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

Method for high resolution magnetic resonance analysis using magic angle technique

DOEpatents

Wind, Robert A.; Hu, Jian Zhi

2003-11-25

A method of performing a magnetic resonance analysis of a biological object that includes placing the biological object in a main magnetic field and in a radio frequency field, the main magnetic field having a static field direction; rotating the biological object at a rotational frequency of less than about 100 Hz around an axis positioned at an angle of about 54.degree.44' relative to the main magnetic static field direction; pulsing the radio frequency to provide a sequence that includes a magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. According to another embodiment, the radio frequency is pulsed to provide a sequence capable of producing a spectrum that is substantially free of spinning sideband peaks.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis

PubMed Central

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

Design and Analysis of Single-Cell Sequencing Experiments.

PubMed

Grün, Dominic; van Oudenaarden, Alexander

2015-11-05

Recent advances in single-cell sequencing hold great potential for exploring biological systems with unprecedented resolution. Sequencing the genome of individual cells can reveal somatic mutations and allows the investigation of clonal dynamics. Single-cell transcriptome sequencing can elucidate the cell type composition of a sample. However, single-cell sequencing comes with major technical challenges and yields complex data output. In this Primer, we provide an overview of available methods and discuss experimental design and single-cell data analysis. We hope that these guidelines will enable a growing number of researchers to leverage the power of single-cell sequencing. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-05-25

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

Enabling next-gen sequencing and analysis at the USDA-ARS U.S. Meat Animal Research Center with MiniLIMS

USDA-ARS?s Scientific Manuscript database

There is a growing need to combine DNA sequencing technologies to address complex problems in genome biology. These genomic studies routinely generate voluminous image, sequence, and mapping files that should be associated with quality control information (gels, spectra, etc.), and other important ...

Understanding sequence similarity and framework analysis between centromere proteins using computational biology.

PubMed

Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S

2014-11-01

Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.

Interpreting the biological relevance of bioinformatic analyses with T-DNA sequence for protein allergenicity.

PubMed

Harper, B; McClain, S; Ganko, E W

2012-08-01

Global regulatory agencies require bioinformatic sequence analysis as part of their safety evaluation for transgenic crops. Analysis typically focuses on encoded proteins and adjacent endogenous flanking sequences. Recently, regulatory expectations have expanded to include all reading frames of the inserted DNA. The intent is to provide biologically relevant results that can be used in the overall assessment of safety. This paper evaluates the relevance of assessing the allergenic potential of all DNA reading frames found in common food genes using methods considered for the analysis of T-DNA sequences used in transgenic crops. FASTA and BLASTX algorithms were used to compare genes from maize, rice, soybean, cucumber, melon, watermelon, and tomato using international regulatory guidance. Results show that BLASTX for maize yielded 7254 alignments that exceeded allergen similarity thresholds and 210,772 alignments that matched eight or more consecutive amino acids with an allergen; other crops produced similar results. This analysis suggests that each nontransgenic crop has a much greater potential for allergenic risk than what has been observed clinically. We demonstrate that a meaningful safety assessment is unlikely to be provided by using methods with inherently high frequencies of false positive alignments when broadly applied to all reading frames of DNA sequence. Copyright © 2012 Elsevier Inc. All rights reserved.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

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

PubMed

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

2011-11-21

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

Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data

Treesearch

Jonathan M. Palmer; Michelle A. Jusino; Mark T. Banik; Daniel L. Lindner

2018-01-01

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer...

Sequence determination and analysis of the NSs genes of two tospoviruses.

PubMed

Hallwass, Mariana; Leastro, Mikhail O; Lima, Mirtes F; Inoue-Nagata, Alice K; Resende, Renato O

2012-03-01

The tospoviruses groundnut ringspot virus (GRSV) and zucchini lethal chlorosis virus (ZLCV) cause severe losses in many crops, especially in solanaceous and cucurbit species. In this study, the non-structural NSs gene and the 5'UTRs of these two biologically distinct tospoviruses were cloned and sequenced. The NSs sequence of GRSV and ZLCV were both 1,404 nucleotides long. Pairwise comparison showed that the NSs amino acid sequence of GRSV shared 69.6% identity with that of ZLCV and 75.9% identity with that of TSWV, while the NSs sequence of ZLCV and TSWV shared 67.9% identity. Phylogenetic analysis based on NSs sequences confirmed that these viruses cluster in the American clade.

Transcriptome Analysis and Development of SSR Molecular Markers in Glycyrrhiza uralensis Fisch.

PubMed Central

Liu, Yaling; Zhang, Pengfei; Song, Meiling; Hou, Junling; Qing, Mei; Wang, Wenquan; Liu, Chunsheng

2015-01-01

Licorice is an important traditional Chinese medicine with clinical and industrial applications. Genetic resources of licorice are insufficient for analysis of molecular biology and genetic functions; as such, transcriptome sequencing must be conducted for functional characterization and development of molecular markers. In this study, transcriptome sequencing on the Illumina HiSeq 2500 sequencing platform generated a total of 5.41 Gb clean data. De novo assembly yielded a total of 46,641 unigenes. Comparison analysis using BLAST showed that the annotations of 29,614 unigenes were conserved. Further study revealed 773 genes related to biosynthesis of secondary metabolites of licorice, 40 genes involved in biosynthesis of the terpenoid backbone, and 16 genes associated with biosynthesis of glycyrrhizic acid. Analysis of unigenes larger than 1 Kb with a length of 11,702 nt presented 7,032 simple sequence repeats (SSR). Sixty-four of 69 randomly designed and synthesized SSR pairs were successfully amplified, 33 pairs of primers were polymorphism in in Glycyrrhiza uralensis Fisch., Glycyrrhiza inflata Bat., Glycyrrhiza glabra L. and Glycyrrhiza pallidiflora Maxim. This study not only presents the molecular biology data of licorice but also provides a basis for genetic diversity research and molecular marker-assisted breeding of licorice. PMID:26571372

Complexity and Entropy Analysis of DNMT1 Gene

USDA-ARS?s Scientific Manuscript database

Background: The application of complexity information on DNA sequence and protein in biological processes are well established in this study. Available sequences for DNMT1 gene, which is a maintenance methyltransferase is responsible for copying DNA methylation patterns to the daughter strands durin...

Nanopore-based fourth-generation DNA sequencing technology.

PubMed

Feng, Yanxiao; Zhang, Yuechuan; Ying, Cuifeng; Wang, Deqiang; Du, Chunlei

2015-02-01

Nanopore-based sequencers, as the fourth-generation DNA sequencing technology, have the potential to quickly and reliably sequence the entire human genome for less than $1000, and possibly for even less than $100. The single-molecule techniques used by this technology allow us to further study the interaction between DNA and protein, as well as between protein and protein. Nanopore analysis opens a new door to molecular biology investigation at the single-molecule scale. In this article, we have reviewed academic achievements in nanopore technology from the past as well as the latest advances, including both biological and solid-state nanopores, and discussed their recent and potential applications. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Biological pattern and transcriptomic exploration and phylogenetic analysis in the odd floral architecture tree: Helwingia willd.

PubMed

Sun, Cheng; Yu, Guoliang; Bao, Manzhu; Zheng, Bo; Ning, Guogui

2014-06-27

Odd traits in few of plant species usually implicate potential biology significances in plant evolutions. The genus Helwingia Willd, a dioecious medical shrub in Aquifoliales order, has an odd floral architecture-epiphyllous inflorescence. The potential significances and possible evolutionary origin of this specie are not well understood due to poorly available data of biological and genetic studies. In addition, the advent of genomics-based technologies has widely revolutionized plant species with unknown genomic information. Morphological and biological pattern were detailed via anatomical and pollination analyses. An RNA sequencing based transcriptomic analysis were undertaken and a high-resolution phylogenetic analysis was conducted based on single-copy genes in more than 80 species of seed plants, including H. japonica. It is verified that a potential fusion of rachis to the leaf midvein facilitates insect pollination. RNA sequencing yielded a total of 111450 unigenes; half of them had significant similarity with proteins in the public database, and 20281 unigenes were mapped to 119 pathways. Deduced from the phylogenetic analysis based on single-copy genes, the group of Helwingia is closer with Euasterids II and rather than Euasterids, congruent with previous reports using plastid sequences. The odd flower architecture make H. Willd adapt to insect pollination by hosting those insects larger than the flower in size via leave, which has little common character that other insect pollination plants hold. Further the present transcriptome greatly riches genomics information of Helwingia species and nucleus genes based phylogenetic analysis also greatly improve the resolution and robustness of phylogenetic reconstruction in H. japonica.

A Novel Cylindrical Representation for Characterizing Intrinsic Properties of Protein Sequences.

PubMed

Yu, Jia-Feng; Dou, Xiang-Hua; Wang, Hong-Bo; Sun, Xiao; Zhao, Hui-Ying; Wang, Ji-Hua

2015-06-22

The composition and sequence order of amino acid residues are the two most important characteristics to describe a protein sequence. Graphical representations facilitate visualization of biological sequences and produce biologically useful numerical descriptors. In this paper, we propose a novel cylindrical representation by placing the 20 amino acid residue types in a circle and sequence positions along the z axis. This representation allows visualization of the composition and sequence order of amino acids at the same time. Ten numerical descriptors and one weighted numerical descriptor have been developed to quantitatively describe intrinsic properties of protein sequences on the basis of the cylindrical model. Their applications to similarity/dissimilarity analysis of nine ND5 proteins indicated that these numerical descriptors are more effective than several classical numerical matrices. Thus, the cylindrical representation obtained here provides a new useful tool for visualizing and charactering protein sequences. An online server is available at http://biophy.dzu.edu.cn:8080/CNumD/input.jsp .

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

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

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

Genetic Code Analysis Toolkit: A novel tool to explore the coding properties of the genetic code and DNA sequences

NASA Astrophysics Data System (ADS)

Kraljić, K.; Strüngmann, L.; Fimmel, E.; Gumbel, M.

2018-01-01

The genetic code is degenerated and it is assumed that redundancy provides error detection and correction mechanisms in the translation process. However, the biological meaning of the code's structure is still under current research. This paper presents a Genetic Code Analysis Toolkit (GCAT) which provides workflows and algorithms for the analysis of the structure of nucleotide sequences. In particular, sets or sequences of codons can be transformed and tested for circularity, comma-freeness, dichotomic partitions and others. GCAT comes with a fertile editor custom-built to work with the genetic code and a batch mode for multi-sequence processing. With the ability to read FASTA files or load sequences from GenBank, the tool can be used for the mathematical and statistical analysis of existing sequence data. GCAT is Java-based and provides a plug-in concept for extensibility. Availability: Open source Homepage:http://www.gcat.bio/

Use of mutation spectra analysis software.

PubMed

Rogozin, I; Kondrashov, F; Glazko, G

2001-02-01

The study and comparison of mutation(al) spectra is an important problem in molecular biology, because these spectra often reflect on important features of mutations and their fixation. Such features include the interaction of DNA with various mutagens, the function of repair/replication enzymes, and properties of target proteins. It is known that mutability varies significantly along nucleotide sequences, such that mutations often concentrate at certain positions, called "hotspots," in a sequence. In this paper, we discuss in detail two approaches for mutation spectra analysis: the comparison of mutation spectra with a HG-PUBL program, (FTP: sunsite.unc.edu/pub/academic/biology/dna-mutations/hyperg) and hotspot prediction with the CLUSTERM program (www.itba.mi.cnr.it/webmutation; ftp.bionet.nsc.ru/pub/biology/dbms/clusterm.zip). Several other approaches for mutational spectra analysis, such as the analysis of a target protein structure, hotspot context revealing, multiple spectra comparisons, as well as a number of mutation databases are briefly described. Mutation spectra in the lacI gene of E. coli and the human p53 gene are used for illustration of various difficulties of such analysis. Copyright 2001 Wiley-Liss, Inc.

Ecological literacy through critical/place-based pedagogy in the environmental studies program at a small liberal arts college

NASA Astrophysics Data System (ADS)

Beeman-Cadwallader, Nicole

In 2007 Pioneer High School, a public school in Whittier, California changed the sequence of its science courses from the Traditional Biology-Chemistry-Physics (B-C-P) to Biology-Physics-Chemistry (B-P-C), or "Physics Second." The California Standards Tests (CSTs) scores in Physics and Chemistry from 2004-2012 were used to determine if there were any effects of the Physics Second sequencing on student achievement in those courses. The data was also used to determine whether the Physics Second sequence had an effect on performance in Physics and Chemistry based on gender. Independent t tests and chi-square analysis of the data determined an improvement in student performance in Chemistry but not Physics. The 2x2 Factorial ANOVA analysis revealed that in Physics male students performed better on the CSTs than their female peers. In Chemistry, it was noted that male and female students performed equally well. Neither finding was a result ofthe change to the "Physics Second" sequencing.

Fractals in biology and medicine

NASA Technical Reports Server (NTRS)

Havlin, S.; Buldyrev, S. V.; Goldberger, A. L.; Mantegna, R. N.; Ossadnik, S. M.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

Our purpose is to describe some recent progress in applying fractal concepts to systems of relevance to biology and medicine. We review several biological systems characterized by fractal geometry, with a particular focus on the long-range power-law correlations found recently in DNA sequences containing noncoding material. Furthermore, we discuss the finding that the exponent alpha quantifying these long-range correlations ("fractal complexity") is 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 normal heart is characterized by long-range "anticorrelations" which are absent in the diseased heart.

Affordable Hands-On DNA Sequencing and Genotyping: An Exercise for Teaching DNA Analysis to Undergraduates

ERIC Educational Resources Information Center

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C…

Ancient dna from pleistocene fossils: Preservation, recovery, and utility of ancient genetic information for quaternary research

NASA Astrophysics Data System (ADS)

Yang, Hong

Until recently, recovery and analysis of genetic information encoded in ancient DNA sequences from Pleistocene fossils were impossible. Recent advances in molecular biology offered technical tools to obtain ancient DNA sequences from well-preserved Quaternary fossils and opened the possibilities to directly study genetic changes in fossil species to address various biological and paleontological questions. Ancient DNA studies involving Pleistocene fossil material and ancient DNA degradation and preservation in Quaternary deposits are reviewed. The molecular technology applied to isolate, amplify, and sequence ancient DNA is also presented. Authentication of ancient DNA sequences and technical problems associated with modern and ancient DNA contamination are discussed. As illustrated in recent studies on ancient DNA from proboscideans, it is apparent that fossil DNA sequence data can shed light on many aspects of Quaternary research such as systematics and phylogeny. conservation biology, evolutionary theory, molecular taphonomy, and forensic sciences. Improvement of molecular techniques and a better understanding of DNA degradation during fossilization are likely to build on current strengths and to overcome existing problems, making fossil DNA data a unique source of information for Quaternary scientists.

BCM Search Launcher--an integrated interface to molecular biology data base search and analysis services available on the World Wide Web.

PubMed

Smith, R F; Wiese, B A; Wojzynski, M K; Davison, D B; Worley, K C

1996-05-01

The BCM Search Launcher is an integrated set of World Wide Web (WWW) pages that organize molecular biology-related search and analysis services available on the WWW by function, and provide a single point of entry for related searches. The Protein Sequence Search Page, for example, provides a single sequence entry form for submitting sequences to WWW servers that offer remote access to a variety of different protein sequence search tools, including BLAST, FASTA, Smith-Waterman, BEAUTY, PROSITE, and BLOCKS searches. Other Launch pages provide access to (1) nucleic acid sequence searches, (2) multiple and pair-wise sequence alignments, (3) gene feature searches, (4) protein secondary structure prediction, and (5) miscellaneous sequence utilities (e.g., six-frame translation). The BCM Search Launcher also provides a mechanism to extend the utility of other WWW services by adding supplementary hypertext links to results returned by remote servers. For example, links to the NCBI's Entrez data base and to the Sequence Retrieval System (SRS) are added to search results returned by the NCBI's WWW BLAST server. These links provide easy access to auxiliary information, such as Medline abstracts, that can be extremely helpful when analyzing BLAST data base hits. For new or infrequent users of sequence data base search tools, we have preset the default search parameters to provide the most informative first-pass sequence analysis possible. We have also developed a batch client interface for Unix and Macintosh computers that allows multiple input sequences to be searched automatically as a background task, with the results returned as individual HTML documents directly to the user's system. The BCM Search Launcher and batch client are available on the WWW at URL http:@gc.bcm.tmc.edu:8088/search-launcher.html.

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

PubMed

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

2017-08-18

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

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

[Big Data Revolution or Data Hubris? : On the Data Positivism of Molecular Biology].

PubMed

Gramelsberger, Gabriele

2017-12-01

Genome data, the core of the 2008 proclaimed big data revolution in biology, are automatically generated and analyzed. The transition from the manual laboratory practice of electrophoresis sequencing to automated DNA-sequencing machines and software-based analysis programs was completed between 1982 and 1992. This transition facilitated the first data deluge, which was considerably increased by the second and third generation of DNA-sequencers during the 2000s. However, the strategies for evaluating sequence data were also transformed along with this transition. The paper explores both the computational strategies of automation, as well as the data evaluation culture connected with it, in order to provide a complete picture of the complexity of today's data generation and its intrinsic data positivism. This paper is thereby guided by the question, whether this data positivism is the basis of the big data revolution of molecular biology announced today, or it marks the beginning of its data hubris.

Combining partially ranked data in plant breeding and biology: II. Analysis with Rasch model.

USDA-ARS?s Scientific Manuscript database

Many years of breeding experiments, germplasm screening, and molecular biologic experimentation have generated volumes of sequence, genotype, and phenotype information that have been stored in public data repositories. These resources afford genetic and genomic researchers the opportunity to handle ...

Differentiation of closely related but biologically distinct cherry isolates of Prunus necrotic ringspot virus by polymerase chain reaction.

PubMed

Hammond, R W; Crosslin, J M; Pasini, R; Howell, W E; Mink, G I

1999-07-01

Prunus necrotic ringspot ilarvirus (PNRSV) exists as a number of biologically distinct variants which differ in host specificity, serology, and pathology. Previous nucleotide sequence alignment and phylogenetic analysis of cloned reverse transcription-polymerase chain reaction (RT-PCR) products of several biologically distinct sweet cherry isolates revealed correlations between symptom type and the nucleotide and amino acid sequences of the 3a (putative movement protein) and 3b (coat protein) open reading frames. Based upon this analysis, RT-PCR assays have been developed that can identify isolates displaying different symptoms and serotypes. The incorporation of primers in a multiplex PCR protocol permits rapid detection and discrimination among the strains. The results of PCR amplification using type-specific primers that amplify a portion of the coat protein gene demonstrate that the primer-selection procedure developed for PNRSV constitutes a reliable method of viral strain discrimination in cherry for disease control and will also be useful for examining biological diversity within the PNRSV virus group.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

A Topical Trajectory on Survival: An Analysis of Link-Making in a Sequence of Lessons on Evolution

ERIC Educational Resources Information Center

Rocksén, Miranda; Olander, Clas

2017-01-01

This study explores the concept of link-making in relation to communicative strategies applied in the teaching and studying of biological evolution. The analysis focused on video recordings of 11 lessons on biological evolution conducted in a Swedish 9th grade class of students aged 15 years. It reveals how the teacher and students connected…

DWARF – a data warehouse system for analyzing protein families

PubMed Central

Fischer, Markus; Thai, Quan K; Grieb, Melanie; Pleiss, Jürgen

2006-01-01

Background The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families. Description The data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of α/β-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families. Conclusion DWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering. PMID:17094801

Company profile: Complete Genomics Inc.

PubMed

Reid, Clifford

2011-02-01

Complete Genomics Inc. is a life sciences company that focuses on complete human genome sequencing. It is taking a completely different approach to DNA sequencing than other companies in the industry. Rather than building a general-purpose platform for sequencing all organisms and all applications, it has focused on a single application - complete human genome sequencing. The company's Complete Genomics Analysis Platform (CGA™ Platform) comprises an integrated package of biochemistry, instrumentation and software that sequences human genomes at the highest quality, lowest cost and largest scale available. Complete Genomics offers a turnkey service that enables customers to outsource their human genome sequencing to the company's genome sequencing center in Mountain View, CA, USA. Customers send in their DNA samples, the company does all the library preparation, DNA sequencing, assembly and variant analysis, and customers receive research-ready data that they can use for biological discovery.

The MIGenAS integrated bioinformatics toolkit for web-based sequence analysis

PubMed Central

Rampp, Markus; Soddemann, Thomas; Lederer, Hermann

2006-01-01

We describe a versatile and extensible integrated bioinformatics toolkit for the analysis of biological sequences over the Internet. The web portal offers convenient interactive access to a growing pool of chainable bioinformatics software tools and databases that are centrally installed and maintained by the RZG. Currently, supported tasks comprise sequence similarity searches in public or user-supplied databases, computation and validation of multiple sequence alignments, phylogenetic analysis and protein–structure prediction. Individual tools can be seamlessly chained into pipelines allowing the user to conveniently process complex workflows without the necessity to take care of any format conversions or tedious parsing of intermediate results. The toolkit is part of the Max-Planck Integrated Gene Analysis System (MIGenAS) of the Max Planck Society available at (click ‘Start Toolkit’). PMID:16844980

CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing data.

PubMed

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-07-01

Small RNAs (sRNAs) are 20-25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci. To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.

Cost-Effectiveness of Treatment Sequences of Chemotherapies and Targeted Biologics for Elderly Metastatic Colorectal Cancer Patients.

PubMed

Parikh, Rohan C; Du, Xianglin L; Robert, Morgan O; Lairson, David R

2017-01-01

Treatment patterns for metastatic colorectal cancer (mCRC) patients have changed considerably over the last decade with the introduction of new chemotherapies and targeted biologics. These treatments are often administered in various sequences with limited evidence regarding their cost-effectiveness. To conduct a pharmacoeconomic evaluation of commonly administered treatment sequences among elderly mCRC patients. A probabilistic discrete event simulation model assuming Weibull distribution was developed to evaluate the cost-effectiveness of the following common treatment sequences: (a) first-line oxaliplatin/irinotecan followed by second-line oxaliplatin/irinotecan + bevacizumab (OI-OIB); (b) first-line oxaliplatin/irinotecan + bevacizumab followed by second-line oxaliplatin/irinotecan + bevacizumab (OIB-OIB); (c) OI-OIB followed by a third-line targeted biologic (OI-OIB-TB); and (d) OIB-OIB followed by a third-line targeted biologic (OIB-OIB-TB). Input parameters for the model were primarily obtained from the Surveillance, Epidemiology, and End Results-Medicare linked dataset for incident mCRC patients aged 65 years and older diagnosed from January 2004 through December 2009. A probabilistic sensitivity analysis was performed to account for parameter uncertainty. Costs (2014 U.S. dollars) and effectiveness were discounted at an annual rate of 3%. In the base case analyses, at the willingness-to-pay (WTP) threshold of $100,000/quality-adjusted life-year (QALY) gained, the treatment sequence OIB-OIB (vs. OI-OIB) was not cost-effective with an incremental cost-effectiveness ratio (ICER) per patient of $119,007/QALY; OI-OIB-TB (vs. OIB-OIB) was dominated; and OIB-OIB-TB (vs. OIB-OIB) was not cost-effective with an ICER of $405,857/QALY. Results similar to the base case analysis were obtained assuming log-normal distribution. Cost-effectiveness acceptability curves derived from a probabilistic sensitivity analysis showed that at a WTP of $100,000/QALY gained, sequence OI-OIB was 34% cost-effective, followed by OIB-OIB (31%), OI-OIB-TB (20%), and OIB-OIB-TB (15%). Overall, survival increases marginally with the addition of targeted biologics, such as bevacizumab, at first line and third line at substantial costs. Treatment sequences with bevacizumab at first line and targeted biologics at third line may not be cost-effective at the commonly used threshold of $100,000/QALY gained, but a marginal decrease in the cost of bevacizumab may make treatment sequences with first-line bevacizumab cost-effective. Future economic evaluations should validate the study results using parameters from ongoing clinical trials. This study was supported in part by a grant from the Agency for Healthcare Research and Quality (R01-HS018956) and in part by a grant from the Cancer Prevention and Research Institute of Texas (RP130051), which were obtained by Du. The authors report no conflicts of interest. Study concept and design were primarily contributed by Parikh, along with the other authors. All authors participated in data collection, and Parikh took the lead in data interpretation and analysis, along with Lairson and Morgan, with assistance from Du. The manuscript was written primarily by Parikh, along with Lairson, Morgan, and Du, and revised by Parikh.

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

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

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

Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.

PubMed

Loh, Yong-Hwee Eddie; Shen, Li

2016-01-01

The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.

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

PubMed

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

2016-04-02

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

On avoided words, absent words, and their application to biological sequence analysis.

PubMed

Almirantis, Yannis; Charalampopoulos, Panagiotis; Gao, Jia; Iliopoulos, Costas S; Mohamed, Manal; Pissis, Solon P; Polychronopoulos, Dimitris

2017-01-01

The deviation of the observed frequency of a word w from its expected frequency in a given sequence x is used to determine whether or not the word is avoided . This concept is particularly useful in DNA linguistic analysis. The value of the deviation of w , denoted by [Formula: see text], effectively characterises the extent of a word by its edge contrast in the context in which it occurs. A word w of length [Formula: see text] is a [Formula: see text]-avoided word in x if [Formula: see text], for a given threshold [Formula: see text]. Notice that such a word may be completely absent from x . Hence, computing all such words naïvely can be a very time-consuming procedure, in particular for large k . In this article, we propose an [Formula: see text]-time and [Formula: see text]-space algorithm to compute all [Formula: see text]-avoided words of length k in a given sequence of length n over a fixed-sized alphabet. We also present a time-optimal [Formula: see text]-time algorithm to compute all [Formula: see text]-avoided words (of any length) in a sequence of length n over an integer alphabet of size [Formula: see text]. In addition, we provide a tight asymptotic upper bound for the number of [Formula: see text]-avoided words over an integer alphabet and the expected length of the longest one. We make available an implementation of our algorithm. Experimental results, using both real and synthetic data, show the efficiency and applicability of our implementation in biological sequence analysis. The systematic search for avoided words is particularly useful for biological sequence analysis. We present a linear-time and linear-space algorithm for the computation of avoided words of length k in a given sequence x . We suggest a modification to this algorithm so that it computes all avoided words of x , irrespective of their length, within the same time complexity. We also present combinatorial results with regards to avoided words and absent words.

Predicting PDZ domain mediated protein interactions from structure

PubMed Central

2013-01-01

Background PDZ domains are structural protein domains that recognize simple linear amino acid motifs, often at protein C-termini, and mediate protein-protein interactions (PPIs) in important biological processes, such as ion channel regulation, cell polarity and neural development. PDZ domain-peptide interaction predictors have been developed based on domain and peptide sequence information. Since domain structure is known to influence binding specificity, we hypothesized that structural information could be used to predict new interactions compared to sequence-based predictors. Results We developed a novel computational predictor of PDZ domain and C-terminal peptide interactions using a support vector machine trained with PDZ domain structure and peptide sequence information. Performance was estimated using extensive cross validation testing. We used the structure-based predictor to scan the human proteome for ligands of 218 PDZ domains and show that the predictions correspond to known PDZ domain-peptide interactions and PPIs in curated databases. The structure-based predictor is complementary to the sequence-based predictor, finding unique known and novel PPIs, and is less dependent on training–testing domain sequence similarity. We used a functional enrichment analysis of our hits to create a predicted map of PDZ domain biology. This map highlights PDZ domain involvement in diverse biological processes, some only found by the structure-based predictor. Based on this analysis, we predict novel PDZ domain involvement in xenobiotic metabolism and suggest new interactions for other processes including wound healing and Wnt signalling. Conclusions We built a structure-based predictor of PDZ domain-peptide interactions, which can be used to scan C-terminal proteomes for PDZ interactions. We also show that the structure-based predictor finds many known PDZ mediated PPIs in human that were not found by our previous sequence-based predictor and is less dependent on training–testing domain sequence similarity. Using both predictors, we defined a functional map of human PDZ domain biology and predict novel PDZ domain function. Users may access our structure-based and previous sequence-based predictors at http://webservice.baderlab.org/domains/POW. PMID:23336252

Visualising "Junk" DNA through Bioinformatics

ERIC Educational Resources Information Center

Elwess, Nancy L.; Latourelle, Sandra M.; Cauthorn, Olivia

2005-01-01

One of the hottest areas of science today is the field in which biology, information technology,and computer science are merged into a single discipline called bioinformatics. This field enables the discovery and analysis of biological data, including nucleotide and amino acid sequences that are easily accessed through the use of computers. As…

Analyzing Immunoglobulin Repertoires

PubMed Central

Chaudhary, Neha; Wesemann, Duane R.

2018-01-01

Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis. PMID:29593723

The Design and Analysis of Transposon-Insertion Sequencing Experiments

PubMed Central

Chao, Michael C.; Abel, Sören; Davis, Brigid M.; Waldor, Matthew K.

2016-01-01

Preface Transposon-insertion sequencing (TIS) is a powerful approach that can be widely applied to genome-wide definition of loci that are required for growth in diverse conditions. However, experimental design choices and stochastic biological processes can heavily influence the results of TIS experiments and affect downstream statistical analysis. Here, we discuss TIS experimental parameters and how these factors relate to the benefits and limitations of the various statistical frameworks that can be applied to computational analysis of TIS data. PMID:26775926

Bioinformatics approaches to single-cell analysis in developmental biology.

PubMed

Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

2016-03-01

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools.

PubMed

Liu, Zhandong; Zheng, W Jim; Allen, Genevera I; Liu, Yin; Ruan, Jianhua; Zhao, Zhongming

2017-10-03

The 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held on December 8-10, 2016 in Houston, Texas, USA. ICIBM included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics on 3D genomics structural analysis, next generation sequencing (NGS) analysis, computational drug discovery, medical informatics, cancer genomics, and systems biology. Here, we present a summary of the nine research articles selected from ICIBM 2016 program for publishing in BMC Bioinformatics.

Transcriptome-based differentiation of closely-related Miscanthus lines.

PubMed

Chouvarine, Philippe; Cooksey, Amanda M; McCarthy, Fiona M; Ray, David A; Baldwin, Brian S; Burgess, Shane C; Peterson, Daniel G

2012-01-01

Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations. A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence. Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation.

Microbes, metagenomes and marine mammals: enabling the next generation of scientist to enter the genomic era

PubMed Central

2013-01-01

Background The revolution in DNA sequencing technology continues unabated, and is affecting all aspects of the biological and medical sciences. The training and recruitment of the next generation of researchers who are able to use and exploit the new technology is severely lacking and potentially negatively influencing research and development efforts to advance genome biology. Here we present a cross-disciplinary course that provides undergraduate students with practical experience in running a next generation sequencing instrument through to the analysis and annotation of the generated DNA sequences. Results Many labs across world are installing next generation sequencing technology and we show that the undergraduate students produce quality sequence data and were excited to participate in cutting edge research. The students conducted the work flow from DNA extraction, library preparation, running the sequencing instrument, to the extraction and analysis of the data. They sequenced microbes, metagenomes, and a marine mammal, the Californian sea lion, Zalophus californianus. The students met sequencing quality controls, had no detectable contamination in the targeted DNA sequences, provided publication quality data, and became part of an international collaboration to investigate carcinomas in carnivores. Conclusions Students learned important skills for their future education and career opportunities, and a perceived increase in students’ ability to conduct independent scientific research was measured. DNA sequencing is rapidly expanding in the life sciences. Teaching undergraduates to use the latest technology to sequence genomic DNA ensures they are ready to meet the challenges of the genomic era and allows them to participate in annotating the tree of life. PMID:24007365

Computation of repetitions and regularities of biologically weighted sequences.

PubMed

Christodoulakis, M; Iliopoulos, C; Mouchard, L; Perdikuri, K; Tsakalidis, A; Tsichlas, K

2006-01-01

Biological weighted sequences are used extensively in molecular biology as profiles for protein families, in the representation of binding sites and often for the representation of sequences produced by a shotgun sequencing strategy. In this paper, we address three fundamental problems in the area of biologically weighted sequences: (i) computation of repetitions, (ii) pattern matching, and (iii) computation of regularities. Our algorithms can be used as basic building blocks for more sophisticated algorithms applied on weighted sequences.

Candidate causative mutation on BTA18 associated with calving and conformation traits in Holstein bulls

USDA-ARS?s Scientific Manuscript database

Complementing quantitative methods with sequence data analysis is a major goal of the post-genome era of biology. In this study, we analyzed Illumina HiSeq sequence data derived from 11 US Holstein bulls in order to identify putative causal mutations associated with calving and conformation traits. ...

BioLayout(Java): versatile network visualisation of structural and functional relationships.

PubMed

Goldovsky, Leon; Cases, Ildefonso; Enright, Anton J; Ouzounis, Christos A

2005-01-01

Visualisation of biological networks is becoming a common task for the analysis of high-throughput data. These networks correspond to a wide variety of biological relationships, such as sequence similarity, metabolic pathways, gene regulatory cascades and protein interactions. We present a general approach for the representation and analysis of networks of variable type, size and complexity. The application is based on the original BioLayout program (C-language implementation of the Fruchterman-Rheingold layout algorithm), entirely re-written in Java to guarantee portability across platforms. BioLayout(Java) provides broader functionality, various analysis techniques, extensions for better visualisation and a new user interface. Examples of analysis of biological networks using BioLayout(Java) are presented.

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

PubMed Central

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; Breitbart, Mya; Edwards, Robert A.

2015-01-01

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. We propose adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution. PMID:26005436

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

DOE PAGES

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; ...

2015-05-08

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set ofmore » publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.« less

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

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

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set ofmore » publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.« less

"On the Job" Learning: A Bioinformatics Course Incorporating Undergraduates in Actual Research Projects and Manuscript Submissions

ERIC Educational Resources Information Center

Smith, Jason T.; Harris, Justine C.; Lopez, Oscar J.; Valverde, Laura; Borchert, Glen M.

2015-01-01

The sequencing of whole genomes and the analysis of genetic information continues to fundamentally change biological and medical research. Unfortunately, the people best suited to interpret this data (biologically trained researchers) are commonly discouraged by their own perceived computational limitations. To address this, we developed a course…

Comparative genetics: a lens through which to clarify the genomes, the transmission history, and the reproductive biology of Trichinella spp.

USDA-ARS?s Scientific Manuscript database

Progress in studying the biology of Trichinella spp. was greatly advanced with the publication and analysis of the draft genome sequence of T. spiralis. Those data provide a basis for constructing testable hypothesis concerning parasite physiology, immunology, and genetics. They also provide tools...

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

PubMed

Fuentes-Pardo, Angela P; Ruzzante, Daniel E

2017-10-01

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

A Study of the Comparative Effectiveness of Zoology Prerequisites at Slippery Rock State College.

ERIC Educational Resources Information Center

Morrison, William Sechler

This study compared the effectiveness of three sequences of prerequisite courses required before taking zoology. Sequence 1 prerequisite courses consisted of general biology and human biology; Sequence 2 consisted of general biology; and Sequence 3 required cell biology. Zoology students in the spring of 1972 were pretest and a posttest. The mean…

Protein interface classification by evolutionary analysis

PubMed Central

2012-01-01

Background Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved. Results We present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts. Conclusions An evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org. PMID:23259833

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

The missing graphical user interface for genomics.

PubMed

Schatz, Michael C

2010-01-01

The Galaxy package empowers regular users to perform rich DNA sequence analysis through a much-needed and user-friendly graphical web interface. See research article http://genomebiology.com/2010/11/8/R86 RESEARCH HIGHLIGHT: With the advent of affordable and high-throughput DNA sequencing, sequencing is becoming an essential component in nearly every genetics lab. These data are being generated to probe sequence variations, to understand transcribed, regulated or methylated DNA elements, and to explore a host of other biological features across the tree of life and across a range of environments and conditions. Given this deluge of data, novices and experts alike are facing the daunting challenge of trying to analyze the raw sequence data computationally. With so many tools available and so many assays to analyze, how can one be expected to stay current with the state of the art? How can one be expected to learn to use each tool and construct robust end-to-end analysis pipelines, all while ensuring that input formats, command-line options, sequence databases and program libraries are set correctly? Finally, once the analysis is complete, how does one ensure the results are reproducible and transparent for others to scrutinize and study?In an article published in Genome Biology, Jeremy Goecks, Anton Nekrutenko, James Taylor and the rest of the Galaxy Team (Goecks et al. 1) make a great advance towards resolving these critical questions with the latest update to their Galaxy Project. The ambitious goal of Galaxy is to empower regular users to carry out their own computational analysis without having to be an expert in computational biology or computer science. Galaxy adds a desperately needed graphical user interface to genomics research, making data analysis universally accessible in a web browser, and freeing users from the minutiae of archaic command-line parameters, data formats and scripting languages. Data inputs and computational steps are selected from dynamic graphical menus, and the results are displayed in intuitive plots and summaries that encourage interactive workflows and the exploration of hypotheses. The underlying data analysis tools can be almost any piece of software, written in any language, but all their complexity is neatly hidden inside of Galaxy, allowing users to focus on scientific rather than technical questions.

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

NASA Astrophysics Data System (ADS)

Serra, Reviewed By Martin J.

2000-01-01

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

Investigation of Microbial Diversity in Geothermal Hot Springs in Unkeshwar, India, Based on 16S rRNA Amplicon Metagenome Sequencing

PubMed Central

Mehetre, Gajanan T.; Paranjpe, Aditi; Dastager, Syed G.

2016-01-01

Microbial diversity in geothermal waters of the Unkeshwar hot springs in Maharashtra, India, was studied using 16S rRNA amplicon metagenomic sequencing. Taxonomic analysis revealed the presence of Bacteroidetes, Proteobacteria, Cyanobacteria, Actinobacteria, Archeae, and OD1 phyla. Metabolic function prediction analysis indicated a battery of biological information systems indicating rich and novel microbial diversity, with potential biotechnological applications in this niche. PMID:26950332

Lineage-Specific Biology Revealed by a Finished Genome Assembly of the Mouse

PubMed Central

Hillier, LaDeana W.; Zody, Michael C.; Goldstein, Steve; She, Xinwe; Bult, Carol J.; Agarwala, Richa; Cherry, Joshua L.; DiCuccio, Michael; Hlavina, Wratko; Kapustin, Yuri; Meric, Peter; Maglott, Donna; Birtle, Zoë; Marques, Ana C.; Graves, Tina; Zhou, Shiguo; Teague, Brian; Potamousis, Konstantinos; Churas, Christopher; Place, Michael; Herschleb, Jill; Runnheim, Ron; Forrest, Daniel; Amos-Landgraf, James; Schwartz, David C.; Cheng, Ze; Lindblad-Toh, Kerstin; Eichler, Evan E.; Ponting, Chris P.

2009-01-01

The mouse (Mus musculus) is the premier animal model for understanding human disease and development. Here we show that a comprehensive understanding of mouse biology is only possible with the availability of a finished, high-quality genome assembly. The finished clone-based assembly of the mouse strain C57BL/6J reported here has over 175,000 fewer gaps and over 139 Mb more of novel sequence, compared with the earlier MGSCv3 draft genome assembly. In a comprehensive analysis of this revised genome sequence, we are now able to define 20,210 protein-coding genes, over a thousand more than predicted in the human genome (19,042 genes). In addition, we identified 439 long, non–protein-coding RNAs with evidence for transcribed orthologs in human. We analyzed the complex and repetitive landscape of 267 Mb of sequence that was missing or misassembled in the previously published assembly, and we provide insights into the reasons for its resistance to sequencing and assembly by whole-genome shotgun approaches. Duplicated regions within newly assembled sequence tend to be of more recent ancestry than duplicates in the published draft, correcting our initial understanding of recent evolution on the mouse lineage. These duplicates appear to be largely composed of sequence regions containing transposable elements and duplicated protein-coding genes; of these, some may be fixed in the mouse population, but at least 40% of segmentally duplicated sequences are copy number variable even among laboratory mouse strains. Mouse lineage-specific regions contain 3,767 genes drawn mainly from rapidly-changing gene families associated with reproductive functions. The finished mouse genome assembly, therefore, greatly improves our understanding of rodent-specific biology and allows the delineation of ancestral biological functions that are shared with human from derived functions that are not. PMID:19468303

Development and integration of block operations for data invariant automation of digital preprocessing and analysis of biological and biomedical Raman spectra.

PubMed

Schulze, H Georg; Turner, Robin F B

2015-06-01

High-throughput information extraction from large numbers of Raman spectra is becoming an increasingly taxing problem due to the proliferation of new applications enabled using advances in instrumentation. Fortunately, in many of these applications, the entire process can be automated, yielding reproducibly good results with significant time and cost savings. Information extraction consists of two stages, preprocessing and analysis. We focus here on the preprocessing stage, which typically involves several steps, such as calibration, background subtraction, baseline flattening, artifact removal, smoothing, and so on, before the resulting spectra can be further analyzed. Because the results of some of these steps can affect the performance of subsequent ones, attention must be given to the sequencing of steps, the compatibility of these sequences, and the propensity of each step to generate spectral distortions. We outline here important considerations to effect full automation of Raman spectral preprocessing: what is considered full automation; putative general principles to effect full automation; the proper sequencing of processing and analysis steps; conflicts and circularities arising from sequencing; and the need for, and approaches to, preprocessing quality control. These considerations are discussed and illustrated with biological and biomedical examples reflecting both successful and faulty preprocessing.

Identifying Novel Helix-Loop-Helix Genes in "Caenorhabditis elegans" through a Classroom Demonstration of Functional Genomics

ERIC Educational Resources Information Center

Griffin, Vernetta; McMiller, Tracee; Jones, Erika; Johnson, Casonya M.

2003-01-01

A 14-week, undergraduate-level Genetics and Population Biology course at Morgan State University was modified to include a demonstration of functional genomics in the research laboratory. Students performed a rudimentary sequence analysis of the "Caenorhabditis elegans" genome and further characterized three sequences that were predicted to encode…

Cloning of the poly(ADP-ribose) Gene from Rat Liver.

DTIC Science & Technology

1986-09-24

Levinson, Ph.D. (Cetus Corp., Berkeley). 5. Amino acid analysis done in UCSF Bioanal. Lab. TABLE OF CONTENTS Page METHOD I...TABLE I ............. ............................... ... 12 Proteolytic degradation, isolation of peptide and amino acid sequences...technique developed for enzyme quantitation in biological materials. The amino- acid sequence of the enzyme has so far been determined because the amino

Update on Genomic Databases and Resources at the National Center for Biotechnology Information.

PubMed

Tatusova, Tatiana

2016-01-01

The National Center for Biotechnology Information (NCBI), as a primary public repository of genomic sequence data, collects and maintains enormous amounts of heterogeneous data. Data for genomes, genes, gene expressions, gene variation, gene families, proteins, and protein domains are integrated with the analytical, search, and retrieval resources through the NCBI website, text-based search and retrieval system, provides a fast and easy way to navigate across diverse biological databases.Comparative genome analysis tools lead to further understanding of evolution processes quickening the pace of discovery. Recent technological innovations have ignited an explosion in genome sequencing that has fundamentally changed our understanding of the biology of living organisms. This huge increase in DNA sequence data presents new challenges for the information management system and the visualization tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data.

Version VI of the ESTree db: an improved tool for peach transcriptome analysis

PubMed Central

Lazzari, Barbara; Caprera, Andrea; Vecchietti, Alberto; Merelli, Ivan; Barale, Francesca; Milanesi, Luciano; Stella, Alessandra; Pozzi, Carlo

2008-01-01

Background The ESTree database (db) is a collection of Prunus persica and Prunus dulcis EST sequences that in its current version encompasses 75,404 sequences from 3 almond and 19 peach libraries. Nine peach genotypes and four peach tissues are represented, from four fruit developmental stages. The aim of this work was to implement the already existing ESTree db by adding new sequences and analysis programs. Particular care was given to the implementation of the web interface, that allows querying each of the database features. Results A Perl modular pipeline is the backbone of sequence analysis in the ESTree db project. Outputs obtained during the pipeline steps are automatically arrayed into the fields of a MySQL database. Apart from standard clustering and annotation analyses, version VI of the ESTree db encompasses new tools for tandem repeat identification, annotation against genomic Rosaceae sequences, and positioning on the database of oligomer sequences that were used in a peach microarray study. Furthermore, known protein patterns and motifs were identified by comparison to PROSITE. Based on data retrieved from sequence annotation against the UniProtKB database, a script was prepared to track positions of homologous hits on the GO tree and build statistics on the ontologies distribution in GO functional categories. EST mapping data were also integrated in the database. The PHP-based web interface was upgraded and extended. The aim of the authors was to enable querying the database according to all the biological aspects that can be investigated from the analysis of data available in the ESTree db. This is achieved by allowing multiple searches on logical subsets of sequences that represent different biological situations or features. Conclusions The version VI of ESTree db offers a broad overview on peach gene expression. Sequence analyses results contained in the database, extensively linked to external related resources, represent a large amount of information that can be queried via the tools offered in the web interface. Flexibility and modularity of the ESTree analysis pipeline and of the web interface allowed the authors to set up similar structures for different datasets, with limited manual intervention. PMID:18387211

[Cloning and characterization of genes differentially expressed in human dental pulp cells and gingival fibroblasts].

PubMed

Wang, Zhong-dong; Wu, Ji-nan; Zhou, Lin; Ling, Jun-qi; Guo, Xi-min; Xiao, Ming-zhen; Zhu, Feng; Pu, Qin; Chai, Yu-bo; Zhao, Zhong-liang

2007-02-01

To study the biological properties of human dental pulp cells (HDPC) by cloning and analysis of genes differentially expressed in HDPC in comparison with human gingival fibroblasts (HGF). HDPC and HGF were cultured and identified by immunocytochemistry. HPDC and HGF subtractive cDNA library was established by PCR-based modified subtractive hybridization, genes differentially expressed by HPDC were cloned, sequenced and compared to find homogeneous sequence in GenBank by BLAST. Cloning and sequencing analysis indicate 12 genes differentially expressed were obtained, in which two were unknown genes. Among the 10 known genes, 4 were related to signal transduction, 2 were related to trans-membrane transportation (both cell membrane and nuclear membrane), and 2 were related to RNA splicing mechanisms. The biological properties of HPDC are determined by the differential expression of some genes and the growth and differentiation of HPDC are associated to the dynamic protein synthesis and secretion activities of the cell.

Reverse Genetics and High Throughput Sequencing Methodologies for Plant Functional Genomics

PubMed Central

Ben-Amar, Anis; Daldoul, Samia; Reustle, Götz M.; Krczal, Gabriele; Mliki, Ahmed

2016-01-01

In the post-genomic era, increasingly sophisticated genetic tools are being developed with the long-term goal of understanding how the coordinated activity of genes gives rise to a complex organism. With the advent of the next generation sequencing associated with effective computational approaches, wide variety of plant species have been fully sequenced giving a wealth of data sequence information on structure and organization of plant genomes. Since thousands of gene sequences are already known, recently developed functional genomics approaches provide powerful tools to analyze plant gene functions through various gene manipulation technologies. Integration of different omics platforms along with gene annotation and computational analysis may elucidate a complete view in a system biology level. Extensive investigations on reverse genetics methodologies were deployed for assigning biological function to a specific gene or gene product. We provide here an updated overview of these high throughout strategies highlighting recent advances in the knowledge of functional genomics in plants. PMID:28217003

Finding similar nucleotide sequences using network BLAST searches.

PubMed

Ladunga, Istvan

2009-06-01

The Basic Local Alignment Search Tool (BLAST) is a keystone of bioinformatics due to its performance and user-friendliness. Beginner and intermediate users will learn how to design and submit blastn and Megablast searches on the Web pages at the National Center for Biotechnology Information. We map nucleic acid sequences to genomes, find identical or similar mRNA, expressed sequence tag, and noncoding RNA sequences, and run Megablast searches, which are much faster than blastn. Understanding results is assisted by taxonomy reports, genomic views, and multiple alignments. We interpret expected frequency thresholds, biological significance, and statistical significance. Weak hits provide no evidence, but hints for further analyses. We find genes that may code for homologous proteins by translated BLAST. We reduce false positives by filtering out low-complexity regions. Parsed BLAST results can be integrated into analysis pipelines. Links in the output connect to Entrez, PUBMED, structural, sequence, interaction, and expression databases. This facilitates integration with a wide spectrum of biological knowledge.

Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

PubMed

Huang, Ying; Chen, Shi-Yi; Deng, Feilong

2016-01-01

In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

Pattern matching through Chaos Game Representation: bridging numerical and discrete data structures for biological sequence analysis

PubMed Central

2012-01-01

Background Chaos Game Representation (CGR) is an iterated function that bijectively maps discrete sequences into a continuous domain. As a result, discrete sequences can be object of statistical and topological analyses otherwise reserved to numerical systems. Characteristically, CGR coordinates of substrings sharing an L-long suffix will be located within 2-L distance of each other. In the two decades since its original proposal, CGR has been generalized beyond its original focus on genomic sequences and has been successfully applied to a wide range of problems in bioinformatics. This report explores the possibility that it can be further extended to approach algorithms that rely on discrete, graph-based representations. Results The exploratory analysis described here consisted of selecting foundational string problems and refactoring them using CGR-based algorithms. We found that CGR can take the role of suffix trees and emulate sophisticated string algorithms, efficiently solving exact and approximate string matching problems such as finding all palindromes and tandem repeats, and matching with mismatches. The common feature of these problems is that they use longest common extension (LCE) queries as subtasks of their procedures, which we show to have a constant time solution with CGR. Additionally, we show that CGR can be used as a rolling hash function within the Rabin-Karp algorithm. Conclusions The analysis of biological sequences relies on algorithmic foundations facing mounting challenges, both logistic (performance) and analytical (lack of unifying mathematical framework). CGR is found to provide the latter and to promise the former: graph-based data structures for sequence analysis operations are entailed by numerical-based data structures produced by CGR maps, providing a unifying analytical framework for a diversity of pattern matching problems. PMID:22551152

Sirius PSB: a generic system for analysis of biological sequences.

