Modular protein domains: an engineering approach toward functional biomaterials.

PubMed

Lin, Charng-Yu; Liu, Julie C

2016-08-01

Protein domains and peptide sequences are a powerful tool for conferring specific functions to engineered biomaterials. Protein sequences with a wide variety of functionalities, including structure, bioactivity, protein-protein interactions, and stimuli responsiveness, have been identified, and advances in molecular biology continue to pinpoint new sequences. Protein domains can be combined to make recombinant proteins with multiple functionalities. The high fidelity of the protein translation machinery results in exquisite control over the sequence of recombinant proteins and the resulting properties of protein-based materials. In this review, we discuss protein domains and peptide sequences in the context of functional protein-based materials, composite materials, and their biological applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

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.

RBT-GA: a novel metaheuristic for solving the Multiple Sequence Alignment problem.

PubMed

Taheri, Javid; Zomaya, Albert Y

2009-07-07

Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences.

PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences.

PubMed

Mirarab, Siavash; Nguyen, Nam; Guo, Sheng; Wang, Li-San; Kim, Junhyong; Warnow, Tandy

2015-05-01

We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate--slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2010-01-01

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys. PMID:20530533

Sequence Segmentation with changeptGUI.

PubMed

Tasker, Edward; Keith, Jonathan M

2017-01-01

Many biological sequences have a segmental structure that can provide valuable clues to their content, structure, and function. The program changept is a tool for investigating the segmental structure of a sequence, and can also be applied to multiple sequences in parallel to identify a common segmental structure, thus providing a method for integrating multiple data types to identify functional elements in genomes. In the previous edition of this book, a command line interface for changept is described. Here we present a graphical user interface for this package, called changeptGUI. This interface also includes tools for pre- and post-processing of data and results to facilitate investigation of the number and characteristics of segment classes.

PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences

PubMed Central

Mirarab, Siavash; Nguyen, Nam; Guo, Sheng; Wang, Li-San; Kim, Junhyong

2015-01-01

Abstract We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate—slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory. PMID:25549288

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.

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/ .

RBT-GA: a novel metaheuristic for solving the multiple sequence alignment problem

PubMed Central

Taheri, Javid; Zomaya, Albert Y

2009-01-01

Background Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. Results This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. Conclusion RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences. PMID:19594869

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word “data-mining” is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

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

Discovering Motifs in Biological Sequences Using the Micron Automata Processor.

PubMed

Roy, Indranil; Aluru, Srinivas

2016-01-01

Finding approximately conserved sequences, called motifs, across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the (l, d) motif search problem of identifying one or more motifs of length l present in at least q of the n given sequences, with each occurrence differing from the motif in at most d substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is (26,11). We propose a novel algorithm for the (l,d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the (l, d) motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances (39,18) and (40,17). The paper serves as a useful guide to solving problems using this new accelerator technology.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

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

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

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

BEAUTY: an enhanced BLAST-based search tool that integrates multiple biological information resources into sequence similarity search results.

PubMed

Worley, K C; Wiese, B A; Smith, R F

1995-09-01

BEAUTY (BLAST enhanced alignment utility) is an enhanced version of the NCBI's BLAST data base search tool that facilitates identification of the functions of matched sequences. We have created new data bases of conserved regions and functional domains for protein sequences in NCBI's Entrez data base, and BEAUTY allows this information to be incorporated directly into BLAST search results. A Conserved Regions Data Base, containing the locations of conserved regions within Entrez protein sequences, was constructed by (1) clustering the entire data base into families, (2) aligning each family using our PIMA multiple sequence alignment program, and (3) scanning the multiple alignments to locate the conserved regions within each aligned sequence. A separate Annotated Domains Data Base was constructed by extracting the locations of all annotated domains and sites from sequences represented in the Entrez, PROSITE, BLOCKS, and PRINTS data bases. BEAUTY performs a BLAST search of those Entrez sequences with conserved regions and/or annotated domains. BEAUTY then uses the information from the Conserved Regions and Annotated Domains data bases to generate, for each matched sequence, a schematic display that allows one to directly compare the relative locations of (1) the conserved regions, (2) annotated domains and sites, and (3) the locally aligned regions matched in the BLAST search. In addition, BEAUTY search results include World-Wide Web hypertext links to a number of external data bases that provide a variety of additional types of information on the function of matched sequences. This convenient integration of protein families, conserved regions, annotated domains, alignment displays, and World-Wide Web resources greatly enhances the biological informativeness of sequence similarity searches. BEAUTY searches can be performed remotely on our system using the "BCM Search Launcher" World-Wide Web pages (URL is < http:/ /gc.bcm.tmc.edu:8088/ search-launcher/launcher.html > ).

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

PubMed

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

2013-01-01

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

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

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

Atypical case of Wolfram syndrome revealed through targeted exome sequencing in a patient with suspected mitochondrial disease

PubMed Central

2012-01-01

Background Mitochondrial diseases comprise a diverse set of clinical disorders that affect multiple organ systems with varying severity and age of onset. Due to their clinical and genetic heterogeneity, these diseases are difficult to diagnose. We have developed a targeted exome sequencing approach to improve our ability to properly diagnose mitochondrial diseases and apply it here to an individual patient. Our method targets mitochondrial DNA (mtDNA) and the exons of 1,600 nuclear genes involved in mitochondrial biology or Mendelian disorders with multi-system phenotypes, thereby allowing for simultaneous evaluation of multiple disease loci. Case Presentation Targeted exome sequencing was performed on a patient initially suspected to have a mitochondrial disorder. The patient presented with diabetes mellitus, diffuse brain atrophy, autonomic neuropathy, optic nerve atrophy, and a severe amnestic syndrome. Further work-up revealed multiple heteroplasmic mtDNA deletions as well as profound thiamine deficiency without a clear nutritional cause. Targeted exome sequencing revealed a homozygous c.1672C > T (p.R558C) missense mutation in exon 8 of WFS1 that has previously been reported in a patient with Wolfram syndrome. Conclusion This case demonstrates how clinical application of next-generation sequencing technology can enhance the diagnosis of patients suspected to have rare genetic disorders. Furthermore, the finding of unexplained thiamine deficiency in a patient with Wolfram syndrome suggests a potential link between WFS1 biology and thiamine metabolism that has implications for the clinical management of Wolfram syndrome patients. PMID:22226368

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs.

PubMed

Blazewicz, Jacek; Frohmberg, Wojciech; Kierzynka, Michal; Pesch, Erwin; Wojciechowski, Pawel

2011-05-20

Pairwise sequence alignment methods are widely used in biological research. The increasing number of sequences is perceived as one of the upcoming challenges for sequence alignment methods in the nearest future. To overcome this challenge several GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of a GPU platform but in most cases address the problem of sequence database scanning and computing only the alignment score whereas the alignment itself is omitted. Thus, the need arose to implement the global and semiglobal Needleman-Wunsch, and Smith-Waterman algorithms with a backtracking procedure which is needed to construct the alignment. In this paper we present the solution that performs the alignment of every given sequence pair, which is a required step for progressive multiple sequence alignment methods, as well as for DNA recognition at the DNA assembly stage. Performed tests show that the implementation, with performance up to 6.3 GCUPS on a single GPU for affine gap penalties, is very efficient in comparison to other CPU and GPU-based solutions. Moreover, multiple GPUs support with load balancing makes the application very scalable. The article shows that the backtracking procedure of the sequence alignment algorithms may be designed to fit in with the GPU architecture. Therefore, our algorithm, apart from scores, is able to compute pairwise alignments. This opens a wide range of new possibilities, allowing other methods from the area of molecular biology to take advantage of the new computational architecture. Performed tests show that the efficiency of the implementation is excellent. Moreover, the speed of our GPU-based algorithms can be almost linearly increased when using more than one graphics card.

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

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies.

PubMed

Utturkar, Sagar M; Klingeman, Dawn M; Hurt, Richard A; Brown, Steven D

2017-01-01

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted. PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.

Natural product-inspired cascade synthesis yields modulators of centrosome integrity.

PubMed

Dückert, Heiko; Pries, Verena; Khedkar, Vivek; Menninger, Sascha; Bruss, Hanna; Bird, Alexander W; Maliga, Zoltan; Brockmeyer, Andreas; Janning, Petra; Hyman, Anthony; Grimme, Stefan; Schürmann, Markus; Preut, Hans; Hübel, Katja; Ziegler, Slava; Kumar, Kamal; Waldmann, Herbert

2011-12-25

In biology-oriented synthesis, the scaffolds of biologically relevant compound classes inspire the synthesis of focused compound collections enriched in bioactivity. This criterion is, in particular, met by the scaffolds of natural products selected in evolution. The synthesis of natural product-inspired compound collections calls for efficient reaction sequences that preferably combine multiple individual transformations in one operation. Here we report the development of a one-pot, twelve-step cascade reaction sequence that includes nine different reactions and two opposing kinds of organocatalysis. The cascade sequence proceeds within 10-30 min and transforms readily available substrates into complex indoloquinolizines that resemble the core tetracyclic scaffold of numerous polycyclic indole alkaloids. Biological investigation of a corresponding focused compound collection revealed modulators of centrosome integrity, termed centrocountins, which caused fragmented and supernumerary centrosomes, chromosome congression defects, multipolar mitotic spindles, acentrosomal spindle poles and multipolar cell division by targeting the centrosome-associated proteins nucleophosmin and Crm1.

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

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

Sequence alignment visualization in HTML5 without Java.

PubMed

Gille, Christoph; Birgit, Weyand; Gille, Andreas

2014-01-01

Java has been extensively used for the visualization of biological data in the web. However, the Java runtime environment is an additional layer of software with an own set of technical problems and security risks. HTML in its new version 5 provides features that for some tasks may render Java unnecessary. Alignment-To-HTML is the first HTML-based interactive visualization for annotated multiple sequence alignments. The server side script interpreter can perform all tasks like (i) sequence retrieval, (ii) alignment computation, (iii) rendering, (iv) identification of a homologous structural models and (v) communication with BioDAS-servers. The rendered alignment can be included in web pages and is displayed in all browsers on all platforms including touch screen tablets. The functionality of the user interface is similar to legacy Java applets and includes color schemes, highlighting of conserved and variable alignment positions, row reordering by drag and drop, interlinked 3D visualization and sequence groups. Novel features are (i) support for multiple overlapping residue annotations, such as chemical modifications, single nucleotide polymorphisms and mutations, (ii) mechanisms to quickly hide residue annotations, (iii) export to MS-Word and (iv) sequence icons. Alignment-To-HTML, the first interactive alignment visualization that runs in web browsers without additional software, confirms that to some extend HTML5 is already sufficient to display complex biological data. The low speed at which programs are executed in browsers is still the main obstacle. Nevertheless, we envision an increased use of HTML and JavaScript for interactive biological software. Under GPL at: http://www.bioinformatics.org/strap/toHTML/.

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

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.

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

Use of Multiple Fluorescent Labels in Biological Sensing

DTIC Science & Technology

2006-05-01

resulting in labels that are brighter and have longer Stokes shifts than the current standard; (B) to make excimer- and exciplex -forming probes for...2) to make excimer- and exciplex -forming probes for repetitive DNA sequences such as telomeres and centromeres, and to demonstrate them both...between fluorophores, and characterized unusual interactions, including water-soluble excimers and exciplexes . We investigated multiple ways to

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

PubMed Central

Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean

2009-01-01

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology. PMID:19816554

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies

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

Utturkar, Sagar M.; Klingeman, Dawn M.; Hurt, Jr., Richard A.

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted.more » PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Furthermore, our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.« less

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies

DOE PAGES

Utturkar, Sagar M.; Klingeman, Dawn M.; Hurt, Jr., Richard A.; ...

2017-07-18

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted.more » PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Furthermore, our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.« less

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies

PubMed Central

Utturkar, Sagar M.; Klingeman, Dawn M.; Hurt, Richard A.; Brown, Steven D.

2017-01-01

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted. PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences. PMID:28769883

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

PubMed Central

2013-01-01

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

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

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

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

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

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.

A parallel approach of COFFEE objective function to multiple sequence alignment

NASA Astrophysics Data System (ADS)

Zafalon, G. F. D.; Visotaky, J. M. V.; Amorim, A. R.; Valêncio, C. R.; Neves, L. A.; de Souza, R. C. G.; Machado, J. M.

2015-09-01

The computational tools to assist genomic analyzes show even more necessary due to fast increasing of data amount available. With high computational costs of deterministic algorithms for sequence alignments, many works concentrate their efforts in the development of heuristic approaches to multiple sequence alignments. However, the selection of an approach, which offers solutions with good biological significance and feasible execution time, is a great challenge. Thus, this work aims to show the parallelization of the processing steps of MSA-GA tool using multithread paradigm in the execution of COFFEE objective function. The standard objective function implemented in the tool is the Weighted Sum of Pairs (WSP), which produces some distortions in the final alignments when sequences sets with low similarity are aligned. Then, in studies previously performed we implemented the COFFEE objective function in the tool to smooth these distortions. Although the nature of COFFEE objective function implies in the increasing of execution time, this approach presents points, which can be executed in parallel. With the improvements implemented in this work, we can verify the execution time of new approach is 24% faster than the sequential approach with COFFEE. Moreover, the COFFEE multithreaded approach is more efficient than WSP, because besides it is slightly fast, its biological results are better.

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

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.

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

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

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

AntiClustal: Multiple Sequence Alignment by antipole clustering and linear approximate 1-median computation.

PubMed

Di Pietro, C; Di Pietro, V; Emmanuele, G; Ferro, A; Maugeri, T; Modica, E; Pigola, G; Pulvirenti, A; Purrello, M; Ragusa, M; Scalia, M; Shasha, D; Travali, S; Zimmitti, V

2003-01-01

In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.

Identification of radiation responsive genes and transcriptome profiling via complete RNA sequencing in a stable radioresistant U87 glioblastoma model.

PubMed

Doan, Ninh B; Nguyen, Ha S; Alhajala, Hisham S; Jaber, Basem; Al-Gizawiy, Mona M; Ahn, Eun-Young Erin; Mueller, Wade M; Chitambar, Christopher R; Mirza, Shama P; Schmainda, Kathleen M

2018-05-04

The absence of major progress in the treatment of glioblastoma (GBM) is partly attributable to our poor understanding of both GBM tumor biology and the acquirement of treatment resistance in recurrent GBMs. Recurrent GBMs are characterized by their resistance to radiation. In this study, we used an established stable U87 radioresistant GBM model and total RNA sequencing to shed light on global mRNA expression changes following irradiation. We identified many genes, the expressions of which were altered in our radioresistant GBM model, that have never before been reported to be associated with the development of radioresistant GBM and should be concertedly further investigated to understand their roles in radioresistance. These genes were enriched in various biological processes such as inflammatory response, cell migration, positive regulation of epithelial to mesenchymal transition, angiogenesis, apoptosis, positive regulation of T-cell migration, positive regulation of macrophage chemotaxis, T-cell antigen processing and presentation, and microglial cell activation involved in immune response genes. These findings furnish crucial information for elucidating the molecular mechanisms associated with radioresistance in GBM. Therapeutically, with the global alterations of multiple biological pathways observed in irradiated GBM cells, an effective GBM therapy may require a cocktail carrying multiple agents targeting multiple implicated pathways in order to have a chance at making a substantial impact on improving the overall GBM survival.

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.

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

Unipro UGENE: a unified bioinformatics toolkit.

PubMed

Okonechnikov, Konstantin; Golosova, Olga; Fursov, Mikhail

2012-04-15

Unipro UGENE is a multiplatform open-source software with the main goal of assisting molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality. UGENE binaries are freely available for MS Windows, Linux and Mac OS X at http://ugene.unipro.ru/download.html. UGENE code is licensed under the GPLv2; the information about the code licensing and copyright of integrated tools can be found in the LICENSE.3rd_party file provided with the source bundle.

Simulating Chemical-Induced Injury Using Virtual Hepatic Tissues

EPA Science Inventory

Chemical-induced liver injury involves a dynamic sequence of events that span multiple levels of biological organization. Current methods for testing the toxicity of a single chemical can cost millions of dollars, take up to two years and sacrifice thousands of animals. It is dif...

Efficient Identification of Murine M2 Macrophage Peptide Targeting Ligands by Phage Display and Next-Generation Sequencing.

PubMed

Liu, Gary W; Livesay, Brynn R; Kacherovsky, Nataly A; Cieslewicz, Maryelise; Lutz, Emi; Waalkes, Adam; Jensen, Michael C; Salipante, Stephen J; Pun, Suzie H

2015-08-19

Peptide ligands are used to increase the specificity of drug carriers to their target cells and to facilitate intracellular delivery. One method to identify such peptide ligands, phage display, enables high-throughput screening of peptide libraries for ligands binding to therapeutic targets of interest. However, conventional methods for identifying target binders in a library by Sanger sequencing are low-throughput, labor-intensive, and provide a limited perspective (<0.01%) of the complete sequence space. Moreover, the small sample space can be dominated by nonspecific, preferentially amplifying "parasitic sequences" and plastic-binding sequences, which may lead to the identification of false positives or exclude the identification of target-binding sequences. To overcome these challenges, we employed next-generation Illumina sequencing to couple high-throughput screening and high-throughput sequencing, enabling more comprehensive access to the phage display library sequence space. In this work, we define the hallmarks of binding sequences in next-generation sequencing data, and develop a method that identifies several target-binding phage clones for murine, alternatively activated M2 macrophages with a high (100%) success rate: sequences and binding motifs were reproducibly present across biological replicates; binding motifs were identified across multiple unique sequences; and an unselected, amplified library accurately filtered out parasitic sequences. In addition, we validate the Multiple Em for Motif Elicitation tool as an efficient and principled means of discovering binding sequences.

DynaMIT: the dynamic motif integration toolkit

PubMed Central

Dassi, Erik; Quattrone, Alessandro

2016-01-01

De-novo motif search is a frequently applied bioinformatics procedure to identify and prioritize recurrent elements in sequences sets for biological investigation, such as the ones derived from high-throughput differential expression experiments. Several algorithms have been developed to perform motif search, employing widely different approaches and often giving divergent results. In order to maximize the power of these investigations and ultimately be able to draft solid biological hypotheses, there is the need for applying multiple tools on the same sequences and merge the obtained results. However, motif reporting formats and statistical evaluation methods currently make such an integration task difficult to perform and mostly restricted to specific scenarios. We thus introduce here the Dynamic Motif Integration Toolkit (DynaMIT), an extremely flexible platform allowing to identify motifs employing multiple algorithms, integrate them by means of a user-selected strategy and visualize results in several ways; furthermore, the platform is user-extendible in all its aspects. DynaMIT is freely available at http://cibioltg.bitbucket.org. PMID:26253738

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output.

PubMed

Zaal, Dionne; Nota, Benjamin

2016-01-01

We present ADOMA, a command line tool that produces alternative outputs from ClustalW multiple alignments of nucleotide or protein sequences. ADOMA can simplify the output of alignments by showing only the different residues between sequences, which is often desirable when only small differences such as single nucleotide polymorphisms are present (e.g., between different alleles). Another feature of ADOMA is that it can enhance the ClustalW output by coloring the residues in the alignment. This tool is easily integrated into automated Linux pipelines for next-generation sequencing data analysis, and may be useful for researchers in a broad range of scientific disciplines including evolutionary biology and biomedical sciences. The source code is freely available at https://sourceforge. net/projects/adoma/. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detecting false positive sequence homology: a machine learning approach.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

CMSA: a heterogeneous CPU/GPU computing system for multiple similar RNA/DNA sequence alignment.

PubMed

Chen, Xi; Wang, Chen; Tang, Shanjiang; Yu, Ce; Zou, Quan

2017-06-24

The multiple sequence alignment (MSA) is a classic and powerful technique for sequence analysis in bioinformatics. With the rapid growth of biological datasets, MSA parallelization becomes necessary to keep its running time in an acceptable level. Although there are a lot of work on MSA problems, their approaches are either insufficient or contain some implicit assumptions that limit the generality of usage. First, the information of users' sequences, including the sizes of datasets and the lengths of sequences, can be of arbitrary values and are generally unknown before submitted, which are unfortunately ignored by previous work. Second, the center star strategy is suited for aligning similar sequences. But its first stage, center sequence selection, is highly time-consuming and requires further optimization. Moreover, given the heterogeneous CPU/GPU platform, prior studies consider the MSA parallelization on GPU devices only, making the CPUs idle during the computation. Co-run computation, however, can maximize the utilization of the computing resources by enabling the workload computation on both CPU and GPU simultaneously. This paper presents CMSA, a robust and efficient MSA system for large-scale datasets on the heterogeneous CPU/GPU platform. It performs and optimizes multiple sequence alignment automatically for users' submitted sequences without any assumptions. CMSA adopts the co-run computation model so that both CPU and GPU devices are fully utilized. Moreover, CMSA proposes an improved center star strategy that reduces the time complexity of its center sequence selection process from O(mn 2 ) to O(mn). The experimental results show that CMSA achieves an up to 11× speedup and outperforms the state-of-the-art software. CMSA focuses on the multiple similar RNA/DNA sequence alignment and proposes a novel bitmap based algorithm to improve the center star strategy. We can conclude that harvesting the high performance of modern GPU is a promising approach to accelerate multiple sequence alignment. Besides, adopting the co-run computation model can maximize the entire system utilization significantly. The source code is available at https://github.com/wangvsa/CMSA .

Transcription elongation. Heterogeneous tracking of RNA polymerase and its biological implications.

PubMed

Imashimizu, Masahiko; Shimamoto, Nobuo; Oshima, Taku; Kashlev, Mikhail

2014-01-01

Regulation of transcription elongation via pausing of RNA polymerase has multiple physiological roles. The pausing mechanism depends on the sequence heterogeneity of the DNA being transcribed, as well as on certain interactions of polymerase with specific DNA sequences. In order to describe the mechanism of regulation, we introduce the concept of heterogeneity into the previously proposed alternative models of elongation, power stroke and Brownian ratchet. We also discuss molecular origins and physiological significances of the heterogeneity.

A heritable symbiont and host-associated factors shape fungal endophyte communities across spatial scales

USDA-ARS?s Scientific Manuscript database

Microbial ecologists are intensely interested in the processes governing microbial community assembly, progress has been limited by a lack of studies that span multiple geographical scales and levels of biological organization. High throughput sequencing was used to characterize foliar fungal endoph...

Non-redundant patent sequence databases with value-added annotations at two levels

PubMed Central

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/. PMID:19884134

Non-redundant patent sequence databases with value-added annotations at two levels.

PubMed

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/.

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

On the Split Personality of Penultimate Proline

PubMed Central

Glover, Matthew S.; Shi, Liuqing; Fuller, Daniel R.; Arnold, Randy J.; Radivojac, Predrag; Clemmer, David E.

2014-01-01

The influence of the position of the amino acid proline in polypeptide sequences is examined by a combination of ion mobility spectrometry-mass spectrometry (IMS-MS), amino acid substitutions, and molecular modeling. The results suggest that when proline exists as the second residue from the N-terminus (i.e., penultimate proline), two families of conformers are formed. We demonstrate the existence of these families by a study of a series of truncated and mutated peptides derived from the 11-residue peptide Ser1-Pro2-Glu3-Leu4-Pro5-Ser6-Pro7-Gln8-Ala9-Glu10-Lys11. We find that every peptide from this sequence with a penultimate proline residue has multiple conformations. Substitution of Ala for Pro residues indicates that multiple conformers arise from the cis- trans isomerization of Xaa1–Pro2 peptide bonds as Xaa–Ala peptide bonds are unlikely to adopt the cis isomer, and examination of spectra from a library of 58 peptides indicates that ~80% of sequences show this effect. A simple mechanism suggesting that the barrier between the cis-and trans-proline forms is lowered because of low steric impedance is proposed. This observation may have interesting biological implications as well, and we note that a number of biologically active peptides have penultimate proline residues. PMID:25503299

Recombinant Collagenlike Proteins

NASA Technical Reports Server (NTRS)

Fertala, Andzej

2007-01-01

A group of collagenlike recombinant proteins containing high densities of biologically active sites has been invented. The method used to express these proteins is similar to a method of expressing recombinant procollagens and collagens described in U. S. Patent 5,593,859, "Synthesis of human procollagens and collagens in recombinant DNA systems." Customized collagenous proteins are needed for biomedical applications. In particular, fibrillar collagens are attractive for production of matrices needed for tissue engineering and drug delivery. Prior to this invention, there was no way of producing customized collagenous proteins for these and other applications. Heretofore, collagenous proteins have been produced by use of such biological systems as yeasts, bacteria, and transgenic animals and plants. These products are normal collagens that can also be extracted from such sources as tendons, bones, and hides. These products cannot be made to consist only of biologically active, specific amino acid sequences that may be needed for specific applications. Prior to this invention, it had been established that fibrillar collagens consist of domains that are responsible for such processes as interaction with cells, binding of growth factors, and interaction with a number of structural proteins present in the extracellular matrix. A normal collagen consists of a sequence of domains that can be represented by a corresponding sequence of labels, e.g., D1D2D3D4. A collagenlike protein of the present invention contains regions of collagen II that contain multiples of a single domain (e.g., D1D1D1D1 or D4D4D4D4) chosen for its specific biological activity. By virtue of the multiplicity of the chosen domain, the density of sites having that specific biological activity is greater than it is in a normal collagen. A collagenlike protein according to this invention can thus be made to have properties that are necessary for tissue engineering.

An ensemble approach for large-scale identification of protein-protein interactions using the alignments of multiple sequences

PubMed Central

Wang, Lei; You, Zhu-Hong; Chen, Xing; Li, Jian-Qiang; Yan, Xin; Zhang, Wei; Huang, Yu-An

2017-01-01

Protein–Protein Interactions (PPI) is not only the critical component of various biological processes in cells, but also the key to understand the mechanisms leading to healthy and diseased states in organisms. However, it is time-consuming and cost-intensive to identify the interactions among proteins using biological experiments. Hence, how to develop a more efficient computational method rapidly became an attractive topic in the post-genomic era. In this paper, we propose a novel method for inference of protein-protein interactions from protein amino acids sequences only. Specifically, protein amino acids sequence is firstly transformed into Position-Specific Scoring Matrix (PSSM) generated by multiple sequences alignments; then the Pseudo PSSM is used to extract feature descriptors. Finally, ensemble Rotation Forest (RF) learning system is trained to predict and recognize PPIs based solely on protein sequence feature. When performed the proposed method on the three benchmark data sets (Yeast, H. pylori, and independent dataset) for predicting PPIs, our method can achieve good average accuracies of 98.38%, 89.75%, and 96.25%, respectively. In order to further evaluate the prediction performance, we also compare the proposed method with other methods using same benchmark data sets. The experiment results demonstrate that the proposed method consistently outperforms other state-of-the-art method. Therefore, our method is effective and robust and can be taken as a useful tool in exploring and discovering new relationships between proteins. A web server is made publicly available at the URL http://202.119.201.126:8888/PsePSSM/ for academic use. PMID:28029645

Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications

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

Torella, JP; Lienert, F; Boehm, CR

2014-08-07

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts, and they hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies-for example, repeated terminator and insulator sequences-that complicate recombination-based assembly. We and others have recently developed DNA assembly methods, which we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked withmore » UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly assembled constructs, or into high-quality combinatorial libraries in only 2-3 d. If the DNA parts must be generated from scratch, an additional 2-5 d are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques.« less

Unique nucleotide sequence (UNS)-guided assembly of repetitive DNA parts for synthetic biology applications

PubMed Central

Torella, Joseph P.; Lienert, Florian; Boehm, Christian R.; Chen, Jan-Hung; Way, Jeffrey C.; Silver, Pamela A.

2016-01-01

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts and hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies — for example repeated terminator and insulator sequences — that complicate recombination-based assembly. We and others have recently developed DNA assembly methods that we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked with UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly-assembled constructs, or into high-quality combinatorial libraries in only 2–3 days. If the DNA parts must be generated from scratch, an additional 2–5 days are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques. PMID:25101822

COACH: profile-profile alignment of protein families using hidden Markov models.

PubMed

Edgar, Robert C; Sjölander, Kimmen

2004-05-22

Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile-profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence-sequence methods (such as BLAST) and profile-sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile-profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM. We compare the alignment accuracy of COACH with two recently published methods: Yona and Levitt's prof_sim and Sadreyev and Grishin's COMPASS. On two sets of reference alignments selected from the FSSP database, we find that COACH is able, on average, to produce alignments giving the best coverage or the fewest errors, depending on the chosen parameter settings. COACH is freely available from www.drive5.com/lobster

JavaScript DNA translator: DNA-aligned protein translations.

PubMed

Perry, William L

2002-12-01

There are many instances in molecular biology when it is necessary to identify ORFs in a DNA sequence. While programs exist for displaying protein translations in multiple ORFs in alignment with a DNA sequence, they are often expensive, exist as add-ons to software that must be purchased, or are only compatible with a particular operating system. JavaScript DNA Translator is a shareware application written in JavaScript, a scripting language interpreted by the Netscape Communicator and Internet Explorer Web browsers, which makes it compatible with several different operating systems. While the program uses a familiar Web page interface, it requires no connection to the Internet since calculations are performed on the user's own computer. The program analyzes one or multiple DNA sequences and generates translations in up to six reading frames aligned to a DNA sequence, in addition to displaying translations as separate sequences in FASTA format. ORFs within a reading frame can also be displayed as separate sequences. Flexible formatting options are provided, including the ability to hide ORFs below a minimum size specified by the user. The program is available free of charge at the BioTechniques Software Library (www.Biotechniques.com).

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read-Write Genome Evolution as an Active Biological Process.

PubMed

Shapiro, James A

2016-06-08

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess "Read-Write Genomes" they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification.

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read–Write Genome Evolution as an Active Biological Process

PubMed Central

Shapiro, James A.

2016-01-01

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess “Read–Write Genomes” they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification. PMID:27338490

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Recapitulating phylogenies using k-mers: from trees to networks.

PubMed

Bernard, Guillaume; Ragan, Mark A; Chan, Cheong Xin

2016-01-01

Ernst Haeckel based his landmark Tree of Life on the supposed ontogenic recapitulation of phylogeny, i.e. that successive embryonic stages during the development of an organism re-trace the morphological forms of its ancestors over the course of evolution. Much of this idea has since been discredited. Today, phylogenies are often based on families of molecular sequences. The standard approach starts with a multiple sequence alignment, in which the sequences are arranged relative to each other in a way that maximises a measure of similarity position-by-position along their entire length. A tree (or sometimes a network) is then inferred. Rigorous multiple sequence alignment is computationally demanding, and evolutionary processes that shape the genomes of many microbes (bacteria, archaea and some morphologically simple eukaryotes) can add further complications. In particular, recombination, genome rearrangement and lateral genetic transfer undermine the assumptions that underlie multiple sequence alignment, and imply that a tree-like structure may be too simplistic. Here, using genome sequences of 143 bacterial and archaeal genomes, we construct a network of phylogenetic relatedness based on the number of shared k -mers (subsequences at fixed length k ). Our findings suggest that the network captures not only key aspects of microbial genome evolution as inferred from a tree, but also features that are not treelike. The method is highly scalable, allowing for investigation of genome evolution across a large number of genomes. Instead of using specific regions or sequences from genome sequences, or indeed Haeckel's idea of ontogeny, we argue that genome phylogenies can be inferred using k -mers from whole-genome sequences. Representing these networks dynamically allows biological questions of interest to be formulated and addressed quickly and in a visually intuitive manner.

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/

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology

PubMed Central

Udy, Dylan B.; Voorhies, Mark; Chan, Patricia P.; Lowe, Todd M.; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes—and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics. PMID:26252667

Parallel Implementation of MAFFT on CUDA-Enabled Graphics Hardware.

PubMed

Zhu, Xiangyuan; Li, Kenli; Salah, Ahmad; Shi, Lin; Li, Keqin

2015-01-01

Multiple sequence alignment (MSA) constitutes an extremely powerful tool for many biological applications including phylogenetic tree estimation, secondary structure prediction, and critical residue identification. However, aligning large biological sequences with popular tools such as MAFFT requires long runtimes on sequential architectures. Due to the ever increasing sizes of sequence databases, there is increasing demand to accelerate this task. In this paper, we demonstrate how graphic processing units (GPUs), powered by the compute unified device architecture (CUDA), can be used as an efficient computational platform to accelerate the MAFFT algorithm. To fully exploit the GPU's capabilities for accelerating MAFFT, we have optimized the sequence data organization to eliminate the bandwidth bottleneck of memory access, designed a memory allocation and reuse strategy to make full use of limited memory of GPUs, proposed a new modified-run-length encoding (MRLE) scheme to reduce memory consumption, and used high-performance shared memory to speed up I/O operations. Our implementation tested in three NVIDIA GPUs achieves speedup up to 11.28 on a Tesla K20m GPU compared to the sequential MAFFT 7.015.

Draft De Novo Transcriptome of the Rat Kangaroo Potorous tridactylus as a Tool for Cell Biology.

PubMed

Udy, Dylan B; Voorhies, Mark; Chan, Patricia P; Lowe, Todd M; Dumont, Sophie

2015-01-01

The rat kangaroo (long-nosed potoroo, Potorous tridactylus) is a marsupial native to Australia. Cultured rat kangaroo kidney epithelial cells (PtK) are commonly used to study cell biological processes. These mammalian cells are large, adherent, and flat, and contain large and few chromosomes-and are thus ideal for imaging intra-cellular dynamics such as those of mitosis. Despite this, neither the rat kangaroo genome nor transcriptome have been sequenced, creating a challenge for probing the molecular basis of these cellular dynamics. Here, we present the sequencing, assembly and annotation of the draft rat kangaroo de novo transcriptome. We sequenced 679 million reads that mapped to 347,323 Trinity transcripts and 20,079 Unigenes. We present statistics emerging from transcriptome-wide analyses, and analyses suggesting that the transcriptome covers full-length sequences of most genes, many with multiple isoforms. We also validate our findings with a proof-of-concept gene knockdown experiment. We expect that this high quality transcriptome will make rat kangaroo cells a more tractable system for linking molecular-scale function and cellular-scale dynamics.

Rapid construction of insulated genetic circuits via synthetic sequence-guided isothermal assembly

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

Torella, JP; Boehm, CR; Lienert, F

2013-12-28

In vitro recombination methods have enabled one-step construction of large DNA sequences from multiple parts. Although synthetic biological circuits can in principle be assembled in the same fashion, they typically contain repeated sequence elements such as standard promoters and terminators that interfere with homologous recombination. Here we use a computational approach to design synthetic, biologically inactive unique nucleotide sequences (UNSes) that facilitate accurate ordered assembly. Importantly, our designed UNSes make it possible to assemble parts with repeated terminator and insulator sequences, and thereby create insulated functional genetic circuits in bacteria and mammalian cells. Using UNS-guided assembly to construct repeating promoter-gene-terminatormore » parts, we systematically varied gene expression to optimize production of a deoxychromoviridans biosynthetic pathway in Escherichia coli. We then used this system to construct complex eukaryotic AND-logic gates for genomic integration into embryonic stem cells. Construction was performed by using a standardized series of UNS-bearing BioBrick-compatible vectors, which enable modular assembly and facilitate reuse of individual parts. UNS-guided isothermal assembly is broadly applicable to the construction and optimization of genetic circuits and particularly those requiring tight insulation, such as complex biosynthetic pathways, sensors, counters and logic gates.« less

R3D-2-MSA: the RNA 3D structure-to-multiple sequence alignment server

PubMed Central

Cannone, Jamie J.; Sweeney, Blake A.; Petrov, Anton I.; Gutell, Robin R.; Zirbel, Craig L.; Leontis, Neocles

2015-01-01

The RNA 3D Structure-to-Multiple Sequence Alignment Server (R3D-2-MSA) is a new web service that seamlessly links RNA three-dimensional (3D) structures to high-quality RNA multiple sequence alignments (MSAs) from diverse biological sources. In this first release, R3D-2-MSA provides manual and programmatic access to curated, representative ribosomal RNA sequence alignments from bacterial, archaeal, eukaryal and organellar ribosomes, using nucleotide numbers from representative atomic-resolution 3D structures. A web-based front end is available for manual entry and an Application Program Interface for programmatic access. Users can specify up to five ranges of nucleotides and 50 nucleotide positions per range. The R3D-2-MSA server maps these ranges to the appropriate columns of the corresponding MSA and returns the contents of the columns, either for display in a web browser or in JSON format for subsequent programmatic use. The browser output page provides a 3D interactive display of the query, a full list of sequence variants with taxonomic information and a statistical summary of distinct sequence variants found. The output can be filtered and sorted in the browser. Previous user queries can be viewed at any time by resubmitting the output URL, which encodes the search and re-generates the results. The service is freely available with no login requirement at http://rna.bgsu.edu/r3d-2-msa. PMID:26048960

MACSIMS : multiple alignment of complete sequences information management system

PubMed Central

Thompson, Julie D; Muller, Arnaud; Waterhouse, Andrew; Procter, Jim; Barton, Geoffrey J; Plewniak, Frédéric; Poch, Olivier

2006-01-01

Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at . PMID:16792820

G-quadruplex dynamics.

PubMed

Harkness, Robert W; Mittermaier, Anthony K

2017-11-01

G-quadruplexes (GQs) are four-stranded nucleic acid secondary structures formed by guanosine (G)-rich DNA and RNA sequences. It is becoming increasingly clear that cellular processes including gene expression and mRNA translation are regulated by GQs. GQ structures have been extensively characterized, however little attention to date has been paid to their conformational dynamics, despite the fact that many biological GQ sequences populate multiple structures of similar free energies, leading to an ensemble of exchanging conformations. The impact of these dynamics on biological function is currently not well understood. Recently, structural dynamics have been demonstrated to entropically stabilize GQ ensembles, potentially modulating gene expression. Transient, low-populated states in GQ ensembles may additionally regulate nucleic acid interactions and function. This review will underscore the interplay of GQ dynamics and biological function, focusing on several dynamic processes for biological GQs and the characterization of GQ dynamics by nuclear magnetic resonance (NMR) spectroscopy in conjunction with other biophysical techniques. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

Fusagene vectors: a novel strategy for the expression of multiple genes from a single cistron.

PubMed

Gäken, J; Jiang, J; Daniel, K; van Berkel, E; Hughes, C; Kuiper, M; Darling, D; Tavassoli, M; Galea-Lauri, J; Ford, K; Kemeny, M; Russell, S; Farzaneh, F

2000-12-01

Transduction of cells with multiple genes, allowing their stable and co-ordinated expression, is difficult with the available methodologies. A method has been developed for expression of multiple gene products, as fusion proteins, from a single cistron. The encoded proteins are post-synthetically cleaved and processed into each of their constituent proteins as individual, biologically active factors. Specifically, linkers encoding cleavage sites for the Golgi expressed endoprotease, furin, have been incorporated between in-frame cDNA sequences encoding different secreted or membrane bound proteins. With this strategy we have developed expression vectors encoding multiple proteins (IL-2 and B7.1, IL-4 and B7.1, IL-4 and IL-2, IL-12 p40 and p35, and IL-12 p40, p35 and IL-2 ). Transduction and analysis of over 100 individual clones, derived from murine and human tumour cell lines, demonstrate the efficient expression and biological activity of each of the encoded proteins. Fusagene vectors enable the co-ordinated expression of multiple gene products from a single, monocistronic, expression cassette.

Biopython: freely available Python tools for computational molecular biology and bioinformatics.

PubMed

Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T; Chapman, Brad A; Cox, Cymon J; Dalke, Andrew; Friedberg, Iddo; Hamelryck, Thomas; Kauff, Frank; Wilczynski, Bartek; de Hoon, Michiel J L

2009-06-01

The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Biopython is freely available, with documentation and source code at (www.biopython.org) under the Biopython license.

Conservation of hot regions in protein-protein interaction in evolution.

PubMed

Hu, Jing; Li, Jiarui; Chen, Nansheng; Zhang, Xiaolong

2016-11-01

The hot regions of protein-protein interactions refer to the active area which formed by those most important residues to protein combination process. With the research development on protein interactions, lots of predicted hot regions can be discovered efficiently by intelligent computing methods, while performing biology experiments to verify each every prediction is hardly to be done due to the time-cost and the complexity of the experiment. This study based on the research of hot spot residue conservations, the proposed method is used to verify authenticity of predicted hot regions that using machine learning algorithm combined with protein's biological features and sequence conservation, though multiple sequence alignment, module substitute matrix and sequence similarity to create conservation scoring algorithm, and then using threshold module to verify the conservation tendency of hot regions in evolution. This research work gives an effective method to verify predicted hot regions in protein-protein interactions, which also provides a useful way to deeply investigate the functional activities of protein hot regions. Copyright © 2016. Published by Elsevier Inc.

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Multiplexed Sequence Encoding: A Framework for DNA Communication.

PubMed

Zakeri, Bijan; Carr, Peter A; Lu, Timothy K

2016-01-01

Synthetic DNA has great propensity for efficiently and stably storing non-biological information. With DNA writing and reading technologies rapidly advancing, new applications for synthetic DNA are emerging in data storage and communication. Traditionally, DNA communication has focused on the encoding and transfer of complete sets of information. Here, we explore the use of DNA for the communication of short messages that are fragmented across multiple distinct DNA molecules. We identified three pivotal points in a communication-data encoding, data transfer & data extraction-and developed novel tools to enable communication via molecules of DNA. To address data encoding, we designed DNA-based individualized keyboards (iKeys) to convert plaintext into DNA, while reducing the occurrence of DNA homopolymers to improve synthesis and sequencing processes. To address data transfer, we implemented a secret-sharing system-Multiplexed Sequence Encoding (MuSE)-that conceals messages between multiple distinct DNA molecules, requiring a combination key to reveal messages. To address data extraction, we achieved the first instance of chromatogram patterning through multiplexed sequencing, thereby enabling a new method for data extraction. We envision these approaches will enable more widespread communication of information via DNA.

Biclustering as a method for RNA local multiple sequence alignment.

PubMed

Wang, Shu; Gutell, Robin R; Miranker, Daniel P

2007-12-15

Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment; precisely the kind of dual situation biclustering is intended to address. We define a representation of the MSA problem enabling the application of biclustering algorithms. We develop a computer program for local MSA, BlockMSA, that combines biclustering with divide-and-conquer. BlockMSA simultaneously finds groups of similar sequences and locally aligns subsequences within them. Further alignment is accomplished by dividing both the set of sequences and their contents. The net result is both a multiple sequence alignment and a hierarchical clustering of the sequences. BlockMSA was tested on the subsets of the BRAliBase 2.1 benchmark suite that display high variability and on an extension to that suite to larger problem sizes. Also, alignments were evaluated of two large datasets of current biological interest, T box sequences and Group IC1 Introns. The results were compared with alignments computed by ClustalW, MAFFT, MUCLE and PROBCONS alignment programs using Sum of Pairs (SPS) and Consensus Count. Results for the benchmark suite are sensitive to problem size. On problems of 15 or greater sequences, BlockMSA is consistently the best. On none of the problems in the test suite are there appreciable differences in scores among BlockMSA, MAFFT and PROBCONS. On the T box sequences, BlockMSA does the most faithful job of reproducing known annotations. MAFFT and PROBCONS do not. On the Intron sequences, BlockMSA, MAFFT and MUSCLE are comparable at identifying conserved regions. BlockMSA is implemented in Java. Source code and supplementary datasets are available at http://aug.csres.utexas.edu/msa/

Decoding the Heart through Next Generation Sequencing Approaches.