PubMed

Koh, Chuan Hock; Lin, Sharene; Jedd, Gregory; Wong, Limsoon

2009-12-01

Computational tools are essential components of modern biological research. For example, BLAST searches can be used to identify related proteins based on sequence homology, or when a new genome is sequenced, prediction models can be used to annotate functional sites such as transcription start sites, translation initiation sites and polyadenylation sites and to predict protein localization. Here we present Sirius Prediction Systems Builder (PSB), a new computational tool for sequence analysis, classification and searching. Sirius PSB has four main operations: (1) Building a classifier, (2) Deploying a classifier, (3) Search for proteins similar to query proteins, (4) Preliminary and post-prediction analysis. Sirius PSB supports all these operations via a simple and interactive graphical user interface. Besides being a convenient tool, Sirius PSB has also introduced two novelties in sequence analysis. Firstly, genetic algorithm is used to identify interesting features in the feature space. Secondly, instead of the conventional method of searching for similar proteins via sequence similarity, we introduced searching via features' similarity. To demonstrate the capabilities of Sirius PSB, we have built two prediction models - one for the recognition of Arabidopsis polyadenylation sites and another for the subcellular localization of proteins. Both systems are competitive against current state-of-the-art models based on evaluation of public datasets. More notably, the time and effort required to build each model is greatly reduced with the assistance of Sirius PSB. Furthermore, we show that under certain conditions when BLAST is unable to find related proteins, Sirius PSB can identify functionally related proteins based on their biophysical similarities. Sirius PSB and its related supplements are available at: http://compbio.ddns.comp.nus.edu.sg/~sirius.

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

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

2017-10-09

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

RetroTector online, a rational tool for analysis of retroviral elements in small and medium size vertebrate genomic sequences

PubMed Central

Sperber, Göran; Lövgren, Anders; Eriksson, Nils-Einar; Benachenhou, Farid; Blomberg, Jonas

2009-01-01

Background The rapid accumulation of genomic information in databases necessitates rapid and specific algorithms for extracting biologically meaningful information. More or less complete retroviral sequences, also called proviral or endogenous retroviral sequences; ERVs, constitutes at least 5% of vertebrate genomes. After infecting the host, these retroviruses have integrated in germ line cells, and have then been carried in genomes for at least several 100 million years. A better understanding of structure and function of these sequences can have profound biological and medical consequences. Methods RetroTector© (ReTe) is a platform-independent Java program for identification and characterization of proviral sequences in vertebrate genomes. The full ReTe requires a local installation with a MySQL database. Although not overly complicated, the installation may take some time. A "light" version of ReTe, (RetroTector online; ROL) which does not require specific installation procedures is provided, via the World Wide Web. Results ROL was implemented under the Batchelor web interface (A Lövgren et al). It allows both GenBank accession number, file and FASTA cut-and-paste admission of sequences (5 to 10 000 kilobases). Up to ten submissions can be done simultaneously, allowing batch analysis of <= 100 Megabases. Jobs are shown in an IP-number specific list. Results are text files, and can be viewed with the program, RetroTectorViewer.jar (at the same site), which has the full graphical capabilities of the basic ReTe program. A detailed analysis of any retroviral sequences found in the submitted sequence is graphically presented, exportable in standard formats. With the current server, a complete analysis of a 1 Megabase sequence is complete in 10 minutes. It is possible to mask nonretroviral repetitive sequences in the submitted sequence, using host genome specific "brooms", which increase specificity. Discussion Proviral sequences can be hard to recognize, especially if the integration occurred many million years ago. Precise delineation of LTR, gag, pro, pol and env can be difficult, requiring manual work. ROL is a way of simplifying these tasks. Conclusion ROL provides 1. annotation and presentation of known retroviral sequences, 2. detection of proviral chains in unknown genomic sequences, with up to 100 Mbase per submission. PMID:19534753

RetroTector online, a rational tool for analysis of retroviral elements in small and medium size vertebrate genomic sequences.

PubMed

Sperber, Göran; Lövgren, Anders; Eriksson, Nils-Einar; Benachenhou, Farid; Blomberg, Jonas

2009-06-16

The rapid accumulation of genomic information in databases necessitates rapid and specific algorithms for extracting biologically meaningful information. More or less complete retroviral sequences, also called proviral or endogenous retroviral sequences; ERVs, constitutes at least 5% of vertebrate genomes. After infecting the host, these retroviruses have integrated in germ line cells, and have then been carried in genomes for at least several 100 million years. A better understanding of structure and function of these sequences can have profound biological and medical consequences. RetroTector (ReTe) is a platform-independent Java program for identification and characterization of proviral sequences in vertebrate genomes. The full ReTe requires a local installation with a MySQL database. Although not overly complicated, the installation may take some time. A "light" version of ReTe, (RetroTector online; ROL) which does not require specific installation procedures is provided, via the World Wide Web. ROL http://www.fysiologi.neuro.uu.se/jbgs/ was implemented under the Batchelor web interface (A Lövgren et al). It allows both GenBank accession number, file and FASTA cut-and-paste admission of sequences (5 to 10,000 kilobases). Up to ten submissions can be done simultaneously, allowing batch analysis of

Affordable hands-on DNA sequencing and genotyping: an exercise for teaching DNA analysis to undergraduates.

PubMed

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C Sanger sequencing reactions. They prepare and run the gels, perform Southern blots (which require only 10 min), and detect sequencing ladders using a colorimetric detection system. Students enlarge their sequencing ladders from digital images of their small nylon membranes, and read the sequence manually. They compare their reads with the actual DNA sequence using BLAST2. After mastering the DNA sequencing system, students prepare their own DNA from a cheek swab, polymerase chain reaction-amplify a region of their DNA that encompasses a SNP of interest, and perform sequencing to determine their genotype at the SNP position. A family pedigree can also be constructed. The SNP chosen by the instructor was rs17822931, which is in the ABCC11 gene and is the determinant of human earwax type. Genotypes at the rs178229931 site vary in different ethnic populations. © 2013 by The International Union of Biochemistry and Molecular Biology.

MicroScope: a platform for microbial genome annotation and comparative genomics

PubMed Central

Vallenet, D.; Engelen, S.; Mornico, D.; Cruveiller, S.; Fleury, L.; Lajus, A.; Rouy, Z.; Roche, D.; Salvignol, G.; Scarpelli, C.; Médigue, C.

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope’s rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone. Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc PMID:20157493

MicroScope: a platform for microbial genome annotation and comparative genomics.

PubMed

Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

PubMed

Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

Biology of Symbioses between Marine Invertebrates and Intracellular Bacteria

DTIC Science & Technology

1991-01-21

bisphosphate carboxylase ( RubisCO ) from symbiotic bacteria of various origins, b) To continue methods development for 16S rRNA sequencing from symbionts in...frozen and badly preserved specimens, and c) To use these new techniques to sequence 16s DNA from a variety of symbionts a) RubisCO We have cloned the...gene coding for RubisCO from the sulfur oxidixing symbiont of the gastropod Alvinochoncha hessleri. Nucleotide sequence analysis of the cloned fragment

REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

PubMed Central

Leonard, Guy; Stevens, Jamie R.; Richards, Thomas A.

2009-01-01

The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends. PMID:19812722

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus.

PubMed

de Vries, Ronald P; Riley, Robert; Wiebenga, Ad; Aguilar-Osorio, Guillermo; Amillis, Sotiris; Uchima, Cristiane Akemi; Anderluh, Gregor; Asadollahi, Mojtaba; Askin, Marion; Barry, Kerrie; Battaglia, Evy; Bayram, Özgür; Benocci, Tiziano; Braus-Stromeyer, Susanna A; Caldana, Camila; Cánovas, David; Cerqueira, Gustavo C; Chen, Fusheng; Chen, Wanping; Choi, Cindy; Clum, Alicia; Dos Santos, Renato Augusto Corrêa; Damásio, André Ricardo de Lima; Diallinas, George; Emri, Tamás; Fekete, Erzsébet; Flipphi, Michel; Freyberg, Susanne; Gallo, Antonia; Gournas, Christos; Habgood, Rob; Hainaut, Matthieu; Harispe, María Laura; Henrissat, Bernard; Hildén, Kristiina S; Hope, Ryan; Hossain, Abeer; Karabika, Eugenia; Karaffa, Levente; Karányi, Zsolt; Kraševec, Nada; Kuo, Alan; Kusch, Harald; LaButti, Kurt; Lagendijk, Ellen L; Lapidus, Alla; Levasseur, Anthony; Lindquist, Erika; Lipzen, Anna; Logrieco, Antonio F; MacCabe, Andrew; Mäkelä, Miia R; Malavazi, Iran; Melin, Petter; Meyer, Vera; Mielnichuk, Natalia; Miskei, Márton; Molnár, Ákos P; Mulé, Giuseppina; Ngan, Chew Yee; Orejas, Margarita; Orosz, Erzsébet; Ouedraogo, Jean Paul; Overkamp, Karin M; Park, Hee-Soo; Perrone, Giancarlo; Piumi, Francois; Punt, Peter J; Ram, Arthur F J; Ramón, Ana; Rauscher, Stefan; Record, Eric; Riaño-Pachón, Diego Mauricio; Robert, Vincent; Röhrig, Julian; Ruller, Roberto; Salamov, Asaf; Salih, Nadhira S; Samson, Rob A; Sándor, Erzsébet; Sanguinetti, Manuel; Schütze, Tabea; Sepčić, Kristina; Shelest, Ekaterina; Sherlock, Gavin; Sophianopoulou, Vicky; Squina, Fabio M; Sun, Hui; Susca, Antonia; Todd, Richard B; Tsang, Adrian; Unkles, Shiela E; van de Wiele, Nathalie; van Rossen-Uffink, Diana; Oliveira, Juliana Velasco de Castro; Vesth, Tammi C; Visser, Jaap; Yu, Jae-Hyuk; Zhou, Miaomiao; Andersen, Mikael R; Archer, David B; Baker, Scott E; Benoit, Isabelle; Brakhage, Axel A; Braus, Gerhard H; Fischer, Reinhard; Frisvad, Jens C; Goldman, Gustavo H; Houbraken, Jos; Oakley, Berl; Pócsi, István; Scazzocchio, Claudio; Seiboth, Bernhard; vanKuyk, Patricia A; Wortman, Jennifer; Dyer, Paul S; Grigoriev, Igor V

2017-02-14

The fungal genus Aspergillus is of critical importance to humankind. Species include those with industrial applications, important pathogens of humans, animals and crops, a source of potent carcinogenic contaminants of food, and an important genetic model. The genome sequences of eight aspergilli have already been explored to investigate aspects of fungal biology, raising questions about evolution and specialization within this genus. We have generated genome sequences for ten novel, highly diverse Aspergillus species and compared these in detail to sister and more distant genera. Comparative studies of key aspects of fungal biology, including primary and secondary metabolism, stress response, biomass degradation, and signal transduction, revealed both conservation and diversity among the species. Observed genomic differences were validated with experimental studies. This revealed several highlights, such as the potential for sex in asexual species, organic acid production genes being a key feature of black aspergilli, alternative approaches for degrading plant biomass, and indications for the genetic basis of stress response. A genome-wide phylogenetic analysis demonstrated in detail the relationship of the newly genome sequenced species with other aspergilli. Many aspects of biological differences between fungal species cannot be explained by current knowledge obtained from genome sequences. The comparative genomics and experimental study, presented here, allows for the first time a genus-wide view of the biological diversity of the aspergilli and in many, but not all, cases linked genome differences to phenotype. Insights gained could be exploited for biotechnological and medical applications of fungi.

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database.

PubMed

Ikeda, Shun; Abe, Takashi; Nakamura, Yukiko; Kibinge, Nelson; Hirai Morita, Aki; Nakatani, Atsushi; Ono, Naoaki; Ikemura, Toshimichi; Nakamura, Kensuke; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2013-05-01

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

Conserved noncoding sequences conserve biological networks and influence genome evolution.

PubMed

Xie, Jianbo; Qian, Kecheng; Si, Jingna; Xiao, Liang; Ci, Dong; Zhang, Deqiang

2018-05-01

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

CoLIde

PubMed Central

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-01-01

Small RNAs (sRNAs) are 20–25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci.   To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk. PMID:23851377

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

PubMed Central

Miller, Ian J.; Chevrette, Marc G.; Kwan, Jason C.

2017-01-01

Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC. PMID:28587290

The golden ratio and Loshu-Fibonacci Diagram: novel research view on relationship of Chinese medicine and modern biology.

PubMed

Chen, Zhao-xue; Huang, Yun-kun; Sun, Ying

2014-02-01

Associating geometric arrangements of 9 Loshu numbers modulo 5, investigating property of golden rectangles and characteristics of Fibonacci sequence modulo 10 as well as the two subsequences of its modular sequence by modulo 5, the Loshu-Fibonacci Diagram is created based on strict logical deduction in this paper, which can disclose inherent relationship among Taiji sign, Loshu and Fibonacci sequence modulo 10 perfectly and unite such key ideas of holism, symmetry, holographic thought and yin-yang balance pursuit from Chinese medicine as a whole. Based on further analysis and reasoning, the authors discover that taking the golden ratio and Loshu-Fibonacci Diagram as a link, there is profound and universal association existing between researches of Chinese medicine and modern biology.

Information resources at the National Center for Biotechnology Information.

PubMed Central

Woodsmall, R M; Benson, D A

1993-01-01

The National Center for Biotechnology Information (NCBI), part of the National Library of Medicine, was established in 1988 to perform basic research in the field of computational molecular biology as well as build and distribute molecular biology databases. The basic research has led to new algorithms and analysis tools for interpreting genomic data and has been instrumental in the discovery of human disease genes for neurofibromatosis and Kallmann syndrome. The principal database responsibility is the National Institutes of Health (NIH) genetic sequence database, GenBank. NCBI, in collaboration with international partners, builds, distributes, and provides online and CD-ROM access to over 112,000 DNA sequences. Another major program is the integration of multiple sequences databases and related bibliographic information and the development of network-based retrieval systems for Internet access. PMID:8374583

The Large Mitochondrial Genome of Symbiodinium minutum Reveals Conserved Noncoding Sequences between Dinoflagellates and Apicomplexans.

PubMed

Shoguchi, Eiichi; Shinzato, Chuya; Hisata, Kanako; Satoh, Nori; Mungpakdee, Sutada

2015-07-20

Even though mitochondrial genomes, which characterize eukaryotic cells, were first discovered more than 50 years ago, mitochondrial genomics remains an important topic in molecular biology and genome sciences. The Phylum Alveolata comprises three major groups (ciliates, apicomplexans, and dinoflagellates), the mitochondrial genomes of which have diverged widely. Even though the gene content of dinoflagellate mitochondrial genomes is reportedly comparable to that of apicomplexans, the highly fragmented and rearranged genome structures of dinoflagellates have frustrated whole genomic analysis. Consequently, noncoding sequences and gene arrangements of dinoflagellate mitochondrial genomes have not been well characterized. Here we report that the continuous assembled genome (∼326 kb) of the dinoflagellate, Symbiodinium minutum, is AT-rich (∼64.3%) and that it contains three protein-coding genes. Based upon in silico analysis, the remaining 99% of the genome comprises transcriptomic noncoding sequences. RNA edited sites and unique, possible start and stop codons clarify conserved regions among dinoflagellates. Our massive transcriptome analysis shows that almost all regions of the genome are transcribed, including 27 possible fragmented ribosomal RNA genes and 12 uncharacterized small RNAs that are similar to mitochondrial RNA genes of the malarial parasite, Plasmodium falciparum. Gene map comparisons show that gene order is only slightly conserved between S. minutum and P. falciparum. However, small RNAs and intergenic sequences share sequence similarities with P. falciparum, suggesting that the function of noncoding sequences has been preserved despite development of very different genome structures. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Investigation of Microbial Diversity in Geothermal Hot Springs in Unkeshwar, India, Based on 16S rRNA Amplicon Metagenome Sequencing.

PubMed

Mehetre, Gajanan T; Paranjpe, Aditi; Dastager, Syed G; Dharne, Mahesh S

2016-02-25

Microbial diversity in geothermal waters of the Unkeshwar hot springs in Maharashtra, India, was studied using 16S rRNA amplicon metagenomic sequencing. Taxonomic analysis revealed the presence of Bacteroidetes, Proteobacteria, Cyanobacteria, Actinobacteria, Archeae, and OD1 phyla. Metabolic function prediction analysis indicated a battery of biological information systems indicating rich and novel microbial diversity, with potential biotechnological applications in this niche. Copyright © 2016 Mehetre et al.

Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores.

PubMed

Bastien, Olivier; Maréchal, Eric

2008-08-07

Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2) following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory) is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure). Homologous sequences were considered as systems 1) having a high redundancy of information reflected by the magnitude of their alignment scores, 2) which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a constant rate, corresponding to the information hazard rate, and that pairwise sequence alignment scores should follow a Gumbel distribution, which parameters could find some theoretical rationale. In particular, one parameter corresponds to the information hazard rate. Extreme value distribution of alignment scores, assessed from high scoring segments pairs following the Karlin-Altschul model, can also be deduced from the Reliability Theory applied to molecular sequences. It reflects the redundancy of information between homologous sequences, under functional conservative pressure. This model also provides a link between concepts of biological sequence analysis and of systems biology.

ISOL@: an Italian SOLAnaceae genomics resource.

PubMed

Chiusano, Maria Luisa; D'Agostino, Nunzio; Traini, Alessandra; Licciardello, Concetta; Raimondo, Enrico; Aversano, Mario; Frusciante, Luigi; Monti, Luigi

2008-03-26

Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality. The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations. In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs). The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family.

Advanced Applications of Next-Generation Sequencing Technologies to Orchid Biology.

PubMed

Yeh, Chuan-Ming; Liu, Zhong-Jian; Tsai, Wen-Chieh

2018-01-01

Next-generation sequencing technologies are revolutionizing biology by permitting, transcriptome sequencing, whole-genome sequencing and resequencing, and genome-wide single nucleotide polymorphism profiling. Orchid research has benefited from this breakthrough, and a few orchid genomes are now available; new biological questions can be approached and new breeding strategies can be designed. The first part of this review describes the unique features of orchid biology. The second part provides an overview of the current next-generation sequencing platforms, many of which are already used in plant laboratories. The third part summarizes the state of orchid transcriptome and genome sequencing and illustrates current achievements. The genetic sequences currently obtained will not only provide a broad scope for the study of orchid biology, but also serves as a starting point for uncovering the mystery of orchid evolution.

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

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2008-04-08

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

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

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2010-10-05

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

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

Integrated databanks access and sequence/structure analysis services at the PBIL.

PubMed

Perrière, Guy; Combet, Christophe; Penel, Simon; Blanchet, Christophe; Thioulouse, Jean; Geourjon, Christophe; Grassot, Julien; Charavay, Céline; Gouy, Manolo; Duret, Laurent; Deléage, Gilbert

2003-07-01

The World Wide Web server of the PBIL (Pôle Bioinformatique Lyonnais) provides on-line access to sequence databanks and to many tools of nucleic acid and protein sequence analyses. This server allows to query nucleotide sequence banks in the EMBL and GenBank formats and protein sequence banks in the SWISS-PROT and PIR formats. The query engine on which our data bank access is based is the ACNUC system. It allows the possibility to build complex queries to access functional zones of biological interest and to retrieve large sequence sets. Of special interest are the unique features provided by this system to query the data banks of gene families developed at the PBIL. The server also provides access to a wide range of sequence analysis methods: similarity search programs, multiple alignments, protein structure prediction and multivariate statistics. An originality of this server is the integration of these two aspects: sequence retrieval and sequence analysis. Indeed, thanks to the introduction of re-usable lists, it is possible to perform treatments on large sets of data. The PBIL server can be reached at: http://pbil.univ-lyon1.fr.

Vaginal microbial flora analysis by next generation sequencing and microarrays; can microbes indicate vaginal origin in a forensic context?

PubMed

Benschop, Corina C G; Quaak, Frederike C A; Boon, Mathilde E; Sijen, Titia; Kuiper, Irene

2012-03-01

Forensic analysis of biological traces generally encompasses the investigation of both the person who contributed to the trace and the body site(s) from which the trace originates. For instance, for sexual assault cases, it can be beneficial to distinguish vaginal samples from skin or saliva samples. In this study, we explored the use of microbial flora to indicate vaginal origin. First, we explored the vaginal microbiome for a large set of clinical vaginal samples (n = 240) by next generation sequencing (n = 338,184 sequence reads) and found 1,619 different sequences. Next, we selected 389 candidate probes targeting genera or species and designed a microarray, with which we analysed a diverse set of samples; 43 DNA extracts from vaginal samples and 25 DNA extracts from samples from other body sites, including sites in close proximity of or in contact with the vagina. Finally, we used the microarray results and next generation sequencing dataset to assess the potential for a future approach that uses microbial markers to indicate vaginal origin. Since no candidate genera/species were found to positively identify all vaginal DNA extracts on their own, while excluding all non-vaginal DNA extracts, we deduce that a reliable statement about the cellular origin of a biological trace should be based on the detection of multiple species within various genera. Microarray analysis of a sample will then render a microbial flora pattern that is probably best analysed in a probabilistic approach.

Novel chaperonins are prevalent in the virioplankton and demonstrate links to viral biology and ecology

PubMed Central

Marine, Rachel L; Nasko, Daniel J; Wray, Jeffrey; Polson, Shawn W; Wommack, K Eric

2017-01-01

Chaperonins are protein-folding machinery found in all cellular life. Chaperonin genes have been documented within a few viruses, yet, surprisingly, analysis of metagenome sequence data indicated that chaperonin-carrying viruses are common and geographically widespread in marine ecosystems. Also unexpected was the discovery of viral chaperonin sequences related to thermosome proteins of archaea, indicating the presence of virioplankton populations infecting marine archaeal hosts. Virioplankton large subunit chaperonin sequences (GroELs) were divergent from bacterial sequences, indicating that viruses have carried this gene over long evolutionary time. Analysis of viral metagenome contigs indicated that: the order of large and small subunit genes was linked to the phylogeny of GroEL; both lytic and temperate phages may carry group I chaperonin genes; and viruses carrying a GroEL gene likely have large double-stranded DNA (dsDNA) genomes (>70 kb). Given these connections, it is likely that chaperonins are critical to the biology and ecology of virioplankton populations that carry these genes. Moreover, these discoveries raise the intriguing possibility that viral chaperonins may more broadly alter the structure and function of viral and cellular proteins in infected host cells. PMID:28731469

Novel chaperonins are prevalent in the virioplankton and demonstrate links to viral biology and ecology.

PubMed

Marine, Rachel L; Nasko, Daniel J; Wray, Jeffrey; Polson, Shawn W; Wommack, K Eric

2017-11-01

Chaperonins are protein-folding machinery found in all cellular life. Chaperonin genes have been documented within a few viruses, yet, surprisingly, analysis of metagenome sequence data indicated that chaperonin-carrying viruses are common and geographically widespread in marine ecosystems. Also unexpected was the discovery of viral chaperonin sequences related to thermosome proteins of archaea, indicating the presence of virioplankton populations infecting marine archaeal hosts. Virioplankton large subunit chaperonin sequences (GroELs) were divergent from bacterial sequences, indicating that viruses have carried this gene over long evolutionary time. Analysis of viral metagenome contigs indicated that: the order of large and small subunit genes was linked to the phylogeny of GroEL; both lytic and temperate phages may carry group I chaperonin genes; and viruses carrying a GroEL gene likely have large double-stranded DNA (dsDNA) genomes (>70 kb). Given these connections, it is likely that chaperonins are critical to the biology and ecology of virioplankton populations that carry these genes. Moreover, these discoveries raise the intriguing possibility that viral chaperonins may more broadly alter the structure and function of viral and cellular proteins in infected host cells.

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

FAST: FAST Analysis of Sequences Toolbox

PubMed Central

Lawrence, Travis J.; Kauffman, Kyle T.; Amrine, Katherine C. H.; Carper, Dana L.; Lee, Raymond S.; Becich, Peter J.; Canales, Claudia J.; Ardell, David H.

2015-01-01

FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought. PMID:26042145

Tracking B-Cell Repertoires and Clonal Histories in Normal and Malignant Lymphocytes.

PubMed

Weston-Bell, Nicola J; Cowan, Graeme; Sahota, Surinder S

2017-01-01

Methods for tracking B-cell repertoires and clonal history in normal and malignant B-cells based on immunoglobulin variable region (IGV) gene analysis have developed rapidly with the advent of massive parallel next-generation sequencing (mpNGS) protocols. mpNGS permits a depth of analysis of IGV genes not hitherto feasible, and presents challenges of bioinformatics analysis, which can be readily met by current pipelines. This strategy offers a potential resolution of B-cell usage at a depth that may capture fully the natural state, in a given biological setting. Conventional methods based on RT-PCR amplification and Sanger sequencing are also available where mpNGS is not accessible. Each method offers distinct advantages. Conventional methods for IGV gene sequencing are readily adaptable to most laboratories and provide an ease of analysis to capture salient features of B-cell use. This chapter describes two methods in detail for analysis of IGV genes, mpNGS and conventional RT-PCR with Sanger sequencing.

Getting to the root of plant biology: impact of the Arabidopsis genome sequence on root research

PubMed Central

Benfey, Philip N.; Bennett, Malcolm; Schiefelbein, John

2010-01-01

Summary Prior to the availability of the genome sequence, the root of Arabidopsis had attracted a small but ardent group of researchers drawn to its accessibility and developmental simplicity. Roots are easily observed when grown on the surface of nutrient agar media, facilitating analysis of responses to stimuli such as gravity and touch. Developmental biologists were attracted to the simple radial organization of primary root tissues, which form a series of concentric cylinders around the central vascular tissue. Equally attractive was the mode of propagation, with stem cells at the tip giving rise to progeny that were confined to cell files. These properties of root development reduced the normal four-dimensional problem of development (three spatial dimensions and time) to a two-dimensional problem, with cell type on the radial axis and developmental time along the longitudinal axis. The availability of the complete Arabidopsis genome sequence has dramatically accelerated traditional genetic research on root biology, and has also enabled entirely new experimental strategies to be applied. Here we review examples of the ways in which availability of the Arabidopsis genome sequence has enhanced progress in understanding root biology. PMID:20409273

Special Focus

PubMed Central

Nawrocki, Eric P.; Burge, Sarah W.

2013-01-01

The development of RNA bioinformatic tools began more than 30 y ago with the description of the Nussinov and Zuker dynamic programming algorithms for single sequence RNA secondary structure prediction. Since then, many tools have been developed for various RNA sequence analysis problems such as homology search, multiple sequence alignment, de novo RNA discovery, read-mapping, and many more. In this issue, we have collected a sampling of reviews and original research that demonstrate some of the many ways bioinformatics is integrated with current RNA biology research. PMID:23948768

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

An "in silico" Bioinformatics Laboratory Manual for Bioscience Departments: "Prediction of Glycosylation Sites in Phosphoethanolamine Transferases"

ERIC Educational Resources Information Center

Alyuruk, Hakan; Cavas, Levent

2014-01-01

Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data.…

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

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

PubMed Central

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

2015-01-01

Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki. PMID:26248053

Differential principal component analysis of ChIP-seq.

PubMed

Ji, Hongkai; Li, Xia; Wang, Qian-fei; Ning, Yang

2013-04-23

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.

Markov model plus k-word distributions: a synergy that produces novel statistical measures for sequence comparison.

PubMed

Dai, Qi; Yang, Yanchun; Wang, Tianming

2008-10-15

Many proposed statistical measures can efficiently compare biological sequences to further infer their structures, functions and evolutionary information. They are related in spirit because all the ideas for sequence comparison try to use the information on the k-word distributions, Markov model or both. Motivated by adding k-word distributions to Markov model directly, we investigated two novel statistical measures for sequence comparison, called wre.k.r and S2.k.r. The proposed measures were tested by similarity search, evaluation on functionally related regulatory sequences and phylogenetic analysis. This offers the systematic and quantitative experimental assessment of our measures. Moreover, we compared our achievements with these based on alignment or alignment-free. We grouped our experiments into two sets. The first one, performed via ROC (receiver operating curve) analysis, aims at assessing the intrinsic ability of our statistical measures to search for similar sequences from a database and discriminate functionally related regulatory sequences from unrelated sequences. The second one aims at assessing how well our statistical measure is used for phylogenetic analysis. The experimental assessment demonstrates that our similarity measures intending to incorporate k-word distributions into Markov model are more efficient.

A new set of ESTs and cDNA clones from full-length and normalized libraries for gene discovery and functional characterization in citrus

PubMed Central

Marques, M Carmen; Alonso-Cantabrana, Hugo; Forment, Javier; Arribas, Raquel; Alamar, Santiago; Conejero, Vicente; Perez-Amador, Miguel A

2009-01-01

Background Interpretation of ever-increasing raw sequence information generated by modern genome sequencing technologies faces multiple challenges, such as gene function analysis and genome annotation. Indeed, nearly 40% of genes in plants encode proteins of unknown function. Functional characterization of these genes is one of the main challenges in modern biology. In this regard, the availability of full-length cDNA clones may fill in the gap created between sequence information and biological knowledge. Full-length cDNA clones facilitate functional analysis of the corresponding genes enabling manipulation of their expression in heterologous systems and the generation of a variety of tagged versions of the native protein. In addition, the development of full-length cDNA sequences has the power to improve the quality of genome annotation. Results We developed an integrated method to generate a new normalized EST collection enriched in full-length and rare transcripts of different citrus species from multiple tissues and developmental stages. We constructed a total of 15 cDNA libraries, from which we isolated 10,898 high-quality ESTs representing 6142 different genes. Percentages of redundancy and proportion of full-length clones range from 8 to 33, and 67 to 85, respectively, indicating good efficiency of the approach employed. The new EST collection adds 2113 new citrus ESTs, representing 1831 unigenes, to the collection of citrus genes available in the public databases. To facilitate functional analysis, cDNAs were introduced in a Gateway-based cloning vector for high-throughput functional analysis of genes in planta. Herein, we describe the technical methods used in the library construction, sequence analysis of clones and the overexpression of CitrSEP, a citrus homolog to the Arabidopsis SEP3 gene, in Arabidopsis as an example of a practical application of the engineered Gateway vector for functional analysis. Conclusion The new EST collection denotes an important step towards the identification of all genes in the citrus genome. Furthermore, public availability of the cDNA clones generated in this study, and not only their sequence, enables testing of the biological function of the genes represented in the collection. Expression of the citrus SEP3 homologue, CitrSEP, in Arabidopsis results in early flowering, along with other phenotypes resembling the over-expression of the Arabidopsis SEPALLATA genes. Our findings suggest that the members of the SEP gene family play similar roles in these quite distant plant species. PMID:19747386

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

SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing.

PubMed

Sato, Yukuto; Kojima, Kaname; Nariai, Naoki; Yamaguchi-Kabata, Yumi; Kawai, Yosuke; Takahashi, Mamoru; Mimori, Takahiro; Nagasaki, Masao

2014-08-08

Next-generation sequencers (NGSs) have become one of the main tools for current biology. To obtain useful insights from the NGS data, it is essential to control low-quality portions of the data affected by technical errors such as air bubbles in sequencing fluidics. We develop a software SUGAR (subtile-based GUI-assisted refiner) which can handle ultra-high-throughput data with user-friendly graphical user interface (GUI) and interactive analysis capability. The SUGAR generates high-resolution quality heatmaps of the flowcell, enabling users to find possible signals of technical errors during the sequencing. The sequencing data generated from the error-affected regions of a flowcell can be selectively removed by automated analysis or GUI-assisted operations implemented in the SUGAR. The automated data-cleaning function based on sequence read quality (Phred) scores was applied to a public whole human genome sequencing data and we proved the overall mapping quality was improved. The detailed data evaluation and cleaning enabled by SUGAR would reduce technical problems in sequence read mapping, improving subsequent variant analysis that require high-quality sequence data and mapping results. Therefore, the software will be especially useful to control the quality of variant calls to the low population cells, e.g., cancers, in a sample with technical errors of sequencing procedures.

Algorithm, applications and evaluation for protein comparison by Ramanujan Fourier transform.

PubMed

Zhao, Jian; Wang, Jiasong; Hua, Wei; Ouyang, Pingkai

2015-12-01

The amino acid sequence of a protein determines its chemical properties, chain conformation and biological functions. Protein sequence comparison is of great importance to identify similarities of protein structures and infer their functions. Many properties of a protein correspond to the low-frequency signals within the sequence. Low frequency modes in protein sequences are linked to the secondary structures, membrane protein types, and sub-cellular localizations of the proteins. In this paper, we present Ramanujan Fourier transform (RFT) with a fast algorithm to analyze the low-frequency signals of protein sequences. The RFT method is applied to similarity analysis of protein sequences with the Resonant Recognition Model (RRM). The results show that the proposed fast RFT method on protein comparison is more efficient than commonly used discrete Fourier transform (DFT). RFT can detect common frequencies as significant feature for specific protein families, and the RFT spectrum heat-map of protein sequences demonstrates the information conservation in the sequence comparison. The proposed method offers a new tool for pattern recognition, feature extraction and structural analysis on protein sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2014-01-01

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

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

PubMed

Myschyshyn, Mike; Farren-Dai, Marco; Chuang, Tien-Jui; Vocadlo, David

2017-11-25

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically relevant data analysis, and the uncovering of variations in the time-dependent behavior of chromatin. TDCA automates the analysis of TC ChIP-seq experiments, permitting researchers to easily obtain raw and modeled data for specific loci or groups of loci with similar behavior while also enhancing consistency of data analysis of TC data within the genomics field.

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

PubMed

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

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

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

PubMed

Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

Generation, annotation and analysis of ESTs from Trichoderma harzianum CECT 2413

PubMed Central

Vizcaíno, Juan Antonio; González, Francisco Javier; Suárez, M Belén; Redondo, José; Heinrich, Julian; Delgado-Jarana, Jesús; Hermosa, Rosa; Gutiérrez, Santiago; Monte, Enrique; Llobell, Antonio; Rey, Manuel

2006-01-01

Background The filamentous fungus Trichoderma harzianum is used as biological control agent of several plant-pathogenic fungi. In order to study the genome of this fungus, a functional genomics project called "TrichoEST" was developed to give insights into genes involved in biological control activities using an approach based on the generation of expressed sequence tags (ESTs). Results Eight different cDNA libraries from T. harzianum strain CECT 2413 were constructed. Different growth conditions involving mainly different nutrient conditions and/or stresses were used. We here present the analysis of the 8,710 ESTs generated. A total of 3,478 unique sequences were identified of which 81.4% had sequence similarity with GenBank entries, using the BLASTX algorithm. Using the Gene Ontology hierarchy, we performed the annotation of 51.1% of the unique sequences and compared its distribution among the gene libraries. Additionally, the InterProScan algorithm was used in order to further characterize the sequences. The identification of the putatively secreted proteins was also carried out. Later, based on the EST abundance, we examined the highly expressed genes and a hydrophobin was identified as the gene expressed at the highest level. We compared our collection of ESTs with the previous collections obtained from Trichoderma species and we also compared our sequence set with different complete eukaryotic genomes from several animals, plants and fungi. Accordingly, the presence of similar sequences in different kingdoms was also studied. Conclusion This EST collection and its annotation provide a significant resource for basic and applied research on T. harzianum, a fungus with a high biotechnological interest. PMID:16872539

Mapping and Sequencing the Human Genome

DOE R&D Accomplishments Database

1988-01-01

Numerous meetings have been held and a debate has developed in the biological community over the merits of mapping and sequencing the human genome. In response a committee to examine the desirability and feasibility of mapping and sequencing the human genome was formed to suggest options for implementing the project. The committee asked many questions. Should the analysis of the human genome be left entirely to the traditionally uncoordinated, but highly successful, support systems that fund the vast majority of biomedical research. Or should a more focused and coordinated additional support system be developed that is limited to encouraging and facilitating the mapping and eventual sequencing of the human genome. If so, how can this be done without distorting the broader goals of biological research that are crucial for any understanding of the data generated in such a human genome project. As the committee became better informed on the many relevant issues, the opinions of its members coalesced, producing a shared consensus of what should be done. This report reflects that consensus.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

Overview of recurrent chromosomal losses in retinoblastoma detected by low coverage next generation sequencing

PubMed Central

García-Chequer, A.J.; Méndez-Tenorio, A.; Olguín-Ruiz, G.; Sánchez-Vallejo, C.; Isa, P.; Arias, C.F.; Torres, J.; Hernández-Angeles, A.; Ramírez-Ortiz, M.A.; Lara, C.; Cabrera-Muñoz, M.L.; Sadowinski-Pine, S.; Bravo-Ortiz, J.C.; Ramón-García, G.; Diegopérez-Ramírez, J.; Ramírez-Reyes, G.; Casarrubias-Islas, R.; Ramírez, J.; Orjuela, M.A.; Ponce-Castañeda, M.V.

2016-01-01

Genes are frequently lost or gained in malignant tumors and the analysis of these changes can be informative about the underlying tumor biology. Retinoblastoma is a pediatric intraocular malignancy, and since deletions in chromosome 13 have been described in this tumor, we performed genome wide sequencing with the Illumina platform to test whether recurrent losses could be detected in low coverage data from DNA pools of Rb cases. An in silico reference profile for each pool was created from the human genome sequence GRCh37p5; a chromosome integrity score and a graphics 40 Kb window analysis approach, allowed us to identify with high resolution previously reported non random recurrent losses in all chromosomes of these tumors. We also found a pattern of gains and losses associated to clear and dark cytogenetic bands respectively. We further analyze a pool of medulloblastoma and found a more stable genomic profile and previously reported losses in this tumor. This approach facilitates identification of recurrent deletions from many patients that may be biological relevant for tumor development. PMID:26883451

Ensembl 2002: accommodating comparative genomics.

PubMed

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

The promise and challenge of high-throughput sequencing of the antibody repertoire

PubMed Central

Georgiou, George; Ippolito, Gregory C; Beausang, John; Busse, Christian E; Wardemann, Hedda; Quake, Stephen R

2014-01-01

Efforts to determine the antibody repertoire encoded by B cells in the blood or lymphoid organs using high-throughput DNA sequencing technologies have been advancing at an extremely rapid pace and are transforming our understanding of humoral immune responses. Information gained from high-throughput DNA sequencing of immunoglobulin genes (Ig-seq) can be applied to detect B-cell malignancies with high sensitivity, to discover antibodies specific for antigens of interest, to guide vaccine development and to understand autoimmunity. Rapid progress in the development of experimental protocols and informatics analysis tools is helping to reduce sequencing artifacts, to achieve more precise quantification of clonal diversity and to extract the most pertinent biological information. That said, broader application of Ig-seq, especially in clinical settings, will require the development of a standardized experimental design framework that will enable the sharing and meta-analysis of sequencing data generated by different laboratories. PMID:24441474

GWFASTA: server for FASTA search in eukaryotic and microbial genomes.

PubMed

Issac, Biju; Raghava, G P S

2002-09-01

Similarity searches are a powerful method for solving important biological problems such as database scanning, evolutionary studies, gene prediction, and protein structure prediction. FASTA is a widely used sequence comparison tool for rapid database scanning. Here we describe the GWFASTA server that was developed to assist the FASTA user in similarity searches against partially and/or completely sequenced genomes. GWFASTA consists of more than 60 microbial genomes, eight eukaryote genomes, and proteomes of annotatedgenomes. Infact, it provides the maximum number of databases for similarity searching from a single platform. GWFASTA allows the submission of more than one sequence as a single query for a FASTA search. It also provides integrated post-processing of FASTA output, including compositional analysis of proteins, multiple sequences alignment, and phylogenetic analysis. Furthermore, it summarizes the search results organism-wise for prokaryotes and chromosome-wise for eukaryotes. Thus, the integration of different tools for sequence analyses makes GWFASTA a powerful toolfor biologists.

Sequence and analysis of chromosome 4 of the plant Arabidopsis thaliana.

PubMed

Mayer, K; Schüller, C; Wambutt, R; Murphy, G; Volckaert, G; Pohl, T; Düsterhöft, A; Stiekema, W; Entian, K D; Terryn, N; Harris, B; Ansorge, W; Brandt, P; Grivell, L; Rieger, M; Weichselgartner, M; de Simone, V; Obermaier, B; Mache, R; Müller, M; Kreis, M; Delseny, M; Puigdomenech, P; Watson, M; Schmidtheini, T; Reichert, B; Portatelle, D; Perez-Alonso, M; Boutry, M; Bancroft, I; Vos, P; Hoheisel, J; Zimmermann, W; Wedler, H; Ridley, P; Langham, S A; McCullagh, B; Bilham, L; Robben, J; Van der Schueren, J; Grymonprez, B; Chuang, Y J; Vandenbussche, F; Braeken, M; Weltjens, I; Voet, M; Bastiaens, I; Aert, R; Defoor, E; Weitzenegger, T; Bothe, G; Ramsperger, U; Hilbert, H; Braun, M; Holzer, E; Brandt, A; Peters, S; van Staveren, M; Dirske, W; Mooijman, P; Klein Lankhorst, R; Rose, M; Hauf, J; Kötter, P; Berneiser, S; Hempel, S; Feldpausch, M; Lamberth, S; Van den Daele, H; De Keyser, A; Buysshaert, C; Gielen, J; Villarroel, R; De Clercq, R; Van Montagu, M; Rogers, J; Cronin, A; Quail, M; Bray-Allen, S; Clark, L; Doggett, J; Hall, S; Kay, M; Lennard, N; McLay, K; Mayes, R; Pettett, A; Rajandream, M A; Lyne, M; Benes, V; Rechmann, S; Borkova, D; Blöcker, H; Scharfe, M; Grimm, M; Löhnert, T H; Dose, S; de Haan, M; Maarse, A; Schäfer, M; Müller-Auer, S; Gabel, C; Fuchs, M; Fartmann, B; Granderath, K; Dauner, D; Herzl, A; Neumann, S; Argiriou, A; Vitale, D; Liguori, R; Piravandi, E; Massenet, O; Quigley, F; Clabauld, G; Mündlein, A; Felber, R; Schnabl, S; Hiller, R; Schmidt, W; Lecharny, A; Aubourg, S; Chefdor, F; Cooke, R; Berger, C; Montfort, A; Casacuberta, E; Gibbons, T; Weber, N; Vandenbol, M; Bargues, M; Terol, J; Torres, A; Perez-Perez, A; Purnelle, B; Bent, E; Johnson, S; Tacon, D; Jesse, T; Heijnen, L; Schwarz, S; Scholler, P; Heber, S; Francs, P; Bielke, C; Frishman, D; Haase, D; Lemcke, K; Mewes, H W; Stocker, S; Zaccaria, P; Bevan, M; Wilson, R K; de la Bastide, M; Habermann, K; Parnell, L; Dedhia, N; Gnoj, L; Schutz, K; Huang, E; Spiegel, L; Sehkon, M; Murray, J; Sheet, P; Cordes, M; Abu-Threideh, J; Stoneking, T; Kalicki, J; Graves, T; Harmon, G; Edwards, J; Latreille, P; Courtney, L; Cloud, J; Abbott, A; Scott, K; Johnson, D; Minx, P; Bentley, D; Fulton, B; Miller, N; Greco, T; Kemp, K; Kramer, J; Fulton, L; Mardis, E; Dante, M; Pepin, K; Hillier, L; Nelson, J; Spieth, J; Ryan, E; Andrews, S; Geisel, C; Layman, D; Du, H; Ali, J; Berghoff, A; Jones, K; Drone, K; Cotton, M; Joshu, C; Antonoiu, B; Zidanic, M; Strong, C; Sun, H; Lamar, B; Yordan, C; Ma, P; Zhong, J; Preston, R; Vil, D; Shekher, M; Matero, A; Shah, R; Swaby, I K; O'Shaughnessy, A; Rodriguez, M; Hoffmann, J; Till, S; Granat, S; Shohdy, N; Hasegawa, A; Hameed, A; Lodhi, M; Johnson, A; Chen, E; Marra, M; Martienssen, R; McCombie, W R

1999-12-16

The higher plant Arabidopsis thaliana (Arabidopsis) is an important model for identifying plant genes and determining their function. To assist biological investigations and to define chromosome structure, a coordinated effort to sequence the Arabidopsis genome was initiated in late 1996. Here we report one of the first milestones of this project, the sequence of chromosome 4. Analysis of 17.38 megabases of unique sequence, representing about 17% of the genome, reveals 3,744 protein coding genes, 81 transfer RNAs and numerous repeat elements. Heterochromatic regions surrounding the putative centromere, which has not yet been completely sequenced, are characterized by an increased frequency of a variety of repeats, new repeats, reduced recombination, lowered gene density and lowered gene expression. Roughly 60% of the predicted protein-coding genes have been functionally characterized on the basis of their homology to known genes. Many genes encode predicted proteins that are homologous to human and Caenorhabditis elegans proteins.

Glycan fragment database: a database of PDB-based glycan 3D structures.

PubMed

Jo, Sunhwan; Im, Wonpil

2013-01-01

The glycan fragment database (GFDB), freely available at http://www.glycanstructure.org, is a database of the glycosidic torsion angles derived from the glycan structures in the Protein Data Bank (PDB). Analogous to protein structure, the structure of an oligosaccharide chain in a glycoprotein, referred to as a glycan, can be characterized by the torsion angles of glycosidic linkages between relatively rigid carbohydrate monomeric units. Knowledge of accessible conformations of biologically relevant glycans is essential in understanding their biological roles. The GFDB provides an intuitive glycan sequence search tool that allows the user to search complex glycan structures. After a glycan search is complete, each glycosidic torsion angle distribution is displayed in terms of the exact match and the fragment match. The exact match results are from the PDB entries that contain the glycan sequence identical to the query sequence. The fragment match results are from the entries with the glycan sequence whose substructure (fragment) or entire sequence is matched to the query sequence, such that the fragment results implicitly include the influences from the nearby carbohydrate residues. In addition, clustering analysis based on the torsion angle distribution can be performed to obtain the representative structures among the searched glycan structures.

Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

PubMed Central

Kearse, Matthew; Moir, Richard; Wilson, Amy; Stones-Havas, Steven; Cheung, Matthew; Sturrock, Shane; Buxton, Simon; Cooper, Alex; Markowitz, Sidney; Duran, Chris; Thierer, Tobias; Ashton, Bruce; Meintjes, Peter; Drummond, Alexei

2012-01-01

Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com PMID:22543367

Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data.

PubMed

Kearse, Matthew; Moir, Richard; Wilson, Amy; Stones-Havas, Steven; Cheung, Matthew; Sturrock, Shane; Buxton, Simon; Cooper, Alex; Markowitz, Sidney; Duran, Chris; Thierer, Tobias; Ashton, Bruce; Meintjes, Peter; Drummond, Alexei

2012-06-15

The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl.

Diverse nucleotide compositions and sequence fluctuation in Rubisco protein genes

NASA Astrophysics Data System (ADS)

Holden, Todd; Dehipawala, S.; Cheung, E.; Bienaime, R.; Ye, J.; Tremberger, G., Jr.; Schneider, P.; Lieberman, D.; Cheung, T.

2011-10-01

The Rubisco protein-enzyme is arguably the most abundance protein on Earth. The biology dogma of transcription and translation necessitates the study of the Rubisco genes and Rubisco-like genes in various species. Stronger correlation of fractal dimension of the atomic number fluctuation along a DNA sequence with Shannon entropy has been observed in the studied Rubisco-like gene sequences, suggesting a more diverse evolutionary pressure and constraints in the Rubisco sequences. The strategy of using metal for structural stabilization appears to be an ancient mechanism, with data from the porphobilinogen deaminase gene in Capsaspora owczarzaki and Monosiga brevicollis. Using the chi-square distance probability, our analysis supports the conjecture that the more ancient Rubisco-like sequence in Microcystis aeruginosa would have experienced very different evolutionary pressure and bio-chemical constraint as compared to Bordetella bronchiseptica, the two microbes occupying either end of the correlation graph. Our exploratory study would indicate that high fractal dimension Rubisco sequence would support high carbon dioxide rate via the Michaelis- Menten coefficient; with implication for the control of the whooping cough pathogen Bordetella bronchiseptica, a microbe containing a high fractal dimension Rubisco-like sequence (2.07). Using the internal comparison of chi-square distance probability for 16S rRNA (~ E-22) versus radiation repair Rec-A gene (~ E-05) in high GC content Deinococcus radiodurans, our analysis supports the conjecture that high GC content microbes containing Rubisco-like sequence are likely to include an extra-terrestrial origin, relative to Deinococcus radiodurans. Similar photosynthesis process that could utilize host star radiation would not compete with radiation resistant process from the biology dogma perspective in environments such as Mars and exoplanets.

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.

Sequence-structure mapping errors in the PDB: OB-fold domains

PubMed Central

Venclovas, Česlovas; Ginalski, Krzysztof; Kang, Chulhee

2004-01-01

The Protein Data Bank (PDB) is the single most important repository of structural data for proteins and other biologically relevant molecules. Therefore, it is critically important to keep the PDB data, as much as possible, error-free. In this study, we have analyzed PDB crystal structures possessing oligonucleotide/oligosaccharide binding (OB)-fold, one of the highly populated folds, for the presence of sequence-structure mapping errors. Using energy-based structure quality assessment coupled with sequence analyses, we have found that there are at least five OB-structures in the PDB that have regions where sequences have been incorrectly mapped onto the structure. We have demonstrated that the combination of these computation techniques is effective not only in detecting sequence-structure mapping errors, but also in providing guidance to correct them. Namely, we have used results of computational analysis to direct a revision of X-ray data for one of the PDB entries containing a fairly inconspicuous sequence-structure mapping error. The revised structure has been deposited with the PDB. We suggest use of computational energy assessment and sequence analysis techniques to facilitate structure determination when homologs having known structure are available to use as a reference. Such computational analysis may be useful in either guiding the sequence-structure assignment process or verifying the sequence mapping within poorly defined regions. PMID:15133161

BlockLogo: visualization of peptide and sequence motif conservation

PubMed Central

Olsen, Lars Rønn; Kudahl, Ulrich Johan; Simon, Christian; Sun, Jing; Schönbach, Christian; Reinherz, Ellis L.; Zhang, Guang Lan; Brusic, Vladimir

2013-01-01

BlockLogo is a web-server application for visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, selection of motif positions, type of sequence, and output format definition. The output has BlockLogo along with the sequence logo, and a table of motif frequencies. We deployed BlockLogo as an online application and have demonstrated its utility through examples that show visualization of T-cell epitopes and B-cell epitopes (both continuous and discontinuous). Our additional example shows a visualization and analysis of structural motifs that determine specificity of peptide binding to HLA-DR molecules. The BlockLogo server also employs selected experimentally validated prediction algorithms to enable on-the-fly prediction of MHC binding affinity to 15 common HLA class I and class II alleles as well as visual analysis of discontinuous epitopes from multiple sequence alignments. It enables the visualization and analysis of structural and functional motifs that are usually described as regular expressions. It provides a compact view of discontinuous motifs composed of distant positions within biological sequences. BlockLogo is available at: http://research4.dfci.harvard.edu/cvc/blocklogo/ and http://methilab.bu.edu/blocklogo/ PMID:24001880

Azospirillum canadense sp. nov., a nitrogen-fixing bacterium isolated from corn rhizosphere.

PubMed

Mehnaz, Samina; Weselowski, Brian; Lazarovits, George

2007-03-01

A free-living diazotrophic strain, DS2(T), was isolated from corn rhizosphere. Polyphasic taxonomy was performed including morphological characterization, Biolog analysis, and 16S rRNA, cpn60 and nifH gene sequence analyses. 16S rRNA gene sequence analysis indicated that strain DS2(T) was closely related to the genus Azospirillum (96 % similarity). Chemotaxonomic characteristics (DNA G+C content 67.9 mol%; Q-10 quinone system; major fatty acid 18 : 1omega7c) were also similar to those of the genus Azospirillum. In all the analyses, including phenotypic characterization using Biolog analysis and comparison of cellular fatty acids, this isolate was found to be different from the closely related species Azospirillum lipoferum, Azospirillum oryzae and Azospirillum brasilense. On the basis of these results, a novel species is proposed for this nitrogen-fixing strain. The name Azospirillum canadense sp. nov. is suggested with the type strain DS2(T) (=NCCB 100108(T)=LMG 23617(T)).

Community Structure Analysis and Biodegradation Potential of Aniline-Degrading Bacteria in Biofilters.

PubMed

Hou, Luanfeng; Wu, Qingping; Gu, Qihui; Zhou, Qin; Zhang, Jumei

2018-07-01

Aniline has aroused general concern owing to its strong toxicity and widespread distribution in water and soil. In the present study, the bacterial community composition before and after aniline acclimation was investigated. High-throughput Illumina MiSeq sequencing analysis illustrated a large shift in the structure of the bacterial community during the aniline acclimation period. Bacillus, Lactococcus, and Enterococcus were the dominant bacteria in biologically activated carbon before acclimation. However, the proportions of Pseudomonas, Thermomonas, and Acinetobacter increased significantly and several new bacterial taxa appeared after aniline acclimation, indicating that aniline acclimation had a strong impact on the bacterial community structure of biological activated carbon samples. Strain AN-1 accounted for the highest number of colonies on incubation plates and was identified as Acinetobacter sp. according to phylogenetic analysis of the 16S ribosomal ribonucleic acid gene sequence. Strain AN-1 was able to grow on aniline at pH value 4.0-10.0 and showed high aniline-degrading ability at neutral pH.

Cross species analysis of microarray expression data

PubMed Central

Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv

2009-01-01

Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

NASA Astrophysics Data System (ADS)

Trifonov, Vladimir; Pasqualucci, Laura; Dalla-Favera, Riccardo; Rabadan, Raul

2011-12-01

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing (HTS), expression profiles, proteomics, and electronic health records (EHR) are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of fractal-like distributions that commonly appear in the analysis of such data. The first set of examples are drawn from a HTS experiment. Here, the distributions appear as part of the evaluation of the error rate of the sequencing and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in EHR. The distributions are also relevant to identification of subclonal populations in tumors and the study of quasi-species and intrahost diversity of viral populations.

Molecular characterization, biological forms and sporozoite rate of Anopheles stephensi in southern Iran

PubMed Central

Chavshin, Ali Reza; Oshaghi, Mohammad Ali; Vatandoost, Hasan; Hanafi-Bojd, Ahmad Ali; Raeisi, Ahmad; Nikpoor, Fatemeh

2014-01-01

Objective To identify the biological forms, sporozoite rate and molecular characterization of the Anopheles stephensi (An. stephensi) in Hormozgan and Sistan-Baluchistan provinces, the most important malarious areas in Iran. Methods Wild live An. stephensi samples were collected from different malarious areas in southern Iran. The biological forms were identified based on number of egg-ridges. Molecular characterization of biological forms was verified by analysis of the mitochondrial cytochrome oxidase subunit I and II (mtDNA-COI/COII). The Plasmodium infection was examined in the wild female specimens by species-specific nested–PCR method. Results Results showed that all three biological forms including mysorensis, intermediate and type are present in the study areas. Molecular investigations revealed no genetic variation between mtDNA COI/COII sequences of the biological forms and no Plasmodium parasites was detected in the collected mosquito samples. Conclusions Presence of three biological forms with identical sequences showed that the known biological forms belong to a single taxon and the various vectorial capacities reported for these forms are more likely corresponded to other epidemiological factors than to the morphotype of the populations. Lack of malaria parasite infection in An. stephensi, the most important vector of malaria, may be partly due to the success and achievement of ongoing active malaria control program in the region. PMID:24144130

Multifaceted biological insights from a draft genome sequence of the tobacco hornworm moth, Manduca sexta

PubMed Central

Kanost, Michael R.; Arrese, Estela L.; Cao, Xiaolong; Chen, Yun-Ru; Chellapilla, Sanjay; Goldsmith, Marian R; Grosse-Wilde, Ewald; Heckel, David G.; Herndon, Nicolae; Jiang, Haobo; Papanicolaou, Alexie; Qu, Jiaxin; Soulages, Jose L.; Vogel, Heiko; Walters, James; Waterhouse, Robert M.; Ahn, Seung-Joon; Almeida, Francisca C.; An, Chunju; Aqrawi, Peshtewani; Bretschneider, Anne; Bryant, William B.; Bucks, Sascha; Chao, Hsu; Chevignon, Germain; Christen, Jayne M.; Clarke, David F.; Dittmer, Neal T.; Ferguson, Laura C.F.; Garavelou, Spyridoula; Gordon, Karl H.J.; Gunaratna, Ramesh T.; Han, Yi; Hauser, Frank; He, Yan; Heidel-Fischer, Hanna; Hirsh, Ariana; Hu, Yingxia; Jiang, Hongbo; Kalra, Divya; Klinner, Christian; König, Christopher; Kovar, Christie; Kroll, Ashley R.; Kuwar, Suyog S.; Lee, Sandy L.; Lehman, Rüdiger; Li, Kai; Li, Zhaofei; Liang, Hanquan; Lovelace, Shanna; Lu, Zhiqiang; Mansfield, Jennifer H.; McCulloch, Kyle J.; Mathew, Tittu; Morton, Brian; Muzny, Donna M.; Neunemann, David; Ongeri, Fiona; Pauchet, Yannick; Pu, Ling-Ling; Pyrousis, Ioannis; Rao, Xiang-Jun; Redding, Amanda; Roesel, Charles; Sanchez-Gracia, Alejandro; Schaack, Sarah; Shukla, Aditi; Tetreau, Guillaume; Wang, Yang; Xiong, Guang-Hua; Traut, Walther; Walsh, Tom K.; Worley, Kim C.; Wu, Di; Wu, Wenbi; Wu, Yuan-Qing; Zhang, Xiufeng; Zou, Zhen; Zucker, Hannah; Briscoe, Adriana D.; Burmester, Thorsten; Clem, Rollie J.; Feyereisen, René; Grimmelikhuijzen, Cornelis J.P; Hamodrakas, Stavros J.; Hansson, Bill S.; Huguet, Elisabeth; Jermiin, Lars S.; Lan, Que; Lehman, Herman K.; Lorenzen, Marce; Merzendorfer, Hans; Michalopoulos, Ioannis; Morton, David B.; Muthukrishnan, Subbaratnam; Oakeshott, John G.; Palmer, Will; Park, Yoonseong; Passarelli, A. Lorena; Rozas, Julio; Schwartz, Lawrence M.; Smith, Wendy; Southgate, Agnes; Vilcinskas, Andreas; Vogt, Richard; Wang, Ping; Werren, John; Yu, Xiao-Qiang; Zhou, Jing-Jiang; Brown, Susan J.; Scherer, Steven E.; Richards, Stephen; Blissard, Gary W.

2016-01-01

Manduca sexta, known as the tobacco hornworm or Carolina sphinx moth, is a lepidopteran insect that is used extensively as a model system for research in insect biochemistry, physiology, neurobiology, development, and immunity. One important benefit of this species as an experimental model is its extremely large size, reaching more than 10 g in the larval stage. M. sexta larvae feed on solanaceous plants and thus must tolerate a substantial challenge from plant allelochemicals, including nicotine. We report the sequence and annotation of the M. sexta genome, and a survey of gene expression in various tissues and developmental stages. The Msex_1.0 genome assembly resulted in a total genome size of 419.4 Mbp. Repetitive sequences accounted for 25.8% of the assembled genome. The official gene set is comprised of 15,451 protein-coding genes, of which 2498 were manually curated. Extensive RNA-seq data from many tissues and developmental stages were used to improve gene models and for insights into gene expression patterns. Genome wide synteny analysis indicated a high level of macrosynteny in the Lepidoptera. Annotation and analyses were carried out for gene families involved in a wide spectrum of biological processes, including apoptosis, vacuole sorting, growth and development, structures of exoskeleton, egg shells, and muscle, vision, chemosensation, ion channels, signal transduction, neuropeptide signaling, neurotransmitter synthesis and transport, nicotine tolerance, lipid metabolism, and immunity. This genome sequence, annotation, and analysis provide an important new resource from a well-studied model insect species and will facilitate further biochemical and mechanistic experimental studies of many biological systems in insects. PMID:27522922

The Fourier analysis of biological transients.

PubMed

Harris, C M

1998-08-31

With modern computing technology the digital implementation of the Fourier transform is widely available, mostly in the form of the fast Fourier transform (FFT). Although the FFT has become almost synonymous with the Fourier transform, it is a fast numerical technique for computing the discrete Fourier transform (DFT) of a finite sequence of sampled data. The DFT is not directly equivalent to the continuous Fourier transform of the underlying biological signal, which becomes important when analyzing biological transients. Although this distinction is well known by some, for many it leads to confusion in how to interpret the FFT of biological data, and in how to precondition data so as to yield a more accurate Fourier transform using the FFT. We review here the fundamentals of Fourier analysis with emphasis on the analysis of transient signals. As an example of a transient, we consider the human saccade to illustrate the pitfalls and advantages of various Fourier analyses.

A novel approach to enhance biological nutrient removal using a culture supernatant from Micrococcus luteus containing resuscitation-promoting factor (Rpf) in SBR process.

PubMed

Liu, Yindong; Su, Xiaomei; Lu, Lian; Ding, Linxian; Shen, Chaofeng

2016-03-01

A culture supernatant from Micrococcus luteus containing resuscitation-promoting factor (SRpf) was used to enhance the biological nutrient removal of potentially functional bacteria. The obtained results suggest that SRpf accelerated the start-up process and significantly enhanced the biological nutrient removal in sequencing batch reactor (SBR). PO4 (3-)-P removal efficiency increased by over 12 % and total nitrogen removal efficiency increased by over 8 % in treatment reactor acclimated by SRpf compared with those without SRpf addition. The Illumina high-throughput sequencing analysis showed that SRpf played an essential role in shifts in the composition and diversity of bacterial community. The phyla of Proteobacteria and Actinobacteria, which were closely related to biological nutrient removal, were greatly abundant after SRpf addition. This study demonstrates that SRpf acclimation or addition might hold great potential as an efficient and cost-effective alternative for wastewater treatment plants (WWTPs) to meet more stringent operation conditions and legislations.

Examining inter-family differences in intra-family (parent-adolescent) dynamics using grid-sequence analysis.

PubMed

Brinberg, Miriam; Fosco, Gregory M; Ram, Nilam

2017-12-01

Family systems theorists have forwarded a set of theoretical principles meant to guide family scientists and practitioners in their conceptualization of patterns of family interaction-intra-family dynamics-that, over time, give rise to family and individual dysfunction and/or adaptation. In this article, we present an analytic approach that merges state space grid methods adapted from the dynamic systems literature with sequence analysis methods adapted from molecular biology into a "grid-sequence" method for studying inter-family differences in intra-family dynamics. Using dyadic data from 86 parent-adolescent dyads who provided up to 21 daily reports about connectedness, we illustrate how grid-sequence analysis can be used to identify a typology of intrafamily dynamics and to inform theory about how specific types of intrafamily dynamics contribute to adolescent behavior problems and family members' mental health. Methodologically, grid-sequence analysis extends the toolbox of techniques for analysis of family experience sampling and daily diary data. Substantively, we identify patterns of family level microdynamics that may serve as new markers of risk/protective factors and potential points for intervention in families. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

PubMed

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

2003-01-01

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

Efficient use of unlabeled data for protein sequence classification: a comparative study.

PubMed

Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-04-29

Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.

[Research on soil bacteria under the impact of sealed CO2 leakage by high-throughput sequencing technology].

PubMed

Tian, Di; Ma, Xin; Li, Yu-E; Zha, Liang-Song; Wu, Yang; Zou, Xiao-Xia; Liu, Shuang

2013-10-01

Carbon dioxide Capture and Storage has provided a new option for mitigating global anthropogenic CO2 emission with its unique advantages. However, there is a risk of the sealed CO2 leakage, bringing a serious threat to the ecology system. It is widely known that soil microorganisms are closely related to soil health, while the study on the impact of sequestered CO2 leakage on soil microorganisms is quite deficient. In this study, the leakage scenarios of sealed CO2 were constructed and the 16S rRNA genes of soil bacteria were sequenced by Illumina high-throughput sequencing technology on Miseq platform, and related biological analysis was conducted to explore the changes of soil bacterial abundance, diversity and structure. There were 486,645 reads for 43,017 OTUs of 15 soil samples and the results of biological analysis showed that there were differences in the abundance, diversity and community structure of soil bacterial community under different CO, leakage scenarios while the abundance and diversity of the bacterial community declined with the amplification of CO2 leakage quantity and leakage time, and some bacteria species became the dominant bacteria species in the bacteria community, therefore the increase of Acidobacteria species would be a biological indicator for the impact of sealed CO2 leakage on soil ecology system.

Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing

PubMed Central

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2015-01-01

The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research. PMID:25649523

The genome of the sea urchin Strongylocentrotus purpuratus.

PubMed

Sodergren, Erica; Weinstock, George M; Davidson, Eric H; Cameron, R Andrew; Gibbs, Richard A; Angerer, Robert C; Angerer, Lynne M; Arnone, Maria Ina; Burgess, David R; Burke, Robert D; Coffman, James A; Dean, Michael; Elphick, Maurice R; Ettensohn, Charles A; Foltz, Kathy R; Hamdoun, Amro; Hynes, Richard O; Klein, William H; Marzluff, William; McClay, David R; Morris, Robert L; Mushegian, Arcady; Rast, Jonathan P; Smith, L Courtney; Thorndyke, Michael C; Vacquier, Victor D; Wessel, Gary M; Wray, Greg; Zhang, Lan; Elsik, Christine G; Ermolaeva, Olga; Hlavina, Wratko; Hofmann, Gretchen; Kitts, Paul; Landrum, Melissa J; Mackey, Aaron J; Maglott, Donna; Panopoulou, Georgia; Poustka, Albert J; Pruitt, Kim; Sapojnikov, Victor; Song, Xingzhi; Souvorov, Alexandre; Solovyev, Victor; Wei, Zheng; Whittaker, Charles A; Worley, Kim; Durbin, K James; Shen, Yufeng; Fedrigo, Olivier; Garfield, David; Haygood, Ralph; Primus, Alexander; Satija, Rahul; Severson, Tonya; Gonzalez-Garay, Manuel L; Jackson, Andrew R; Milosavljevic, Aleksandar; Tong, Mark; Killian, Christopher E; Livingston, Brian T; Wilt, Fred H; Adams, Nikki; Bellé, Robert; Carbonneau, Seth; Cheung, Rocky; Cormier, Patrick; Cosson, Bertrand; Croce, Jenifer; Fernandez-Guerra, Antonio; Genevière, Anne-Marie; Goel, Manisha; Kelkar, Hemant; Morales, Julia; Mulner-Lorillon, Odile; Robertson, Anthony J; Goldstone, Jared V; Cole, Bryan; Epel, David; Gold, Bert; Hahn, Mark E; Howard-Ashby, Meredith; Scally, Mark; Stegeman, John J; Allgood, Erin L; Cool, Jonah; Judkins, Kyle M; McCafferty, Shawn S; Musante, Ashlan M; Obar, Robert A; Rawson, Amanda P; Rossetti, Blair J; Gibbons, Ian R; Hoffman, Matthew P; Leone, Andrew; Istrail, Sorin; Materna, Stefan C; Samanta, Manoj P; Stolc, Viktor; Tongprasit, Waraporn; Tu, Qiang; Bergeron, Karl-Frederik; Brandhorst, Bruce P; Whittle, James; Berney, Kevin; Bottjer, David J; Calestani, Cristina; Peterson, Kevin; Chow, Elly; Yuan, Qiu Autumn; Elhaik, Eran; Graur, Dan; Reese, Justin T; Bosdet, Ian; Heesun, Shin; Marra, Marco A; Schein, Jacqueline; Anderson, Michele K; Brockton, Virginia; Buckley, Katherine M; Cohen, Avis H; Fugmann, Sebastian D; Hibino, Taku; Loza-Coll, Mariano; Majeske, Audrey J; Messier, Cynthia; Nair, Sham V; Pancer, Zeev; Terwilliger, David P; Agca, Cavit; Arboleda, Enrique; Chen, Nansheng; Churcher, Allison M; Hallböök, F; Humphrey, Glen W; Idris, Mohammed M; Kiyama, Takae; Liang, Shuguang; Mellott, Dan; Mu, Xiuqian; Murray, Greg; Olinski, Robert P; Raible, Florian; Rowe, Matthew; Taylor, John S; Tessmar-Raible, Kristin; Wang, D; Wilson, Karen H; Yaguchi, Shunsuke; Gaasterland, Terry; Galindo, Blanca E; Gunaratne, Herath J; Juliano, Celina; Kinukawa, Masashi; Moy, Gary W; Neill, Anna T; Nomura, Mamoru; Raisch, Michael; Reade, Anna; Roux, Michelle M; Song, Jia L; Su, Yi-Hsien; Townley, Ian K; Voronina, Ekaterina; Wong, Julian L; Amore, Gabriele; Branno, Margherita; Brown, Euan R; Cavalieri, Vincenzo; Duboc, Véronique; Duloquin, Louise; Flytzanis, Constantin; Gache, Christian; Lapraz, François; Lepage, Thierry; Locascio, Annamaria; Martinez, Pedro; Matassi, Giorgio; Matranga, Valeria; Range, Ryan; Rizzo, Francesca; Röttinger, Eric; Beane, Wendy; Bradham, Cynthia; Byrum, Christine; Glenn, Tom; Hussain, Sofia; Manning, Gerard; Miranda, Esther; Thomason, Rebecca; Walton, Katherine; Wikramanayke, Athula; Wu, Shu-Yu; Xu, Ronghui; Brown, C Titus; Chen, Lili; Gray, Rachel F; Lee, Pei Yun; Nam, Jongmin; Oliveri, Paola; Smith, Joel; Muzny, Donna; Bell, Stephanie; Chacko, Joseph; Cree, Andrew; Curry, Stacey; Davis, Clay; Dinh, Huyen; Dugan-Rocha, Shannon; Fowler, Jerry; Gill, Rachel; Hamilton, Cerrissa; Hernandez, Judith; Hines, Sandra; Hume, Jennifer; Jackson, Laronda; Jolivet, Angela; Kovar, Christie; Lee, Sandra; Lewis, Lora; Miner, George; Morgan, Margaret; Nazareth, Lynne V; Okwuonu, Geoffrey; Parker, David; Pu, Ling-Ling; Thorn, Rachel; Wright, Rita

2006-11-10

We report the sequence and analysis of the 814-megabase genome of the sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology. The sequencing strategy combined whole-genome shotgun and bacterial artificial chromosome (BAC) sequences. This use of BAC clones, aided by a pooling strategy, overcame difficulties associated with high heterozygosity of the genome. The genome encodes about 23,300 genes, including many previously thought to be vertebrate innovations or known only outside the deuterostomes. This echinoderm genome provides an evolutionary outgroup for the chordates and yields insights into the evolution of deuterostomes.

Genome analysis of the platypus reveals unique signatures of evolution.

PubMed

Warren, Wesley C; Hillier, LaDeana W; Marshall Graves, Jennifer A; Birney, Ewan; Ponting, Chris P; Grützner, Frank; Belov, Katherine; Miller, Webb; Clarke, Laura; Chinwalla, Asif T; Yang, Shiaw-Pyng; Heger, Andreas; Locke, Devin P; Miethke, Pat; Waters, Paul D; Veyrunes, Frédéric; Fulton, Lucinda; Fulton, Bob; Graves, Tina; Wallis, John; Puente, Xose S; López-Otín, Carlos; Ordóñez, Gonzalo R; Eichler, Evan E; Chen, Lin; Cheng, Ze; Deakin, Janine E; Alsop, Amber; Thompson, Katherine; Kirby, Patrick; Papenfuss, Anthony T; Wakefield, Matthew J; Olender, Tsviya; Lancet, Doron; Huttley, Gavin A; Smit, Arian F A; Pask, Andrew; Temple-Smith, Peter; Batzer, Mark A; Walker, Jerilyn A; Konkel, Miriam K; Harris, Robert S; Whittington, Camilla M; Wong, Emily S W; Gemmell, Neil J; Buschiazzo, Emmanuel; Vargas Jentzsch, Iris M; Merkel, Angelika; Schmitz, Juergen; Zemann, Anja; Churakov, Gennady; Kriegs, Jan Ole; Brosius, Juergen; Murchison, Elizabeth P; Sachidanandam, Ravi; Smith, Carly; Hannon, Gregory J; Tsend-Ayush, Enkhjargal; McMillan, Daniel; Attenborough, Rosalind; Rens, Willem; Ferguson-Smith, Malcolm; Lefèvre, Christophe M; Sharp, Julie A; Nicholas, Kevin R; Ray, David A; Kube, Michael; Reinhardt, Richard; Pringle, Thomas H; Taylor, James; Jones, Russell C; Nixon, Brett; Dacheux, Jean-Louis; Niwa, Hitoshi; Sekita, Yoko; Huang, Xiaoqiu; Stark, Alexander; Kheradpour, Pouya; Kellis, Manolis; Flicek, Paul; Chen, Yuan; Webber, Caleb; Hardison, Ross; Nelson, Joanne; Hallsworth-Pepin, Kym; Delehaunty, Kim; Markovic, Chris; Minx, Pat; Feng, Yucheng; Kremitzki, Colin; Mitreva, Makedonka; Glasscock, Jarret; Wylie, Todd; Wohldmann, Patricia; Thiru, Prathapan; Nhan, Michael N; Pohl, Craig S; Smith, Scott M; Hou, Shunfeng; Nefedov, Mikhail; de Jong, Pieter J; Renfree, Marilyn B; Mardis, Elaine R; Wilson, Richard K

2008-05-08

We present a draft genome sequence of the platypus, Ornithorhynchus anatinus. This monotreme exhibits a fascinating combination of reptilian and mammalian characters. For example, platypuses have a coat of fur adapted to an aquatic lifestyle; platypus females lactate, yet lay eggs; and males are equipped with venom similar to that of reptiles. Analysis of the first monotreme genome aligned these features with genetic innovations. We find that reptile and platypus venom proteins have been co-opted independently from the same gene families; milk protein genes are conserved despite platypuses laying eggs; and immune gene family expansions are directly related to platypus biology. Expansions of protein, non-protein-coding RNA and microRNA families, as well as repeat elements, are identified. Sequencing of this genome now provides a valuable resource for deep mammalian comparative analyses, as well as for monotreme biology and conservation.

Genome analysis of the platypus reveals unique signatures of evolution

PubMed Central

Warren, Wesley C.; Hillier, LaDeana W.; Marshall Graves, Jennifer A.; Birney, Ewan; Ponting, Chris P.; Grützner, Frank; Belov, Katherine; Miller, Webb; Clarke, Laura; Chinwalla, Asif T.; Yang, Shiaw-Pyng; Heger, Andreas; Locke, Devin P.; Miethke, Pat; Waters, Paul D.; Veyrunes, Frédéric; Fulton, Lucinda; Fulton, Bob; Graves, Tina; Wallis, John; Puente, Xose S.; López-Otín, Carlos; Ordóñez, Gonzalo R.; Eichler, Evan E.; Chen, Lin; Cheng, Ze; Deakin, Janine E.; Alsop, Amber; Thompson, Katherine; Kirby, Patrick; Papenfuss, Anthony T.; Wakefield, Matthew J.; Olender, Tsviya; Lancet, Doron; Huttley, Gavin A.; Smit, Arian F. A.; Pask, Andrew; Temple-Smith, Peter; Batzer, Mark A.; Walker, Jerilyn A.; Konkel, Miriam K.; Harris, Robert S.; Whittington, Camilla M.; Wong, Emily S. W.; Gemmell, Neil J.; Buschiazzo, Emmanuel; Vargas Jentzsch, Iris M.; Merkel, Angelika; Schmitz, Juergen; Zemann, Anja; Churakov, Gennady; Kriegs, Jan Ole; Brosius, Juergen; Murchison, Elizabeth P.; Sachidanandam, Ravi; Smith, Carly; Hannon, Gregory J.; Tsend-Ayush, Enkhjargal; McMillan, Daniel; Attenborough, Rosalind; Rens, Willem; Ferguson-Smith, Malcolm; Lefèvre, Christophe M.; Sharp, Julie A.; Nicholas, Kevin R.; Ray, David A.; Kube, Michael; Reinhardt, Richard; Pringle, Thomas H.; Taylor, James; Jones, Russell C.; Nixon, Brett; Dacheux, Jean-Louis; Niwa, Hitoshi; Sekita, Yoko; Huang, Xiaoqiu; Stark, Alexander; Kheradpour, Pouya; Kellis, Manolis; Flicek, Paul; Chen, Yuan; Webber, Caleb; Hardison, Ross; Nelson, Joanne; Hallsworth-Pepin, Kym; Delehaunty, Kim; Markovic, Chris; Minx, Pat; Feng, Yucheng; Kremitzki, Colin; Mitreva, Makedonka; Glasscock, Jarret; Wylie, Todd; Wohldmann, Patricia; Thiru, Prathapan; Nhan, Michael N.; Pohl, Craig S.; Smith, Scott M.; Hou, Shunfeng; Renfree, Marilyn B.; Mardis, Elaine R.; Wilson, Richard K.

2009-01-01

We present a draft genome sequence of the platypus, Ornithorhynchus anatinus. This monotreme exhibits a fascinating combination of reptilian and mammalian characters. For example, platypuses have a coat of fur adapted to an aquatic lifestyle; platypus females lactate, yet lay eggs; and males are equipped with venom similar to that of reptiles. Analysis of the first monotreme genome aligned these features with genetic innovations. We find that reptile and platypus venom proteins have been co-opted independently from the same gene families; milk protein genes are conserved despite platypuses laying eggs; and immune gene family expansions are directly related to platypus biology. Expansions of protein, non-protein-coding RNA and microRNA families, as well as repeat elements, are identified. Sequencing of this genome now provides a valuable resource for deep mammalian comparative analyses, as well as for monotreme biology and conservation. PMID:18464734

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.

Comprehensive analysis of genetic variations in strictly-defined Leber congenital amaurosis with whole-exome sequencing in Chinese.

PubMed

Wang, Shi-Yuan; Zhang, Qi; Zhang, Xiang; Zhao, Pei-Quan

2016-01-01

To make a comprehensive analysis of the potential pathogenic genes related with Leber congenital amaurosis (LCA) in Chinese. LCA subjects and their families were retrospectively collected from 2013 to 2015. Firstly, whole-exome sequencing was performed in patients who had underwent gene mutation screening with nothing found, and then homozygous sites was selected, candidate sites were annotated, and pathogenic analysis was conducted using softwares including Sorting Tolerant from Intolerant (SIFT), Polyphen-2, Mutation assessor, Condel, and Functional Analysis through Hidden Markov Models (FATHMM). Furthermore, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of pathogenic genes were performed followed by co-segregation analysis using Fisher exact Test. Sanger sequencing was used to validate single-nucleotide variations (SNVs). Expanded verification was performed in the rest patients. Totally 51 LCA families with 53 patients and 24 family members were recruited. A total of 104 SNVs (66 LCA-related genes and 15 co-segregated genes) were submitted for expand verification. The frequencies of homozygous mutation of KRT12 and CYP1A1 were simultaneously observed in 3 families. Enrichment analysis showed that the potential pathogenic genes were mainly enriched in functions related to cell adhesion, biological adhesion, retinoid metabolic process, and eye development biological adhesion. Additionally, WFS1 and STAU2 had the highest homozygous frequencies. LCA is a highly heterogeneous disease. Mutations in KRT12, CYP1A1, WFS1, and STAU2 may be involved in the development of LCA.

Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

PubMed

Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

2017-01-01

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

Sequence signatures of allosteric proteins towards rational design.

PubMed

Namboodiri, Saritha; Verma, Chandra; Dhar, Pawan K; Giuliani, Alessandro; Nair, Achuthsankar S

2010-12-01

Allostery is the phenomenon of changes in the structure and activity of proteins that appear as a consequence of ligand binding at sites other than the active site. Studying mechanistic basis of allostery leading to protein design with predetermined functional endpoints is an important unmet need of synthetic biology. Here, we screened the amino acid sequence landscape in search of sequence-signatures of allostery using Recurrence Quantitative Analysis (RQA) method. A characteristic vector, comprised of 10 features extracted from RQA was defined for amino acid sequences. Using Principal Component Analysis, four factors were found to be important determinants of allosteric behavior. Our sequence-based predictor method shows 82.6% accuracy, 85.7% sensitivity and 77.9% specificity with the current dataset. Further, we show that Laminarity-Mean-hydrophobicity representing repeated hydrophobic patches is the most crucial indicator of allostery. To our best knowledge this is the first report that describes sequence determinants of allostery based on hydrophobicity. As an outcome of these findings, we plan to explore possibility of inducing allostery in proteins.

Biological Sexing of a 4000-Year-Old Egyptian Mummy Head to Assess the Potential of Nuclear DNA Recovery from the Most Damaged and Limited Forensic Specimens

PubMed Central

Loreille, Odile; Ratnayake, Shashikala; Stockwell, Timothy B.; Mallick, Swapan; Skoglund, Pontus; Onorato, Anthony J.; Bergman, Nicholas H.; Reich, David; Irwin, Jodi A.

2018-01-01

High throughput sequencing (HTS) has been used for a number of years in the field of paleogenomics to facilitate the recovery of small DNA fragments from ancient specimens. Recently, these techniques have also been applied in forensics, where they have been used for the recovery of mitochondrial DNA sequences from samples where traditional PCR-based assays fail because of the very short length of endogenous DNA molecules. Here, we describe the biological sexing of a ~4000-year-old Egyptian mummy using shotgun sequencing and two established methods of biological sex determination (RX and RY), by way of mitochondrial genome analysis as a means of sequence data authentication. This particular case of historical interest increases the potential utility of HTS techniques for forensic purposes by demonstrating that data from the more discriminatory nuclear genome can be recovered from the most damaged specimens, even in cases where mitochondrial DNA cannot be recovered with current PCR-based forensic technologies. Although additional work remains to be done before nuclear DNA recovered via these methods can be used routinely in operational casework for individual identification purposes, these results indicate substantial promise for the retrieval of probative individually identifying DNA data from the most limited and degraded forensic specimens. PMID:29494531

MOLECULAR CLONING, SEQUENCING, EXPRESSION AND BIOLOGICAL ACTIVITY OF GIANT PANDA (AILUROPODA MELANOLEUCA) INTERFERON-GAMMA.

PubMed

Zhu, Hui; Wang, Wen-Xiu; Wang, Bao-Qin; Zhu, Xiao-Fu; Wu, Xu-Jin; Ma, Qing-Yi; Chen, De-Kun

2012-06-29

The giant panda (Ailuropoda melanoleuca) is an endangered species and indigenous to China. Interferon-gamma (IFN-γ) is the only member of type □ IFN and is vital for the regulation of host adapted immunity and inflammatory response. Little is known aboutthe FN-γ gene and its roles in giant panda.In this study, IFN-γ gene of Qinling giant panda was amplified from total blood RNA by RT-CPR, cloned, sequenced and analysed. The open reading frame (ORF) of Qinling giant panda IFN-γ encodes 152 amino acidsand is highly similar to Sichuan giant panda with an identity of 99.3% in cDNA sequence. The IFN-γ cDNA sequence was ligated to the pET32a vector and transformed into E. coli BL21 competent cells. Expression of recombinant IFN-γ protein of Qinling giant panda in E. coli was confirmed by SDS-PAGE and Western blot analysis. Biological activity assay indicated that the recombinant IFN-γ protein at the concentration of 4-10 µg/ml activated the giant panda peripheral blood lymphocytes,while at 12 µg/mlinhibited. the activation of the lymphocytes.These findings provide insights into the evolution of giant panda IFN-γ and information regarding amino acid residues essential for their biological activity.

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

Networking Omic Data to Envisage Systems Biological Regulation.

PubMed

Kalapanulak, Saowalak; Saithong, Treenut; Thammarongtham, Chinae

To understand how biological processes work, it is necessary to explore the systematic regulation governing the behaviour of the processes. Not only driving the normal behavior of organisms, the systematic regulation evidently underlies the temporal responses to surrounding environments (dynamics) and long-term phenotypic adaptation (evolution). The systematic regulation is, in effect, formulated from the regulatory components which collaboratively work together as a network. In the drive to decipher such a code of lives, a spectrum of technologies has continuously been developed in the post-genomic era. With current advances, high-throughput sequencing technologies are tremendously powerful for facilitating genomics and systems biology studies in the attempt to understand system regulation inside the cells. The ability to explore relevant regulatory components which infer transcriptional and signaling regulation, driving core cellular processes, is thus enhanced. This chapter reviews high-throughput sequencing technologies, including second and third generation sequencing technologies, which support the investigation of genomics and transcriptomics data. Utilization of this high-throughput data to form the virtual network of systems regulation is explained, particularly transcriptional regulatory networks. Analysis of the resulting regulatory networks could lead to an understanding of cellular systems regulation at the mechanistic and dynamics levels. The great contribution of the biological networking approach to envisage systems regulation is finally demonstrated by a broad range of examples.

Azospirillum zeae sp. nov., a diazotrophic bacterium isolated from rhizosphere soil of Zea mays.

PubMed

Mehnaz, Samina; Weselowski, Brian; Lazarovits, George

2007-12-01

Two free-living nitrogen-fixing bacterial strains, N6 and N7(T), were isolated from corn rhizosphere. A polyphasic taxonomic approach, including morphological characterization, Biolog analysis, DNA-DNA hybridization, and 16S rRNA, cpn60 and nifH gene sequence analysis, was taken to analyse the two strains. 16S rRNA gene sequence analysis indicated that strains N6 and N7(T) both belonged to the genus Azospirillum and were closely related to Azospirillum oryzae (98.7 and 98.8 % similarity, respectively) and Azospirillum lipoferum (97.5 and 97.6 % similarity, respectively). DNA-DNA hybridization of strains N6 and N7(T) showed reassociation values of 48 and 37 %, respectively, with A. oryzae and 43 % with A. lipoferum. Sequences of the nifH and cpn60 genes of both strains showed 99 and approximately 95 % similarity, respectively, with those of A. oryzae. Chemotaxonomic characteristics (Q-10 as quinone system, 18 : 1omega7c as major fatty acid) and G+C content of the DNA (67.6 mol%) were also similar to those of members of the genus Azospirillum. Gene sequences and Biolog and fatty acid analysis showed that strains N6 and N7(T) differed from the closely related species A. lipoferum and A. oryzae. On the basis of these results, it is proposed that these nitrogen-fixing strains represent a novel species. The name Azospirillum zeae sp. nov. is suggested, with N7(T) (=NCCB 100147(T)=LMG 23989(T)) as the type strain.

The Ensembl genome database project.

PubMed

Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

2002-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

Plastome Sequence Determination and Comparative Analysis for Members of the Lolium-Festuca Grass Species Complex

PubMed Central

Hand, Melanie L.; Spangenberg, German C.; Forster, John W.; Cogan, Noel O. I.

2013-01-01

Chloroplast genome sequences are of broad significance in plant biology, due to frequent use in molecular phylogenetics, comparative genomics, population genetics, and genetic modification studies. The present study used a second-generation sequencing approach to determine and assemble the plastid genomes (plastomes) of four representatives from the agriculturally important Lolium-Festuca species complex of pasture grasses (Lolium multiflorum, Festuca pratensis, Festuca altissima, and Festuca ovina). Total cellular DNA was extracted from either roots or leaves, was sequenced, and the output was filtered for plastome-related reads. A comparison between sources revealed fewer plastome-related reads from root-derived template but an increase in incidental bacterium-derived sequences. Plastome assembly and annotation indicated high levels of sequence identity and a conserved organization and gene content between species. However, frequent deletions within the F. ovina plastome appeared to contribute to a smaller plastid genome size. Comparative analysis with complete plastome sequences from other members of the Poaceae confirmed conservation of most grass-specific features. Detailed analysis of the rbcL–psaI intergenic region, however, revealed a “hot-spot” of variation characterized by independent deletion events. The evolutionary implications of this observation are discussed. The complete plastome sequences are anticipated to provide the basis for potential organelle-specific genetic modification of pasture grasses. PMID:23550121

Single-cell sequencing technologies: current and future.

PubMed

Liang, Jialong; Cai, Wanshi; Sun, Zhongsheng

2014-10-20

Intensively developed in the last few years, single-cell sequencing technologies now present numerous advantages over traditional sequencing methods for solving the problems of biological heterogeneity and low quantities of available biological materials. The application of single-cell sequencing technologies has profoundly changed our understanding of a series of biological phenomena, including gene transcription, embryo development, and carcinogenesis. However, before single-cell sequencing technologies can be used extensively, researchers face the serious challenge of overcoming inherent issues of high amplification bias, low accuracy and reproducibility. Here, we simply summarize the techniques used for single-cell isolation, and review the current technologies used in single-cell genomic, transcriptomic, and epigenomic sequencing. We discuss the merits, defects, and scope of application of single-cell sequencing technologies and then speculate on the direction of future developments. Copyright © 2014 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Analysis of expressed sequence tags from Prunus mume flower and fruit and development of simple sequence repeat markers

PubMed Central

2010-01-01

Background Expressed Sequence Tag (EST) has been a cost-effective tool in molecular biology and represents an abundant valuable resource for genome annotation, gene expression, and comparative genomics in plants. Results In this study, we constructed a cDNA library of Prunus mume flower and fruit, sequenced 10,123 clones of the library, and obtained 8,656 expressed sequence tag (EST) sequences with high quality. The ESTs were assembled into 4,473 unigenes composed of 1,492 contigs and 2,981 singletons and that have been deposited in NCBI (accession IDs: GW868575 - GW873047), among which 1,294 unique ESTs were with known or putative functions. Furthermore, we found 1,233 putative simple sequence repeats (SSRs) in the P. mume unigene dataset. We randomly tested 42 pairs of PCR primers flanking potential SSRs, and 14 pairs were identified as true-to-type SSR loci and could amplify polymorphic bands from 20 individual plants of P. mume. We further used the 14 EST-SSR primer pairs to test the transferability on peach and plum. The result showed that nearly 89% of the primer pairs produced target PCR bands in the two species. A high level of marker polymorphism was observed in the plum species (65%) and low in the peach (46%), and the clustering analysis of the three species indicated that these SSR markers were useful in the evaluation of genetic relationships and diversity between and within the Prunus species. Conclusions We have constructed the first cDNA library of P. mume flower and fruit, and our data provide sets of molecular biology resources for P. mume and other Prunus species. These resources will be useful for further study such as genome annotation, new gene discovery, gene functional analysis, molecular breeding, evolution and comparative genomics between Prunus species. PMID:20626882

The Alveolate Perkinsus marinus: Biological Insights from EST Gene Discovery

PubMed Central

2010-01-01

Background Perkinsus marinus, a protozoan parasite of the eastern oyster Crassostrea virginica, has devastated natural and farmed oyster populations along the Atlantic and Gulf coasts of the United States. It is classified as a member of the Perkinsozoa, a recently established phylum considered close to the ancestor of ciliates, dinoflagellates, and apicomplexans, and a key taxon for understanding unique adaptations (e.g. parasitism) within the Alveolata. Despite intense parasite pressure, no disease-resistant oysters have been identified and no effective therapies have been developed to date. Results To gain insight into the biological basis of the parasite's virulence and pathogenesis mechanisms, and to identify genes encoding potential targets for intervention, we generated >31,000 5' expressed sequence tags (ESTs) derived from four trophozoite libraries generated from two P. marinus strains. Trimming and clustering of the sequence tags yielded 7,863 unique sequences, some of which carry a spliced leader. Similarity searches revealed that 55% of these had hits in protein sequence databases, of which 1,729 had their best hit with proteins from the chromalveolates (E-value ≤ 1e-5). Some sequences are similar to those proven to be targets for effective intervention in other protozoan parasites, and include not only proteases, antioxidant enzymes, and heat shock proteins, but also those associated with relict plastids, such as acetyl-CoA carboxylase and methyl erythrithol phosphate pathway components, and those involved in glycan assembly, protein folding/secretion, and parasite-host interactions. Conclusions Our transcriptome analysis of P. marinus, the first for any member of the Perkinsozoa, contributes new insight into its biology and taxonomic position. It provides a very informative, albeit preliminary, glimpse into the expression of genes encoding functionally relevant proteins as potential targets for chemotherapy, and evidence for the presence of a relict plastid. Further, although P. marinus sequences display significant similarity to those from both apicomplexans and dinoflagellates, the presence of trans-spliced transcripts confirms the previously established affinities with the latter. The EST analysis reported herein, together with the recently completed sequence of the P. marinus genome and the development of transfection methodology, should result in improved intervention strategies against dermo disease. PMID:20374649

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.

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

A dictionary based informational genome analysis

PubMed Central

2012-01-01

Background In the post-genomic era several methods of computational genomics are emerging to understand how the whole information is structured within genomes. Literature of last five years accounts for several alignment-free methods, arisen as alternative metrics for dissimilarity of biological sequences. Among the others, recent approaches are based on empirical frequencies of DNA k-mers in whole genomes. Results Any set of words (factors) occurring in a genome provides a genomic dictionary. About sixty genomes were analyzed by means of informational indexes based on genomic dictionaries, where a systemic view replaces a local sequence analysis. A software prototype applying a methodology here outlined carried out some computations on genomic data. We computed informational indexes, built the genomic dictionaries with different sizes, along with frequency distributions. The software performed three main tasks: computation of informational indexes, storage of these in a database, index analysis and visualization. The validation was done by investigating genomes of various organisms. A systematic analysis of genomic repeats of several lengths, which is of vivid interest in biology (for example to compute excessively represented functional sequences, such as promoters), was discussed, and suggested a method to define synthetic genetic networks. Conclusions We introduced a methodology based on dictionaries, and an efficient motif-finding software application for comparative genomics. This approach could be extended along many investigation lines, namely exported in other contexts of computational genomics, as a basis for discrimination of genomic pathologies. PMID:22985068

Transcriptome Analysis of the Octopus vulgaris Central Nervous System

PubMed Central

Zhang, Xiang; Mao, Yong; Huang, Zixia; Qu, Meng; Chen, Jun; Ding, Shaoxiong; Hong, Jingni; Sun, Tiantian

2012-01-01

Background Cephalopoda are a class of Mollusca species found in all the world's oceans. They are an important model organism in neurobiology. Unfortunately, the lack of neuronal molecular sequences, such as ESTs, transcriptomic or genomic information, has limited the development of molecular neurobiology research in this unique model organism. Results With high-throughput Illumina Solexa sequencing technology, we have generated 59,859 high quality sequences from 12,918,391 paired-end reads. Using BLASTx/BLASTn, 12,227 contigs have blast hits in the Swissprot, NR protein database and NT nucleotide database with E-value cutoff 1e−5. The comparison between the Octopus vulgaris central nervous system (CNS) library and the Aplysia californica/Lymnaea stagnalis CNS ESTs library yielded 5.93%/13.45% of O. vulgaris sequences with significant matches (1e−5) using BLASTn/tBLASTx. Meanwhile the hit percentage of the recently published Schistocerca gregaria, Tilapia or Hirudo medicinalis CNS library to the O. vulgaris CNS library is 21.03%–46.19%. We constructed the Phylogenetic tree using two genes related to CNS function, Synaptotagmin-7 and Synaptophysin. Lastly, we demonstrated that O. vulgaris may have a vertebrate-like Blood-Brain Barrier based on bioinformatic analysis. Conclusion This study provides a mass of molecular information that will contribute to further molecular biology research on O. vulgaris. In our presentation of the first CNS transcriptome analysis of O. vulgaris, we hope to accelerate the study of functional molecular neurobiology and comparative evolutionary biology. PMID:22768275

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

PubMed Central

Nichio, Bruno T. L.; Marchaukoski, Jeroniza Nunes; Raittz, Roberto Tadeu

2017-01-01

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST “all-against-all” methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology. PMID:29163633

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.

PubMed

Nichio, Bruno T L; Marchaukoski, Jeroniza Nunes; Raittz, Roberto Tadeu

2017-01-01

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST "all-against-all" methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology.

Dissecting biological “dark matter” with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth

PubMed Central

Marcy, Yann; Ouverney, Cleber; Bik, Elisabeth M.; Lösekann, Tina; Ivanova, Natalia; Martin, Hector Garcia; Szeto, Ernest; Platt, Darren; Hugenholtz, Philip; Relman, David A.; Quake, Stephen R.

2007-01-01

We have developed a microfluidic device that allows the isolation and genome amplification of individual microbial cells, thereby enabling organism-level genomic analysis of complex microbial ecosystems without the need for culture. This device was used to perform a directed survey of the human subgingival crevice and to isolate bacteria having rod-like morphology. Several isolated microbes had a 16S rRNA sequence that placed them in candidate phylum TM7, which has no cultivated or sequenced members. Genome amplification from individual TM7 cells allowed us to sequence and assemble >1,000 genes, providing insight into the physiology of members of this phylum. This approach enables single-cell genetic analysis of any uncultivated minority member of a microbial community. PMID:17620602

A detailed gene expression study of the Miscanthus genus reveals changes in the transcriptome associated with the rejuvenation of spring rhizomes.