PubMed

Pawlak, Michal; Niescierowicz, Katarzyna; Winata, Cecilia Lanny

2018-06-07

: Vertebrate organs develop through a complex process which involves interaction between multiple signaling pathways at the molecular, cell, and tissue levels. Heart development is an example of such complex process which, when disrupted, results in congenital heart disease (CHD). This complexity necessitates a holistic approach which allows the visualization of genome-wide interaction networks, as opposed to assessment of limited subsets of factors. Genomics offers a powerful solution to address the problem of biological complexity by enabling the observation of molecular processes at a genome-wide scale. The emergence of next generation sequencing (NGS) technology has facilitated the expansion of genomics, increasing its output capacity and applicability in various biological disciplines. The application of NGS in various aspects of heart biology has resulted in new discoveries, generating novel insights into this field of study. Here we review the contributions of NGS technology into the understanding of heart development and its disruption reflected in CHD and discuss how emerging NGS based methodologies can contribute to the further understanding of heart repair.

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.

GibbsCluster: unsupervised clustering and alignment of peptide sequences.

PubMed

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-07-03

Receptor interactions with short linear peptide fragments (ligands) are at the base of many biological signaling processes. Conserved and information-rich amino acid patterns, commonly called sequence motifs, shape and regulate these interactions. Because of the properties of a receptor-ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Methods for open innovation on a genome-design platform associating scientific, commercial, and educational communities in synthetic biology.

PubMed

Toyoda, Tetsuro

2011-01-01

Synthetic biology requires both engineering efficiency and compliance with safety guidelines and ethics. Focusing on the rational construction of biological systems based on engineering principles, synthetic biology depends on a genome-design platform to explore the combinations of multiple biological components or BIO bricks for quickly producing innovative devices. This chapter explains the differences among various platform models and details a methodology for promoting open innovation within the scope of the statutory exemption of patent laws. The detailed platform adopts a centralized evaluation model (CEM), computer-aided design (CAD) bricks, and a freemium model. It is also important for the platform to support the legal aspects of copyrights as well as patent and safety guidelines because intellectual work including DNA sequences designed rationally by human intelligence is basically copyrightable. An informational platform with high traceability, transparency, auditability, and security is required for copyright proof, safety compliance, and incentive management for open innovation in synthetic biology. GenoCon, which we have organized and explained here, is a competition-styled, open-innovation method involving worldwide participants from scientific, commercial, and educational communities that aims to improve the designs of genomic sequences that confer a desired function on an organism. Using only a Web browser, a participating contributor proposes a design expressed with CAD bricks that generate a relevant DNA sequence, which is then experimentally and intensively evaluated by the GenoCon organizers. The CAD bricks that comprise programs and databases as a Semantic Web are developed, executed, shared, reused, and well stocked on the secure Semantic Web platform called the Scientists' Networking System or SciNetS/SciNeS, based on which a CEM research center for synthetic biology and open innovation should be established. Copyright © 2011 Elsevier Inc. All rights reserved.

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

A Guide to the PLAZA 3.0 Plant Comparative Genomic Database.

PubMed

Vandepoele, Klaas

2017-01-01

PLAZA 3.0 is an online resource for comparative genomics and offers a versatile platform to study gene functions and gene families or to analyze genome organization and evolution in the green plant lineage. Starting from genome sequence information for over 35 plant species, precomputed comparative genomic data sets cover homologous gene families, multiple sequence alignments, phylogenetic trees, and genomic colinearity information within and between species. Complementary functional data sets, a Workbench, and interactive visualization tools are available through a user-friendly web interface, making PLAZA an excellent starting point to translate sequence or omics data sets into biological knowledge. PLAZA is available at http://bioinformatics.psb.ugent.be/plaza/ .

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.

Change in IgHV Mutational Status of CLL Suggests Origin From Multiple Clones.

PubMed

Osman, Afaf; Gocke, Christopher D; Gladstone, Douglas E

2017-02-01

Fluorescence in situ hybridization and immunoglobulin (Ig) heavy-chain variable-region (IgHV) mutational status are used to predict outcome in chronic lymphocytic leukemia (CLL). Although DNA aberrations change over time, IgHV sequences and mutational status are considered stable. In a retrospective review, 409 CLL patients, between 2008 and 2015, had IgHV analysis: 56 patients had multiple analyses performed. Seven patients' IgHV results changed: 2 from unmutated to mutated and 5 from mutated to unmutated IgHV sequence. Three concurrently changed their variable heavy-chain sequence. Secondary to allelic exclusion, 2 of the new variable heavy chains produced were biologically nonplausible. The existence of these new nonplausible heavy-chain variable regions suggests either the CLL cancer stem-cell maintains the ability to rearrange a previously silenced IgH allele or more likely that the cancer stem-cell produced at least 2 subclones, suggesting that the CLL cancer stem cell exists before the process of allelic exclusion occurs. Copyright © 2016 Elsevier Inc. All rights reserved.

WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches

PubMed Central

Romer, Katherine A.; Kayombya, Guy-Richard; Fraenkel, Ernest

2007-01-01

WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs. PMID:17584794

PipeOnline 2.0: automated EST processing and functional data sorting.

PubMed

Ayoubi, Patricia; Jin, Xiaojing; Leite, Saul; Liu, Xianghui; Martajaja, Jeson; Abduraham, Abdurashid; Wan, Qiaolan; Yan, Wei; Misawa, Eduardo; Prade, Rolf A

2002-11-01

Expressed sequence tags (ESTs) are generated and deposited in the public domain, as redundant, unannotated, single-pass reactions, with virtually no biological content. PipeOnline automatically analyses and transforms large collections of raw DNA-sequence data from chromatograms or FASTA files by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene EST data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. Records are examined through a function ordered browser or keyword queries with automated export of results. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service. PipeOnline is available at http://stress-genomics.org.

Highly multiplexed targeted DNA sequencing from single nuclei.

PubMed

Leung, Marco L; Wang, Yong; Kim, Charissa; Gao, Ruli; Jiang, Jerry; Sei, Emi; Navin, Nicholas E

2016-02-01

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.

From biomedicine to natural history research: EST resources for ambystomatid salamanders

PubMed Central

Putta, Srikrishna; Smith, Jeramiah J; Walker, John A; Rondet, Mathieu; Weisrock, David W; Monaghan, James; Samuels, Amy K; Kump, Kevin; King, David C; Maness, Nicholas J; Habermann, Bianca; Tanaka, Elly; Bryant, Susan V; Gardiner, David M; Parichy, David M; Voss, S Randal

2004-01-01

Background Establishing genomic resources for closely related species will provide comparative insights that are crucial for understanding diversity and variability at multiple levels of biological organization. We developed ESTs for Mexican axolotl (Ambystoma mexicanum) and Eastern tiger salamander (A. tigrinum tigrinum), species with deep and diverse research histories. Results Approximately 40,000 quality cDNA sequences were isolated for these species from various tissues, including regenerating limb and tail. These sequences and an existing set of 16,030 cDNA sequences for A. mexicanum were processed to yield 35,413 and 20,599 high quality ESTs for A. mexicanum and A. t. tigrinum, respectively. Because the A. t. tigrinum ESTs were obtained primarily from a normalized library, an approximately equal number of contigs were obtained for each species, with 21,091 unique contigs identified overall. The 10,592 contigs that showed significant similarity to sequences from the human RefSeq database reflected a diverse array of molecular functions and biological processes, with many corresponding to genes expressed during spinal cord injury in rat and fin regeneration in zebrafish. To demonstrate the utility of these EST resources, we searched databases to identify probes for regeneration research, characterized intra- and interspecific nucleotide polymorphism, saturated a human – Ambystoma synteny group with marker loci, and extended PCR primer sets designed for A. mexicanum / A. t. tigrinum orthologues to a related tiger salamander species. Conclusions Our study highlights the value of developing resources in traditional model systems where the likelihood of information transfer to multiple, closely related taxa is high, thus simultaneously enabling both laboratory and natural history research. PMID:15310388

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.

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.

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

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.

Generalized causal mediation and path analysis: Extensions and practical considerations.

PubMed

Albert, Jeffrey M; Cho, Jang Ik; Liu, Yiying; Nelson, Suchitra

2018-01-01

Causal mediation analysis seeks to decompose the effect of a treatment or exposure among multiple possible paths and provide casually interpretable path-specific effect estimates. Recent advances have extended causal mediation analysis to situations with a sequence of mediators or multiple contemporaneous mediators. However, available methods still have limitations, and computational and other challenges remain. The present paper provides an extended causal mediation and path analysis methodology. The new method, implemented in the new R package, gmediation (described in a companion paper), accommodates both a sequence (two stages) of mediators and multiple mediators at each stage, and allows for multiple types of outcomes following generalized linear models. The methodology can also handle unsaturated models and clustered data. Addressing other practical issues, we provide new guidelines for the choice of a decomposition, and for the choice of a reference group multiplier for the reduction of Monte Carlo error in mediation formula computations. The new method is applied to data from a cohort study to illuminate the contribution of alternative biological and behavioral paths in the effect of socioeconomic status on dental caries in adolescence.

R3D-2-MSA: the RNA 3D structure-to-multiple sequence alignment server.

PubMed

Cannone, Jamie J; Sweeney, Blake A; Petrov, Anton I; Gutell, Robin R; Zirbel, Craig L; Leontis, Neocles

2015-07-01

The RNA 3D Structure-to-Multiple Sequence Alignment Server (R3D-2-MSA) is a new web service that seamlessly links RNA three-dimensional (3D) structures to high-quality RNA multiple sequence alignments (MSAs) from diverse biological sources. In this first release, R3D-2-MSA provides manual and programmatic access to curated, representative ribosomal RNA sequence alignments from bacterial, archaeal, eukaryal and organellar ribosomes, using nucleotide numbers from representative atomic-resolution 3D structures. A web-based front end is available for manual entry and an Application Program Interface for programmatic access. Users can specify up to five ranges of nucleotides and 50 nucleotide positions per range. The R3D-2-MSA server maps these ranges to the appropriate columns of the corresponding MSA and returns the contents of the columns, either for display in a web browser or in JSON format for subsequent programmatic use. The browser output page provides a 3D interactive display of the query, a full list of sequence variants with taxonomic information and a statistical summary of distinct sequence variants found. The output can be filtered and sorted in the browser. Previous user queries can be viewed at any time by resubmitting the output URL, which encodes the search and re-generates the results. The service is freely available with no login requirement at http://rna.bgsu.edu/r3d-2-msa. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integration of bioinformatics into an undergraduate biology curriculum and the impact on development of mathematical skills.

PubMed

Wightman, Bruce; Hark, Amy T

2012-01-01

The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this study, we deliberately integrated bioinformatics instruction at multiple course levels into an existing biology curriculum. Students in an introductory biology course, intermediate lab courses, and advanced project-oriented courses all participated in new course components designed to sequentially introduce bioinformatics skills and knowledge, as well as computational approaches that are common to many bioinformatics applications. In each course, bioinformatics learning was embedded in an existing disciplinary instructional sequence, as opposed to having a single course where all bioinformatics learning occurs. We designed direct and indirect assessment tools to follow student progress through the course sequence. Our data show significant gains in both student confidence and ability in bioinformatics during individual courses and as course level increases. Despite evidence of substantial student learning in both bioinformatics and mathematics, students were skeptical about the link between learning bioinformatics and learning mathematics. While our approach resulted in substantial learning gains, student "buy-in" and engagement might be better in longer project-based activities that demand application of skills to research problems. Nevertheless, in situations where a concentrated focus on project-oriented bioinformatics is not possible or desirable, our approach of integrating multiple smaller components into an existing curriculum provides an alternative. Copyright © 2012 Wiley Periodicals, Inc.

Multiple criteria-based screening of Trichoderma isolates for biological control of Botrytis cinerea on tomato

USDA-ARS?s Scientific Manuscript database

Seventy-two isolates of Trichoderma were obtained from Hubei Province of China and identified to species based on the ITS-rDNA sequences. The isolates were initially tested for invasive growth on the colonies of Botrytis cinerea in the dual cultures with B. cinerea on potato dextrose agar at 20°C. T...

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

Droplet microfluidics for synthetic biology

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

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Droplet microfluidics for synthetic biology

DOE PAGES

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee; ...

2017-08-10

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

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

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.

Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

A dynamic bead-based microarray for parallel DNA detection

NASA Astrophysics Data System (ADS)

Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

2011-05-01

A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

BIOZON: a system for unification, management and analysis of heterogeneous biological data.

PubMed

Birkland, Aaron; Yona, Golan

2006-02-15

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.

Learning multiple variable-speed sequences in striatum via cortical tutoring.

PubMed

Murray, James M; Escola, G Sean

2017-05-08

Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.

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.

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

CisSERS: Customizable in silico sequence evaluation for restriction sites

DOE PAGES

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus; ...

2016-04-12

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

CisSERS: Customizable in silico sequence evaluation for restriction sites

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

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

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

PubMed

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

2017-11-01

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

Holding a grudge

PubMed Central

Mick, Eran; Stern, Adi; Sorek, Rotem

2013-01-01

The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated) system of bacteria and archaea constitutes a mechanism of acquired adaptive immunity against phages, which is based on genome-encoded markers of previously infecting phage sequences (“spacers”). As a repository of phage sequences, these spacers make the system particularly suitable for elucidating phage-bacteria interactions in metagenomic studies. Recent metagenomic analyses of CRISPRs associated with the human microbiome intriguingly revealed conserved “memory spacers” shared by bacteria in multiple unrelated, geographically separated individuals. Here, we discuss possible avenues for explaining this phenomenon by integrating insights from CRISPR biology and phage-bacteria ecology, with a special focus on the human gut. We further explore the growing body of evidence for the role of CRISPR/Cas in regulating the interplay between bacteria and lysogenic phages, which may be intimately related to the presence of memory spacers and sheds new light on the multifaceted biological and ecological modes of action of CRISPR/Cas. PMID:23439321

Multiplexed Sequence Encoding: A Framework for DNA Communication

PubMed Central

Zakeri, Bijan; Carr, Peter A.; Lu, Timothy K.

2016-01-01

Synthetic DNA has great propensity for efficiently and stably storing non-biological information. With DNA writing and reading technologies rapidly advancing, new applications for synthetic DNA are emerging in data storage and communication. Traditionally, DNA communication has focused on the encoding and transfer of complete sets of information. Here, we explore the use of DNA for the communication of short messages that are fragmented across multiple distinct DNA molecules. We identified three pivotal points in a communication—data encoding, data transfer & data extraction—and developed novel tools to enable communication via molecules of DNA. To address data encoding, we designed DNA-based individualized keyboards (iKeys) to convert plaintext into DNA, while reducing the occurrence of DNA homopolymers to improve synthesis and sequencing processes. To address data transfer, we implemented a secret-sharing system—Multiplexed Sequence Encoding (MuSE)—that conceals messages between multiple distinct DNA molecules, requiring a combination key to reveal messages. To address data extraction, we achieved the first instance of chromatogram patterning through multiplexed sequencing, thereby enabling a new method for data extraction. We envision these approaches will enable more widespread communication of information via DNA. PMID:27050646

GenomeGems: evaluation of genetic variability from deep sequencing data

PubMed Central

2012-01-01

Background Detection of disease-causing mutations using Deep Sequencing technologies possesses great challenges. In particular, organizing the great amount of sequences generated so that mutations, which might possibly be biologically relevant, are easily identified is a difficult task. Yet, for this assignment only limited automatic accessible tools exist. Findings We developed GenomeGems to gap this need by enabling the user to view and compare Single Nucleotide Polymorphisms (SNPs) from multiple datasets and to load the data onto the UCSC Genome Browser for an expanded and familiar visualization. As such, via automatic, clear and accessible presentation of processed Deep Sequencing data, our tool aims to facilitate ranking of genomic SNP calling. GenomeGems runs on a local Personal Computer (PC) and is freely available at http://www.tau.ac.il/~nshomron/GenomeGems. Conclusions GenomeGems enables researchers to identify potential disease-causing SNPs in an efficient manner. This enables rapid turnover of information and leads to further experimental SNP validation. The tool allows the user to compare and visualize SNPs from multiple experiments and to easily load SNP data onto the UCSC Genome browser for further detailed information. PMID:22748151

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

Sequencing of a QTL-rich region of the Theobroma cacao genome using pooled BACs and the identification of trait specific candidate genes

PubMed Central

2011-01-01

Background BAC-based physical maps provide for sequencing across an entire genome or a selected sub-genomic region of biological interest. Such a region can be approached with next-generation whole-genome sequencing and assembly as if it were an independent small genome. Using the minimum tiling path as a guide, specific BAC clones representing the prioritized genomic interval are selected, pooled, and used to prepare a sequencing library. Results This pooled BAC approach was taken to sequence and assemble a QTL-rich region, of ~3 Mbp and represented by twenty-seven BACs, on linkage group 5 of the Theobroma cacao cv. Matina 1-6 genome. Using various mixtures of read coverages from paired-end and linear 454 libraries, multiple assemblies of varied quality were generated. Quality was assessed by comparing the assembly of 454 reads with a subset of ten BACs individually sequenced and assembled using Sanger reads. A mixture of reads optimal for assembly was identified. We found, furthermore, that a quality assembly suitable for serving as a reference genome template could be obtained even with a reduced depth of sequencing coverage. Annotation of the resulting assembly revealed several genes potentially responsible for three T. cacao traits: black pod disease resistance, bean shape index, and pod weight. Conclusions Our results, as with other pooled BAC sequencing reports, suggest that pooling portions of a minimum tiling path derived from a BAC-based physical map is an effective method to target sub-genomic regions for sequencing. While we focused on a single QTL region, other QTL regions of importance could be similarly sequenced allowing for biological discovery to take place before a high quality whole-genome assembly is completed. PMID:21794110

Sequencing of a QTL-rich region of the Theobroma cacao genome using pooled BACs and the identification of trait specific candidate genes.

PubMed

Feltus, Frank A; Saski, Christopher A; Mockaitis, Keithanne; Haiminen, Niina; Parida, Laxmi; Smith, Zachary; Ford, James; Staton, Margaret E; Ficklin, Stephen P; Blackmon, Barbara P; Cheng, Chun-Huai; Schnell, Raymond J; Kuhn, David N; Motamayor, Juan-Carlos

2011-07-27

BAC-based physical maps provide for sequencing across an entire genome or a selected sub-genomic region of biological interest. Such a region can be approached with next-generation whole-genome sequencing and assembly as if it were an independent small genome. Using the minimum tiling path as a guide, specific BAC clones representing the prioritized genomic interval are selected, pooled, and used to prepare a sequencing library. This pooled BAC approach was taken to sequence and assemble a QTL-rich region, of ~3 Mbp and represented by twenty-seven BACs, on linkage group 5 of the Theobroma cacao cv. Matina 1-6 genome. Using various mixtures of read coverages from paired-end and linear 454 libraries, multiple assemblies of varied quality were generated. Quality was assessed by comparing the assembly of 454 reads with a subset of ten BACs individually sequenced and assembled using Sanger reads. A mixture of reads optimal for assembly was identified. We found, furthermore, that a quality assembly suitable for serving as a reference genome template could be obtained even with a reduced depth of sequencing coverage. Annotation of the resulting assembly revealed several genes potentially responsible for three T. cacao traits: black pod disease resistance, bean shape index, and pod weight. Our results, as with other pooled BAC sequencing reports, suggest that pooling portions of a minimum tiling path derived from a BAC-based physical map is an effective method to target sub-genomic regions for sequencing. While we focused on a single QTL region, other QTL regions of importance could be similarly sequenced allowing for biological discovery to take place before a high quality whole-genome assembly is completed.

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.

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

Chromosome Evolution in Connection with Repetitive Sequences and Epigenetics in Plants.

PubMed

Li, Shu-Fen; Su, Ting; Cheng, Guang-Qian; Wang, Bing-Xiao; Li, Xu; Deng, Chuan-Liang; Gao, Wu-Jun

2017-10-24

Chromosome evolution is a fundamental aspect of evolutionary biology. The evolution of chromosome size, structure and shape, number, and the change in DNA composition suggest the high plasticity of nuclear genomes at the chromosomal level. Repetitive DNA sequences, which represent a conspicuous fraction of every eukaryotic genome, particularly in plants, are found to be tightly linked with plant chromosome evolution. Different classes of repetitive sequences have distinct distribution patterns on the chromosomes. Mounting evidence shows that repetitive sequences may play multiple generative roles in shaping the chromosome karyotypes in plants. Furthermore, recent development in our understanding of the repetitive sequences and plant chromosome evolution has elucidated the involvement of a spectrum of epigenetic modification. In this review, we focused on the recent evidence relating to the distribution pattern of repetitive sequences in plant chromosomes and highlighted their potential relevance to chromosome evolution in plants. We also discussed the possible connections between evolution and epigenetic alterations in chromosome structure and repatterning, such as heterochromatin formation, centromere function, and epigenetic-associated transposable element inactivation.

Blueprints for green biotech: development and application of standards for plant synthetic biology.

PubMed

Patron, Nicola J

2016-06-15

Synthetic biology aims to apply engineering principles to the design and modification of biological systems and to the construction of biological parts and devices. The ability to programme cells by providing new instructions written in DNA is a foundational technology of the field. Large-scale de novo DNA synthesis has accelerated synthetic biology by offering custom-made molecules at ever decreasing costs. However, for large fragments and for experiments in which libraries of DNA sequences are assembled in different combinations, assembly in the laboratory is still desirable. Biological assembly standards allow DNA parts, even those from multiple laboratories and experiments, to be assembled together using the same reagents and protocols. The adoption of such standards for plant synthetic biology has been cohesive for the plant science community, facilitating the application of genome editing technologies to plant systems and streamlining progress in large-scale, multi-laboratory bioengineering projects. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

Low-pass sequencing for microbial comparative genomics

PubMed Central

Goo, Young Ah; Roach, Jared; Glusman, Gustavo; Baliga, Nitin S; Deutsch, Kerry; Pan, Min; Kennedy, Sean; DasSarma, Shiladitya; Victor Ng, Wailap; Hood, Leroy

2004-01-01

Background We studied four extremely halophilic archaea by low-pass shotgun sequencing: (1) the metabolically versatile Haloarcula marismortui; (2) the non-pigmented Natrialba asiatica; (3) the psychrophile Halorubrum lacusprofundi and (4) the Dead Sea isolate Halobaculum gomorrense. Approximately one thousand single pass genomic sequences per genome were obtained. The data were analyzed by comparative genomic analyses using the completed Halobacterium sp. NRC-1 genome as a reference. Low-pass shotgun sequencing is a simple, inexpensive, and rapid approach that can readily be performed on any cultured microbe. Results As expected, the four archaeal halophiles analyzed exhibit both bacterial and eukaryotic characteristics as well as uniquely archaeal traits. All five halophiles exhibit greater than sixty percent GC content and low isoelectric points (pI) for their predicted proteins. Multiple insertion sequence (IS) elements, often involved in genome rearrangements, were identified in H. lacusprofundi and H. marismortui. The core biological functions that govern cellular and genetic mechanisms of H. sp. NRC-1 appear to be conserved in these four other halophiles. Multiple TATA box binding protein (TBP) and transcription factor IIB (TFB) homologs were identified from most of the four shotgunned halophiles. The reconstructed molecular tree of all five halophiles shows a large divergence between these species, but with the closest relationship being between H. sp. NRC-1 and H. lacusprofundi. Conclusion Despite the diverse habitats of these species, all five halophiles share (1) high GC content and (2) low protein isoelectric points, which are characteristics associated with environmental exposure to UV radiation and hypersalinity, respectively. Identification of multiple IS elements in the genome of H. lacusprofundi and H. marismortui suggest that genome structure and dynamic genome reorganization might be similar to that previously observed in the IS-element rich genome of H. sp. NRC-1. Identification of multiple TBP and TFB homologs in these four halophiles are consistent with the hypothesis that different types of complex transcriptional regulation may occur through multiple TBP-TFB combinations in response to rapidly changing environmental conditions. Low-pass shotgun sequence analyses of genomes permit extensive and diverse analyses, and should be generally useful for comparative microbial genomics. PMID:14718067

Simultaneous knockdown of six non-family genes using a single synthetic RNAi fragment in Arabidopsis thaliana

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

Czarnecki, Olaf; Bryan, Anthony C.; Jawdy, Sara S.

Genetic engineering of plants that results in successful establishment of new biochemical or regulatory pathways requires stable introduction of one or more genes into the plant genome. It might also be necessary to down-regulate or turn off expression of endogenous genes in order to reduce activity of competing pathways. An established way to knockdown gene expression in plants is expressing a hairpin-RNAi construct, eventually leading to degradation of a specifically targeted mRNA. Knockdown of multiple genes that do not share homologous sequences is still challenging and involves either sophisticated cloning strategies to create vectors with different serial expression constructs ormore » multiple transformation events that is often restricted by a lack of available transformation markers. Synthetic RNAi fragments were assembled in yeast carrying homologous sequences to six or seven non-family genes and introduced into pAGRIKOLA. Transformation of Arabidopsis thaliana and subsequent expression analysis of targeted genes proved efficient knockdown of all target genes. In conclusion, we present a simple and cost-effective method to create constructs to simultaneously knockdown multiple non-family genes or genes that do not share sequence homology. The presented method can be applied in plant and animal synthetic biology as well as traditional plant and animal genetic engineering.« less

QuickNGS elevates Next-Generation Sequencing data analysis to a new level of automation.

PubMed

Wagle, Prerana; Nikolić, Miloš; Frommolt, Peter

2015-07-01

Next-Generation Sequencing (NGS) has emerged as a widely used tool in molecular biology. While time and cost for the sequencing itself are decreasing, the analysis of the massive amounts of data remains challenging. Since multiple algorithmic approaches for the basic data analysis have been developed, there is now an increasing need to efficiently use these tools to obtain results in reasonable time. We have developed QuickNGS, a new workflow system for laboratories with the need to analyze data from multiple NGS projects at a time. QuickNGS takes advantage of parallel computing resources, a comprehensive back-end database, and a careful selection of previously published algorithmic approaches to build fully automated data analysis workflows. We demonstrate the efficiency of our new software by a comprehensive analysis of 10 RNA-Seq samples which we can finish in only a few minutes of hands-on time. The approach we have taken is suitable to process even much larger numbers of samples and multiple projects at a time. Our approach considerably reduces the barriers that still limit the usability of the powerful NGS technology and finally decreases the time to be spent before proceeding to further downstream analysis and interpretation of the data.

Simultaneous knockdown of six non-family genes using a single synthetic RNAi fragment in Arabidopsis thaliana

DOE PAGES

Czarnecki, Olaf; Bryan, Anthony C.; Jawdy, Sara S.; ...

2016-02-17

Genetic engineering of plants that results in successful establishment of new biochemical or regulatory pathways requires stable introduction of one or more genes into the plant genome. It might also be necessary to down-regulate or turn off expression of endogenous genes in order to reduce activity of competing pathways. An established way to knockdown gene expression in plants is expressing a hairpin-RNAi construct, eventually leading to degradation of a specifically targeted mRNA. Knockdown of multiple genes that do not share homologous sequences is still challenging and involves either sophisticated cloning strategies to create vectors with different serial expression constructs ormore » multiple transformation events that is often restricted by a lack of available transformation markers. Synthetic RNAi fragments were assembled in yeast carrying homologous sequences to six or seven non-family genes and introduced into pAGRIKOLA. Transformation of Arabidopsis thaliana and subsequent expression analysis of targeted genes proved efficient knockdown of all target genes. In conclusion, we present a simple and cost-effective method to create constructs to simultaneously knockdown multiple non-family genes or genes that do not share sequence homology. The presented method can be applied in plant and animal synthetic biology as well as traditional plant and animal genetic engineering.« less

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 .

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.

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.

The Genome Portal of the Department of Energy Joint Genome Institute

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

Nordberg, Henrik; Cantor, Michael; Dushekyo, Serge

2014-03-14

The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Genome Portal in the past 2 years was significantly updated, with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI. A critical aspect of handling big data in genomics is the development of visualization and analysis tools that allow scientists to derive meaning from what are otherwise terrabases ofmore » inert sequence. An interactive visualization tool developed in the group allows us to explore contigs resulting from a single metagenome assembly. Implemented with modern web technologies that take advantage of the power of the computer's graphical processing unit (gpu), the tool allows the user to easily navigate over a 100,000 data points in multiple dimensions, among many biologically meaningful parameters of a dataset such as relative abundance, contig length, and G+C content.« less

ARTS: automated randomization of multiple traits for study design.

PubMed

Maienschein-Cline, Mark; Lei, Zhengdeng; Gardeux, Vincent; Abbasi, Taimur; Machado, Roberto F; Gordeuk, Victor; Desai, Ankit A; Saraf, Santosh; Bahroos, Neil; Lussier, Yves

2014-06-01

Collecting data from large studies on high-throughput platforms, such as microarray or next-generation sequencing, typically requires processing samples in batches. There are often systematic but unpredictable biases from batch-to-batch, so proper randomization of biologically relevant traits across batches is crucial for distinguishing true biological differences from experimental artifacts. When a large number of traits are biologically relevant, as is common for clinical studies of patients with varying sex, age, genotype and medical background, proper randomization can be extremely difficult to prepare by hand, especially because traits may affect biological inferences, such as differential expression, in a combinatorial manner. Here we present ARTS (automated randomization of multiple traits for study design), which aids researchers in study design by automatically optimizing batch assignment for any number of samples, any number of traits and any batch size. ARTS is implemented in Perl and is available at github.com/mmaiensc/ARTS. ARTS is also available in the Galaxy Tool Shed, and can be used at the Galaxy installation hosted by the UIC Center for Research Informatics (CRI) at galaxy.cri.uic.edu. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Characterisation of minimalist co-assembled fluorenylmethyloxycarbonyl self-assembling peptide systems for presentation of multiple bioactive peptides.

PubMed

Horgan, Conor C; Rodriguez, Alexandra L; Li, Rui; Bruggeman, Kiara F; Stupka, Nicole; Raynes, Jared K; Day, Li; White, John W; Williams, Richard J; Nisbet, David R

2016-07-01

The nanofibrillar structures that underpin self-assembling peptide (SAP) hydrogels offer great potential for the development of finely tuned cellular microenvironments suitable for tissue engineering. However, biofunctionalisation without disruption of the assembly remains a key issue. SAPS present the peptide sequence within their structure, and studies to date have typically focused on including a single biological motif, resulting in chemically and biologically homogenous scaffolds. This limits the utility of these systems, as they cannot effectively mimic the complexity of the multicomponent extracellular matrix (ECM). In this work, we demonstrate the first successful co-assembly of two biologically active SAPs to form a coassembled scaffold of distinct two-component nanofibrils, and demonstrate that this approach is more bioactive than either of the individual systems alone. Here, we use two bioinspired SAPs from two key ECM proteins: Fmoc-FRGDF containing the RGD sequence from fibronectin and Fmoc-DIKVAV containing the IKVAV sequence from laminin. Our results demonstrate that these SAPs are able to co-assemble to form stable hybrid nanofibres containing dual epitopes. Comparison of the co-assembled SAP system to the individual SAP hydrogels and to a mixed system (composed of the two hydrogels mixed together post-assembly) demonstrates its superior stable, transparent, shear-thinning hydrogels at biological pH, ideal characteristics for tissue engineering applications. Importantly, we show that only the coassembled hydrogel is able to induce in vitro multinucleate myotube formation with C2C12 cells. This work illustrates the importance of tissue engineering scaffold functionalisation and the need to develop increasingly advanced multicomponent systems for effective ECM mimicry. Successful control of stem cell fate in tissue engineering applications requires the use of sophisticated scaffolds that deliver biological signals to guide growth and differentiation. The complexity of such processes necessitates the presentation of multiple signals in order to effectively mimic the native extracellular matrix (ECM). Here, we establish the use of two biofunctional, minimalist self-assembling peptides (SAPs) to construct the first co-assembled SAP scaffold. Our work characterises this construct, demonstrating that the physical, chemical, and biological properties of the peptides are maintained during the co-assembly process. Importantly, the coassembled system demonstrates superior biological performance relative to the individual SAPs, highlighting the importance of complex ECM mimicry. This work has important implications for future tissue engineering studies. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Systematic and fully automated identification of protein sequence patterns.

PubMed

Hart, R K; Royyuru, A K; Stolovitzky, G; Califano, A

2000-01-01

We present an efficient algorithm to systematically and automatically identify patterns in protein sequence families. The procedure is based on the Splash deterministic pattern discovery algorithm and on a framework to assess the statistical significance of patterns. We demonstrate its application to the fully automated discovery of patterns in 974 PROSITE families (the complete subset of PROSITE families which are defined by patterns and contain DR records). Splash generates patterns with better specificity and undiminished sensitivity, or vice versa, in 28% of the families; identical statistics were obtained in 48% of the families, worse statistics in 15%, and mixed behavior in the remaining 9%. In about 75% of the cases, Splash patterns identify sequence sites that overlap more than 50% with the corresponding PROSITE pattern. The procedure is sufficiently rapid to enable its use for daily curation of existing motif and profile databases. Third, our results show that the statistical significance of discovered patterns correlates well with their biological significance. The trypsin subfamily of serine proteases is used to illustrate this method's ability to exhaustively discover all motifs in a family that are statistically and biologically significant. Finally, we discuss applications of sequence patterns to multiple sequence alignment and the training of more sensitive score-based motif models, akin to the procedure used by PSI-BLAST. All results are available at httpl//www.research.ibm.com/spat/.

Discovering Sequence Motifs with Arbitrary Insertions and Deletions

PubMed Central

Frith, Martin C.; Saunders, Neil F. W.; Kobe, Bostjan; Bailey, Timothy L.

2008-01-01

Biology is encoded in molecular sequences: deciphering this encoding remains a grand scientific challenge. Functional regions of DNA, RNA, and protein sequences often exhibit characteristic but subtle motifs; thus, computational discovery of motifs in sequences is a fundamental and much-studied problem. However, most current algorithms do not allow for insertions or deletions (indels) within motifs, and the few that do have other limitations. We present a method, GLAM2 (Gapped Local Alignment of Motifs), for discovering motifs allowing indels in a fully general manner, and a companion method GLAM2SCAN for searching sequence databases using such motifs. glam2 is a generalization of the gapless Gibbs sampling algorithm. It re-discovers variable-width protein motifs from the PROSITE database significantly more accurately than the alternative methods PRATT and SAM-T2K. Furthermore, it usefully refines protein motifs from the ELM database: in some cases, the refined motifs make orders of magnitude fewer overpredictions than the original ELM regular expressions. GLAM2 performs respectably on the BAliBASE multiple alignment benchmark, and may be superior to leading multiple alignment methods for “motif-like” alignments with N- and C-terminal extensions. Finally, we demonstrate the use of GLAM2 to discover protein kinase substrate motifs and a gapped DNA motif for the LIM-only transcriptional regulatory complex: using GLAM2SCAN, we identify promising targets for the latter. GLAM2 is especially promising for short protein motifs, and it should improve our ability to identify the protein cleavage sites, interaction sites, post-translational modification attachment sites, etc., that underlie much of biology. It may be equally useful for arbitrarily gapped motifs in DNA and RNA, although fewer examples of such motifs are known at present. GLAM2 is public domain software, available for download at http://bioinformatics.org.au/glam2. PMID:18437229

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.

Massively parallel whole genome amplification for single-cell sequencing using droplet microfluidics.

PubMed

Hosokawa, Masahito; Nishikawa, Yohei; Kogawa, Masato; Takeyama, Haruko

2017-07-12

Massively parallel single-cell genome sequencing is required to further understand genetic diversities in complex biological systems. Whole genome amplification (WGA) is the first step for single-cell sequencing, but its throughput and accuracy are insufficient in conventional reaction platforms. Here, we introduce single droplet multiple displacement amplification (sd-MDA), a method that enables massively parallel amplification of single cell genomes while maintaining sequence accuracy and specificity. Tens of thousands of single cells are compartmentalized in millions of picoliter droplets and then subjected to lysis and WGA by passive droplet fusion in microfluidic channels. Because single cells are isolated in compartments, their genomes are amplified to saturation without contamination. This enables the high-throughput acquisition of contamination-free and cell specific sequence reads from single cells (21,000 single-cells/h), resulting in enhancement of the sequence data quality compared to conventional methods. This method allowed WGA of both single bacterial cells and human cancer cells. The obtained sequencing coverage rivals those of conventional techniques with superior sequence quality. In addition, we also demonstrate de novo assembly of uncultured soil bacteria and obtain draft genomes from single cell sequencing. This sd-MDA is promising for flexible and scalable use in single-cell sequencing.

Three distinct clades of cultured heterocystous cyanobacteria constitute the dominant N2-fixing members of biological soil crusts of the Colorado Plateau, USA

USGS Publications Warehouse

Yeager, C.M.; Kornosky, J.L.; Morgan, R.E.; Cain, E.C.; Garcia-Pichel, F.; Housman, D.C.; Belnap, J.; Kuske, C.R.

2007-01-01

The identity of the numerically dominant N2-fixing bacteria in biological soil crusts of the Colorado Plateau region and two outlying areas was determined using multiple approaches, to link the environmental diversity of nifH gene sequences to cultured bacterial isolates from the regions. Of the nifH sequence-types detected in soil crusts of the Colorado Plateau, 89% (421/473) were most closely related to nifH signature sequences from cyanobacteria of the order Nostocales. N2-fixing cyanobacterial strains were cultured from crusts and their morphotypes, 16S rRNA gene and nifH gene sequences were characterized. The numerically dominant diazotrophs in the Colorado Plateau crusts fell within three clades of heterocystous cyanobacteria. Two clades are well-represented by phylogenetically and morphologically coherent strains, corresponding to the descriptions of Nostoc commune and Scytonema hyalinum, which are widely recognized as important N2-fixing components of soil crusts. A third, previously-overlooked clade was represented by a phylogenetically coherent but morphologically diverse group of strains that encompass the morphogenera Tolypothrix and Spirirestis. Many of the strains in each of these groups contained at least two nifH copies that represent different clusters in the nifH environmental survey. ?? 2007 Federation of European Microbiological Societies.

A new method to cluster genomes based on cumulative Fourier power spectrum.

PubMed

Dong, Rui; Zhu, Ziyue; Yin, Changchuan; He, Rong L; Yau, Stephen S-T

2018-06-20

Analyzing phylogenetic relationships using mathematical methods has always been of importance in bioinformatics. Quantitative research may interpret the raw biological data in a precise way. Multiple Sequence Alignment (MSA) is used frequently to analyze biological evolutions, but is very time-consuming. When the scale of data is large, alignment methods cannot finish calculation in reasonable time. Therefore, we present a new method using moments of cumulative Fourier power spectrum in clustering the DNA sequences. Each sequence is translated into a vector in Euclidean space. Distances between the vectors can reflect the relationships between sequences. The mapping between the spectra and moment vector is one-to-one, which means that no information is lost in the power spectra during the calculation. We cluster and classify several datasets including Influenza A, primates, and human rhinovirus (HRV) datasets to build up the phylogenetic trees. Results show that the new proposed cumulative Fourier power spectrum is much faster and more accurately than MSA and another alignment-free method known as k-mer. The research provides us new insights in the study of phylogeny, evolution, and efficient DNA comparison algorithms for large genomes. The computer programs of the cumulative Fourier power spectrum are available at GitHub (https://github.com/YaulabTsinghua/cumulative-Fourier-power-spectrum). Copyright © 2018. Published by Elsevier B.V.

Alignment-free microbial phylogenomics under scenarios of sequence divergence, genome rearrangement and lateral genetic transfer.

PubMed

Bernard, Guillaume; Chan, Cheong Xin; Ragan, Mark A

2016-07-01

Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

PubMed Central

Lise, Stefano; Broxholme, John; Cazier, Jean-Baptiste; Rimmer, Andy; Kanapin, Alexander; Lunter, Gerton; Fiddy, Simon; Allan, Chris; Aricescu, A. Radu; Attar, Moustafa; Babbs, Christian; Becq, Jennifer; Beeson, David; Bento, Celeste; Bignell, Patricia; Blair, Edward; Buckle, Veronica J; Bull, Katherine; Cais, Ondrej; Cario, Holger; Chapel, Helen; Copley, Richard R; Cornall, Richard; Craft, Jude; Dahan, Karin; Davenport, Emma E; Dendrou, Calliope; Devuyst, Olivier; Fenwick, Aimée L; Flint, Jonathan; Fugger, Lars; Gilbert, Rodney D; Goriely, Anne; Green, Angie; Greger, Ingo H.; Grocock, Russell; Gruszczyk, Anja V; Hastings, Robert; Hatton, Edouard; Higgs, Doug; Hill, Adrian; Holmes, Chris; Howard, Malcolm; Hughes, Linda; Humburg, Peter; Johnson, David; Karpe, Fredrik; Kingsbury, Zoya; Kini, Usha; Knight, Julian C; Krohn, Jonathan; Lamble, Sarah; Langman, Craig; Lonie, Lorne; Luck, Joshua; McCarthy, Davis; McGowan, Simon J; McMullin, Mary Frances; Miller, Kerry A; Murray, Lisa; Németh, Andrea H; Nesbit, M Andrew; Nutt, David; Ormondroyd, Elizabeth; Oturai, Annette Bang; Pagnamenta, Alistair; Patel, Smita Y; Percy, Melanie; Petousi, Nayia; Piazza, Paolo; Piret, Sian E; Polanco-Echeverry, Guadalupe; Popitsch, Niko; Powrie, Fiona; Pugh, Chris; Quek, Lynn; Robbins, Peter A; Robson, Kathryn; Russo, Alexandra; Sahgal, Natasha; van Schouwenburg, Pauline A; Schuh, Anna; Silverman, Earl; Simmons, Alison; Sørensen, Per Soelberg; Sweeney, Elizabeth; Taylor, John; Thakker, Rajesh V; Tomlinson, Ian; Trebes, Amy; Twigg, Stephen RF; Uhlig, Holm H; Vyas, Paresh; Vyse, Tim; Wall, Steven A; Watkins, Hugh; Whyte, Michael P; Witty, Lorna; Wright, Ben; Yau, Chris; Buck, David; Humphray, Sean; Ratcliffe, Peter J; Bell, John I; Wilkie, Andrew OM; Bentley, David; Donnelly, Peter; McVean, Gilean

2015-01-01

To assess factors influencing the success of whole genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases across a broad spectrum of disorders in whom prior screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritisation. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease causing variants in 21% of cases, rising to 34% (23/68) for Mendelian disorders and 57% (8/14) in trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, though only four were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis, but also highlight many outstanding challenges. PMID:25985138

Greater than the sum of its parts: single-nucleus sequencing identifies convergent evolution of independent EGFR mutants in GBM.

PubMed

Gini, Beatrice; Mischel, Paul S

2014-08-01

Single-cell sequencing approaches are needed to characterize the genomic diversity of complex tumors, shedding light on their evolutionary paths and potentially suggesting more effective therapies. In this issue of Cancer Discovery, Francis and colleagues develop a novel integrative approach to identify distinct tumor subpopulations based on joint detection of clonal and subclonal events from bulk tumor and single-nucleus whole-genome sequencing, allowing them to infer a subclonal architecture. Surprisingly, the authors identify convergent evolution of multiple, mutually exclusive, independent EGFR gain-of-function variants in a single tumor. This study demonstrates the value of integrative single-cell genomics and highlights the biologic primacy of EGFR as an actionable target in glioblastoma. ©2014 American Association for Cancer Research.