PubMed

Barling, Adam; Swaminathan, Kankshita; Mitros, Therese; James, Brandon T; Morris, Juliette; Ngamboma, Ornella; Hall, Megan C; Kirkpatrick, Jessica; Alabady, Magdy; Spence, Ashley K; Hudson, Matthew E; Rokhsar, Daniel S; Moose, Stephen P

2013-12-09

The Miscanthus genus of perennial C4 grasses contains promising biofuel crops for temperate climates. However, few genomic resources exist for Miscanthus, which limits understanding of its interesting biology and future genetic improvement. A comprehensive catalog of expressed sequences were generated from a variety of Miscanthus species and tissue types, with an emphasis on characterizing gene expression changes in spring compared to fall rhizomes. Illumina short read sequencing technology was used to produce transcriptome sequences from different tissues and organs during distinct developmental stages for multiple Miscanthus species, including Miscanthus sinensis, Miscanthus sacchariflorus, and their interspecific hybrid Miscanthus × giganteus. More than fifty billion base-pairs of Miscanthus transcript sequence were produced. Overall, 26,230 Sorghum gene models (i.e., ~ 96% of predicted Sorghum genes) had at least five Miscanthus reads mapped to them, suggesting that a large portion of the Miscanthus transcriptome is represented in this dataset. The Miscanthus × giganteus data was used to identify genes preferentially expressed in a single tissue, such as the spring rhizome, using Sorghum bicolor as a reference. Quantitative real-time PCR was used to verify examples of preferential expression predicted via RNA-Seq. Contiguous consensus transcript sequences were assembled for each species and annotated using InterProScan. Sequences from the assembled transcriptome were used to amplify genomic segments from a doubled haploid Miscanthus sinensis and from Miscanthus × giganteus to further disentangle the allelic and paralogous variations in genes. This large expressed sequence tag collection creates a valuable resource for the study of Miscanthus biology by providing detailed gene sequence information and tissue preferred expression patterns. We have successfully generated a database of transcriptome assemblies and demonstrated its use in the study of genes of interest. Analysis of gene expression profiles revealed biological pathways that exhibit altered regulation in spring compared to fall rhizomes, which are consistent with their different physiological functions. The expression profiles of the subterranean rhizome provides a better understanding of the biological activities of the underground stem structures that are essentials for perenniality and the storage or remobilization of carbon and nutrient resources.

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

Taub, Margaret A; Corrada Bravo, Hector; Irizarry, Rafael A

2010-12-10

Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies, data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area, we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article, we review current knowledge about these biases, discuss their impact on analysis results, and propose solutions.

ChIP-seq: advantages and challenges of a maturing technology.

PubMed

Park, Peter J

2009-10-01

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a technique for genome-wide profiling of DNA-binding proteins, histone modifications or nucleosomes. Owing to the tremendous progress in next-generation sequencing technology, ChIP-seq offers higher resolution, less noise and greater coverage than its array-based predecessor ChIP-chip. With the decreasing cost of sequencing, ChIP-seq has become an indispensable tool for studying gene regulation and epigenetic mechanisms. In this Review, I describe the benefits and challenges in harnessing this technique with an emphasis on issues related to experimental design and data analysis. ChIP-seq experiments generate large quantities of data, and effective computational analysis will be crucial for uncovering biological mechanisms.

Expressed sequence tags from Atta laevigata and identification of candidate genes for the control of pest leaf-cutting ants.

PubMed

Rodovalho, Cynara M; Ferro, Milene; Fonseca, Fernando Pp; Antonio, Erik A; Guilherme, Ivan R; Henrique-Silva, Flávio; Bacci, Maurício

2011-06-17

Leafcutters are the highest evolved within Neotropical ants in the tribe Attini and model systems for studying caste formation, labor division and symbiosis with microorganisms. Some species of leafcutters are agricultural pests controlled by chemicals which affect other animals and accumulate in the environment. Aiming to provide genetic basis for the study of leafcutters and for the development of more specific and environmentally friendly methods for the control of pest leafcutters, we generated expressed sequence tag data from Atta laevigata, one of the pest ants with broad geographic distribution in South America. The analysis of the expressed sequence tags allowed us to characterize 2,006 unique sequences in Atta laevigata. Sixteen of these genes had a high number of transcripts and are likely positively selected for high level of gene expression, being responsible for three basic biological functions: energy conservation through redox reactions in mitochondria; cytoskeleton and muscle structuring; regulation of gene expression and metabolism. Based on leafcutters lifestyle and reports of genes involved in key processes of other social insects, we identified 146 sequences potential targets for controlling pest leafcutters. The targets are responsible for antixenobiosis, development and longevity, immunity, resistance to pathogens, pheromone function, cell signaling, behavior, polysaccharide metabolism and arginine kynase activity. The generation and analysis of expressed sequence tags from Atta laevigata have provided important genetic basis for future studies on the biology of leaf-cutting ants and may contribute to the development of a more specific and environmentally friendly method for the control of agricultural pest leafcutters.

Expressed sequence tags from Atta laevigata and identification of candidate genes for the control of pest leaf-cutting ants

PubMed Central

2011-01-01

Background Leafcutters are the highest evolved within Neotropical ants in the tribe Attini and model systems for studying caste formation, labor division and symbiosis with microorganisms. Some species of leafcutters are agricultural pests controlled by chemicals which affect other animals and accumulate in the environment. Aiming to provide genetic basis for the study of leafcutters and for the development of more specific and environmentally friendly methods for the control of pest leafcutters, we generated expressed sequence tag data from Atta laevigata, one of the pest ants with broad geographic distribution in South America. Results The analysis of the expressed sequence tags allowed us to characterize 2,006 unique sequences in Atta laevigata. Sixteen of these genes had a high number of transcripts and are likely positively selected for high level of gene expression, being responsible for three basic biological functions: energy conservation through redox reactions in mitochondria; cytoskeleton and muscle structuring; regulation of gene expression and metabolism. Based on leafcutters lifestyle and reports of genes involved in key processes of other social insects, we identified 146 sequences potential targets for controlling pest leafcutters. The targets are responsible for antixenobiosis, development and longevity, immunity, resistance to pathogens, pheromone function, cell signaling, behavior, polysaccharide metabolism and arginine kynase activity. Conclusion The generation and analysis of expressed sequence tags from Atta laevigata have provided important genetic basis for future studies on the biology of leaf-cutting ants and may contribute to the development of a more specific and environmentally friendly method for the control of agricultural pest leafcutters. PMID:21682882

RNA-Seq Analysis of Cocos nucifera: Transcriptome Sequencing and De Novo Assembly for Subsequent Functional Genomics Approaches

PubMed Central

Xia, Wei; Mason, Annaliese S.; Xia, Zhihui; Qiao, Fei; Zhao, Songlin; Tang, Haoru

2013-01-01

Background Cocos nucifera (coconut), a member of the Arecaceae family, is an economically important woody palm grown in tropical regions. Despite its agronomic importance, previous germplasm assessment studies have relied solely on morphological and agronomical traits. Molecular biology techniques have been scarcely used in assessment of genetic resources and for improvement of important agronomic and quality traits in Cocos nucifera, mostly due to the absence of available sequence information. Methodology/Principal Findings To provide basic information for molecular breeding and further molecular biological analysis in Cocos nucifera, we applied RNA-seq technology and de novo assembly to gain a global overview of the Cocos nucifera transcriptome from mixed tissue samples. Using Illumina sequencing, we obtained 54.9 million short reads and conducted de novo assembly to obtain 57,304 unigenes with an average length of 752 base pairs. Sequence comparison between assembled unigenes and released cDNA sequences of Cocos nucifera and Elaeis guineensis indicated that the assembled sequences were of high quality. Approximately 99.9% of unigenes were novel compared to the released coconut EST sequences. Using BLASTX, 68.2% of unigenes were successfully annotated based on the Genbank non-redundant (Nr) protein database. The annotated unigenes were then further classified using the Gene Ontology (GO), Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Conclusions/Significance Our study provides a large quantity of novel genetic information for Cocos nucifera. This information will act as a valuable resource for further molecular genetic studies and breeding in coconut, as well as for isolation and characterization of functional genes involved in different biochemical pathways in this important tropical crop species. PMID:23555859

RNA-Seq analysis of Cocos nucifera: transcriptome sequencing and de novo assembly for subsequent functional genomics approaches.

PubMed

Fan, Haikuo; Xiao, Yong; Yang, Yaodong; Xia, Wei; Mason, Annaliese S; Xia, Zhihui; Qiao, Fei; Zhao, Songlin; Tang, Haoru

2013-01-01

Cocos nucifera (coconut), a member of the Arecaceae family, is an economically important woody palm grown in tropical regions. Despite its agronomic importance, previous germplasm assessment studies have relied solely on morphological and agronomical traits. Molecular biology techniques have been scarcely used in assessment of genetic resources and for improvement of important agronomic and quality traits in Cocos nucifera, mostly due to the absence of available sequence information. To provide basic information for molecular breeding and further molecular biological analysis in Cocos nucifera, we applied RNA-seq technology and de novo assembly to gain a global overview of the Cocos nucifera transcriptome from mixed tissue samples. Using Illumina sequencing, we obtained 54.9 million short reads and conducted de novo assembly to obtain 57,304 unigenes with an average length of 752 base pairs. Sequence comparison between assembled unigenes and released cDNA sequences of Cocos nucifera and Elaeis guineensis indicated that the assembled sequences were of high quality. Approximately 99.9% of unigenes were novel compared to the released coconut EST sequences. Using BLASTX, 68.2% of unigenes were successfully annotated based on the Genbank non-redundant (Nr) protein database. The annotated unigenes were then further classified using the Gene Ontology (GO), Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Our study provides a large quantity of novel genetic information for Cocos nucifera. This information will act as a valuable resource for further molecular genetic studies and breeding in coconut, as well as for isolation and characterization of functional genes involved in different biochemical pathways in this important tropical crop species.

The Naegleria genome: a free-living microbial eukaryote lends unique insights into core eukaryotic cell biology

PubMed Central

Fritz-Laylin, Lillian K.; Ginger, Michael L.; Walsh, Charles; Dawson, Scott C.; Fulton, Chandler

2016-01-01

Naegleria gruberi, a free-living protist, has long been treasured as a model for basal body and flagellar assembly due to its ability to differentiate from crawling amoebae into swimming flagellates. The full genome sequence of Naegleria gruberi has recently been used to estimate gene families ancestral to all eukaryotes and to identify novel aspects of Naegleria biology, including likely facultative anaerobic metabolism, extensive signaling cascades, and evidence for sexuality. Distinctive features of the Naegleria genome and nuclear biology provide unique perspectives for comparative cell biology, including cell division, RNA processing and nucleolar assembly. We highlight here exciting new and novel aspects of Naegleria biology identified through genomic analysis. PMID:21392573

The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis.

PubMed

Mohorianu, Irina; Stocks, Matthew Benedict; Applegate, Christopher Steven; Folkes, Leighton; Moulton, Vincent

2017-01-01

RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation.The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed transcripts and a summary of their corresponding patterns. Finally we describe individual analysis tools such as PAREsnip, for the analysis of PARE (degradome) data or CoLIde for the identification of sRNA loci based on their expression patterns and the visualization of the results using the software. We illustrate the features of the UEA sRNA Workbench on Arabidopsis thaliana and Homo sapiens datasets.

Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation.

PubMed

Dueck, Hannah; Khaladkar, Mugdha; Kim, Tae Kyung; Spaethling, Jennifer M; Francis, Chantal; Suresh, Sangita; Fisher, Stephen A; Seale, Patrick; Beck, Sheryl G; Bartfai, Tamas; Kuhn, Bernhard; Eberwine, James; Kim, Junhyong

2015-06-09

Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question. We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved. Single-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.

MAGIC database and interfaces: an integrated package for gene discovery and expression.

PubMed

Cordonnier-Pratt, Marie-Michèle; Liang, Chun; Wang, Haiming; Kolychev, Dmitri S; Sun, Feng; Freeman, Robert; Sullivan, Robert; Pratt, Lee H

2004-01-01

The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC) Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs), and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

Microsporidian genome analysis reveals evolutionary strategies for obligate intracellular growth

USDA-ARS?s Scientific Manuscript database

Microsporidia comprise a large phylum of obligate intracellular eukaryotes that are fungalrelated parasites responsible for widespread disease, and here we address questions about microsporidia biology and evolution. We sequenced three microsporidian genomes from two species, Nematocida parisii and...

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis

PubMed Central

Steele, Joe; Bastola, Dhundy

2014-01-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base–base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel–Ziv techniques from data compression. PMID:23904502

Genomic analysis of five Lymantria dispar nucleopolyhedrovirus isolates and biological activity against different host strains of Lymantria dispar

USDA-ARS?s Scientific Manuscript database

To evaluate genetic diversity of Lymantria dispar nucleopolyhedrovirus (LdMNPV) at the genomic level, five isolates of LdMNPV from North America, Europe, and Asia were selected for complete genome sequence determination and analysis. These isolates consist of LdMNPV-2161 from Korea; LdMNPV-3029, a ...

Using a color-coded ambigraphic nucleic acid notation to visualize conserved palindromic motifs within and across genomes

PubMed Central

2014-01-01

Background Ambiscript is a graphically-designed nucleic acid notation that uses symbol symmetries to support sequence complementation, highlight biologically-relevant palindromes, and facilitate the analysis of consensus sequences. Although the original Ambiscript notation was designed to easily represent consensus sequences for multiple sequence alignments, the notation’s black-on-white ambiguity characters are unable to reflect the statistical distribution of nucleotides found at each position. We now propose a color-augmented ambigraphic notation to encode the frequency of positional polymorphisms in these consensus sequences. Results We have implemented this color-coding approach by creating an Adobe Flash® application ( http://www.ambiscript.org) that shades and colors modified Ambiscript characters according to the prevalence of the encoded nucleotide at each position in the alignment. The resulting graphic helps viewers perceive biologically-relevant patterns in multiple sequence alignments by uniquely combining color, shading, and character symmetries to highlight palindromes and inverted repeats in conserved DNA motifs. Conclusion Juxtaposing an intuitive color scheme over the deliberate character symmetries of an ambigraphic nucleic acid notation yields a highly-functional nucleic acid notation that maximizes information content and successfully embodies key principles of graphic excellence put forth by the statistician and graphic design theorist, Edward Tufte. PMID:24447494

Going forward with genetics: recent technological advances and forward genetics in mice.

PubMed

Moresco, Eva Marie Y; Li, Xiaohong; Beutler, Bruce

2013-05-01

Forward genetic analysis is an unbiased approach for identifying genes essential to defined biological phenomena. When applied to mice, it is one of the most powerful methods to facilitate understanding of the genetic basis of human biology and disease. The speed at which disease-causing mutations can be identified in mutagenized mice has been markedly increased by recent advances in DNA sequencing technology. Creating and analyzing mutant phenotypes may therefore become rate-limiting in forward genetic experimentation. We review the forward genetic approach and its future in the context of recent technological advances, in particular massively parallel DNA sequencing, induced pluripotent stem cells, and haploid embryonic stem cells. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Design, synthesis and biological evaluation of non-peptide PAR1 thrombin receptor antagonists based on small bifunctional templates: arginine and phenylalanine side chain groups are keys for receptor activity.

PubMed

Androutsou, Maria-Eleni; Saifeddine, Mahmoud; Hollenberg, Morley D; Matsoukas, John; Agelis, George

2010-04-01

In the present study, we report the synthesis and biological evaluation of a series of new non-peptide PAR(1) mimetic receptor antagonists, based on conformational analysis of the S(42)FLLR(46) tethered ligand (TL) sequence of PAR(1). These compounds incorporate the key pharmacophore groups in the TL sequence, guanidyl, amino and phenyl, which are essential for triggering receptor activity. Compounds 5 and 15 (50-100 microM) inhibited both TFLLR-amide (10 microM) and thrombin-mediated (0.5 and 1 U/ml; 5 and 10 microM) calcium signaling in a cultured human HEK cell assay.

Multifaceted biological insights from a draft genome sequence of the tobacco hornworm moth, Manduca sexta.

PubMed

Kanost, Michael R; Arrese, Estela L; Cao, Xiaolong; Chen, Yun-Ru; Chellapilla, Sanjay; Goldsmith, Marian R; Grosse-Wilde, Ewald; Heckel, David G; Herndon, Nicolae; Jiang, Haobo; Papanicolaou, Alexie; Qu, Jiaxin; Soulages, Jose L; Vogel, Heiko; Walters, James; Waterhouse, Robert M; Ahn, Seung-Joon; Almeida, Francisca C; An, Chunju; Aqrawi, Peshtewani; Bretschneider, Anne; Bryant, William B; Bucks, Sascha; Chao, Hsu; Chevignon, Germain; Christen, Jayne M; Clarke, David F; Dittmer, Neal T; Ferguson, Laura C F; Garavelou, Spyridoula; Gordon, Karl H J; Gunaratna, Ramesh T; Han, Yi; Hauser, Frank; He, Yan; Heidel-Fischer, Hanna; Hirsh, Ariana; Hu, Yingxia; Jiang, Hongbo; Kalra, Divya; Klinner, Christian; König, Christopher; Kovar, Christie; Kroll, Ashley R; Kuwar, Suyog S; Lee, Sandy L; Lehman, Rüdiger; Li, Kai; Li, Zhaofei; Liang, Hanquan; Lovelace, Shanna; Lu, Zhiqiang; Mansfield, Jennifer H; McCulloch, Kyle J; Mathew, Tittu; Morton, Brian; Muzny, Donna M; Neunemann, David; Ongeri, Fiona; Pauchet, Yannick; Pu, Ling-Ling; Pyrousis, Ioannis; Rao, Xiang-Jun; Redding, Amanda; Roesel, Charles; Sanchez-Gracia, Alejandro; Schaack, Sarah; Shukla, Aditi; Tetreau, Guillaume; Wang, Yang; Xiong, Guang-Hua; Traut, Walther; Walsh, Tom K; Worley, Kim C; Wu, Di; Wu, Wenbi; Wu, Yuan-Qing; Zhang, Xiufeng; Zou, Zhen; Zucker, Hannah; Briscoe, Adriana D; Burmester, Thorsten; Clem, Rollie J; Feyereisen, René; Grimmelikhuijzen, Cornelis J P; Hamodrakas, Stavros J; Hansson, Bill S; Huguet, Elisabeth; Jermiin, Lars S; Lan, Que; Lehman, Herman K; Lorenzen, Marce; Merzendorfer, Hans; Michalopoulos, Ioannis; Morton, David B; Muthukrishnan, Subbaratnam; Oakeshott, John G; Palmer, Will; Park, Yoonseong; Passarelli, A Lorena; Rozas, Julio; Schwartz, Lawrence M; Smith, Wendy; Southgate, Agnes; Vilcinskas, Andreas; Vogt, Richard; Wang, Ping; Werren, John; Yu, Xiao-Qiang; Zhou, Jing-Jiang; Brown, Susan J; Scherer, Steven E; Richards, Stephen; Blissard, Gary W

2016-09-01

Manduca sexta, known as the tobacco hornworm or Carolina sphinx moth, is a lepidopteran insect that is used extensively as a model system for research in insect biochemistry, physiology, neurobiology, development, and immunity. One important benefit of this species as an experimental model is its extremely large size, reaching more than 10 g in the larval stage. M. sexta larvae feed on solanaceous plants and thus must tolerate a substantial challenge from plant allelochemicals, including nicotine. We report the sequence and annotation of the M. sexta genome, and a survey of gene expression in various tissues and developmental stages. The Msex_1.0 genome assembly resulted in a total genome size of 419.4 Mbp. Repetitive sequences accounted for 25.8% of the assembled genome. The official gene set is comprised of 15,451 protein-coding genes, of which 2498 were manually curated. Extensive RNA-seq data from many tissues and developmental stages were used to improve gene models and for insights into gene expression patterns. Genome wide synteny analysis indicated a high level of macrosynteny in the Lepidoptera. Annotation and analyses were carried out for gene families involved in a wide spectrum of biological processes, including apoptosis, vacuole sorting, growth and development, structures of exoskeleton, egg shells, and muscle, vision, chemosensation, ion channels, signal transduction, neuropeptide signaling, neurotransmitter synthesis and transport, nicotine tolerance, lipid metabolism, and immunity. This genome sequence, annotation, and analysis provide an important new resource from a well-studied model insect species and will facilitate further biochemical and mechanistic experimental studies of many biological systems in insects. Copyright © 2016 Elsevier Ltd. All rights reserved.

An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance.

PubMed

Casimiro, Ana C; Vinga, Susana; Freitas, Ana T; Oliveira, Arlindo L

2008-02-07

Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior classification of the output still suffers from some limitations, which makes it difficult to assess the biological significance of the motifs found. Previous work has highlighted the existence of positional bias of motifs in the DNA sequences, which might indicate not only that the pattern is important, but also provide hints of the positions where these patterns occur preferentially. We propose to integrate position uniformity tests and over-representation tests to improve the accuracy of the classification of motifs. Using artificial data, we have compared three different statistical tests (Chi-Square, Kolmogorov-Smirnov and a Chi-Square bootstrap) to assess whether a given motif occurs uniformly in the promoter region of a gene. Using the test that performed better in this dataset, we proceeded to study the positional distribution of several well known cis-regulatory elements, in the promoter sequences of different organisms (S. cerevisiae, H. sapiens, D. melanogaster, E. coli and several Dicotyledons plants). The results show that position conservation is relevant for the transcriptional machinery. We conclude that many biologically relevant motifs appear heterogeneously distributed in the promoter region of genes, and therefore, that non-uniformity is a good indicator of biological relevance and can be used to complement over-representation tests commonly used. In this article we present the results obtained for the S. cerevisiae data sets.

Solid phase sequencing of biopolymers

DOEpatents

Cantor, Charles; Koster, Hubert

2010-09-28

This invention relates to methods for detecting and sequencing target nucleic acid sequences, to mass modified nucleic acid probes and arrays of probes useful in these methods, and to kits and systems which contain these probes. Useful methods involve hybridizing the nucleic acids or nucleic acids which represent complementary or homologous sequences of the target to an array of nucleic acid probes. These probes comprise a single-stranded portion, an optional double-stranded portion and a variable sequence within the single-stranded portion. The molecular weights of the hybridized nucleic acids of the set can be determined by mass spectroscopy, and the sequence of the target determined from the molecular weights of the fragments. Nucleic acids whose sequences can be determined include DNA or RNA in biological samples such as patient biopsies and environmental samples. Probes may be fixed to a solid support such as a hybridization chip to facilitate automated molecular weight analysis and identification of the target sequence.

[Application of mtDNA polymorphism in species identification of sarcosaphagous insects].

PubMed

Li, Xiang; Cai, Ji-feng

2011-04-01

Species identification of sarcosaphagous insects is one of the important steps in forensic research based on the knowledge of entomology. Recent studies reveal that the application of molecular biology, especially the mtDNA sequences analysis, works well in the species identification of sarcosaphagous insects. The molecular biology characteristics, structures, polymorphism of mtDNA of sarcosaphagous insects, and the recent studies in species identification of sarcosaphagous insects are reviewed in this article.

Unraveling the Complexities of Life Sciences Data.

PubMed

Higdon, Roger; Haynes, Winston; Stanberry, Larissa; Stewart, Elizabeth; Yandl, Gregory; Howard, Chris; Broomall, William; Kolker, Natali; Kolker, Eugene

2013-03-01

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

PubMed Central

Vallejos, Catalina A.; Marioni, John C.; Richardson, Sylvia

2015-01-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell’s lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach. PMID:26107944

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.

PubMed

Vallejos, Catalina A; Marioni, John C; Richardson, Sylvia

2015-06-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell's lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach.

Human genome project: revolutionizing biology through leveraging technology

NASA Astrophysics Data System (ADS)

Dahl, Carol A.; Strausberg, Robert L.

1996-04-01

The Human Genome Project (HGP) is an international project to develop genetic, physical, and sequence-based maps of the human genome. Since the inception of the HGP it has been clear that substantially improved technology would be required to meet the scientific goals, particularly in order to acquire the complete sequence of the human genome, and that these technologies coupled with the information forthcoming from the project would have a dramatic effect on the way biomedical research is performed in the future. In this paper, we discuss the state-of-the-art for genomic DNA sequencing, technological challenges that remain, and the potential technological paths that could yield substantially improved genomic sequencing technology. The impact of the technology developed from the HGP is broad-reaching and a discussion of other research and medical applications that are leveraging HGP-derived DNA analysis technologies is included. The multidisciplinary approach to the development of new technologies that has been successful for the HGP provides a paradigm for facilitating new genomic approaches toward understanding the biological role of functional elements and systems within the cell, including those encoded within genomic DNA and their molecular products.

StrBioLib: a Java library for development of custom computational structural biology applications.

PubMed

Chandonia, John-Marc

2007-08-01

StrBioLib is a library of Java classes useful for developing software for computational structural biology research. StrBioLib contains classes to represent and manipulate protein structures, biopolymer sequences, sets of biopolymer sequences, and alignments between biopolymers based on either sequence or structure. Interfaces are provided to interact with commonly used bioinformatics applications, including (psi)-blast, modeller, muscle and Primer3, and tools are provided to read and write many file formats used to represent bioinformatic data. The library includes a general-purpose neural network object with multiple training algorithms, the Hooke and Jeeves non-linear optimization algorithm, and tools for efficient C-style string parsing and formatting. StrBioLib is the basis for the Pred2ary secondary structure prediction program, is used to build the astral compendium for sequence and structure analysis, and has been extensively tested through use in many smaller projects. Examples and documentation are available at the site below. StrBioLib may be obtained under the terms of the GNU LGPL license from http://strbio.sourceforge.net/

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

[MALDI-TOF mass spectrometry in the investigation of large high-molecular biological compounds].

PubMed

Porubl'ova, L V; Rebriiev, A V; Hromovyĭ, T Iu; Minia, I I; Obolens'ka, M Iu

2009-01-01

MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight) mass spectrometry has become, in the recent years, a tool of choice for analyses of biological polymers. The wide mass range, high accuracy, informativity and sensitivity make it a superior method for analysis of all kinds of high-molecular biological compounds including proteins, nucleic acids and lipids. MALDI-TOF-MS is particularly suitable for the identification of proteins by mass fingerprint or microsequencing. Therefore it has become an important technique of proteomics. Furthermore, the method allows making a detailed analysis of post-translational protein modifications, protein-protein and protein-nucleic acid interactions. Recently, the method was also successfully applied to nucleic acid sequencing as well as screening for mutations.

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow.

PubMed

Suryawanshi, Gajendra W; Xu, Song; Xie, Yiming; Chou, Tom; Kim, Namshin; Chen, Irvin S Y; Kim, Sanggu

2017-06-14

Integration Site (IS) assays are a critical component of the study of retroviral integration sites and their biological significance. In recent retroviral gene therapy studies, IS assays, in combination with next-generation sequencing, have been used as a cell-tracking tool to characterize clonal stem cell populations sharing the same IS. For the accurate comparison of repopulating stem cell clones within and across different samples, the detection sensitivity, data reproducibility, and high-throughput capacity of the assay are among the most important assay qualities. This work provides a detailed protocol and data analysis workflow for bidirectional IS analysis. The bidirectional assay can simultaneously sequence both upstream and downstream vector-host junctions. Compared to conventional unidirectional IS sequencing approaches, the bidirectional approach significantly improves IS detection rates and the characterization of integration events at both ends of the target DNA. The data analysis pipeline described here accurately identifies and enumerates identical IS sequences through multiple steps of comparison that map IS sequences onto the reference genome and determine sequencing errors. Using an optimized assay procedure, we have recently published the detailed repopulation patterns of thousands of Hematopoietic Stem Cell (HSC) clones following transplant in rhesus macaques, demonstrating for the first time the precise time point of HSC repopulation and the functional heterogeneity of HSCs in the primate system. The following protocol describes the step-by-step experimental procedure and data analysis workflow that accurately identifies and quantifies identical IS sequences.

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

PubMed

Madrigal, Pedro

2017-03-01

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

Novel methodologies for spectral classification of exon and intron sequences

NASA Astrophysics Data System (ADS)

Kwan, Hon Keung; Kwan, Benjamin Y. M.; Kwan, Jennifer Y. Y.

2012-12-01

Digital processing of a nucleotide sequence requires it to be mapped to a numerical sequence in which the choice of nucleotide to numeric mapping affects how well its biological properties can be preserved and reflected from nucleotide domain to numerical domain. Digital spectral analysis of nucleotide sequences unfolds a period-3 power spectral value which is more prominent in an exon sequence as compared to that of an intron sequence. The success of a period-3 based exon and intron classification depends on the choice of a threshold value. The main purposes of this article are to introduce novel codes for 1-sequence numerical representations for spectral analysis and compare them to existing codes to determine appropriate representation, and to introduce novel thresholding methods for more accurate period-3 based exon and intron classification of an unknown sequence. The main findings of this study are summarized as follows: Among sixteen 1-sequence numerical representations, the K-Quaternary Code I offers an attractive performance. A windowed 1-sequence numerical representation (with window length of 9, 15, and 24 bases) offers a possible speed gain over non-windowed 4-sequence Voss representation which increases as sequence length increases. A winner threshold value (chosen from the best among two defined threshold values and one other threshold value) offers a top precision for classifying an unknown sequence of specified fixed lengths. An interpolated winner threshold value applicable to an unknown and arbitrary length sequence can be estimated from the winner threshold values of fixed length sequences with a comparable performance. In general, precision increases as sequence length increases. The study contributes an effective spectral analysis of nucleotide sequences to better reveal embedded properties, and has potential applications in improved genome annotation.

G-quadruplex prediction in E. coli genome reveals a conserved putative G-quadruplex-Hairpin-Duplex switch.

PubMed

Kaplan, Oktay I; Berber, Burak; Hekim, Nezih; Doluca, Osman

2016-11-02

Many studies show that short non-coding sequences are widely conserved among regulatory elements. More and more conserved sequences are being discovered since the development of next generation sequencing technology. A common approach to identify conserved sequences with regulatory roles relies on topological changes such as hairpin formation at the DNA or RNA level. G-quadruplexes, non-canonical nucleic acid topologies with little established biological roles, are increasingly considered for conserved regulatory element discovery. Since the tertiary structure of G-quadruplexes is strongly dependent on the loop sequence which is disregarded by the generally accepted algorithm, we hypothesized that G-quadruplexes with similar topology and, indirectly, similar interaction patterns, can be determined using phylogenetic clustering based on differences in the loop sequences. Phylogenetic analysis of 52 G-quadruplex forming sequences in the Escherichia coli genome revealed two conserved G-quadruplex motifs with a potential regulatory role. Further analysis revealed that both motifs tend to form hairpins and G quadruplexes, as supported by circular dichroism studies. The phylogenetic analysis as described in this work can greatly improve the discovery of functional G-quadruplex structures and may explain unknown regulatory patterns. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen).

PubMed

Rambaut, Andrew; Lam, Tommy T; Max Carvalho, Luiz; Pybus, Oliver G

2016-01-01

Gene sequences sampled at different points in time can be used to infer molecular phylogenies on a natural timescale of months or years, provided that the sequences in question undergo measurable amounts of evolutionary change between sampling times. Data sets with this property are termed heterochronous and have become increasingly common in several fields of biology, most notably the molecular epidemiology of rapidly evolving viruses. Here we introduce the cross-platform software tool, TempEst (formerly known as Path-O-Gen), for the visualization and analysis of temporally sampled sequence data. Given a molecular phylogeny and the dates of sampling for each sequence, TempEst uses an interactive regression approach to explore the association between genetic divergence through time and sampling dates. TempEst can be used to (1) assess whether there is sufficient temporal signal in the data to proceed with phylogenetic molecular clock analysis, and (2) identify sequences whose genetic divergence and sampling date are incongruent. Examination of the latter can help identify data quality problems, including errors in data annotation, sample contamination, sequence recombination, or alignment error. We recommend that all users of the molecular clock models implemented in BEAST first check their data using TempEst prior to analysis.

GenomeFingerprinter: the genome fingerprint and the universal genome fingerprint analysis for systematic comparative genomics.

PubMed

Ai, Yuncan; Ai, Hannan; Meng, Fanmei; Zhao, Lei

2013-01-01

No attention has been paid on comparing a set of genome sequences crossing genetic components and biological categories with far divergence over large size range. We define it as the systematic comparative genomics and aim to develop the methodology. First, we create a method, GenomeFingerprinter, to unambiguously produce a set of three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections, to illustrate the genome fingerprint of a given genome sequence. Second, we develop a set of concepts and tools, and thereby establish a method called the universal genome fingerprint analysis (UGFA). Particularly, we define the total genetic component configuration (TGCC) (including chromosome, plasmid, and phage) for describing a strain as a systematic unit, the universal genome fingerprint map (UGFM) of TGCC for differentiating strains as a universal system, and the systematic comparative genomics (SCG) for comparing a set of genomes crossing genetic components and biological categories. Third, we construct a method of quantitative analysis to compare two genomes by using the outcome dataset of genome fingerprint analysis. Specifically, we define the geometric center and its geometric mean for a given genome fingerprint map, followed by the Euclidean distance, the differentiate rate, and the weighted differentiate rate to quantitatively describe the difference between two genomes of comparison. Moreover, we demonstrate the applications through case studies on various genome sequences, giving tremendous insights into the critical issues in microbial genomics and taxonomy. We have created a method, GenomeFingerprinter, for rapidly computing, geometrically visualizing, intuitively comparing a set of genomes at genome fingerprint level, and hence established a method called the universal genome fingerprint analysis, as well as developed a method of quantitative analysis of the outcome dataset. These have set up the methodology of systematic comparative genomics based on the genome fingerprint analysis.

Metagenomic Assembly: Overview, Challenges and Applications

PubMed Central

Ghurye, Jay S.; Cepeda-Espinoza, Victoria; Pop, Mihai

2016-01-01

Advances in sequencing technologies have led to the increased use of high throughput sequencing in characterizing the microbial communities associated with our bodies and our environment. Critical to the analysis of the resulting data are sequence assembly algorithms able to reconstruct genes and organisms from complex mixtures. Metagenomic assembly involves new computational challenges due to the specific characteristics of the metagenomic data. In this survey, we focus on major algorithmic approaches for genome and metagenome assembly, and discuss the new challenges and opportunities afforded by this new field. We also review several applications of metagenome assembly in addressing interesting biological problems. PMID:27698619

kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences

PubMed Central

2017-01-01

Abstract Motifs of only 1–4 letters can play important roles when present at key locations within macromolecules. Because existing motif-discovery tools typically miss these position-specific short motifs, we developed kpLogo, a probability-based logo tool for integrated detection and visualization of position-specific ultra-short motifs from a set of aligned sequences. kpLogo also overcomes the limitations of conventional motif-visualization tools in handling positional interdependencies and utilizing ranked or weighted sequences increasingly available from high-throughput assays. kpLogo can be found at http://kplogo.wi.mit.edu/. PMID:28460012

The Genome of the Sea Urchin Strongylocentrotus purpuratus

PubMed Central

2011-01-01

We report the sequence and analysis of the 814-megabase genome of the sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology. The sequencing strategy combined whole-genome shotgun and bacterial artificial chromosome (BAC) sequences. This use of BAC clones, aided by a pooling strategy, overcame difficulties associated with high heterozygosity of the genome. The genome encodes about 23,300 genes, including many previously thought to be vertebrate innovations or known only outside the deuterostomes. This echinoderm genome provides an evolutionary outgroup for the chordates and yields insights into the evolution of deuterostomes. PMID:17095691

Markov models of genome segmentation

NASA Astrophysics Data System (ADS)

Thakur, Vivek; Azad, Rajeev K.; Ramaswamy, Ram

2007-01-01

We introduce Markov models for segmentation of symbolic sequences, extending a segmentation procedure based on the Jensen-Shannon divergence that has been introduced earlier. Higher-order Markov models are more sensitive to the details of local patterns and in application to genome analysis, this makes it possible to segment a sequence at positions that are biologically meaningful. We show the advantage of higher-order Markov-model-based segmentation procedures in detecting compositional inhomogeneity in chimeric DNA sequences constructed from genomes of diverse species, and in application to the E. coli K12 genome, boundaries of genomic islands, cryptic prophages, and horizontally acquired regions are accurately identified.

Importance of databases of nucleic acids for bioinformatic analysis focused to genomics

NASA Astrophysics Data System (ADS)

Jimenez-Gutierrez, L. R.; Barrios-Hernández, C. J.; Pedraza-Ferreira, G. R.; Vera-Cala, L.; Martinez-Perez, F.

2016-08-01

Recently, bioinformatics has become a new field of science, indispensable in the analysis of millions of nucleic acids sequences, which are currently deposited in international databases (public or private); these databases contain information of genes, RNA, ORF, proteins, intergenic regions, including entire genomes from some species. The analysis of this information requires computer programs; which were renewed in the use of new mathematical methods, and the introduction of the use of artificial intelligence. In addition to the constant creation of supercomputing units trained to withstand the heavy workload of sequence analysis. However, it is still necessary the innovation on platforms that allow genomic analyses, faster and more effectively, with a technological understanding of all biological processes.

Deep sequencing and genome-wide analysis reveals the expansion of MicroRNA genes in the gall midge Mayetiola destructor

PubMed Central

2013-01-01

Background MicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in regulating post transcriptional gene expression. Gall midges encompass a large group of insects that are of economic importance and also possess fascinating biological traits. The gall midge Mayetiola destructor, commonly known as the Hessian fly, is a destructive pest of wheat and model organism for studying gall midge biology and insect – host plant interactions. Results In this study, we systematically analyzed miRNAs from the Hessian fly. Deep-sequencing a Hessian fly larval transcriptome led to the identification of 89 miRNA species that are either identical or very similar to known miRNAs from other insects, and 184 novel miRNAs that have not been reported from other species. A genome-wide search through a draft Hessian fly genome sequence identified a total of 611 putative miRNA-encoding genes based on sequence similarity and the existence of a stem-loop structure for miRNA precursors. Analysis of the 611 putative genes revealed a striking feature: the dramatic expansion of several miRNA gene families. The largest family contained 91 genes that encoded 20 different miRNAs. Microarray analyses revealed the expression of miRNA genes was strictly regulated during Hessian fly larval development and abundance of many miRNA genes were affected by host genotypes. Conclusion The identification of a large number of miRNAs for the first time from a gall midge provides a foundation for further studies of miRNA functions in gall midge biology and behavior. The dramatic expansion of identical or similar miRNAs provides a unique system to study functional relations among miRNA iso-genes as well as changes in sequence specificity due to small changes in miRNAs and in their mRNA targets. These results may also facilitate the identification of miRNA genes for potential pest control through transgenic approaches. PMID:23496979

Efficient use of unlabeled data for protein sequence classification: a comparative study

PubMed Central

Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-01-01

Background Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags–the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Results Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. Conclusion The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably. PMID:19426450

Comprehensive analysis of genetic variations in strictly-defined Leber congenital amaurosis with whole-exome sequencing in Chinese

PubMed Central

Wang, Shi-Yuan; Zhang, Qi; Zhang, Xiang; Zhao, Pei-Quan

2016-01-01

AIM To make a comprehensive analysis of the potential pathogenic genes related with Leber congenital amaurosis (LCA) in Chinese. METHODS LCA subjects and their families were retrospectively collected from 2013 to 2015. Firstly, whole-exome sequencing was performed in patients who had underwent gene mutation screening with nothing found, and then homozygous sites was selected, candidate sites were annotated, and pathogenic analysis was conducted using softwares including Sorting Tolerant from Intolerant (SIFT), Polyphen-2, Mutation assessor, Condel, and Functional Analysis through Hidden Markov Models (FATHMM). Furthermore, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of pathogenic genes were performed followed by co-segregation analysis using Fisher exact Test. Sanger sequencing was used to validate single-nucleotide variations (SNVs). Expanded verification was performed in the rest patients. RESULTS Totally 51 LCA families with 53 patients and 24 family members were recruited. A total of 104 SNVs (66 LCA-related genes and 15 co-segregated genes) were submitted for expand verification. The frequencies of homozygous mutation of KRT12 and CYP1A1 were simultaneously observed in 3 families. Enrichment analysis showed that the potential pathogenic genes were mainly enriched in functions related to cell adhesion, biological adhesion, retinoid metabolic process, and eye development biological adhesion. Additionally, WFS1 and STAU2 had the highest homozygous frequencies. CONCLUSION LCA is a highly heterogeneous disease. Mutations in KRT12, CYP1A1, WFS1, and STAU2 may be involved in the development of LCA. PMID:27672588

Identification, expression and tissue distribution of a renalase homologue from mouse.

PubMed

Wang, Jian; Qi, Shaoling; Cheng, Wei; Li, Li; Wang, Fu; Li, Ying-Zi; Zhang, Shu-Ping

2008-12-01

FAD (flavin adenine dinucleotide)-dependent monoamine oxidases play very important roles in many biological processes. A novel monoamine oxidase, named renalase, has been identified in human kidney recently and is found to be markedly reduced in patients with end-stage renal disease (ESRD). Here, we reported the identification of a renalase homologue from mouse, termed mMAO-C (mouse monoamine oxidase-C) after the monoamine oxidase-A and -B (MAO-A and -B). This gene locates on the mouse chromosome 19C1 and its coding region spans 7 exons. The deuced amino acid sequences were predicted to contain a typical secretive signal peptide and a conserved amine oxidase domain. Phylogenetic analysis and multiple sequences alignment indicated that mMAO-C-like sequences exist in all examined species and share significant similarities. This gene has been submitted to the NCBI GenBank database (Accession number: DQ788834). With expression vectors generated from the cloned mMAO-C gene, exogenous protein was effectively expressed in both prokaryotic and eukaryotic cells. Recombinant mMAO-C protein was secreted out of human cell lines, indicating the biological function of its signal peptide. Moreover, tissue expression pattern analysis revealed that mMAO-C gene is predominantly expressed in the mouse kidney and testicle, which implies that kidney and testicle are the main sources of renalase secretion. Shortly, this study provides an insight into understanding the physiological and biological functions of mMAO-C and its homologues in endocrine.

An investigation of the impact of science course sequencing on student performance in high school science and math

NASA Astrophysics Data System (ADS)

Mary, Michael Todd

High school students in the United States for the past century have typically taken science courses in a sequence of biology followed by chemistry and concluding with physics. An alternative sequence, typically referred to as "physics first" inverts the traditional sequence by having students begin with physics and end with biology. Proponents of physics first cite advances in biological sciences that have dramatically changed the nature of high school biology and the potential benefit to student learning in math that would accompany taking an algebra-based physics course in the early years of high school to support changing the sequence. Using a quasi-experimental, quantitative research design, the purpose of this study was to investigate the impact of science course sequencing on student achievement in math and science at a school district that offered both course sequences. The Texas state end-of-course exams in biology, chemistry, physics, algebra I and geometry were used as the instruments measuring student achievement in math and science at the end of each academic year. Various statistical models were used to analyze these achievement data. The conclusion was, for students in this study, the sequence in which students took biology, chemistry, and physics had little or no impact on performance on the end-of-course assessments in each of these courses. Additionally there was only a minimal effect found with respect to math performance, leading to the conclusion that neither the traditional or "physics first" science course sequence presented an advantage for student achievement in math or science.

NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data

PubMed Central

Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole; Buus, Søren; Nielsen, Morten

2011-01-01

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new “omics”-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign. PMID:22073191

NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data.

PubMed

Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole; Buus, Søren; Nielsen, Morten

2011-01-01

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign.

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench

PubMed Central

Beckers, Matthew; Mohorianu, Irina; Stocks, Matthew; Applegate, Christopher; Dalmay, Tamas; Moulton, Vincent

2017-01-01

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this. PMID:28289155

Next-Generation Sequencing Platforms

NASA Astrophysics Data System (ADS)

Mardis, Elaine R.

2013-06-01

Automated DNA sequencing instruments embody an elegant interplay among chemistry, engineering, software, and molecular biology and have built upon Sanger's founding discovery of dideoxynucleotide sequencing to perform once-unfathomable tasks. Combined with innovative physical mapping approaches that helped to establish long-range relationships between cloned stretches of genomic DNA, fluorescent DNA sequencers produced reference genome sequences for model organisms and for the reference human genome. New types of sequencing instruments that permit amazing acceleration of data-collection rates for DNA sequencing have been developed. The ability to generate genome-scale data sets is now transforming the nature of biological inquiry. Here, I provide an historical perspective of the field, focusing on the fundamental developments that predated the advent of next-generation sequencing instruments and providing information about how these instruments work, their application to biological research, and the newest types of sequencers that can extract data from single DNA molecules.

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

PubMed

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

2016-10-10

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

High-Throughput Single-Cell RNA Sequencing and Data Analysis.

PubMed

Sagar; Herman, Josip Stefan; Pospisilik, John Andrew; Grün, Dominic

2018-01-01

Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

TaxI: a software tool for DNA barcoding using distance methods

PubMed Central

Steinke, Dirk; Vences, Miguel; Salzburger, Walter; Meyer, Axel

2005-01-01

DNA barcoding is a promising approach to the diagnosis of biological diversity in which DNA sequences serve as the primary key for information retrieval. Most existing software for evolutionary analysis of DNA sequences was designed for phylogenetic analyses and, hence, those algorithms do not offer appropriate solutions for the rapid, but precise analyses needed for DNA barcoding, and are also unable to process the often large comparative datasets. We developed a flexible software tool for DNA taxonomy, named TaxI. This program calculates sequence divergences between a query sequence (taxon to be barcoded) and each sequence of a dataset of reference sequences defined by the user. Because the analysis is based on separate pairwise alignments this software is also able to work with sequences characterized by multiple insertions and deletions that are difficult to align in large sequence sets (i.e. thousands of sequences) by multiple alignment algorithms because of computational restrictions. Here, we demonstrate the utility of this approach with two datasets of fish larvae and juveniles from Lake Constance and juvenile land snails under different models of sequence evolution. Sets of ribosomal 16S rRNA sequences, characterized by multiple indels, performed as good as or better than cox1 sequence sets in assigning sequences to species, demonstrating the suitability of rRNA genes for DNA barcoding. PMID:16214755

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

A comparison of sequencing platforms and bioinformatics pipelines for compositional analysis of the gut microbiome.

PubMed

Allali, Imane; Arnold, Jason W; Roach, Jeffrey; Cadenas, Maria Belen; Butz, Natasha; Hassan, Hosni M; Koci, Matthew; Ballou, Anne; Mendoza, Mary; Ali, Rizwana; Azcarate-Peril, M Andrea

2017-09-13

Advancements in Next Generation Sequencing (NGS) technologies regarding throughput, read length and accuracy had a major impact on microbiome research by significantly improving 16S rRNA amplicon sequencing. As rapid improvements in sequencing platforms and new data analysis pipelines are introduced, it is essential to evaluate their capabilities in specific applications. The aim of this study was to assess whether the same project-specific biological conclusions regarding microbiome composition could be reached using different sequencing platforms and bioinformatics pipelines. Chicken cecum microbiome was analyzed by 16S rRNA amplicon sequencing using Illumina MiSeq, Ion Torrent PGM, and Roche 454 GS FLX Titanium platforms, with standard and modified protocols for library preparation. We labeled the bioinformatics pipelines included in our analysis QIIME1 and QIIME2 (de novo OTU picking [not to be confused with QIIME version 2 commonly referred to as QIIME2]), QIIME3 and QIIME4 (open reference OTU picking), UPARSE1 and UPARSE2 (each pair differs only in the use of chimera depletion methods), and DADA2 (for Illumina data only). GS FLX+ yielded the longest reads and highest quality scores, while MiSeq generated the largest number of reads after quality filtering. Declines in quality scores were observed starting at bases 150-199 for GS FLX+ and bases 90-99 for MiSeq. Scores were stable for PGM-generated data. Overall microbiome compositional profiles were comparable between platforms; however, average relative abundance of specific taxa varied depending on sequencing platform, library preparation method, and bioinformatics analysis. Specifically, QIIME with de novo OTU picking yielded the highest number of unique species and alpha diversity was reduced with UPARSE and DADA2 compared to QIIME. The three platforms compared in this study were capable of discriminating samples by treatment, despite differences in diversity and abundance, leading to similar biological conclusions. Our results demonstrate that while there were differences in depth of coverage and phylogenetic diversity, all workflows revealed comparable treatment effects on microbial diversity. To increase reproducibility and reliability and to retain consistency between similar studies, it is important to consider the impact on data quality and relative abundance of taxa when selecting NGS platforms and analysis tools for microbiome studies.

A Thiazole Coumarin (TC) Turn-On Fluorescence Probe for AT-Base Pair Detection and Multipurpose Applications in Different Biological Systems

NASA Astrophysics Data System (ADS)

Narayanaswamy, Nagarjun; Kumar, Manoj; Das, Sadhan; Sharma, Rahul; Samanta, Pralok K.; Pati, Swapan K.; Dhar, Suman K.; Kundu, Tapas K.; Govindaraju, T.

2014-09-01

Sequence-specific recognition of DNA by small turn-on fluorescence probes is a promising tool for bioimaging, bioanalytical and biomedical applications. Here, the authors report a novel cell-permeable and red fluorescent hemicyanine-based thiazole coumarin (TC) probe for DNA recognition, nuclear staining and cell cycle analysis. TC exhibited strong fluorescence enhancement in the presence of DNA containing AT-base pairs, but did not fluoresce with GC sequences, single-stranded DNA, RNA and proteins. The fluorescence staining of HeLa S3 and HEK 293 cells by TC followed by DNase and RNase digestion studies depicted the selective staining of DNA in the nucleus over the cytoplasmic region. Fluorescence-activated cell sorting (FACS) analysis by flow cytometry demonstrated the potential application of TC in cell cycle analysis in HEK 293 cells. Metaphase chromosome and malaria parasite DNA imaging studies further confirmed the in vivo diagnostic and therapeutic applications of probe TC. Probe TC may find multiple applications in fluorescence spectroscopy, diagnostics, bioimaging and molecular and cell biology.