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets.

PubMed

Naegle, Kristen M; Welsch, Roy E; Yaffe, Michael B; White, Forest M; Lauffenburger, Douglas A

2011-07-01

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems. © 2011 Naegle et al.

Droplet microfluidics for synthetic biology

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

Gach, PC; Iwai, K; Kim, PW

2017-01-01

© 2017 The Royal Society of Chemistry. Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselvesmore » expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Determination of haplotypes at structurally complex regions using emulsion haplotype fusion PCR.

PubMed

Tyson, Jess; Armour, John A L

2012-12-11

Genotyping and massively-parallel sequencing projects result in a vast amount of diploid data that is only rarely resolved into its constituent haplotypes. It is nevertheless this phased information that is transmitted from one generation to the next and is most directly associated with biological function and the genetic causes of biological effects. Despite progress made in genome-wide sequencing and phasing algorithms and methods, problems assembling (and reconstructing linear haplotypes in) regions of repetitive DNA and structural variation remain. These dynamic and structurally complex regions are often poorly understood from a sequence point of view. Regions such as these that are highly similar in their sequence tend to be collapsed onto the genome assembly. This is turn means downstream determination of the true sequence haplotype in these regions poses a particular challenge. For structurally complex regions, a more focussed approach to assembling haplotypes may be required. In order to investigate reconstruction of spatial information at structurally complex regions, we have used an emulsion haplotype fusion PCR approach to reproducibly link sequences of up to 1kb in length to allow phasing of multiple variants from neighbouring loci, using allele-specific PCR and sequencing to detect the phase. By using emulsion systems linking flanking regions to amplicons within the CNV, this led to the reconstruction of a 59kb haplotype across the DEFA1A3 CNV in HapMap individuals. This study has demonstrated a novel use for emulsion haplotype fusion PCR in addressing the issue of reconstructing structural haplotypes at multiallelic copy variable regions, using the DEFA1A3 locus as an example.

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

PubMed Central

Peng, Hao; Yang, Yifan; Zhe, Shandian; Wang, Jian; Gribskov, Michael; Qi, Yuan

2017-01-01

Abstract Motivation High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy. Results We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature. Availability and implementation The software is available at https://github.com/hao-peng/DEIsoM Contact pengh@alumni.purdue.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28595376

Passing Messages between Biological Networks to Refine Predicted Interactions

PubMed Central

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402

Sequence-specific 1H-NMR assignments for the aromatic region of several biologically active, monomeric insulins including native human insulin.

PubMed

Roy, M; Lee, R W; Kaarsholm, N C; Thøgersen, H; Brange, J; Dunn, M F

1990-06-12

The aromatic region of the 1H-FT-NMR spectrum of the biologically fully-potent, monomeric human insulin mutant, B9 Ser----Asp, B27 Thr----Glu has been investigated in D2O. At 1 to 5 mM concentrations, this mutant insulin is monomeric above pH 7.5. Coupling and amino acid classification of all aromatic signals is established via a combination of homonuclear one- and two-dimensional methods, including COSY, multiple quantum filters, selective spin decoupling and pH titrations. By comparisons with other insulin mutants and with chemically modified native insulins, all resonances in the aromatic region are given sequence-specific assignments without any reliance on the various crystal structures reported for insulin. These comparisons also give the sequence-specific assignments of most of the aromatic resonances of the mutant insulins B16 Tyr----Glu, B27 Thr----Glu and B25 Phe----Asp and the chemically modified species des-(B23-B30) insulin and monoiodo-Tyr A14 insulin. Chemical dispersion of the assigned resonances, ring current perturbations and comparisons at high pH have made possible the assignment of the aromatic resonances of human insulin, and these studies indicate that the major structural features of the human insulin monomer (including those critical to biological function) are also present in the monomeric mutant.

Evolutionarily conserved regions and hydrophobic contacts at the superfamily level: The case of the fold-type I, pyridoxal-5′-phosphate-dependent enzymes

PubMed Central

Paiardini, Alessandro; Bossa, Francesco; Pascarella, Stefano

2004-01-01

The wealth of biological information provided by structural and genomic projects opens new prospects of understanding life and evolution at the molecular level. In this work, it is shown how computational approaches can be exploited to pinpoint protein structural features that remain invariant upon long evolutionary periods in the fold-type I, PLP-dependent enzymes. A nonredundant set of 23 superposed crystallographic structures belonging to this superfamily was built. Members of this family typically display high-structural conservation despite low-sequence identity. For each structure, a multiple-sequence alignment of orthologous sequences was obtained, and the 23 alignments were merged using the structural information to obtain a comprehensive multiple alignment of 921 sequences of fold-type I enzymes. The structurally conserved regions (SCRs), the evolutionarily conserved residues, and the conserved hydrophobic contacts (CHCs) were extracted from this data set, using both sequence and structural information. The results of this study identified a structural pattern of hydrophobic contacts shared by all of the superfamily members of fold-type I enzymes and involved in native interactions. This profile highlights the presence of a nucleus for this fold, in which residues participating in the most conserved native interactions exhibit preferential evolutionary conservation, that correlates significantly (r = 0.70) with the extent of mean hydrophobic contact value of their apolar fraction. PMID:15498941

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…

Creation of a data base for sequences of ribosomal nucleic acids and detection of conserved restriction endonucleases sites through computerized processing.

PubMed Central

Patarca, R; Dorta, B; Ramirez, J L

1982-01-01

As part of a project pertaining the organization of ribosomal genes in Kinetoplastidae, we have created a data base for published sequences of ribosomal nucleic acids, with information in Spanish. As a first step in their processing, we have written a computer program which introduces the new feature of determining the length of the fragments produced after single or multiple digestion with any of the known restriction enzymes. With this information we have detected conserved SAU 3A sites: (i) at the 5' end of the 5.8S rRNA and at the 3' end of the small subunit rRNA, both included in similar larger sequences; (ii) in the 5.8S rRNA of vertebrates (a second one), which is not present in lower eukaryotes, showing a clear evolutive divergence; and, (iii) at the 5' terminal of the small subunit rRNA, included in a larger conserved sequence. The possible biological importance of these sequences is discussed. PMID:6278402

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

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.

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.

Reefgenomics.Org - a repository for marine genomics data.

PubMed

Liew, Yi Jin; Aranda, Manuel; Voolstra, Christian R

2016-01-01

Over the last decade, technological advancements have substantially decreased the cost and time of obtaining large amounts of sequencing data. Paired with the exponentially increased computing power, individual labs are now able to sequence genomes or transcriptomes to investigate biological questions of interest. This has led to a significant increase in available sequence data. Although the bulk of data published in articles are stored in public sequence databases, very often, only raw sequencing data are available; miscellaneous data such as assembled transcriptomes, genome annotations etc. are not easily obtainable through the same means. Here, we introduce our website (http://reefgenomics.org) that aims to centralize genomic and transcriptomic data from marine organisms. Besides providing convenient means to download sequences, we provide (where applicable) a genome browser to explore available genomic features, and a BLAST interface to search through the hosted sequences. Through the interface, multiple datasets can be queried simultaneously, allowing for the retrieval of matching sequences from organisms of interest. The minimalistic, no-frills interface reduces visual clutter, making it convenient for end-users to search and explore processed sequence data. DATABASE URL: http://reefgenomics.org. © The Author(s) 2016. Published by Oxford University Press.

Plant-RRBS, a bisulfite and next-generation sequencing-based methylome profiling method enriching for coverage of cytosine positions.

PubMed

Schmidt, Martin; Van Bel, Michiel; Woloszynska, Magdalena; Slabbinck, Bram; Martens, Cindy; De Block, Marc; Coppens, Frederik; Van Lijsebettens, Mieke

2017-07-06

Cytosine methylation in plant genomes is important for the regulation of gene transcription and transposon activity. Genome-wide methylomes are studied upon mutation of the DNA methyltransferases, adaptation to environmental stresses or during development. However, from basic biology to breeding programs, there is a need to monitor multiple samples to determine transgenerational methylation inheritance or differential cytosine methylation. Methylome data obtained by sodium hydrogen sulfite (bisulfite)-conversion and next-generation sequencing (NGS) provide genome-wide information on cytosine methylation. However, a profiling method that detects cytosine methylation state dispersed over the genome would allow high-throughput analysis of multiple plant samples with distinct epigenetic signatures. We use specific restriction endonucleases to enrich for cytosine coverage in a bisulfite and NGS-based profiling method, which was compared to whole-genome bisulfite sequencing of the same plant material. We established an effective methylome profiling method in plants, termed plant-reduced representation bisulfite sequencing (plant-RRBS), using optimized double restriction endonuclease digestion, fragment end repair, adapter ligation, followed by bisulfite conversion, PCR amplification and NGS. We report a performant laboratory protocol and a straightforward bioinformatics data analysis pipeline for plant-RRBS, applicable for any reference-sequenced plant species. As a proof of concept, methylome profiling was performed using an Oryza sativa ssp. indica pure breeding line and a derived epigenetically altered line (epiline). Plant-RRBS detects methylation levels at tens of millions of cytosine positions deduced from bisulfite conversion in multiple samples. To evaluate the method, the coverage of cytosine positions, the intra-line similarity and the differential cytosine methylation levels between the pure breeding line and the epiline were determined. Plant-RRBS reproducibly covers commonly up to one fourth of the cytosine positions in the rice genome when using MspI-DpnII within a group of five biological replicates of a line. The method predominantly detects cytosine methylation in putative promoter regions and not-annotated regions in rice. Plant-RRBS offers high-throughput and broad, genome-dispersed methylation detection by effective read number generation obtained from reproducibly covered genome fractions using optimized endonuclease combinations, facilitating comparative analyses of multi-sample studies for cytosine methylation and transgenerational stability in experimental material and plant breeding populations.

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes.

PubMed

Troell, Karin; Hallström, Björn; Divne, Anna-Maria; Alsmark, Cecilia; Arrighi, Romanico; Huss, Mikael; Beser, Jessica; Bertilsson, Stefan

2016-06-23

Infectious disease involving multiple genetically distinct populations of pathogens is frequently concurrent, but difficult to detect or describe with current routine methodology. Cryptosporidium sp. is a widespread gastrointestinal protozoan of global significance in both animals and humans. It cannot be easily maintained in culture and infections of multiple strains have been reported. To explore the potential use of single cell genomics methodology for revealing genome-level variation in clinical samples from Cryptosporidium-infected hosts, we sorted individual oocysts for subsequent genome amplification and full-genome sequencing. Cells were identified with fluorescent antibodies with an 80 % success rate for the entire single cell genomics workflow, demonstrating that the methodology can be applied directly to purified fecal samples. Ten amplified genomes from sorted single cells were selected for genome sequencing and compared both to the original population and a reference genome in order to evaluate the accuracy and performance of the method. Single cell genome coverage was on average 81 % even with a moderate sequencing effort and by combining the 10 single cell genomes, the full genome was accounted for. By a comparison to the original sample, biological variation could be distinguished and separated from noise introduced in the amplification. As a proof of principle, we have demonstrated the power of applying single cell genomics to dissect infectious disease caused by closely related parasite species or subtypes. The workflow can easily be expanded and adapted to target other protozoans, and potential applications include mapping genome-encoded traits, virulence, pathogenicity, host specificity and resistance at the level of cells as truly meaningful biological units.

MYD88 and functionally related genes are associated with multiple infections in a model population of Kenyan village dogs.

PubMed

Necesankova, Michaela; Vychodilova, Leona; Albrechtova, Katerina; Kennedy, Lorna J; Hlavac, Jan; Sedlak, Kamil; Modry, David; Janova, Eva; Vyskocil, Mirko; Horin, Petr

2016-12-01

The purpose of this study was to seek associations between immunity-related molecular markers and endemic infections in a model population of African village dogs from Northern Kenya with no veterinary care and no selective breeding. A population of village dogs from Northern Kenya composed of three sub-populations from three different areas (84, 50 and 55 dogs) was studied. Canine distemper virus (CDV), Hepatozoon canis, Microfilariae (Acantocheilonema dracunculoides, Acantocheilonema reconditum) and Neospora caninum were the pathogens studied. The presence of antibodies (CDV, Neospora), light microscopy (Hepatozoon) and diagnostic PCR (Microfilariae) were the methods used for diagnosing infection. Genes involved in innate immune mechanisms, NOS3, IL6, TLR1, TLR2, TLR4, TLR7, TLR9, LY96, MYD88, and three major histocompatibility genes class II genes were selected as candidates. Single nucleotide polymorphism (SNP) markers were detected by Sanger sequencing, next generation sequencing and PCR-RFLP. The Fisher´s exact test for additive and non-additive models was used for association analyses. Three SNPs within the MYD88 gene and one TLR4 SNP marker were associated with more than one infection. Combined genotypes and further markers identified by next generation sequencing confirmed associations observed for individual genes. The genes associated with infection and their combinations in specific genotypes match well our knowledge on their biological role and on the role of the relevant biological pathways, respectively. Associations with multiple infections observed between the MYD88 and TLR4 genes suggest their involvement in the mechanisms of anti-infectious defenses in dogs.

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

The Reference Genome of the Halophytic Plant Eutrema salsugineum

PubMed Central

Yang, Ruolin; Jarvis, David E.; Chen, Hao; Beilstein, Mark A.; Grimwood, Jane; Jenkins, Jerry; Shu, ShengQiang; Prochnik, Simon; Xin, Mingming; Ma, Chuang; Schmutz, Jeremy; Wing, Rod A.; Mitchell-Olds, Thomas; Schumaker, Karen S.; Wang, Xiangfeng

2013-01-01

Halophytes are plants that can naturally tolerate high concentrations of salt in the soil, and their tolerance to salt stress may occur through various evolutionary and molecular mechanisms. Eutrema salsugineum is a halophytic species in the Brassicaceae that can naturally tolerate multiple types of abiotic stresses that typically limit crop productivity, including extreme salinity and cold. It has been widely used as a laboratorial model for stress biology research in plants. Here, we present the reference genome sequence (241 Mb) of E. salsugineum at 8× coverage sequenced using the traditional Sanger sequencing-based approach with comparison to its close relative Arabidopsis thaliana. The E. salsugineum genome contains 26,531 protein-coding genes and 51.4% of its genome is composed of repetitive sequences that mostly reside in pericentromeric regions. Comparative analyses of the genome structures, protein-coding genes, microRNAs, stress-related pathways, and estimated translation efficiency of proteins between E. salsugineum and A. thaliana suggest that halophyte adaptation to environmental stresses may occur via a global network adjustment of multiple regulatory mechanisms. The E. salsugineum genome provides a resource to identify naturally occurring genetic alterations contributing to the adaptation of halophytic plants to salinity and that might be bioengineered in related crop species. PMID:23518688

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

Synergy and contingency as driving forces for the evolution of multiple secondary metabolite production by Streptomyces species.

PubMed

Challis, Gregory L; Hopwood, David A

2003-11-25

In this article we briefly review theories about the ecological roles of microbial secondary metabolites and discuss the prevalence of multiple secondary metabolite production by strains of Streptomyces, highlighting results from analysis of the recently sequenced Streptomyces coelicolor and Streptomyces avermitilis genomes. We address this question: Why is multiple secondary metabolite production in Streptomyces species so commonplace? We argue that synergy or contingency in the action of individual metabolites against biological competitors may, in some cases, be a powerful driving force for the evolution of multiple secondary metabolite production. This argument is illustrated with examples of the coproduction of synergistically acting antibiotics and contingently acting siderophores: two well-known classes of secondary metabolite. We focus, in particular, on the coproduction of beta-lactam antibiotics and beta-lactamase inhibitors, the coproduction of type A and type B streptogramins, and the coregulated production and independent uptake of structurally distinct siderophores by species of Streptomyces. Possible mechanisms for the evolution of multiple synergistic and contingent metabolite production in Streptomyces species are discussed. It is concluded that the production by Streptomyces species of two or more secondary metabolites that act synergistically or contingently against biological competitors may be far more common than has previously been recognized, and that synergy and contingency may be common driving forces for the evolution of multiple secondary metabolite production by these sessile saprophytes.

Synergy and contingency as driving forces for the evolution of multiple secondary metabolite production by Streptomyces species

PubMed Central

Challis, Gregory L.; Hopwood, David A.

2003-01-01

In this article we briefly review theories about the ecological roles of microbial secondary metabolites and discuss the prevalence of multiple secondary metabolite production by strains of Streptomyces, highlighting results from analysis of the recently sequenced Streptomyces coelicolor and Streptomyces avermitilis genomes. We address this question: Why is multiple secondary metabolite production in Streptomyces species so commonplace? We argue that synergy or contingency in the action of individual metabolites against biological competitors may, in some cases, be a powerful driving force for the evolution of multiple secondary metabolite production. This argument is illustrated with examples of the coproduction of synergistically acting antibiotics and contingently acting siderophores: two well-known classes of secondary metabolite. We focus, in particular, on the coproduction of β-lactam antibiotics and β-lactamase inhibitors, the coproduction of type A and type B streptogramins, and the coregulated production and independent uptake of structurally distinct siderophores by species of Streptomyces. Possible mechanisms for the evolution of multiple synergistic and contingent metabolite production in Streptomyces species are discussed. It is concluded that the production by Streptomyces species of two or more secondary metabolites that act synergistically or contingently against biological competitors may be far more common than has previously been recognized, and that synergy and contingency may be common driving forces for the evolution of multiple secondary metabolite production by these sessile saprophytes. PMID:12970466

It’s More Than Stamp Collecting: How Genome Sequencing Can Unify Biological Research

PubMed Central

Richards, Stephen

2015-01-01

The availability of reference genome sequences, especially the human reference, has revolutionized the study of biology. However, whilst the genomes of some species have been fully sequenced, a wide range of biological problems still cannot be effectively studied for lack of genome sequence information. Here, I identify neglected areas of biology and describe how both targeted species sequencing and more broad taxonomic surveys of the tree of life can address important biological questions. I enumerate the significant benefits that would accrue from sequencing a broader range of taxa, as well as discuss the technical advances in sequencing and assembly methods that would allow for wide-ranging application of whole-genome analysis. Finally, I suggest that in addition to “Big Science” survey initiatives to sequence the tree of life, a modified infrastructure-funding paradigm would better support reference genome sequence generation for research communities most in need. PMID:26003218

It's more than stamp collecting: how genome sequencing can unify biological research.

PubMed

Richards, Stephen

2015-07-01

The availability of reference genome sequences, especially the human reference, has revolutionized the study of biology. However, while the genomes of some species have been fully sequenced, a wide range of biological problems still cannot be effectively studied for lack of genome sequence information. Here, I identify neglected areas of biology and describe how both targeted species sequencing and more broad taxonomic surveys of the tree of life can address important biological questions. I enumerate the significant benefits that would accrue from sequencing a broader range of taxa, as well as discuss the technical advances in sequencing and assembly methods that would allow for wide-ranging application of whole-genome analysis. Finally, I suggest that in addition to 'big science' survey initiatives to sequence the tree of life, a modified infrastructure-funding paradigm would better support reference genome sequence generation for research communities most in need. Copyright © 2015 Elsevier Ltd. All rights reserved.

Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

PubMed

Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

2017-12-15

This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

Sequencing and assembly of the 22-gb loblolly pine genome.

PubMed

Zimin, Aleksey; Stevens, Kristian A; Crepeau, Marc W; Holtz-Morris, Ann; Koriabine, Maxim; Marçais, Guillaume; Puiu, Daniela; Roberts, Michael; Wegrzyn, Jill L; de Jong, Pieter J; Neale, David B; Salzberg, Steven L; Yorke, James A; Langley, Charles H

2014-03-01

Conifers are the predominant gymnosperm. The size and complexity of their genomes has presented formidable technical challenges for whole-genome shotgun sequencing and assembly. We employed novel strategies that allowed us to determine the loblolly pine (Pinus taeda) reference genome sequence, the largest genome assembled to date. Most of the sequence data were derived from whole-genome shotgun sequencing of a single megagametophyte, the haploid tissue of a single pine seed. Although that constrained the quantity of available DNA, the resulting haploid sequence data were well-suited for assembly. The haploid sequence was augmented with multiple linking long-fragment mate pair libraries from the parental diploid DNA. For the longest fragments, we used novel fosmid DiTag libraries. Sequences from the linking libraries that did not match the megagametophyte were identified and removed. Assembly of the sequence data were aided by condensing the enormous number of paired-end reads into a much smaller set of longer "super-reads," rendering subsequent assembly with an overlap-based assembly algorithm computationally feasible. To further improve the contiguity and biological utility of the genome sequence, additional scaffolding methods utilizing independent genome and transcriptome assemblies were implemented. The combination of these strategies resulted in a draft genome sequence of 20.15 billion bases, with an N50 scaffold size of 66.9 kbp.

Gene Expression Profiling in Fish Toxicology: A Review.

PubMed

Kumar, Girish; Denslow, Nancy D

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring gene expression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressed gene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressed genes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

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

Protein Sequence Classification with Improved Extreme Learning Machine Algorithms

PubMed Central

2014-01-01

Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms. PMID:24795876

Chromosome Evolution in Connection with Repetitive Sequences and Epigenetics in Plants

PubMed Central

Li, Shu-Fen; Su, Ting; Cheng, Guang-Qian; Wang, Bing-Xiao; Li, Xu; Deng, Chuan-Liang; Gao, Wu-Jun

2017-01-01

Chromosome evolution is a fundamental aspect of evolutionary biology. The evolution of chromosome size, structure and shape, number, and the change in DNA composition suggest the high plasticity of nuclear genomes at the chromosomal level. Repetitive DNA sequences, which represent a conspicuous fraction of every eukaryotic genome, particularly in plants, are found to be tightly linked with plant chromosome evolution. Different classes of repetitive sequences have distinct distribution patterns on the chromosomes. Mounting evidence shows that repetitive sequences may play multiple generative roles in shaping the chromosome karyotypes in plants. Furthermore, recent development in our understanding of the repetitive sequences and plant chromosome evolution has elucidated the involvement of a spectrum of epigenetic modification. In this review, we focused on the recent evidence relating to the distribution pattern of repetitive sequences in plant chromosomes and highlighted their potential relevance to chromosome evolution in plants. We also discussed the possible connections between evolution and epigenetic alterations in chromosome structure and repatterning, such as heterochromatin formation, centromere function, and epigenetic-associated transposable element inactivation. PMID:29064432

The new modern era of yeast genomics: community sequencing and the resulting annotation of multiple Saccharomyces cerevisiae strains at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R.; Cherry, J. Michael

2013-01-01

The first completed eukaryotic genome sequence was that of the yeast Saccharomyces cerevisiae, and the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the original model organism database. SGD remains the authoritative community resource for the S. cerevisiae reference genome sequence and its annotation, and continues to provide comprehensive biological information correlated with S. cerevisiae genes and their products. A diverse set of yeast strains have been sequenced to explore commercial and laboratory applications, and a brief history of those strains is provided. The publication of these new genomes has motivated the creation of new tools, and SGD will annotate and provide comparative analyses of these sequences, correlating changes with variations in strain phenotypes and protein function. We are entering a new era at SGD, as we incorporate these new sequences and make them accessible to the scientific community, all in an effort to continue in our mission of educating researchers and facilitating discovery. Database URL: http://www.yeastgenome.org/ PMID:23487186

Identifying functionally informative evolutionary sequence profiles.

PubMed

Gil, Nelson; Fiser, Andras

2018-04-15

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.

GenoMetric Query Language: a novel approach to large-scale genomic data management.

PubMed

Masseroli, Marco; Pinoli, Pietro; Venco, Francesco; Kaitoua, Abdulrahman; Jalili, Vahid; Palluzzi, Fernando; Muller, Heiko; Ceri, Stefano

2015-06-15

Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art 'big data' computing strategies, with abstraction levels beyond available tool capabilities. We propose a high-level, declarative GenoMetric Query Language (GMQL) and a toolkit for its use. GMQL operates downstream of raw data preprocessing pipelines and supports queries over thousands of heterogeneous datasets and samples; as such it is key to genomic 'big data' analysis. GMQL leverages a simple data model that provides both abstractions of genomic region data and associated experimental, biological and clinical metadata and interoperability between many data formats. Based on Hadoop framework and Apache Pig platform, GMQL ensures high scalability, expressivity, flexibility and simplicity of use, as demonstrated by several biological query examples on ENCODE and TCGA datasets. The GMQL toolkit is freely available for non-commercial use at http://www.bioinformatics.deib.polimi.it/GMQL/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Biopython: freely available Python tools for computational molecular biology and bioinformatics

PubMed Central

Cock, Peter J. A.; Antao, Tiago; Chang, Jeffrey T.; Chapman, Brad A.; Cox, Cymon J.; Dalke, Andrew; Friedberg, Iddo; Hamelryck, Thomas; Kauff, Frank; Wilczynski, Bartek; de Hoon, Michiel J. L.

2009-01-01

Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license. Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_listspeter.cock@scri.ac.uk. PMID:19304878

A standard-enabled workflow for synthetic biology.

PubMed

Myers, Chris J; Beal, Jacob; Gorochowski, Thomas E; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach

2017-06-15

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Copper metallothioneins.

PubMed

Calvo, Jenifer; Jung, Hunmin; Meloni, Gabriele

2017-04-01

Metallothioneins (MTs) are a class of low molecular weight and cysteine-rich metal binding proteins present in all the branches of the tree of life. MTs efficiently bind with high affinity several essential and toxic divalent and monovalent transition metals by forming characteristic polynuclear metal-thiolate clusters within their structure. MTs fulfil multiple biological functions related to their metal binding properties, with essential roles in both Zn(II) and Cu(I) homeostasis as well as metal detoxification. Depending on the organism considered, the primary sequence, and the specific physiological and metabolic status, Cu(I)-bound MT isoforms have been isolated, and their chemistry and biology characterized. Besides the recognized role in the biochemistry of divalent metals, it is becoming evident that unique biological functions in selectively controlling copper levels, its reactivity as well as copper-mediated biochemical processes have evolved in some members of the MT superfamily. Selected examples are reviewed to highlight the peculiar chemical properties and biological functions of copper MTs. © 2016 IUBMB Life, 69(4):236-245, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

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.

Convolutional neural network architectures for predicting DNA–protein binding

PubMed Central

Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

2016-01-01

Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

Draft genome of the living fossil Ginkgo biloba.

PubMed

Guan, Rui; Zhao, Yunpeng; Zhang, He; Fan, Guangyi; Liu, Xin; Zhou, Wenbin; Shi, Chengcheng; Wang, Jiahao; Liu, Weiqing; Liang, Xinming; Fu, Yuanyuan; Ma, Kailong; Zhao, Lijun; Zhang, Fumin; Lu, Zuhong; Lee, Simon Ming-Yuen; Xu, Xun; Wang, Jian; Yang, Huanming; Fu, Chengxin; Ge, Song; Chen, Wenbin

2016-11-21

Ginkgo biloba L. (Ginkgoaceae) is one of the most distinctive plants. It possesses a suite of fascinating characteristics including a large genome, outstanding resistance/tolerance to abiotic and biotic stresses, and dioecious reproduction, making it an ideal model species for biological studies. However, the lack of a high-quality genome sequence has been an impediment to our understanding of its biology and evolution. The 10.61 Gb genome sequence containing 41,840 annotated genes was assembled in the present study. Repetitive sequences account for 76.58% of the assembled sequence, and long terminal repeat retrotransposons (LTR-RTs) are particularly prevalent. The diversity and abundance of LTR-RTs is due to their gradual accumulation and a remarkable amplification between 16 and 24 million years ago, and they contribute to the long introns and large genome. Whole genome duplication (WGD) may have occurred twice, with an ancient WGD consistent with that shown to occur in other seed plants, and a more recent event specific to ginkgo. Abundant gene clusters from tandem duplication were also evident, and enrichment of expanded gene families indicates a remarkable array of chemical and antibacterial defense pathways. The ginkgo genome consists mainly of LTR-RTs resulting from ancient gradual accumulation and two WGD events. The multiple defense mechanisms underlying the characteristic resilience of ginkgo are fostered by a remarkable enrichment in ancient duplicated and ginkgo-specific gene clusters. The present study sheds light on sequencing large genomes, and opens an avenue for further genetic and evolutionary research.

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.

ePlant and the 3D data display initiative: integrative systems biology on the world wide web.

PubMed

Fucile, Geoffrey; Di Biase, David; Nahal, Hardeep; La, Garon; Khodabandeh, Shokoufeh; Chen, Yani; Easley, Kante; Christendat, Dinesh; Kelley, Lawrence; Provart, Nicholas J

2011-01-10

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed "ePlant" (http://bar.utoronto.ca/eplant) - a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the "3D Data Display Initiative" (http://3ddi.org).

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189

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.

Determination of haplotypes at structurally complex regions using emulsion haplotype fusion PCR

PubMed Central

2012-01-01

Background Genotyping and massively-parallel sequencing projects result in a vast amount of diploid data that is only rarely resolved into its constituent haplotypes. It is nevertheless this phased information that is transmitted from one generation to the next and is most directly associated with biological function and the genetic causes of biological effects. Despite progress made in genome-wide sequencing and phasing algorithms and methods, problems assembling (and reconstructing linear haplotypes in) regions of repetitive DNA and structural variation remain. These dynamic and structurally complex regions are often poorly understood from a sequence point of view. Regions such as these that are highly similar in their sequence tend to be collapsed onto the genome assembly. This is turn means downstream determination of the true sequence haplotype in these regions poses a particular challenge. For structurally complex regions, a more focussed approach to assembling haplotypes may be required. Results In order to investigate reconstruction of spatial information at structurally complex regions, we have used an emulsion haplotype fusion PCR approach to reproducibly link sequences of up to 1kb in length to allow phasing of multiple variants from neighbouring loci, using allele-specific PCR and sequencing to detect the phase. By using emulsion systems linking flanking regions to amplicons within the CNV, this led to the reconstruction of a 59kb haplotype across the DEFA1A3 CNV in HapMap individuals. Conclusion This study has demonstrated a novel use for emulsion haplotype fusion PCR in addressing the issue of reconstructing structural haplotypes at multiallelic copy variable regions, using the DEFA1A3 locus as an example. PMID:23231411

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.

Multiple introductions and recombination in Cryphonectria hypovirus 1: perspective for a sustainable biological control of chestnut blight

PubMed Central

Feau, Nicolas; Dutech, Cyril; Brusini, Jérémie; Rigling, Daniel; Robin, Cécile

2014-01-01

Cryphonectria hypovirus 1 (CHV1) is a mycovirus which decreases the virulence of its fungal host Cryphonectria parasitica, the causal agent of chestnut blight recently introduced in Europe. The understanding of the evolutionary processes which have shaped CHV1 populations in Europe is required to develop a sustainable biocontrol strategy targeting chestnut blight and effective in European chestnut forests. To retrace the evolutionary history of CHV1, we analyzed sequences from two genomic regions on a collection of 55 CHV1 strains from France and northern Spain, two countries where multiple introductions of C. parasitica occurred. Several recombination events and variable selection pressures contributed to CHV1 evolution, agreeing with a non-clock-like diversification rate. These two mechanisms may be at the origin of CHV1 population diversity observed in western Europe. Considering the actual prevalence of CHV1 and its association with host genotypes, multiple introductions of CHV1 may have occurred in Europe, some of them directly from Asia and some of them through North America. Although some viral strains remained with low frequency in their introduction area, multiple infections might have allowed homologous recombination within parental sequences. Some of these recombinant lineages are associated with the spread of CHV1 in European regions. PMID:24944571

Elucidation of hepatitis C virus transmission and early diversification by single genome sequencing.

PubMed

Li, Hui; Stoddard, Mark B; Wang, Shuyi; Blair, Lily M; Giorgi, Elena E; Parrish, Erica H; Learn, Gerald H; Hraber, Peter; Goepfert, Paul A; Saag, Michael S; Denny, Thomas N; Haynes, Barton F; Hahn, Beatrice H; Ribeiro, Ruy M; Perelson, Alan S; Korber, Bette T; Bhattacharya, Tanmoy; Shaw, George M

2012-01-01

A precise molecular identification of transmitted hepatitis C virus (HCV) genomes could illuminate key aspects of transmission biology, immunopathogenesis and natural history. We used single genome sequencing of 2,922 half or quarter genomes from plasma viral RNA to identify transmitted/founder (T/F) viruses in 17 subjects with acute community-acquired HCV infection. Sequences from 13 of 17 acute subjects, but none of 14 chronic controls, exhibited one or more discrete low diversity viral lineages. Sequences within each lineage generally revealed a star-like phylogeny of mutations that coalesced to unambiguous T/F viral genomes. Numbers of transmitted viruses leading to productive clinical infection were estimated to range from 1 to 37 or more (median = 4). Four acutely infected subjects showed a distinctly different pattern of virus diversity that deviated from a star-like phylogeny. In these cases, empirical analysis and mathematical modeling suggested high multiplicity virus transmission from individuals who themselves were acutely infected or had experienced a virus population bottleneck due to antiviral drug therapy. These results provide new quantitative and qualitative insights into HCV transmission, revealing for the first time virus-host interactions that successful vaccines or treatment interventions will need to overcome. Our findings further suggest a novel experimental strategy for identifying full-length T/F genomes for proteome-wide analyses of HCV biology and adaptation to antiviral drug or immune pressures.

Elucidation of Hepatitis C Virus Transmission and Early Diversification by Single Genome Sequencing

PubMed Central

Li, Hui; Stoddard, Mark B.; Wang, Shuyi; Blair, Lily M.; Giorgi, Elena E.; Parrish, Erica H.; Learn, Gerald H.; Hraber, Peter; Goepfert, Paul A.; Saag, Michael S.; Denny, Thomas N.; Haynes, Barton F.; Hahn, Beatrice H.; Ribeiro, Ruy M.; Perelson, Alan S.; Korber, Bette T.; Bhattacharya, Tanmoy; Shaw, George M.

2012-01-01

A precise molecular identification of transmitted hepatitis C virus (HCV) genomes could illuminate key aspects of transmission biology, immunopathogenesis and natural history. We used single genome sequencing of 2,922 half or quarter genomes from plasma viral RNA to identify transmitted/founder (T/F) viruses in 17 subjects with acute community-acquired HCV infection. Sequences from 13 of 17 acute subjects, but none of 14 chronic controls, exhibited one or more discrete low diversity viral lineages. Sequences within each lineage generally revealed a star-like phylogeny of mutations that coalesced to unambiguous T/F viral genomes. Numbers of transmitted viruses leading to productive clinical infection were estimated to range from 1 to 37 or more (median = 4). Four acutely infected subjects showed a distinctly different pattern of virus diversity that deviated from a star-like phylogeny. In these cases, empirical analysis and mathematical modeling suggested high multiplicity virus transmission from individuals who themselves were acutely infected or had experienced a virus population bottleneck due to antiviral drug therapy. These results provide new quantitative and qualitative insights into HCV transmission, revealing for the first time virus-host interactions that successful vaccines or treatment interventions will need to overcome. Our findings further suggest a novel experimental strategy for identifying full-length T/F genomes for proteome-wide analyses of HCV biology and adaptation to antiviral drug or immune pressures. PMID:22927816

Identification of multiple serine to asparagine sequence variation sites in an intended copy product of LUCENTIS® by mass spectrometry.

PubMed

Griaud, François; Winter, Andrej; Denefeld, Blandine; Lang, Manuel; Hensinger, Héloïse; Straube, Frank; Sackewitz, Mirko; Berg, Matthias

Patent expiration of first-generation biologics and the high cost of innovative biologics are 2 drivers for the development of biosimilar products. There are, however, technical challenges to the production of exact copies of such large molecules. In this study, we performed a head-to-head comparison between the originator anti-VEGF-A Fab product LUCENTIS® (ranibizumab) and an intended copy product using an integrated analytical approach. While no differences could be observed using size-exclusion chromatography, capillary electrophoresis-sodium dodecyl sulfate and potency assays, different acidic peaks were identified with cation ion exchange chromatography and capillary zone electrophoresis. Further investigation of the intact Fab, subunits and primary sequence with mass spectrometry demonstrated the presence of a modified light chain variant in the intended copy product batches. This variant was characterized with a mass increase of 27.01 Da compared to the originator sequence and its abundance was estimated in the range of 6-9% of the intended copy product light chain. MS/MS spectra interrogation confirmed that this modification relates to a serine to asparagine sequence variant found in the intended copy product light chain. We demonstrated that the integration of high-resolution and sensitive orthogonal technologies was beneficial to assess the similarity of an originator and an intended copy product.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species.

PubMed

Perumal, Deepak; Lim, Chu Sing; Chow, Vincent T K; Sakharkar, Kishore R; Sakharkar, Meena K

2008-09-10

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

MSDB: A Comprehensive Database of Simple Sequence Repeats.

PubMed

Avvaru, Akshay Kumar; Saxena, Saketh; Sowpati, Divya Tej; Mishra, Rakesh Kumar

2017-06-01

Microsatellites, also known as Simple Sequence Repeats (SSRs), are short tandem repeats of 1-6 nt motifs present in all genomes, particularly eukaryotes. Besides their usefulness as genome markers, SSRs have been shown to perform important regulatory functions, and variations in their length at coding regions are linked to several disorders in humans. Microsatellites show a taxon-specific enrichment in eukaryotic genomes, and some may be functional. MSDB (Microsatellite Database) is a collection of >650 million SSRs from 6,893 species including Bacteria, Archaea, Fungi, Plants, and Animals. This database is by far the most exhaustive resource to access and analyze SSR data of multiple species. In addition to exploring data in a customizable tabular format, users can view and compare the data of multiple species simultaneously using our interactive plotting system. MSDB is developed using the Django framework and MySQL. It is freely available at http://tdb.ccmb.res.in/msdb. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.

PubMed

Werling, Donna M; Brand, Harrison; An, Joon-Yong; Stone, Matthew R; Zhu, Lingxue; Glessner, Joseph T; Collins, Ryan L; Dong, Shan; Layer, Ryan M; Markenscoff-Papadimitriou, Eirene; Farrell, Andrew; Schwartz, Grace B; Wang, Harold Z; Currall, Benjamin B; Zhao, Xuefang; Dea, Jeanselle; Duhn, Clif; Erdman, Carolyn A; Gilson, Michael C; Yadav, Rachita; Handsaker, Robert E; Kashin, Seva; Klei, Lambertus; Mandell, Jeffrey D; Nowakowski, Tomasz J; Liu, Yuwen; Pochareddy, Sirisha; Smith, Louw; Walker, Michael F; Waterman, Matthew J; He, Xin; Kriegstein, Arnold R; Rubenstein, John L; Sestan, Nenad; McCarroll, Steven A; Neale, Benjamin M; Coon, Hilary; Willsey, A Jeremy; Buxbaum, Joseph D; Daly, Mark J; State, Matthew W; Quinlan, Aaron R; Marth, Gabor T; Roeder, Kathryn; Devlin, Bernie; Talkowski, Michael E; Sanders, Stephan J

2018-05-01

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

Hexagonal ice in pure water and biological NMR samples.

PubMed

Bauer, Thomas; Gath, Julia; Hunkeler, Andreas; Ernst, Matthias; Böckmann, Anja; Meier, Beat H

2017-01-01

Ice, in addition to "liquid" water and protein, is an important component of protein samples for NMR spectroscopy at subfreezing temperatures but it has rarely been observed spectroscopically in this context. We characterize its spectroscopic behavior in the temperature range from 100 to 273 K, and find that it behaves like pure water ice. The interference of magic-angle spinning (MAS) as well as rf multiple-pulse sequences with Bjerrum-defect motion greatly influences the ice spectra.

Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps.

PubMed

Mortazavi, Ali; Pepke, Shirley; Jansen, Camden; Marinov, Georgi K; Ernst, Jason; Kellis, Manolis; Hardison, Ross C; Myers, Richard M; Wold, Barbara J

2013-12-01

We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and mine diverse genomics data types, including complex chromatin signatures. A fine-grained SOM was trained on 72 ChIP-seq histone modifications and DNase-seq data sets from six biologically diverse cell lines studied by The ENCODE Project Consortium. We mined the resulting SOM to identify chromatin signatures related to sequence-specific transcription factor occupancy, sequence motif enrichment, and biological functions. To highlight clusters enriched for specific functions such as transcriptional promoters or enhancers, we overlaid onto the map additional data sets not used during training, such as ChIP-seq, RNA-seq, CAGE, and information on cis-acting regulatory modules from the literature. We used the SOM to parse known transcriptional enhancers according to the cell-type-specific chromatin signature, and we further corroborated this pattern on the map by EP300 (also known as p300) occupancy. New candidate cell-type-specific enhancers were identified for multiple ENCODE cell types in this way, along with new candidates for ubiquitous enhancer activity. An interactive web interface was developed to allow users to visualize and custom-mine the ENCODE SOM. We conclude that large SOMs trained on chromatin data from multiple cell types provide a powerful way to identify complex relationships in genomic data at user-selected levels of granularity.

Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps

PubMed Central

Mortazavi, Ali; Pepke, Shirley; Jansen, Camden; Marinov, Georgi K.; Ernst, Jason; Kellis, Manolis; Hardison, Ross C.; Myers, Richard M.; Wold, Barbara J.

2013-01-01

We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and mine diverse genomics data types, including complex chromatin signatures. A fine-grained SOM was trained on 72 ChIP-seq histone modifications and DNase-seq data sets from six biologically diverse cell lines studied by The ENCODE Project Consortium. We mined the resulting SOM to identify chromatin signatures related to sequence-specific transcription factor occupancy, sequence motif enrichment, and biological functions. To highlight clusters enriched for specific functions such as transcriptional promoters or enhancers, we overlaid onto the map additional data sets not used during training, such as ChIP-seq, RNA-seq, CAGE, and information on cis-acting regulatory modules from the literature. We used the SOM to parse known transcriptional enhancers according to the cell-type-specific chromatin signature, and we further corroborated this pattern on the map by EP300 (also known as p300) occupancy. New candidate cell-type-specific enhancers were identified for multiple ENCODE cell types in this way, along with new candidates for ubiquitous enhancer activity. An interactive web interface was developed to allow users to visualize and custom-mine the ENCODE SOM. We conclude that large SOMs trained on chromatin data from multiple cell types provide a powerful way to identify complex relationships in genomic data at user-selected levels of granularity. PMID:24170599

BIOSPIDA: A Relational Database Translator for NCBI

PubMed Central

Hagen, Matthew S.; Lee, Eva K.

2010-01-01

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time. PMID:21347013

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.

Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data

PubMed Central

2010-01-01

Background In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models. Results The latest advances in the field allowed us to use a technique of optimal Markov chain embedding based on deterministic finite automata to introduce three innovative algorithms. Algorithm 1 is the only one able to deal with heterogeneous models. It also permits to avoid any product of convolution of the pattern distribution in individual sequences. When working with homogeneous models, Algorithm 2 yields a dramatic reduction in the complexity by taking advantage of previous computations to obtain moment generating functions efficiently. In the particular case of low or moderate complexity patterns, Algorithm 3 exploits power computation and binary decomposition to further reduce the time complexity to a logarithmic scale. All these algorithms and their relative interest in comparison with existing ones were then tested and discussed on a toy-example and three biological data sets: structural patterns in protein loop structures, PROSITE signatures in a bacterial proteome, and transcription factors in upstream gene regions. On these data sets, we also compared our exact approaches to the tempting approximation that consists in concatenating the sequences in the data set into a single sequence. Conclusions Our algorithms prove to be effective and able to handle real data sets with multiple sequences, as well as biological patterns of interest, even when the latter display a high complexity (PROSITE signatures for example). In addition, these exact algorithms allow us to avoid the edge effect observed under the single sequence approximation, which leads to erroneous results, especially when the marginal distribution of the model displays a slow convergence toward the stationary distribution. We end up with a discussion on our method and on its potential improvements. PMID:20205909

Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data.

PubMed

Nuel, Gregory; Regad, Leslie; Martin, Juliette; Camproux, Anne-Claude

2010-01-26

In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models. The latest advances in the field allowed us to use a technique of optimal Markov chain embedding based on deterministic finite automata to introduce three innovative algorithms. Algorithm 1 is the only one able to deal with heterogeneous models. It also permits to avoid any product of convolution of the pattern distribution in individual sequences. When working with homogeneous models, Algorithm 2 yields a dramatic reduction in the complexity by taking advantage of previous computations to obtain moment generating functions efficiently. In the particular case of low or moderate complexity patterns, Algorithm 3 exploits power computation and binary decomposition to further reduce the time complexity to a logarithmic scale. All these algorithms and their relative interest in comparison with existing ones were then tested and discussed on a toy-example and three biological data sets: structural patterns in protein loop structures, PROSITE signatures in a bacterial proteome, and transcription factors in upstream gene regions. On these data sets, we also compared our exact approaches to the tempting approximation that consists in concatenating the sequences in the data set into a single sequence. Our algorithms prove to be effective and able to handle real data sets with multiple sequences, as well as biological patterns of interest, even when the latter display a high complexity (PROSITE signatures for example). In addition, these exact algorithms allow us to avoid the edge effect observed under the single sequence approximation, which leads to erroneous results, especially when the marginal distribution of the model displays a slow convergence toward the stationary distribution. We end up with a discussion on our method and on its potential improvements.

Prospective identification of parasitic sequences in phage display screens

PubMed Central

Matochko, Wadim L.; Cory Li, S.; Tang, Sindy K.Y.; Derda, Ratmir

2014-01-01

Phage display empowered the development of proteins with new function and ligands for clinically relevant targets. In this report, we use next-generation sequencing to analyze phage-displayed libraries and uncover a strong bias induced by amplification preferences of phage in bacteria. This bias favors fast-growing sequences that collectively constitute <0.01% of the available diversity. Specifically, a library of 109 random 7-mer peptides (Ph.D.-7) includes a few thousand sequences that grow quickly (the ‘parasites’), which are the sequences that are typically identified in phage display screens published to date. A similar collapse was observed in other libraries. Using Illumina and Ion Torrent sequencing and multiple biological replicates of amplification of Ph.D.-7 library, we identified a focused population of 770 ‘parasites’. In all, 197 sequences from this population have been identified in literature reports that used Ph.D.-7 library. Many of these enriched sequences have confirmed function (e.g. target binding capacity). The bias in the literature, thus, can be viewed as a selection with two different selection pressures: (i) target-binding selection, and (ii) amplification-induced selection. Enrichment of parasitic sequences could be minimized if amplification bias is removed. Here, we demonstrate that emulsion amplification in libraries of ∼106 diverse clones prevents the biased selection of parasitic clones. PMID:24217917

Genome-wide characterization of centromeric satellites from multiple mammalian genomes.

PubMed

Alkan, Can; Cardone, Maria Francesca; Catacchio, Claudia Rita; Antonacci, Francesca; O'Brien, Stephen J; Ryder, Oliver A; Purgato, Stefania; Zoli, Monica; Della Valle, Giuliano; Eichler, Evan E; Ventura, Mario

2011-01-01

Despite its importance in cell biology and evolution, the centromere has remained the final frontier in genome assembly and annotation due to its complex repeat structure. However, isolation and characterization of the centromeric repeats from newly sequenced species are necessary for a complete understanding of genome evolution and function. In recent years, various genomes have been sequenced, but the characterization of the corresponding centromeric DNA has lagged behind. Here, we present a computational method (RepeatNet) to systematically identify higher-order repeat structures from unassembled whole-genome shotgun sequence and test whether these sequence elements correspond to functional centromeric sequences. We analyzed genome datasets from six species of mammals representing the diversity of the mammalian lineage, namely, horse, dog, elephant, armadillo, opossum, and platypus. We define candidate monomer satellite repeats and demonstrate centromeric localization for five of the six genomes. Our analysis revealed the greatest diversity of centromeric sequences in horse and dog in contrast to elephant and armadillo, which showed high-centromeric sequence homogeneity. We could not isolate centromeric sequences within the platypus genome, suggesting that centromeres in platypus are not enriched in satellite DNA. Our method can be applied to the characterization of thousands of other vertebrate genomes anticipated for sequencing in the near future, providing an important tool for annotation of centromeres.

A confidence interval analysis of sampling effort, sequencing depth, and taxonomic resolution of fungal community ecology in the era of high-throughput sequencing.

PubMed

Oono, Ryoko

2017-01-01

High-throughput sequencing technology has helped microbial community ecologists explore ecological and evolutionary patterns at unprecedented scales. The benefits of a large sample size still typically outweigh that of greater sequencing depths per sample for accurate estimations of ecological inferences. However, excluding or not sequencing rare taxa may mislead the answers to the questions 'how and why are communities different?' This study evaluates the confidence intervals of ecological inferences from high-throughput sequencing data of foliar fungal endophytes as case studies through a range of sampling efforts, sequencing depths, and taxonomic resolutions to understand how technical and analytical practices may affect our interpretations. Increasing sampling size reliably decreased confidence intervals across multiple community comparisons. However, the effects of sequencing depths on confidence intervals depended on how rare taxa influenced the dissimilarity estimates among communities and did not significantly decrease confidence intervals for all community comparisons. A comparison of simulated communities under random drift suggests that sequencing depths are important in estimating dissimilarities between microbial communities under neutral selective processes. Confidence interval analyses reveal important biases as well as biological trends in microbial community studies that otherwise may be ignored when communities are only compared for statistically significant differences.

Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences

PubMed Central

Sevy, Alexander M.; Jacobs, Tim M.; Crowe, James E.; Meiler, Jens

2015-01-01

Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a ‘single state’ design (SSD) paradigm. Multi-specificity design (MSD), on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON). The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain) an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design “promiscuous”, polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes. PMID:26147100

A confidence interval analysis of sampling effort, sequencing depth, and taxonomic resolution of fungal community ecology in the era of high-throughput sequencing

PubMed Central

2017-01-01

High-throughput sequencing technology has helped microbial community ecologists explore ecological and evolutionary patterns at unprecedented scales. The benefits of a large sample size still typically outweigh that of greater sequencing depths per sample for accurate estimations of ecological inferences. However, excluding or not sequencing rare taxa may mislead the answers to the questions ‘how and why are communities different?’ This study evaluates the confidence intervals of ecological inferences from high-throughput sequencing data of foliar fungal endophytes as case studies through a range of sampling efforts, sequencing depths, and taxonomic resolutions to understand how technical and analytical practices may affect our interpretations. Increasing sampling size reliably decreased confidence intervals across multiple community comparisons. However, the effects of sequencing depths on confidence intervals depended on how rare taxa influenced the dissimilarity estimates among communities and did not significantly decrease confidence intervals for all community comparisons. A comparison of simulated communities under random drift suggests that sequencing depths are important in estimating dissimilarities between microbial communities under neutral selective processes. Confidence interval analyses reveal important biases as well as biological trends in microbial community studies that otherwise may be ignored when communities are only compared for statistically significant differences. PMID:29253889

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Improved design of hammerhead ribozyme for selective digestion of target RNA through recognition of site-specific adenosine-to-inosine RNA editing

PubMed Central

Fukuda, Masatora; Kurihara, Kei; Yamaguchi, Shota; Oyama, Yui; Deshimaru, Masanobu

2014-01-01

Adenosine-to-inosine (A-to-I) RNA editing is an endogenous regulatory mechanism involved in various biological processes. Site-specific, editing-state–dependent degradation of target RNA may be a powerful tool both for analyzing the mechanism of RNA editing and for regulating biological processes. Previously, we designed an artificial hammerhead ribozyme (HHR) for selective, site-specific RNA cleavage dependent on the A-to-I RNA editing state. In the present work, we developed an improved strategy for constructing a trans-acting HHR that specifically cleaves target editing sites in the adenosine but not the inosine state. Specificity for unedited sites was achieved by utilizing a sequence encoding the intrinsic cleavage specificity of a natural HHR. We used in vitro selection methods in an HHR library to select for an extended HHR containing a tertiary stabilization motif that facilitates HHR folding into an active conformation. By using this method, we successfully constructed highly active HHRs with unedited-specific cleavage. Moreover, using HHR cleavage followed by direct sequencing, we demonstrated that this ribozyme could cleave serotonin 2C receptor (HTR2C) mRNA extracted from mouse brain, depending on the site-specific editing state. This unedited-specific cleavage also enabled us to analyze the effect of editing state at the E and C sites on editing at other sites by using direct sequencing for the simultaneous quantification of the editing ratio at multiple sites. Our approach has the potential to elucidate the mechanism underlying the interdependencies of different editing states in substrate RNA with multiple editing sites. PMID:24448449

Subclonal diversification of primary breast cancer revealed by multiregion sequencing

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

Yates, Lucy R.; Gerstung, Moritz; Knappskog, Stian

Sequencing cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and latemore » in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.« less

Subclonal diversification of primary breast cancer revealed by multiregion sequencing

DOE PAGES

Yates, Lucy R.; Gerstung, Moritz; Knappskog, Stian; ...

2015-06-22

Sequencing cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and latemore » in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.« less

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

A Systolic Array-Based FPGA Parallel Architecture for the BLAST Algorithm

PubMed Central

Guo, Xinyu; Wang, Hong; Devabhaktuni, Vijay

2012-01-01

A design of systolic array-based Field Programmable Gate Array (FPGA) parallel architecture for Basic Local Alignment Search Tool (BLAST) Algorithm is proposed. BLAST is a heuristic biological sequence alignment algorithm which has been used by bioinformatics experts. In contrast to other designs that detect at most one hit in one-clock-cycle, our design applies a Multiple Hits Detection Module which is a pipelining systolic array to search multiple hits in a single-clock-cycle. Further, we designed a Hits Combination Block which combines overlapping hits from systolic array into one hit. These implementations completed the first and second step of BLAST architecture and achieved significant speedup comparing with previously published architectures. PMID:25969747

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

The dynamics of genome replication using deep sequencing

PubMed Central

Müller, Carolin A.; Hawkins, Michelle; Retkute, Renata; Malla, Sunir; Wilson, Ray; Blythe, Martin J.; Nakato, Ryuichiro; Komata, Makiko; Shirahige, Katsuhiko; de Moura, Alessandro P.S.; Nieduszynski, Conrad A.

2014-01-01

Eukaryotic genomes are replicated from multiple DNA replication origins. We present complementary deep sequencing approaches to measure origin location and activity in Saccharomyces cerevisiae. Measuring the increase in DNA copy number during a synchronous S-phase allowed the precise determination of genome replication. To map origin locations, replication forks were stalled close to their initiation sites; therefore, copy number enrichment was limited to origins. Replication timing profiles were generated from asynchronous cultures using fluorescence-activated cell sorting. Applying this technique we show that the replication profiles of haploid and diploid cells are indistinguishable, indicating that both cell types use the same cohort of origins with the same activities. Finally, increasing sequencing depth allowed the direct measure of replication dynamics from an exponentially growing culture. This is the first time this approach, called marker frequency analysis, has been successfully applied to a eukaryote. These data provide a high-resolution resource and methodological framework for studying genome biology. PMID:24089142

Unique features of a global human ectoparasite identified through sequencing of the bed bug genome.

PubMed

Benoit, Joshua B; Adelman, Zach N; Reinhardt, Klaus; Dolan, Amanda; Poelchau, Monica; Jennings, Emily C; Szuter, Elise M; Hagan, Richard W; Gujar, Hemant; Shukla, Jayendra Nath; Zhu, Fang; Mohan, M; Nelson, David R; Rosendale, Andrew J; Derst, Christian; Resnik, Valentina; Wernig, Sebastian; Menegazzi, Pamela; Wegener, Christian; Peschel, Nicolai; Hendershot, Jacob M; Blenau, Wolfgang; Predel, Reinhard; Johnston, Paul R; Ioannidis, Panagiotis; Waterhouse, Robert M; Nauen, Ralf; Schorn, Corinna; Ott, Mark-Christoph; Maiwald, Frank; Johnston, J Spencer; Gondhalekar, Ameya D; Scharf, Michael E; Peterson, Brittany F; Raje, Kapil R; Hottel, Benjamin A; Armisén, David; Crumière, Antonin Jean Johan; Refki, Peter Nagui; Santos, Maria Emilia; Sghaier, Essia; Viala, Sèverine; Khila, Abderrahman; Ahn, Seung-Joon; Childers, Christopher; Lee, Chien-Yueh; Lin, Han; Hughes, Daniel S T; Duncan, Elizabeth J; Murali, Shwetha C; Qu, Jiaxin; Dugan, Shannon; Lee, Sandra L; Chao, Hsu; Dinh, Huyen; Han, Yi; Doddapaneni, Harshavardhan; Worley, Kim C; Muzny, Donna M; Wheeler, David; Panfilio, Kristen A; Vargas Jentzsch, Iris M; Vargo, Edward L; Booth, Warren; Friedrich, Markus; Weirauch, Matthew T; Anderson, Michelle A E; Jones, Jeffery W; Mittapalli, Omprakash; Zhao, Chaoyang; Zhou, Jing-Jiang; Evans, Jay D; Attardo, Geoffrey M; Robertson, Hugh M; Zdobnov, Evgeny M; Ribeiro, Jose M C; Gibbs, Richard A; Werren, John H; Palli, Subba R; Schal, Coby; Richards, Stephen

2016-02-02

The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host-symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human-bed bug and symbiont-bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite.

Parallel Continuous Flow: A Parallel Suffix Tree Construction Tool for Whole Genomes

PubMed Central

Farreras, Montse

2014-01-01

Abstract The construction of suffix trees for very long sequences is essential for many applications, and it plays a central role in the bioinformatic domain. With the advent of modern sequencing technologies, biological sequence databases have grown dramatically. Also the methodologies required to analyze these data have become more complex everyday, requiring fast queries to multiple genomes. In this article, we present parallel continuous flow (PCF), a parallel suffix tree construction method that is suitable for very long genomes. We tested our method for the suffix tree construction of the entire human genome, about 3GB. We showed that PCF can scale gracefully as the size of the input genome grows. Our method can work with an efficiency of 90% with 36 processors and 55% with 172 processors. We can index the human genome in 7 minutes using 172 processes. PMID:24597675

Unique features of a global human ectoparasite identified through sequencing of the bed bug genome

PubMed Central

Benoit, Joshua B.; Adelman, Zach N.; Reinhardt, Klaus; Dolan, Amanda; Poelchau, Monica; Jennings, Emily C.; Szuter, Elise M.; Hagan, Richard W.; Gujar, Hemant; Shukla, Jayendra Nath; Zhu, Fang; Mohan, M.; Nelson, David R.; Rosendale, Andrew J.; Derst, Christian; Resnik, Valentina; Wernig, Sebastian; Menegazzi, Pamela; Wegener, Christian; Peschel, Nicolai; Hendershot, Jacob M.; Blenau, Wolfgang; Predel, Reinhard; Johnston, Paul R.; Ioannidis, Panagiotis; Waterhouse, Robert M.; Nauen, Ralf; Schorn, Corinna; Ott, Mark-Christoph; Maiwald, Frank; Johnston, J. Spencer; Gondhalekar, Ameya D.; Scharf, Michael E.; Peterson, Brittany F.; Raje, Kapil R.; Hottel, Benjamin A.; Armisén, David; Crumière, Antonin Jean Johan; Refki, Peter Nagui; Santos, Maria Emilia; Sghaier, Essia; Viala, Sèverine; Khila, Abderrahman; Ahn, Seung-Joon; Childers, Christopher; Lee, Chien-Yueh; Lin, Han; Hughes, Daniel S. T.; Duncan, Elizabeth J.; Murali, Shwetha C.; Qu, Jiaxin; Dugan, Shannon; Lee, Sandra L.; Chao, Hsu; Dinh, Huyen; Han, Yi; Doddapaneni, Harshavardhan; Worley, Kim C.; Muzny, Donna M.; Wheeler, David; Panfilio, Kristen A.; Vargas Jentzsch, Iris M.; Vargo, Edward L.; Booth, Warren; Friedrich, Markus; Weirauch, Matthew T.; Anderson, Michelle A. E.; Jones, Jeffery W.; Mittapalli, Omprakash; Zhao, Chaoyang; Zhou, Jing-Jiang; Evans, Jay D.; Attardo, Geoffrey M.; Robertson, Hugh M.; Zdobnov, Evgeny M.; Ribeiro, Jose M. C.; Gibbs, Richard A.; Werren, John H.; Palli, Subba R.; Schal, Coby; Richards, Stephen

2016-01-01

The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host–symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human–bed bug and symbiont–bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite. PMID:26836814

A Multiple-Sequence Variant of the Multiple-Baseline Design: A Strategy for Analysis of Sequence Effects and Treatment Comparison.

ERIC Educational Resources Information Center

Noell, George H.; Gresham, Frank M.

2001-01-01

Describes design logic and potential uses of a variant of the multiple-baseline design. The multiple-baseline multiple-sequence (MBL-MS) consists of multiple-baseline designs that are interlaced with one another and include all possible sequences of treatments. The MBL-MS design appears to be primarily useful for comparison of treatments taking…

Sequential addition of short DNA oligos in DNA-polymerase-based synthesis reactions

DOEpatents

Gardner, Shea N; Mariella, Jr., Raymond P; Christian, Allen T; Young, Jennifer A; Clague, David S

2013-06-25

A method of preselecting a multiplicity of DNA sequence segments that will comprise the DNA molecule of user-defined sequence, separating the DNA sequence segments temporally, and combining the multiplicity of DNA sequence segments with at least one polymerase enzyme wherein the multiplicity of DNA sequence segments join to produce the DNA molecule of user-defined sequence. Sequence segments may be of length n, where n is an odd integer. In one embodiment the length of desired hybridizing overlap is specified by the user and the sequences and the protocol for combining them are guided by computational (bioinformatics) predictions. In one embodiment sequence segments are combined from multiple reading frames to span the same region of a sequence, so that multiple desired hybridizations may occur with different overlap lengths.

Using Genotype Abundance to Improve Phylogenetic Inference

PubMed Central

Mesin, Luka; Victora, Gabriel D; Minin, Vladimir N; Matsen, Frederick A

2018-01-01

Abstract Modern biological techniques enable very dense genetic sampling of unfolding evolutionary histories, and thus frequently sample some genotypes multiple times. This motivates strategies to incorporate genotype abundance information in phylogenetic inference. In this article, we synthesize a stochastic process model with standard sequence-based phylogenetic optimality, and show that tree estimation is substantially improved by doing so. Our method is validated with extensive simulations and an experimental single-cell lineage tracing study of germinal center B cell receptor affinity maturation. PMID:29474671

Aligning the unalignable: bacteriophage whole genome alignments.

PubMed

Bérard, Sèverine; Chateau, Annie; Pompidor, Nicolas; Guertin, Paul; Bergeron, Anne; Swenson, Krister M

2016-01-13

In recent years, many studies focused on the description and comparison of large sets of related bacteriophage genomes. Due to the peculiar mosaic structure of these genomes, few informative approaches for comparing whole genomes exist: dot plots diagrams give a mostly qualitative assessment of the similarity/dissimilarity between two or more genomes, and clustering techniques are used to classify genomes. Multiple alignments are conspicuously absent from this scene. Indeed, whole genome aligners interpret lack of similarity between sequences as an indication of rearrangements, insertions, or losses. This behavior makes them ill-prepared to align bacteriophage genomes, where even closely related strains can accomplish the same biological function with highly dissimilar sequences. In this paper, we propose a multiple alignment strategy that exploits functional collinearity shared by related strains of bacteriophages, and uses partial orders to capture mosaicism of sets of genomes. As classical alignments do, the computed alignments can be used to predict that genes have the same biological function, even in the absence of detectable similarity. The Alpha aligner implements these ideas in visual interactive displays, and is used to compute several examples of alignments of Staphylococcus aureus and Mycobacterium bacteriophages, involving up to 29 genomes. Using these datasets, we prove that Alpha alignments are at least as good as those computed by standard aligners. Comparison with the progressive Mauve aligner - which implements a partial order strategy, but whose alignments are linearized - shows a greatly improved interactive graphic display, while avoiding misalignments. Multiple alignments of whole bacteriophage genomes work, and will become an important conceptual and visual tool in comparative genomics of sets of related strains. A python implementation of Alpha, along with installation instructions for Ubuntu and OSX, is available on bitbucket (https://bitbucket.org/thekswenson/alpha).

Dryland biological soil crust cyanobacteria show unexpected decreases in abundance under long-term elevated CO2.

PubMed

Steven, Blaire; Gallegos-Graves, La Verne; Yeager, Chris M; Belnap, Jayne; Evans, R David; Kuske, Cheryl R

2012-12-01

Biological soil crusts (biocrusts) cover soil surfaces in many drylands globally. The impacts of 10 years of elevated atmospheric CO2 on the cyanobacteria in biocrusts of an arid shrubland were examined at a large manipulated experiment in Nevada, USA. Cyanobacteria-specific quantitative PCR surveys of cyanobacteria small-subunit (SSU) rRNA genes suggested a reduction in biocrust cyanobacterial biomass in the elevated CO2 treatment relative to the ambient controls. Additionally, SSU rRNA gene libraries and shotgun metagenomes showed reduced representation of cyanobacteria in the total microbial community. Taxonomic composition of the cyanobacteria was similar under ambient and elevated CO2 conditions, indicating the decline was manifest across multiple cyanobacterial lineages. Recruitment of cyanobacteria sequences from replicate shotgun metagenomes to cyanobacterial genomes representing major biocrust orders also suggested decreased abundance of cyanobacteria sequences across the majority of genomes tested. Functional assignment of cyanobacteria-related shotgun metagenome sequences indicated that four subsystem categories, three related to oxidative stress, were differentially abundant in relation to the elevated CO2 treatment. Taken together, these results suggest that elevated CO2 affected a generalized decrease in cyanobacteria in the biocrusts and may have favoured cyanobacteria with altered gene inventories for coping with oxidative stress. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Dryland biological soil crust cyanobacteria show unexpected decreases in abundance under long-term elevated CO2

USGS Publications Warehouse

Steven, Blaire; Gallegos-Graves, La Verne; Yeager, Chris M.; Belnap, Jayne; Evans, R. David; Kuske, Cheryl R.

2012-01-01

Biological soil crusts (biocrusts) cover soil surfaces in many drylands globally. The impacts of 10 years of elevated atmospheric CO2 on the cyanobacteria in biocrusts of an arid shrubland were examined at a large manipulated experiment in Nevada, USA. Cyanobacteria-specific quantitative PCR surveys of cyanobacteria small-subunit (SSU) rRNA genes suggested a reduction in biocrust cyanobacterial biomass in the elevated CO2 treatment relative to the ambient controls. Additionally, SSU rRNA gene libraries and shotgun metagenomes showed reduced representation of cyanobacteria in the total microbial community. Taxonomic composition of the cyanobacteria was similar under ambient and elevated CO2 conditions, indicating the decline was manifest across multiple cyanobacterial lineages. Recruitment of cyanobacteria sequences from replicate shotgun metagenomes to cyanobacterial genomes representing major biocrust orders also suggested decreased abundance of cyanobacteria sequences across the majority of genomes tested. Functional assignment of cyanobacteria-related shotgun metagenome sequences indicated that four subsystem categories, three related to oxidative stress, were differentially abundant in relation to the elevated CO2 treatment. Taken together, these results suggest that elevated CO2 affected a generalized decrease in cyanobacteria in the biocrusts and may have favoured cyanobacteria with altered gene inventories for coping with oxidative stress.

SeqCompress: an algorithm for biological sequence compression.

PubMed

Sardaraz, Muhammad; Tahir, Muhammad; Ikram, Ataul Aziz; Bajwa, Hassan

2014-10-01

The growth of Next Generation Sequencing technologies presents significant research challenges, specifically to design bioinformatics tools that handle massive amount of data efficiently. Biological sequence data storage cost has become a noticeable proportion of total cost in the generation and analysis. Particularly increase in DNA sequencing rate is significantly outstripping the rate of increase in disk storage capacity, which may go beyond the limit of storage capacity. It is essential to develop algorithms that handle large data sets via better memory management. This article presents a DNA sequence compression algorithm SeqCompress that copes with the space complexity of biological sequences. The algorithm is based on lossless data compression and uses statistical model as well as arithmetic coding to compress DNA sequences. The proposed algorithm is compared with recent specialized compression tools for biological sequences. Experimental results show that proposed algorithm has better compression gain as compared to other existing algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Angiosperm phylogeny inferred from multiple genes as a tool for comparative biology.

PubMed

Soltis, P S; Soltis, D E; Chase, M W

1999-11-25

Comparative biology requires a firm phylogenetic foundation to uncover and understand patterns of diversification and evaluate hypotheses of the processes responsible for these patterns. In the angiosperms, studies of diversification in floral form, stamen organization, reproductive biology, photosynthetic pathway, nitrogen-fixing symbioses and life histories have relied on either explicit or implied phylogenetic trees. Furthermore, to understand the evolution of specific genes and gene families, evaluate the extent of conservation of plant genomes and make proper sense of the huge volume of molecular genetic data available for model organisms such as Arabidopsis, Antirrhinum, maize, rice and wheat, a phylogenetic perspective is necessary. Here we report the results of parsimony analyses of DNA sequences of the plastid genes rbcL and atpB and the nuclear 18S rDNA for 560 species of angiosperms and seven non-flowering seed plants and show a well-resolved and well-supported phylogenetic tree for the angiosperms for use in comparative biology.

BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts.

PubMed

Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D; Bader, Joel S

2016-03-15

Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder joel.bader@jhu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Uptake, Results, and Outcomes of Germline Multiple-Gene Sequencing After Diagnosis of Breast Cancer.

PubMed

Kurian, Allison W; Ward, Kevin C; Hamilton, Ann S; Deapen, Dennis M; Abrahamse, Paul; Bondarenko, Irina; Li, Yun; Hawley, Sarah T; Morrow, Monica; Jagsi, Reshma; Katz, Steven J

2018-05-10

Low-cost sequencing of multiple genes is increasingly available for cancer risk assessment. Little is known about uptake or outcomes of multiple-gene sequencing after breast cancer diagnosis in community practice. To examine the effect of multiple-gene sequencing on the experience and treatment outcomes for patients with breast cancer. For this population-based retrospective cohort study, patients with breast cancer diagnosed from January 2013 to December 2015 and accrued from SEER registries across Georgia and in Los Angeles, California, were surveyed (n = 5080, response rate = 70%). Responses were merged with SEER data and results of clinical genetic tests, either BRCA1 and BRCA2 (BRCA1/2) sequencing only or including additional other genes (multiple-gene sequencing), provided by 4 laboratories. Type of testing (multiple-gene sequencing vs BRCA1/2-only sequencing), test results (negative, variant of unknown significance, or pathogenic variant), patient experiences with testing (timing of testing, who discussed results), and treatment (strength of patient consideration of, and surgeon recommendation for, prophylactic mastectomy), and prophylactic mastectomy receipt. We defined a patient subgroup with higher pretest risk of carrying a pathogenic variant according to practice guidelines. Among 5026 patients (mean [SD] age, 59.9 [10.7]), 1316 (26.2%) were linked to genetic results from any laboratory. Multiple-gene sequencing increasingly replaced BRCA1/2-only testing over time: in 2013, the rate of multiple-gene sequencing was 25.6% and BRCA1/2-only testing, 74.4%;in 2015 the rate of multiple-gene sequencing was 66.5% and BRCA1/2-only testing, 33.5%. Multiple-gene sequencing was more often ordered by genetic counselors (multiple-gene sequencing, 25.5% and BRCA1/2-only testing, 15.3%) and delayed until after surgery (multiple-gene sequencing, 32.5% and BRCA1/2-only testing, 19.9%). Multiple-gene sequencing substantially increased rate of detection of any pathogenic variant (multiple-gene sequencing: higher-risk patients, 12%; average-risk patients, 4.2% and BRCA1/2-only testing: higher-risk patients, 7.8%; average-risk patients, 2.2%) and variants of uncertain significance, especially in minorities (multiple-gene sequencing: white patients, 23.7%; black patients, 44.5%; and Asian patients, 50.9% and BRCA1/2-only testing: white patients, 2.2%; black patients, 5.6%; and Asian patients, 0%). Multiple-gene sequencing was not associated with an increase in the rate of prophylactic mastectomy use, which was highest with pathogenic variants in BRCA1/2 (BRCA1/2, 79.0%; other pathogenic variant, 37.6%; variant of uncertain significance, 30.2%; negative, 35.3%). Multiple-gene sequencing rapidly replaced BRCA1/2-only testing for patients with breast cancer in the community and enabled 2-fold higher detection of clinically relevant pathogenic variants without an associated increase in prophylactic mastectomy. However, important targets for improvement in the clinical utility of multiple-gene sequencing include postsurgical delay and racial/ethnic disparity in variants of uncertain significance.

Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity.

PubMed

Wagner, Andreas

2014-02-18

Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

One-pot DNA construction for synthetic biology: the Modular Overlap-Directed Assembly with Linkers (MODAL) strategy

PubMed Central

Casini, Arturo; MacDonald, James T.; Jonghe, Joachim De; Christodoulou, Georgia; Freemont, Paul S.; Baldwin, Geoff S.; Ellis, Tom

2014-01-01

Overlap-directed DNA assembly methods allow multiple DNA parts to be assembled together in one reaction. These methods, which rely on sequence homology between the ends of DNA parts, have become widely adopted in synthetic biology, despite being incompatible with a key principle of engineering: modularity. To answer this, we present MODAL: a Modular Overlap-Directed Assembly with Linkers strategy that brings modularity to overlap-directed methods, allowing assembly of an initial set of DNA parts into a variety of arrangements in one-pot reactions. MODAL is accompanied by a custom software tool that designs overlap linkers to guide assembly, allowing parts to be assembled in any specified order and orientation. The in silico design of synthetic orthogonal overlapping junctions allows for much greater efficiency in DNA assembly for a variety of different methods compared with using non-designed sequence. In tests with three different assembly technologies, the MODAL strategy gives assembly of both yeast and bacterial plasmids, composed of up to five DNA parts in the kilobase range with efficiencies of between 75 and 100%. It also seamlessly allows mutagenesis to be performed on any specified DNA parts during the process, allowing the one-step creation of construct libraries valuable for synthetic biology applications. PMID:24153110

Harnessing glycomics technologies: integrating structure with function for glycan characterization

PubMed Central

Robinson, Luke N.; Artpradit, Charlermchai; Raman, Rahul; Shriver, Zachary H.; Ruchirawat, Mathuros; Sasisekharan, Ram

2013-01-01

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecules which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships. PMID:22522536

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.

Glyceraldehyde-3-phosphate dehydrogenase from Chironomidae showed differential activity towards metals.

PubMed

Chong, Isaac K W; Ho, Wing S

2013-09-01

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is known to interact with different biomolecules and was implicated in many novel cellular activities including programmed cell death, nuclear RNA transport unrelated to the commonly known carbohydrate metabolism. We reported here the purification of GAPDH from Chironomidae larvae (Insecta, Diptera) that showed different biologic activity towards heavy metals. It was inhibited by copper, cobalt nickel, iron and lead but was activated by zinc. The GAPDH was purified by ammonium sulphate fractionation and Chelating Sepharose CL-6B chromatography followed by Blue Sepharose CL-6B chromatography. The 150-kDa tetrameric GAPDH showed optimal activity at pH 8.5 and 37°C. The multiple alignment of sequence of the Chironomidae GAPDH with other known species showed 78 - 88% identity to the conserved regions of the GADPH. Bioinformatic analysis unveils substantial N-terminal sequence similarity of GAPDH of Chironomidae larvae to mammalian GADPHs. However, the GADPH of Chironomidae larvae showed different biologic activities and cytotoxicity towards heavy metals. The GAPDH enzyme would undergo adaptive molecular changes through binding at the active site leading to higher tolerance to heavy metals.

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

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

RPAN: rice pan-genome browser for ∼3000 rice genomes.

PubMed

Sun, Chen; Hu, Zhiqiang; Zheng, Tianqing; Lu, Kuangchen; Zhao, Yue; Wang, Wensheng; Shi, Jianxin; Wang, Chunchao; Lu, Jinyuan; Zhang, Dabing; Li, Zhikang; Wei, Chaochun

2017-01-25

A pan-genome is the union of the gene sets of all the individuals of a clade or a species and it provides a new dimension of genome complexity with the presence/absence variations (PAVs) of genes among these genomes. With the progress of sequencing technologies, pan-genome study is becoming affordable for eukaryotes with large-sized genomes. The Asian cultivated rice, Oryza sativa L., is one of the major food sources for the world and a model organism in plant biology. Recently, the 3000 Rice Genome Project (3K RGP) sequenced more than 3000 rice genomes with a mean sequencing depth of 14.3×, which provided a tremendous resource for rice research. In this paper, we present a genome browser, Rice Pan-genome Browser (RPAN), as a tool to search and visualize the rice pan-genome derived from 3K RGP. RPAN contains a database of the basic information of 3010 rice accessions, including genomic sequences, gene annotations, PAV information and gene expression data of the rice pan-genome. At least 12 000 novel genes absent in the reference genome were included. RPAN also provides multiple search and visualization functions. RPAN can be a rich resource for rice biology and rice breeding. It is available at http://cgm.sjtu.edu.cn/3kricedb/ or http://www.rmbreeding.cn/pan3k. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Whole-genome sequencing of Bacillus subtilis XF-1 reveals mechanisms for biological control and multiple beneficial properties in plants.

PubMed

Guo, Shengye; Li, Xingyu; He, Pengfei; Ho, Honhing; Wu, Yixin; He, Yueqiu

2015-06-01

Bacillus subtilis XF-1 is a gram-positive, plant-associated bacterium that stimulates plant growth and produces secondary metabolites that suppress soil-borne plant pathogens. In particular, it is especially highly efficient at controlling the clubroot disease of cruciferous crops. Its 4,061,186-bp genome contains an estimated 3853 protein-coding sequences and the 1155 genes of XF-1 are present in most genome-sequenced Bacillus strains: 3757 genes in B. subtilis 168, and 1164 in B. amyloliquefaciens FZB42. Analysis using the Cluster of Orthologous Groups database of proteins shows that 60 genes control bacterial mobility, 221 genes are related to cell wall and membrane biosynthesis, and more than 112 are genes associated with secondary metabolites. In addition, the genes contributed to the strain's plant colonization, bio-control and stimulation of plant growth. Sequencing of the genome is a fundamental step for developing a desired strain to serve as an efficient biological control agent and plant growth stimulator. Similar to other members of the taxon, XF-1 has a genome that contains giant gene clusters for the non-ribosomal synthesis of antifungal lipopeptides (surfactin and fengycin), the polyketides (macrolactin and bacillaene), the siderophore bacillibactin, and the dipeptide bacilysin. There are two synthesis pathways for volatile growth-promoting compounds. The expression of biosynthesized antibiotic peptides in XF-1 was revealed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry.

Sequential addition of short DNA oligos in DNA-polymerase-based synthesis reactions

DOEpatents

Gardner, Shea N [San Leandro, CA; Mariella, Jr., Raymond P.; Christian, Allen T [Tracy, CA; Young, Jennifer A [Berkeley, CA; Clague, David S [Livermore, CA

2011-01-18

A method of fabricating a DNA molecule of user-defined sequence. The method comprises the steps of preselecting a multiplicity of DNA sequence segments that will comprise the DNA molecule of user-defined sequence, separating the DNA sequence segments temporally, and combining the multiplicity of DNA sequence segments with at least one polymerase enzyme wherein the multiplicity of DNA sequence segments join to produce the DNA molecule of user-defined sequence. Sequence segments may be of length n, where n is an even or odd integer. In one embodiment the length of desired hybridizing overlap is specified by the user and the sequences and the protocol for combining them are guided by computational (bioinformatics) predictions. In one embodiment sequence segments are combined from multiple reading frames to span the same region of a sequence, so that multiple desired hybridizations may occur with different overlap lengths. In one embodiment starting sequence fragments are of different lengths, n, n+1, n+2, etc.

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PubMed

Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

QuickProbs—A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

PubMed Central

Gudyś, Adam; Deorowicz, Sebastian

2014-01-01

Multiple sequence alignment is a crucial task in a number of biological analyses like secondary structure prediction, domain searching, phylogeny, etc. MSAProbs is currently the most accurate alignment algorithm, but its effectiveness is obtained at the expense of computational time. In the paper we present QuickProbs, the variant of MSAProbs customised for graphics processors. We selected the two most time consuming stages of MSAProbs to be redesigned for GPU execution: the posterior matrices calculation and the consistency transformation. Experiments on three popular benchmarks (BAliBASE, PREFAB, OXBench-X) on quad-core PC equipped with high-end graphics card show QuickProbs to be 5.7 to 9.7 times faster than original CPU-parallel MSAProbs. Additional tests performed on several protein families from Pfam database give overall speed-up of 6.7. Compared to other algorithms like MAFFT, MUSCLE, or ClustalW, QuickProbs proved to be much more accurate at similar speed. Additionally we introduce a tuned variant of QuickProbs which is significantly more accurate on sets of distantly related sequences than MSAProbs without exceeding its computation time. The GPU part of QuickProbs was implemented in OpenCL, thus the package is suitable for graphics processors produced by all major vendors. PMID:24586435

Is multiple-sequence alignment required for accurate inference of phylogeny?

PubMed

Höhl, Michael; Ragan, Mark A

2007-04-01

The process of inferring phylogenetic trees from molecular sequences almost always starts with a multiple alignment of these sequences but can also be based on methods that do not involve multiple sequence alignment. Very little is known about the accuracy with which such alignment-free methods recover the correct phylogeny or about the potential for increasing their accuracy. We conducted a large-scale comparison of ten alignment-free methods, among them one new approach that does not calculate distances and a faster variant of our pattern-based approach; all distance-based alignment-free methods are freely available from http://www.bioinformatics.org.au (as Python package decaf+py). We show that most methods exhibit a higher overall reconstruction accuracy in the presence of high among-site rate variation. Under all conditions that we considered, variants of the pattern-based approach were significantly better than the other alignment-free methods. The new pattern-based variant achieved a speed-up of an order of magnitude in the distance calculation step, accompanied by a small loss of tree reconstruction accuracy. A method of Bayesian inference from k-mers did not improve on classical alignment-free (and distance-based) methods but may still offer other advantages due to its Bayesian nature. We found the optimal word length k of word-based methods to be stable across various data sets, and we provide parameter ranges for two different alphabets. The influence of these alphabets was analyzed to reveal a trade-off in reconstruction accuracy between long and short branches. We have mapped the phylogenetic accuracy for many alignment-free methods, among them several recently introduced ones, and increased our understanding of their behavior in response to biologically important parameters. In all experiments, the pattern-based approach emerged as superior, at the expense of higher resource consumption. Nonetheless, no alignment-free method that we examined recovers the correct phylogeny as accurately as does an approach based on maximum-likelihood distance estimates of multiply aligned sequences.

Characterizing protein domain associations by Small-molecule ligand binding

PubMed Central

Li, Qingliang; Cheng, Tiejun; Wang, Yanli; Bryant, Stephen H.

2012-01-01

Background Protein domains are evolutionarily conserved building blocks for protein structure and function, which are conventionally identified based on protein sequence or structure similarity. Small molecule binding domains are of great importance for the recognition of small molecules in biological systems and drug development. Many small molecules, including drugs, have been increasingly identified to bind to multiple targets, leading to promiscuous interactions with protein domains. Thus, a large scale characterization of the protein domains and their associations with respect to small-molecule binding is of particular interest to system biology research, drug target identification, as well as drug repurposing. Methods We compiled a collection of 13,822 physical interactions of small molecules and protein domains derived from the Protein Data Bank (PDB) structures. Based on the chemical similarity of these small molecules, we characterized pairwise associations of the protein domains and further investigated their global associations from a network point of view. Results We found that protein domains, despite lack of similarity in sequence and structure, were comprehensively associated through binding the same or similar small-molecule ligands. Moreover, we identified modules in the domain network that consisted of closely related protein domains by sharing similar biochemical mechanisms, being involved in relevant biological pathways, or being regulated by the same cognate cofactors. Conclusions A novel protein domain relationship was identified in the context of small-molecule binding, which is complementary to those identified by traditional sequence-based or structure-based approaches. The protein domain network constructed in the present study provides a novel perspective for chemogenomic study and network pharmacology, as well as target identification for drug repurposing. PMID:23745168

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.

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

PubMed Central

Thomsen, Martin Christen Frølund; Nielsen, Morten

2012-01-01

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

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

Controlling subcellular delivery to optimize therapeutic effect

PubMed Central

Mossalam, Mohanad; Dixon, Andrew S; Lim, Carol S

2010-01-01

This article focuses on drug targeting to specific cellular organelles for therapeutic purposes. Drugs can be delivered to all major organelles of the cell (cytosol, endosome/lysosome, nucleus, nucleolus, mitochondria, endoplasmic reticulum, Golgi apparatus, peroxisomes and proteasomes) where they exert specific effects in those particular subcellular compartments. Delivery can be achieved by chemical (e.g., polymeric) or biological (e.g., signal sequences) means. Unidirectional targeting to individual organelles has proven to be immensely successful for drug therapy. Newer technologies that accommodate multiple signals (e.g., protein switch and virus-like delivery systems) mimic nature and allow for a more sophisticated approach to drug delivery. Harnessing different methods of targeting multiple organelles in a cell will lead to better drug delivery and improvements in disease therapy. PMID:21113240

Evolution of MHC class I genes in the endangered loggerhead sea turtle (Caretta caretta) revealed by 454 amplicon sequencing.

PubMed

Stiebens, Victor A; Merino, Sonia E; Chain, Frédéric J J; Eizaguirre, Christophe

2013-04-30

In evolutionary and conservation biology, parasitism is often highlighted as a major selective pressure. To fight against parasites and pathogens, genetic diversity of the immune genes of the major histocompatibility complex (MHC) are particularly important. However, the extensive degree of polymorphism observed in these genes makes it difficult to conduct thorough population screenings. We utilized a genotyping protocol that uses 454 amplicon sequencing to characterize the MHC class I in the endangered loggerhead sea turtle (Caretta caretta) and to investigate their evolution at multiple relevant levels of organization. MHC class I genes revealed signatures of trans-species polymorphism across several reptile species. In the studied loggerhead turtle individuals, it results in the maintenance of two ancient allelic lineages. We also found that individuals carrying an intermediate number of MHC class I alleles are larger than those with either a low or high number of alleles. Multiple modes of evolution seem to maintain MHC diversity in the loggerhead turtles, with relatively high polymorphism for an endangered species.

A Bayesian Sampler for Optimization of Protein Domain Hierarchies

PubMed Central

2014-01-01

Abstract The process of identifying and modeling functionally divergent subgroups for a specific protein domain class and arranging these subgroups hierarchically has, thus far, largely been done via manual curation. How to accomplish this automatically and optimally is an unsolved statistical and algorithmic problem that is addressed here via Markov chain Monte Carlo sampling. Taking as input a (typically very large) multiple-sequence alignment, the sampler creates and optimizes a hierarchy by adding and deleting leaf nodes, by moving nodes and subtrees up and down the hierarchy, by inserting or deleting internal nodes, and by redefining the sequences and conserved patterns associated with each node. All such operations are based on a probability distribution that models the conserved and divergent patterns defining each subgroup. When we view these patterns as sequence determinants of protein function, each node or subtree in such a hierarchy corresponds to a subgroup of sequences with similar biological properties. The sampler can be applied either de novo or to an existing hierarchy. When applied to 60 protein domains from multiple starting points in this way, it converged on similar solutions with nearly identical log-likelihood ratio scores, suggesting that it typically finds the optimal peak in the posterior probability distribution. Similarities and differences between independently generated, nearly optimal hierarchies for a given domain help distinguish robust from statistically uncertain features. Thus, a future application of the sampler is to provide confidence measures for various features of a domain hierarchy. PMID:24494927

Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes.

PubMed

Olson, Nathan D; Treangen, Todd J; Hill, Christopher M; Cepeda-Espinoza, Victoria; Ghurye, Jay; Koren, Sergey; Pop, Mihai

2017-08-07

Metagenomic samples are snapshots of complex ecosystems at work. They comprise hundreds of known and unknown species, contain multiple strain variants and vary greatly within and across environments. Many microbes found in microbial communities are not easily grown in culture making their DNA sequence our only clue into their evolutionary history and biological function. Metagenomic assembly is a computational process aimed at reconstructing genes and genomes from metagenomic mixtures. Current methods have made significant strides in reconstructing DNA segments comprising operons, tandem gene arrays and syntenic blocks. Shorter, higher-throughput sequencing technologies have become the de facto standard in the field. Sequencers are now able to generate billions of short reads in only a few days. Multiple metagenomic assembly strategies, pipelines and assemblers have appeared in recent years. Owing to the inherent complexity of metagenome assembly, regardless of the assembly algorithm and sequencing method, metagenome assemblies contain errors. Recent developments in assembly validation tools have played a pivotal role in improving metagenomics assemblers. Here, we survey recent progress in the field of metagenomic assembly, provide an overview of key approaches for genomic and metagenomic assembly validation and demonstrate the insights that can be derived from assemblies through the use of assembly validation strategies. We also discuss the potential for impact of long-read technologies in metagenomics. We conclude with a discussion of future challenges and opportunities in the field of metagenomic assembly and validation. © The Author 2017. Published by Oxford University Press.

Visualization and dissemination of multidimensional proteomics data comparing protein abundance during Caenorhabditis elegans development.

PubMed

Riffle, Michael; Merrihew, Gennifer E; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N; Noble, William S; MacCoss, Michael J

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/ . Graphical Abstract ᅟ.

Visualization and Dissemination of Multidimensional Proteomics Data Comparing Protein Abundance During Caenorhabditis elegans Development

NASA Astrophysics Data System (ADS)

Riffle, Michael; Merrihew, Gennifer E.; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N.; Noble, William S.; MacCoss, Michael J.

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/.

Next-generation sequencing reveals cryptic mtDNA diversity of Plasmodium relictum in the Hawaiian Islands

USGS Publications Warehouse

Jarvi, S.I.; Farias, M.E.; Lapointe, D.A.; Belcaid, M.; Atkinson, C.T.

2013-01-01

Next-generation 454 sequencing techniques were used to re-examine diversity of mitochondrial cytochrome b lineages of avian malaria (Plasmodium relictum) in Hawaii. We document a minimum of 23 variant lineages of the parasite based on single nucleotide transitional changes, in addition to the previously reported single lineage (GRW4). A new, publicly available portal (Integroomer) was developed for initial parsing of 454 datasets. Mean variant prevalence and frequency was higher in low elevation Hawaii Amakihi (Hemignathus virens) with Avipoxvirus-like lesions (P = 0·001), suggesting that the variants may be biologically distinct. By contrast, variant prevalence and frequency did not differ significantly among mid-elevation Apapane (Himatione sanguinea) with or without lesions (P = 0·691). The low frequency and the lack of detection of variants independent of GRW4 suggest that multiple independent introductions of P. relictum to Hawaii are unlikely. Multiple variants may have been introduced in heteroplasmy with GRW4 or exist within the tandem repeat structure of the mitochondrial genome. The discovery of multiple mitochondrial lineages of P. relictum in Hawaii provides a measure of genetic diversity within a geographically isolated population of this parasite and suggests the origins and evolution of parasite diversity may be more complicated than previously recognized.

Next-generation sequencing reveals cryptic mtDNA diversity of Plasmodium relictum in the Hawaiian Islands.

PubMed

Jarvi, S I; Farias, M E; Lapointe, D A; Belcaid, M; Atkinson, C T

2013-12-01

Next-generation 454 sequencing techniques were used to re-examine diversity of mitochondrial cytochrome b lineages of avian malaria (Plasmodium relictum) in Hawaii. We document a minimum of 23 variant lineages of the parasite based on single nucleotide transitional changes, in addition to the previously reported single lineage (GRW4). A new, publicly available portal (Integroomer) was developed for initial parsing of 454 datasets. Mean variant prevalence and frequency was higher in low elevation Hawaii Amakihi (Hemignathus virens) with Avipoxvirus-like lesions (P = 0·001), suggesting that the variants may be biologically distinct. By contrast, variant prevalence and frequency did not differ significantly among mid-elevation Apapane (Himatione sanguinea) with or without lesions (P = 0·691). The low frequency and the lack of detection of variants independent of GRW4 suggest that multiple independent introductions of P. relictum to Hawaii are unlikely. Multiple variants may have been introduced in heteroplasmy with GRW4 or exist within the tandem repeat structure of the mitochondrial genome. The discovery of multiple mitochondrial lineages of P. relictum in Hawaii provides a measure of genetic diversity within a geographically isolated population of this parasite and suggests the origins and evolution of parasite diversity may be more complicated than previously recognized.

Adverse Outcome Pathway (AOP) Network Development for ...

EPA Pesticide Factsheets

Adverse outcome pathways (AOPs) are descriptive biological sequences that start from a molecular initiating event (MIE) and end with an adverse health outcome. AOPs provide biological context for high throughput chemical testing and further prioritize environmental health risk research. According to the Organization for Economic Co-operation and Development guidelines, AOPs are pathways with one MIE anchored to an adverse outcome (AO) by key events (KEs) and key event relationships (KERs). However, this approach does not always capture the cumulative impacts of multiple MIEs on the AO. For example, hepatic lipid flux due to chemical-induced toxicity initiates from multiple ligand-activated receptors and signaling pathways that cascade across biology to converge upon a common fatty liver (FL, also known as steatosis) outcome. To capture this complexity, a top-down strategy was used to develop a FL AOP network (AOPnet). Literature was queried based on the terms steatosis, fatty liver, cirrhosis, and hepatocellular carcinoma. Search results were analyzed for physiological and pathophysiological organ level, cellular and molecular processes, as well as pathway intermediates, to identify potential KEs and MIEs that are key for hepatic lipid metabolism, maintenance, and dysregulation. The analysis identified four apical KE nodes (hepatic fatty acid uptake, de novo fatty acid and lipid synthesis, fatty acid oxidation, and lipid efflux) juxtaposed to the FL AO. The apic

Regulation of gene expression by manipulating transcriptional repressor activity using a novel CoSRI technology.

PubMed

Xu, Yue; Li, Song Feng; Parish, Roger W

2017-07-01

Targeted gene manipulation is a central strategy for studying gene function and identifying related biological processes. However, a methodology for manipulating the regulatory motifs of transcription factors is lacking as these factors commonly possess multiple motifs (e.g. repression and activation motifs) which collaborate with each other to regulate multiple biological processes. We describe a novel approach designated conserved sequence-guided repressor inhibition (CoSRI) that can specifically reduce or abolish the repressive activities of transcription factors in vivo. The technology was evaluated using the chimeric MYB80-EAR transcription factor and subsequently the endogenous WUS transcription factor. The technology was employed to develop a reversible male sterility system applicable to hybrid seed production. In order to determine the capacity of the technology to regulate the activity of endogenous transcription factors, the WUS repressor was chosen. The WUS repression motif could be inhibited in vivo and the transformed plants exhibited the wus-1 phenotype. Consequently, the technology can be used to manipulate the activities of transcriptional repressor motifs regulating beneficial traits in crop plants and other eukaryotic organisms. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

A survey of enabling technologies in synthetic biology

PubMed Central

2013-01-01

Background Realizing constructive applications of synthetic biology requires continued development of enabling technologies as well as policies and practices to ensure these technologies remain accessible for research. Broadly defined, enabling technologies for synthetic biology include any reagent or method that, alone or in combination with associated technologies, provides the means to generate any new research tool or application. Because applications of synthetic biology likely will embody multiple patented inventions, it will be important to create structures for managing intellectual property rights that best promote continued innovation. Monitoring the enabling technologies of synthetic biology will facilitate the systematic investigation of property rights coupled to these technologies and help shape policies and practices that impact the use, regulation, patenting, and licensing of these technologies. Results We conducted a survey among a self-identifying community of practitioners engaged in synthetic biology research to obtain their opinions and experiences with technologies that support the engineering of biological systems. Technologies widely used and considered enabling by survey participants included public and private registries of biological parts, standard methods for physical assembly of DNA constructs, genomic databases, software tools for search, alignment, analysis, and editing of DNA sequences, and commercial services for DNA synthesis and sequencing. Standards and methods supporting measurement, functional composition, and data exchange were less widely used though still considered enabling by a subset of survey participants. Conclusions The set of enabling technologies compiled from this survey provide insight into the many and varied technologies that support innovation in synthetic biology. Many of these technologies are widely accessible for use, either by virtue of being in the public domain or through legal tools such as non-exclusive licensing. Access to some patent protected technologies is less clear and use of these technologies may be subject to restrictions imposed by material transfer agreements or other contract terms. We expect the technologies considered enabling for synthetic biology to change as the field advances. By monitoring the enabling technologies of synthetic biology and addressing the policies and practices that impact their development and use, our hope is that the field will be better able to realize its full potential. PMID:23663447

Common Amino Acid Subsequences in a Universal Proteome—Relevance for Food Science

PubMed Central

Minkiewicz, Piotr; Darewicz, Małgorzata; Iwaniak, Anna; Sokołowska, Jolanta; Starowicz, Piotr; Bucholska, Justyna; Hrynkiewicz, Monika

2015-01-01

A common subsequence is a fragment of the amino acid chain that occurs in more than one protein. Common subsequences may be an object of interest for food scientists as biologically active peptides, epitopes, and/or protein markers that are used in comparative proteomics. An individual bioactive fragment, in particular the shortest fragment containing two or three amino acid residues, may occur in many protein sequences. An individual linear epitope may also be present in multiple sequences of precursor proteins. Although recent recommendations for prediction of allergenicity and cross-reactivity include not only sequence identity, but also similarities in secondary and tertiary structures surrounding the common fragment, local sequence identity may be used to screen protein sequence databases for potential allergens in silico. The main weakness of the screening process is that it overlooks allergens and cross-reactivity cases without identical fragments corresponding to linear epitopes. A single peptide may also serve as a marker of a group of allergens that belong to the same family and, possibly, reveal cross-reactivity. This review article discusses the benefits for food scientists that follow from the common subsequences concept. PMID:26340620

AutoFACT: An Automatic Functional Annotation and Classification Tool

PubMed Central

Koski, Liisa B; Gray, Michael W; Lang, B Franz; Burger, Gertraud

2005-01-01

Background Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. Results We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. Conclusion AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at . PMID:15960857

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

PubMed Central

Wang, Ruijia; Nambiar, Ram; Zheng, Dinghai

2018-01-01

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

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.

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

Legume Genome Initiative at the University of Oklahoma

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

Bruce A. Roe

2004-02-27

Consolidated Appropriations Resolution, 2003 Conference Report for the Department of Energy's Biological and Environmental Research (BER) program provided $481,000 for the Legume Genome Initiative at the University of Oklahoma. These funds were used to support our research that is aimed at determining the entire sequence of the gene rich regions of the genome of the legume, Medicago truncatula, by allowing us to obtain a greater degree of finished BAC sequences from the draft sequences we have already obtained through research funded by the Noble Foundation. During the funding period we increased the number of Medicago truncatula BACs with finished (Bermudamore » standard) sequences from 109 to 359, and the total number of BACs for which we collected sequence data from 584 to 842, 359 of which reached phase 2 (ordered and oriented contigs). We also sequenced a series of pooled BAC clones that cover additional euchromatic (gene rich) genomic regions. This work resulted in 6 refereed publications, see below. Genes whose sequence was determined during this study included multiple members of the plant disease resistance (R-gene) family as well as several genes involved in flavinoid biosynthesis, nitrogen fixation and plant-microbial symbosis. This work also served as a prelude to obtaining NSF funding for the international collaborative effort to complete the entire sequence of the Medicago truncatula genomic euchromatic regions using a BAC based approach.« less

Genetic Differences Between Humans and Great Apes -- Implications for the Evolution of Humans

NASA Astrophysics Data System (ADS)

Varki, Ajit

2004-06-01

At the level of individual protein sequences, humans are 97-100% identical to the great apes, our closest evolutionary relatives. The evolution of humans (and of human intelligence) from a common ancestor with the chimpanzee and bonobo involved many steps, influenced by interactions amongst factors of genetic, developmental, ecological, microbial, climatic, behavioral, cultural and social origin. The genetic factors can be approached by direct comparisons of human and great ape genomes, genes and gene products, and by elucidating biochemical and biological consequences of any differences found. We have discovered multiple genetic and biochemical differences between humans and great apes, particularly with respect to a family of cell surface molecules called sialic acids, as well as in the metabolism of thyroid hormones. The hormone differences have potential consequences for human brain development. The differences in sialic acid biology have multiple implications for the human condition, ranging from susceptibility or resistance to microbial pathogens, effects on endogenous receptors in the immune system, and potential effects on placental signaling, expression of oncofetal antigens in cancers, consequences of dietary intake of animal foods, and development of the mammalian brain.

Multiple, novel biologically active endophytic actinomycetes isolated from upper Amazonian rainforests.

PubMed

Bascom-Slack, Carol A; Ma, Cong; Moore, Emily; Babbs, Beatrice; Fenn, Kathleen; Greene, Joshua S; Hann, Bradley D; Keehner, Jocelyn; Kelley-Swift, Elizabeth G; Kembaiyan, Vivek; Lee, Sun Jin; Li, Puyao; Light, David Y; Lin, Emily H; Schorn, Michelle A; Vekhter, Daniel; Boulanger, Lori-Ann; Hess, W M; Vargas, Percy Núñez; Strobel, Gary A; Strobel, Scott A

2009-08-01

Microbial biodiversity provides an increasingly important source of medically and industrially useful compounds. We have isolated 14 actinomycete species from a collection of approximately 300 plant stem samples from the upper Amazonian rainforest in Peru. All of the cultured isolates produce substances with inhibitory activity directed at a range of potential fungal and bacterial pathogens. For some organisms, this activity is very broad in spectrum while other organisms show specific activity against a limited number of organisms. Two of these organisms preferentially inhibit bacterial test organisms over eukaryotic organisms. rDNA sequence analysis indicates that these organisms are not equivalent to any other cultured deposits in GenBank. Our results provide evidence of the untapped biodiversity in the form of biologically active microbes present within the tissues of higher plants.

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.

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

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.

Rate-determining Step of Flap Endonuclease 1 (FEN1) Reflects a Kinetic Bias against Long Flaps and Trinucleotide Repeat Sequences.

PubMed

Tarantino, Mary E; Bilotti, Katharina; Huang, Ji; Delaney, Sarah

2015-08-21

Flap endonuclease 1 (FEN1) is a structure-specific nuclease responsible for removing 5'-flaps formed during Okazaki fragment maturation and long patch base excision repair. In this work, we use rapid quench flow techniques to examine the rates of 5'-flap removal on DNA substrates of varying length and sequence. Of particular interest are flaps containing trinucleotide repeats (TNR), which have been proposed to affect FEN1 activity and cause genetic instability. We report that FEN1 processes substrates containing flaps of 30 nucleotides or fewer at comparable single-turnover rates. However, for flaps longer than 30 nucleotides, FEN1 kinetically discriminates substrates based on flap length and flap sequence. In particular, FEN1 removes flaps containing TNR sequences at a rate slower than mixed sequence flaps of the same length. Furthermore, multiple-turnover kinetic analysis reveals that the rate-determining step of FEN1 switches as a function of flap length from product release to chemistry (or a step prior to chemistry). These results provide a kinetic perspective on the role of FEN1 in DNA replication and repair and contribute to our understanding of FEN1 in mediating genetic instability of TNR sequences. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

j5 v2.8.4

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

Hillson, Nathan

j5 automates and optimizes the design of the molecular biological process of cloning/constructing DNA. j5 enables users to benefit from (combinatorial) multi-part scar-less SLIC, Gibson, CPEC, Golden Gate assembly, or variants thereof, for which automation software does not currently exist, without the intense labor currently associated with the process. j5 inputs a list of the DNA sequences to be assembled, along with a Genbank, FASTA, jbei-seq, or SBOL v1.1 format sequence file for each DNA source. Given the list of DNA sequences to be assembled, j5 first determines the cost-minimizing assembly strategy for each part (direct synthesis, PCR/SOE, or oligo-embedding),more » designs DNA oligos with Primer3, adds flanking homology sequences (SLIC, Gibson, and CPEC; optimized with Primer3 for CPEC) or optimized overhang sequences (Golden Gate) to the oligos and direct synthesis pieces, and utilizes BLAST to check against oligo mis-priming and assembly piece incompatibility events. After identifying DNA oligos that are already contained within a local collection for reuse, the program estimates the total cost of direct synthesis and new oligos to be ordered. In the instance that j5 identifies putative assembly piece incompatibilities (multiple pieces with high flanking sequence homology), the program suggests hierarchical subassemblies where possible. The program outputs a comma-separated value (CSV) file, viewable via Excel or other spreadsheet software, that contains assembly design information (such as the PCR/SOE reactions to perform, their anticipated sizes and sequences, etc.) as well as a properly annotated genbank file containing the sequence resulting from the assembly, and appends the local oligo library with the oligos to be ordered j5 condenses multiple independent assembly projects into 96-well format for high-throughput liquid-handling robotics platforms, and generates configuration files for the PR-PR biology-friendly robot programming language. j5 thus provides a new way to design DNA assembly procedures much more productively and efficiently, not only in terms of time, but also in terms of cost. To a large extent, however, j5 does not allow people to do something that could not be done before by hand given enough time and effort. An exception to this is that, since the very act of using j5 to design the DNA assembly process standardizes the experimental details and workflow, j5 enables a single person to concurrently perform the independent DNA construction tasks of an entire group of researchers. Currently, this is not readily possible, since separate researchers employ disparate design strategies and workflows, and furthermore, their designs and workflows are very infrequently fully captured in an electronic format which is conducive to automation.« less

Functional and mechanistic diversity of distal transcription enhancers

PubMed Central

Bulger, Michael; Groudine, Mark

2013-01-01

Biological differences among metazoans, and between cell types in a given organism, arise in large part due to differences in gene expression patterns. The sequencing of multiple metazoan genomes, coupled with recent advances in genome-wide analysis of histone modifications and transcription factor binding, has revealed that among regulatory DNA sequences, gene-distal enhancers appear to exhibit the greatest diversity and cell-type specificity. Moreover, such elements are emerging as important targets for mutations that can give rise to disease and to genetic variability that underlies evolutionary change. Studies of long-range interactions between distal genomic sequences in the nucleus indicate that enhancers are often important determinants of nuclear organization, contributing to a general model for enhancer function that involves direct enhancer-promoter contact. In a number of systems, however, mechanisms for enhancer function are emerging that do not fit solely within such a model, suggesting that enhancers as a class of DNA regulatory element may be functionally and mechanistically diverse. PMID:21295696

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.

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.

Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-Based Curation

PubMed Central

Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

2015-01-01

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. PMID:25505034

FASMA: a service to format and analyze sequences in multiple alignments.

PubMed

Costantini, Susan; Colonna, Giovanni; Facchiano, Angelo M

2007-12-01

Multiple sequence alignments are successfully applied in many studies for under- standing the structural and functional relations among single nucleic acids and protein sequences as well as whole families. Because of the rapid growth of sequence databases, multiple sequence alignments can often be very large and difficult to visualize and analyze. We offer a new service aimed to visualize and analyze the multiple alignments obtained with different external algorithms, with new features useful for the comparison of the aligned sequences as well as for the creation of a final image of the alignment. The service is named FASMA and is available at http://bioinformatica.isa.cnr.it/FASMA/.

fLPS: Fast discovery of compositional biases for the protein universe.

PubMed

Harrison, Paul M

2017-11-13

Proteins often contain regions that are compositionally biased (CB), i.e., they are made from a small subset of amino-acid residue types. These CB regions can be functionally important, e.g., the prion-forming and prion-like regions that are rich in asparagine and glutamine residues. Here I report a new program fLPS that can rapidly annotate CB regions. It discovers both single-residue and multiple-residue biases. It works through a process of probability minimization. First, contigs are constructed for each amino-acid type out of sequence windows with a low degree of bias; second, these contigs are searched exhaustively for low-probability subsequences (LPSs); third, such LPSs are iteratively assessed for merger into possible multiple-residue biases. At each of these stages, efficiency measures are taken to avoid or delay probability calculations unless/until they are necessary. On a current desktop workstation, the fLPS algorithm can annotate the biased regions of the yeast proteome (>5700 sequences) in <1 s, and of the whole current TrEMBL database (>65 million sequences) in as little as ~1 h, which is >2 times faster than the commonly used program SEG, using default parameters. fLPS discovers both shorter CB regions (of the sort that are often termed 'low-complexity sequence'), and milder biases that may only be detectable over long tracts of sequence. fLPS can readily handle very large protein data sets, such as might come from metagenomics projects. It is useful in searching for proteins with similar CB regions, and for making functional inferences about CB regions for a protein of interest. The fLPS package is available from: http://biology.mcgill.ca/faculty/harrison/flps.html , or https://github.com/pmharrison/flps , or is a supplement to this article.

Responding to a Zoonotic Emergency with Multi-omics Research: Pentatrichomonas hominis Hydrogenosomal Protein Characterization with Use of RNA Sequencing and Proteomics.

PubMed

Fang, Yi-Kai; Chien, Kun-Yi; Huang, Kuo-Yang; Cheng, Wei-Hung; Ku, Fu-Mann; Lin, Rose; Chen, Ting-Wen; Huang, Po-Jung; Chiu, Cheng-Hsun; Tang, Petrus

2016-11-01

Pentatrichomonas hominis is an anaerobic flagellated protist that colonizes the large intestine of a number of mammals, including cats, dogs, nonhuman primates, and humans. The wide host range of this organism is alarming and suggests a rising zoonotic emergency. However, knowledge on in-depth biology of this protist is still limited. Similar to the human pathogen, Trichomonas vaginalis, P. hominis possesses hydrogenosomes instead of mitochondria. Studies in T. vaginalis indicated that hydrogenosome is essential for cell survival and associated with numerous pivotal biological functions, including drug resistance. To further decipher the biology of this important organelle, we undertook proteomic research in P. hominis hydrogenosomes. Lacking a decoded P. hominis genome, we utilized an RNA sequencing (RNA-seq) data set generated from P. hominis axenic culture as the reference for proteome analysis. Using this in-house reference data set and mass spectrometry (MS), we identified 442 putative hydrogenosomal proteins. Interestingly, the composition of the P. hominis hydrogenosomal proteins is very similar to that of T. vaginalis, but proteins such as Hmp36, Pam16, Pam18, and Isd11 are absent based on both MS and the RNA-seq. Our data underscore that P. hominis expresses different homologs of multiple gene families from T. vaginalis. To the best of our knowledge, we present here the first hydrogenosome proteome in a protist other than T. vaginalis that offers crucial new scholarship for global health, therapeutics, diagnostics, and veterinary medicine research. In addition, the research strategy used here using RNA sequencing and proteomics might inform future multi-omics research in other understudied organisms without decoded genomes.

Cofactors in the RNA World

NASA Technical Reports Server (NTRS)

Ditzler, Mark A.

2014-01-01

RNA world theories figure prominently in many scenarios for the origin and early evolution of life. These theories posit that RNA molecules played a much larger role in ancient biology than they do now, acting both as the dominant biocatalysts and as the repository of genetic information. Many features of modern RNA biology are potential examples of molecular fossils from an RNA world, such as the pervasive involvement of nucleotides in coenzymes, the existence of natural aptamers that bind these coenzymes, the existence of natural ribozymes, a biosynthetic pathway in which deoxynucleotides are produced from ribonucleotides, and the central role of ribosomal RNA in protein synthesis in the peptidyl transferase center of the ribosome. Here, we uses both a top-down approach that evaluates RNA function in modern biology and a bottom-up approach that examines the capacities of RNA independent of modern biology. These complementary approaches exploit multiple in vitro evolution techniques coupled with high-throughput sequencing and bioinformatics analysis. Together these complementary approaches advance our understanding of the most primitive organisms, their early evolution, and their eventual transition to modern biochemistry.

Biological species in the viral world.

PubMed

Bobay, Louis-Marie; Ochman, Howard

2018-06-05

Due to their dependence on cellular organisms for metabolism and replication, viruses are typically named and assigned to species according to their genome structure and the original host that they infect. But because viruses often infect multiple hosts and the numbers of distinct lineages within a host can be vast, their delineation into species is often dictated by arbitrary sequence thresholds, which are highly inconsistent across lineages. Here we apply an approach to determine the boundaries of viral species based on the detection of gene flow within populations, thereby defining viral species according to the biological species concept (BSC). Despite the potential for gene transfer between highly divergent genomes, viruses, like the cellular organisms they infect, assort into reproductively isolated groups and can be organized into biological species. This approach revealed that BSC-defined viral species are often congruent with the taxonomic partitioning based on shared gene contents and host tropism, and that bacteriophages can similarly be classified in biological species. These results open the possibility to use a single, universal definition of species that is applicable across cellular and acellular lifeforms.

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.

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).

A computational genomics pipeline for prokaryotic sequencing projects.

PubMed

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

2010-08-01

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. 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. 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.

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…

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.

Comparative study of classification algorithms for immunosignaturing data

PubMed Central

2012-01-01

Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696

SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments

PubMed Central

Di Tommaso, Paolo; Bussotti, Giovanni; Kemena, Carsten; Capriotti, Emidio; Chatzou, Maria; Prieto, Pablo; Notredame, Cedric

2014-01-01

This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available. The server can be accessed from http://tcoffee.crg.cat/apps/tcoffee/do:saracoffee. PMID:24972831

The Protein Structure Initiative Structural Biology Knowledgebase Technology Portal: a structural biology web resource.

PubMed

Gifford, Lida K; Carter, Lester G; Gabanyi, Margaret J; Berman, Helen M; Adams, Paul D

2012-06-01

The Technology Portal of the Protein Structure Initiative Structural Biology Knowledgebase (PSI SBKB; http://technology.sbkb.org/portal/ ) is a web resource providing information about methods and tools that can be used to relieve bottlenecks in many areas of protein production and structural biology research. Several useful features are available on the web site, including multiple ways to search the database of over 250 technological advances, a link to videos of methods on YouTube, and access to a technology forum where scientists can connect, ask questions, get news, and develop collaborations. The Technology Portal is a component of the PSI SBKB ( http://sbkb.org ), which presents integrated genomic, structural, and functional information for all protein sequence targets selected by the Protein Structure Initiative. Created in collaboration with the Nature Publishing Group, the SBKB offers an array of resources for structural biologists, such as a research library, editorials about new research advances, a featured biological system each month, and a functional sleuth for searching protein structures of unknown function. An overview of the various features and examples of user searches highlight the information, tools, and avenues for scientific interaction available through the Technology Portal.

Phage Therapy in the Era of Synthetic Biology.

PubMed

Barbu, E Magda; Cady, Kyle C; Hubby, Bolyn

2016-10-03

For more than a century, bacteriophage (or phage) research has enabled some of the most important discoveries in biological sciences and has equipped scientists with many of the molecular biology tools that have advanced our understanding of replication, maintenance, and expression of genetic material. Phages have also been recognized and exploited as natural antimicrobial agents and nanovectors for gene therapy, but their potential as therapeutics has not been fully exploited in Western medicine because of challenges such as narrow host range, bacterial resistance, and unique pharmacokinetics. However, increasing concern related to the emergence of bacteria resistant to multiple antibiotics has heightened interest in phage therapy and the development of strategies to overcome hurdles associated with bacteriophage therapeutics. Recent progress in sequencing technologies, DNA manipulation, and synthetic biology allowed scientists to refactor the entire bacterial genome of Mycoplasma mycoides, thereby creating the first synthetic cell. These new strategies for engineering genomes may have the potential to accelerate the construction of designer phage genomes with superior therapeutic potential. Here, we discuss the use of phage as therapeutics, as well as how synthetic biology can create bacteriophage with desirable attributes. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.

Hunting down the chimera of multiple disciplinarity in conservation science.

PubMed

Pooley, Simon P; Mendelsohn, J Andrew; Milner-Gulland, E J

2014-02-01

The consensus is that both ecological and social factors are essential dimensions of conservation research and practice. However, much of the literature on multiple disciplinary collaboration focuses on the difficulties of undertaking it. This review of the challenges of conducting multiple disciplinary collaboration offers a framework for thinking about the diversity and complexity of this endeavor. We focused on conceptual challenges, of which 5 main categories emerged: methodological challenges, value judgments, theories of knowledge, disciplinary prejudices, and interdisciplinary communication. The major problems identified in these areas have proved remarkably persistent in the literature surveyed (c.1960-2012). Reasons for these failures to learn from past experience include the pressure to produce positive outcomes and gloss over disagreements, the ephemeral nature of many such projects and resulting lack of institutional memory, and the apparent complexity and incoherence of the endeavor. We suggest that multiple disciplinary collaboration requires conceptual integration among carefully selected multiple disciplinary team members united in investigating a shared problem or question. We outline a 9-point sequence of steps for setting up a successful multiple disciplinary project. This encompasses points on recruitment, involving stakeholders, developing research questions, negotiating power dynamics and hidden values and conceptual differences, explaining and choosing appropriate methods, developing a shared language, facilitating on-going communications, and discussing data integration and project outcomes. Although numerous solutions to the challenges of multiple disciplinary research have been proposed, lessons learned are often lost when projects end or experienced individuals move on. We urge multiple disciplinary teams to capture the challenges recognized, and solutions proposed, by their researchers while projects are in process. A database of well-documented case studies would showcase theories and methods from a variety of disciplines and their interactions, enable better comparative study and evaluation, and provide a useful resource for developing future projects and training multiple disciplinary researchers. © 2013 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

Experimental Aspects of Polarization Optimized Experiments (POE) for Magic Angle Spinning Solid-State NMR of Microcrystalline and Membrane-Bound Proteins.

PubMed

Gopinath, T; Veglia, Gianluigi

2018-01-01

Conventional NMR pulse sequences record one spectrum per experiment, while spending most of the time waiting for the spin system to return to the equilibrium. As a result, a full set of multidimensional NMR experiments for biological macromolecules may take up to several months to complete. Here, we present a practical guide for setting up a new class of MAS solid-state NMR experiments (POE or polarization optimized experiments) that enable the simultaneous acquisition of multiple spectra of proteins, accelerating data acquisition. POE exploit the long-lived 15 N polarization of isotopically labeled proteins and enable one to obtain up to eight spectra, by concatenating classical NMR pulse sequences. This new strategy propels data throughput of solid-state NMR spectroscopy of fibers, microcrystalline preparations, as well as membrane proteins.

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

Circular RNA expression profiles in placental villi from women with gestational diabetes mellitus.

PubMed

Yan, Linping; Feng, Jie; Cheng, Feng; Cui, Xianwei; Gao, Lingjuan; Chen, Yajun; Wang, Fei; Zhong, Tianying; Li, Yun; Liu, Lan

2018-04-15

Circular RNAs (circRNAs) have recently been shown to exert their effects on multiple pathological processes by acting as microRNA (miRNA) sponges. However, the roles of circRNAs in gestational diabetes mellitus (GDM) are largely unknown. This study aimed to identify the circRNAs involved in GDM and predict their potential biological functions. We first performed next-generation sequencing (NGS) to generate unbiased placental villi circRNA expression profiles of GDM and normal controls. In total, 48,270 circRNAs from the placental villi of the two groups were sequenced. Of these, 227 circRNAs were significantly up-regulated and 255 circRNAs were significantly down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses demonstrated that glycometabolism and lipometabolism processes, which are important in GDM development, were significantly enriched. Further analysis showed that most of the circRNAs harbored miRNA binding sites, and some were associated with GDM. These results showed that circRNAs are aberrantly expressed in the placental villi of GDM patients and play potential roles in the development of GDM. Copyright © 2018 Elsevier Inc. All rights reserved.

Studies toward the unique pederin family member psymberin: full structure elucidation, two alternative total syntheses, and analogs.

PubMed

Feng, Yu; Jiang, Xin; De Brabander, Jef K

2012-10-17

Two synthetic approaches to psymberin have been accomplished. A highly convergent first generation synthesis led to the complete stereochemical assignment and demonstrated that psymberin and irciniastatin A are identical compounds. This synthesis featured a diastereoselective aldol coupling between the aryl fragment and a central tetrahydropyran core and a novel one-pot procedure to convert an amide, via intermediacy of a sensitive methyl imidate, to the N-acyl aminal reminiscent of psymberin. The highlights of the second generation synthesis include an efficient iridium-catalyzed enantioselective bisallylation of neopentyl glycol and a stepwise Sonogashira coupling/cycloisomerization/reduction sequence to construct the dihydroisocoumarin unit. The two synthetic avenues were achieved in 17-18 steps (longest linear sequence, ~14-15 isolations) from 3 fragments prepared in 7-8 (first generation) and 3-8 (second generation) steps each. This convergent approach allowed for the preparation of sufficient amounts of psymberin (~ 0.5 g) for follow-up biological studies. Meanwhile, our highly flexible strategy enabled the design and synthesis of multiple analogs, including a psymberin-pederin hybrid, termed psympederin, that proved crucial to a comprehensive understanding of the chemical biology of psymberin and related compounds that will be described in a subsequent manuscript.

No wisdom in the crowd: genome annotation in the era of big data - current status and future prospects.

PubMed

Danchin, Antoine; Ouzounis, Christos; Tokuyasu, Taku; Zucker, Jean-Daniel

2018-07-01

Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in biological research and reflects the nature of biology itself. Annotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. By combining deduction, induction and abduction, investigators can generate hypotheses when accurate knowledge is extracted from model databases. A key stance is to depart from 'the sequence tells the structure tells the function' fallacy, placing function first. We illustrate our approach with examples of critical or unexpected pathways, using MicroScope to demonstrate how tools can be implemented following the principles we advocate. We end with a challenge to the reader. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Genome Engineering and Modification Toward Synthetic Biology for the Production of Antibiotics.

PubMed

Zou, Xuan; Wang, Lianrong; Li, Zhiqiang; Luo, Jie; Wang, Yunfu; Deng, Zixin; Du, Shiming; Chen, Shi

2018-01-01

Antibiotic production is often governed by large gene clusters composed of genes related to antibiotic scaffold synthesis, tailoring, regulation, and resistance. With the expansion of genome sequencing, a considerable number of antibiotic gene clusters has been isolated and characterized. The emerging genome engineering techniques make it possible towards more efficient engineering of antibiotics. In addition to genomic editing, multiple synthetic biology approaches have been developed for the exploration and improvement of antibiotic natural products. Here, we review the progress in the development of these genome editing techniques used to engineer new antibiotics, focusing on three aspects of genome engineering: direct cloning of large genomic fragments, genome engineering of gene clusters, and regulation of gene cluster expression. This review will not only summarize the current uses of genomic engineering techniques for cloning and assembly of antibiotic gene clusters or for altering antibiotic synthetic pathways but will also provide perspectives on the future directions of rebuilding biological systems for the design of novel antibiotics. © 2017 Wiley Periodicals, Inc.

Synthetic biology for microbial heavy metal biosensors.

PubMed

Kim, Hyun Ju; Jeong, Haeyoung; Lee, Sang Jun

2018-02-01

Using recombinant DNA technology, various whole-cell biosensors have been developed for detection of environmental pollutants, including heavy metal ions. Whole-cell biosensors have several advantages: easy and inexpensive cultivation, multiple assays, and no requirement of any special techniques for analysis. In the era of synthetic biology, cutting-edge DNA sequencing and gene synthesis technologies have accelerated the development of cell-based biosensors. Here, we summarize current technological advances in whole-cell heavy metal biosensors, including the synthetic biological components (bioparts), sensing and reporter modules, genetic circuits, and chassis cells. We discuss several opportunities for improvement of synthetic cell-based biosensors. First, new functional modules must be discovered in genome databases, and this knowledge must be used to upgrade specific bioparts through molecular engineering. Second, modules must be assembled into functional biosystems in chassis cells. Third, heterogeneity of individual cells in the microbial population must be eliminated. In the perspectives, the development of whole-cell biosensors is also discussed in the aspects of cultivation methods and synthetic cells.

Recent Advances in CRISPR-Cas9 Genome Editing Technology for Biological and Biomedical Investigations.

PubMed

Singh, Vijai; Gohil, Nisarg; Ramírez García, Robert; Braddick, Darren; Fofié, Christian Kuete

2018-01-01

The Type II CRISPR-Cas9 system is a simple, efficient, and versatile tool for targeted genome editing in a wide range of organisms and cell types. It continues to gain more scientific interest and has established itself as an extremely powerful technology within our synthetic biology toolkit. It works upon a targeted site and generates a double strand breaks that become repaired by either the NHEJ or the HDR pathway, modifying or permanently replacing the genomic target sequences of interest. These can include viral targets, single-mutation genetic diseases, and multiple-site corrections for wide scale disease states, offering the potential to manage and cure some of mankind's most persistent biomedical menaces. Here, we present the developing progress and future potential of CRISPR-Cas9 in biological and biomedical investigations, toward numerous therapeutic, biomedical, and biotechnological applications, as well as some of the challenges within. J. Cell. Biochem. 119: 81-94, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multiplexed fragaria chloroplast genome sequencing

Treesearch

W. Njuguna; A. Liston; R. Cronn; N.V. Bassil

2010-01-01

A method to sequence multiple chloroplast genomes using ultra high throughput sequencing technologies was recently described. Complete chloroplast genome sequences can resolve phylogenetic relationships at low taxonomic levels and identify informative point mutations and indels. The objective of this research was to sequence multiple Fragaria...

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.

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)

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.

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates.

PubMed

Leung, Kaston; Klaus, Anders; Lin, Bill K; Laks, Emma; Biele, Justina; Lai, Daniel; Bashashati, Ali; Huang, Yi-Fei; Aniba, Radhouane; Moksa, Michelle; Steif, Adi; Mes-Masson, Anne-Marie; Hirst, Martin; Shah, Sohrab P; Aparicio, Samuel; Hansen, Carl L

2016-07-26

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.

Lateral Gene Transfer in a Heavy Metal-Contaminated-Groundwater Microbial Community

PubMed Central

Hemme, Christopher L.; Green, Stefan J.; Rishishwar, Lavanya; Prakash, Om; Pettenato, Angelica; Chakraborty, Romy; Deutschbauer, Adam M.; Van Nostrand, Joy D.; Wu, Liyou; He, Zhili; Jordan, I. King; Arkin, Adam P.; Kostka, Joel E.

2016-01-01

ABSTRACT Unraveling the drivers controlling the response and adaptation of biological communities to environmental change, especially anthropogenic activities, is a central but poorly understood issue in ecology and evolution. Comparative genomics studies suggest that lateral gene transfer (LGT) is a major force driving microbial genome evolution, but its role in the evolution of microbial communities remains elusive. To delineate the importance of LGT in mediating the response of a groundwater microbial community to heavy metal contamination, representative Rhodanobacter reference genomes were sequenced and compared to shotgun metagenome sequences. 16S rRNA gene-based amplicon sequence analysis indicated that Rhodanobacter populations were highly abundant in contaminated wells with low pHs and high levels of nitrate and heavy metals but remained rare in the uncontaminated wells. Sequence comparisons revealed that multiple geochemically important genes, including genes encoding Fe2+/Pb2+ permeases, most denitrification enzymes, and cytochrome c553, were native to Rhodanobacter and not subjected to LGT. In contrast, the Rhodanobacter pangenome contained a recombinational hot spot in which numerous metal resistance genes were subjected to LGT and/or duplication. In particular, Co2+/Zn2+/Cd2+ efflux and mercuric resistance operon genes appeared to be highly mobile within Rhodanobacter populations. Evidence of multiple duplications of a mercuric resistance operon common to most Rhodanobacter strains was also observed. Collectively, our analyses indicated the importance of LGT during the evolution of groundwater microbial communities in response to heavy metal contamination, and a conceptual model was developed to display such adaptive evolutionary processes for explaining the extreme dominance of Rhodanobacter populations in the contaminated groundwater microbiome. PMID:27048805

A genomic library-based amplification approach (GL-PCR) for the mapping of multiple IS6110 insertion sites and strain differentiation of Mycobacterium tuberculosis.

PubMed

Namouchi, Amine; Mardassi, Helmi

2006-11-01

Evidence suggests that insertion of the IS6110 element is not without consequence to the biology of Mycobacterium tuberculosis complex strains. Thus, mapping of multiple IS6110 insertion sites in the genome of biomedically relevant clinical isolates would result in a better understanding of the role of this mobile element, particularly with regard to transmission, adaptability and virulence. In the present paper, we describe a versatile strategy, referred to as GL-PCR, that amplifies IS6110-flanking sequences based on the construction of a genomic library. M. tuberculosis chromosomal DNA is fully digested with HincII and then ligated into a plasmid vector between T7 and T3 promoter sequences. The ligation reaction product is transformed into Escherichia coli and selective PCR amplification targeting both 5' and 3' IS6110-flanking sequences are performed on the plasmid library DNA. For this purpose, four separate PCR reactions are performed, each combining an outward primer specific for one IS6110 end with either T7 or T3 primer. Determination of the nucleotide sequence of the PCR products generated from a single ligation reaction allowed mapping of 21 out of the 24 IS6110 copies of two 12 banded M. tuberculosis strains, yielding an overall sensitivity of 87,5%. Furthermore, by simply comparing the migration pattern of GL-PCR-generated products, the strategy proved to be as valuable as IS6110 RFLP for molecular typing of M. tuberculosis complex strains. Importantly, GL-PCR was able to discriminate between strains differing by a single IS6110 band.

DeF-GPU: Efficient and effective deletions finding in hepatitis B viral genomic DNA using a GPU architecture.