A Thiazole Coumarin (TC) Turn-On Fluorescence Probe for AT-Base Pair Detection and Multipurpose Applications in Different Biological Systems

PubMed Central

Narayanaswamy, Nagarjun; Kumar, Manoj; Das, Sadhan; Sharma, Rahul; Samanta, Pralok K.; Pati, Swapan K.; Dhar, Suman K.; Kundu, Tapas K.; Govindaraju, T.

2014-01-01

Sequence-specific recognition of DNA by small turn-on fluorescence probes is a promising tool for bioimaging, bioanalytical and biomedical applications. Here, the authors report a novel cell-permeable and red fluorescent hemicyanine-based thiazole coumarin (TC) probe for DNA recognition, nuclear staining and cell cycle analysis. TC exhibited strong fluorescence enhancement in the presence of DNA containing AT-base pairs, but did not fluoresce with GC sequences, single-stranded DNA, RNA and proteins. The fluorescence staining of HeLa S3 and HEK 293 cells by TC followed by DNase and RNase digestion studies depicted the selective staining of DNA in the nucleus over the cytoplasmic region. Fluorescence-activated cell sorting (FACS) analysis by flow cytometry demonstrated the potential application of TC in cell cycle analysis in HEK 293 cells. Metaphase chromosome and malaria parasite DNA imaging studies further confirmed the in vivo diagnostic and therapeutic applications of probe TC. Probe TC may find multiple applications in fluorescence spectroscopy, diagnostics, bioimaging and molecular and cell biology. PMID:25252596

Computational discovery of small open reading frames in Bacillus lehensis

NASA Astrophysics Data System (ADS)

Zainuddin, Nurhafizhoh; Illias, Rosli Md.; Mahadi, Nor Muhammad; Firdaus-Raih, Mohd

2015-09-01

Bacillus lehensis is a Gram-positive and endospore-forming alkalitolerant bacterial strain. In recent years there has been increasing interest in alkaliphilic bacteria and their ability to grow under extreme conditions as well as their ability to serve various important functions in industrial biology especially enzyme production. Small open reading frames (sORFs) have emerged as important regulators in various biological roles such as tumor progression, hormone signalling and stress response. Over the past decade, many biocomputational tools have been developed to predict genes in bacterial genomes. In this study, three softwares were used to predict sORF (≤ 80 aa) in B. lehensis by using whole genome sequence. We used comparative analysis to identify the sORFs in B. lehensis that conserved across all other bacterial genomes. We extended the analysis by doing the homology analysis against protein database. This study established the sORFs in B. lehensis that are conserved across bacteria which might has important biological function which still remain elusive in biological field.

GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

PubMed

Subhash, Santhilal; Kanduri, Chandrasekhar

2016-09-13

High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc. In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies. GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Resources and Recommendations for Using Transcriptomics to Address Grand Challenges in Comparative Biology.

PubMed

Mykles, Donald L; Burnett, Karen G; Durica, David S; Joyce, Blake L; McCarthy, Fiona M; Schmidt, Carl J; Stillman, Jonathon H

2016-12-01

High-throughput RNA sequencing (RNA-seq) technology has become an important tool for studying physiological responses of organisms to changes in their environment. De novo assembly of RNA-seq data has allowed researchers to create a comprehensive catalog of genes expressed in a tissue and to quantify their expression without a complete genome sequence. The contributions from the "Tapping the Power of Crustacean Transcriptomics to Address Grand Challenges in Comparative Biology" symposium in this issue show the successes and limitations of using RNA-seq in the study of crustaceans. In conjunction with the symposium, the Animal Genome to Phenome Research Coordination Network collated comments from participants at the meeting regarding the challenges encountered when using transcriptomics in their research. Input came from novices and experts ranging from graduate students to principal investigators. Many were unaware of the bioinformatics analysis resources currently available on the CyVerse platform. Our analysis of community responses led to three recommendations for advancing the field: (1) integration of genomic and RNA-seq sequence assemblies for crustacean gene annotation and comparative expression; (2) development of methodologies for the functional analysis of genes; and (3) information and training exchange among laboratories for transmission of best practices. The field lacks the methods for manipulating tissue-specific gene expression. The decapod crustacean research community should consider the cherry shrimp, Neocaridina denticulata, as a decapod model for the application of transgenic tools for functional genomics. This would require a multi-investigator effort. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Algorithm to find distant repeats in a single protein sequence

PubMed Central

Banerjee, Nirjhar; Sarani, Rangarajan; Ranjani, Chellamuthu Vasuki; Sowmiya, Govindaraj; Michael, Daliah; Balakrishnan, Narayanasamy; Sekar, Kanagaraj

2008-01-01

Distant repeats in protein sequence play an important role in various aspects of protein analysis. A keen analysis of the distant repeats would enable to establish a firm relation of the repeats with respect to their function and three-dimensional structure during the evolutionary process. Further, it enlightens the diversity of duplication during the evolution. To this end, an algorithm has been developed to find all distant repeats in a protein sequence. The scores from Point Accepted Mutation (PAM) matrix has been deployed for the identification of amino acid substitutions while detecting the distant repeats. Due to the biological importance of distant repeats, the proposed algorithm will be of importance to structural biologists, molecular biologists, biochemists and researchers involved in phylogenetic and evolutionary studies. PMID:19052663

Node fingerprinting: an efficient heuristic for aligning biological networks.

PubMed

Radu, Alex; Charleston, Michael

2014-10-01

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

Using SQL Databases for Sequence Similarity Searching and Analysis.

PubMed

Pearson, William R; Mackey, Aaron J

2017-09-13

Relational databases can integrate diverse types of information and manage large sets of similarity search results, greatly simplifying genome-scale analyses. By focusing on taxonomic subsets of sequences, relational databases can reduce the size and redundancy of sequence libraries and improve the statistical significance of homologs. In addition, by loading similarity search results into a relational database, it becomes possible to explore and summarize the relationships between all of the proteins in an organism and those in other biological kingdoms. This unit describes how to use relational databases to improve the efficiency of sequence similarity searching and demonstrates various large-scale genomic analyses of homology-related data. It also describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. The unit also introduces search_demo, a database that stores sequence similarity search results. The search_demo database is then used to explore the evolutionary relationships between E. coli proteins and proteins in other organisms in a large-scale comparative genomic analysis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Quantitative analysis and prediction of G-quadruplex forming sequences in double-stranded DNA

PubMed Central

Kim, Minji; Kreig, Alex; Lee, Chun-Ying; Rube, H. Tomas; Calvert, Jacob; Song, Jun S.; Myong, Sua

2016-01-01

Abstract G-quadruplex (GQ) is a four-stranded DNA structure that can be formed in guanine-rich sequences. GQ structures have been proposed to regulate diverse biological processes including transcription, replication, translation and telomere maintenance. Recent studies have demonstrated the existence of GQ DNA in live mammalian cells and a significant number of potential GQ forming sequences in the human genome. We present a systematic and quantitative analysis of GQ folding propensity on a large set of 438 GQ forming sequences in double-stranded DNA by integrating fluorescence measurement, single-molecule imaging and computational modeling. We find that short minimum loop length and the thymine base are two main factors that lead to high GQ folding propensity. Linear and Gaussian process regression models further validate that the GQ folding potential can be predicted with high accuracy based on the loop length distribution and the nucleotide content of the loop sequences. Our study provides important new parameters that can inform the evaluation and classification of putative GQ sequences in the human genome. PMID:27095201

Statistical properties of DNA sequences

NASA Technical Reports Server (NTRS)

Peng, C. K.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Simons, M.; Stanley, H. E.

1995-01-01

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Whole exome sequencing: a state-of-the-art approach for defining (and exploring!) genetic landscapes in pediatric nephrology.

PubMed

Gulati, Ashima; Somlo, Stefan

2018-05-01

The genesis of whole exome sequencing as a powerful tool for detailing the protein coding sequence of the human genome was conceptualized based on the availability of next-generation sequencing technology and knowledge of the human reference genome. The field of pediatric nephrology enriched with molecularly unsolved phenotypes is allowing the clinical and research application of whole exome sequencing to enable novel gene discovery and provide amendment of phenotypic misclassification. Recent studies in the field have informed us that newer high-throughput sequencing techniques are likely to be of high yield when applied in conjunction with conventional genomic approaches such as linkage analysis and other strategies used to focus subsequent analysis. They have also emphasized the need for the validation of novel genetic findings in large collaborative cohorts and the production of robust corroborative biological data. The well-structured application of comprehensive genomic testing in clinical and research arenas will hopefully continue to advance patient care and precision medicine, but does call for attention to be paid to its integrated challenges.

In silico analysis of expressed sequence tags from Trichostrongylus vitrinus (Nematoda): comparison of the automated ESTExplorer workflow platform with conventional database searches.

PubMed

Nagaraj, Shivashankar H; Gasser, Robin B; Nisbet, Alasdair J; Ranganathan, Shoba

2008-01-01

The analysis of expressed sequence tags (EST) offers a rapid and cost effective approach to elucidate the transcriptome of an organism, but requires several computational methods for assembly and annotation. Researchers frequently analyse each step manually, which is laborious and time consuming. We have recently developed ESTExplorer, a semi-automated computational workflow system, in order to achieve the rapid analysis of EST datasets. In this study, we evaluated EST data analysis for the parasitic nematode Trichostrongylus vitrinus (order Strongylida) using ESTExplorer, compared with database matching alone. We functionally annotated 1776 ESTs obtained via suppressive-subtractive hybridisation from T. vitrinus, an important parasitic trichostrongylid of small ruminants. Cluster and comparative genomic analyses of the transcripts using ESTExplorer indicated that 290 (41%) sequences had homologues in Caenorhabditis elegans, 329 (42%) in parasitic nematodes, 202 (28%) in organisms other than nematodes, and 218 (31%) had no significant match to any sequence in the current databases. Of the C. elegans homologues, 90 were associated with 'non-wildtype' double-stranded RNA interference (RNAi) phenotypes, including embryonic lethality, maternal sterility, sterile progeny, larval arrest and slow growth. We could functionally classify 267 (38%) sequences using the Gene Ontologies (GO) and establish pathway associations for 230 (33%) sequences using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Further examination of this EST dataset revealed a number of signalling molecules, proteases, protease inhibitors, enzymes, ion channels and immune-related genes. In addition, we identified 40 putative secreted proteins that could represent potential candidates for developing novel anthelmintics or vaccines. We further compared the automated EST sequence annotations, using ESTExplorer, with database search results for individual T. vitrinus ESTs. ESTExplorer reliably and rapidly annotated 301 ESTs, with pathway and GO information, eliminating 60 low quality hits from database searches. We evaluated the efficacy of ESTExplorer in analysing EST data, and demonstrate that computational tools can be used to accelerate the process of gene discovery in EST sequencing projects. The present study has elucidated sets of relatively conserved and potentially novel genes for biological investigation, and the annotated EST set provides further insight into the molecular biology of T. vitrinus, towards the identification of novel drug targets.

Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes

NASA Astrophysics Data System (ADS)

Weigt, Martin

Over the last years, biological research has been revolutionized by experimental high-throughput techniques, in particular by next-generation sequencing technology. Unprecedented amounts of data are accumulating, and there is a growing request for computational methods unveiling the information hidden in raw data, thereby increasing our understanding of complex biological systems. Statistical-physics models based on the maximum-entropy principle have, in the last few years, played an important role in this context. To give a specific example, proteins and many non-coding RNA show a remarkable degree of structural and functional conservation in the course of evolution, despite a large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach - called Direct-Coupling Analysis - to link this sequence variability (easy to observe in sequence alignments, which are available in public sequence databases) to bio-molecular structure and function. In my presentation I will show, how this methodology can be used (i) to infer contacts between residues and thus to guide tertiary and quaternary protein structure prediction and RNA structure prediction, (ii) to discriminate interacting from non-interacting protein families, and thus to infer conserved protein-protein interaction networks, and (iii) to reconstruct mutational landscapes and thus to predict the phenotypic effect of mutations. References [1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt ''Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1'', Mol. Biol. Evol. (2015), doi: 10.1093/molbev/msv211 [2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt ''Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction'', Nucleic Acids Research (2015), doi: 10.1093/nar/gkv932 [3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R. Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, ''Direct-coupling analysis of residue co-evolution captures native contacts across many protein families'', Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).

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.

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

Deciphering the genomic targets of alkylating polyamide conjugates using high-throughput sequencing

PubMed Central

Chandran, Anandhakumar; Syed, Junetha; Taylor, Rhys D.; Kashiwazaki, Gengo; Sato, Shinsuke; Hashiya, Kaori; Bando, Toshikazu; Sugiyama, Hiroshi

2016-01-01

Chemically engineered small molecules targeting specific genomic sequences play an important role in drug development research. Pyrrole-imidazole polyamides (PIPs) are a group of molecules that can bind to the DNA minor-groove and can be engineered to target specific sequences. Their biological effects rely primarily on their selective DNA binding. However, the binding mechanism of PIPs at the chromatinized genome level is poorly understood. Herein, we report a method using high-throughput sequencing to identify the DNA-alkylating sites of PIP-indole-seco-CBI conjugates. High-throughput sequencing analysis of conjugate 2 showed highly similar DNA-alkylating sites on synthetic oligos (histone-free DNA) and on human genomes (chromatinized DNA context). To our knowledge, this is the first report identifying alkylation sites across genomic DNA by alkylating PIP conjugates using high-throughput sequencing. PMID:27098039

For the Love of Statistics: Appreciating and Learning to Apply Experimental Analysis and Statistics through Computer Programming Activities

ERIC Educational Resources Information Center

Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.

2016-01-01

For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…

Biological sequence compression algorithms.

PubMed

Matsumoto, T; Sadakane, K; Imai, H

2000-01-01

Today, more and more DNA sequences are becoming available. The information about DNA sequences are stored in molecular biology databases. The size and importance of these databases will be bigger and bigger in the future, therefore this information must be stored or communicated efficiently. Furthermore, sequence compression can be used to define similarities between biological sequences. The standard compression algorithms such as gzip or compress cannot compress DNA sequences, but only expand them in size. On the other hand, CTW (Context Tree Weighting Method) can compress DNA sequences less than two bits per symbol. These algorithms do not use special structures of biological sequences. Two characteristic structures of DNA sequences are known. One is called palindromes or reverse complements and the other structure is approximate repeats. Several specific algorithms for DNA sequences that use these structures can compress them less than two bits per symbol. In this paper, we improve the CTW so that characteristic structures of DNA sequences are available. Before encoding the next symbol, the algorithm searches an approximate repeat and palindrome using hash and dynamic programming. If there is a palindrome or an approximate repeat with enough length then our algorithm represents it with length and distance. By using this preprocessing, a new program achieves a little higher compression ratio than that of existing DNA-oriented compression algorithms. We also describe new compression algorithm for protein sequences.

PyPathway: Python Package for Biological Network Analysis and Visualization.

PubMed

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

Novel features and enhancements in BioBin, a tool for the biologically inspired binning and association analysis of rare variants

PubMed Central

Byrska-Bishop, Marta; Wallace, John; Frase, Alexander T; Ritchie, Marylyn D

2018-01-01

Abstract Motivation BioBin is an automated bioinformatics tool for the multi-level biological binning of sequence variants. Herein, we present a significant update to BioBin which expands the software to facilitate a comprehensive rare variant analysis and incorporates novel features and analysis enhancements. Results In BioBin 2.3, we extend our software tool by implementing statistical association testing, updating the binning algorithm, as well as incorporating novel analysis features providing for a robust, highly customizable, and unified rare variant analysis tool. Availability and implementation The BioBin software package is open source and freely available to users at http://www.ritchielab.com/software/biobin-download Contact mdritchie@geisinger.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28968757

Analysis of expressed sequence tags from Maize mosaic rhabdovirus-infected gut tissues of Peregrinus maidis reveals the presence of key components of insect innate immunity.

PubMed

Whitfield, A E; Rotenberg, D; Aritua, V; Hogenhout, S A

2011-04-01

The corn planthopper, Peregrinus maidis, causes direct feeding damage to plants and transmits Maize mosaic rhabdovirus (MMV) in a persistent-propagative manner. MMV must cross several insect tissue layers for successful transmission to occur, and the gut serves as an important barrier for rhabdovirus transmission. In order to facilitate the identification of proteins that may interact with MMV either by facilitating acquisition or responding to virus infection, we generated and analysed the gut transcriptome of P. maidis. From two normalized cDNA libraries, we generated a P. maidis gut transcriptome composed of 20,771 expressed sequence tags (ESTs). Assembly of the sequences yielded 1860 contigs and 14,032 singletons, and biological roles were assigned to 5793 (36%). Comparison of P. maidis ESTs with other insect amino acid sequences revealed that P. maidis shares greatest sequence similarity with another hemipteran, the brown planthopper Nilaparvata lugens. We identified 202 P. maidis transcripts with putative homology to proteins associated with insect innate immunity, including those implicated in the Toll, Imd, JAK/STAT, Jnk and the small-interfering RNA-mediated pathways. Sequence comparisons between our P. maidis gut EST collection and the currently available National Center for Biotechnology Information EST database collection for Ni. lugens revealed that a pathogen recognition receptor in the Imd pathway, peptidoglycan recognition protein-long class (PGRP-LC), is present in these two members of the family Delphacidae; however, these recognition receptors are lacking in the model hemipteran Acyrthosiphon pisum. In addition, we identified sequences in the P. maidis gut transcriptome that share significant amino acid sequence similarities with the rhabdovirus receptor molecule, acetylcholine receptor (AChR), found in other hosts. This EST analysis sheds new light on immune response pathways in hemipteran guts that will be useful for further dissecting innate defence response pathways to rhabdovirus infection. © 2011 The Authors. Insect Molecular Biology © 2011 The Royal Entomological Society.

Evaluation of a Secondary School Science Program Inversion: Moving from a Traditional to a Modifified-PCB Sequence

ERIC Educational Resources Information Center

Gaubatz, Julie

2013-01-01

Studies of high-school science course sequences have been limited primarily to a small number of site-specific investigations comparing traditional science sequences (e.g., Biology-Chemistry-Physics: BCP) to various Physics First-influenced sequences (Physics-Chemistry-Biology: PCB). The present study summarizes a five-year program evaluation…

GenePRIMP: Improving Microbial Gene Prediction Quality

ScienceCinema

Pati, Amrita

2018-01-24

Amrita Pati of the DOE Joint Genome Institute's Genome Biology group talks about a computational pipeline that evaluates the accuracy of gene models in genomes and metagenomes at different stages of finishing at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.

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

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences.

PubMed

Du, Pu-Feng; Zhao, Wei; Miao, Yang-Yang; Wei, Le-Yi; Wang, Likun

2017-11-14

With the avalanche of biological sequences in public databases, one of the most challenging problems in computational biology is to predict their biological functions and cellular attributes. Most of the existing prediction algorithms can only handle fixed-length numerical vectors. Therefore, it is important to be able to represent biological sequences with various lengths using fixed-length numerical vectors. Although several algorithms, as well as software implementations, have been developed to address this problem, these existing programs can only provide a fixed number of representation modes. Every time a new sequence representation mode is developed, a new program will be needed. In this paper, we propose the UltraPse as a universal software platform for this problem. The function of the UltraPse is not only to generate various existing sequence representation modes, but also to simplify all future programming works in developing novel representation modes. The extensibility of UltraPse is particularly enhanced. It allows the users to define their own representation mode, their own physicochemical properties, or even their own types of biological sequences. Moreover, UltraPse is also the fastest software of its kind. The source code package, as well as the executables for both Linux and Windows platforms, can be downloaded from the GitHub repository.

The Transcriptome Analysis and Comparison Explorer--T-ACE: a platform-independent, graphical tool to process large RNAseq datasets of non-model organisms.

PubMed

Philipp, E E R; Kraemer, L; Mountfort, D; Schilhabel, M; Schreiber, S; Rosenstiel, P

2012-03-15

Next generation sequencing (NGS) technologies allow a rapid and cost-effective compilation of large RNA sequence datasets in model and non-model organisms. However, the storage and analysis of transcriptome information from different NGS platforms is still a significant bottleneck, leading to a delay in data dissemination and subsequent biological understanding. Especially database interfaces with transcriptome analysis modules going beyond mere read counts are missing. Here, we present the Transcriptome Analysis and Comparison Explorer (T-ACE), a tool designed for the organization and analysis of large sequence datasets, and especially suited for transcriptome projects of non-model organisms with little or no a priori sequence information. T-ACE offers a TCL-based interface, which accesses a PostgreSQL database via a php-script. Within T-ACE, information belonging to single sequences or contigs, such as annotation or read coverage, is linked to the respective sequence and immediately accessible. Sequences and assigned information can be searched via keyword- or BLAST-search. Additionally, T-ACE provides within and between transcriptome analysis modules on the level of expression, GO terms, KEGG pathways and protein domains. Results are visualized and can be easily exported for external analysis. We developed T-ACE for laboratory environments, which have only a limited amount of bioinformatics support, and for collaborative projects in which different partners work on the same dataset from different locations or platforms (Windows/Linux/MacOS). For laboratories with some experience in bioinformatics and programming, the low complexity of the database structure and open-source code provides a framework that can be customized according to the different needs of the user and transcriptome project.

What the Aspergillus genomes have told us.

PubMed

Nierman, W C; May, G; Kim, H S; Anderson, M J; Chen, D; Denning, D W

2005-05-01

The sequencing and annotation of the genomes of the first strains of Aspergillus nidulans, Aspergillus oryzae, and Aspergillus fumigatus will be seen in retrospect as a transformational event in Aspergillus biology. With this event the entire genetic composition of A. nidulans, the sexual experimental model organism of the genus Aspergillus, A. oryzae, the food biotechnology organism which is the product of centuries of cultivation, and A. fumigatus, the most common causative agent of invasive aspergillosis is now revealed to the extent that we are at present able to understand. Each genome exhibits a large set of genes common to the three as well as a much smaller set of genes unique to each. Moreover, these sequences serve as resources providing the major tool to expanding our understanding of the biology of each. Transcription profiling of A. fumigatus at high temperatures and comparative genomic hybridization between A. fumigatus and a closely related Aspergillus species provides microarray based examples of the beginning of functional analysis of the genomes of these organisms going forward from the genome sequence.

Extensive characterization of peptides from Panax ginseng C. A. Meyer using mass spectrometric approach.

PubMed

Ye, Xueting; Zhao, Nan; Yu, Xi; Han, Xiaoli; Gao, Huiyuan; Zhang, Xiaozhe

2016-11-01

Panax ginseng is an important herb that has clear effects on the treatment of diverse diseases. Until now, the natural peptide constitution of this herb remains unclear. Here, we conduct an extensive characterization of Ginseng peptidome using MS-based data mining and sequencing. The screen on the charge states of precursor ions indicated that Ginseng is a peptide-rich herb in comparison of a number of commonly used herbs. The Ginseng peptides were then extracted and submitted to nano-LC-MS/MS analysis using different fragmentation modes, including CID, high-energy collisional dissociation, and electron transfer dissociation. Further database search and de novo sequencing allowed the identification of total 308 peptides, some of which might have important biological activities. This study illustrates the abundance and sequences of endogenous Ginseng peptides, thus providing the information of more candidates for the screening of active compounds for future biological research and drug discovery studies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-resolution characterization of sequence signatures due to non-random cleavage of cell-free DNA.

PubMed

Chandrananda, Dineika; Thorne, Natalie P; Bahlo, Melanie

2015-06-17

High-throughput sequencing of cell-free DNA fragments found in human plasma has been used to non-invasively detect fetal aneuploidy, monitor organ transplants and investigate tumor DNA. However, many biological properties of this extracellular genetic material remain unknown. Research that further characterizes circulating DNA could substantially increase its diagnostic value by allowing the application of more sophisticated bioinformatics tools that lead to an improved signal to noise ratio in the sequencing data. In this study, we investigate various features of cell-free DNA in plasma using deep-sequencing data from two pregnant women (>70X, >50X) and compare them with matched cellular DNA. We utilize a descriptive approach to examine how the biological cleavage of cell-free DNA affects different sequence signatures such as fragment lengths, sequence motifs at fragment ends and the distribution of cleavage sites along the genome. We show that the size distributions of these cell-free DNA molecules are dependent on their autosomal and mitochondrial origin as well as the genomic location within chromosomes. DNA mapping to particular microsatellites and alpha repeat elements display unique size signatures. We show how cell-free fragments occur in clusters along the genome, localizing to nucleosomal arrays and are preferentially cleaved at linker regions by correlating the mapping locations of these fragments with ENCODE annotation of chromatin organization. Our work further demonstrates that cell-free autosomal DNA cleavage is sequence dependent. The region spanning up to 10 positions on either side of the DNA cleavage site show a consistent pattern of preference for specific nucleotides. This sequence motif is present in cleavage sites localized to nucleosomal cores and linker regions but is absent in nucleosome-free mitochondrial DNA. These background signals in cell-free DNA sequencing data stem from the non-random biological cleavage of these fragments. This sequence structure can be harnessed to improve bioinformatics algorithms, in particular for CNV and structural variant detection. Descriptive measures for cell-free DNA features developed here could also be used in biomarker analysis to monitor the changes that occur during different pathological conditions.

Reading biological processes from nucleotide sequences

NASA Astrophysics Data System (ADS)

Murugan, Anand

Cellular processes have traditionally been investigated by techniques of imaging and biochemical analysis of the molecules involved. The recent rapid progress in our ability to manipulate and read nucleic acid sequences gives us direct access to the genetic information that directs and constrains biological processes. While sequence data is being used widely to investigate genotype-phenotype relationships and population structure, here we use sequencing to understand biophysical mechanisms. We present work on two different systems. First, in chapter 2, we characterize the stochastic genetic editing mechanism that produces diverse T-cell receptors in the human immune system. We do this by inferring statistical distributions of the underlying biochemical events that generate T-cell receptor coding sequences from the statistics of the observed sequences. This inferred model quantitatively describes the potential repertoire of T-cell receptors that can be produced by an individual, providing insight into its potential diversity and the probability of generation of any specific T-cell receptor. Then in chapter 3, we present work on understanding the functioning of regulatory DNA sequences in both prokaryotes and eukaryotes. Here we use experiments that measure the transcriptional activity of large libraries of mutagenized promoters and enhancers and infer models of the sequence-function relationship from this data. For the bacterial promoter, we infer a physically motivated 'thermodynamic' model of the interaction of DNA-binding proteins and RNA polymerase determining the transcription rate of the downstream gene. For the eukaryotic enhancers, we infer heuristic models of the sequence-function relationship and use these models to find synthetic enhancer sequences that optimize inducibility of expression. Both projects demonstrate the utility of sequence information in conjunction with sophisticated statistical inference techniques for dissecting underlying biophysical mechanisms.

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.

The diploid genome sequence of an Asian individual

PubMed Central

Wang, Jun; Wang, Wei; Li, Ruiqiang; Li, Yingrui; Tian, Geng; Goodman, Laurie; Fan, Wei; Zhang, Junqing; Li, Jun; Zhang, Juanbin; Guo, Yiran; Feng, Binxiao; Li, Heng; Lu, Yao; Fang, Xiaodong; Liang, Huiqing; Du, Zhenglin; Li, Dong; Zhao, Yiqing; Hu, Yujie; Yang, Zhenzhen; Zheng, Hancheng; Hellmann, Ines; Inouye, Michael; Pool, John; Yi, Xin; Zhao, Jing; Duan, Jinjie; Zhou, Yan; Qin, Junjie; Ma, Lijia; Li, Guoqing; Yang, Zhentao; Zhang, Guojie; Yang, Bin; Yu, Chang; Liang, Fang; Li, Wenjie; Li, Shaochuan; Li, Dawei; Ni, Peixiang; Ruan, Jue; Li, Qibin; Zhu, Hongmei; Liu, Dongyuan; Lu, Zhike; Li, Ning; Guo, Guangwu; Zhang, Jianguo; Ye, Jia; Fang, Lin; Hao, Qin; Chen, Quan; Liang, Yu; Su, Yeyang; san, A.; Ping, Cuo; Yang, Shuang; Chen, Fang; Li, Li; Zhou, Ke; Zheng, Hongkun; Ren, Yuanyuan; Yang, Ling; Gao, Yang; Yang, Guohua; Li, Zhuo; Feng, Xiaoli; Kristiansen, Karsten; Wong, Gane Ka-Shu; Nielsen, Rasmus; Durbin, Richard; Bolund, Lars; Zhang, Xiuqing; Li, Songgang; Yang, Huanming; Wang, Jian

2009-01-01

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics. PMID:18987735

A computational genomics pipeline for prokaryotic sequencing projects

PubMed Central

Kislyuk, Andrey O.; Katz, Lee S.; Agrawal, Sonia; Hagen, Matthew S.; Conley, Andrew B.; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C.; Sammons, Scott A.; Govil, Dhwani; Mair, Raydel D.; Tatti, Kathleen M.; Tondella, Maria L.; Harcourt, Brian H.; Mayer, Leonard W.; Jordan, I. King

2010-01-01

Motivation: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. Results: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. Availability and implementation: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems. Contact: king.jordan@biology.gatech.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20519285

Draft genome of the medaka fish: a comprehensive resource for medaka developmental genetics and vertebrate evolutionary biology.

PubMed

Takeda, Hiroyuki

2008-06-01

The medaka Oryzias latipes is a small egg-laying freshwater teleost, and has become an excellent model system for developmental genetics and evolutionary biology. The medaka genome is relatively small in size, approximately 800 Mb, and the genome sequencing project was recently completed by Japanese research groups, providing a high-quality draft genome sequence of the inbred Hd-rR strain of medaka. In this review, I present an overview of the medaka genome project including genome resources, followed by specific findings obtained with the medaka draft genome. In particular, I focus on the analysis that was done by taking advantage of the medaka system, such as the sex chromosome differentiation and the regional history of medaka species using single nucleotide polymorphisms as genomic markers.

A Framework for the Evaluation of Biosecurity, Commercial, Regulatory, and Scientific Impacts of Plant Viruses and Viroids Identified by NGS Technologies

PubMed Central

Massart, Sebastien; Candresse, Thierry; Gil, José; Lacomme, Christophe; Predajna, Lukas; Ravnikar, Maja; Reynard, Jean-Sébastien; Rumbou, Artemis; Saldarelli, Pasquale; Škorić, Dijana; Vainio, Eeva J.; Valkonen, Jari P. T.; Vanderschuren, Hervé; Varveri, Christina; Wetzel, Thierry

2017-01-01

Recent advances in high-throughput sequencing technologies and bioinformatics have generated huge new opportunities for discovering and diagnosing plant viruses and viroids. Plant virology has undoubtedly benefited from these new methodologies, but at the same time, faces now substantial bottlenecks, namely the biological characterization of the newly discovered viruses and the analysis of their impact at the biosecurity, commercial, regulatory, and scientific levels. This paper proposes a scaled and progressive scientific framework for efficient biological characterization and risk assessment when a previously known or a new plant virus is detected by next generation sequencing (NGS) technologies. Four case studies are also presented to illustrate the need for such a framework, and to discuss the scenarios. PMID:28174561

Discovery and Enumeration of Organic-Chemical and Biomimetic Reaction Cycles within the Network of Chemistry.

PubMed

Bajczyk, Michał D; Dittwald, Piotr; Wołos, Agnieszka; Szymkuć, Sara; Grzybowski, Bartosz A

2018-02-23

Analysis of the chemical-organic knowledge represented as a giant network reveals that it contains millions of reaction sequences closing into cycles. Without realizing it, independent chemists working at different times have jointly created examples of cyclic sequences that allow for the recovery of useful reagents and for the autoamplification of synthetically important molecules, those that mimic biological cycles, and those that can be operated one-pot. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bacillus pumilus SAFR-032 isolate

NASA Technical Reports Server (NTRS)

Venkateswaran, Kasthuri J. (Inventor)

2007-01-01

The present invention relates to discovery and isolation of a biologically pure culture of a Bacillus pumilus SAFR-032 isolate with UV sterilization resistant properties. This novel strain has been characterized on the basis of phenotypic traits, 16S rDNA sequence analysis and DNA-DNA hybridization. According to the results of these analyses, this strain belongs to the genus Bacillus. The GenBank accession number for the 16S rDNA sequence of the Bacillus pumilus SAFR-032 isolate is AY167879.

IBS: an illustrator for the presentation and visualization of biological sequences.

PubMed

Liu, Wenzhong; Xie, Yubin; Ma, Jiyong; Luo, Xiaotong; Nie, Peng; Zuo, Zhixiang; Lahrmann, Urs; Zhao, Qi; Zheng, Yueyuan; Zhao, Yong; Xue, Yu; Ren, Jian

2015-10-15

Biological sequence diagrams are fundamental for visualizing various functional elements in protein or nucleotide sequences that enable a summarization and presentation of existing information as well as means of intuitive new discoveries. Here, we present a software package called illustrator of biological sequences (IBS) that can be used for representing the organization of either protein or nucleotide sequences in a convenient, efficient and precise manner. Multiple options are provided in IBS, and biological sequences can be manipulated, recolored or rescaled in a user-defined mode. Also, the final representational artwork can be directly exported into a publication-quality figure. The standalone package of IBS was implemented in JAVA, while the online service was implemented in HTML5 and JavaScript. Both the standalone package and online service are freely available at http://ibs.biocuckoo.org. renjian.sysu@gmail.com or xueyu@hust.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

IBS: an illustrator for the presentation and visualization of biological sequences

PubMed Central

Liu, Wenzhong; Xie, Yubin; Ma, Jiyong; Luo, Xiaotong; Nie, Peng; Zuo, Zhixiang; Lahrmann, Urs; Zhao, Qi; Zheng, Yueyuan; Zhao, Yong; Xue, Yu; Ren, Jian

2015-01-01

Summary: Biological sequence diagrams are fundamental for visualizing various functional elements in protein or nucleotide sequences that enable a summarization and presentation of existing information as well as means of intuitive new discoveries. Here, we present a software package called illustrator of biological sequences (IBS) that can be used for representing the organization of either protein or nucleotide sequences in a convenient, efficient and precise manner. Multiple options are provided in IBS, and biological sequences can be manipulated, recolored or rescaled in a user-defined mode. Also, the final representational artwork can be directly exported into a publication-quality figure. Availability and implementation: The standalone package of IBS was implemented in JAVA, while the online service was implemented in HTML5 and JavaScript. Both the standalone package and online service are freely available at http://ibs.biocuckoo.org. Contact: renjian.sysu@gmail.com or xueyu@hust.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26069263

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

PubMed

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Sequence analysis by iterated maps, a review.

PubMed

Almeida, Jonas S

2014-05-01

Among alignment-free methods, Iterated Maps (IMs) are on a particular extreme: they are also scale free (order free). The use of IMs for sequence analysis is also distinct from other alignment-free methodologies in being rooted in statistical mechanics instead of computational linguistics. Both of these roots go back over two decades to the use of fractal geometry in the characterization of phase-space representations. The time series analysis origin of the field is betrayed by the title of the manuscript that started this alignment-free subdomain in 1990, 'Chaos Game Representation'. The clash between the analysis of sequences as continuous series and the better established use of Markovian approaches to discrete series was almost immediate, with a defining critique published in same journal 2 years later. The rest of that decade would go by before the scale-free nature of the IM space was uncovered. The ensuing decade saw this scalability generalized for non-genomic alphabets as well as an interest in its use for graphic representation of biological sequences. Finally, in the past couple of years, in step with the emergence of BigData and MapReduce as a new computational paradigm, there is a surprising third act in the IM story. Multiple reports have described gains in computational efficiency of multiple orders of magnitude over more conventional sequence analysis methodologies. The stage appears to be now set for a recasting of IMs with a central role in processing nextgen sequencing results.

A Personal Journey of Discovery: Developing Technology and Changing Biology

NASA Astrophysics Data System (ADS)

Hood, Lee

2008-07-01

This autobiographical article describes my experiences in developing chemically based, biological technologies for deciphering biological information: DNA, RNA, proteins, interactions, and networks. The instruments developed include protein and DNA sequencers and synthesizers, as well as ink-jet technology for synthesizing DNA chips. Diverse new strategies for doing biology also arose from novel applications of these instruments. The functioning of these instruments can be integrated to generate powerful new approaches to cloning and characterizing genes from a small amount of protein sequence or to using gene sequences to synthesize peptide fragments so as to characterize various properties of the proteins. I also discuss the five paradigm changes in which I have participated: the development and integration of biological instrumentation; the human genome project; cross-disciplinary biology; systems biology; and predictive, personalized, preventive, and participatory (P4) medicine. Finally, I discuss the origins, the philosophy, some accomplishments, and the future trajectories of the Institute for Systems Biology.

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

Genetic and biological variation among nucleopolyhedrovirus isolates from spodoptera frugiperda (lepidotpera: noctuidae)

USDA-ARS?s Scientific Manuscript database

A PCR-based method was used to identify and distinguish among 40 uncharacterized nucleopolyhedrovirus (NPV) isolates from the moth Spodoptera frugiperda that were part of an insect virus collection. Phylogenetic analysis was carried out with sequences amplified from two strongly conserved loci (pol...

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.

PubMed

Bonham-Carter, Oliver; Steele, Joe; Bastola, Dhundy

2014-11-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base-base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel-Ziv techniques from data compression. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Use of Internet Resources in the Biology Lecture Classroom.

ERIC Educational Resources Information Center

Francis, Joseph W.

2000-01-01

Introduces internet resources that are available for instructional use in biology classrooms. Provides information on video-based technologies to create and capture video sequences, interactive web sites that allow interaction with biology simulations, online texts, and interactive videos that display animated video sequences. (YDS)

Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

PubMed

Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

2017-02-21

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

SALAD database: a motif-based database of protein annotations for plant comparative genomics

PubMed Central

Mihara, Motohiro; Itoh, Takeshi; Izawa, Takeshi

2010-01-01

Proteins often have several motifs with distinct evolutionary histories. Proteins with similar motifs have similar biochemical properties and thus related biological functions. We constructed a unique comparative genomics database termed the SALAD database (http://salad.dna.affrc.go.jp/salad/) from plant-genome-based proteome data sets. We extracted evolutionarily conserved motifs by MEME software from 209 529 protein-sequence annotation groups selected by BLASTP from the proteome data sets of 10 species: rice, sorghum, Arabidopsis thaliana, grape, a lycophyte, a moss, 3 algae, and yeast. Similarity clustering of each protein group was performed by pairwise scoring of the motif patterns of the sequences. The SALAD database provides a user-friendly graphical viewer that displays a motif pattern diagram linked to the resulting bootstrapped dendrogram for each protein group. Amino-acid-sequence-based and nucleotide-sequence-based phylogenetic trees for motif combination alignment, a logo comparison diagram for each clade in the tree, and a Pfam-domain pattern diagram are also available. We also developed a viewer named ‘SALAD on ARRAYs’ to view arbitrary microarray data sets of paralogous genes linked to the same dendrogram in a window. The SALAD database is a powerful tool for comparing protein sequences and can provide valuable hints for biological analysis. PMID:19854933

RNA regulators responding to ribosomal protein S15 are frequent in sequence space

PubMed Central

Slinger, Betty L.; Meyer, Michelle M.

2016-01-01

There are several natural examples of distinct RNA structures that interact with the same ligand to regulate the expression of homologous genes in different organisms. One essential question regarding this phenomenon is whether such RNA regulators are the result of convergent or divergent evolution. Are the RNAs derived from some common ancestor and diverged to the point where we cannot identify the similarity, or have multiple solutions to the same biological problem arisen independently? A key variable in assessing these alternatives is how frequently such regulators arise within sequence space. Ribosomal protein S15 is autogenously regulated via an RNA regulator in many bacterial species; four apparently distinct regulators have been functionally validated in different bacterial phyla. Here, we explore how frequently such regulators arise within a partially randomized sequence population. We find many RNAs that interact specifically with ribosomal protein S15 from Geobacillus kaustophilus with biologically relevant dissociation constants. Furthermore, of the six sequences we characterize, four show regulatory activity in an Escherichia coli reporter assay. Subsequent footprinting and mutagenesis analysis indicates that protein binding proximal to regulatory features such as the Shine–Dalgarno sequence is sufficient to enable regulation, suggesting that regulation in response to S15 is relatively easily acquired. PMID:27580716

A Molecular Genetics Laboratory Course Applying Bioinformatics and Cell Biology in the Context of Original Research

PubMed Central

Pruitt, Wendy M.; Robinson, Lucy C.

2008-01-01

Research based laboratory courses have been shown to stimulate student interest in science and to improve scientific skills. We describe here a project developed for a semester-long research-based laboratory course that accompanies a genetics lecture course. The project was designed to allow students to become familiar with the use of bioinformatics tools and molecular biology and genetic approaches while carrying out original research. Students were required to present their hypotheses, experiments, and results in a comprehensive lab report. The lab project concerned the yeast casein kinase 1 (CK1) protein kinase Yck2. CK1 protein kinases are present in all organisms and are well conserved in primary structure. These enzymes display sequence features that differ from other protein kinase subfamilies. Students identified such sequences within the CK1 subfamily, chose a sequence to analyze, used available structural data to determine possible functions for their sequences, and designed mutations within the sequences. After generating the mutant alleles, these were expressed in yeast and tested for function by using two growth assays. The student response to the project was positive, both in terms of knowledge and skills increases and interest in research, and several students are continuing the analysis of mutant alleles as summer projects. PMID:19047427

SALAD database: a motif-based database of protein annotations for plant comparative genomics.

PubMed

Mihara, Motohiro; Itoh, Takeshi; Izawa, Takeshi

2010-01-01

Proteins often have several motifs with distinct evolutionary histories. Proteins with similar motifs have similar biochemical properties and thus related biological functions. We constructed a unique comparative genomics database termed the SALAD database (http://salad.dna.affrc.go.jp/salad/) from plant-genome-based proteome data sets. We extracted evolutionarily conserved motifs by MEME software from 209,529 protein-sequence annotation groups selected by BLASTP from the proteome data sets of 10 species: rice, sorghum, Arabidopsis thaliana, grape, a lycophyte, a moss, 3 algae, and yeast. Similarity clustering of each protein group was performed by pairwise scoring of the motif patterns of the sequences. The SALAD database provides a user-friendly graphical viewer that displays a motif pattern diagram linked to the resulting bootstrapped dendrogram for each protein group. Amino-acid-sequence-based and nucleotide-sequence-based phylogenetic trees for motif combination alignment, a logo comparison diagram for each clade in the tree, and a Pfam-domain pattern diagram are also available. We also developed a viewer named 'SALAD on ARRAYs' to view arbitrary microarray data sets of paralogous genes linked to the same dendrogram in a window. The SALAD database is a powerful tool for comparing protein sequences and can provide valuable hints for biological analysis.

Survey of local and global biological network alignment: the need to reconcile the two sides of the same coin.

PubMed

Guzzi, Pietro Hiram; Milenkovic, Tijana

2018-05-01

Analogous to genomic sequence alignment that allows for across-species transfer of biological knowledge between conserved sequence regions, biological network alignment can be used to guide the knowledge transfer between conserved regions of molecular networks of different species. Hence, biological network alignment can be used to redefine the traditional notion of a sequence-based homology to a new notion of network-based homology. Analogous to genomic sequence alignment, there exist local and global biological network alignments. Here, we survey prominent and recent computational approaches of each network alignment type and discuss their (dis)advantages. Then, as it was recently shown that the two approach types are complementary, in the sense that they capture different slices of cellular functioning, we discuss the need to reconcile the two network alignment types and present a recent first step in this direction. We conclude with some open research problems on this topic and comment on the usefulness of network alignment in other domains besides computational biology.

Ensembl 2004.

PubMed

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

Single-cell sequencing in stem cell biology.

PubMed

Wen, Lu; Tang, Fuchou

2016-04-15

Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequencing technologies serve as powerful tools to dissect cellular heterogeneity comprehensively and to identify distinct phenotypic cell types, even within a 'homogeneous' stem cell population. These technologies, including single-cell genome, epigenome, and transcriptome sequencing technologies, have been developing rapidly in recent years. The application of these methods to different types of stem cells, including pluripotent stem cells and tissue-specific stem cells, has led to exciting new findings in the stem cell field. In this review, we discuss the recent progress as well as future perspectives in the methodologies and applications of single-cell omic sequencing technologies.

Analysis of the ergosterol biosynthesis pathway cloning, molecular characterization and phylogeny of lanosterol 14 α-demethylase (ERG11) gene of Moniliophthora perniciosa.

PubMed

de Oliveira Ceita, Geruza; Vilas-Boas, Laurival Antônio; Castilho, Marcelo Santos; Carazzolle, Marcelo Falsarella; Pirovani, Carlos Priminho; Selbach-Schnadelbach, Alessandra; Gramacho, Karina Peres; Ramos, Pablo Ivan Pereira; Barbosa, Luciana Veiga; Pereira, Gonçalo Amarante Guimarães; Góes-Neto, Aristóteles

2014-10-01

The phytopathogenic fungus Moniliophthora perniciosa (Stahel) Aime & Philips-Mora, causal agent of witches' broom disease of cocoa, causes countless damage to cocoa production in Brazil. Molecular studies have attempted to identify genes that play important roles in fungal survival and virulence. In this study, sequences deposited in the M. perniciosa Genome Sequencing Project database were analyzed to identify potential biological targets. For the first time, the ergosterol biosynthetic pathway in M. perniciosa was studied and the lanosterol 14α-demethylase gene (ERG11) that encodes the main enzyme of this pathway and is a target for fungicides was cloned, characterized molecularly and its phylogeny analyzed. ERG11 genomic DNA and cDNA were characterized and sequence analysis of the ERG11 protein identified highly conserved domains typical of this enzyme, such as SRS1, SRS4, EXXR and the heme-binding region (HBR). Comparison of the protein sequences and phylogenetic analysis revealed that the M. perniciosa enzyme was most closely related to that of Coprinopsis cinerea.

Analysis of the ergosterol biosynthesis pathway cloning, molecular characterization and phylogeny of lanosterol 14 α-demethylase (ERG11) gene of Moniliophthora perniciosa

PubMed Central

de Oliveira Ceita, Geruza; Vilas-Boas, Laurival Antônio; Castilho, Marcelo Santos; Carazzolle, Marcelo Falsarella; Pirovani, Carlos Priminho; Selbach-Schnadelbach, Alessandra; Gramacho, Karina Peres; Ramos, Pablo Ivan Pereira; Barbosa, Luciana Veiga; Pereira, Gonçalo Amarante Guimarães; Góes-Neto, Aristóteles

2014-01-01

The phytopathogenic fungus Moniliophthora perniciosa (Stahel) Aime & Philips-Mora, causal agent of witches’ broom disease of cocoa, causes countless damage to cocoa production in Brazil. Molecular studies have attempted to identify genes that play important roles in fungal survival and virulence. In this study, sequences deposited in the M. perniciosa Genome Sequencing Project database were analyzed to identify potential biological targets. For the first time, the ergosterol biosynthetic pathway in M. perniciosa was studied and the lanosterol 14α-demethylase gene (ERG11) that encodes the main enzyme of this pathway and is a target for fungicides was cloned, characterized molecularly and its phylogeny analyzed. ERG11 genomic DNA and cDNA were characterized and sequence analysis of the ERG11 protein identified highly conserved domains typical of this enzyme, such as SRS1, SRS4, EXXR and the heme-binding region (HBR). Comparison of the protein sequences and phylogenetic analysis revealed that the M. perniciosa enzyme was most closely related to that of Coprinopsis cinerea. PMID:25505843

Analysis of Biological Features Associated with Meiotic Recombination Hot and Cold Spots in Saccharomyces cerevisiae

PubMed Central

Hansen, Loren; Kim, Nak-Kyeong; Mariño-Ramírez, Leonardo; Landsman, David

2011-01-01

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented. PMID:22242140

Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the Alphacoronavirus 1 Species

PubMed Central

André, Nicole M.

2018-01-01

ABSTRACT The difficulties related to virus taxonomy have been amplified by recent advances in next-generation sequencing and metagenomics, prompting the field to revisit the question of what constitutes a useful viral classification. Here, taking a challenging classification found in coronaviruses, we argue that consideration of biological properties in addition to sequence-based demarcations is critical for generating useful taxonomy that recapitulates complex evolutionary histories. Within the Alphacoronavirus genus, the Alphacoronavirus 1 species encompasses several biologically distinct viruses. We carried out functionally based phylogenetic analysis, centered on the spike gene, which encodes the main surface antigen and primary driver of tropism and pathogenesis. Within the Alphacoronavirus 1 species, we identify clade A (encompassing serotype I feline coronavirus [FCoV] and canine coronavirus [CCoV]) and clade B (grouping serotype II FCoV and CCoV and transmissible gastroenteritis virus [TGEV]-like viruses). We propose this clade designation, along with the newly proposed Alphacoronavirus 2 species, as an improved way to classify the Alphacoronavirus genus. IMPORTANCE Our work focuses on improving the classification of the Alphacoronavirus genus. The Alphacoronavirus 1 species groups viruses of veterinary importance that infect distinct mammalian hosts and includes canine and feline coronaviruses and transmissible gastroenteritis virus. It is the prototype species of the Alphacoronavirus genus; however, it encompasses biologically distinct viruses. To better characterize this prototypical species, we performed phylogenetic analyses based on the sequences of the spike protein, one of the main determinants of tropism and pathogenesis, and reveal the existence of two subgroups or clades that fit with previously established serotype demarcations. We propose a new clade designation to better classify Alphacoronavirus 1 members. PMID:29299531

Improving Virus Taxonomy by Recontextualizing Sequence-Based Classification with Biologically Relevant Data: the Case of the Alphacoronavirus 1 Species.