PubMed

Cheng, Chun-Pei; Lan, Kuo-Lun; Liu, Wen-Chun; Chang, Ting-Tsung; Tseng, Vincent S

2016-12-01

Hepatitis B viral (HBV) infection is strongly associated with an increased risk of liver diseases like cirrhosis or hepatocellular carcinoma (HCC). Many lines of evidence suggest that deletions occurring in HBV genomic DNA are highly associated with the activity of HBV via the interplay between aberrant viral proteins release and human immune system. Deletions finding on the HBV whole genome sequences is thus a very important issue though there exist underlying the challenges in mining such big and complex biological data. Although some next generation sequencing (NGS) tools are recently designed for identifying structural variations such as insertions or deletions, their validity is generally committed to human sequences study. This design may not be suitable for viruses due to different species. We propose a graphics processing unit (GPU)-based data mining method called DeF-GPU to efficiently and precisely identify HBV deletions from large NGS data, which generally contain millions of reads. To fit the single instruction multiple data instructions, sequencing reads are referred to as multiple data and the deletion finding procedure is referred to as a single instruction. We use Compute Unified Device Architecture (CUDA) to parallelize the procedures, and further validate DeF-GPU on 5 synthetic and 1 real datasets. Our results suggest that DeF-GPU outperforms the existing commonly-used method Pindel and is able to exactly identify the deletions of our ground truth in few seconds. The source code and other related materials are available at https://sourceforge.net/projects/defgpu/. Copyright © 2016 Elsevier Inc. All rights reserved.

Embedding strategies for effective use of information from multiple sequence alignments.

PubMed Central

Henikoff, S.; Henikoff, J. G.

1997-01-01

We describe a new strategy for utilizing multiple sequence alignment information to detect distant relationships in searches of sequence databases. A single sequence representing a protein family is enriched by replacing conserved regions with position-specific scoring matrices (PSSMs) or consensus residues derived from multiple alignments of family members. In comprehensive tests of these and other family representations, PSSM-embedded queries produced the best results overall when used with a special version of the Smith-Waterman searching algorithm. Moreover, embedding consensus residues instead of PSSMs improved performance with readily available single sequence query searching programs, such as BLAST and FASTA. Embedding PSSMs or consensus residues into a representative sequence improves searching performance by extracting multiple alignment information from motif regions while retaining single sequence information where alignment is uncertain. PMID:9070452

Systems Biology of Recombinant Protein Production in Bacillus megaterium

NASA Astrophysics Data System (ADS)

Biedendieck, Rebekka; Bunk, Boyke; Fürch, Tobias; Franco-Lara, Ezequiel; Jahn, Martina; Jahn, Dieter

Over the last two decades the Gram-positive bacterium Bacillus megaterium was systematically developed to a useful alternative protein production host. Multiple vector systems for high yield intra- and extracellular protein production were constructed. Strong inducible promoters were combined with DNA sequences for optimised ribosome binding sites, various leader peptides for protein export and N- as well as C-terminal affinity tags for affinity chromatographic purification of the desired protein. High cell density cultivation and recombinant protein production were successfully tested. For further system biology based control and optimisation of the production process the genomes of two B. megaterium strains were completely elucidated, DNA arrays designed, proteome, fluxome and metabolome analyses performed and all data integrated using the bioinformatics platform MEGABAC. Now, solid theoretical and experimental bases for primary modeling attempts of the production process are available.

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.

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

MIDAS: A Modular DNA Assembly System for Synthetic Biology.

PubMed

van Dolleweerd, Craig J; Kessans, Sarah A; Van de Bittner, Kyle C; Bustamante, Leyla Y; Bundela, Rudranuj; Scott, Barry; Nicholson, Matthew J; Parker, Emily J

2018-04-20

A modular and hierarchical DNA assembly platform for synthetic biology based on Golden Gate (Type IIS restriction enzyme) cloning is described. This enabling technology, termed MIDAS (for Modular Idempotent DNA Assembly System), can be used to precisely assemble multiple DNA fragments in a single reaction using a standardized assembly design. It can be used to build genes from libraries of sequence-verified, reusable parts and to assemble multiple genes in a single vector, with full user control over gene order and orientation, as well as control of the direction of growth (polarity) of the multigene assembly, a feature that allows genes to be nested between other genes or genetic elements. We describe the detailed design and use of MIDAS, exemplified by the reconstruction, in the filamentous fungus Penicillium paxilli, of the metabolic pathway for production of paspaline and paxilline, key intermediates in the biosynthesis of a range of indole diterpenes-a class of secondary metabolites produced by several species of filamentous fungi. MIDAS was used to efficiently assemble a 25.2 kb plasmid from 21 different modules (seven genes, each composed of three basic parts). By using a parts library-based system for construction of complex assemblies, and a unique set of vectors, MIDAS can provide a flexible route to assembling tailored combinations of genes and other genetic elements, thereby supporting synthetic biology applications in a wide range of expression hosts.

Simultaneous phylogeny reconstruction and multiple sequence alignment

PubMed Central

Yue, Feng; Shi, Jian; Tang, Jijun

2009-01-01

Background A phylogeny is the evolutionary history of a group of organisms. To date, sequence data is still the most used data type for phylogenetic reconstruction. Before any sequences can be used for phylogeny reconstruction, they must be aligned, and the quality of the multiple sequence alignment has been shown to affect the quality of the inferred phylogeny. At the same time, all the current multiple sequence alignment programs use a guide tree to produce the alignment and experiments showed that good guide trees can significantly improve the multiple alignment quality. Results We devise a new algorithm to simultaneously align multiple sequences and search for the phylogenetic tree that leads to the best alignment. We also implemented the algorithm as a C program package, which can handle both DNA and protein data and can take simple cost model as well as complex substitution matrices, such as PAM250 or BLOSUM62. The performance of the new method are compared with those from other popular multiple sequence alignment tools, including the widely used programs such as ClustalW and T-Coffee. Experimental results suggest that this method has good performance in terms of both phylogeny accuracy and alignment quality. Conclusion We present an algorithm to align multiple sequences and reconstruct the phylogenies that minimize the alignment score, which is based on an efficient algorithm to solve the median problems for three sequences. Our extensive experiments suggest that this method is very promising and can produce high quality phylogenies and alignments. PMID:19208110

Single-cell genomic sequencing using Multiple Displacement Amplification.

PubMed

Lasken, Roger S

2007-10-01

Single microbial cells can now be sequenced using DNA amplified by the Multiple Displacement Amplification (MDA) reaction. The few femtograms of DNA in a bacterium are amplified into micrograms of high molecular weight DNA suitable for DNA library construction and Sanger sequencing. The MDA-generated DNA also performs well when used directly as template for pyrosequencing by the 454 Life Sciences method. While MDA from single cells loses some of the genomic sequence, this approach will greatly accelerate the pace of sequencing from uncultured microbes. The genetically linked sequences from single cells are also a powerful tool to be used in guiding genomic assembly of shotgun sequences of multiple organisms from environmental DNA extracts (metagenomic sequences).

A method of alignment masking for refining the phylogenetic signal of multiple sequence alignments.

PubMed

Rajan, Vaibhav

2013-03-01

Inaccurate inference of positional homologies in multiple sequence alignments and systematic errors introduced by alignment heuristics obfuscate phylogenetic inference. Alignment masking, the elimination of phylogenetically uninformative or misleading sites from an alignment before phylogenetic analysis, is a common practice in phylogenetic analysis. Although masking is often done manually, automated methods are necessary to handle the much larger data sets being prepared today. In this study, we introduce the concept of subsplits and demonstrate their use in extracting phylogenetic signal from alignments. We design a clustering approach for alignment masking where each cluster contains similar columns-similarity being defined on the basis of compatible subsplits; our approach then identifies noisy clusters and eliminates them. Trees inferred from the columns in the retained clusters are found to be topologically closer to the reference trees. We test our method on numerous standard benchmarks (both synthetic and biological data sets) and compare its performance with other methods of alignment masking. We find that our method can eliminate sites more accurately than other methods, particularly on divergent data, and can improve the topologies of the inferred trees in likelihood-based analyses. Software available upon request from the author.

The glatiramoid class of immunomodulator drugs.

PubMed

Varkony, Haim; Weinstein, Vera; Klinger, Ety; Sterling, Jeffrey; Cooperman, Helena; Komlosh, Turi; Ladkani, David; Schwartz, Rivka

2009-03-01

Glatiramer acetate (GA) is a complex heterogenous mixture of polypeptides with immunomodulatory activity approved for treatment of relapsing-remitting multiple sclerosis. GA is the first, and was until recently, the only member of the glatiramoids, a family of synthetic copolymer mixtures comprising the four amino acids, L-glutamic acid, L-alanine, L-lysine and L-tyrosine, in a defined molar ratio. Another glatiramoid, protiramer, was recently evaluated in preclinical studies and in two small Phase II clinical trials with relapsing-remitting multiple sclerosis patients. Due to the complexity and heterogeneity of GA and other glatiramoids, the clinically active epitopes within the mixture cannot be identified and the consistency of polypeptide sequences within the mixture is dependent on a tightly controlled manufacturing process. Although no two glatiramoids can be proved identical, it is possible to differentiate among members of the glatiramoid class using analytical methods and immunological and biological markers. Even slight differences in the distribution of molecular masses or in the composition of antigenic polypeptide sequences among glatiramoids can significantly influence their efficacy, toxicity and immunogenicity profiles. Experience with GA may be instructive regarding important safety and efficacy considerations for new glatiramoid mixtures now in development.

Sequence polymorphism data of the hypervariable regions of mitochondrial DNA in the Yadav population of Haryana.

PubMed

Verma, Kapil; Sharma, Sapna; Sharma, Arun; Dalal, Jyoti; Bhardwaj, Tapeshwar

2018-06-01

Genetic variations among humans occur both within and among populations and range from single nucleotide changes to multiple-nucleotide variants. These multiple-nucleotide variants are useful for studying the relationships among individuals or various population groups. The study of human genetic variations can help scientists understand how different population groups are biologically related to one another. Sequence analysis of hypervariable regions of human mitochondrial DNA (mtDNA) has been successfully used for the genetic characterization of different population groups for forensic purposes. It is well established that different ethnic or population groups differ significantly in their mtDNA distributions. In the last decade, very little research has been conducted on mtDNA variations in the Indian population, although such data would be useful for elucidating the history of human population expansion across the world. Moreover, forensic studies on mtDNA variations in the Indian subcontinent are also scarce, particularly in the northern part of India. In this report, variations in the hypervariable regions of mtDNA were analyzed in the Yadav population of Haryana. Different molecular diversity indices were computed. Further, the obtained haplotypes were classified into different haplogroups and the phylogenetic relationship between different haplogroups was inferred.

Bellerophon: A program to detect chimeric sequences in multiple sequence alignments

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

Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2003-12-23

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments.

Whole exome sequencing reveals concomitant mutations of multiple FA genes in individual Fanconi anemia patients

PubMed Central

2014-01-01

Background Fanconi anemia (FA) is a rare inherited genetic syndrome with highly variable clinical manifestations. Fifteen genetic subtypes of FA have been identified. Traditional complementation tests for grouping studies have been used generally in FA patients and in stepwise methods to identify the FA type, which can result in incomplete genetic information from FA patients. Methods We diagnosed five pediatric patients with FA based on clinical manifestations, and we performed exome sequencing of peripheral blood specimens from these patients and their family members. The related sequencing data were then analyzed by bioinformatics, and the FANC gene mutations identified by exome sequencing were confirmed by PCR re-sequencing. Results Homozygous and compound heterozygous mutations of FANC genes were identified in all of the patients. The FA subtypes of the patients included FANCA, FANCM and FANCD2. Interestingly, four FA patients harbored multiple mutations in at least two FA genes, and some of these mutations have not been previously reported. These patients’ clinical manifestations were vastly different from each other, as were their treatment responses to androstanazol and prednisone. This finding suggests that heterozygous mutation(s) in FA genes could also have diverse biological and/or pathophysiological effects on FA patients or FA gene carriers. Interestingly, we were not able to identify de novo mutations in the genes implicated in DNA repair pathways when the sequencing data of patients were compared with those of their parents. Conclusions Our results indicate that Chinese FA patients and carriers might have higher and more complex mutation rates in FANC genes than have been conventionally recognized. Testing of the fifteen FANC genes in FA patients and their family members should be a regular clinical practice to determine the optimal care for the individual patient, to counsel the family and to obtain a better understanding of FA pathophysiology. PMID:24885126

Whole exome sequencing reveals concomitant mutations of multiple FA genes in individual Fanconi anemia patients.

PubMed

Chang, Lixian; Yuan, Weiping; Zeng, Huimin; Zhou, Quanquan; Wei, Wei; Zhou, Jianfeng; Li, Miaomiao; Wang, Xiaomin; Xu, Mingjiang; Yang, Fengchun; Yang, Yungui; Cheng, Tao; Zhu, Xiaofan

2014-05-15

Fanconi anemia (FA) is a rare inherited genetic syndrome with highly variable clinical manifestations. Fifteen genetic subtypes of FA have been identified. Traditional complementation tests for grouping studies have been used generally in FA patients and in stepwise methods to identify the FA type, which can result in incomplete genetic information from FA patients. We diagnosed five pediatric patients with FA based on clinical manifestations, and we performed exome sequencing of peripheral blood specimens from these patients and their family members. The related sequencing data were then analyzed by bioinformatics, and the FANC gene mutations identified by exome sequencing were confirmed by PCR re-sequencing. Homozygous and compound heterozygous mutations of FANC genes were identified in all of the patients. The FA subtypes of the patients included FANCA, FANCM and FANCD2. Interestingly, four FA patients harbored multiple mutations in at least two FA genes, and some of these mutations have not been previously reported. These patients' clinical manifestations were vastly different from each other, as were their treatment responses to androstanazol and prednisone. This finding suggests that heterozygous mutation(s) in FA genes could also have diverse biological and/or pathophysiological effects on FA patients or FA gene carriers. Interestingly, we were not able to identify de novo mutations in the genes implicated in DNA repair pathways when the sequencing data of patients were compared with those of their parents. Our results indicate that Chinese FA patients and carriers might have higher and more complex mutation rates in FANC genes than have been conventionally recognized. Testing of the fifteen FANC genes in FA patients and their family members should be a regular clinical practice to determine the optimal care for the individual patient, to counsel the family and to obtain a better understanding of FA pathophysiology.

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation.

PubMed

Aubrey, Wayne; Riley, Michael C; Young, Michael; King, Ross D; Oliver, Stephen G; Clare, Amanda

2015-01-01

Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar sequences which can cause genome instability and rearrangements. No existing marker recycling method is automation-friendly. We have developed a novel openly available deletion tool that consists of: 1) a method for deleting genomic elements that can be repeatedly used without limit, is precise, scar-free, and suitable for automation; and 2) software to design the method's primers. Our tool is sequence agnostic and could be used to delete large numbers of coding sequences, promoter regions, transcription factor binding sites, terminators, etc in a single genome. We have validated our tool on the deletion of non-essential open reading frames (ORFs) from S. cerevisiae. The tool is applicable to arbitrary genomes, and we provide primer sequences for the deletion of: 90% of the ORFs from the S. cerevisiae genome, 88% of the ORFs from S. pombe genome, and 85% of the ORFs from the L. lactis genome.

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation

PubMed Central

Aubrey, Wayne; Riley, Michael C.; Young, Michael; King, Ross D.; Oliver, Stephen G.; Clare, Amanda

2015-01-01

Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar sequences which can cause genome instability and rearrangements. No existing marker recycling method is automation-friendly. We have developed a novel openly available deletion tool that consists of: 1) a method for deleting genomic elements that can be repeatedly used without limit, is precise, scar-free, and suitable for automation; and 2) software to design the method’s primers. Our tool is sequence agnostic and could be used to delete large numbers of coding sequences, promoter regions, transcription factor binding sites, terminators, etc in a single genome. We have validated our tool on the deletion of non-essential open reading frames (ORFs) from S. cerevisiae. The tool is applicable to arbitrary genomes, and we provide primer sequences for the deletion of: 90% of the ORFs from the S. cerevisiae genome, 88% of the ORFs from S. pombe genome, and 85% of the ORFs from the L. lactis genome. PMID:26630677

CFGP: a web-based, comparative fungal genomics platform

PubMed Central

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. PMID:17947331

Miniaturization Technologies for Efficient Single-Cell Library Preparation for Next-Generation Sequencing.

PubMed

Mora-Castilla, Sergio; To, Cuong; Vaezeslami, Soheila; Morey, Robert; Srinivasan, Srimeenakshi; Dumdie, Jennifer N; Cook-Andersen, Heidi; Jenkins, Joby; Laurent, Louise C

2016-08-01

As the cost of next-generation sequencing has decreased, library preparation costs have become a more significant proportion of the total cost, especially for high-throughput applications such as single-cell RNA profiling. Here, we have applied novel technologies to scale down reaction volumes for library preparation. Our system consisted of in vitro differentiated human embryonic stem cells representing two stages of pancreatic differentiation, for which we prepared multiple biological and technical replicates. We used the Fluidigm (San Francisco, CA) C1 single-cell Autoprep System for single-cell complementary DNA (cDNA) generation and an enzyme-based tagmentation system (Nextera XT; Illumina, San Diego, CA) with a nanoliter liquid handler (mosquito HTS; TTP Labtech, Royston, UK) for library preparation, reducing the reaction volume down to 2 µL and using as little as 20 pg of input cDNA. The resulting sequencing data were bioinformatically analyzed and correlated among the different library reaction volumes. Our results showed that decreasing the reaction volume did not interfere with the quality or the reproducibility of the sequencing data, and the transcriptional data from the scaled-down libraries allowed us to distinguish between single cells. Thus, we have developed a process to enable efficient and cost-effective high-throughput single-cell transcriptome sequencing. © 2016 Society for Laboratory Automation and Screening.

SubVis: an interactive R package for exploring the effects of multiple substitution matrices on pairwise sequence alignment

PubMed Central

Coan, Heather B.; Youker, Robert T.

2017-01-01

Understanding how proteins mutate is critical to solving a host of biological problems. Mutations occur when an amino acid is substituted for another in a protein sequence. The set of likelihoods for amino acid substitutions is stored in a matrix and input to alignment algorithms. The quality of the resulting alignment is used to assess the similarity of two or more sequences and can vary according to assumptions modeled by the substitution matrix. Substitution strategies with minor parameter variations are often grouped together in families. For example, the BLOSUM and PAM matrix families are commonly used because they provide a standard, predefined way of modeling substitutions. However, researchers often do not know if a given matrix family or any individual matrix within a family is the most suitable. Furthermore, predefined matrix families may inaccurately reflect a particular hypothesis that a researcher wishes to model or otherwise result in unsatisfactory alignments. In these cases, the ability to compare the effects of one or more custom matrices may be needed. This laborious process is often performed manually because the ability to simultaneously load multiple matrices and then compare their effects on alignments is not readily available in current software tools. This paper presents SubVis, an interactive R package for loading and applying multiple substitution matrices to pairwise alignments. Users can simultaneously explore alignments resulting from multiple predefined and custom substitution matrices. SubVis utilizes several of the alignment functions found in R, a common language among protein scientists. Functions are tied together with the Shiny platform which allows the modification of input parameters. Information regarding alignment quality and individual amino acid substitutions is displayed with the JavaScript language which provides interactive visualizations for revealing both high-level and low-level alignment information. PMID:28674656

EdiPy: a resource to simulate the evolution of plant mitochondrial genes under the RNA editing.

PubMed

Picardi, Ernesto; Quagliariello, Carla

2006-02-01

EdiPy is an online resource appropriately designed to simulate the evolution of plant mitochondrial genes in a biologically realistic fashion. EdiPy takes into account the presence of sites subjected to RNA editing and provides multiple artificial alignments corresponding to both genomic and cDNA sequences. Each artificial data set can successively be submitted to main and widespread evolutionary and phylogenetic software packages such as PAUP, Phyml, PAML and Phylip. As an online bioinformatic resource, EdiPy is available at the following web page: http://biologia.unical.it/py_script/index.html.

SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments.

PubMed

Jessen, Leon Eyrich; Hoof, Ilka; Lund, Ole; Nielsen, Morten

2013-07-01

Identifying which mutation(s) within a given genotype is responsible for an observable phenotype is important in many aspects of molecular biology. Here, we present SigniSite, an online application for subgroup-free residue-level genotype-phenotype correlation. In contrast to similar methods, SigniSite does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set phenotype. As output, SigniSite displays a sequence logo, depicting the strength of the phenotype association of each residue and a heat-map identifying 'hot' or 'cold' regions. SigniSite was benchmarked against SPEER, a state-of-the-art method for the prediction of specificity determining positions (SDP) using a set of human immunodeficiency virus protease-inhibitor genotype-phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found to outperform SPEER. SigniSite is available at: http://www.cbs.dtu.dk/services/SigniSite/.

An FPGA Implementation to Detect Selective Cationic Antibacterial Peptides

PubMed Central

Polanco González, Carlos; Nuño Maganda, Marco Aurelio; Arias-Estrada, Miguel; del Rio, Gabriel

2011-01-01

Exhaustive prediction of physicochemical properties of peptide sequences is used in different areas of biological research. One example is the identification of selective cationic antibacterial peptides (SCAPs), which may be used in the treatment of different diseases. Due to the discrete nature of peptide sequences, the physicochemical properties calculation is considered a high-performance computing problem. A competitive solution for this class of problems is to embed algorithms into dedicated hardware. In the present work we present the adaptation, design and implementation of an algorithm for SCAPs prediction into a Field Programmable Gate Array (FPGA) platform. Four physicochemical properties codes useful in the identification of peptide sequences with potential selective antibacterial activity were implemented into an FPGA board. The speed-up gained in a single-copy implementation was up to 108 times compared with a single Intel processor cycle for cycle. The inherent scalability of our design allows for replication of this code into multiple FPGA cards and consequently improvements in speed are possible. Our results show the first embedded SCAPs prediction solution described and constitutes the grounds to efficiently perform the exhaustive analysis of the sequence-physicochemical properties relationship of peptides. PMID:21738652

Patterns and plasticity in RNA-protein interactions enable recruitment of multiple proteins through a single site

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

Valley, Cary T.; Porter, Douglas F.; Qiu, Chen

2012-06-28

mRNA control hinges on the specificity and affinity of proteins for their RNA binding sites. Regulatory proteins must bind their own sites and reject even closely related noncognate sites. In the PUF [Pumilio and fem-3 binding factor (FBF)] family of RNA binding proteins, individual proteins discriminate differences in the length and sequence of binding sites, allowing each PUF to bind a distinct battery of mRNAs. Here, we show that despite these differences, the pattern of RNA interactions is conserved among PUF proteins: the two ends of the PUF protein make critical contacts with the two ends of the RNA sites.more » Despite this conserved 'two-handed' pattern of recognition, the RNA sequence is flexible. Among the binding sites of yeast Puf4p, RNA sequence dictates the pattern in which RNA bases are flipped away from the binding surface of the protein. Small differences in RNA sequence allow new modes of control, recruiting Puf5p in addition to Puf4p to a single site. This embedded information adds a new layer of biological meaning to the connections between RNA targets and PUF proteins.« less

A Study of Two Instructional Sequences Informed by Alternative Learning Progressions in Genetics

NASA Astrophysics Data System (ADS)

Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L.

2017-12-01

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus molecular genetics and the order in which they should be taught. In order to determine the relative difficulty of the different genetic ideas included in the two progressions, and to test which one is a better fit with students' actual learning, we developed two modules in classical and molecular genetics and alternated their sequence in an implementation study with 11th grade students studying biology. We developed a set of 56 ordered multiple-choice items that collectively assessed both molecular and classical genetic ideas. We found significant gains in students' learning in both molecular and classical genetics, with the largest gain relating to understanding the informational content of genes and the smallest gain in understanding modes of inheritance. Using multidimensional item response modeling, we found no statistically significant differences between the two instructional sequences. However, there was a trend of slightly higher gains for the molecular-first sequence for all genetic ideas.

Purification of High Molecular Weight Genomic DNA from Powdery Mildew for Long-Read Sequencing.

PubMed

Feehan, Joanna M; Scheibel, Katherine E; Bourras, Salim; Underwood, William; Keller, Beat; Somerville, Shauna C

2017-03-31

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics of these pathogens, in part due to a lack of well-developed genetic and genomic resources. These organisms have large, repetitive genomes, which have made genome sequencing and assembly prohibitively difficult. Here, we describe methods for the collection, extraction, purification and quality control assessment of high molecular weight genomic DNA from one powdery mildew species, Golovinomyces cichoracearum. The protocol described includes mechanical disruption of spores followed by an optimized phenol/chloroform genomic DNA extraction. A typical yield was 7 µg DNA per 150 mg conidia. The genomic DNA that is isolated using this procedure is suitable for long-read sequencing (i.e., > 48.5 kbp). Quality control measures to ensure the size, yield, and purity of the genomic DNA are also described in this method. Sequencing of the genomic DNA of the quality described here will allow for the assembly and comparison of multiple powdery mildew genomes, which in turn will lead to a better understanding and improved control of this agricultural pathogen.

Optimization of techniques for multiple platform testing in small, precious samples such as human chorionic villus sampling.

PubMed

Pisarska, Margareta D; Akhlaghpour, Marzieh; Lee, Bora; Barlow, Gillian M; Xu, Ning; Wang, Erica T; Mackey, Aaron J; Farber, Charles R; Rich, Stephen S; Rotter, Jerome I; Chen, Yii-der I; Goodarzi, Mark O; Guller, Seth; Williams, John

2016-11-01

Multiple testing to understand global changes in gene expression based on genetic and epigenetic modifications is evolving. Chorionic villi, obtained for prenatal testing, is limited, but can be used to understand ongoing human pregnancies. However, optimal storage, processing and utilization of CVS for multiple platform testing have not been established. Leftover CVS samples were flash-frozen or preserved in RNAlater. Modifications to standard isolation kits were performed to isolate quality DNA and RNA from samples as small as 2-5 mg. RNAlater samples had significantly higher RNA yields and quality and were successfully used in microarray and RNA-sequencing (RNA-seq). RNA-seq libraries generated using 200 versus 800-ng RNA showed similar biological coefficients of variation. RNAlater samples had lower DNA yields and quality, which improved by heating the elution buffer to 70 °C. Purification of DNA was not necessary for bisulfite-conversion and genome-wide methylation profiling. CVS cells were propagated and continue to express genes found in freshly isolated chorionic villi. CVS samples preserved in RNAlater are superior. Our optimized techniques provide specimens for genetic, epigenetic and gene expression studies from a single small sample which can be used to develop diagnostics and treatments using a systems biology approach in the prenatal period. © 2016 John Wiley & Sons, Ltd. © 2016 John Wiley & Sons, Ltd.

A novel approach to multiple sequence alignment using hadoop data grids.

PubMed

Sudha Sadasivam, G; Baktavatchalam, G

2010-01-01

Multiple alignment of protein sequences helps to determine evolutionary linkage and to predict molecular structures. The factors to be considered while aligning multiple sequences are speed and accuracy of alignment. Although dynamic programming algorithms produce accurate alignments, they are computation intensive. In this paper we propose a time efficient approach to sequence alignment that also produces quality alignment. The dynamic nature of the algorithm coupled with data and computational parallelism of hadoop data grids improves the accuracy and speed of sequence alignment. The principle of block splitting in hadoop coupled with its scalability facilitates alignment of very large sequences.

ARResT/AssignSubsets: a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy.

PubMed

Bystry, Vojtech; Agathangelidis, Andreas; Bikos, Vasilis; Sutton, Lesley Ann; Baliakas, Panagiotis; Hadzidimitriou, Anastasia; Stamatopoulos, Kostas; Darzentas, Nikos

2015-12-01

An ever-increasing body of evidence supports the importance of B cell receptor immunoglobulin (BcR IG) sequence restriction, alias stereotypy, in chronic lymphocytic leukemia (CLL). This phenomenon accounts for ∼30% of studied cases, one in eight of which belong to major subsets, and extends beyond restricted sequence patterns to shared biologic and clinical characteristics and, generally, outcome. Thus, the robust assignment of new cases to major CLL subsets is a critical, and yet unmet, requirement. We introduce a novel application, ARResT/AssignSubsets, which enables the robust assignment of BcR IG sequences from CLL patients to major stereotyped subsets. ARResT/AssignSubsets uniquely combines expert immunogenetic sequence annotation from IMGT/V-QUEST with curation to safeguard quality, statistical modeling of sequence features from more than 7500 CLL patients, and results from multiple perspectives to allow for both objective and subjective assessment. We validated our approach on the learning set, and evaluated its real-world applicability on a new representative dataset comprising 459 sequences from a single institution. ARResT/AssignSubsets is freely available on the web at http://bat.infspire.org/arrest/assignsubsets/ nikos.darzentas@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Ruggles, Kelly V.; Tang, Zuojian; Wang, Xuya

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we therefore describe a proteogenomic data integration tool (QUILTS) and illustrate its application to whole genome, transcriptome and global MS peptide sequence datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS process replicates. Despite over thirty sample replicates, only about 10% of all SNV (somatic andmore » germline) were detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNV without a detectable mRNA transcript were also observed demonstrating the transcriptome coverage was also incomplete (~80%). In contrast to germ-line variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, the QUILTS program integrates DNA, RNA and peptide sequencing to assess the degree to which somatic mutations are translated and therefore biologically active. By identifying gaps in sequence coverage QUILTS benchmarks current technology and assesses progress towards whole cancer proteome and transcriptome analysis.« less

Sequence analysis of the complete genome of Trichoplusia ni single nucleopolyhedrovirus and the identification of a baculoviral photolyase gene

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

Willis, Leslie G.; Siepp, Robyn; Stewart, Taryn M.

2005-08-01

The genome of the Trichoplusia ni single nucleopolyhedrovirus (TnSNPV), a group II NPV which infects the cabbage looper (T. ni), has been completely sequenced and analyzed. The TnSNPV DNA genome consists of 134,394 bp and has an overall G + C content of 39%. Gene analysis predicted 144 open reading frames (ORFs) of 150 nucleotides or greater that showed minimal overlap. Comparisons with previously sequenced baculoviruses indicate that 119 TnSNPV ORFs were homologues of previously reported viral gene sequences. Ninety-four TnSNPV ORFs returned an Autographa californica multiple NPV (AcMNPV) homologue while 25 ORFs returned poor or no sequence matches withmore » the current databases. A putative photolyase gene was also identified that had highest amino acid identity to the photolyase genes of Chrysodeixis chalcites NPV (ChchNPV) (47%) and Danio rerio (zebrafish) (40%). In addition unlike all other baculoviruses no obvious homologous repeat (hr) sequences were identified. Comparison of the TnSNPV and AcMNPV genomes provides a unique opportunity to examine two baculoviruses that are highly virulent for a common insect host (T. ni) yet belong to diverse baculovirus taxonomic groups and possess distinct biological features. In vitro fusion assays demonstrated that the TnSNPV F protein induces membrane fusion and syncytia formation and were compared to syncytia formed by AcMNPV GP64.« less

[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.

Zika virus evolution and spread in the Americas.

PubMed

Metsky, Hayden C; Matranga, Christian B; Wohl, Shirlee; Schaffner, Stephen F; Freije, Catherine A; Winnicki, Sarah M; West, Kendra; Qu, James; Baniecki, Mary Lynn; Gladden-Young, Adrianne; Lin, Aaron E; Tomkins-Tinch, Christopher H; Ye, Simon H; Park, Daniel J; Luo, Cynthia Y; Barnes, Kayla G; Shah, Rickey R; Chak, Bridget; Barbosa-Lima, Giselle; Delatorre, Edson; Vieira, Yasmine R; Paul, Lauren M; Tan, Amanda L; Barcellona, Carolyn M; Porcelli, Mario C; Vasquez, Chalmers; Cannons, Andrew C; Cone, Marshall R; Hogan, Kelly N; Kopp, Edgar W; Anzinger, Joshua J; Garcia, Kimberly F; Parham, Leda A; Ramírez, Rosa M Gélvez; Montoya, Maria C Miranda; Rojas, Diana P; Brown, Catherine M; Hennigan, Scott; Sabina, Brandon; Scotland, Sarah; Gangavarapu, Karthik; Grubaugh, Nathan D; Oliveira, Glenn; Robles-Sikisaka, Refugio; Rambaut, Andrew; Gehrke, Lee; Smole, Sandra; Halloran, M Elizabeth; Villar, Luis; Mattar, Salim; Lorenzana, Ivette; Cerbino-Neto, Jose; Valim, Clarissa; Degrave, Wim; Bozza, Patricia T; Gnirke, Andreas; Andersen, Kristian G; Isern, Sharon; Michael, Scott F; Bozza, Fernando A; Souza, Thiago M L; Bosch, Irene; Yozwiak, Nathan L; MacInnis, Bronwyn L; Sabeti, Pardis C

2017-06-15

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.

CRAVE: a database, middleware and visualization system for phenotype ontologies.

PubMed

Gkoutos, Georgios V; Green, Eain C J; Greenaway, Simon; Blake, Andrew; Mallon, Ann-Marie; Hancock, John M

2005-04-01

A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

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 ...

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

Differential gene expression profiles in the venom gland/sac of Eumenes pomiformis (Hymenoptera: Eumenidae).

PubMed

Baek, Ji Hyeong; Lee, Si Hyeock

2010-06-01

To search for novel transcripts encoding biologically active venom components, a subtractive cDNA library specific to the venom gland and sac (gland/sac) of a solitary hunting wasp species, Eumenes pomiformis Fabricius (1781), was constructed by suppression subtractive hybridization. A total of 541 expressed sequence tags (ESTs) were clustered and assembled into 102 contigs (31 multiple sequences and 71 singletons). In total, 37 cDNAs were found in the library via BLASTx searching and manual annotation. Eight contigs (337 ESTs) encoding short venom peptides (10 to 16 amino acids) occupied 62% of the library. The deduced amino acid sequence (78 amino acids) of a novel venom peptide transcript shared sequence similarity with trypsin inhibitors and dendrotoxin-like venom peptides known to be K(+) channel blockers, implying that this novel peptide may play a role in the paralysis of prey. In addition to phospholipase A2 and hyaluronidase, which are known to be the main components of wasp venoms, several transcripts encoding enzymes, including three metallopeptidases and a decarboxylase likely involved in the processing and activation of venomous proteins, peptides, amines, and neurotransmitters, were also isolated from the library. The presence of a transcript encoding a putative insulin/insulin-like peptide binding protein suggests that solitary hunting wasps use their venom to control their prey, leading to larval growth cessation. The abundance of these venom components in the venom gland/sac and in the alimentary canal was confirmed by quantitative real-time PCR. Discovery of venom gland/sac-specific transcripts should promote further studies on biologically active components in the venom of solitary hunting wasps. Copyright 2010 Elsevier Ltd. All rights reserved.

Genome Sequence of the Pea Aphid Acyrthosiphon pisum

PubMed Central

2010-01-01

Aphids are important agricultural pests and also biological models for studies of insect-plant interactions, symbiosis, virus vectoring, and the developmental causes of extreme phenotypic plasticity. Here we present the 464 Mb draft genome assembly of the pea aphid Acyrthosiphon pisum. This first published whole genome sequence of a basal hemimetabolous insect provides an outgroup to the multiple published genomes of holometabolous insects. Pea aphids are host-plant specialists, they can reproduce both sexually and asexually, and they have coevolved with an obligate bacterial symbiont. Here we highlight findings from whole genome analysis that may be related to these unusual biological features. These findings include discovery of extensive gene duplication in more than 2000 gene families as well as loss of evolutionarily conserved genes. Gene family expansions relative to other published genomes include genes involved in chromatin modification, miRNA synthesis, and sugar transport. Gene losses include genes central to the IMD immune pathway, selenoprotein utilization, purine salvage, and the entire urea cycle. The pea aphid genome reveals that only a limited number of genes have been acquired from bacteria; thus the reduced gene count of Buchnera does not reflect gene transfer to the host genome. The inventory of metabolic genes in the pea aphid genome suggests that there is extensive metabolite exchange between the aphid and Buchnera, including sharing of amino acid biosynthesis between the aphid and Buchnera. The pea aphid genome provides a foundation for post-genomic studies of fundamental biological questions and applied agricultural problems. PMID:20186266

Plant Omics Data Center: an integrated web repository for interspecies gene expression networks with NLP-based curation.

PubMed

Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

2015-01-01

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Database Resources of the BIG Data Center in 2018

PubMed Central

Xu, Xingjian; Hao, Lili; Zhu, Junwei; Tang, Bixia; Zhou, Qing; Song, Fuhai; Chen, Tingting; Zhang, Sisi; Dong, Lili; Lan, Li; Wang, Yanqing; Sang, Jian; Hao, Lili; Liang, Fang; Cao, Jiabao; Liu, Fang; Liu, Lin; Wang, Fan; Ma, Yingke; Xu, Xingjian; Zhang, Lijuan; Chen, Meili; Tian, Dongmei; Li, Cuiping; Dong, Lili; Du, Zhenglin; Yuan, Na; Zeng, Jingyao; Zhang, Zhewen; Wang, Jinyue; Shi, Shuo; Zhang, Yadong; Pan, Mengyu; Tang, Bixia; Zou, Dong; Song, Shuhui; Sang, Jian; Xia, Lin; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Zhang, Yang; Sheng, Xin; Lu, Mingming; Wang, Qi; Xiao, Jingfa; Zou, Dong; Wang, Fan; Hao, Lili; Liang, Fang; Li, Mengwei; Sun, Shixiang; Zou, Dong; Li, Rujiao; Yu, Chunlei; Wang, Guangyu; Sang, Jian; Liu, Lin; Li, Mengwei; Li, Man; Niu, Guangyi; Cao, Jiabao; Sun, Shixiang; Xia, Lin; Yin, Hongyan; Zou, Dong; Xu, Xingjian; Ma, Lina; Chen, Huanxin; Sun, Yubin; Yu, Lei; Zhai, Shuang; Sun, Mingyuan; Zhang, Zhang; Zhao, Wenming; Xiao, Jingfa; Bao, Yiming; Song, Shuhui; Hao, Lili; Li, Rujiao; Ma, Lina; Sang, Jian; Wang, Yanqing; Tang, Bixia; Zou, Dong; Wang, Fan

2018-01-01

Abstract The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. PMID:29036542

Ribosomal RNA Genes Contribute to the Formation of Pseudogenes and Junk DNA in the Human Genome.

PubMed

Robicheau, Brent M; Susko, Edward; Harrigan, Amye M; Snyder, Marlene

2017-02-01

Approximately 35% of the human genome can be identified as sequence devoid of a selected-effect function, and not derived from transposable elements or repeated sequences. We provide evidence supporting a known origin for a fraction of this sequence. We show that: 1) highly degraded, but near full length, ribosomal DNA (rDNA) units, including both 45S and Intergenic Spacer (IGS), can be found at multiple sites in the human genome on chromosomes without rDNA arrays, 2) that these rDNA sequences have a propensity for being centromere proximal, and 3) that sequence at all human functional rDNA array ends is divergent from canonical rDNA to the point that it is pseudogenic. We also show that small sequence strings of rDNA (from 45S + IGS) can be found distributed throughout the genome and are identifiable as an "rDNA-like signal", representing 0.26% of the q-arm of HSA21 and ∼2% of the total sequence of other regions tested. The size of sequence strings found in the rDNA-like signal intergrade into the size of sequence strings that make up the full-length degrading rDNA units found scattered throughout the genome. We conclude that the displaced and degrading rDNA sequences are likely of a similar origin but represent different stages in their evolution towards random sequence. Collectively, our data suggests that over vast evolutionary time, rDNA arrays contribute to the production of junk DNA. The concept that the production of rDNA pseudogenes is a by-product of concerted evolution represents a previously under-appreciated process; we demonstrate here its importance. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Methods for magnetic resonance analysis using magic angle technique

DOEpatents

Hu, Jian Zhi [Richland, WA; Wind, Robert A [Kennewick, WA; Minard, Kevin R [Kennewick, WA; Majors, Paul D [Kennewick, WA

2011-11-22

Methods of performing a magnetic resonance analysis of a biological object are disclosed that include placing the object in a main magnetic field (that has a static field direction) and in a radio frequency field; rotating the object at a 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 phase-corrected magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. In particular embodiments the method includes pulsing the radio frequency to provide at least two of a spatially selective read pulse, a spatially selective phase pulse, and a spatially selective storage pulse. Further disclosed methods provide pulse sequences that provide extended imaging capabilities, such as chemical shift imaging or multiple-voxel data acquisition.

A rapid, one step molecular identification of Trichoderma citrinoviride and Trichoderma reesei.

PubMed

Saroj, Dina B; Dengeti, Shrinivas N; Aher, Supriya; Gupta, Anil K

2015-06-01

Trichoderma species are widely used as production hosts for industrial enzymes. Identification of Trichoderma species requires a complex molecular biology based identification involving amplification and sequencing of multiple genes. Industrial laboratories are required to run identification tests repeatedly in cell banking procedures and also to prove absence of production host in the product. Such demands can be fulfilled by a brief method which enables confirmation of strain identity. This communication describes one step identification method for two common Trichoderma species; T. citrinoviride and T. reesei, based on identification of polymorphic region in the nucleotide sequence of translation elongation factor 1 alpha. A unique forward primer and common reverse primer resulted in 153 and 139 bp amplicon for T. citrinoviride and T. reesei, respectively. Simplification was further introduced by using mycelium as template for PCR amplification. Method described in this communication allows rapid, one step identification of two Trichoderma species.

PFAAT version 2.0: a tool for editing, annotating, and analyzing multiple sequence alignments.

PubMed

Caffrey, Daniel R; Dana, Paul H; Mathur, Vidhya; Ocano, Marco; Hong, Eun-Jong; Wang, Yaoyu E; Somaroo, Shyamal; Caffrey, Brian E; Potluri, Shobha; Huang, Enoch S

2007-10-11

By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis. Here we describe the release of PFAAT version 2.0, a tool for editing, analyzing, and annotating multiple sequence alignments. Support for multiple annotations is a key component of this release as it provides a framework for most of the new functionalities. The sequence annotations are accessible from the alignment and tree, where they are typically used to label sequences or hyperlink them to related databases. Sequence annotations can be created manually or extracted automatically from UniProt entries. Once a multiple sequence alignment is populated with sequence annotations, sequences can be easily selected and sorted through a sophisticated search dialog. The selected sequences can be further analyzed using statistical methods that explicitly model relationships between the sequence annotations and residue properties. Residue annotations are accessible from the alignment viewer and are typically used to designate binding sites or properties for a particular residue. Residue annotations are also searchable, and allow one to quickly select alignment columns for further sequence analysis, e.g. computing percent identities. Other features include: novel algorithms to compute sequence conservation, mapping conservation scores to a 3D structure in Jmol, displaying secondary structure elements, and sorting sequences by residue composition. PFAAT provides a framework whereby end-users can specify knowledge for a protein family in the form of annotation. The annotations can be combined with sophisticated analysis to test hypothesis that relate to sequence, structure and function.

Combining multiple tools outperforms individual methods in gene set enrichment analyses.

PubMed

Alhamdoosh, Monther; Ng, Milica; Wilson, Nicholas J; Sheridan, Julie M; Huynh, Huy; Wilson, Michael J; Ritchie, Matthew E

2017-02-01

Gene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions. The ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA's gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists' feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes. EGSEA is available as an R package at http://www.bioconductor.org/packages/EGSEA/ . The gene sets collections are available in the R package EGSEAdata from http://www.bioconductor.org/packages/EGSEAdata/ . monther.alhamdoosh@csl.com.au mritchie@wehi.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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.

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.

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.

Asynchronous, Decentralized DS-CDMA Using Feedback-Controlled Spreading Sequences for Time-Dispersive Channels

NASA Astrophysics Data System (ADS)

Miyatake, Teruhiko; Chiba, Kazuki; Hamamura, Masanori; Tachikawa, Shin'ichi

We propose a novel asynchronous direct-sequence codedivision multiple access (DS-CDMA) using feedback-controlled spreading sequences (FCSSs) (FCSS/DS-CDMA). At the receiver of FCSS/DS-CDMA, the code-orthogonalizing filter (COF) produces a spreading sequence, and the receiver returns the spreading sequence to the transmitter. Then the transmitter uses the spreading sequence as its updated version. The performance of FCSS/DS-CDMA is evaluated over time-dispersive channels. The results indicate that FCSS/DS-CDMA greatly suppresses both the intersymbol interference (ISI) and multiple access interference (MAI) over time-invariant channels. FCSS/DS-CDMA is applicable to the decentralized multiple access.

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.…

Computational design of RNAs with complex energy landscapes.

PubMed

Höner zu Siederdissen, Christian; Hammer, Stefan; Abfalter, Ingrid; Hofacker, Ivo L; Flamm, Christoph; Stadler, Peter F

2013-12-01

RNA has become an integral building material in synthetic biology. Dominated by their secondary structures, which can be computed efficiently, RNA molecules are amenable not only to in vitro and in vivo selection, but also to rational, computation-based design. While the inverse folding problem of constructing an RNA sequence with a prescribed ground-state structure has received considerable attention for nearly two decades, there have been few efforts to design RNAs that can switch between distinct prescribed conformations. We introduce a user-friendly tool for designing RNA sequences that fold into multiple target structures. The underlying algorithm makes use of a combination of graph coloring and heuristic local optimization to find sequences whose energy landscapes are dominated by the prescribed conformations. A flexible interface allows the specification of a wide range of design goals. We demonstrate that bi- and tri-stable "switches" can be designed easily with moderate computational effort for the vast majority of compatible combinations of desired target structures. RNAdesign is freely available under the GPL-v3 license. Copyright © 2013 Wiley Periodicals, Inc.

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.

PubMed

Jinawath, Natini; Bunbanjerdsuk, Sacarin; Chayanupatkul, Maneerat; Ngamphaiboon, Nuttapong; Asavapanumas, Nithi; Svasti, Jisnuson; Charoensawan, Varodom

2016-11-22

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians' point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world's major diseases.

Apoptosis: a four-week laboratory investigation for advanced molecular and cellular biology students.

PubMed

DiBartolomeis, Susan M; Moné, James P

2003-01-01

Over the past decade, apoptosis has emerged as an important field of study central to ongoing research in many diverse fields, from developmental biology to cancer research. Apoptosis proceeds by a highly coordinated series of events that includes enzyme activation, DNA fragmentation, and alterations in plasma membrane permeability. The detection of each of these phenotypic changes is accessible to advanced undergraduate cell and molecular biology students. We describe a 4-week laboratory sequence that integrates cell culture, fluorescence microscopy, DNA isolation and analysis, and western blotting (immunoblotting) to follow apoptosis in cultured human cells. Students working in teams chemically induce apoptosis, and harvest, process, and analyze cells, using their data to determine the order of events during apoptosis. We, as instructors, expose the students to an environment closely simulating what they would encounter in an active cell or molecular biology research laboratory by having students coordinate and perform multiple tasks simultaneously and by having them experience experimental design using current literature, data interpretation, and analysis to answer a single question. Students are assessed by examination of laboratory notebooks for completeness of experimental protocols and analysis of results and for completion of an assignment that includes questions pertaining to data interpretation and apoptosis.

The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing.

PubMed

Binladen, Jonas; Gilbert, M Thomas P; Bollback, Jonathan P; Panitz, Frank; Bendixen, Christian; Nielsen, Rasmus; Willerslev, Eske

2007-02-14

The invention of the Genome Sequence 20 DNA Sequencing System (454 parallel sequencing platform) has enabled the rapid and high-volume production of sequence data. Until now, however, individual emulsion PCR (emPCR) reactions and subsequent sequencing runs have been unable to combine template DNA from multiple individuals, as homologous sequences cannot be subsequently assigned to their original sources. We use conventional PCR with 5'-nucleotide tagged primers to generate homologous DNA amplification products from multiple specimens, followed by sequencing through the high-throughput Genome Sequence 20 DNA Sequencing System (GS20, Roche/454 Life Sciences). Each DNA sequence is subsequently traced back to its individual source through 5'tag-analysis. We demonstrate that this new approach enables the assignment of virtually all the generated DNA sequences to the correct source once sequencing anomalies are accounted for (miss-assignment rate<0.4%). Therefore, the method enables accurate sequencing and assignment of homologous DNA sequences from multiple sources in single high-throughput GS20 run. We observe a bias in the distribution of the differently tagged primers that is dependent on the 5' nucleotide of the tag. In particular, primers 5' labelled with a cytosine are heavily overrepresented among the final sequences, while those 5' labelled with a thymine are strongly underrepresented. A weaker bias also exists with regards to the distribution of the sequences as sorted by the second nucleotide of the dinucleotide tags. As the results are based on a single GS20 run, the general applicability of the approach requires confirmation. However, our experiments demonstrate that 5'primer tagging is a useful method in which the sequencing power of the GS20 can be applied to PCR-based assays of multiple homologous PCR products. The new approach will be of value to a broad range of research areas, such as those of comparative genomics, complete mitochondrial analyses, population genetics, and phylogenetics.

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

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Natural history of hepatic metastases from colorectal cancer--pathobiological pathways with clinical significance.

PubMed

Paschos, Konstantinos A; Majeed, Ali W; Bird, Nigel C

2014-04-14

Colorectal cancer hepatic metastases represent the final stage of a multi-step biological process. This process starts with a series of mutations in colonic epithelial cells, continues with their detachment from the large intestine, dissemination through the blood and/or lymphatic circulation, attachment to the hepatic sinusoids and interactions with the sinusoidal cells, such as sinusoidal endothelial cells, Kupffer cells, stellate cells and pit cells. The metastatic sequence terminates with colorectal cancer cell invasion, adaptation and colonisation of the hepatic parenchyma. All these events, termed the colorectal cancer invasion-metastasis cascade, include multiple molecular pathways, intercellular interactions and expression of a plethora of chemokines and growth factors, and adhesion molecules, such as the selectins, the integrins or the cadherins, as well as enzymes including matrix metalloproteinases. This review aims to present recent advances that provide insights into these cell-biological events and emphasizes those that may be amenable to therapeutic targeting.

Mayo Clinic Zebrafish Facility Overview.

PubMed

Leveque, Ryan E; Clark, Karl J; Ekker, Stephen C

2016-07-01

The zebrafish (Danio rerio) is a premier nonmammalian vertebrate model organism. This small aquatic fish is utilized in multiple disciplines in the Mayo Clinic community and by many laboratories around the world because of its biological similarity to humans, its advanced molecular genetics, the elucidation of its genome sequence, and the ever-expanding and outstanding new biological tools now available to the zebrafish researcher. The Mayo Clinic Zebrafish Facility (MCZF) houses ∼2,000 tanks annotated using an in-house, Internet cloud-based bar-coding system tied to our established zfishbook.org web infrastructure. Paramecia are the primary food source for larval fish rearing, using a simplified culture protocol described herein. The MCZF supports the specific ongoing research in a variety of laboratories, while also serving as a local hub for new scientists as they learn to tap into the potential of this model system for understanding normal development, disease, and as models of health.

Biological classification with RNA-Seq data: Can alternatively spliced transcript expression enhance machine learning classifier?

PubMed

Johnson, Nathan T; Dhroso, Andi; Hughes, Katelyn J; Korkin, Dmitry

2018-06-25

The extent to which the genes are expressed in the cell can be simplistically defined as a function of one or more factors of the environment, lifestyle, and genetics. RNA sequencing (RNA-Seq) is becoming a prevalent approach to quantify gene expression, and is expected to gain better insights to a number of biological and biomedical questions, compared to the DNA microarrays. Most importantly, RNA-Seq allows to quantify expression at the gene and alternative splicing isoform levels. However, leveraging the RNA-Seq data requires development of new data mining and analytics methods. Supervised machine learning methods are commonly used approaches for biological data analysis, and have recently gained attention for their applications to the RNA-Seq data. In this work, we assess the utility of supervised learning methods trained on RNA-Seq data for a diverse range of biological classification tasks. We hypothesize that the isoform-level expression data is more informative for biological classification tasks than the gene-level expression data. Our large-scale assessment is done through utilizing multiple datasets, organisms, lab groups, and RNA-Seq analysis pipelines. Overall, we performed and assessed 61 biological classification problems that leverage three independent RNA-Seq datasets and include over 2,000 samples that come from multiple organisms, lab groups, and RNA-Seq analyses. These 61 problems include predictions of the tissue type, sex, or age of the sample, healthy or cancerous phenotypes and, the pathological tumor stage for the samples from the cancerous tissue. For each classification problem, the performance of three normalization techniques and six machine learning classifiers was explored. We find that for every single classification problem, the isoform-based classifiers outperform or are comparable with gene expression based methods. The top-performing supervised learning techniques reached a near perfect classification accuracy, demonstrating the utility of supervised learning for RNA-Seq based data analysis. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Development of unidentified dna-specific hif 1α gene of lizard (hemidactylus platyurus) which plays a role in tissue regeneration process

NASA Astrophysics Data System (ADS)

Novianti, T.; Sadikin, M.; Widia, S.; Juniantito, V.; Arida, E. A.

2018-03-01

Development of unidentified specific gene is essential to analyze the availability these genes in biological process. Identification unidentified specific DNA of HIF 1α genes is important to analyze their contribution in tissue regeneration process in lizard tail (Hemidactylus platyurus). Bioinformatics and PCR techniques are relatively an easier method to identify an unidentified gene. The most widely used method is BLAST (Basic Local Alignment Sequence Tools) method for alignment the sequences from the other organism. BLAST technique is online software from website https://blast.ncbi.nlm.nih.gov/Blast.cgi that capable to generate the similar sequences from closest kinship to distant kindship. Gecko japonicus is a species that it has closest kinship with H. platyurus. Comparing HIF 1 α gene sequence of G. japonicus with the other species used multiple alignment methods from Mega7 software. Conserved base areas were identified using Clustal IX method. Primary DNA of HIF 1 α gene was design by Primer3 software. HIF 1α gene of lizard (H. platyurus) was successfully amplified using a real-time PCR machine by primary DNA that we had designed from Gecko japonicus. Identification unidentified gene of HIF 1a lizard has been done successfully with multiple alignment method. The study was conducted by analyzing during the growth of tail on day 1, 3, 5, 7, 10, 13 and 17 of lizard tail after autotomy. Process amplification of HIF 1α gene was described by CT value in real time PCR machine. HIF 1α expression of gene is quantified by Livak formula. Chi-square statistic test is 0.000 which means that there is a different expression of HIF 1 α gene in every growth day treatment.

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 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.

AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences

PubMed Central

2010-01-01

Background Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses. Results AlignMiner is a Web-based application for detection of conserved and divergent regions in alignments of conserved sequences, focusing particularly on divergence. It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results. AlignMiner uses different scoring methods for assessing conserved/divergent regions, Entropy being the method that provides the highest number of regions with the greatest length, and Weighted being the most restrictive. Conserved/divergent regions can be generated either with respect to the consensus sequence or to one master sequence. The resulting data are presented in a graphical interface developed in AJAX, which provides remarkable user interaction capabilities. Users do not need to wait until execution is complete and can.even inspect their results on a different computer. Data can be downloaded onto a user disk, in standard formats. In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies. Primer design is assisted by a module that deploys several oligonucleotide parameters for designing primers "on the fly". Conclusions AlignMiner can be used to reliably detect divergent regions via several scoring methods that provide different levels of selectivity. Its predictions have been verified by experimental means. Hence, it is expected that its usage will save researchers' time and ensure an objective selection of the best-possible divergent region when closely related sequences are analysed. AlignMiner is freely available at http://www.scbi.uma.es/alignminer. PMID:20525162

Sequencing Data Discovery and Integration for Earth System Science with MetaSeek

NASA Astrophysics Data System (ADS)

Hoarfrost, A.; Brown, N.; Arnosti, C.

2017-12-01

Microbial communities play a central role in biogeochemical cycles. Sequencing data resources from environmental sources have grown exponentially in recent years, and represent a singular opportunity to investigate microbial interactions with Earth system processes. Carrying out such meta-analyses depends on our ability to discover and curate sequencing data into large-scale integrated datasets. However, such integration efforts are currently challenging and time-consuming, with sequencing data scattered across multiple repositories and metadata that is not easily or comprehensively searchable. MetaSeek is a sequencing data discovery tool that integrates sequencing metadata from all the major data repositories, allowing the user to search and filter on datasets in a lightweight application with an intuitive, easy-to-use web-based interface. Users can save and share curated datasets, while other users can browse these data integrations or use them as a jumping off point for their own curation. Missing and/or erroneous metadata are inferred automatically where possible, and where not possible, users are prompted to contribute to the improvement of the sequencing metadata pool by correcting and amending metadata errors. Once an integrated dataset has been curated, users can follow simple instructions to download their raw data and quickly begin their investigations. In addition to the online interface, the MetaSeek database is easily queryable via an open API, further enabling users and facilitating integrations of MetaSeek with other data curation tools. This tool lowers the barriers to curation and integration of environmental sequencing data, clearing the path forward to illuminating the ecosystem-scale interactions between biological and abiotic processes.

Using a Sequence of Earcons to Monitor Multiple Simulated Patients.

PubMed

Hickling, Anna; Brecknell, Birgit; Loeb, Robert G; Sanderson, Penelope

2017-03-01

The aim of this study was to determine whether a sequence of earcons can effectively convey the status of multiple processes, such as the status of multiple patients in a clinical setting. Clinicians often monitor multiple patients. An auditory display that intermittently conveys the status of multiple patients may help. Nonclinician participants listened to sequences of 500-ms earcons that each represented the heart rate (HR) and oxygen saturation (SpO 2 ) levels of a different simulated patient. In each sequence, one, two, or three patients had an abnormal level of HR and/or SpO 2 . In Experiment 1, participants reported which of nine patients in a sequence were abnormal. In Experiment 2, participants identified the vital signs of one, two, or three abnormal patients in sequences of one, five, or nine patients, where the interstimulus interval (ISI) between earcons was 150 ms. Experiment 3 used the five-sequence condition of Experiment 2, but the ISI was either 150 ms or 800 ms. Participants reported which patient(s) were abnormal with median 95% accuracy. Identification accuracy for vital signs decreased as the number of abnormal patients increased from one to three, p < .001, but accuracy was unaffected by number of patients in a sequence. Overall, identification accuracy was significantly higher with an ISI of 800 ms (89%) compared with an ISI of 150 ms (83%), p < .001. A multiple-patient display can be created by cycling through earcons that represent individual patients. The principles underlying the multiple-patient display can be extended to other vital signs, designs, and domains.

DNA is structured as a linear "jigsaw puzzle" in the genomes of Arabidopsis, rice, and budding yeast.

PubMed

Liu, Yun-Hua; Zhang, Meiping; Wu, Chengcang; Huang, James J; Zhang, Hong-Bin

2014-01-01

Knowledge of how a genome is structured and organized from its constituent elements is crucial to understanding its biology and evolution. Here, we report the genome structuring and organization pattern as revealed by systems analysis of the sequences of three model species, Arabidopsis, rice and yeast, at the whole-genome and chromosome levels. We found that all fundamental function elements (FFE) constituting the genomes, including genes (GEN), DNA transposable elements (DTE), retrotransposable elements (RTE), simple sequence repeats (SSR), and (or) low complexity repeats (LCR), are structured in a nonrandom and correlative manner, thus leading to a hypothesis that the DNA of the species is structured as a linear "jigsaw puzzle". Furthermore, we showed that different FFE differ in their importance in the formation and evolution of the DNA jigsaw puzzle structure between species. DTE and RTE play more important roles than GEN, LCR, and SSR in Arabidopsis, whereas GEN and RTE play more important roles than LCR, SSR, and DTE in rice. The genes having multiple recognized functions play more important roles than those having single functions. These results provide useful knowledge necessary for better understanding genome biology and evolution of the species and for effective molecular breeding of rice.

Transforming plant biology and breeding with CRISPR/Cas9, Cas12 and Cas13.

PubMed

Schindele, Patrick; Wolter, Felix; Puchta, Holger

2018-04-30

Currently, biology is revolutionized by ever growing applications of the CRISPR/Cas system. As discussed in this Review, new avenues have opened up for plant research and breeding by the use of the sequence-specific DNases Cas9 and Cas12 (formerly named Cpf1) and, more recently, the RNase Cas13 (formerly named C2c2). Although double strand break-induced gene editing based on error-prone nonhomologous end joining has been applied to obtain new traits, such as powdery mildew resistance in wheat or improved pathogen resistance and increased yield in tomato, improved technologies based on CRISPR/Cas for programmed change in plant genomes via homologous recombination have recently been developed. Cas9- and Cas12- mediated DNA binding is used to develop tools for many useful applications, such as transcriptional regulation or fluorescence-based imaging of specific chromosomal loci in plant genomes. Cas13 has recently been applied to degrade mRNAs and combat viral RNA replication. By the possibility to address multiple sequences with different guide RNAs and by the simultaneous use of different Cas proteins in a single cell, we should soon be able to achieve complex changes of plant metabolism in a controlled way. © 2018 Federation of European Biochemical Societies.

Final Technical Report - Use of Systems Biology Approaches to Develop Advanced Biofuel-Synthesizing Cyanobacterial Strains

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

Pakrasi, Himadri

The overall objective of this project was to use a systems biology approach to evaluate the potentials of a number of cyanobacterial strains for photobiological production of advanced biofuels and/or their chemical precursors. Cyanobacteria are oxygen evolving photosynthetic prokaryotes. Among them, certain unicellular species such as Cyanothece can also fix N 2, a process that is exquisitely sensitive to oxygen. To accommodate such incompatible processes in a single cell, Cyanothece produces oxygen during the day, and creates an O 2-limited intracellular environment during the night to perform O 2-sensitive processes such as N 2-fixation. Thus, Cyanothece cells are natural bioreactorsmore » for the storage of captured solar energy with subsequent utilization at a different time during a diurnal cycle. Our studies include the identification of a novel, fast-growing, mixotrophic, transformable cyanobacterium. This strain has been sequenced and will be made available to the community. In addition, we have developed genome-scale models for a family of cyanobacteria to assess their metabolic repertoire. Furthermore, we developed a method for rapid construction of metabolic models using multiple annotation sources and a metabolic model of a related organism. This method will allow rapid annotation and screening of potential phenotypes based on the newly available genome sequences of many organisms.« less

Nuclear and cpDNA sequences combined provide strong inference of higher phylogenetic relationships in the phlox family (Polemoniaceae).

PubMed

Johnson, Leigh A; Chan, Lauren M; Weese, Terri L; Busby, Lisa D; McMurry, Samuel

2008-09-01

Members of the phlox family (Polemoniaceae) serve as useful models for studying various evolutionary and biological processes. Despite its biological importance, no family-wide phylogenetic estimate based on multiple DNA regions with complete generic sampling is available. Here, we analyze one nuclear and five chloroplast DNA sequence regions (nuclear ITS, chloroplast matK, trnL intron plus trnL-trnF intergeneric spacer, and the trnS-trnG, trnD-trnT, and psbM-trnD intergenic spacers) using parsimony and Bayesian methods, as well as assessments of congruence and long branch attraction, to explore phylogenetic relationships among 84 ingroup species representing all currently recognized Polemoniaceae genera. Relationships inferred from the ITS and concatenated chloroplast regions are similar overall. A combined analysis provides strong support for the monophyly of Polemoniaceae and subfamilies Acanthogilioideae, Cobaeoideae, and Polemonioideae. Relationships among subfamilies, and thus for the precise root of Polemoniaceae, remain poorly supported. Within the largest subfamily, Polemonioideae, four clades corresponding to tribes Polemonieae, Phlocideae, Gilieae, and Loeselieae receive strong support. The monogeneric Polemonieae appears sister to Phlocideae. Relationships within Polemonieae, Phlocideae, and Gilieae are mostly consistent between analyses and data permutations. Many relationships within Loeselieae remain uncertain. Overall, inferred phylogenetic relationships support a higher-level classification for Polemoniaceae proposed in 2000.

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…

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

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

2006-03-09

The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

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.

Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

PubMed

Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

2017-01-01

The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

3D: diversity, dynamics, differential testing - a proposed pipeline for analysis of next-generation sequencing T cell repertoire data.

PubMed

Zhang, Li; Cham, Jason; Paciorek, Alan; Trager, James; Sheikh, Nadeem; Fong, Lawrence

2017-02-27

Cancer immunotherapy has demonstrated significant clinical activity in different cancers. T cells represent a crucial component of the adaptive immune system and are thought to mediate anti-tumoral immunity. Antigen-specific recognition by T cells is via the T cell receptor (TCR) which is unique for each T cell. Next generation sequencing (NGS) of the TCRs can be used as a platform to profile the T cell repertoire. Though there are a number of software tools available for processing repertoire data by mapping antigen receptor segments to sequencing reads and assembling the clonotypes, most of them are not designed to track and examine the dynamic nature of the TCR repertoire across multiple time points or between different biologic compartments (e.g., blood and tissue samples) in a clinical context. We integrated different diversity measures to assess the T cell repertoire diversity and examined the robustness of the diversity indices. Among those tested, Clonality was identified for its robustness as a key metric for study design and the first choice to measure TCR repertoire diversity. To evaluate the dynamic nature of T cell clonotypes across time, we utilized several binary similarity measures (such as Baroni-Urbani and Buser overlap index), relative clonality and Morisita's overlap index, as well as the intraclass correlation coefficient, and performed fold change analysis, which was further extended to investigate the transition of clonotypes among different biological compartments. Furthermore, the application of differential testing enabled the detection of clonotypes which were significantly changed across time. By applying the proposed "3D" analysis pipeline to the real example of prostate cancer subjects who received sipuleucel-T, an FDA-approved immunotherapy, we were able to detect changes in TCR sequence frequency and diversity thus demonstrating that sipuleucel-T treatment affected TCR repertoire in blood and in prostate tissue. We also found that the increase in common TCR sequences between tissue and blood after sipuleucel-T treatment supported the hypothesis that treatment-induced T cell migrated into the prostate tissue. In addition, a second example of prostate cancer subjects treated with Ipilimumab and granulocyte macrophage colony stimulating factor (GM-CSF) was presented in the supplementary documents to further illustrate assessing the treatment-associated change in a clinical context by the proposed workflow. Our paper provides guidance to study the diversity and dynamics of NGS-based TCR repertoire profiling in a clinical context to ensure consistency and reproducibility of post-analysis. This analysis pipeline will provide an initial workflow for TCR sequencing data with serial time points and for comparing T cells in multiple compartments for a clinical study.

Genome-Wide Mutagenesis in Borrelia burgdorferi.

PubMed

Lin, Tao; Gao, Lihui

2018-01-01

Signature-tagged mutagenesis (STM) is a functional genomics approach to identify bacterial virulence determinants and virulence factors by simultaneously screening multiple mutants in a single host animal, and has been utilized extensively for the study of bacterial pathogenesis, host-pathogen interactions, and spirochete and tick biology. The signature-tagged transposon mutagenesis has been developed to investigate virulence determinants and pathogenesis of Borrelia burgdorferi. Mutants in genes important in virulence are identified by negative selection in which the mutants fail to colonize or disseminate in the animal host and tick vector. STM procedure combined with Luminex Flex ® Map™ technology and next-generation sequencing (e.g., Tn-seq) are the powerful high-throughput tools for the determination of Borrelia burgdorferi virulence determinants. The assessment of multiple tissue sites and two DNA resources at two different time points using Luminex Flex ® Map™ technology provides a robust data set. B. burgdorferi transposon mutant screening indicates that a high proportion of genes are the novel virulence determinants that are required for mouse and tick infection. In this protocol, an effective signature-tagged Himar1-based transposon suicide vector was developed and used to generate a sequence-defined library of nearly 4800 mutants in the infectious B. burgdorferi B31 clone. In STM, signature-tagged suicide vectors are constructed by inserting unique DNA sequences (tags) into the transposable elements. The signature-tagged transposon mutants are generated when transposon suicide vectors are transformed into an infectious B. burgdorferi clone, and the transposable element is transposed into the 5'-TA-3' sequence in the B. burgdorferi genome with the signature tag. The transposon library is created and consists of many sub-libraries, each sub-library has several hundreds of mutants with same tags. A group of mice or ticks are infected with a mixed population of mutants with different tags, after recovered from different tissues of infected mice and ticks, mutants from output pool and input pool are detected using high-throughput, semi-quantitative Luminex ® FLEXMAP™ or next-generation sequencing (Tn-seq) technologies. Thus far, we have created a high-density, sequence-defined transposon library of over 6600 STM mutants for the efficient genome-wide investigation of genes and gene products required for wild-type pathogenesis, host-pathogen interactions, in vitro growth, in vivo survival, physiology, morphology, chemotaxis, motility, structure, metabolism, gene regulation, plasmid maintenance and replication, etc. The insertion sites of 4480 transposon mutants have been determined. About 800 predicted protein-encoding genes in the genome were disrupted in the STM transposon library. The infectivity and some functions of 800 mutants in 500 genes have been determined. Analysis of these transposon mutants has yielded valuable information regarding the genes and gene products important in the pathogenesis and biology of B. burgdorferi and its tick vectors.

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.

Using Phylogenetic Analysis to Detect Market Substitution of Atlantic Salmon for Pacific Salmon: An Introductory Biology Laboratory Experiment

ERIC Educational Resources Information Center

Cline, Erica; Gogarten, Jennifer

2012-01-01

We describe a laboratory exercise developed for the cell and molecular biology quarter of a year-long majors' undergraduate introductory biology sequence. In an analysis of salmon samples collected by students in their local stores and restaurants, DNA sequencing and phylogenetic analysis were used to detect market substitution of Atlantic salmon…

Evolution of Cocirculating Varicella-Zoster Virus Genotypes during a Chickenpox Outbreak in Guinea-Bissau

PubMed Central

Gray, Eleanor R.; Kundu, Samit; Cooray, Samantha; Poulsen, Anja; Aaby, Peter; Breuer, Judith

2014-01-01

ABSTRACT Varicella-zoster virus (VZV), a double-stranded DNA alphaherpesvirus, is associated with seasonal outbreaks of varicella in nonimmunized populations. Little is known about whether these outbreaks are associated with a single or multiple viral genotypes and whether new mutations rapidly accumulate during transmission. Here, we take advantage of a well-characterized population cohort in Guinea-Bissau and produce a unique set of 23 full-length genome sequences, collected over 7 months from eight households. Comparative sequence analysis reveals that four distinct genotypes cocirculated among the population, three of which were present during the first week of the outbreak, although no patients were coinfected, which indicates that exposure to infectious virus from multiple sources is common during VZV outbreaks. Transmission of VZV was associated with length polymorphisms in the R1 repeat region and the origin of DNA replication. In two cases, these were associated with the formation of distinct lineages and point to the possible coevolution of these loci, despite the lack of any known functional link in VZV or related herpesviruses. We show that these and all other sequenced clade 5 viruses possess a distinct R1 repeat motif that increases the acidity of an ORF11p protein domain and postulate that this has either arisen or been lost following divergence of the major clades. Thus, sequencing of whole VZV genomes collected during an outbreak has provided novel insights into VZV biology, transmission patterns, and (recent) natural history. IMPORTANCE VZV is a highly infectious virus and the causative agent of chickenpox and shingles, the latter being particularly associated with the risk of painful complications. Seasonal outbreaks of chickenpox are very common among young children, yet little is known about the dynamics of the virus during person-to-person to transmission or whether multiple distinct viruses seed and/or cocirculate during an outbreak. In this study, we have sequenced chickenpox viruses from an outbreak in Guinea-Bissau that are supported by detailed epidemiological data. Our data show that multiple different virus strains seeded and were maintained throughout the 6-month outbreak period and that viruses transmitted between individuals accumulated new mutations in specific genomic regions. Of particular interest is the potential coevolution of two distinct parts of the genomes and our calculations of the rate of viral mutation, both of which increase our understanding of how VZV evolves over short periods of time in human populations. PMID:25275123

Evolution of cocirculating varicella-zoster virus genotypes during a chickenpox outbreak in Guinea-Bissau.

PubMed

Depledge, Daniel P; Gray, Eleanor R; Kundu, Samit; Cooray, Samantha; Poulsen, Anja; Aaby, Peter; Breuer, Judith

2014-12-01

Varicella-zoster virus (VZV), a double-stranded DNA alphaherpesvirus, is associated with seasonal outbreaks of varicella in nonimmunized populations. Little is known about whether these outbreaks are associated with a single or multiple viral genotypes and whether new mutations rapidly accumulate during transmission. Here, we take advantage of a well-characterized population cohort in Guinea-Bissau and produce a unique set of 23 full-length genome sequences, collected over 7 months from eight households. Comparative sequence analysis reveals that four distinct genotypes cocirculated among the population, three of which were present during the first week of the outbreak, although no patients were coinfected, which indicates that exposure to infectious virus from multiple sources is common during VZV outbreaks. Transmission of VZV was associated with length polymorphisms in the R1 repeat region and the origin of DNA replication. In two cases, these were associated with the formation of distinct lineages and point to the possible coevolution of these loci, despite the lack of any known functional link in VZV or related herpesviruses. We show that these and all other sequenced clade 5 viruses possess a distinct R1 repeat motif that increases the acidity of an ORF11p protein domain and postulate that this has either arisen or been lost following divergence of the major clades. Thus, sequencing of whole VZV genomes collected during an outbreak has provided novel insights into VZV biology, transmission patterns, and (recent) natural history. VZV is a highly infectious virus and the causative agent of chickenpox and shingles, the latter being particularly associated with the risk of painful complications. Seasonal outbreaks of chickenpox are very common among young children, yet little is known about the dynamics of the virus during person-to-person to transmission or whether multiple distinct viruses seed and/or cocirculate during an outbreak. In this study, we have sequenced chickenpox viruses from an outbreak in Guinea-Bissau that are supported by detailed epidemiological data. Our data show that multiple different virus strains seeded and were maintained throughout the 6-month outbreak period and that viruses transmitted between individuals accumulated new mutations in specific genomic regions. Of particular interest is the potential coevolution of two distinct parts of the genomes and our calculations of the rate of viral mutation, both of which increase our understanding of how VZV evolves over short periods of time in human populations. Copyright © 2014 Depledge et al.

Automatic Prediction of Protein 3D Structures by Probabilistic Multi-template Homology Modeling.

PubMed

Meier, Armin; Söding, Johannes

2015-10-01

Homology modeling predicts the 3D structure of a query protein based on the sequence alignment with one or more template proteins of known structure. Its great importance for biological research is owed to its speed, simplicity, reliability and wide applicability, covering more than half of the residues in protein sequence space. Although multiple templates have been shown to generally increase model quality over single templates, the information from multiple templates has so far been combined using empirically motivated, heuristic approaches. We present here a rigorous statistical framework for multi-template homology modeling. First, we find that the query proteins' atomic distance restraints can be accurately described by two-component Gaussian mixtures. This insight allowed us to apply the standard laws of probability theory to combine restraints from multiple templates. Second, we derive theoretically optimal weights to correct for the redundancy among related templates. Third, a heuristic template selection strategy is proposed. We improve the average GDT-ha model quality score by 11% over single template modeling and by 6.5% over a conventional multi-template approach on a set of 1000 query proteins. Robustness with respect to wrong constraints is likewise improved. We have integrated our multi-template modeling approach with the popular MODELLER homology modeling software in our free HHpred server http://toolkit.tuebingen.mpg.de/hhpred and also offer open source software for running MODELLER with the new restraints at https://bitbucket.org/soedinglab/hh-suite.

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

SIRW: A web server for the Simple Indexing and Retrieval System that combines sequence motif searches with keyword searches.

PubMed

Ramu, Chenna

2003-07-01

SIRW (http://sirw.embl.de/) is a World Wide Web interface to the Simple Indexing and Retrieval System (SIR) that is capable of parsing and indexing various flat file databases. In addition it provides a framework for doing sequence analysis (e.g. motif pattern searches) for selected biological sequences through keyword search. SIRW is an ideal tool for the bioinformatics community for searching as well as analyzing biological sequences of interest.

Fungi in Thailand: a case study of the efficacy of an ITS barcode for automatically identifying species within the Annulohypoxylon and Hypoxylon genera.

PubMed

Suwannasai, Nuttika; Martín, María P; Phosri, Cherdchai; Sihanonth, Prakitsin; Whalley, Anthony J S; Spouge, John L

2013-01-01

Thailand, a part of the Indo-Burma biodiversity hotspot, has many endemic animals and plants. Some of its fungal species are difficult to recognize and separate, complicating assessments of biodiversity. We assessed species diversity within the fungal genera Annulohypoxylon and Hypoxylon, which produce biologically active and potentially therapeutic compounds, by applying classical taxonomic methods to 552 teleomorphs collected from across Thailand. Using probability of correct identification (PCI), we also assessed the efficacy of automated species identification with a fungal barcode marker, ITS, in the model system of Annulohypoxylon and Hypoxylon. The 552 teleomorphs yielded 137 ITS sequences; in addition, we examined 128 GenBank ITS sequences, to assess biases in evaluating a DNA barcode with GenBank data. The use of multiple sequence alignment in a barcode database like BOLD raises some concerns about non-protein barcode markers like ITS, so we also compared species identification using different alignment methods. Our results suggest the following. (1) Multiple sequence alignment of ITS sequences is competitive with pairwise alignment when identifying species, so BOLD should be able to preserve its present bioinformatics workflow for species identification for ITS, and possibly therefore with at least some other non-protein barcode markers. (2) Automated species identification is insensitive to a specific choice of evolutionary distance, contributing to resolution of a current debate in DNA barcoding. (3) Statistical methods are available to address, at least partially, the possibility of expert misidentification of species. Phylogenetic trees discovered a cryptic species and strongly supported monophyletic clades for many Annulohypoxylon and Hypoxylon species, suggesting that ITS can contribute usefully to a barcode for these fungi. The PCIs here, derived solely from ITS, suggest that a fungal barcode will require secondary markers in Annulohypoxylon and Hypoxylon, however. The URL http://tinyurl.com/spouge-barcode contains computer programs and other supplementary material relevant to this article.

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.

Integrated Analyses of Cuticular Hydrocarbons, Chromosome and mtDNA in the Neotropical Social Wasp Mischocyttarus consimilis Zikán (Hymenoptera, Vespidae).

PubMed

Cunha, D A S; Menezes, R S T; Costa, M A; Lima, S M; Andrade, L H C; Antonialli, W F

2017-12-01

In the present work, we explored multiple data from different biological levels such as cuticular hydrocarbons, chromosomal features, and mtDNA sequences in the Neotropical social wasp Mischocyttarus consimilis (J.F. Zikán). Particularly, we explored the genetic and chemical differentiation level within and between populations of this insect. Our dataset revealed shallow intraspecific differentiation in M. consimilis. The similarity among the analyzed samples can probably be due to the geographical proximity where the colonies were sampled, and we argue that Paraná River did not contribute effectively as a historical barrier to this wasp.

EPIGENETIC TRANSGENERATIONAL ACTIONS OF ENVIRONMENTAL FACTORS IN DISEASE ETIOLOGY

PubMed Central

Skinner, Michael K.; Manikkam, Mohan; Guerrero-Bosagna, Carlos

2010-01-01

The ability of environmental factors to promote a phenotype or disease state not only in the individual exposed but also in subsequent progeny for multiple generations is termed transgenerational inheritance. The majority of environmental factors such as nutrition or toxicants such as endocrine disruptors do not promote genetic mutations or alterations in DNA sequence. In contrast, these factors have the capacity to alter the epigenome. Epimutations in the germ line that become permanently programmed can allow transmission of epigenetic transgenerational phenotypes. This review provides an overview of the epigenetics and biology of how environmental factors can promote transgenerational phenotypes and disease. PMID:20074974

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.

Review and International Recommendation of Methods for Typing Neisseria gonorrhoeae Isolates and Their Implications for Improved Knowledge of Gonococcal Epidemiology, Treatment, and Biology

PubMed Central

Unemo, Magnus; Dillon, Jo-Anne R.

2011-01-01

Summary: Gonorrhea, which may become untreatable due to multiple resistance to available antibiotics, remains a public health problem worldwide. Precise methods for typing Neisseria gonorrhoeae, together with epidemiological information, are crucial for an enhanced understanding regarding issues involving epidemiology, test of cure and contact tracing, identifying core groups and risk behaviors, and recommending effective antimicrobial treatment, control, and preventive measures. This review evaluates methods for typing N. gonorrhoeae isolates and recommends various methods for different situations. Phenotypic typing methods, as well as some now-outdated DNA-based methods, have limited usefulness in differentiating between strains of N. gonorrhoeae. Genotypic methods based on DNA sequencing are preferred, and the selection of the appropriate genotypic method should be guided by its performance characteristics and whether short-term epidemiology (microepidemiology) or long-term and/or global epidemiology (macroepidemiology) matters are being investigated. Currently, for microepidemiological questions, the best methods for fast, objective, portable, highly discriminatory, reproducible, typeable, and high-throughput characterization are N. gonorrhoeae multiantigen sequence typing (NG-MAST) or full- or extended-length porB gene sequencing. However, pulsed-field gel electrophoresis (PFGE) and Opa typing can be valuable in specific situations, i.e., extreme microepidemiology, despite their limitations. For macroepidemiological studies and phylogenetic studies, DNA sequencing of chromosomal housekeeping genes, such as multilocus sequence typing (MLST), provides a more nuanced understanding. PMID:21734242

The EMBL-EBI bioinformatics web and programmatic tools framework.

PubMed

Li, Weizhong; Cowley, Andrew; Uludag, Mahmut; Gur, Tamer; McWilliam, Hamish; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Lopez, Rodrigo

2015-07-01

Since 2009 the EMBL-EBI Job Dispatcher framework has provided free access to a range of mainstream sequence analysis applications. These include sequence similarity search services (https://www.ebi.ac.uk/Tools/sss/) such as BLAST, FASTA and PSI-Search, multiple sequence alignment tools (https://www.ebi.ac.uk/Tools/msa/) such as Clustal Omega, MAFFT and T-Coffee, and other sequence analysis tools (https://www.ebi.ac.uk/Tools/pfa/) such as InterProScan. Through these services users can search mainstream sequence databases such as ENA, UniProt and Ensembl Genomes, utilising a uniform web interface or systematically through Web Services interfaces (https://www.ebi.ac.uk/Tools/webservices/) using common programming languages, and obtain enriched results with novel visualisations. Integration with EBI Search (https://www.ebi.ac.uk/ebisearch/) and the dbfetch retrieval service (https://www.ebi.ac.uk/Tools/dbfetch/) further expands the usefulness of the framework. New tools and updates such as NCBI BLAST+, InterProScan 5 and PfamScan, new categories such as RNA analysis tools (https://www.ebi.ac.uk/Tools/rna/), new databases such as ENA non-coding, WormBase ParaSite, Pfam and Rfam, and new workflow methods, together with the retirement of depreciated services, ensure that the framework remains relevant to today's biological community. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Local Renyi entropic profiles of DNA sequences.

PubMed

Vinga, Susana; Almeida, Jonas S

2007-10-16

In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at http://kdbio.inesc-id.pt/~svinga/ep/. The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures.

Local Renyi entropic profiles of DNA sequences

PubMed Central

Vinga, Susana; Almeida, Jonas S

2007-01-01

Background In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. Results The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at . Conclusion The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures. PMID:17939871

Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models.

PubMed

Jacquin, Hugo; Gilson, Amy; Shakhnovich, Eugene; Cocco, Simona; Monasson, Rémi

2016-05-01

Inverse statistical approaches to determine protein structure and function from Multiple Sequence Alignments (MSA) are emerging as powerful tools in computational biology. However the underlying assumptions of the relationship between the inferred effective Potts Hamiltonian and real protein structure and energetics remain untested so far. Here we use lattice protein model (LP) to benchmark those inverse statistical approaches. We build MSA of highly stable sequences in target LP structures, and infer the effective pairwise Potts Hamiltonians from those MSA. We find that inferred Potts Hamiltonians reproduce many important aspects of 'true' LP structures and energetics. Careful analysis reveals that effective pairwise couplings in inferred Potts Hamiltonians depend not only on the energetics of the native structure but also on competing folds; in particular, the coupling values reflect both positive design (stabilization of native conformation) and negative design (destabilization of competing folds). In addition to providing detailed structural information, the inferred Potts models used as protein Hamiltonian for design of new sequences are able to generate with high probability completely new sequences with the desired folds, which is not possible using independent-site models. Those are remarkable results as the effective LP Hamiltonians used to generate MSA are not simple pairwise models due to the competition between the folds. Our findings elucidate the reasons for the success of inverse approaches to the modelling of proteins from sequence data, and their limitations.

The Human Transcript Database: A Catalogue of Full Length cDNA Inserts

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

Bouckk John; Michael McLeod; Kim Worley

1999-09-10

The BCM Search Launcher provided improved access to web-based sequence analysis services during the granting period and beyond. The Search Launcher web site grouped analysis procedures by function and provided default parameters that provided reasonable search results for most applications. For instance, most queries were automatically masked for repeat sequences prior to sequence database searches to avoid spurious matches. In addition to the web-based access and arrangements that were made using the functions easier, the BCM Search Launcher provided unique value-added applications like the BEAUTY sequence database search tool that combined information about protein domains and sequence database search resultsmore » to give an enhanced, more complete picture of the reliability and relative value of the information reported. This enhanced search tool made evaluating search results more straight-forward and consistent. Some of the favorite features of the web site are the sequence utilities and the batch client functionality that allows processing of multiple samples from the command line interface. One measure of the success of the BCM Search Launcher is the number of sites that have adopted the models first developed on the site. The graphic display on the BLAST search from the NCBI web site is one such outgrowth, as is the display of protein domain search results within BLAST search results, and the design of the Biology Workbench application. The logs of usage and comments from users confirm the great utility of this resource.« less

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications.

PubMed

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene-patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene-patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at http://www.patome.org/; the information is updated bimonthly.

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications

PubMed Central

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H.; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene–patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene–patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at ; the information is updated bimonthly. PMID:17085479

Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

PubMed

Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

2013-02-01

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

Single-Cell Sequencing of the Healthy and Diseased Heart Reveals Ckap4 as a New Modulator of Fibroblasts Activation.