PubMed

Whittaker, Gary R; André, Nicole M; Millet, Jean Kaoru

2018-01-01

The difficulties related to virus taxonomy have been amplified by recent advances in next-generation sequencing and metagenomics, prompting the field to revisit the question of what constitutes a useful viral classification. Here, taking a challenging classification found in coronaviruses, we argue that consideration of biological properties in addition to sequence-based demarcations is critical for generating useful taxonomy that recapitulates complex evolutionary histories. Within the Alphacoronavirus genus, the Alphacoronavirus 1 species encompasses several biologically distinct viruses. We carried out functionally based phylogenetic analysis, centered on the spike gene, which encodes the main surface antigen and primary driver of tropism and pathogenesis. Within the Alphacoronavirus 1 species, we identify clade A (encompassing serotype I feline coronavirus [FCoV] and canine coronavirus [CCoV]) and clade B (grouping serotype II FCoV and CCoV and transmissible gastroenteritis virus [TGEV]-like viruses). We propose this clade designation, along with the newly proposed Alphacoronavirus 2 species, as an improved way to classify the Alphacoronavirus genus. IMPORTANCE Our work focuses on improving the classification of the Alphacoronavirus genus. The Alphacoronavirus 1 species groups viruses of veterinary importance that infect distinct mammalian hosts and includes canine and feline coronaviruses and transmissible gastroenteritis virus. It is the prototype species of the Alphacoronavirus genus; however, it encompasses biologically distinct viruses. To better characterize this prototypical species, we performed phylogenetic analyses based on the sequences of the spike protein, one of the main determinants of tropism and pathogenesis, and reveal the existence of two subgroups or clades that fit with previously established serotype demarcations. We propose a new clade designation to better classify Alphacoronavirus 1 members.

Wasabi: An Integrated Platform for Evolutionary Sequence Analysis and Data Visualization.

PubMed

Veidenberg, Andres; Medlar, Alan; Löytynoja, Ari

2016-04-01

Wasabi is an open source, web-based environment for evolutionary sequence analysis. Wasabi visualizes sequence data together with a phylogenetic tree within a modern, user-friendly interface: The interface hides extraneous options, supports context sensitive menus, drag-and-drop editing, and displays additional information, such as ancestral sequences, associated with specific tree nodes. The Wasabi environment supports reproducibility by automatically storing intermediate analysis steps and includes built-in functions to share data between users and publish analysis results. For computational analysis, Wasabi supports PRANK and PAGAN for phylogeny-aware alignment and alignment extension, and it can be easily extended with other tools. Along with drag-and-drop import of local files, Wasabi can access remote data through URL and import sequence data, GeneTrees and EPO alignments directly from Ensembl. To demonstrate a typical workflow using Wasabi, we reproduce key findings from recent comparative genomics studies, including a reanalysis of the EGLN1 gene from the tiger genome study: These case studies can be browsed within Wasabi at http://wasabiapp.org:8000?id=usecases. Wasabi runs inside a web browser and does not require any installation. One can start using it at http://wasabiapp.org. All source code is licensed under the AGPLv3. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Efficient Mining of Interesting Patterns in Large Biological Sequences

PubMed Central

Rashid, Md. Mamunur; Karim, Md. Rezaul; Jeong, Byeong-Soo

2012-01-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time. PMID:23105928

Efficient mining of interesting patterns in large biological sequences.

PubMed

Rashid, Md Mamunur; Karim, Md Rezaul; Jeong, Byeong-Soo; Choi, Ho-Jin

2012-03-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

Phylogenetic shadowing of primate sequences to find functional regions of the human genome.

PubMed

Boffelli, Dario; McAuliffe, Jon; Ovcharenko, Dmitriy; Lewis, Keith D; Ovcharenko, Ivan; Pachter, Lior; Rubin, Edward M

2003-02-28

Nonhuman primates represent the most relevant model organisms to understand the biology of Homo sapiens. The recent divergence and associated overall sequence conservation between individual members of this taxon have nonetheless largely precluded the use of primates in comparative sequence studies. We used sequence comparisons of an extensive set of Old World and New World monkeys and hominoids to identify functional regions in the human genome. Analysis of these data enabled the discovery of primate-specific gene regulatory elements and the demarcation of the exons of multiple genes. Much of the information content of the comprehensive primate sequence comparisons could be captured with a small subset of phylogenetically close primates. These results demonstrate the utility of intraprimate sequence comparisons to discover common mammalian as well as primate-specific functional elements in the human genome, which are unattainable through the evaluation of more evolutionarily distant species.

The Impact of Normalization Methods on RNA-Seq Data Analysis

PubMed Central

Zyprych-Walczak, J.; Szabelska, A.; Handschuh, L.; Górczak, K.; Klamecka, K.; Figlerowicz, M.; Siatkowski, I.

2015-01-01

High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational methods that can tackle the analysis and management of data. The data normalization is one of the most crucial steps of data processing and this process must be carefully considered as it has a profound effect on the results of the analysis. In this work, we focus on a comprehensive comparison of five normalization methods related to sequencing depth, widely used for transcriptome sequencing (RNA-seq) data, and their impact on the results of gene expression analysis. Based on this study, we suggest a universal workflow that can be applied for the selection of the optimal normalization procedure for any particular data set. The described workflow includes calculation of the bias and variance values for the control genes, sensitivity and specificity of the methods, and classification errors as well as generation of the diagnostic plots. Combining the above information facilitates the selection of the most appropriate normalization method for the studied data sets and determines which methods can be used interchangeably. PMID:26176014

Designing a Bioengine for Detection and Analysis of Base String on an Affected Sequence in High-Concentration Regions

PubMed Central

Mandal, Bijoy Kumar; Kim, Tai-hoon

2013-01-01

We design an Algorithm for bioengine. As a program are enable optimal alignments searching between two sequences, the host sequence (normal plant) as well as query sequence (virus). Searching for homologues has become a routine operation of biological sequences in 4 × 4 combination with different subsequence (word size). This program takes the advantage of the high degree of homology between such sequences to construct an alignment of the matching regions. There is a main aim which is to detect the overlapping reading frames. This program also enables to find out the highly infected colones selection highest matching region with minimum gap or mismatch zones and unique virus colones matches. This is a small, portable, interactive, front-end program intended to be used to find out the regions of matching between host sequence and query subsequences. All the operations are carried out in fraction of seconds, depending on the required task and on the sequence length. PMID:24000321

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

in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies

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

Zhou, Xiaofan; Peris, David; Kominek, Jacek

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimentalmore » design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.« less

in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies

DOE PAGES

Zhou, Xiaofan; Peris, David; Kominek, Jacek; ...

2016-09-16

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimentalmore » design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.« less

Identification of species by multiplex analysis of variable-length sequences

PubMed Central

Pereira, Filipe; Carneiro, João; Matthiesen, Rune; van Asch, Barbara; Pinto, Nádia; Gusmão, Leonor; Amorim, António

2010-01-01

The quest for a universal and efficient method of identifying species has been a longstanding challenge in biology. Here, we show that accurate identification of species in all domains of life can be accomplished by multiplex analysis of variable-length sequences containing multiple insertion/deletion variants. The new method, called SPInDel, is able to discriminate 93.3% of eukaryotic species from 18 taxonomic groups. We also demonstrate that the identification of prokaryotic and viral species with numeric profiles of fragment lengths is generally straightforward. A computational platform is presented to facilitate the planning of projects and includes a large data set with nearly 1800 numeric profiles for species in all domains of life (1556 for eukaryotes, 105 for prokaryotes and 130 for viruses). Finally, a SPInDel profiling kit for discrimination of 10 mammalian species was successfully validated on highly processed food products with species mixtures and proved to be easily adaptable to multiple screening procedures routinely used in molecular biology laboratories. These results suggest that SPInDel is a reliable and cost-effective method for broad-spectrum species identification that is appropriate for use in suboptimal samples and is amenable to different high-throughput genotyping platforms without the need for DNA sequencing. PMID:20923781

Optimization and quality control of genome-wide Hi-C library preparation.

PubMed

Zhang, Xiang-Yuan; He, Chao; Ye, Bing-Yu; Xie, De-Jian; Shi, Ming-Lei; Zhang, Yan; Shen, Wen-Long; Li, Ping; Zhao, Zhi-Hu

2017-09-20

Highest-throughput chromosome conformation capture (Hi-C) is one of the key assays for genome- wide chromatin interaction studies. It is a time-consuming process that involves many steps and many different kinds of reagents, consumables, and equipments. At present, the reproducibility is unsatisfactory. By optimizing the key steps of the Hi-C experiment, such as crosslinking, pretreatment of digestion, inactivation of restriction enzyme, and in situ ligation etc., we established a robust Hi-C procedure and prepared two biological replicates of Hi-C libraries from the GM12878 cells. After preliminary quality control by Sanger sequencing, the two replicates were high-throughput sequenced. The bioinformatics analysis of the raw sequencing data revealed the mapping-ability and pair-mate rate of the raw data were around 90% and 72%, respectively. Additionally, after removal of self-circular ligations and dangling-end products, more than 96% of the valid pairs were reached. Genome-wide interactome profiling shows clear topological associated domains (TADs), which is consistent with previous reports. Further correlation analysis showed that the two biological replicates strongly correlate with each other in terms of both bin coverage and all bin pairs. All these results indicated that the optimized Hi-C procedure is robust and stable, which will be very helpful for the wide applications of the Hi-C assay.

DRME: Count-based differential RNA methylation analysis at small sample size scenario.

PubMed

Liu, Lian; Zhang, Shao-Wu; Gao, Fan; Zhang, Yixin; Huang, Yufei; Chen, Runsheng; Meng, Jia

2016-04-15

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation. We developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. We tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies and compared it with Fisher's exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing and PAR-CLIP. The code together with an MeRIP-Seq dataset is available online (https://github.com/lzcyzm/DRME) for evaluation and reproduction of the figures shown in this article. Copyright © 2016 Elsevier Inc. All rights reserved.

MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences of Cell Populations in Fluorescence Microscopy.

PubMed

Svoboda, David; Ulman, Vladimir

2017-01-01

The proper analysis of biological microscopy images is an important and complex task. Therefore, it requires verification of all steps involved in the process, including image segmentation and tracking algorithms. It is generally better to verify algorithms with computer-generated ground truth datasets, which, compared to manually annotated data, nowadays have reached high quality and can be produced in large quantities even for 3D time-lapse image sequences. Here, we propose a novel framework, called MitoGen, which is capable of generating ground truth datasets with fully 3D time-lapse sequences of synthetic fluorescence-stained cell populations. MitoGen shows biologically justified cell motility, shape and texture changes as well as cell divisions. Standard fluorescence microscopy phenomena such as photobleaching, blur with real point spread function (PSF), and several types of noise, are simulated to obtain realistic images. The MitoGen framework is scalable in both space and time. MitoGen generates visually plausible data that shows good agreement with real data in terms of image descriptors and mean square displacement (MSD) trajectory analysis. Additionally, it is also shown in this paper that four publicly available segmentation and tracking algorithms exhibit similar performance on both real and MitoGen-generated data. The implementation of MitoGen is freely available.

Human Chromosome Y and Haplogroups; introducing YDHS Database.

PubMed

Tiirikka, Timo; Moilanen, Jukka S

2015-12-01

As the high throughput sequencing efforts generate more biological information, scientists from different disciplines are interpreting the polymorphisms that make us unique. In addition, there is an increasing trend in general public to research their own genealogy, find distant relatives and to know more about their biological background. Commercial vendors are providing analyses of mitochondrial and Y-chromosomal markers for such purposes. Clearly, an easy-to-use free interface to the existing data on the identified variants would be in the interest of general public and professionals less familiar with the field. Here we introduce a novel metadatabase YDHS that aims to provide such an interface for Y-chromosomal DNA (Y-DNA) haplogroups and sequence variants. The database uses ISOGG Y-DNA tree as the source of mutations and haplogroups and by using genomic positions of the mutations the database links them to genes and other biological entities. YDHS contains analysis tools for deeper Y-SNP analysis. YDHS addresses the shortage of Y-DNA related databases. We have tested our database using a set of different cases from literature ranging from infertility to autism. The database is at http://www.semanticgen.net/ydhs Y-chromosomal DNA (Y-DNA) haplogroups and sequence variants have not been in the scientific limelight, excluding certain specialized fields like forensics, mainly because there is not much freely available information or it is scattered in different sources. However, as we have demonstrated Y-SNPs do play a role in various cases on the haplogroup level and it is possible to create a free Y-DNA dedicated bioinformatics resource.

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

Diazotrophic Community Structure and Function in Two Successional Stages of Biological Soil Crusts from the Colorado Plateau and Chihuahuan Desert

USGS Publications Warehouse

Yeager, C.M.; Kornosky, J.L.; Housman, D.C.; Grote, E.E.; Belnap, J.; Kuske, C.R.

2004-01-01

The objective of this study was to characterize the community structure and activity of N2-fixing microorganisms in mature and poorly developed biological soil crusts from both the Colorado Plateau and Chihuahuan Desert. Nitrogenase activity was approximately 10 and 2.5 times higher in mature crusts than in poorly developed crusts at the Colorado Plateau site and Chihuahuan Desert site, respectively. Analysis of nifH sequences by clone sequencing and the terminal restriction fragment length polymorphism technique indicated that the crust diazotrophic community was 80 to 90% heterocystous cyanobacteria most closely related to Nostoc spp. and that the composition of N2-fixing species did not vary significantly between the poorly developed and mature crusts at either site. In contrast, the abundance of nifH sequences was approximately 7.5 times greater (per microgram of total DNA) in mature crusts than in poorly developed crusts at a given site as measured by quantitative PCR. 16S rRNA gene clone sequencing and microscopic analysis of the cyanobacterial community within both crust types demonstrated a transition from a Microcoleus vaginatus-dominated, poorly developed crust to mature crusts harboring a greater percentage of Nostoc and Scytonema spp. We hypothesize that ecological factors, such as soil instability and water stress, may constrain the growth of N2-fixing microorganisms at our study sites and that the transition to a mature, nitrogen-producing crust initially requires bioengineering of the surface microenvironment by Microcoleus vaginatus.

Generation and Analysis of the Expressed Sequence Tags from the Mycelium of Ganoderma lucidum

PubMed Central

Huang, Yen-Hua; Wu, Hung-Yi; Wu, Keh-Ming; Liu, Tze-Tze; Liou, Ruey-Fen; Tsai, Shih-Feng; Shiao, Ming-Shi; Ho, Low-Tone; Tzean, Shean-Shong; Yang, Ueng-Cheng

2013-01-01

Ganoderma lucidum (G. lucidum) is a medicinal mushroom renowned in East Asia for its potential biological effects. To enable a systematic exploration of the genes associated with the various phenotypes of the fungus, the genome consortium of G. lucidum has carried out an expressed sequence tag (EST) sequencing project. Using a Sanger sequencing based approach, 47,285 ESTs were obtained from in vitro cultures of G. lucidum mycelium of various durations. These ESTs were further clustered and merged into 7,774 non-redundant expressed loci. The features of these expressed contigs were explored in terms of over-representation, alternative splicing, and natural antisense transcripts. Our results provide an invaluable information resource for exploring the G. lucidum transcriptome and its regulation. Many cases of the genes over-represented in fast-growing dikaryotic mycelium are closely related to growth, such as cell wall and bioactive compound synthesis. In addition, the EST-genome alignments containing putative cassette exons and retained introns were manually curated and then used to make inferences about the predominating splice-site recognition mechanism of G. lucidum. Moreover, a number of putative antisense transcripts have been pinpointed, from which we noticed that two cases are likely to reveal hitherto undiscovered biological pathways. To allow users to access the data and the initial analysis of the results of this project, a dedicated web site has been created at http://csb2.ym.edu.tw/est/. PMID:23658685

Discovery and Annotation of Plant Endogenous Target Mimicry Sequences from Public Transcriptome Libraries: A Case Study of Prunus persica.

PubMed

Karakülah, Gökhan

2017-06-28

Novel transcript discovery through RNA sequencing has substantially improved our understanding of the transcriptome dynamics of biological systems. Endogenous target mimicry (eTM) transcripts, a novel class of regulatory molecules, bind to their target microRNAs (miRNAs) by base pairing and block their biological activity. The objective of this study was to provide a computational analysis framework for the prediction of putative eTM sequences in plants, and as an example, to discover previously un-annotated eTMs in Prunus persica (peach) transcriptome. Therefore, two public peach transcriptome libraries downloaded from Sequence Read Archive (SRA) and a previously published set of long non-coding RNAs (lncRNAs) were investigated with multi-step analysis pipeline, and 44 putative eTMs were found. Additionally, an eTM-miRNA-mRNA regulatory network module associated with peach fruit organ development was built via integration of the miRNA target information and predicted eTM-miRNA interactions. My findings suggest that one of the most widely expressed miRNA families among diverse plant species, miR156, might be potentially sponged by seven putative eTMs. Besides, the study indicates eTMs potentially play roles in the regulation of development processes in peach fruit via targeting specific miRNAs. In conclusion, by following the step-by step instructions provided in this study, novel eTMs can be identified and annotated effectively in public plant transcriptome libraries.

Blackboard Electrophoresis: An Inexpensive Exercise on the Principles of DNA Restriction Analysis

ERIC Educational Resources Information Center

Costa, M. J.

2007-01-01

Undergraduates with little training on molecular biology may find the technical level of the typical introductory restriction laboratory too challenging and have problems with mastering the underlying concepts and processes. "Blackboard electrophoresis" is an active learning exercise, which focuses student attention on the sequences and principles…

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

PubMed Central

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

2015-01-01

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

SAMSA2: a standalone metatranscriptome analysis pipeline.

PubMed

Westreich, Samuel T; Treiber, Michelle L; Mills, David A; Korf, Ian; Lemay, Danielle G

2018-05-21

Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the experiments generate a large volume of sequence data and each sequence must be compared with reference sequences from thousands of organisms. SAMSA2 is an upgrade to the original Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) pipeline that has been redesigned for standalone use on a supercomputing cluster. SAMSA2 is faster due to the use of the DIAMOND aligner, and more flexible and reproducible because it uses local databases. SAMSA2 is available with detailed documentation, and example input and output files along with examples of master scripts for full pipeline execution. SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its reference databases may be upgraded, altered or customized to fit the needs of any experiment.

De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data.

PubMed

Islam, Mohammad Tawhidul; Mohamedali, Abidali; Fernandes, Criselda Santan; Baker, Mark S; Ranganathan, Shoba

2017-01-01

High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. Although the analysis of spectra by de novo sequences removes such biases and has been available for a long period of time, its uptake has been slow or almost nonexistent within the scientific community. In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.

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

PubMed

Jones, Roger A C; Kehoe, Monica A

2016-07-01

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

DNA confinement in nanochannels: physics and biological applications

NASA Astrophysics Data System (ADS)

Reisner, Walter; Pedersen, Jonas N.; Austin, Robert H.

2012-10-01

DNA is the central storage molecule of genetic information in the cell, and reading that information is a central problem in biology. While sequencing technology has made enormous advances over the past decade, there is growing interest in platforms that can readout genetic information directly from long single DNA molecules, with the ultimate goal of single-cell, single-genome analysis. Such a capability would obviate the need for ensemble averaging over heterogeneous cellular populations and eliminate uncertainties introduced by cloning and molecular amplification steps (thus enabling direct assessment of the genome in its native state). In this review, we will discuss how the information contained in genomic-length single DNA molecules can be accessed via physical confinement in nanochannels. Due to self-avoidance interactions, DNA molecules will stretch out when confined in nanochannels, creating a linear unscrolling of the genome along the channel for analysis. We will first review the fundamental physics of DNA nanochannel confinement—including the effect of varying ionic strength—and then discuss recent applications of these systems to genomic mapping. Apart from the intense biological interest in extracting linear sequence information from elongated DNA molecules, from a physics view these systems are fascinating as they enable probing of single-molecule conformation in environments with dimensions that intersect key physical length-scales in the 1 nm to 100 µm range.

Can we better predict the biologic behavior of incidental IPMN? A comprehensive analysis of molecular diagnostics and biomarkers in intraductal papillary mucinous neoplasms of the pancreas.

PubMed

Tulla, Kiara A; Maker, Ajay V

2018-03-01

Predicting the biologic behavior of intraductal papillary mucinous neoplasm (IPMN) remains challenging. Current guidelines utilize patient symptoms and imaging characteristics to determine appropriate surgical candidates. However, the majority of resected cysts remain low-risk lesions, many of which may be feasible to have under surveillance. We herein characterize the most promising and up-to-date molecular diagnostics in order to identify optimal components of a molecular signature to distinguish levels of IPMN dysplasia. A comprehensive systematic review of pertinent literature, including our own experience, was conducted based on the PRISMA guidelines. Molecular diagnostics in IPMN patient tissue, duodenal secretions, cyst fluid, saliva, and serum were evaluated and organized into the following categories: oncogenes, tumor suppressor genes, glycoproteins, markers of the immune response, proteomics, DNA/RNA mutations, and next-generation sequencing/microRNA. Specific targets in each of these categories, and in aggregate, were identified by their ability to both characterize a cyst as an IPMN and determine the level of cyst dysplasia. Combining molecular signatures with clinical and imaging features in this era of next-generation sequencing and advanced computational analysis will enable enhanced sensitivity and specificity of current models to predict the biologic behavior of IPMN.

A singular value decomposition approach for improved taxonomic classification of biological sequences

PubMed Central

2011-01-01

Background Singular value decomposition (SVD) is a powerful technique for information retrieval; it helps uncover relationships between elements that are not prima facie related. SVD was initially developed to reduce the time needed for information retrieval and analysis of very large data sets in the complex internet environment. Since information retrieval from large-scale genome and proteome data sets has a similar level of complexity, SVD-based methods could also facilitate data analysis in this research area. Results We found that SVD applied to amino acid sequences demonstrates relationships and provides a basis for producing clusters and cladograms, demonstrating evolutionary relatedness of species that correlates well with Linnaean taxonomy. The choice of a reasonable number of singular values is crucial for SVD-based studies. We found that fewer singular values are needed to produce biologically significant clusters when SVD is employed. Subsequently, we developed a method to determine the lowest number of singular values and fewest clusters needed to guarantee biological significance; this system was developed and validated by comparison with Linnaean taxonomic classification. Conclusions By using SVD, we can reduce uncertainty concerning the appropriate rank value necessary to perform accurate information retrieval analyses. In tests, clusters that we developed with SVD perfectly matched what was expected based on Linnaean taxonomy. PMID:22369633

Consistency of biological networks inferred from microarray and sequencing data.

PubMed

Vinciotti, Veronica; Wit, Ernst C; Jansen, Rick; de Geus, Eco J C N; Penninx, Brenda W J H; Boomsma, Dorret I; 't Hoen, Peter A C

2016-06-24

Sparse Gaussian graphical models are popular for inferring biological networks, such as gene regulatory networks. In this paper, we investigate the consistency of these models across different data platforms, such as microarray and next generation sequencing, on the basis of a rich dataset containing samples that are profiled under both techniques as well as a large set of independent samples. Our analysis shows that individual node variances can have a remarkable effect on the connectivity of the resulting network. Their inconsistency across platforms and the fact that the variability level of a node may not be linked to its regulatory role mean that, failing to scale the data prior to the network analysis, leads to networks that are not reproducible across different platforms and that may be misleading. Moreover, we show how the reproducibility of networks across different platforms is significantly higher if networks are summarised in terms of enrichment amongst functional groups of interest, such as pathways, rather than at the level of individual edges. Careful pre-processing of transcriptional data and summaries of networks beyond individual edges can improve the consistency of network inference across platforms. However, caution is needed at this stage in the (over)interpretation of gene regulatory networks inferred from biological data.

DNA confinement in nanochannels: physics and biological applications.

PubMed

Reisner, Walter; Pedersen, Jonas N; Austin, Robert H

2012-10-01

DNA is the central storage molecule of genetic information in the cell, and reading that information is a central problem in biology. While sequencing technology has made enormous advances over the past decade, there is growing interest in platforms that can readout genetic information directly from long single DNA molecules, with the ultimate goal of single-cell, single-genome analysis. Such a capability would obviate the need for ensemble averaging over heterogeneous cellular populations and eliminate uncertainties introduced by cloning and molecular amplification steps (thus enabling direct assessment of the genome in its native state). In this review, we will discuss how the information contained in genomic-length single DNA molecules can be accessed via physical confinement in nanochannels. Due to self-avoidance interactions, DNA molecules will stretch out when confined in nanochannels, creating a linear unscrolling of the genome along the channel for analysis. We will first review the fundamental physics of DNA nanochannel confinement--including the effect of varying ionic strength--and then discuss recent applications of these systems to genomic mapping. Apart from the intense biological interest in extracting linear sequence information from elongated DNA molecules, from a physics view these systems are fascinating as they enable probing of single-molecule conformation in environments with dimensions that intersect key physical length-scales in the 1 nm to 100 µm range.

Predicting Amyloidogenic Proteins in the Proteomes of Plants.

PubMed

Antonets, Kirill S; Nizhnikov, Anton A

2017-10-16

Amyloids are protein fibrils with characteristic spatial structure. Though amyloids were long perceived to be pathogens that cause dozens of incurable pathologies in humans and mammals, it is currently clear that amyloids also represent a functionally important form of protein structure implicated in a variety of biological processes in organisms ranging from archaea and bacteria to fungi and animals. Despite their social significance, plants remain the most poorly studied group of organisms in the field of amyloid biology. To date, amyloid properties have only been demonstrated in vitro or in heterologous systems for a small number of plant proteins. Here, for the first time, we performed a comprehensive analysis of the distribution of potentially amyloidogenic proteins in the proteomes of approximately 70 species of land plants using the Waltz and SARP (Sequence Analysis based on the Ranking of Probabilities) bioinformatic algorithms. We analyzed more than 2.9 million protein sequences and found that potentially amyloidogenic proteins are abundant in plant proteomes. We found that such proteins are overrepresented among membrane as well as DNA- and RNA-binding proteins of plants. Moreover, seed storage and defense proteins of most plant species are rich in amyloidogenic regions. Taken together, our data demonstrate the diversity of potentially amyloidogenic proteins in plant proteomes and suggest biological processes where formation of amyloids might be functionally important.

Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models

PubMed Central

Stephens, Zachary D.; Hudson, Matthew E.; Mainzer, Liudmila S.; Taschuk, Morgan; Weber, Matthew R.; Iyer, Ravishankar K.

2016-01-01

An obstacle to validating and benchmarking methods for genome analysis is that there are few reference datasets available for which the “ground truth” about the mutational landscape of the sample genome is known and fully validated. Additionally, the free and public availability of real human genome datasets is incompatible with the preservation of donor privacy. In order to better analyze and understand genomic data, we need test datasets that model all variants, reflecting known biology as well as sequencing artifacts. Read simulators can fulfill this requirement, but are often criticized for limited resemblance to true data and overall inflexibility. We present NEAT (NExt-generation sequencing Analysis Toolkit), a set of tools that not only includes an easy-to-use read simulator, but also scripts to facilitate variant comparison and tool evaluation. NEAT has a wide variety of tunable parameters which can be set manually on the default model or parameterized using real datasets. The software is freely available at github.com/zstephens/neat-genreads. PMID:27893777

A study of entropy/clarity of genetic sequences using metric spaces and fuzzy sets.

PubMed

Georgiou, D N; Karakasidis, T E; Nieto, Juan J; Torres, A

2010-11-07

The study of genetic sequences is of great importance in biology and medicine. Sequence analysis and taxonomy are two major fields of application of bioinformatics. In the present paper we extend the notion of entropy and clarity to the use of different metrics and apply them in the case of the Fuzzy Polynuclotide Space (FPS). Applications of these notions on selected polynucleotides and complete genomes both in the I(12×k) space, but also using their representation in FPS are presented. Our results show that the values of fuzzy entropy/clarity are indicative of the degree of complexity necessary for the description of the polynucleotides in the FPS, although in the latter case the interpretation is slightly different than in the case of the I(12×k) hypercube. Fuzzy entropy/clarity along with the use of appropriate metrics can contribute to sequence analysis and taxonomy. Copyright © 2010 Elsevier Ltd. All rights reserved.

India's Computational Biology Growth and Challenges.

PubMed

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Agoramoorthy, Govindasamy

2016-09-01

India's computational science is growing swiftly due to the outburst of internet and information technology services. The bioinformatics sector of India has been transforming rapidly by creating a competitive position in global bioinformatics market. Bioinformatics is widely used across India to address a wide range of biological issues. Recently, computational researchers and biologists are collaborating in projects such as database development, sequence analysis, genomic prospects and algorithm generations. In this paper, we have presented the Indian computational biology scenario highlighting bioinformatics-related educational activities, manpower development, internet boom, service industry, research activities, conferences and trainings undertaken by the corporate and government sectors. Nonetheless, this new field of science faces lots of challenges.

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

PubMed Central

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

2011-01-01

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

Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome

PubMed Central

2010-01-01

Background A goal of the Bovine Genome Database (BGD; http://BovineGenome.org) has been to support the Bovine Genome Sequencing and Analysis Consortium (BGSAC) in the annotation and analysis of the bovine genome. We were faced with several challenges, including the need to maintain consistent quality despite diversity in annotation expertise in the research community, the need to maintain consistent data formats, and the need to minimize the potential duplication of annotation effort. With new sequencing technologies allowing many more eukaryotic genomes to be sequenced, the demand for collaborative annotation is likely to increase. Here we present our approach, challenges and solutions facilitating a large distributed annotation project. Results and Discussion BGD has provided annotation tools that supported 147 members of the BGSAC in contributing 3,871 gene models over a fifteen-week period, and these annotations have been integrated into the bovine Official Gene Set. Our approach has been to provide an annotation system, which includes a BLAST site, multiple genome browsers, an annotation portal, and the Apollo Annotation Editor configured to connect directly to our Chado database. In addition to implementing and integrating components of the annotation system, we have performed computational analyses to create gene evidence tracks and a consensus gene set, which can be viewed on individual gene pages at BGD. Conclusions We have provided annotation tools that alleviate challenges associated with distributed annotation. Our system provides a consistent set of data to all annotators and eliminates the need for annotators to format data. Involving the bovine research community in genome annotation has allowed us to leverage expertise in various areas of bovine biology to provide biological insight into the genome sequence. PMID:21092105

Advantages of genome sequencing by long-read sequencer using SMRT technology in medical area.

PubMed

Nakano, Kazuma; Shiroma, Akino; Shimoji, Makiko; Tamotsu, Hinako; Ashimine, Noriko; Ohki, Shun; Shinzato, Misuzu; Minami, Maiko; Nakanishi, Tetsuhiro; Teruya, Kuniko; Satou, Kazuhito; Hirano, Takashi

2017-07-01

PacBio RS II is the first commercialized third-generation DNA sequencer able to sequence a single molecule DNA in real-time without amplification. PacBio RS II's sequencing technology is novel and unique, enabling the direct observation of DNA synthesis by DNA polymerase. PacBio RS II confers four major advantages compared to other sequencing technologies: long read lengths, high consensus accuracy, a low degree of bias, and simultaneous capability of epigenetic characterization. These advantages surmount the obstacle of sequencing genomic regions such as high/low G+C, tandem repeat, and interspersed repeat regions. Moreover, PacBio RS II is ideal for whole genome sequencing, targeted sequencing, complex population analysis, RNA sequencing, and epigenetics characterization. With PacBio RS II, we have sequenced and analyzed the genomes of many species, from viruses to humans. Herein, we summarize and review some of our key genome sequencing projects, including full-length viral sequencing, complete bacterial genome and almost-complete plant genome assemblies, and long amplicon sequencing of a disease-associated gene region. We believe that PacBio RS II is not only an effective tool for use in the basic biological sciences but also in the medical/clinical setting.

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

Bio and health informatics meets cloud : BioVLab as an example.

PubMed

Chae, Heejoon; Jung, Inuk; Lee, Hyungro; Marru, Suresh; Lee, Seong-Whan; Kim, Sun

2013-01-01

The exponential increase of genomic data brought by the advent of the next or the third generation sequencing (NGS) technologies and the dramatic drop in sequencing cost have driven biological and medical sciences to data-driven sciences. This revolutionary paradigm shift comes with challenges in terms of data transfer, storage, computation, and analysis of big bio/medical data. Cloud computing is a service model sharing a pool of configurable resources, which is a suitable workbench to address these challenges. From the medical or biological perspective, providing computing power and storage is the most attractive feature of cloud computing in handling the ever increasing biological data. As data increases in size, many research organizations start to experience the lack of computing power, which becomes a major hurdle in achieving research goals. In this paper, we review the features of publically available bio and health cloud systems in terms of graphical user interface, external data integration, security and extensibility of features. We then discuss about issues and limitations of current cloud systems and conclude with suggestion of a biological cloud environment concept, which can be defined as a total workbench environment assembling computational tools and databases for analyzing bio/medical big data in particular application domains.

[Progress on molecular biology of Isaria farinosa, pathogen of host of Ophiocordyceps sinensis during the artificial culture].

PubMed

Liu, Fei; Wu, Xiao-Li; Liu, Ying; Chen, Da-Xia; Zhang, De-Li; Yang, Da-Jian

2016-02-01

Isaria farinosa is the pathogen of the host of Ophiocordyceps sinensis. The present research has analyzed the progress on the molecular biology according to the bibliometrics, the sequences (including the gene sequences) of I. farinosa in the NCBI. The results indicated that different country had published different number of the papers, and had landed different kinds and different number of the sequences (including the gene sequences). China had published the most number of the papers, and had landed the most number of the sequences (including the gene sequences). America had landed the most numbers of the function genes. The main content about the pathogen study was focus on the biological controlling. The main content about the molecular study concentrated on the phylogenies classification. In recent years some protease genes and chitinase genes had been researched. With the increase of the effect on the healthy of O. sinensis, and the whole sequence and more and more pharmacological activities of I. farinosa being made known to the public, the study on the molecular biology of the I. farinosa would be deeper and wider. Copyright© by the Chinese Pharmaceutical Association.

Tapping the Power of Crustacean Transcriptomics to Address Grand Challenges in Comparative Biology: An Introduction to the Symposium.

PubMed

Mykles, Donald L; Burnett, Karen G; Durica, David S; Stillman, Jonathon H

2016-12-01

Crustaceans, and decapods in particular (i.e., crabs, shrimp, and lobsters), are a diverse and ecologically and commercially important group of organisms. Understanding responses to abiotic and biotic factors is critical for developing best practices in aquaculture and assessing the effects of changing environments on the biology of these important animals. A relatively small number of decapod crustacean species have been intensively studied at the molecular level; the availability, experimental tractability, and economic relevance factor into the selection of a particular species as a model. Transcriptomics, using high-throughput next generation sequencing (NGS, coupled with RNA sequencing or RNA-seq) is revolutionizing crustacean biology. The 11 symposium papers in this volume illustrate how RNA-seq is being used to study stress response, molting and limb regeneration, immunity and disease, reproduction and development, neurobiology, and ecology and evolution. This symposium occurred on the 10th anniversary of the symposium, "Genomic and Proteomic Approaches to Crustacean Biology", held at the Society for Integrative and Comparative Biology 2006 meeting. Two participants in the 2006 symposium, the late Paul Gross and David Towle, were recognized as leaders who pioneered the use of molecular techniques that would ultimately foster the transcriptomics research reviewed in this volume. RNA-seq is a powerful tool for hypothesis-driven research, as well as an engine for discovery. It has eclipsed the technologies available in 2006, such as microarrays, expressed sequence tags, and subtractive hybridization screening, as the millions of "reads" from NGS enable researchers to de novo assemble a comprehensive transcriptome without a complete genome sequence. The symposium series concludes with a policy paper that gives an overview of the resources available and makes recommendations for developing better tools for functional annotation and pathway and network analysis in organisms in which the genome is not available or is incomplete. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Status of duckweed genomics and transcriptomics.

PubMed

Wang, W; Messing, J

2015-01-01

Duckweeds belong to the smallest flowering plants that undergo fast vegetative growth in an aquatic environment. They are commonly used in wastewater treatment and animal feed. Whereas duckweeds have been studied at the biochemical level, their reduced morphology and wide environmental adaption had not been subjected to molecular analysis until recently. Here, we review the progress that has been made in using a DNA barcode system and the sequences of chloroplast and mitochondrial genomes to identify duckweed species at the species or population level. We also review analysis of the nuclear genome sequence of Spirodela that provides new insights into fundamental biological questions. Indeed, reduced gene families and missing genes are consistent with its compact morphogenesis, aquatic floating and suppression of juvenile-to-adult transition. Furthermore, deep RNA sequencing of Spirodela at the onset of dormancy and Landoltia in exposure of nutrient deficiency illustrate the molecular network for environmental adaption and stress response, constituting major progress towards a post-genome sequencing phase, where further functional genomic details can be explored. Rapid advances in sequencing technologies could continue to promote a proliferation of genome sequences for additional ecotypes as well as for other duckweed species. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Influenza virus sequence feature variant type analysis: evidence of a role for NS1 in influenza virus host range restriction.

PubMed

Noronha, Jyothi M; Liu, Mengya; Squires, R Burke; Pickett, Brett E; Hale, Benjamin G; Air, Gillian M; Galloway, Summer E; Takimoto, Toru; Schmolke, Mirco; Hunt, Victoria; Klem, Edward; García-Sastre, Adolfo; McGee, Monnie; Scheuermann, Richard H

2012-05-01

Genetic drift of influenza virus genomic sequences occurs through the combined effects of sequence alterations introduced by a low-fidelity polymerase and the varying selective pressures experienced as the virus migrates through different host environments. While traditional phylogenetic analysis is useful in tracking the evolutionary heritage of these viruses, the specific genetic determinants that dictate important phenotypic characteristics are often difficult to discern within the complex genetic background arising through evolution. Here we describe a novel influenza virus sequence feature variant type (Flu-SFVT) approach, made available through the public Influenza Research Database resource (www.fludb.org), in which variant types (VTs) identified in defined influenza virus protein sequence features (SFs) are used for genotype-phenotype association studies. Since SFs have been defined for all influenza virus proteins based on known structural, functional, and immune epitope recognition properties, the Flu-SFVT approach allows the rapid identification of the molecular genetic determinants of important influenza virus characteristics and their connection to underlying biological functions. We demonstrate the use of the SFVT approach to obtain statistical evidence for effects of NS1 protein sequence variations in dictating influenza virus host range restriction.

Positioning Genomics in Biology Education: Content Mapping of Undergraduate Biology Textbooks†

PubMed Central

Wernick, Naomi L. B.; Ndung’u, Eric; Haughton, Dominique; Ledley, Fred D.

2014-01-01

Biological thought increasingly recognizes the centrality of the genome in constituting and regulating processes ranging from cellular systems to ecology and evolution. In this paper, we ask whether genomics is similarly positioned as a core concept in the instructional sequence for undergraduate biology. Using quantitative methods, we analyzed the order in which core biological concepts were introduced in textbooks for first-year general and human biology. Statistical analysis was performed using self-organizing map algorithms and conventional methods to identify clusters of terms and their relative position in the books. General biology textbooks for both majors and nonmajors introduced genome-related content after text related to cell biology and biological chemistry, but before content describing higher-order biological processes. However, human biology textbooks most often introduced genomic content near the end of the books. These results suggest that genomics is not yet positioned as a core concept in commonly used textbooks for first-year biology and raises questions about whether such textbooks, or courses based on the outline of these textbooks, provide an appropriate foundation for understanding contemporary biological science. PMID:25574293

Positioning genomics in biology education: content mapping of undergraduate biology textbooks.

PubMed

Wernick, Naomi L B; Ndung'u, Eric; Haughton, Dominique; Ledley, Fred D

2014-12-01

Biological thought increasingly recognizes the centrality of the genome in constituting and regulating processes ranging from cellular systems to ecology and evolution. In this paper, we ask whether genomics is similarly positioned as a core concept in the instructional sequence for undergraduate biology. Using quantitative methods, we analyzed the order in which core biological concepts were introduced in textbooks for first-year general and human biology. Statistical analysis was performed using self-organizing map algorithms and conventional methods to identify clusters of terms and their relative position in the books. General biology textbooks for both majors and nonmajors introduced genome-related content after text related to cell biology and biological chemistry, but before content describing higher-order biological processes. However, human biology textbooks most often introduced genomic content near the end of the books. These results suggest that genomics is not yet positioned as a core concept in commonly used textbooks for first-year biology and raises questions about whether such textbooks, or courses based on the outline of these textbooks, provide an appropriate foundation for understanding contemporary biological science.

Rapid differentiation of citrus Hop stunt viroid variants by real-time RT-PCR and high resolution melting analysis.

PubMed

Loconsole, Giuliana; Onelge, Nuket; Yokomi, Raymond K; Kubaa, Raied Abou; Savino, Vito; Saponari, Maria

2013-01-01

The RNA genome of pathogenic and non-pathogenic variants of citrus Hop stunt viroid (HSVd) differ by five to six nucleotides located within the variable (V) domain referred to as the "cachexia expression motif". Sensitive hosts such as mandarin and its hybrids are seriously affected by cachexia disease. Current methods to differentiate HSVd variants rely on lengthy greenhouse biological indexing on Parson's Special mandarin and/or direct nucleotide sequence analysis of amplicons from RT-PCR of HSVd-infected plants. Two independent high throughput assays to segregate HSVd variants by real-time RT-PCR and High-Resolution Melting Temperature (HRM) analysis were developed: one based on EVAGreen dye; the other based on TaqMan probes. Primers for both assays targeted three differentiating nucleotides in the V domain which separated HSVd variants into three clusters by distinct melting temperatures with a confidence level higher than 98%. The accuracy of the HRM assays were validated by nucleotide sequencing of representative samples within each HRM cluster and by testing 45 HSVd-infected field trees from California, Italy, Spain, Syria and Turkey. To our knowledge, this is the first report of a rapid and sensitive approach to detect and differentiate HSVd variants associated with different biological behaviors. Although, HSVd is found in several crops including citrus, cachexia variants are restricted to some citrus-growing areas, particularly the Mediterranean Region. Rapid diagnosis for cachexia and non-cachexia variants is, thus, important for the management of HSVd in citrus and reduces the need for bioindexing and sequencing analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genome sequences of three strains of Aspergillus flavus for the biological control of Aflatoxin

USDA-ARS?s Scientific Manuscript database

The genomes of three strains of Aspergillus flavus with demonstrated utility for the biological control of aflatoxin were sequenced. These sequences were assembled with MIRA and annotated with Augustus using A. flavus strain 3357 (NCBI EQ963472) as a reference. Each strain had a genome of 36.3 to ...

SNAD: Sequence Name Annotation-based Designer.

PubMed

Sidorov, Igor A; Reshetov, Denis A; Gorbalenya, Alexander E

2009-08-14

A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Here we introduce SNAD (Sequence Name Annotation-based Designer) that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list) into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

High definition for systems biology of microbial communities: metagenomics gets genome-centric and strain-resolved.

PubMed

Turaev, Dmitrij; Rattei, Thomas

2016-06-01

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. Copyright © 2016 Elsevier Ltd. All rights reserved.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: summary and innovation in genomics.

PubMed

Zhao, Zhongming; Liu, Zhandong; Chen, Ken; Guo, Yan; Allen, Genevera I; Zhang, Jiajie; Jim Zheng, W; Ruan, Jianhua

2017-10-03

In this editorial, we first summarize the 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016) that was held on December 8-10, 2016 in Houston, Texas, USA, and then briefly introduce the ten research articles included in this supplement issue. ICIBM 2016 included four workshops or tutorials, four keynote lectures, four conference invited talks, eight concurrent scientific sessions and a poster session for 53 accepted abstracts, covering current topics in bioinformatics, systems biology, intelligent computing, and biomedical informatics. Through our call for papers, a total of 77 original manuscripts were submitted to ICIBM 2016. After peer review, 11 articles were selected in this special issue, covering topics such as single cell RNA-seq analysis method, genome sequence and variation analysis, bioinformatics method for vaccine development, and cancer genomics.

Biospark: scalable analysis of large numerical datasets from biological simulations and experiments using Hadoop and Spark.

PubMed

Klein, Max; Sharma, Rati; Bohrer, Chris H; Avelis, Cameron M; Roberts, Elijah

2017-01-15

Data-parallel programming techniques can dramatically decrease the time needed to analyze large datasets. While these methods have provided significant improvements for sequencing-based analyses, other areas of biological informatics have not yet adopted them. Here, we introduce Biospark, a new framework for performing data-parallel analysis on large numerical datasets. Biospark builds upon the open source Hadoop and Spark projects, bringing domain-specific features for biology. Source code is licensed under the Apache 2.0 open source license and is available at the project website: https://www.assembla.com/spaces/roberts-lab-public/wiki/Biospark CONTACT: eroberts@jhu.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

PubMed Central

Partha, Raghavendran; Raman, Karthik

2014-01-01

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to normal populations evolving on neutral networks. PMID:25390641

Toward a Genome-Wide Systems Biology Analysis of Host-Pathogen Interactions in Group A Streptococcus

PubMed Central

Musser, James M.; DeLeo, Frank R.

2005-01-01

Genome-wide analysis of microbial pathogens and molecular pathogenesis processes has become an area of considerable activity in the last 5 years. These studies have been made possible by several advances, including completion of the human genome sequence, publication of genome sequences for many human pathogens, development of microarray technology and high-throughput proteomics, and maturation of bioinformatics. Despite these advances, relatively little effort has been expended in the bacterial pathogenesis arena to develop and use integrated research platforms in a systems biology approach to enhance our understanding of disease processes. This review discusses progress made in exploiting an integrated genome-wide research platform to gain new knowledge about how the human bacterial pathogen group A Streptococcus causes disease. Results of these studies have provided many new avenues for basic pathogenesis research and translational research focused on development of an efficacious human vaccine and novel therapeutics. One goal in summarizing this line of study is to bring exciting new findings to the attention of the investigative pathology community. In addition, we hope the review will stimulate investigators to consider using analogous approaches for analysis of the molecular pathogenesis of other microbes. PMID:16314461

pYEMF, a pUC18-derived XcmI T-vector for efficient cloning of PCR products.

PubMed

Gu, Jingsong; Ye, Chunjiang

2011-03-01

A 1330-bp DNA sequence with two XcmI cassettes was inserted into pUC18 to construct an efficient XcmI T-vector parent plasmid, pYEMF. The large size of the inserted DNA fragment improved T-vector cleavage efficiency, and guaranteed good separation of the molecular components after restriction digestion. The pYEMF-T-vector generated from parent plasmid pYEMF permits blue/white colony screening; cloning efficiency analysis showed that most white colonies (>75%) were putative transformants which carried the cloning product. The sequence analysis and design approach presented here will facilitate applications in the fields of molecular biology and genetic engineering.

Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

PubMed

Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

2016-07-19

Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

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

Model-based reconstruction of synthetic promoter library in Corynebacterium glutamicum.

PubMed

Zhang, Shuanghong; Liu, Dingyu; Mao, Zhitao; Mao, Yufeng; Ma, Hongwu; Chen, Tao; Zhao, Xueming; Wang, Zhiwen

2018-05-01

To develop an efficient synthetic promoter library for fine-tuned expression of target genes in Corynebacterium glutamicum. A synthetic promoter library for C. glutamicum was developed based on conserved sequences of the - 10 and - 35 regions. The synthetic promoter library covered a wide range of strengths, ranging from 1 to 193% of the tac promoter. 68 promoters were selected and sequenced for correlation analysis between promoter sequence and strength with a statistical model. A new promoter library was further reconstructed with improved promoter strength and coverage based on the results of correlation analysis. Tandem promoter P70 was finally constructed with increased strength by 121% over the tac promoter. The promoter library developed in this study showed a great potential for applications in metabolic engineering and synthetic biology for the optimization of metabolic networks. To the best of our knowledge, this is the first reconstruction of synthetic promoter library based on statistical analysis of C. glutamicum.

A basic analysis toolkit for biological sequences

PubMed Central

Giancarlo, Raffaele; Siragusa, Alessandro; Siragusa, Enrico; Utro, Filippo

2007-01-01

This paper presents a software library, nicknamed BATS, for some basic sequence analysis tasks. Namely, local alignments, via approximate string matching, and global alignments, via longest common subsequence and alignments with affine and concave gap cost functions. Moreover, it also supports filtering operations to select strings from a set and establish their statistical significance, via z-score computation. None of the algorithms is new, but although they are generally regarded as fundamental for sequence analysis, they have not been implemented in a single and consistent software package, as we do here. Therefore, our main contribution is to fill this gap between algorithmic theory and practice by providing an extensible and easy to use software library that includes algorithms for the mentioned string matching and alignment problems. The library consists of C/C++ library functions as well as Perl library functions. It can be interfaced with Bioperl and can also be used as a stand-alone system with a GUI. The software is available at under the GNU GPL. PMID:17877802

MethylViewer: computational analysis and editing for bisulfite sequencing and methyltransferase accessibility protocol for individual templates (MAPit) projects.

PubMed

Pardo, Carolina E; Carr, Ian M; Hoffman, Christopher J; Darst, Russell P; Markham, Alexander F; Bonthron, David T; Kladde, Michael P

2011-01-01

Bisulfite sequencing is a widely-used technique for examining cytosine DNA methylation at nucleotide resolution along single DNA strands. Probing with cytosine DNA methyltransferases followed by bisulfite sequencing (MAPit) is an effective technique for mapping protein-DNA interactions. Here, MAPit methylation footprinting with M.CviPI, a GC methyltransferase we previously cloned and characterized, was used to probe hMLH1 chromatin in HCT116 and RKO colorectal cancer cells. Because M.CviPI-probed samples contain both CG and GC methylation, we developed a versatile, visually-intuitive program, called MethylViewer, for evaluating the bisulfite sequencing results. Uniquely, MethylViewer can simultaneously query cytosine methylation status in bisulfite-converted sequences at as many as four different user-defined motifs, e.g. CG, GC, etc., including motifs with degenerate bases. Data can also be exported for statistical analysis and as publication-quality images. Analysis of hMLH1 MAPit data with MethylViewer showed that endogenous CG methylation and accessible GC sites were both mapped on single molecules at high resolution. Disruption of positioned nucleosomes on single molecules of the PHO5 promoter was detected in budding yeast using M.CviPII, increasing the number of enzymes available for probing protein-DNA interactions. MethylViewer provides an integrated solution for primer design and rapid, accurate and detailed analysis of bisulfite sequencing or MAPit datasets from virtually any biological or biochemical system.

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

PubMed

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

2012-01-01

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

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Sequence determination of synthesized chondroitin sulfate dodecasaccharides.

PubMed

Shioiri, Tatsumasa; Tsuchimoto, Jun; Watanabe, Hideto; Sugiura, Nobuo

2016-06-01

Chondroitin sulfate (CS) is a linear acidic polysaccharide composed of repeating disaccharide units of glucuronic acid and N-acetyl-d-galactosamine. The polysaccharide is modified with sulfate groups at different positions by a variety of sulfotransferases. CS chains exhibit various biological and pathological functions by interacting with cytokines and growth factors and regulating their signal transduction. The fine structure of the CS chain defines its specific biological roles. However, structural analysis of CS has been restricted to disaccharide analysis, hampering the understanding of the structure-function relationship of CS chains. Here, we chemo-enzymatically synthesized CS dodecasaccharides having various sulfate modifications using a bioreactor system of bacterial chondroitin polymerase mutants and various CS sulfotransferases. We developed a sequencing method for CS chains using the CS dodecasaccharides. The method consists of (i) labeling a reducing end with 2-aminopyridine (PA), (ii) partial digestion of CS with testicular hyaluronidase, followed by separation of PA-conjugated oligosaccharides with different chain lengths, (iii) limited digestion of these oligosaccharides with chondroitin lyase AC II into disaccharides, followed by labeling with 2-aminobenzamide, (iv) CS disaccharide analysis using a dual-fluorescence HPLC system (reversed-phase ion-pair and ion-exchange chromatography), and (v) estimation of the composition by calculating individual disaccharide ratios. This CS chain sequencing allows characterization of CS-modifying enzymes and provides a useful tool toward understanding the structure-function relationship of CS chains. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

KinFin: Software for Taxon-Aware Analysis of Clustered Protein Sequences.

PubMed

Laetsch, Dominik R; Blaxter, Mark L

2017-10-05

The field of comparative genomics is concerned with the study of similarities and differences between the information encoded in the genomes of organisms. A common approach is to define gene families by clustering protein sequences based on sequence similarity, and analyze protein cluster presence and absence in different species groups as a guide to biology. Due to the high dimensionality of these data, downstream analysis of protein clusters inferred from large numbers of species, or species with many genes, is nontrivial, and few solutions exist for transparent, reproducible, and customizable analyses. We present KinFin, a streamlined software solution capable of integrating data from common file formats and delivering aggregative annotation of protein clusters. KinFin delivers analyses based on systematic taxonomy of the species analyzed, or on user-defined, groupings of taxa, for example, sets based on attributes such as life history traits, organismal phenotypes, or competing phylogenetic hypotheses. Results are reported through graphical and detailed text output files. We illustrate the utility of the KinFin pipeline by addressing questions regarding the biology of filarial nematodes, which include parasites of veterinary and medical importance. We resolve the phylogenetic relationships between the species and explore functional annotation of proteins in clusters in key lineages and between custom taxon sets, identifying gene families of interest. KinFin can easily be integrated into existing comparative genomic workflows, and promotes transparent and reproducible analysis of clustered protein data. Copyright © 2017 Laetsch and Blaxter.

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

PubMed

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

2016-03-01

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

Fourteenth-Sixteenth Microbial Genomics Conference-2006-2008

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

Miller, Jeffrey H

2011-04-18

The concept of an annual meeting on the E. coli genome was formulated at the Banbury Center Conference on the Genome of E. coli in October, 1991. The first meeting was held on September 10-14, 1992 at the University of Wisconsin, and this was followed by a yearly series of meetings, and by an expansion to include The fourteenth meeting took place September 24-28, 2006 at Lake Arrowhead, CA, the fifteenth September 16-20, 2007 at the University of Maryland, College Park, MD, and the sixteenth September 14-18, 2008 at Lake Arrowhead. The full program for the 16th meeting is attached.more » There have been rapid and exciting advances in microbial genomics that now make possible comparing large data sets of sequences from a wide variety of microbial genomes, and from whole microbial communities. Examining the “microbiomes”, the living microbial communities in different host organisms opens up many possibilities for understanding the landscape presented to pathogenic microorganisms. For quite some time there has been a shifting emphasis from pure sequence data to trying to understand how to use that information to solve biological problems. Towards this end new technologies are being developed and improved. Using genetics, functional genomics, and proteomics has been the recent focus of many different laboratories. A key element is the integration of different aspects of microbiology, sequencing technology, analysis techniques, and bioinformatics. The goal of these conference is to provide a regular forum for these interactions to occur. While there have been a number of genome conferences, what distinguishes the Microbial Genomics Conference is its emphasis on bringing together biology and genetics with sequencing and bioinformatics. Also, this conference is the longest continuing meeting, now established as a major regular annual meeting. In addition to its coverage of microbial genomes and biodiversity, the meetings also highlight microbial communities and the use of genomic information to aid in the understanding of pathogens and biothreats. An additional focus cover s“bioenergetics. The meetings have a mix of invited and participant-initiated presentations and poster sessions during which investigators from different disciplines become familiar with available data bases and new tools facilitating coordination of information. The fields are moving very fast both in the acquisition of new knowledge of genome contents and also in the management and analysis of the information. The key is connecting bodies of knowledge on sequences, genetic organization and regulation to be able to relate the significance of this information to understanding cellular processes. To our knowledge, no other meeting synthesizes the biology of organisms, sequence information and database analysis, as well as the comparison with other completed genome sequences.« less

Detecting cooperative sequences in the binding of RNA Polymerase-II

NASA Astrophysics Data System (ADS)

Glass, Kimberly; Rozenberg, Julian; Girvan, Michelle; Losert, Wolfgang; Ott, Ed; Vinson, Charles

2008-03-01

Regulation of the expression level of genes is a key biological process controlled largely by the 1000 base pair (bp) sequence preceding each gene (the promoter region). Within that region transcription factor binding sites (TFBS), 5-10 bp long sequences, act individually or cooperate together in the recruitment of, and therefore subsequent gene transcription by, RNA Polymerase-II (RNAP). We have measured the binding of RNAP to promoters on a genome-wide basis using Chromatin Immunoprecipitation (ChIP-on-Chip) microarray assays. Using all 8-base pair long sequences as a test set, we have identified the DNA sequences that are enriched in promoters with high RNAP binding values. We are able to demonstrate that virtually all sequences enriched in such promoters contain a CpG dinucleotide, indicating that TFBS that contain the CpG dinucleotide are involved in RNAP binding to promoters. Further analysis shows that the presence of pairs of CpG containing sequences cooperate to enhance the binding of RNAP to the promoter.

Perigone Lobe Transcriptome Analysis Provides Insights into Rafflesia cantleyi Flower Development.

PubMed

Lee, Xin-Wei; Mat-Isa, Mohd-Noor; Mohd-Elias, Nur-Atiqah; Aizat-Juhari, Mohd Afiq; Goh, Hoe-Han; Dear, Paul H; Chow, Keng-See; Haji Adam, Jumaat; Mohamed, Rahmah; Firdaus-Raih, Mohd; Wan, Kiew-Lian

2016-01-01

Rafflesia is a biologically enigmatic species that is very rare in occurrence and possesses an extraordinary morphology. This parasitic plant produces a gigantic flower up to one metre in diameter with no leaves, stem or roots. However, little is known about the floral biology of this species especially at the molecular level. In an effort to address this issue, we have generated and characterised the transcriptome of the Rafflesia cantleyi flower, and performed a comparison with the transcriptome of its floral bud to predict genes that are expressed and regulated during flower development. Approximately 40 million sequencing reads were generated and assembled de novo into 18,053 transcripts with an average length of 641 bp. Of these, more than 79% of the transcripts had significant matches to annotated sequences in the public protein database. A total of 11,756 and 7,891 transcripts were assigned to Gene Ontology categories and clusters of orthologous groups respectively. In addition, 6,019 transcripts could be mapped to 129 pathways in Kyoto Encyclopaedia of Genes and Genomes Pathway database. Digital abundance analysis identified 52 transcripts with very high expression in the flower transcriptome of R. cantleyi. Subsequently, analysis of differential expression between developing flower and the floral bud revealed a set of 105 transcripts with potential role in flower development. Our work presents a deep transcriptome resource analysis for the developing flower of R. cantleyi. Genes potentially involved in the growth and development of the R. cantleyi flower were identified and provide insights into biological processes that occur during flower development.

Genomics and metagenomics in medical microbiology.

PubMed

Padmanabhan, Roshan; Mishra, Ajay Kumar; Raoult, Didier; Fournier, Pierre-Edouard

2013-12-01

Over the last two decades, sequencing tools have evolved from laborious time-consuming methodologies to real-time detection and deciphering of genomic DNA. Genome sequencing, especially using next generation sequencing (NGS) has revolutionized the landscape of microbiology and infectious disease. This deluge of sequencing data has not only enabled advances in fundamental biology but also helped improve diagnosis, typing of pathogen, virulence and antibiotic resistance detection, and development of new vaccines and culture media. In addition, NGS also enabled efficient analysis of complex human micro-floras, both commensal, and pathological, through metagenomic methods, thus helping the comprehension and management of human diseases such as obesity. This review summarizes technological advances in genomics and metagenomics relevant to the field of medical microbiology. Copyright © 2013 Elsevier B.V. All rights reserved.

Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data.

PubMed

Dunn, Joshua G; Weissman, Jonathan S

2016-11-22

Next-generation sequencing (NGS) informs many biological questions with unprecedented depth and nucleotide resolution. These assays have created a need for analytical tools that enable users to manipulate data nucleotide-by-nucleotide robustly and easily. Furthermore, because many NGS assays encode information jointly within multiple properties of read alignments - for example, in ribosome profiling, the locations of ribosomes are jointly encoded in alignment coordinates and length - analytical tools are often required to extract the biological meaning from the alignments before analysis. Many assay-specific pipelines exist for this purpose, but there remains a need for user-friendly, generalized, nucleotide-resolution tools that are not limited to specific experimental regimes or analytical workflows. Plastid is a Python library designed specifically for nucleotide-resolution analysis of genomics and NGS data. As such, Plastid is designed to extract assay-specific information from read alignments while retaining generality and extensibility to novel NGS assays. Plastid represents NGS and other biological data as arrays of values associated with genomic or transcriptomic positions, and contains configurable tools to convert data from a variety of sources to such arrays. Plastid also includes numerous tools to manipulate even discontinuous genomic features, such as spliced transcripts, with nucleotide precision. Plastid automatically handles conversion between genomic and feature-centric coordinates, accounting for splicing and strand, freeing users of burdensome accounting. Finally, Plastid's data models use consistent and familiar biological idioms, enabling even beginners to develop sophisticated analytical workflows with minimal effort. Plastid is a versatile toolkit that has been used to analyze data from multiple NGS assays, including RNA-seq, ribosome profiling, and DMS-seq. It forms the genomic engine of our ORF annotation tool, ORF-RATER, and is readily adapted to novel NGS assays. Examples, tutorials, and extensive documentation can be found at https://plastid.readthedocs.io .

Applications of Mass Spectrometry to Structural Analysis of Marine Oligosaccharides

PubMed Central

Lang, Yinzhi; Zhao, Xia; Liu, Lili; Yu, Guangli

2014-01-01

Marine oligosaccharides have attracted increasing attention recently in developing potential drugs and biomaterials for their particular physical and chemical properties. However, the composition and sequence analysis of marine oligosaccharides are very challenging for their structural complexity and heterogeneity. Mass spectrometry (MS) has become an important technique for carbohydrate analysis by providing more detailed structural information, including molecular mass, sugar constituent, sequence, inter-residue linkage position and substitution pattern. This paper provides an overview of the structural analysis based on MS approaches in marine oligosaccharides, which are derived from some biologically important marine polysaccharides, including agaran, carrageenan, alginate, sulfated fucan, chitosan, glycosaminoglycan (GAG) and GAG-like polysaccharides. Applications of electrospray ionization mass spectrometry (ESI-MS) are mainly presented and the general applications of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) are also outlined. Some technical challenges in the structural analysis of marine oligosaccharides by MS have also been pointed out. PMID:24983643

Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan).

PubMed

Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Kumar, Vinay; Kale, Sandip M; Sinha, Pallavi; Chitikineni, Annapurna; Pazhamala, Lekha T; Garg, Vanika; Sharma, Mamta; Sameer Kumar, Chanda Venkata; Parupalli, Swathi; Vechalapu, Suryanarayana; Patil, Suyash; Muniswamy, Sonnappa; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Dharmaraj, Pallavi Subbanna; Varshney, Rajeev K

2016-05-01

To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing-based bulked segregant analysis (Seq-BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R- and S-bulks with the help of draft genome sequence and reference-guided assembly of ICPL 20096 (resistant parent). Seq-BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re-sequenced and their combined analysis with R- and S-bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2-Mb flanking regions of seven candidate SNPs identified through Seq-BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re-sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics-assisted breeding in pigeonpea. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Growing trend of CE at the omics level: the frontier of systems biology--an update.

PubMed

Ban, Eunmi; Park, Soo Hyun; Kang, Min-Jung; Lee, Hyun-Jung; Song, Eun Joo; Yoo, Young Sook

2012-01-01

Omics is the study of proteins, peptides, genes, and metabolites in living organisms. Systems biology aims to understand the system through the study of the relationship between elements such as genes and proteins in biological system. Recently, systems biology emerged as the result of the advanced development of high-throughput analysis technologies such as DNA sequencers, DNA arrays, and mass spectrometry for omics studies. Among a number of analytical tools and technologies, CE and CE coupled to MS are promising and relatively rapidly developing tools with the potential to provide qualitative and quantitative analyses of biological molecules. With an emphasis on CE for systems biology, this review summarizes the method developments and applications of CE for the genomic, transcriptomic, proteomic, and metabolomic studies focusing on the drug discovery and disease diagnosis and therapies since 2009. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Hydra genome: insights, puzzles and opportunities for developmental biologists.

PubMed

Steele, Robert E

2012-01-01

The sequencing of a Hydra genome marked the beginning of a new era in the use of Hydra as a developmental model. Analysis of the genome sequence has led to a number of interesting findings, has required revisiting of previous work, and most importantly presents new opportunities for understanding the developmental biology of Hydra. This review will de-scribe the history of the Hydra genome project, a selection of results from it that are relevant to developmental biologists, and some future research opportunities provided by Hydra genomics.

Next generation sequencing (NGS): a golden tool in forensic toolkit.

PubMed

Aly, S M; Sabri, D M

The DNA analysis is a cornerstone in contemporary forensic sciences. DNA sequencing technologies are powerful tools that enrich molecular sciences in the past based on Sanger sequencing and continue to glowing these sciences based on Next generation sequencing (NGS). Next generation sequencing has excellent potential to flourish and increase the molecular applications in forensic sciences by jumping over the pitfalls of the conventional method of sequencing. The main advantages of NGS compared to conventional method that it utilizes simultaneously a large number of genetic markers with high-resolution of genetic data. These advantages will help in solving several challenges such as mixture analysis and dealing with minute degraded samples. Based on these new technologies, many markers could be examined to get important biological data such as age, geographical origins, tissue type determination, external visible traits and monozygotic twins identification. It also could get data related to microbes, insects, plants and soil which are of great medico-legal importance. Despite the dozens of forensic research involving NGS, there are requirements before using this technology routinely in forensic cases. Thus, there is a great need to more studies that address robustness of these techniques. Therefore, this work highlights the applications of forensic sciences in the era of massively parallel sequencing.

VKCDB: voltage-gated K+ channel database updated and upgraded.

PubMed

Gallin, Warren J; Boutet, Patrick A

2011-01-01

The Voltage-gated K(+) Channel DataBase (VKCDB) (http://vkcdb.biology.ualberta.ca) makes a comprehensive set of sequence data readily available for phylogenetic and comparative analysis. The current update contains 2063 entries for full-length or nearly full-length unique channel sequences from Bacteria (477), Archaea (18) and Eukaryotes (1568), an increase from 346 solely eukaryotic entries in the original release. In addition to protein sequences for channels, corresponding nucleotide sequences of the open reading frames corresponding to the amino acid sequences are now available and can be extracted in parallel with sets of protein sequences. Channels are categorized into subfamilies by phylogenetic analysis and by using hidden Markov model analyses. Although the raw database contains a number of fragmentary, duplicated, obsolete and non-channel sequences that were collected in early steps of data collection, the web interface will only return entries that have been validated as likely K(+) channels. The retrieval function of the web interface allows retrieval of entries that contain a substantial fraction of the core structural elements of VKCs, fragmentary entries, or both. The full database can be downloaded as either a MySQL dump or as an XML dump from the web site. We have now implemented automated updates at quarterly intervals.

Yeast Genomics for Bread, Beer, Biology, Bucks and Breath

NASA Astrophysics Data System (ADS)

Sakharkar, Kishore R.; Sakharkar, Meena K.

The rapid advances and scale up of projects in DNA sequencing dur ing the past two decades have produced complete genome sequences of several eukaryotic species. The versatile genetic malleability of the yeast, and the high degree of conservation between its cellular processes and those of human cells have made it a model of choice for pioneering research in molecular and cell biology. The complete sequence of yeast genome has proven to be extremely useful as a reference towards the sequences of human and for providing systems to explore key gene functions. Yeast has been a ‘legendary model’ for new technologies and gaining new biological insights into basic biological sciences and biotechnology. This chapter describes the awesome power of yeast genetics, genomics and proteomics in understanding of biological function. The applications of yeast as a screening tool to the field of drug discovery and development are highlighted and the traditional importance of yeast for bakers and brewers is discussed.

Development and Assessment of a Horizontally Integrated Biological Sciences Course Sequence for Pharmacy Education

PubMed Central

Wright, Nicholas J.D.; Alston, Gregory L.

2015-01-01

Objective. To design and assess a horizontally integrated biological sciences course sequence and to determine its effectiveness in imparting the foundational science knowledge necessary to successfully progress through the pharmacy school curriculum and produce competent pharmacy school graduates. Design. A 2-semester course sequence integrated principles from several basic science disciplines: biochemistry, molecular biology, cellular biology, anatomy, physiology, and pathophysiology. Each is a 5-credit course taught 5 days per week, with 50-minute class periods. Assessment. Achievement of outcomes was determined with course examinations, student lecture, and an annual skills mastery assessment. The North American Pharmacist Licensure Examination (NAPLEX) results were used as an indicator of competency to practice pharmacy. Conclusion. Students achieved course objectives and program level outcomes. The biological sciences integrated course sequence was successful in providing students with foundational basic science knowledge required to progress through the pharmacy program and to pass the NAPLEX. The percentage of the school’s students who passed the NAPLEX was not statistically different from the national percentage. PMID:26430276

The Anopheles stephensi odorant binding protein 1 (AsteObp1) gene: a new molecular marker for biological forms diagnosis.

PubMed

Gholizadeh, S; Firooziyan, S; Ladonni, H; Hajipirloo, H Mohammadzadeh; Djadid, N Dinparast; Hosseini, A; Raz, A

2015-06-01

Anopheles (Cellia) stephensi Liston 1901 is known as an Asian malaria vector. Three biological forms, namely "mysorensis", "intermediate", and "type" have been earlier reported in this species. Nevertheless, the present morphological and molecular information is insufficient to diagnose these forms. During this investigation, An. stephensi biological forms were morphologically identified and sequenced for odorant-binding protein 1 (Obp1) gene. Also, intron I sequences were used to construct phylogenetic trees. Despite nucleotide sequence variation in exon of AsteObp1, nearly 100% identity was observed at the amino acid level among the three biological forms. In order to overcome difficulties in using egg morphology characters, intron I sequences of An. stephensi Obp1 opens new molecular way to the identification of the main Asian malaria vector biological forms. However, multidisciplinary studies are needed to establish the taxonomic status of An. stephensi. Copyright © 2015 Elsevier B.V. All rights reserved.

CoryneBase: Corynebacterium Genomic Resources and Analysis Tools at Your Fingertips

PubMed Central

Tan, Mui Fern; Jakubovics, Nick S.; Wee, Wei Yee; Mutha, Naresh V. R.; Wong, Guat Jah; Ang, Mia Yang; Yazdi, Amir Hessam; Choo, Siew Woh

2014-01-01

Corynebacteria are used for a wide variety of industrial purposes but some species are associated with human diseases. With increasing number of corynebacterial genomes having been sequenced, comparative analysis of these strains may provide better understanding of their biology, phylogeny, virulence and taxonomy that may lead to the discoveries of beneficial industrial strains or contribute to better management of diseases. To facilitate the ongoing research of corynebacteria, a specialized central repository and analysis platform for the corynebacterial research community is needed to host the fast-growing amount of genomic data and facilitate the analysis of these data. Here we present CoryneBase, a genomic database for Corynebacterium with diverse functionality for the analysis of genomes aimed to provide: (1) annotated genome sequences of Corynebacterium where 165,918 coding sequences and 4,180 RNAs can be found in 27 species; (2) access to comprehensive Corynebacterium data through the use of advanced web technologies for interactive web interfaces; and (3) advanced bioinformatic analysis tools consisting of standard BLAST for homology search, VFDB BLAST for sequence homology search against the Virulence Factor Database (VFDB), Pairwise Genome Comparison (PGC) tool for comparative genomic analysis, and a newly designed Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomic analysis. CoryneBase offers the access of a range of Corynebacterium genomic resources as well as analysis tools for comparative genomics and pathogenomics. It is publicly available at http://corynebacterium.um.edu.my/. PMID:24466021

Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity.

PubMed

King, Brian R; Aburdene, Maurice; Thompson, Alex; Warres, Zach

2014-01-01

Digital signal processing (DSP) techniques for biological sequence analysis continue to grow in popularity due to the inherent digital nature of these sequences. DSP methods have demonstrated early success for detection of coding regions in a gene. Recently, these methods are being used to establish DNA gene similarity. We present the inter-coefficient difference (ICD) transformation, a novel extension of the discrete Fourier transformation, which can be applied to any DNA sequence. The ICD method is a mathematical, alignment-free DNA comparison method that generates a genetic signature for any DNA sequence that is used to generate relative measures of similarity among DNA sequences. We demonstrate our method on a set of insulin genes obtained from an evolutionarily wide range of species, and on a set of avian influenza viral sequences, which represents a set of highly similar sequences. We compare phylogenetic trees generated using our technique against trees generated using traditional alignment techniques for similarity and demonstrate that the ICD method produces a highly accurate tree without requiring an alignment prior to establishing sequence similarity.

The Effects of Meiosis/Genetics Integration and Instructional Sequence on College Biology Student Achievement in Genetics.

ERIC Educational Resources Information Center

Browning, Mark

The purpose of the research was to manipulate two aspects of genetics instruction in order to measure their effects on college, introductory biology students' achievement in genetics. One instructional sequence that was used dealt first with monohybrid autosomal inheritance patterns, then sex-linkage. The alternate sequence was the reverse.…

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Effectiveness of a cloning and sequencing exercise on student learning with subsequent publication in the National Center for Biotechnology Information GenBank.

PubMed

Lau, Joann M; Robinson, David L

2009-01-01

With rapid advances in biotechnology and molecular biology, instructors are challenged to not only provide undergraduate students with hands-on experiences in these disciplines but also to engage them in the "real-world" scientific process. Two common topics covered in biotechnology or molecular biology courses are gene-cloning and bioinformatics, but to provide students with a continuous laboratory-based research experience in these techniques is difficult. To meet these challenges, we have partnered with Bio-Rad Laboratories in the development of the "Cloning and Sequencing Explorer Series," which combines wet-lab experiences (e.g., DNA extraction, polymerase chain reaction, ligation, transformation, and restriction digestion) with bioinformatics analysis (e.g., evaluation of DNA sequence quality, sequence editing, Basic Local Alignment Search Tool searches, contig construction, intron identification, and six-frame translation) to produce a sequence publishable in the National Center for Biotechnology Information GenBank. This 6- to 8-wk project-based exercise focuses on a pivotal gene of glycolysis (glyceraldehyde-3-phosphate dehydrogenase), in which students isolate, sequence, and characterize the gene from a plant species or cultivar not yet published in GenBank. Student achievement was evaluated using pre-, mid-, and final-test assessments, as well as with a survey to assess student perceptions. Student confidence with basic laboratory techniques and knowledge of bioinformatics tools were significantly increased upon completion of this hands-on exercise.

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.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

Modeling biochemical pathways in the gene ontology

DOE PAGES

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...

2016-09-01

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

Analysis of expressed sequence tags (ESTs) from cocoa (Theobroma cacao L) upon infection with Phytophthora megakarya.

PubMed

Naganeeswaran, Sudalaimuthu Asari; Subbian, Elain Apshara; Ramaswamy, Manimekalai

2012-01-01

Phytophthora megakarya, the causative agent of cacao black pod disease in West African countries causes an extensive loss of yield. In this study we have analyzed 4 libraries of ESTs derived from Phytophthora megakarya infected cocoa leaf and pod tissues. Totally 6379 redundant sequences were retrieved from ESTtik database and EST processing was performed using seqclean tool. Clustering and assembling using CAP3 generated 3333 non-redundant (907 contigs and 2426 singletons) sequences. The primary sequence analysis of 3333 non-redundant sequences showed that the GC percentage was 42.7 and the sequence length ranged from 101 - 2576 nucleotides. Further, functional analysis (Blast, Interproscan, Gene ontology and KEGG search) were executed and 1230 orthologous genes were annotated. Totally 272 enzymes corresponding to 114 metabolic pathways were identified. Functional annotation revealed that most of the sequences are related to molecular function, stress response and biological processes. The annotated enzymes are aldehyde dehydrogenase (E.C: 1.2.1.3), catalase (E.C: 1.11.1.6), acetyl-CoA C-acetyltransferase (E.C: 2.3.1.9), threonine ammonia-lyase (E.C: 4.3.1.19), acetolactate synthase (E.C: 2.2.1.6), O-methyltransferase (E.C: 2.1.1.68) which play an important role in amino acid biosynthesis and phenyl propanoid biosynthesis. All this information was stored in MySQL database management system to be used in future for reconstruction of biotic stress response pathway in cocoa.

Analysis of the whole mitochondrial genome: translation of the Ion Torrent Personal Genome Machine system to the diagnostic bench?

PubMed

Seneca, Sara; Vancampenhout, Kim; Van Coster, Rudy; Smet, Joél; Lissens, Willy; Vanlander, Arnaud; De Paepe, Boel; Jonckheere, An; Stouffs, Katrien; De Meirleir, Linda

2015-01-01

Next-generation sequencing (NGS), an innovative sequencing technology that enables the successful analysis of numerous gene sequences in a massive parallel sequencing approach, has revolutionized the field of molecular biology. Although NGS was introduced in a rather recent past, the technology has already demonstrated its potential and effectiveness in many research projects, and is now on the verge of being introduced into the diagnostic setting of routine laboratories to delineate the molecular basis of genetic disease in undiagnosed patient samples. We tested a benchtop device on retrospective genomic DNA (gDNA) samples of controls and patients with a clinical suspicion of a mitochondrial DNA disorder. This Ion Torrent Personal Genome Machine platform is a high-throughput sequencer with a fast turnaround time and reasonable running costs. We challenged the chemistry and technology with the analysis and processing of a mutational spectrum composed of samples with single-nucleotide substitutions, indels (insertions and deletions) and large single or multiple deletions, occasionally in heteroplasmy. The output data were compared with previously obtained conventional dideoxy sequencing results and the mitochondrial revised Cambridge Reference Sequence (rCRS). We were able to identify the majority of all nucleotide alterations, but three false-negative results were also encountered in the data set. At the same time, the poor performance of the PGM instrument in regions associated with homopolymeric stretches generated many false-positive miscalls demanding additional manual curation of the data.

Biomolecular Analysis Capability for Cellular and Omics Research on the International Space Station

NASA Technical Reports Server (NTRS)

Guinart-Ramirez, Y.; Cooley, V. M.; Love, J. E.

2016-01-01

International Space Station (ISS) assembly complete ushered a new era focused on utilization of this state-of-the-art orbiting laboratory to advance science and technology research in a wide array of disciplines, with benefits to Earth and space exploration. ISS enabling capability for research in cellular and molecular biology includes equipment for in situ, on-orbit analysis of biomolecules. Applications of this growing capability range from biomedicine and biotechnology to the emerging field of Omics. For example, Biomolecule Sequencer is a space-based miniature DNA sequencer that provides nucleotide sequence data for entire samples, which may be used for purposes such as microorganism identification and astrobiology. It complements the use of WetLab-2 SmartCycler"TradeMark", which extracts RNA and provides real-time quantitative gene expression data analysis from biospecimens sampled or cultured onboard the ISS, for downlink to ground investigators, with applications ranging from clinical tissue evaluation to multigenerational assessment of organismal alterations. And the Genes in Space-1 investigation, aimed at examining epigenetic changes, employs polymerase chain reaction to detect immune system alterations. In addition, an increasing assortment of tools to visualize the subcellular distribution of tagged macromolecules is becoming available onboard the ISS. For instance, the NASA LMM (Light Microscopy Module) is a flexible light microscopy imaging facility that enables imaging of physical and biological microscopic phenomena in microgravity. Another light microscopy system modified for use in space to image life sciences payloads is initially used by the Heart Cells investigation ("Effects of Microgravity on Stem Cell-Derived Cardiomyocytes for Human Cardiovascular Disease Modeling and Drug Discovery"). Also, the JAXA Microscope system can perform remotely controllable light, phase-contrast, and fluorescent observations. And upcoming confocal microscopy capability will allow for optical sectioning of biological tissues to determine microanatomical localization of biomarkers. Furthermore, NASA's geneLAB effort addresses integration of genomic, epigenomic, transcriptomic, proteomic and metabolomic datasets, by applying an innovative open source science platform for multi-investigator high throughput utilization of the ISS. In sum, the expanding ISS capability for analysis of biomolecules is enabling innovative research in a broad spectrum of areas such as cellular and molecular biology, biotechnology, tissue engineering, biomedicine, and Omics, providing manifold benefits for humanity.

Molecular Cloning and Analysis of a DNA Repetitive Element from the Mouse Genome

ERIC Educational Resources Information Center

Geisinger, Adriana; Cossio, Gabriela; Wettstein, Rodolfo

2006-01-01

We report the development of a 3-week laboratory activity for an undergraduate molecular biology course. This activity introduces students to the practice of basic molecular techniques such as restriction enzyme digestion, agarose gel electrophoresis, cloning, plasmid DNA purification, Southern blotting, and sequencing. Students learn how to carry…

Comparative genomics of plant-associated Pseudomonas spp.: Insights into diversity and inheritance of traits involved in multitrophic interactions

USDA-ARS?s Scientific Manuscript database

We provide here a comparative genome analysis of the Pseudomonas fluorescens group, including seven new genomic sequences for plant-associated strains. These strains exhibit a diverse spectrum of traits involved in biological control and other multitrophic interactions with plants, microbes, and ins...

Top dogs: wolf domestication and wealth.

PubMed

Driscoll, Carlos A; Macdonald, David W

2010-01-01

A phylogeographic analysis of gene sequences important in determining body size in dogs, recently published in BMC Biology, traces the appearance of small body size to the Neolithic Middle East. This finding strengthens the association of this event with the development of sedentary societies, and perhaps even has implications for the inception of human social inequality.

Classification, genetic variation, and biological activity of nucleopolyhedrovirus samples from larvae of the heliothine pests heliothis virescens, helicoverpa zea, and helicoverpa armigera

USDA-ARS?s Scientific Manuscript database

A PCR-based method was used to classify 109 isolates of nucleopolyhedrovirus (NPV; Baculoviridae: Alphabaculovirus) collected worldwide from larvae of Heliothis virescens, Helicoverpa zea, and Helicoverpa armigera. Partial nucleotide sequencing and phylogenetic analysis of three highly conserved ge...

Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

PubMed

Higgins, Sean A; Savage, David F

2018-01-09

A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

Direct Detection and Sequencing of Damaged DNA Bases

PubMed Central

2011-01-01

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications. PMID:22185597

Direct detection and sequencing of damaged DNA bases.

PubMed

Clark, Tyson A; Spittle, Kristi E; Turner, Stephen W; Korlach, Jonas

2011-12-20

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications.

Novel microbial diversity retrieved by autonomous robotic exploration of the world's deepest vertical phreatic sinkhole.

PubMed

Sahl, Jason W; Fairfield, Nathaniel; Harris, J Kirk; Wettergreen, David; Stone, William C; Spear, John R

2010-03-01

The deep phreatic thermal explorer (DEPTHX) is an autonomous underwater vehicle designed to navigate an unexplored environment, generate high-resolution three-dimensional (3-D) maps, collect biological samples based on an autonomous sampling decision, and return to its origin. In the spring of 2007, DEPTHX was deployed in Zacatón, a deep (approximately 318 m), limestone, phreatic sinkhole (cenote) in northeastern Mexico. As DEPTHX descended, it generated a 3-D map based on the processing of range data from 54 onboard sonars. The vehicle collected water column samples and wall biomat samples throughout the depth profile of the cenote. Post-expedition sample analysis via comparative analysis of 16S rRNA gene sequences revealed a wealth of microbial diversity. Traditional Sanger gene sequencing combined with a barcoded-amplicon pyrosequencing approach revealed novel, phylum-level lineages from the domains Bacteria and Archaea; in addition, several novel subphylum lineages were also identified. Overall, DEPTHX successfully navigated and mapped Zacatón, and collected biological samples based on an autonomous decision, which revealed novel microbial diversity in a previously unexplored environment.

StrBioLib: a Java library for development of custom computationalstructural biology applications

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

Chandonia, John-Marc

2007-05-14

Summary: StrBioLib is a library of Java classes useful fordeveloping software for computational structural biology research.StrBioLib contains classes to represent and manipulate proteinstructures, biopolymer sequences, sets of biopolymer sequences, andalignments between biopolymers based on either sequence or structure.Interfaces are provided to interact with commonly used bioinformaticsapplications, including (PSI)-BLAST, MODELLER, MUSCLE, and Primer3, andtools are provided to read and write many file formats used to representbioinformatic data. The library includes a general-purpose neural networkobject with multiple training algorithms, the Hooke and Jeeves nonlinearoptimization algorithm, and tools for efficient C-style string parsingand formatting. StrBioLib is the basis for the Pred2ary secondarystructure predictionmore » program, is used to build the ASTRAL compendium forsequence and structure analysis, and has been extensively tested throughuse in many smaller projects. Examples and documentation are available atthe site below.Availability: StrBioLib may be obtained under the terms ofthe GNU LGPL license from http://strbio.sourceforge.net/Contact:JMChandonia@lbl.gov« less

KinView: A visual comparative sequence analysis tool for integrated kinome research

PubMed Central

McSkimming, Daniel Ian; Dastgheib, Shima; Baffi, Timothy R.; Byrne, Dominic P.; Ferries, Samantha; Scott, Steven Thomas; Newton, Alexandra C.; Eyers, Claire E.; Kochut, Krzysztof J.; Eyers, Patrick A.

2017-01-01

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats. PMID:27731453

A comparison of complete mitochondrial genomes of silver carp hypophthalmichthys molitrix and bighead carp hypophthalmichthys nobilis: Implications for their taxonomic relationship and phylogeny

USGS Publications Warehouse

Li, S.-F.; Xu, J.-W.; Yang, Q.-L.; Wang, C.H.; Chen, Q.; Chapman, D.C.; Lu, G.

2009-01-01

Based upon morphological characters, Silver carp Hypophthalmichthys molitrix and bighead carp Hypophthalmichthys nobilis (or Aristichthys nobilis) have been classified into either the same genus or two distinct genera. Consequently, the taxonomic relationship of the two species at the generic level remains equivocal. This issue is addressed by sequencing complete mitochondrial genomes of H. molitrix and H. nobilis, comparing their mitogenome organization, structure and sequence similarity, and conducting a comprehensive phylogenetic analysis of cyprinid species. As with other cyprinid fishes, the mitogenomes of the two species were structurally conserved, containing 37 genes including 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA (tRNAs) genes and a putative control region (D-loop). Sequence similarity between the two mitogenomes varied in different genes or regions, being highest in the tRNA genes (98??8%), lowest in the control region (89??4%) and intermediate in the protein-coding genes (94??2%). Analyses of the sequence comparison and phylogeny using concatenated protein sequences support the view that the two species belong to the genus Hypophthalmichthys. Further studies using nuclear markers and involving more closely related species, and the systematic combination of traditional biology and molecular biology are needed in order to confirm this conclusion. ?? 2009 The Fisheries Society of the British Isles.

From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems.

PubMed

Garza, Daniel R; Dutilh, Bas E

2015-11-01

Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach

PubMed Central

Meyer, Pablo; Siwo, Geoffrey; Zeevi, Danny; Sharon, Eilon; Norel, Raquel; Segal, Eran; Stolovitzky, Gustavo; Siwo, Geoffrey; Rider, Andrew K.; Tan, Asako; Pinapati, Richard S.; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael T.; Tung, Yi-An; Chen, Yong-Syuan; Chen, Mei-Ju May; Chen, Chien-Yu; Knight, Jason M.; Sahraeian, Sayed Mohammad Ebrahim; Esfahani, Mohammad Shahrokh; Dreos, Rene; Bucher, Philipp; Maier, Ezekiel; Saeys, Yvan; Szczurek, Ewa; Myšičková, Alena; Vingron, Martin; Klein, Holger; Kiełbasa, Szymon M.; Knisley, Jeff; Bonnell, Jeff; Knisley, Debra; Kursa, Miron B.; Rudnicki, Witold R.; Bhattacharjee, Madhuchhanda; Sillanpää, Mikko J.; Yeung, James; Meysman, Pieter; Rodríguez, Aminael Sánchez; Engelen, Kristof; Marchal, Kathleen; Huang, Yezhou; Mordelet, Fantine; Hartemink, Alexander; Pinello, Luca; Yuan, Guo-Cheng

2013-01-01

The Gene Promoter Expression Prediction challenge consisted of predicting gene expression from promoter sequences in a previously unknown experimentally generated data set. The challenge was presented to the community in the framework of the sixth Dialogue for Reverse Engineering Assessments and Methods (DREAM6), a community effort to evaluate the status of systems biology modeling methodologies. Nucleotide-specific promoter activity was obtained by measuring fluorescence from promoter sequences fused upstream of a gene for yellow fluorescence protein and inserted in the same genomic site of yeast Saccharomyces cerevisiae. Twenty-one teams submitted results predicting the expression levels of 53 different promoters from yeast ribosomal protein genes. Analysis of participant predictions shows that accurate values for low-expressed and mutated promoters were difficult to obtain, although in the latter case, only when the mutation induced a large change in promoter activity compared to the wild-type sequence. As in previous DREAM challenges, we found that aggregation of participant predictions provided robust results, but did not fare better than the three best algorithms. Finally, this study not only provides a benchmark for the assessment of methods predicting activity of a specific set of promoters from their sequence, but it also shows that the top performing algorithm, which used machine-learning approaches, can be improved by the addition of biological features such as transcription factor binding sites. PMID:23950146

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing.

PubMed

Zackay, Arie; Steinhoff, Christine

2010-12-15

Exploration of DNA methylation and its impact on various regulatory mechanisms has become a very active field of research. Simultaneously there is an arising need for tools to process and analyse the data together with statistical investigation and visualisation. MethVisual is a new application that enables exploratory analysis and intuitive visualization of DNA methylation data as is typically generated by bisulfite sequencing. The package allows the import of DNA methylation sequences, aligns them and performs quality control comparison. It comprises basic analysis steps as lollipop visualization, co-occurrence display of methylation of neighbouring and distant CpG sites, summary statistics on methylation status, clustering and correspondence analysis. The package has been developed for methylation data but can be also used for other data types for which binary coding can be inferred. The application of the package, as well as a comparison to existing DNA methylation analysis tools and its workflow based on two datasets is presented in this paper. The R package MethVisual offers various analysis procedures for data that can be binarized, in particular for bisulfite sequenced methylation data. R/Bioconductor has become one of the most important environments for statistical analysis of various types of biological and medical data. Therefore, any data analysis within R that allows the integration of various data types as provided from different technological platforms is convenient. It is the first and so far the only specific package for DNA methylation analysis, in particular for bisulfite sequenced data available in R/Bioconductor enviroment. The package is available for free at http://methvisual.molgen.mpg.de/ and from the Bioconductor Consortium http://www.bioconductor.org.

MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing

PubMed Central

2010-01-01

Background Exploration of DNA methylation and its impact on various regulatory mechanisms has become a very active field of research. Simultaneously there is an arising need for tools to process and analyse the data together with statistical investigation and visualisation. Findings MethVisual is a new application that enables exploratory analysis and intuitive visualization of DNA methylation data as is typically generated by bisulfite sequencing. The package allows the import of DNA methylation sequences, aligns them and performs quality control comparison. It comprises basic analysis steps as lollipop visualization, co-occurrence display of methylation of neighbouring and distant CpG sites, summary statistics on methylation status, clustering and correspondence analysis. The package has been developed for methylation data but can be also used for other data types for which binary coding can be inferred. The application of the package, as well as a comparison to existing DNA methylation analysis tools and its workflow based on two datasets is presented in this paper. Conclusions The R package MethVisual offers various analysis procedures for data that can be binarized, in particular for bisulfite sequenced methylation data. R/Bioconductor has become one of the most important environments for statistical analysis of various types of biological and medical data. Therefore, any data analysis within R that allows the integration of various data types as provided from different technological platforms is convenient. It is the first and so far the only specific package for DNA methylation analysis, in particular for bisulfite sequenced data available in R/Bioconductor enviroment. The package is available for free at http://methvisual.molgen.mpg.de/ and from the Bioconductor Consortium http://www.bioconductor.org. PMID:21159174

Design of a tobacco exon array with application to investigate the differential cadmium accumulation property in two tobacco varieties

PubMed Central

2012-01-01

Background For decades the tobacco plant has served as a model organism in plant biology to answer fundamental biological questions in the areas of plant development, physiology, and genetics. Due to the lack of sufficient coverage of genomic sequences, however, none of the expressed sequence tag (EST)-based chips developed to date cover gene expression from the whole genome. The availability of Tobacco Genome Initiative (TGI) sequences provides a useful resource to build a whole genome exon array, even if the assembled sequences are highly fragmented. Here, the design of a Tobacco Exon Array is reported and an application to improve the understanding of genes regulated by cadmium (Cd) in tobacco is described. Results From the analysis and annotation of the 1,271,256 Nicotiana tabacum fasta and quality files from methyl filtered genomic survey sequences (GSS) obtained from the TGI and ~56,000 ESTs available in public databases, an exon array with 272,342 probesets was designed (four probes per exon) and tested on two selected tobacco varieties. Two tobacco varieties out of 45 accumulating low and high cadmium in leaf were identified based on the GGE biplot analysis, which is analysis of the genotype main effect (G) plus analysis of the genotype by environment interaction (GE) of eight field trials (four fields over two years) showing reproducibility across the trials. The selected varieties were grown under greenhouse conditions in two different soils and subjected to exon array analyses using root and leaf tissues to understand the genetic make-up of the Cd accumulation. Conclusions An Affymetrix Exon Array was developed to cover a large (~90%) proportion of the tobacco gene space. The Tobacco Exon Array will be available for research use through Affymetrix array catalogue. As a proof of the exon array usability, we have demonstrated that the Tobacco Exon Array is a valuable tool for studying Cd accumulation in tobacco leaves. Data from field and greenhouse experiments supported by gene expression studies strongly suggested that the difference in leaf Cd accumulation between the two specific tobacco cultivars is dependent solely on genetic factors and genetic variability rather than on the environment. PMID:23190529

Graph mining for next generation sequencing: leveraging the assembly graph for biological insights.

PubMed

Warnke-Sommer, Julia; Ali, Hesham

2016-05-06

The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are merged into longer sequences or contigs. The assembly graph is information rich and capable of capturing the genomic architecture of an input read data set. We have developed a novel hybrid graph in which nodes represent sequence regions at different levels of granularity. This model, utilized in the assembly and analysis pipeline Focus, presents a concise yet feature rich view of a given input data set, allowing for the extraction of biologically relevant graph structures for graph mining purposes. Focus was used to create hybrid graphs to model metagenomics data sets obtained from the gut microbiomes of five individuals with Crohn's disease and eight healthy individuals. Repetitive and mobile genetic elements are found to be associated with hybrid graph structure. Using graph mining techniques, a comparative study of the Crohn's disease and healthy data sets was conducted with focus on antibiotics resistance genes associated with transposase genes. Results demonstrated significant differences in the phylogenetic distribution of categories of antibiotics resistance genes in the healthy and diseased patients. Focus was also evaluated as a pure assembly tool and produced excellent results when compared against the Meta-velvet, Omega, and UD-IDBA assemblers. Mining the hybrid graph can reveal biological phenomena captured by its structure. We demonstrate the advantages of considering assembly graphs as data-mining support in addition to their role as frameworks for assembly.

The Importance of Biological Databases in Biological Discovery.

PubMed

Baxevanis, Andreas D; Bateman, Alex

2015-06-19

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. Copyright © 2015 John Wiley & Sons, Inc.

The repetitive landscape of the chicken genome.

PubMed

Wicker, Thomas; Robertson, Jon S; Schulze, Stefan R; Feltus, F Alex; Magrini, Vincent; Morrison, Jason A; Mardis, Elaine R; Wilson, Richard K; Peterson, Daniel G; Paterson, Andrew H; Ivarie, Robert

2005-01-01

Cot-based cloning and sequencing (CBCS) is a powerful tool for isolating and characterizing the various repetitive components of any genome, combining the established principles of DNA reassociation kinetics with high-throughput sequencing. CBCS was used to generate sequence libraries representing the high, middle, and low-copy fractions of the chicken genome. Sequencing high-copy DNA of chicken to about 2.7 x coverage of its estimated sequence complexity led to the initial identification of several new repeat families, which were then used for a survey of the newly released first draft of the complete chicken genome. The analysis provided insight into the diversity and biology of known repeat structures such as CR1 and CNM, for which only limited sequence data had previously been available. Cot sequence data also resulted in the identification of four novel repeats (Birddawg, Hitchcock, Kronos, and Soprano), two new subfamilies of CR1 repeats, and many elements absent from the chicken genome assembly. Multiple autonomous elements were found for a novel Mariner-like transposon, Galluhop, in addition to nonautonomous deletion derivatives. Phylogenetic analysis of the high-copy repeats CR1, Galluhop, and Birddawg provided insight into two distinct genome dispersion strategies. This study also exemplifies the power of the CBCS method to create representative databases for the repetitive fractions of genomes for which only limited sequence data is available.

The repetitive landscape of the chicken genome

PubMed Central

Wicker, Thomas; Robertson, Jon S.; Schulze, Stefan R.; Feltus, F. Alex; Magrini, Vincent; Morrison, Jason A.; Mardis, Elaine R.; Wilson, Richard K.; Peterson, Daniel G.; Paterson, Andrew H.; Ivarie, Robert

2005-01-01

Cot-based cloning and sequencing (CBCS) is a powerful tool for isolating and characterizing the various repetitive components of any genome, combining the established principles of DNA reassociation kinetics with high-throughput sequencing. CBCS was used to generate sequence libraries representing the high, middle, and low-copy fractions of the chicken genome. Sequencing high-copy DNA of chicken to about 2.7× coverage of its estimated sequence complexity led to the initial identification of several new repeat families, which were then used for a survey of the newly released first draft of the complete chicken genome. The analysis provided insight into the diversity and biology of known repeat structures such as CR1 and CNM, for which only limited sequence data had previously been available. Cot sequence data also resulted in the identification of four novel repeats (Birddawg, Hitchcock, Kronos, and Soprano), two new subfamilies of CR1 repeats, and many elements absent from the chicken genome assembly. Multiple autonomous elements were found for a novel Mariner-like transposon, Galluhop, in addition to nonautonomous deletion derivatives. Phylogenetic analysis of the high-copy repeats CR1, Galluhop, and Birddawg provided insight into two distinct genome dispersion strategies. This study also exemplifies the power of the CBCS method to create representative databases for the repetitive fractions of genomes for which only limited sequence data is available. PMID:15256510

ASGARD: an open-access database of annotated transcriptomes for emerging model arthropod species.

PubMed

Zeng, Victor; Extavour, Cassandra G

2012-01-01

The increased throughput and decreased cost of next-generation sequencing (NGS) have shifted the bottleneck genomic research from sequencing to annotation, analysis and accessibility. This is particularly challenging for research communities working on organisms that lack the basic infrastructure of a sequenced genome, or an efficient way to utilize whatever sequence data may be available. Here we present a new database, the Assembled Searchable Giant Arthropod Read Database (ASGARD). This database is a repository and search engine for transcriptomic data from arthropods that are of high interest to multiple research communities but currently lack sequenced genomes. We demonstrate the functionality and utility of ASGARD using de novo assembled transcriptomes from the milkweed bug Oncopeltus fasciatus, the cricket Gryllus bimaculatus and the amphipod crustacean Parhyale hawaiensis. We have annotated these transcriptomes to assign putative orthology, coding region determination, protein domain identification and Gene Ontology (GO) term annotation to all possible assembly products. ASGARD allows users to search all assemblies by orthology annotation, GO term annotation or Basic Local Alignment Search Tool. User-friendly features of ASGARD include search term auto-completion suggestions based on database content, the ability to download assembly product sequences in FASTA format, direct links to NCBI data for predicted orthologs and graphical representation of the location of protein domains and matches to similar sequences from the NCBI non-redundant database. ASGARD will be a useful repository for transcriptome data from future NGS studies on these and other emerging model arthropods, regardless of sequencing platform, assembly or annotation status. This database thus provides easy, one-stop access to multi-species annotated transcriptome information. We anticipate that this database will be useful for members of multiple research communities, including developmental biology, physiology, evolutionary biology, ecology, comparative genomics and phylogenomics. Database URL: asgard.rc.fas.harvard.edu.

Sequencing and characterizing the genome of Estrella lausannensis as an undergraduate project: training students and biological insights.

PubMed

Bertelli, Claire; Aeby, Sébastien; Chassot, Bérénice; Clulow, James; Hilfiker, Olivier; Rappo, Samuel; Ritzmann, Sébastien; Schumacher, Paolo; Terrettaz, Céline; Benaglio, Paola; Falquet, Laurent; Farinelli, Laurent; Gharib, Walid H; Goesmann, Alexander; Harshman, Keith; Linke, Burkhard; Miyazaki, Ryo; Rivolta, Carlo; Robinson-Rechavi, Marc; van der Meer, Jan Roelof; Greub, Gilbert

2015-01-01

With the widespread availability of high-throughput sequencing technologies, sequencing projects have become pervasive in the molecular life sciences. The huge bulk of data generated daily must be analyzed further by biologists with skills in bioinformatics and by "embedded bioinformaticians," i.e., bioinformaticians integrated in wet lab research groups. Thus, students interested in molecular life sciences must be trained in the main steps of genomics: sequencing, assembly, annotation and analysis. To reach that goal, a practical course has been set up for master students at the University of Lausanne: the "Sequence a genome" class. At the beginning of the academic year, a few bacterial species whose genome is unknown are provided to the students, who sequence and assemble the genome(s) and perform manual annotation. Here, we report the progress of the first class from September 2010 to June 2011 and the results obtained by seven master students who specifically assembled and annotated the genome of Estrella lausannensis, an obligate intracellular bacterium related to Chlamydia. The draft genome of Estrella is composed of 29 scaffolds encompassing 2,819,825 bp that encode for 2233 putative proteins. Estrella also possesses a 9136 bp plasmid that encodes for 14 genes, among which we found an integrase and a toxin/antitoxin module. Like all other members of the Chlamydiales order, Estrella possesses a highly conserved type III secretion system, considered as a key virulence factor. The annotation of the Estrella genome also allowed the characterization of the metabolic abilities of this strictly intracellular bacterium. Altogether, the students provided the scientific community with the Estrella genome sequence and a preliminary understanding of the biology of this recently-discovered bacterial genus, while learning to use cutting-edge technologies for sequencing and to perform bioinformatics analyses.

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

DROMPA: easy-to-handle peak calling and visualization software for the computational analysis and validation of ChIP-seq data.

PubMed

Nakato, Ryuichiro; Itoh, Tahehiko; Shirahige, Katsuhiko

2013-07-01

Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) can identify genomic regions that bind proteins involved in various chromosomal functions. Although the development of next-generation sequencers offers the technology needed to identify these protein-binding sites, the analysis can be computationally challenging because sequencing data sometimes consist of >100 million reads/sample. Herein, we describe a cost-effective and time-efficient protocol that is generally applicable to ChIP-seq analysis; this protocol uses a novel peak-calling program termed DROMPA to identify peaks and an additional program, parse2wig, to preprocess read-map files. This two-step procedure drastically reduces computational time and memory requirements compared with other programs. DROMPA enables the identification of protein localization sites in repetitive sequences and efficiently identifies both broad and sharp protein localization peaks. Specifically, DROMPA outputs a protein-binding profile map in pdf or png format, which can be easily manipulated by users who have a limited background in bioinformatics. © 2013 The Authors Genes to Cells © 2013 by the Molecular Biology Society of Japan and Wiley Publishing Asia Pty Ltd.

'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

PubMed

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-04-12

Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

'PACLIMS': A component LIM system for high-throughput functional genomic analysis

PubMed Central

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-01-01

Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors. PMID:15826298

Protein location prediction using atomic composition and global features of the amino acid sequence

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

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

Identification of Novel Growth Regulators in Plant Populations Expressing Random Peptides1[OPEN

PubMed Central

Bao, Zhilong; Clancy, Maureen A.

2017-01-01

The use of chemical genomics approaches allows the identification of small molecules that integrate into biological systems, thereby changing discrete processes that influence growth, development, or metabolism. Libraries of chemicals are applied to living systems, and changes in phenotype are observed, potentially leading to the identification of new growth regulators. This work describes an approach that is the nexus of chemical genomics and synthetic biology. Here, each plant in an extensive population synthesizes a unique small peptide arising from a transgene composed of a randomized nucleic acid sequence core flanked by translational start, stop, and cysteine-encoding (for disulfide cyclization) sequences. Ten and 16 amino acid sequences, bearing a core of six and 12 random amino acids, have been synthesized in Arabidopsis (Arabidopsis thaliana) plants. Populations were screened for phenotypes from the seedling stage through senescence. Dozens of phenotypes were observed in over 2,000 plants analyzed. Ten conspicuous phenotypes were verified through separate transformation and analysis of multiple independent lines. The results indicate that these populations contain sequences that often influence discrete aspects of plant biology. Novel peptides that affect photosynthesis, flowering, and red light response are described. The challenge now is to identify the mechanistic integrations of these peptides into biochemical processes. These populations serve as a new tool to identify small molecules that modulate discrete plant functions that could be produced later in transgenic plants or potentially applied exogenously to impart their effects. These findings could usher in a new generation of agricultural growth regulators, herbicides, or defense compounds. PMID:28807931

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

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

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

Transcriptome analysis of Cymbidium sinense and its application to the identification of genes associated with floral development

PubMed Central

2013-01-01

Background Cymbidium sinense belongs to the Orchidaceae, which is one of the most abundant angiosperm families. C. sinense, a high-grade traditional potted flower, is most prevalent in China and some Southeast Asian countries. The control of flowering time is a major bottleneck in the industrialized development of C. sinense. Little is known about the mechanisms responsible for floral development in this orchid. Moreover, genome references for entire transcriptome sequences do not currently exist for C. sinense. Thus, transcriptome and expression profiling data for this species are needed as an important resource to identify genes and to better understand the biological mechanisms of floral development in C. sinense. Results In this study, de novo transcriptome assembly and gene expression analysis using Illumina sequencing technology were performed. Transcriptome analysis assembles gene-related information related to vegetative and reproductive growth of C. sinense. Illumina sequencing generated 54,248,006 high quality reads that were assembled into 83,580 unigenes with an average sequence length of 612 base pairs, including 13,315 clusters and 70,265 singletons. A total of 41,687 (49.88%) unique sequences were annotated, 23,092 of which were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene Ontology (GO) analysis of the annotated unigenes revealed that the majority of sequenced genes were associated with metabolic and cellular processes, cell and cell parts, catalytic activity and binding. Furthermore, 120 flowering-associated unigenes, 73 MADS-box unigenes and 28 CONSTANS-LIKE (COL) unigenes were identified from our collection. In addition, three digital gene expression (DGE) libraries were constructed for the vegetative phase (VP), floral differentiation phase (FDP) and reproductive phase (RP). The specific expression of many genes in the three development phases was also identified. 32 genes among three sub-libraries with high differential expression were selected as candidates connected with flower development. Conclusion RNA-seq and DGE profiling data provided comprehensive gene expression information at the transcriptional level that could facilitate our understanding of the molecular mechanisms of floral development at three development phases of C. sinense. This data could be used as an important resource for investigating the genetics of the flowering pathway and various biological mechanisms in this orchid. PMID:23617896

Transcriptome analysis of Cymbidium sinense and its application to the identification of genes associated with floral development.

PubMed

Zhang, Jianxia; Wu, Kunlin; Zeng, Songjun; Teixeira da Silva, Jaime A; Zhao, Xiaolan; Tian, Chang-En; Xia, Haoqiang; Duan, Jun

2013-04-24

Cymbidium sinense belongs to the Orchidaceae, which is one of the most abundant angiosperm families. C. sinense, a high-grade traditional potted flower, is most prevalent in China and some Southeast Asian countries. The control of flowering time is a major bottleneck in the industrialized development of C. sinense. Little is known about the mechanisms responsible for floral development in this orchid. Moreover, genome references for entire transcriptome sequences do not currently exist for C. sinense. Thus, transcriptome and expression profiling data for this species are needed as an important resource to identify genes and to better understand the biological mechanisms of floral development in C. sinense. In this study, de novo transcriptome assembly and gene expression analysis using Illumina sequencing technology were performed. Transcriptome analysis assembles gene-related information related to vegetative and reproductive growth of C. sinense. Illumina sequencing generated 54,248,006 high quality reads that were assembled into 83,580 unigenes with an average sequence length of 612 base pairs, including 13,315 clusters and 70,265 singletons. A total of 41,687 (49.88%) unique sequences were annotated, 23,092 of which were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene Ontology (GO) analysis of the annotated unigenes revealed that the majority of sequenced genes were associated with metabolic and cellular processes, cell and cell parts, catalytic activity and binding. Furthermore, 120 flowering-associated unigenes, 73 MADS-box unigenes and 28 CONSTANS-LIKE (COL) unigenes were identified from our collection. In addition, three digital gene expression (DGE) libraries were constructed for the vegetative phase (VP), floral differentiation phase (FDP) and reproductive phase (RP). The specific expression of many genes in the three development phases was also identified. 32 genes among three sub-libraries with high differential expression were selected as candidates connected with flower development. RNA-seq and DGE profiling data provided comprehensive gene expression information at the transcriptional level that could facilitate our understanding of the molecular mechanisms of floral development at three development phases of C. sinense. This data could be used as an important resource for investigating the genetics of the flowering pathway and various biological mechanisms in this orchid.

Transformation of a Traditional, Freshman Biology, Three-Semester Sequence, to a Two-Semester, Integrated Thematically Organized, and Team-Taught Course

ERIC Educational Resources Information Center

Soto, Julio G.; Everhart, Jerry

2016-01-01

Biology faculty at San José State University developed, piloted, implemented, and assessed a freshmen course sequence based on the macro-to micro-teaching approach that was team-taught, and organized around unifying themes. Content learning assessment drove the conceptual framework of our course sequence. Content student learning increased…

The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation.

PubMed

Mavromatis, Konstantinos; Land, Miriam L; Brettin, Thomas S; Quest, Daniel J; Copeland, Alex; Clum, Alicia; Goodwin, Lynne; Woyke, Tanja; Lapidus, Alla; Klenk, Hans Peter; Cottingham, Robert W; Kyrpides, Nikos C

2012-01-01

The emergence of next generation sequencing (NGS) has provided the means for rapid and high throughput sequencing and data generation at low cost, while concomitantly creating a new set of challenges. The number of available assembled microbial genomes continues to grow rapidly and their quality reflects the quality of the sequencing technology used, but also of the analysis software employed for assembly and annotation. In this work, we have explored the quality of the microbial draft genomes across various sequencing technologies. We have compared the draft and finished assemblies of 133 microbial genomes sequenced at the Department of Energy-Joint Genome Institute and finished at the Los Alamos National Laboratory using a variety of combinations of sequencing technologies, reflecting the transition of the institute from Sanger-based sequencing platforms to NGS platforms. The quality of the public assemblies and of the associated gene annotations was evaluated using various metrics. Results obtained with the different sequencing technologies, as well as their effects on downstream processes, were analyzed. Our results demonstrate that the Illumina HiSeq 2000 sequencing system, the primary sequencing technology currently used for de novo genome sequencing and assembly at JGI, has various advantages in terms of total sequence throughput and cost, but it also introduces challenges for the downstream analyses. In all cases assembly results although on average are of high quality, need to be viewed critically and consider sources of errors in them prior to analysis. These data follow the evolution of microbial sequencing and downstream processing at the JGI from draft genome sequences with large gaps corresponding to missing genes of significant biological role to assemblies with multiple small gaps (Illumina) and finally to assemblies that generate almost complete genomes (Illumina+PacBio).

Big Data, Big Opportunities, and Big Challenges.

PubMed

Frelinger, Jeffrey A

2015-11-01

High-throughput assays have begun to revolutionize modern biology and medicine. The advent of cheap next-generation sequencing (NGS) has made it possible to interrogate cells and human populations as never before. Although this has allowed us to investigate the genetics, gene expression, and impacts of the microbiome, there remain both practical and conceptual challenges. These include data handling, storage, and statistical analysis, as well as an inherent problem of the analysis of heterogeneous cell populations.

Quantitative Analysis of Repertoire Scale Immunoglobulin properties in Vaccine Induced B cell Responses

DTIC Science & Technology

Immunosequencing now readily generates 103105 sequences per sample ; however, statistical analysis of these repertoires is challenging because of the high genetic...diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative ...repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance.

Reconstructing evolutionary trees in parallel for massive sequences.

PubMed

Zou, Quan; Wan, Shixiang; Zeng, Xiangxiang; Ma, Zhanshan Sam

2017-12-14

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel. HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis. In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

Next Generation Sequencing Technologies: The Doorway to the Unexplored Genomics of Non-Model Plants

PubMed Central

Unamba, Chibuikem I. N.; Nag, Akshay; Sharma, Ram K.

2015-01-01

Non-model plants i.e., the species which have one or all of the characters such as long life cycle, difficulty to grow in the laboratory or poor fecundity, have been schemed out of sequencing projects earlier, due to high running cost of Sanger sequencing. Consequently, the information about their genomics and key biological processes are inadequate. However, the advent of fast and cost effective next generation sequencing (NGS) platforms in the recent past has enabled the unearthing of certain characteristic gene structures unique to these species. It has also aided in gaining insight about mechanisms underlying processes of gene expression and secondary metabolism as well as facilitated development of genomic resources for diversity characterization, evolutionary analysis and marker assisted breeding even without prior availability of genomic sequence information. In this review we explore how different Next Gen Sequencing platforms, as well as recent advances in NGS based high throughput genotyping technologies are rewarding efforts on de-novo whole genome/transcriptome sequencing, development of genome wide sequence based markers resources for improvement of non-model crops that are less costly than phenotyping. PMID:26734016

Nanoscale Bio-engineering Solutions for Space Exploration: The Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Cozmuta, Ioana

2004-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation, with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes.

Novel Strategy for Discrimination of Transcription Factor Binding Motifs Employing Mathematical Neural Network

NASA Astrophysics Data System (ADS)

Sugimoto, Asuka; Sumi, Takuya; Kang, Jiyoung; Tateno, Masaru

2017-07-01

Recognition in biological macromolecular systems, such as DNA-protein recognition, is one of the most crucial problems to solve toward understanding the fundamental mechanisms of various biological processes. Since specific base sequences of genome DNA are discriminated by proteins, such as transcription factors (TFs), finding TF binding motifs (TFBMs) in whole genome DNA sequences is currently a central issue in interdisciplinary biophysical and information sciences. In the present study, a novel strategy to create a discriminant function for discrimination of TFBMs by constituting mathematical neural networks (NNs) is proposed, together with a method to determine the boundary of signals (TFBMs) and noise in the NN-score (output) space. This analysis also leads to the mathematical limitation of discrimination in the recognition of features representing TFBMs, in an information geometrical manifold. Thus, the present strategy enables the identification of the whole space of TFBMs, right up to the noise boundary.

(Mechanisms of inhibition of viral replication in plants)

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

Not Available

1991-01-01

During the last year we have made a number of important observations in the fields of virology and plant molecular biology. By directly sequencing Tomato Mosaic Virus (ToMV) movement genes, previously undetected sequence alterations common to specific viral strains were found. The difficulty in regenerating transgenic tomato plants containing the Tm-2 gene was overcome. Tobacco plants transformed with Cucumber Mosaic Virus (CMV) are being characterized. Analysis of transgenic tobacco plants expressing CMV coat protein have shown no correlation between coat protein expression and level of resistance. Specific amino acid changes have been found to correlate with CMV resistance breaking andmore » degree of pathogenicity. Satellite RNAs are shown to be too unstable for use as a biological control agent. The aphid transmission domain CMV has been localized to one (or more) of three amino acids; constructs have been made to determine the exact amino acids involved. 15 refs.« less

Nanoscale Bioengineering Solutions for Space Exploration the Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Ioana, Cozmuta; Viktor, Stoic

2005-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation. with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes. http://phenomrph.arc.nasa.gov/index.php

A De-Novo Genome Analysis Pipeline (DeNoGAP) for large-scale comparative prokaryotic genomics studies.

PubMed

Thakur, Shalabh; Guttman, David S

2016-06-30

Comparative analysis of whole genome sequence data from closely related prokaryotic species or strains is becoming an increasingly important and accessible approach for addressing both fundamental and applied biological questions. While there are number of excellent tools developed for performing this task, most scale poorly when faced with hundreds of genome sequences, and many require extensive manual curation. We have developed a de-novo genome analysis pipeline (DeNoGAP) for the automated, iterative and high-throughput analysis of data from comparative genomics projects involving hundreds of whole genome sequences. The pipeline is designed to perform reference-assisted and de novo gene prediction, homolog protein family assignment, ortholog prediction, functional annotation, and pan-genome analysis using a range of proven tools and databases. While most existing methods scale quadratically with the number of genomes since they rely on pairwise comparisons among predicted protein sequences, DeNoGAP scales linearly since the homology assignment is based on iteratively refined hidden Markov models. This iterative clustering strategy enables DeNoGAP to handle a very large number of genomes using minimal computational resources. Moreover, the modular structure of the pipeline permits easy updates as new analysis programs become available. DeNoGAP integrates bioinformatics tools and databases for comparative analysis of a large number of genomes. The pipeline offers tools and algorithms for annotation and analysis of completed and draft genome sequences. The pipeline is developed using Perl, BioPerl and SQLite on Ubuntu Linux version 12.04 LTS. Currently, the software package accompanies script for automated installation of necessary external programs on Ubuntu Linux; however, the pipeline should be also compatible with other Linux and Unix systems after necessary external programs are installed. DeNoGAP is freely available at https://sourceforge.net/projects/denogap/ .

Electro-Microfluidic Packaging

NASA Astrophysics Data System (ADS)

Benavides, G. L.; Galambos, P. C.

2002-06-01

There are many examples of electro-microfluidic products that require cost effective packaging solutions. Industry has responded to a demand for products such as drop ejectors, chemical sensors, and biological sensors. Drop ejectors have consumer applications such as ink jet printing and scientific applications such as patterning self-assembled monolayers or ejecting picoliters of expensive analytes/reagents for chemical analysis. Drop ejectors can be used to perform chemical analysis, combinatorial chemistry, drug manufacture, drug discovery, drug delivery, and DNA sequencing. Chemical and biological micro-sensors can sniff the ambient environment for traces of dangerous materials such as explosives, toxins, or pathogens. Other biological sensors can be used to improve world health by providing timely diagnostics and applying corrective measures to the human body. Electro-microfluidic packaging can easily represent over fifty percent of the product cost and, as with Integrated Circuits (IC), the industry should evolve to standard packaging solutions. Standard packaging schemes will minimize cost and bring products to market sooner.

A Novel Framework for the Comparative Analysis of Biological Networks

PubMed Central

Pache, Roland A.; Aloy, Patrick

2012-01-01

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes. PMID:22363585

Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

PubMed

Dewhurst, Henry M; Choudhury, Shilpa; Torres, Matthew P

2015-08-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)--a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits--conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit-N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Whole-genome sequencing of staphylococcus haemolyticus uncovers the extreme plasticity of its genome and the evolution of human-colonizing staphylococcal species.

PubMed

Takeuchi, Fumihiko; Watanabe, Shinya; Baba, Tadashi; Yuzawa, Harumi; Ito, Teruyo; Morimoto, Yuh; Kuroda, Makoto; Cui, Longzhu; Takahashi, Mikio; Ankai, Akiho; Baba, Shin-ichi; Fukui, Shigehiro; Lee, Jean C; Hiramatsu, Keiichi

2005-11-01

Staphylococcus haemolyticus is an opportunistic bacterial pathogen that colonizes human skin and is remarkable for its highly antibiotic-resistant phenotype. We determined the complete genome sequence of S.haemolyticus to better understand its pathogenicity and evolutionary relatedness to the other staphylococcal species. A large proportion of the open reading frames in the genomes of S.haemolyticus, Staphylococcus aureus, and Staphylococcus epidermidis were conserved in their sequence and order on the chromosome. We identified a region of the bacterial chromosome just downstream of the origin of replication that showed little homology among the species but was conserved among strains within a species. This novel region, designated the "oriC environ," likely contributes to the evolution and differentiation of the staphylococcal species, since it was enriched for species-specific nonessential genes that contribute to the biological features of each staphylococcal species. A comparative analysis of the genomes of S.haemolyticus, S.aureus, and S.epidermidis elucidated differences in their biological and genetic characteristics and pathogenic potentials. We identified as many as 82 insertion sequences in the S.haemolyticus chromosome that probably mediated frequent genomic rearrangements, resulting in phenotypic diversification of the strain. Such rearrangements could have brought genomic plasticity to this species and contributed to its acquisition of antibiotic resistance.

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

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

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

RNA-Seq Technology and Its Application in Fish Transcriptomics

PubMed Central

Ba, Yi; Zhuang, Qianfeng

2014-01-01

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

Research Associate | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) at the Frederick National Laboratory for Cancer Research (FNLCR) pursues independent, multidisciplinary research programs in basic or applied molecular biology, immunology, retrovirology, cancer biology or human genetics. As part of the BSP, the Microbiome and Genetics Core (the Core) characterizes microbiomes by next-generation sequencing to determine their composition and variation, as influenced by immune, genetic, and host health factors. The Core provides support across a spectrum of processes, from nucleic acid isolation through bioinformatics and statistical analysis. KEY ROLES/RESPONSIBILITIES The Research Associate II will provide support in the areas of automated isolation, preparation, PCR and sequencing of DNA on next generation platforms (Illumina MiSeq and NextSeq). An opportunity exists to join the Core’s team of highly trained experimentalists and bioinformaticians working to characterize microbiome samples. The following represent requirements of the position: A minimum of five (5) years related of biomedical experience. Experience with high-throughput nucleic acid (DNA/RNA) extraction. Experience in performing PCR amplification (including quantitative real-time PCR). Experience or familiarity with robotic liquid handling protocols (especially on the Eppendorf epMotion 5073 or 5075 platforms). Experience in operating and maintaining benchtop Illumina sequencers (MiSeq and NextSeq). Ability to evaluate experimental quality and to troubleshoot molecular biology protocols. Experience with sample tracking, inventory management and biobanking. Ability to operate and communicate effectively in a team-oriented work environment.

PlanMine--a mineable resource of planarian biology and biodiversity.

PubMed

Brandl, Holger; Moon, HongKee; Vila-Farré, Miquel; Liu, Shang-Yun; Henry, Ian; Rink, Jochen C

2016-01-04

Planarian flatworms are in the midst of a renaissance as a model system for regeneration and stem cells. Besides two well-studied model species, hundreds of species exist worldwide that present a fascinating diversity of regenerative abilities, tissue turnover rates, reproductive strategies and other life history traits. PlanMine (http://planmine.mpi-cbg.de/) aims to accomplish two primary missions: First, to provide an easily accessible platform for sharing, comparing and value-added mining of planarian sequence data. Second, to catalyze the comparative analysis of the phenotypic diversity amongst planarian species. Currently, PlanMine houses transcriptomes independently assembled by our lab and community contributors. Detailed assembly/annotation statistics, a custom-developed BLAST viewer and easy export options enable comparisons at the contig and assembly level. Consistent annotation of all transcriptomes by an automated pipeline, the integration of published gene expression information and inter-relational query tools provide opportunities for mining planarian gene sequences and functions. For inter-species comparisons, we include transcriptomes of, so far, six planarian species, along with images, expert-curated information on their biology and pre-calculated cross-species sequence homologies. PlanMine is based on the popular InterMine system in order to make the rich biology of planarians accessible to the general life sciences research community. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The novel primers for mammal species identification-based mitochondrial cytochrome b sequence: implication for reserved wild animals in Thailand and endangered mammal species in Southeast Asia.

PubMed

Muangkram, Yuttamol; Wajjwalku, Worawidh; Amano, Akira; Sukmak, Manakorn

2018-01-01

We presented the powerful techniques for species identification using the short amplicon of mitochondrial cytochrome b gene sequence. Two faecal samples and one single hair sample of the Asian tapir were tested using the new cytochrome b primers. The results showed a high sequence similarity with the mainland Asian tapir group. The comparative sequence analysis of the reserved wild mammals in Thailand and the other endangered mammal species from Southeast Asia comprehensibly verified the potential of our novel primers. The forward and reverse primers were 94.2 and 93.2%, respectively, by the average value of the sequence identity among 77 species sequences, and the overall mean distance was 35.9%. This development technique could provide rapid, simple, and reliable tools for species confirmation. Especially, it could recognize the problematic biological specimens contained less DNA material from illegal products and assist with wildlife crime investigation of threatened species and related forensic casework.

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

Power law tails in phylogenetic systems.

PubMed

Qin, Chongli; Colwell, Lucy J

2018-01-23

Covariance analysis of protein sequence alignments uses coevolving pairs of sequence positions to predict features of protein structure and function. However, current methods ignore the phylogenetic relationships between sequences, potentially corrupting the identification of covarying positions. Here, we use random matrix theory to demonstrate the existence of a power law tail that distinguishes the spectrum of covariance caused by phylogeny from that caused by structural interactions. The power law is essentially independent of the phylogenetic tree topology, depending on just two parameters-the sequence length and the average branch length. We demonstrate that these power law tails are ubiquitous in the large protein sequence alignments used to predict contacts in 3D structure, as predicted by our theory. This suggests that to decouple phylogenetic effects from the interactions between sequence distal sites that control biological function, it is necessary to remove or down-weight the eigenvectors of the covariance matrix with largest eigenvalues. We confirm that truncating these eigenvectors improves contact prediction.

Novel Substrates as Sources of Ancient DNA: Prospects and Hurdles

PubMed Central

Green, Eleanor Joan

2017-01-01

Following the discovery in the late 1980s that hard tissues such as bones and teeth preserve genetic information, the field of ancient DNA analysis has typically concentrated upon these substrates. The onset of high-throughput sequencing, combined with optimized DNA recovery methods, has enabled the analysis of a myriad of ancient species and specimens worldwide, dating back to the Middle Pleistocene. Despite the growing sophistication of analytical techniques, the genetic analysis of substrates other than bone and dentine remain comparatively “novel”. Here, we review analyses of other biological substrates which offer great potential for elucidating phylogenetic relationships, paleoenvironments, and microbial ecosystems including (1) archaeological artifacts and ecofacts; (2) calcified and/or mineralized biological deposits; and (3) biological and cultural archives. We conclude that there is a pressing need for more refined models of DNA preservation and bespoke tools for DNA extraction and analysis to authenticate and maximize the utility of the data obtained. With such tools in place the potential for neglected or underexploited substrates to provide a unique insight into phylogenetics, microbial evolution and evolutionary processes will be realized. PMID:28703741

Massively Parallel, Molecular Analysis Platform Developed Using a CMOS Integrated Circuit With Biological Nanopores

PubMed Central

Roever, Stefan

2012-01-01

A massively parallel, low cost molecular analysis platform will dramatically change the nature of protein, molecular and genomics research, DNA sequencing, and ultimately, molecular diagnostics. An integrated circuit (IC) with 264 sensors was fabricated using standard CMOS semiconductor processing technology. Each of these sensors is individually controlled with precision analog circuitry and is capable of single molecule measurements. Under electronic and software control, the IC was used to demonstrate the feasibility of creating and detecting lipid bilayers and biological nanopores using wild type α-hemolysin. The ability to dynamically create bilayers over each of the sensors will greatly accelerate pore development and pore mutation analysis. In addition, the noise performance of the IC was measured to be 30fA(rms). With this noise performance, single base detection of DNA was demonstrated using α-hemolysin. The data shows that a single molecule, electrical detection platform using biological nanopores can be operationalized and can ultimately scale to millions of sensors. Such a massively parallel platform will revolutionize molecular analysis and will completely change the field of molecular diagnostics in the future.

Adrenocortical carcinoma: the dawn of a new era of genomic and molecular biology analysis.

PubMed

Armignacco, R; Cantini, G; Canu, L; Poli, G; Ercolino, T; Mannelli, M; Luconi, M

2018-05-01

Over the last decade, the development of novel and high penetrance genomic approaches to analyze biological samples has provided very new insights in the comprehension of the molecular biology and genetics of tumors. The use of these techniques, consisting of exome sequencing, transcriptome, miRNome, chromosome alteration, genome, and epigenome analysis, has also been successfully applied to adrenocortical carcinoma (ACC). In fact, the analysis of large cohorts of patients allowed the stratification of ACC with different patterns of molecular alterations, associated with different outcomes, thus providing a novel molecular classification of the malignancy to be associated with the classical pathological analysis. Improving our knowledge about ACC molecular features will result not only in a better diagnostic and prognostic accuracy, but also in the identification of more specific therapeutic targets for the development of more effective pharmacological anti-cancer approaches. In particular, the specific molecular alteration profiles identified in ACC may represent targetable events by the use of already developed or newly designed drugs enabling a better and more efficacious management of the ACC patient in the context of new frontiers of personalized precision medicine.

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

A Multicenter Study To Evaluate the Performance of High-Throughput Sequencing for Virus Detection

PubMed Central

Ng, Siemon H. S.; Vandeputte, Olivier; Aljanahi, Aisha; Deyati, Avisek; Cassart, Jean-Pol; Charlebois, Robert L.; Taliaferro, Lanyn P.

2017-01-01

ABSTRACT The capability of high-throughput sequencing (HTS) for detection of known and unknown viruses makes it a powerful tool for broad microbial investigations, such as evaluation of novel cell substrates that may be used for the development of new biological products. However, like any new assay, regulatory applications of HTS need method standardization. Therefore, our three laboratories initiated a study to evaluate performance of HTS for potential detection of viral adventitious agents by spiking model viruses in different cellular matrices to mimic putative materials for manufacturing of biologics. Four model viruses were selected based upon different physical and biochemical properties and commercial availability: human respiratory syncytial virus (RSV), Epstein-Barr virus (EBV), feline leukemia virus (FeLV), and human reovirus (REO). Additionally, porcine circovirus (PCV) was tested by one laboratory. Independent samples were prepared for HTS by spiking intact viruses or extracted viral nucleic acids, singly or mixed, into different HeLa cell matrices (resuspended whole cells, cell lysate, or total cellular RNA). Data were obtained using different sequencing platforms (Roche 454, Illumina HiSeq1500 or HiSeq2500). Bioinformatic analyses were performed independently by each laboratory using available tools, pipelines, and databases. The results showed that comparable virus detection was obtained in the three laboratories regardless of sample processing, library preparation, sequencing platform, and bioinformatic analysis: between 0.1 and 3 viral genome copies per cell were detected for all of the model viruses used. This study highlights the potential for using HTS for sensitive detection of adventitious viruses in complex biological samples containing cellular background. IMPORTANCE Recent high-throughput sequencing (HTS) investigations have resulted in unexpected discoveries of known and novel viruses in a variety of sample types, including research materials, clinical materials, and biological products. Therefore, HTS can be a powerful tool for supplementing current methods for demonstrating the absence of adventitious or unwanted viruses in biological products, particularly when using a new cell line. However, HTS is a complex technology with different platforms, which needs standardization for evaluation of biologics. This collaborative study was undertaken to investigate detection of different virus types using two different HTS platforms. The results of the independently performed studies demonstrated a similar sensitivity of virus detection, regardless of the different sample preparation and processing procedures and bioinformatic analyses done in the three laboratories. Comparable HTS detection of different virus types supports future development of reference virus materials for standardization and validation of different HTS platforms. PMID:28932815

[The future of forensic DNA analysis for criminal justice].

PubMed

Laurent, François-Xavier; Vibrac, Geoffrey; Rubio, Aurélien; Thévenot, Marie-Thérèse; Pène, Laurent

2017-11-01

In the criminal framework, the analysis of approximately 20 DNA microsatellites enables the establishment of a genetic profile with a high statistical power of discrimination. This technique gives us the possibility to establish or exclude a match between a biological trace detected at a crime scene and a suspect whose DNA was collected via an oral swab. However, conventional techniques do tend to complexify the interpretation of complex DNA samples, such as degraded DNA and mixture DNA. The aim of this review is to highlight the powerness of new forensic DNA methods (including high-throughput sequencing or single-cell sequencing) to facilitate the interpretation of the expert with full compliance with existing french legislation. © 2017 médecine/sciences – Inserm.

From Sequences to Insights in Microbial Ecology

PubMed Central

Knight, R.

2010-01-01

s4-3 Rapid declines in the cost of sequencing have made large volumes of DNA sequence data available to individual investigators. Now, data analysis is the rate-limiting step: providing a user with sequences alone typically leads to bewilderment, frustration, and skepticism about the technology. In this talk, I focus on how to extract insights from 16S rRNA data, including key lab steps (barcoding and normalization) and on which tools are available to perform routine but essential processing steps such as denoising, chimera detection, taxonomy assignment, and diversity analyses (including detection of biological clusters and gradients in the samples). Providing users with advice on these points and with a standard pipeline they can exploit (but modify if circumstances require) can greatly accelerate the rate of understanding, publication, and acquisition of funding for further studies.

Genome sequence and comparative analysis of a putative entomopathogenic Serratia isolated from Caenorhabditis briggsae.

PubMed

Abebe-Akele, Feseha; Tisa, Louis S; Cooper, Vaughn S; Hatcher, Philip J; Abebe, Eyualem; Thomas, W Kelley

2015-07-18

Entomopathogenic associations between nematodes in the genera Steinernema and Heterorhabdus with their cognate bacteria from the bacterial genera Xenorhabdus and Photorhabdus, respectively, are extensively studied for their potential as biological control agents against invasive insect species. These two highly coevolved associations were results of convergent evolution. Given the natural abundance of bacteria, nematodes and insects, it is surprising that only these two associations with no intermediate forms are widely studied in the entomopathogenic context. Discovering analogous systems involving novel bacterial and nematode species would shed light on the evolutionary processes involved in the transition from free living organisms to obligatory partners in entomopathogenicity. We report the complete genome sequence of a new member of the enterobacterial genus Serratia that forms a putative entomopathogenic complex with Caenorhabditis briggsae. Analysis of the 5.04 MB chromosomal genome predicts 4599 protein coding genes, seven sets of ribosomal RNA genes, 84 tRNA genes and a 64.8 KB plasmid encoding 74 genes. Comparative genomic analysis with three of the previously sequenced Serratia species, S. marcescens DB11 and S. proteamaculans 568, and Serratia sp. AS12, revealed that these four representatives of the genus share a core set of ~3100 genes and extensive structural conservation. The newly identified species shares a more recent common ancestor with S. marcescens with 99% sequence identity in rDNA sequence and orthology across 85.6% of predicted genes. Of the 39 genes/operons implicated in the virulence, symbiosis, recolonization, immune evasion and bioconversion, 21 (53.8%) were present in Serratia while 33 (84.6%) and 35 (89%) were present in Xenorhabdus and Photorhabdus EPN bacteria respectively. The majority of unique sequences in Serratia sp. SCBI (South African Caenorhabditis briggsae Isolate) are found in ~29 genomic islands of 5 to 65 genes and are enriched in putative functions that are biologically relevant to an entomopathogenic lifestyle, including non-ribosomal peptide synthetases, bacteriocins, fimbrial biogenesis, ushering proteins, toxins, secondary metabolite secretion and multiple drug resistance/efflux systems. By revealing the early stages of adaptation to this lifestyle, the Serratia sp. SCBI genome underscores the fact that in EPN formation the composite end result - killing, bioconversion, cadaver protection and recolonization- can be achieved by dissimilar mechanisms. This genome sequence will enable further study of the evolution of entomopathogenic nematode-bacteria complexes.

CFGP: a web-based, comparative fungal genomics platform.

PubMed

Park, Jongsun; Park, Bongsoo; Jung, Kyongyong; Jang, Suwang; Yu, Kwangyul; Choi, Jaeyoung; Kong, Sunghyung; Park, Jaejin; Kim, Seryun; Kim, Hyojeong; Kim, Soonok; Kim, Jihyun F; Blair, Jaime E; Lee, Kwangwon; Kang, Seogchan; Lee, Yong-Hwan

2008-01-01

Since the completion of the Saccharomyces cerevisiae genome sequencing project in 1996, the genomes of over 80 fungal species have been sequenced or are currently being sequenced. Resulting data provide opportunities for studying and comparing fungal biology and evolution at the genome level. To support such studies, the Comparative Fungal Genomics Platform (CFGP; http://cfgp.snu.ac.kr), a web-based multifunctional informatics workbench, was developed. The CFGP comprises three layers, including the basal layer, middleware and the user interface. The data warehouse in the basal layer contains standardized genome sequences of 65 fungal species. The middleware processes queries via six analysis tools, including BLAST, ClustalW, InterProScan, SignalP 3.0, PSORT II and a newly developed tool named BLASTMatrix. The BLASTMatrix permits the identification and visualization of genes homologous to a query across multiple species. The Data-driven User Interface (DUI) of the CFGP was built on a new concept of pre-collecting data and post-executing analysis instead of the 'fill-in-the-form-and-press-SUBMIT' user interfaces utilized by most bioinformatics sites. A tool termed Favorite, which supports the management of encapsulated sequence data and provides a personalized data repository to users, is another novel feature in the DUI.

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

PubMed Central

Lipinski, Leszek; Dziembowski, Andrzej

2018-01-01

Abstract Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions. PMID:29346586

dictyExpress: a web-based platform for sequence data management and analytics in Dictyostelium and beyond.

PubMed

Stajdohar, Miha; Rosengarten, Rafael D; Kokosar, Janez; Jeran, Luka; Blenkus, Domen; Shaulsky, Gad; Zupan, Blaz

2017-06-02

Dictyostelium discoideum, a soil-dwelling social amoeba, is a model for the study of numerous biological processes. Research in the field has benefited mightily from the adoption of next-generation sequencing for genomics and transcriptomics. Dictyostelium biologists now face the widespread challenges of analyzing and exploring high dimensional data sets to generate hypotheses and discovering novel insights. We present dictyExpress (2.0), a web application designed for exploratory analysis of gene expression data, as well as data from related experiments such as Chromatin Immunoprecipitation sequencing (ChIP-Seq). The application features visualization modules that include time course expression profiles, clustering, gene ontology enrichment analysis, differential expression analysis and comparison of experiments. All visualizations are interactive and interconnected, such that the selection of genes in one module propagates instantly to visualizations in other modules. dictyExpress currently stores the data from over 800 Dictyostelium experiments and is embedded within a general-purpose software framework for management of next-generation sequencing data. dictyExpress allows users to explore their data in a broader context by reciprocal linking with dictyBase-a repository of Dictyostelium genomic data. In addition, we introduce a companion application called GenBoard, an intuitive graphic user interface for data management and bioinformatics analysis. dictyExpress and GenBoard enable broad adoption of next generation sequencing based inquiries by the Dictyostelium research community. Labs without the means to undertake deep sequencing projects can mine the data available to the public. The entire information flow, from raw sequence data to hypothesis testing, can be accomplished in an efficient workspace. The software framework is generalizable and represents a useful approach for any research community. To encourage more wide usage, the backend is open-source, available for extension and further development by bioinformaticians and data scientists.

Developing JSequitur to Study the Hierarchical Structure of Biological Sequences in a Grammatical Inference Framework of String Compression Algorithms.

PubMed

Galbadrakh, Bulgan; Lee, Kyung-Eun; Park, Hyun-Seok

2012-12-01

Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

New extension software modules to enhance searching and display of transcriptome data in Tripal databases

PubMed Central

Chen, Ming; Henry, Nathan; Almsaeed, Abdullah; Zhou, Xiao; Wegrzyn, Jill; Ficklin, Stephen

2017-01-01

Abstract Tripal is an open source software package for developing biological databases with a focus on genetic and genomic data. It consists of a set of core modules that deliver essential functions for loading and displaying data records and associated attributes including organisms, sequence features and genetic markers. Beyond the core modules, community members are encouraged to contribute extension modules to build on the Tripal core and to customize Tripal for individual community needs. To expand the utility of the Tripal software system, particularly for RNASeq data, we developed two new extension modules. Tripal Elasticsearch enables fast, scalable searching of the entire content of a Tripal site as well as the construction of customized advanced searches of specific data types. We demonstrate the use of this module for searching assembled transcripts by functional annotation. A second module, Tripal Analysis Expression, houses and displays records from gene expression assays such as RNA sequencing. This includes biological source materials (biomaterials), gene expression values and protocols used to generate the data. In the case of an RNASeq experiment, this would reflect the individual organisms and tissues used to produce sequencing libraries, the normalized gene expression values derived from the RNASeq data analysis and a description of the software or code used to generate the expression values. The module will load data from common flat file formats including standard NCBI Biosample XML. Data loading, display options and other configurations can be controlled by authorized users in the Drupal administrative backend. Both modules are open source, include usage documentation, and can be found in the Tripal organization’s GitHub repository. Database URL: Tripal Elasticsearch module: https://github.com/tripal/tripal_elasticsearch Tripal Analysis Expression module: https://github.com/tripal/tripal_analysis_expression PMID:29220446

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

PubMed

Antanaviciute, Agne; Watson, Christopher M; Harrison, Sally M; Lascelles, Carolina; Crinnion, Laura; Markham, Alexander F; Bonthron, David T; Carr, Ian M

2015-12-01

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. Supplementary data are available at Bioinformatics online. umaan@leeds.ac.uk. © The Author 2015. Published by Oxford University Press.

Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA.

PubMed

Scherer, Florian; Kurtz, David M; Newman, Aaron M; Stehr, Henning; Craig, Alexander F M; Esfahani, Mohammad Shahrokh; Lovejoy, Alexander F; Chabon, Jacob J; Klass, Daniel M; Liu, Chih Long; Zhou, Li; Glover, Cynthia; Visser, Brendan C; Poultsides, George A; Advani, Ranjana H; Maeda, Lauren S; Gupta, Neel K; Levy, Ronald; Ohgami, Robert S; Kunder, Christian A; Diehn, Maximilian; Alizadeh, Ash A

2016-11-09

Patients with diffuse large B cell lymphoma (DLBCL) exhibit marked diversity in tumor behavior and outcomes, yet the identification of poor-risk groups remains challenging. In addition, the biology underlying these differences is incompletely understood. We hypothesized that characterization of mutational heterogeneity and genomic evolution using circulating tumor DNA (ctDNA) profiling could reveal molecular determinants of adverse outcomes. To address this hypothesis, we applied cancer personalized profiling by deep sequencing (CAPP-Seq) analysis to tumor biopsies and cell-free DNA samples from 92 lymphoma patients and 24 healthy subjects. At diagnosis, the amount of ctDNA was found to strongly correlate with clinical indices and was independently predictive of patient outcomes. We demonstrate that ctDNA genotyping can classify transcriptionally defined tumor subtypes, including DLBCL cell of origin, directly from plasma. By simultaneously tracking multiple somatic mutations in ctDNA, our approach outperformed immunoglobulin sequencing and radiographic imaging for the detection of minimal residual disease and facilitated noninvasive identification of emergent resistance mutations to targeted therapies. In addition, we identified distinct patterns of clonal evolution distinguishing indolent follicular lymphomas from those that transformed into DLBCL, allowing for potential noninvasive prediction of histological transformation. Collectively, our results demonstrate that ctDNA analysis reveals biological factors that underlie lymphoma clinical outcomes and could facilitate individualized therapy. Copyright © 2016, American Association for the Advancement of Science.

BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature.

PubMed

Sen Sarma, Moushumi; Arcoleo, David; Khetani, Radhika S; Chee, Brant; Ling, Xu; He, Xin; Jiang, Jing; Mei, Qiaozhu; Zhai, ChengXiang; Schatz, Bruce

2011-07-01

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php.

BAC sequencing using pooled methods.

PubMed

Saski, Christopher A; Feltus, F Alex; Parida, Laxmi; Haiminen, Niina

2015-01-01

Shotgun sequencing and assembly of a large, complex genome can be both expensive and challenging to accurately reconstruct the true genome sequence. Repetitive DNA arrays, paralogous sequences, polyploidy, and heterozygosity are main factors that plague de novo genome sequencing projects that typically result in highly fragmented assemblies and are difficult to extract biological meaning. Targeted, sub-genomic sequencing offers complexity reduction by removing distal segments of the genome and a systematic mechanism for exploring prioritized genomic content through BAC sequencing. If one isolates and sequences the genome fraction that encodes the relevant biological information, then it is possible to reduce overall sequencing costs and efforts that target a genomic segment. This chapter describes the sub-genome assembly protocol for an organism based upon a BAC tiling path derived from a genome-scale physical map or from fine mapping using BACs to target sub-genomic regions. Methods that are described include BAC isolation and mapping, DNA sequencing, and sequence assembly.

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis.

PubMed

Buldyrev, S V; Goldberger, A L; Havlin, S; Mantegna, R N; Matsa, M E; Peng, C K; Simons, M; Stanley, H E

1995-05-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

NASA Technical Reports Server (NTRS)

Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Matsa, M. E.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Phylo-VISTA: Interactive visualization of multiple DNA sequence alignments

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

Shah, Nameeta; Couronne, Olivier; Pennacchio, Len A.

The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. Results: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a frameworkmore » based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. Availability: Phylo-VISTA is available at http://www-gsd.lbl. gov/phylovista. It requires an Internet browser with Java Plugin 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu« less

Factoring local sequence composition in motif significance analysis.

PubMed

Ng, Patrick; Keich, Uri

2008-01-01

We recently introduced a biologically realistic and reliable significance analysis of the output of a popular class of motif finders. In this paper we further improve our significance analysis by incorporating local base composition information. Relying on realistic biological data simulation, as well as on FDR analysis applied to real data, we show that our method is significantly better than the increasingly popular practice of using the normal approximation to estimate the significance of a finder's output. Finally we turn to leveraging our reliable significance analysis to improve the actual motif finding task. Specifically, endowing a variant of the Gibbs Sampler with our improved significance analysis we demonstrate that de novo finders can perform better than has been perceived. Significantly, our new variant outperforms all the finders reviewed in a recently published comprehensive analysis of the Harbison genome-wide binding location data. Interestingly, many of these finders incorporate additional information such as nucleosome positioning and the significance of binding data.

Chemometric analysis of Hymenoptera toxins and defensins: A model for predicting the biological activity of novel peptides from venoms and hemolymph.

PubMed

Saidemberg, Daniel M; Baptista-Saidemberg, Nicoli B; Palma, Mario S

2011-09-01

When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The "trial and error" approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. Copyright © 2011 Elsevier Inc. All rights reserved.

Effects of the Ion PGM™ Hi-Q™ sequencing chemistry on sequence data quality.

PubMed

Churchill, Jennifer D; King, Jonathan L; Chakraborty, Ranajit; Budowle, Bruce

2016-09-01

Massively parallel sequencing (MPS) offers substantial improvements over current forensic DNA typing methodologies such as increased resolution, scalability, and throughput. The Ion PGM™ is a promising MPS platform for analysis of forensic biological evidence. The system employs a sequencing-by-synthesis chemistry on a semiconductor chip that measures a pH change due to the release of hydrogen ions as nucleotides are incorporated into the growing DNA strands. However, implementation of MPS into forensic laboratories requires a robust chemistry. Ion Torrent's Hi-Q™ Sequencing Chemistry was evaluated to determine if it could improve on the quality of the generated sequence data in association with selected genetic marker targets. The whole mitochondrial genome and the HID-Ion STR 10-plex panel were sequenced on the Ion PGM™ system with the Ion PGM™ Sequencing 400 Kit and the Ion PGM™ Hi-Q™ Sequencing Kit. Concordance, coverage, strand balance, noise, and deletion ratios were assessed in evaluating the performance of the Ion PGM™ Hi-Q™ Sequencing Kit. The results indicate that reliable, accurate data are generated and that sequencing through homopolymeric regions can be improved with the use of Ion Torrent's Hi-Q™ Sequencing Chemistry. Overall, the quality of the generated sequencing data supports the potential for use of the Ion PGM™ in forensic genetic laboratories.