PubMed

Gladka, Monika M; Molenaar, Bas; de Ruiter, Hesther; van der Elst, Stefan; Tsui, Hoyee; Versteeg, Danielle; Lacraz, Grègory P A; Huibers, Manon M H; van Oudenaarden, Alexander; van Rooij, Eva

2018-01-31

Background -Genome-wide transcriptome analysis has greatly advanced our understanding of the regulatory networks underlying basic cardiac biology and mechanisms driving disease. However, so far, the resolution of studying gene expression patterns in the adult heart has been limited to the level of extracts from whole tissues. The use of tissue homogenates inherently causes the loss of any information on cellular origin or cell type-specific changes in gene expression. Recent developments in RNA amplification strategies provide a unique opportunity to use small amounts of input RNA for genome-wide sequencing of single cells. Methods -Here, we present a method to obtain high quality RNA from digested cardiac tissue from adult mice for automated single-cell sequencing of both the healthy and diseased heart. Results -After optimization, we were able to perform single-cell sequencing on adult cardiac tissue under both homeostatic conditions and after ischemic injury. Clustering analysis based on differential gene expression unveiled known and novel markers of all main cardiac cell types. Based on differential gene expression we were also able to identify multiple subpopulations within a certain cell type. Furthermore, applying single-cell sequencing on both the healthy and the injured heart indicated the presence of disease-specific cell subpopulations. As such, we identified cytoskeleton associated protein 4 ( Ckap4 ) as a novel marker for activated fibroblasts that positively correlates with known myofibroblast markers in both mouse and human cardiac tissue. Ckap4 inhibition in activated fibroblasts treated with TGFβ triggered a greater increase in the expression of genes related to activated fibroblasts compared to control, suggesting a role of Ckap4 in modulating fibroblast activation in the injured heart. Conclusions -Single-cell sequencing on both the healthy and diseased adult heart allows us to study transcriptomic differences between cardiac cells, as well as cell type-specific changes in gene expression during cardiac disease. This new approach provides a wealth of novel insights into molecular changes that underlie the cellular processes relevant for cardiac biology and pathophysiology. Applying this technology could lead to the discovery of new therapeutic targets relevant for heart disease.

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

PubMed

Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2004-09-22

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

Achieving high confidence protein annotations in a sea of unknowns

NASA Astrophysics Data System (ADS)

Timmins-Schiffman, E.; May, D. H.; Noble, W. S.; Nunn, B. L.; Mikan, M.; Harvey, H. R.

2016-02-01

Increased sensitivity of mass spectrometry (MS) technology allows deep and broad insight into community functional analyses. Metaproteomics holds the promise to reveal functional responses of natural microbial communities, whereas metagenomics alone can only hint at potential functions. The complex datasets resulting from ocean MS have the potential to inform diverse realms of the biological, chemical, and physical ocean sciences, yet the extent of bacterial functional diversity and redundancy has not been fully explored. To take advantage of these impressive datasets, we need a clear bioinformatics pipeline for metaproteomics peptide identification and annotation with a database that can provide confident identifications. Researchers must consider whether it is sufficient to leverage the vast quantities of available ocean sequence data or if they must invest in site-specific metagenomic sequencing. We have sequenced, to our knowledge, the first western arctic metagenomes from the Bering Strait and the Chukchi Sea. We have addressed the long standing question: Is a metagenome required to accurately complete metaproteomics and assess the biological distribution of metabolic functions controlling nutrient acquisition in the ocean? Two different protein databases were constructed from 1) a site-specific metagenome and 2) subarctic/arctic groups available in NCBI's non-redundant database. Multiple proteomic search strategies were employed, against each individual database and against both databases combined, to determine the algorithm and approach that yielded the balance of high sensitivity and confident identification. Results yielded over 8200 confidently identified proteins. Our comparison of these results allows us to quantify the utility of investing resources in a metagenome versus using the constantly expanding and immediately available public databases for metaproteomic studies.

Thyroglobulin Represents a Novel Molecular Architecture of Vertebrates.

PubMed

Holzer, Guillaume; Morishita, Yoshiaki; Fini, Jean-Baptiste; Lorin, Thibault; Gillet, Benjamin; Hughes, Sandrine; Tohmé, Marie; Deléage, Gilbert; Demeneix, Barbara; Arvan, Peter; Laudet, Vincent

2016-08-05

Thyroid hormones modulate not only multiple functions in vertebrates (energy metabolism, central nervous system function, seasonal changes in physiology, and behavior) but also in some non-vertebrates where they control critical post-embryonic developmental transitions such as metamorphosis. Despite their obvious biological importance, the thyroid hormone precursor protein, thyroglobulin (Tg), has been experimentally investigated only in mammals. This may bias our view of how thyroid hormones are produced in other organisms. In this study we searched genomic databases and found Tg orthologs in all vertebrates including the sea lamprey (Petromyzon marinus). We cloned a full-size Tg coding sequence from western clawed frog (Xenopus tropicalis) and zebrafish (Danio rerio). Comparisons between the representative mammal, amphibian, teleost fish, and basal vertebrate indicate that all of the different domains of Tg, as well as Tg regional structure, are conserved throughout the vertebrates. Indeed, in Xenopus, zebrafish, and lamprey Tgs, key residues, including the hormonogenic tyrosines and the disulfide bond-forming cysteines critical for Tg function, are well conserved despite overall divergence of amino acid sequences. We uncovered upstream sequences that include start codons of zebrafish and Xenopus Tgs and experimentally proved that these are full-length secreted proteins, which are specifically recognized by antibodies against rat Tg. By contrast, we have not been able to find any orthologs of Tg among non-vertebrate species. Thus, Tg appears to be a novel protein elaborated as a single event at the base of vertebrates and virtually unchanged thereafter. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Extensive de novo mutation rate variation between individuals and across the genome of Chlamydomonas reinhardtii

PubMed Central

Ness, Rob W.; Morgan, Andrew D.; Vasanthakrishnan, Radhakrishnan B.; Colegrave, Nick; Keightley, Peter D.

2015-01-01

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and much of evolutionary biology. Directly studying spontaneous mutation has been difficult, however, because new mutations are rare. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. Here, we sequenced the genomes of 85 MA lines derived from six genetically diverse strains of the green alga Chlamydomonas reinhardtii. We identified 6843 new mutations, more than any other study of spontaneous mutation. We observed sevenfold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate approximately eightfold in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, with certain sequence motifs mutating at much higher rates, and clusters of multiple mutations occurring at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200 kbp. We generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level, and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome. PMID:26260971

Sounds of silence: synonymous nucleotides as a key to biological regulation and complexity

PubMed Central

Shabalina, Svetlana A.; Spiridonov, Nikolay A.; Kashina, Anna

2013-01-01

Messenger RNA is a key component of an intricate regulatory network of its own. It accommodates numerous nucleotide signals that overlap protein coding sequences and are responsible for multiple levels of regulation and generation of biological complexity. A wealth of structural and regulatory information, which mRNA carries in addition to the encoded amino acid sequence, raises the question of how these signals and overlapping codes are delineated along non-synonymous and synonymous positions in protein coding regions, especially in eukaryotes. Silent or synonymous codon positions, which do not determine amino acid sequences of the encoded proteins, define mRNA secondary structure and stability and affect the rate of translation, folding and post-translational modifications of nascent polypeptides. The RNA level selection is acting on synonymous sites in both prokaryotes and eukaryotes and is more common than previously thought. Selection pressure on the coding gene regions follows three-nucleotide periodic pattern of nucleotide base-pairing in mRNA, which is imposed by the genetic code. Synonymous positions of the coding regions have a higher level of hybridization potential relative to non-synonymous positions, and are multifunctional in their regulatory and structural roles. Recent experimental evidence and analysis of mRNA structure and interspecies conservation suggest that there is an evolutionary tradeoff between selective pressure acting at the RNA and protein levels. Here we provide a comprehensive overview of the studies that define the role of silent positions in regulating RNA structure and processing that exert downstream effects on proteins and their functions. PMID:23293005

Points of View: A Survey of Survey Courses--Are They Effective? A Unique Approach? Four Semesters of Biology Core Curriculum

ERIC Educational Resources Information Center

Batzli, Janet M.

2005-01-01

''Why four semesters? How does this track differ from the two-semester course sequence?'' These are the most common questions students have when they learn about the Biology Core Curriculum (Biocore), a unique four-semester honors biology sequence at University of Wisconsin-Madison (UW-Madison). Biocore was first taught at University of Wisconsin…

A cost-effective high-throughput metabarcoding approach powerful enough to genotype ~44 000 year-old rodent remains from Northern Africa.

PubMed

Guimaraes, S; Pruvost, M; Daligault, J; Stoetzel, E; Bennett, E A; Côté, N M-L; Nicolas, V; Lalis, A; Denys, C; Geigl, E-M; Grange, T

2017-05-01

We present a cost-effective metabarcoding approach, aMPlex Torrent, which relies on an improved multiplex PCR adapted to highly degraded DNA, combining barcoding and next-generation sequencing to simultaneously analyse many heterogeneous samples. We demonstrate the strength of these improvements by generating a phylochronology through the genotyping of ancient rodent remains from a Moroccan cave whose stratigraphy covers the last 120 000 years. Rodents are important for epidemiology, agronomy and ecological investigations and can act as bioindicators for human- and/or climate-induced environmental changes. Efficient and reliable genotyping of ancient rodent remains has the potential to deliver valuable phylogenetic and paleoecological information. The analysis of multiple ancient skeletal remains of very small size with poor DNA preservation, however, requires a sensitive high-throughput method to generate sufficient data. We show this approach to be particularly adapted at accessing this otherwise difficult taxonomic and genetic resource. As a highly scalable, lower cost and less labour-intensive alternative to targeted sequence capture approaches, we propose the aMPlex Torrent strategy to be a useful tool for the genetic analysis of multiple degraded samples in studies involving ecology, archaeology, conservation and evolutionary biology. © 2016 John Wiley & Sons Ltd.

Friedelin Synthase from Maytenus ilicifolia: Leucine 482 Plays an Essential Role in the Production of the Most Rearranged Pentacyclic Triterpene

PubMed Central

Souza-Moreira, Tatiana M.; Alves, Thaís B.; Pinheiro, Karina A.; Felippe, Lidiane G.; De Lima, Gustavo M. A.; Watanabe, Tatiana F.; Barbosa, Cristina C.; Santos, Vânia A. F. F. M.; Lopes, Norberto P.; Valentini, Sandro R.; Guido, Rafael V. C.; Furlan, Maysa; Zanelli, Cleslei F.

2016-01-01

Among the biologically active triterpenes, friedelin has the most-rearranged structure produced by the oxidosqualene cyclases and is the only one containing a cetonic group. In this study, we cloned and functionally characterized friedelin synthase and one cycloartenol synthase from Maytenus ilicifolia (Celastraceae). The complete coding sequences of these 2 genes were cloned from leaf mRNA, and their functions were characterized by heterologous expression in yeast. The cycloartenol synthase sequence is very similar to other known OSCs of this type (approximately 80% identity), although the M. ilicifolia friedelin synthase amino acid sequence is more related to β-amyrin synthases (65–74% identity), which is similar to the friedelin synthase cloned from Kalanchoe daigremontiana. Multiple sequence alignments demonstrated the presence of a leucine residue two positions upstream of the friedelin synthase Asp-Cys-Thr-Ala-Glu (DCTAE) active site motif, while the vast majority of OSCs identified so far have a valine or isoleucine residue at the same position. The substitution of the leucine residue with valine, threonine or isoleucine in M. ilicifolia friedelin synthase interfered with substrate recognition and lead to the production of different pentacyclic triterpenes. Hence, our data indicate a key role for the leucine residue in the structure and function of this oxidosqualene cyclase. PMID:27874020

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

Detecting Genomic Clustering of Risk Variants from Sequence Data: Cases vs. Controls

PubMed Central

Schaid, Daniel J.; Sinnwell, Jason P.; McDonnell, Shannon K.; Thibodeau, Stephen N.

2013-01-01

As the ability to measure dense genetic markers approaches the limit of the DNA sequence itself, taking advantage of possible clustering of genetic variants in, and around, a gene would benefit genetic association analyses, and likely provide biological insights. The greatest benefit might be realized when multiple rare variants cluster in a functional region. Several statistical tests have been developed, one of which is based on the popular Kulldorff scan statistic for spatial clustering of disease. We extended another popular spatial clustering method – Tango’s statistic – to genomic sequence data. An advantage of Tango’s method is that it is rapid to compute, and when single test statistic is computed, its distribution is well approximated by a scaled chi-square distribution, making computation of p-values very rapid. We compared the Type-I error rates and power of several clustering statistics, as well as the omnibus sequence kernel association test (SKAT). Although our version of Tango’s statistic, which we call “Kernel Distance” statistic, took approximately half the time to compute than the Kulldorff scan statistic, it had slightly less power than the scan statistic. Our results showed that the Ionita-Laza version of Kulldorff’s scan statistic had the greatest power over a range of clustering scenarios. PMID:23842950

Scaling up discovery of hidden diversity in fungi: impacts of barcoding approaches.

PubMed

Yahr, Rebecca; Schoch, Conrad L; Dentinger, Bryn T M

2016-09-05

The fungal kingdom is a hyperdiverse group of multicellular eukaryotes with profound impacts on human society and ecosystem function. The challenge of documenting and describing fungal diversity is exacerbated by their typically cryptic nature, their ability to produce seemingly unrelated morphologies from a single individual and their similarity in appearance to distantly related taxa. This multiplicity of hurdles resulted in the early adoption of DNA-based comparisons to study fungal diversity, including linking curated DNA sequence data to expertly identified voucher specimens. DNA-barcoding approaches in fungi were first applied in specimen-based studies for identification and discovery of taxonomic diversity, but are now widely deployed for community characterization based on sequencing of environmental samples. Collectively, fungal barcoding approaches have yielded important advances across biological scales and research applications, from taxonomic, ecological, industrial and health perspectives. A major outstanding issue is the growing problem of 'sequences without names' that are somewhat uncoupled from the traditional framework of fungal classification based on morphology and preserved specimens. This review summarizes some of the most significant impacts of fungal barcoding, its limitations, and progress towards the challenge of effective utilization of the exponentially growing volume of data gathered from high-throughput sequencing technologies.This article is part of the themed issue 'From DNA barcodes to biomes'. © 2016 The Authors.

Friedelin Synthase from Maytenus ilicifolia: Leucine 482 Plays an Essential Role in the Production of the Most Rearranged Pentacyclic Triterpene

NASA Astrophysics Data System (ADS)

Souza-Moreira, Tatiana M.; Alves, Thaís B.; Pinheiro, Karina A.; Felippe, Lidiane G.; de Lima, Gustavo M. A.; Watanabe, Tatiana F.; Barbosa, Cristina C.; Santos, Vânia A. F. F. M.; Lopes, Norberto P.; Valentini, Sandro R.; Guido, Rafael V. C.; Furlan, Maysa; Zanelli, Cleslei F.

2016-11-01

Among the biologically active triterpenes, friedelin has the most-rearranged structure produced by the oxidosqualene cyclases and is the only one containing a cetonic group. In this study, we cloned and functionally characterized friedelin synthase and one cycloartenol synthase from Maytenus ilicifolia (Celastraceae). The complete coding sequences of these 2 genes were cloned from leaf mRNA, and their functions were characterized by heterologous expression in yeast. The cycloartenol synthase sequence is very similar to other known OSCs of this type (approximately 80% identity), although the M. ilicifolia friedelin synthase amino acid sequence is more related to β-amyrin synthases (65-74% identity), which is similar to the friedelin synthase cloned from Kalanchoe daigremontiana. Multiple sequence alignments demonstrated the presence of a leucine residue two positions upstream of the friedelin synthase Asp-Cys-Thr-Ala-Glu (DCTAE) active site motif, while the vast majority of OSCs identified so far have a valine or isoleucine residue at the same position. The substitution of the leucine residue with valine, threonine or isoleucine in M. ilicifolia friedelin synthase interfered with substrate recognition and lead to the production of different pentacyclic triterpenes. Hence, our data indicate a key role for the leucine residue in the structure and function of this oxidosqualene cyclase.

ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules

PubMed Central

Ashkenazy, Haim; Abadi, Shiran; Martz, Eric; Chay, Ofer; Mayrose, Itay; Pupko, Tal; Ben-Tal, Nir

2016-01-01

The degree of evolutionary conservation of an amino acid in a protein or a nucleic acid in DNA/RNA reflects a balance between its natural tendency to mutate and the overall need to retain the structural integrity and function of the macromolecule. The ConSurf web server (http://consurf.tau.ac.il), established over 15 years ago, analyses the evolutionary pattern of the amino/nucleic acids of the macromolecule to reveal regions that are important for structure and/or function. Starting from a query sequence or structure, the server automatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogenetic tree that reflects their evolutionary relations. These data are then used, within a probabilistic framework, to estimate the evolutionary rates of each sequence position. Here we introduce several new features into ConSurf, including automatic selection of the best evolutionary model used to infer the rates, the ability to homology-model query proteins, prediction of the secondary structure of query RNA molecules from sequence, the ability to view the biological assembly of a query (in addition to the single chain), mapping of the conservation grades onto 2D RNA models and an advanced view of the phylogenetic tree that enables interactively rerunning ConSurf with the taxa of a sub-tree. PMID:27166375

Optimization of identity operation in NMR spectroscopy via genetic algorithm: Application to the TEDOR experiment

NASA Astrophysics Data System (ADS)

Manu, V. S.; Veglia, Gianluigi

2016-12-01

Identity operation in the form of π pulses is widely used in NMR spectroscopy. For an isolated single spin system, a sequence of even number of π pulses performs an identity operation, leaving the spin state essentially unaltered. For multi-spin systems, trains of π pulses with appropriate phases and time delays modulate the spin Hamiltonian to perform operations such as decoupling and recoupling. However, experimental imperfections often jeopardize the outcome, leading to severe losses in sensitivity. Here, we demonstrate that a newly designed Genetic Algorithm (GA) is able to optimize a train of π pulses, resulting in a robust identity operation. As proof-of-concept, we optimized the recoupling sequence in the transferred-echo double-resonance (TEDOR) pulse sequence, a key experiment in biological magic angle spinning (MAS) solid-state NMR for measuring multiple carbon-nitrogen distances. The GA modified TEDOR (GMO-TEDOR) experiment with improved recoupling efficiency results in a net gain of sensitivity up to 28% as tested on a uniformly 13C, 15N labeled microcrystalline ubiquitin sample. The robust identity operation achieved via GA paves the way for the optimization of several other pulse sequences used for both solid- and liquid-state NMR used for decoupling, recoupling, and relaxation experiments.

DNA Multiple Sequence Alignment Guided by Protein Domains: The MSA-PAD 2.0 Method.

PubMed

Balech, Bachir; Monaco, Alfonso; Perniola, Michele; Santamaria, Monica; Donvito, Giacinto; Vicario, Saverio; Maggi, Giorgio; Pesole, Graziano

2018-01-01

Multiple sequence alignment (MSA) is a fundamental component in many DNA sequence analyses including metagenomics studies and phylogeny inference. When guided by protein profiles, DNA multiple alignments assume a higher precision and robustness. Here we present details of the use of the upgraded version of MSA-PAD (2.0), which is a DNA multiple sequence alignment framework able to align DNA sequences coding for single/multiple protein domains guided by PFAM or user-defined annotations. MSA-PAD has two alignment strategies, called "Gene" and "Genome," accounting for coding domains order and genomic rearrangements, respectively. Novel options were added to the present version, where the MSA can be guided by protein profiles provided by the user. This allows MSA-PAD 2.0 to run faster and to add custom protein profiles sometimes not present in PFAM database according to the user's interest. MSA-PAD 2.0 is currently freely available as a Web application at https://recasgateway.cloud.ba.infn.it/ .

Sequence Variation of the tRNALeu Intron as a Marker for Genetic Diversity and Specificity of Symbiotic Cyanobacteria in Some Lichens

PubMed Central

Paulsrud, Per; Lindblad, Peter

1998-01-01

We examined the genetic diversity of Nostoc symbionts in some lichens by using the tRNALeu (UAA) intron as a genetic marker. The nucleotide sequence was analyzed in the context of the secondary structure of the transcribed intron. Cyanobacterial tRNALeu (UAA) introns were specifically amplified from freshly collected lichen samples without previous DNA extraction. The lichen species used in the present study were Nephroma arcticum, Peltigera aphthosa, P. membranacea, and P. canina. Introns with different sizes around 300 bp were consistently obtained. Multiple clones from single PCRs were screened by using their single-stranded conformational polymorphism pattern, and the nucleotide sequence was determined. No evidence for sample heterogenity was found. This implies that the symbiont in situ is not a diverse community of cyanobionts but, rather, one Nostoc strain. Furthermore, each lichen thallus contained only one intron type, indicating that each thallus is colonized only once or that there is a high degree of specificity. The same cyanobacterial intron sequence was also found in samples of one lichen species from different localities. In a phylogenetic analysis, the cyanobacterial lichen sequences grouped together with the sequences from two free-living Nostoc strains. The size differences in the intron were due to insertions and deletions in highly variable regions. The sequence data were used in discussions concerning specificity and biology of the lichen symbiosis. It is concluded that the tRNALeu (UAA) intron can be of great value when examining cyanobacterial diversity. PMID:9435083

The World Health Organization Global Programme on AIDS proposal for standardization of HIV sequence nomenclature. WHO Network for HIV Isolation and Characterization.

PubMed

Korber, B T; Osmanov, S; Esparza, J; Myers, G

1994-11-01

The World Health Organization Global Programme on AIDS (WHO/GPA) is conducting a large-scale collaborative study of human immunodeficiency virus type 1 (HIV-1) variation, based in four potential vaccine-trial site countries: Brazil, Rwanda, Thailand, and Uganda. Through the course of this study, it was crucial to keep track of certain attributes of the samples from which the viral nucleotide sequences were derived (e.g., country of origin and viral culture characterization), so that meaningful sequence comparisons could be made. Here we describe a system developed in the context of the WHO/GPA study that summarizes such critical attributes by representing them as standardized characters directly incorporated into sequence names. This nomenclature allows linkage of clinical, phenotypic, and geographic information with molecular data. We propose that other investigators involved in human immunodeficiency virus (HIV) nucleotide sequencing efforts adopt a similar standardized sequence nomenclature to facilitate cross-study sequence comparison. HIV sequence data are being generated at an ever-increasing rate; directly coupled to this increase is our deepening understanding of biological parameters that influence or result from sequence variability. A standardized sequence nomenclature that includes relevant biological information would enable researchers to better utilize the growing body of sequence data, and enhance their ability to interpret the biological implications of their own data through facilitating comparisons with previously published work.

Comparative analysis of response to selection with three insecticides in the dengue mosquito Aedes aegypti using mRNA sequencing

PubMed Central

2014-01-01

Background Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Such resistance can be the consequence of changes in proteins targeted by insecticides (target site mediated resistance), increased insecticide biodegradation (metabolic resistance), altered transport, sequestration or other mechanisms. As opposed to target site resistance, other mechanisms are far from being fully understood. Indeed, insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance. In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Biological materials consisted of a parental susceptible strain together with three child strains selected across multiple generations with three insecticides from different classes: the pyrethroid permethrin, the neonicotinoid imidacloprid and the carbamate propoxur. Results After ten generations, insecticide-selected strains showed elevated resistance levels to the insecticides used for selection. RNA-seq data allowed detecting over 13,000 transcripts, of which 413 were differentially transcribed in insecticide-selected strains as compared to the susceptible strain. Among them, a significant enrichment of transcripts encoding cuticle proteins, transporters and enzymes was observed. Polymorphism analysis revealed over 2500 SNPs showing > 50% allele frequency variations in insecticide-selected strains as compared to the susceptible strain, affecting over 1000 transcripts. Comparing gene transcription and polymorphism patterns revealed marked differences among strains. While imidacloprid selection was linked to the over transcription of many genes, permethrin selection was rather linked to polymorphism variations. Focusing on detoxification enzymes revealed that permethrin selection strongly affected the polymorphism of several transcripts encoding cytochrome P450 monooxygenases likely involved in insecticide biodegradation. Conclusions The present study confirmed the power of RNA-seq for identifying concomitantly quantitative and qualitative transcriptome changes associated with insecticide resistance in mosquitoes. Our results suggest that transcriptome modifications can be selected rapidly by insecticides and affect multiple biological functions. Previously neglected by molecular screenings, polymorphism variations of detoxification enzymes may play an important role in the adaptive response of mosquitoes to insecticides. PMID:24593293

Comparative analysis of response to selection with three insecticides in the dengue mosquito Aedes aegypti using mRNA sequencing.

PubMed

David, Jean-Philippe; Faucon, Frédéric; Chandor-Proust, Alexia; Poupardin, Rodolphe; Riaz, Muhammad Asam; Bonin, Aurélie; Navratil, Vincent; Reynaud, Stéphane

2014-03-05

Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Such resistance can be the consequence of changes in proteins targeted by insecticides (target site mediated resistance), increased insecticide biodegradation (metabolic resistance), altered transport, sequestration or other mechanisms. As opposed to target site resistance, other mechanisms are far from being fully understood. Indeed, insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance. In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Biological materials consisted of a parental susceptible strain together with three child strains selected across multiple generations with three insecticides from different classes: the pyrethroid permethrin, the neonicotinoid imidacloprid and the carbamate propoxur. After ten generations, insecticide-selected strains showed elevated resistance levels to the insecticides used for selection. RNA-seq data allowed detecting over 13,000 transcripts, of which 413 were differentially transcribed in insecticide-selected strains as compared to the susceptible strain. Among them, a significant enrichment of transcripts encoding cuticle proteins, transporters and enzymes was observed. Polymorphism analysis revealed over 2500 SNPs showing > 50% allele frequency variations in insecticide-selected strains as compared to the susceptible strain, affecting over 1000 transcripts. Comparing gene transcription and polymorphism patterns revealed marked differences among strains. While imidacloprid selection was linked to the over transcription of many genes, permethrin selection was rather linked to polymorphism variations. Focusing on detoxification enzymes revealed that permethrin selection strongly affected the polymorphism of several transcripts encoding cytochrome P450 monooxygenases likely involved in insecticide biodegradation. The present study confirmed the power of RNA-seq for identifying concomitantly quantitative and qualitative transcriptome changes associated with insecticide resistance in mosquitoes. Our results suggest that transcriptome modifications can be selected rapidly by insecticides and affect multiple biological functions. Previously neglected by molecular screenings, polymorphism variations of detoxification enzymes may play an important role in the adaptive response of mosquitoes to insecticides.

Phylogenetic estimates of diversification rate are affected by molecular rate variation.

PubMed

Duchêne, D A; Hua, X; Bromham, L

2017-10-01

Molecular phylogenies are increasingly being used to investigate the patterns and mechanisms of macroevolution. In particular, node heights in a phylogeny can be used to detect changes in rates of diversification over time. Such analyses rest on the assumption that node heights in a phylogeny represent the timing of diversification events, which in turn rests on the assumption that evolutionary time can be accurately predicted from DNA sequence divergence. But there are many influences on the rate of molecular evolution, which might also influence node heights in molecular phylogenies, and thus affect estimates of diversification rate. In particular, a growing number of studies have revealed an association between the net diversification rate estimated from phylogenies and the rate of molecular evolution. Such an association might, by influencing the relative position of node heights, systematically bias estimates of diversification time. We simulated the evolution of DNA sequences under several scenarios where rates of diversification and molecular evolution vary through time, including models where diversification and molecular evolutionary rates are linked. We show that commonly used methods, including metric-based, likelihood and Bayesian approaches, can have a low power to identify changes in diversification rate when molecular substitution rates vary. Furthermore, the association between the rates of speciation and molecular evolution rate can cause the signature of a slowdown or speedup in speciation rates to be lost or misidentified. These results suggest that the multiple sources of variation in molecular evolutionary rates need to be considered when inferring macroevolutionary processes from phylogenies. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Database Resources of the BIG Data Center in 2018.

PubMed

2018-01-04

The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cost-effectiveness of biological treatment sequences for fistulising Crohn’s disease across Europe

PubMed Central

Baji, Petra; Gulácsi, László; Brodszky, Valentin; Végh, Zsuzsanna; Danese, Silvio; Irving, Peter M; Peyrin-Biroulet, Laurent; Schreiber, Stefan; Rencz, Fanni; Lakatos, Péter L; Péntek, Márta

2017-01-01

Background In clinical practice, treatment sequences of biologicals are applied for active fistulising Crohn’s disease, however underlying health economic analyses are lacking. Objective The purpose of this study was to analyse the cost-effectiveness of different biological sequences including infliximab, biosimilar-infliximab, adalimumab and vedolizumab in nine European countries. Methods A Markov model was developed to compare treatment sequences of one, two and three biologicals from the payer’s perspective on a five-year time horizon. Data on effectiveness and health state utilities were obtained from the literature. Country-specific costs were considered. Calculations were performed with both official list prices and estimated real prices of biologicals. Results Biosimilar-infliximab is the most cost-effective treatment against standard care across the countries (with list prices: €34684–€72551/quality adjusted life year; with estimated real prices: €24364–€56086/quality adjusted life year). The most cost-effective two-agent sequence, except for Germany, is the biosimilar-infliximab–adalimumab therapy compared with single biosimilar-infliximab (with list prices: €58533–€133831/quality adjusted life year; with estimated prices: €45513–€105875/quality adjusted life year). The cost-effectiveness of the biosimilar-infliximab–adalimumab–vedolizumab three-agent sequence compared wit biosimilar-infliximab –adalimumab is €87214–€152901/quality adjusted life year. Conclusions The suggested first-choice biological treatment is biosimilar-infliximab. In case of treatment failure, switching to adalimumab then to vedolizumab provides meaningful additional health gains but at increased costs. Inter-country differences in cost-effectiveness are remarkable due to significant differences in costs. PMID:29511561

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

PubMed

Schmollinger, Martin; Nieselt, Kay; Kaufmann, Michael; Morgenstern, Burkhard

2004-09-09

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, M.S.

1998-08-18

A computer system for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments are improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area and sample sequences in another area on a display device. 27 figs.

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, Mark S.; Wang, Chunwei; Jevons, Luis C.; Bernhart, Derek H.; Lipshutz, Robert J.

2004-05-11

A computer system for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments are improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area and sample sequences in another area on a display device.

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, Mark S.

1998-08-18

A computer system for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments are improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area and sample sequences in another area on a display device.

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, Mark S.

2003-08-19

A computer system for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments may be improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area and sample sequences in another area on a display device.

eShadow: A tool for comparing closely related sequences

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

Ovcharenko, Ivan; Boffelli, Dario; Loots, Gabriela G.

2004-01-15

Primate sequence comparisons are difficult to interpret due to the high degree of sequence similarity shared between such closely related species. Recently, a novel method, phylogenetic shadowing, has been pioneered for predicting functional elements in the human genome through the analysis of multiple primate sequence alignments. We have expanded this theoretical approach to create a computational tool, eShadow, for the identification of elements under selective pressure in multiple sequence alignments of closely related genomes, such as in comparisons of human to primate or mouse to rat DNA. This tool integrates two different statistical methods and allows for the dynamic visualizationmore » of the resulting conservation profile. eShadow also includes a versatile optimization module capable of training the underlying Hidden Markov Model to differentially predict functional sequences. This module grants the tool high flexibility in the analysis of multiple sequence alignments and in comparing sequences with different divergence rates. Here, we describe the eShadow comparative tool and its potential uses for analyzing both multiple nucleotide and protein alignments to predict putative functional elements. The eShadow tool is publicly available at http://eshadow.dcode.org/« less

Multiple Access Interference Reduction Using Received Response Code Sequence for DS-CDMA UWB System

NASA Astrophysics Data System (ADS)

Toh, Keat Beng; Tachikawa, Shin'ichi

This paper proposes a combination of novel Received Response (RR) sequence at the transmitter and a Matched Filter-RAKE (MF-RAKE) combining scheme receiver system for the Direct Sequence-Code Division Multiple Access Ultra Wideband (DS-CDMA UWB) multipath channel model. This paper also demonstrates the effectiveness of the RR sequence in Multiple Access Interference (MAI) reduction for the DS-CDMA UWB system. It suggests that by using conventional binary code sequence such as the M sequence or the Gold sequence, there is a possibility of generating extra MAI in the UWB system. Therefore, it is quite difficult to collect the energy efficiently although the RAKE reception method is applied at the receiver. The main purpose of the proposed system is to overcome the performance degradation for UWB transmission due to the occurrence of MAI during multiple accessing in the DS-CDMA UWB system. The proposed system improves the system performance by improving the RAKE reception performance using the RR sequence which can reduce the MAI effect significantly. Simulation results verify that significant improvement can be obtained by the proposed system in the UWB multipath channel models.

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.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Comparative multi-goal tradeoffs in systems engineering of microbial metabolism

PubMed Central

2012-01-01

Background Metabolic engineering design methodology has evolved from using pathway-centric, random and empirical-based methods to using systems-wide, rational and integrated computational and experimental approaches. Persistent during these advances has been the desire to develop design strategies that address multiple simultaneous engineering goals, such as maximizing productivity, while minimizing raw material costs. Results Here, we use constraint-based modeling to systematically design multiple combinations of medium compositions and gene-deletion strains for three microorganisms (Escherichia coli, Saccharomyces cerevisiae, and Shewanella oneidensis) and six industrially important byproducts (acetate, D-lactate, hydrogen, ethanol, formate, and succinate). We evaluated over 435 million simulated conditions and 36 engineering metabolic traits, including product rates, costs, yields and purity. Conclusions The resulting metabolic phenotypes can be classified into dominant clusters (meta-phenotypes) for each organism. These meta-phenotypes illustrate global phenotypic variation and sensitivities, trade-offs associated with multiple engineering goals, and fundamental differences in organism-specific capabilities. Given the increasing number of sequenced genomes and corresponding stoichiometric models, we envisage that the proposed strategy could be extended to address a growing range of biological questions and engineering applications. PMID:23009214

Zika virus evolution and spread in the Americas

PubMed Central

Metsky, Hayden C.; Matranga, Christian B.; Wohl, Shirlee; Schaffner, Stephen F.; Freije, Catherine A.; Winnicki, Sarah M.; West, Kendra; Qu, James; Baniecki, Mary Lynn; Gladden-Young, Adrianne; Lin, Aaron E.; Tomkins-Tinch, Christopher H.; Ye, Simon H.; Park, Daniel J.; Luo, Cynthia Y.; Barnes, Kayla G.; Shah, Rickey R.; Chak, Bridget; Barbosa-Lima, Giselle; Delatorre, Edson; Vieira, Yasmine R.; Paul, Lauren M.; Tan, Amanda L.; Barcellona, Carolyn M.; Porcelli, Mario C.; Vasquez, Chalmers; Cannons, Andrew C.; Cone, Marshall R.; Hogan, Kelly N.; Kopp, Edgar W.; Anzinger, Joshua J.; Garcia, Kimberly F.; Parham, Leda A.; Gélvez Ramírez, Rosa M.; Miranda Montoya, Maria C.; Rojas, Diana P.; Brown, Catherine M.; Hennigan, Scott; Sabina, Brandon; Scotland, Sarah; Gangavarapu, Karthik; Grubaugh, Nathan D.; Oliveira, Glenn; Robles-Sikisaka, Refugio; Rambaut, Andrew; Gehrke, Lee; Smole, Sandra; Halloran, M. Elizabeth; Villar, Luis; Mattar, Salim; Lorenzana, Ivette; Cerbino-Neto, Jose; Valim, Clarissa; Degrave, Wim; Bozza, Patricia T.; Gnirke, Andreas; Andersen, Kristian G.; Isern, Sharon; Michael, Scott F.; Bozza, Fernando A.; Souza, Thiago M. L.; Bosch, Irene; Yozwiak, Nathan L.; MacInnis, Bronwyn L.; Sabeti, Pardis C.

2017-01-01

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention1,2, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests. PMID:28538734

The transcriptome of Lutzomyia longipalpis (Diptera: Psychodidae) male reproductive organs.

PubMed

Azevedo, Renata V D M; Dias, Denise B S; Bretãs, Jorge A C; Mazzoni, Camila J; Souza, Nataly A; Albano, Rodolpho M; Wagner, Glauber; Davila, Alberto M R; Peixoto, Alexandre A

2012-01-01

It has been suggested that genes involved in the reproductive biology of insect disease vectors are potential targets for future alternative methods of control. Little is known about the molecular biology of reproduction in phlebotomine sand flies and there is no information available concerning genes that are expressed in male reproductive organs of Lutzomyia longipalpis, the main vector of American visceral leishmaniasis and a species complex. We generated 2678 high quality ESTs ("Expressed Sequence Tags") of L. longipalpis male reproductive organs that were grouped in 1391 non-redundant sequences (1136 singlets and 255 clusters). BLAST analysis revealed that only 57% of these sequences share similarity with a L. longipalpis female EST database. Although no more than 36% of the non-redundant sequences showed similarity to protein sequences deposited in databases, more than half of them presented the best-match hits with mosquito genes. Gene ontology analysis identified subsets of genes involved in biological processes such as protein biosynthesis and DNA replication, which are probably associated with spermatogenesis. A number of non-redundant sequences were also identified as putative male reproductive gland proteins (mRGPs), also known as male accessory gland protein genes (Acps). The transcriptome analysis of L. longipalpis male reproductive organs is one step further in the study of the molecular basis of the reproductive biology of this important species complex. It has allowed the identification of genes potentially involved in spermatogenesis as well as putative mRGPs sequences, which have been studied in many insect species because of their effects on female post-mating behavior and physiology and their potential role in sexual selection and speciation. These data open a number of new avenues for further research in the molecular and evolutionary reproductive biology of sand flies.

The Transcriptome of Lutzomyia longipalpis (Diptera: Psychodidae) Male Reproductive Organs

PubMed Central

Bretãs, Jorge A. C.; Mazzoni, Camila J.; Souza, Nataly A.; Albano, Rodolpho M.; Wagner, Glauber; Davila, Alberto M. R.; Peixoto, Alexandre A.

2012-01-01

Background It has been suggested that genes involved in the reproductive biology of insect disease vectors are potential targets for future alternative methods of control. Little is known about the molecular biology of reproduction in phlebotomine sand flies and there is no information available concerning genes that are expressed in male reproductive organs of Lutzomyia longipalpis, the main vector of American visceral leishmaniasis and a species complex. Methods/Principal Findings We generated 2678 high quality ESTs (“Expressed Sequence Tags”) of L. longipalpis male reproductive organs that were grouped in 1391 non-redundant sequences (1136 singlets and 255 clusters). BLAST analysis revealed that only 57% of these sequences share similarity with a L. longipalpis female EST database. Although no more than 36% of the non-redundant sequences showed similarity to protein sequences deposited in databases, more than half of them presented the best-match hits with mosquito genes. Gene ontology analysis identified subsets of genes involved in biological processes such as protein biosynthesis and DNA replication, which are probably associated with spermatogenesis. A number of non-redundant sequences were also identified as putative male reproductive gland proteins (mRGPs), also known as male accessory gland protein genes (Acps). Conclusions The transcriptome analysis of L. longipalpis male reproductive organs is one step further in the study of the molecular basis of the reproductive biology of this important species complex. It has allowed the identification of genes potentially involved in spermatogenesis as well as putative mRGPs sequences, which have been studied in many insect species because of their effects on female post-mating behavior and physiology and their potential role in sexual selection and speciation. These data open a number of new avenues for further research in the molecular and evolutionary reproductive biology of sand flies. PMID:22496818

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

VHICA, a New Method to Discriminate between Vertical and Horizontal Transposon Transfer: Application to the Mariner Family within Drosophila.

PubMed

Wallau, Gabriel Luz; Capy, Pierre; Loreto, Elgion; Le Rouzic, Arnaud; Hua-Van, Aurélie

2016-04-01

Transposable elements (TEs) are genomic repeated sequences that display complex evolutionary patterns. They are usually inherited vertically, but can occasionally be transmitted between sexually independent species, through so-called horizontal transposon transfers (HTTs). Recurrent HTTs are supposed to be essential in life cycle of TEs, which are otherwise destined for eventual decay. HTTs also impact the host genome evolution. However, the extent of HTTs in eukaryotes is largely unknown, due to the lack of efficient, statistically supported methods that can be applied to multiple species sequence data sets. Here, we developed a new automated method available as a R package "vhica" that discriminates whether a given TE family was vertically or horizontally transferred, and potentially infers donor and receptor species. The method is well suited for TE sequences extracted from complete genomes, and applicable to multiple TEs and species at the same time. We first validated our method using Drosophila TE families with well-known evolutionary histories, displaying both HTTs and vertical transmission. We then tested 26 different lineages of mariner elements recently characterized in 20 Drosophila genomes, and found HTTs in 24 of them. Furthermore, several independent HTT events could often be detected within the same mariner lineage. The VHICA (Vertical and Horizontal Inheritance Consistence Analysis) method thus appears as a valuable tool to analyze the evolutionary history of TEs across a large range of species. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Quantifying selection in evolving populations using time-resolved genetic data

NASA Astrophysics Data System (ADS)

Illingworth, Christopher J. R.; Mustonen, Ville

2013-01-01

Methods which uncover the molecular basis of the adaptive evolution of a population address some important biological questions. For example, the problem of identifying genetic variants which underlie drug resistance, a question of importance for the treatment of pathogens, and of cancer, can be understood as a matter of inferring selection. One difficulty in the inference of variants under positive selection is the potential complexity of the underlying evolutionary dynamics, which may involve an interplay between several contributing processes, including mutation, recombination and genetic drift. A source of progress may be found in modern sequencing technologies, which confer an increasing ability to gather information about evolving populations, granting a window into these complex processes. One particularly interesting development is the ability to follow evolution as it happens, by whole-genome sequencing of an evolving population at multiple time points. We here discuss how to use time-resolved sequence data to draw inferences about the evolutionary dynamics of a population under study. We begin by reviewing our earlier analysis of a yeast selection experiment, in which we used a deterministic evolutionary framework to identify alleles under selection for heat tolerance, and to quantify the selection acting upon them. Considering further the use of advanced intercross lines to measure selection, we here extend this framework to cover scenarios of simultaneous recombination and selection, and of two driver alleles with multiple linked neutral, or passenger, alleles, where the driver pair evolves under an epistatic fitness landscape. We conclude by discussing the limitations of the approach presented and outlining future challenges for such methodologies.

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

Emery, Samantha J; Lacey, Ernest; Haynes, Paul A

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, Mark S.

1999-10-26

A computer system (1) for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments may be improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area (814) and sample sequences in another area (816) on a display device (3).

Computer-aided visualization and analysis system for sequence evaluation

DOEpatents

Chee, Mark S.

2001-06-05

A computer system (1) for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments may be improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area (814) and sample sequences in another area (816) on a display device (3).

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.

The 2010-2011 Canterbury Earthquake Sequence: Environmental effects, seismic triggering thresholds and geologic legacy

NASA Astrophysics Data System (ADS)

Quigley, Mark C.; Hughes, Matthew W.; Bradley, Brendon A.; van Ballegooy, Sjoerd; Reid, Catherine; Morgenroth, Justin; Horton, Travis; Duffy, Brendan; Pettinga, Jarg R.

2016-03-01

Seismic shaking and tectonic deformation during strong earthquakes can trigger widespread environmental effects. The severity and extent of a given effect relates to the characteristics of the causative earthquake and the intrinsic properties of the affected media. Documentation of earthquake environmental effects in well-instrumented, historical earthquakes can enable seismologic triggering thresholds to be estimated across a spectrum of geologic, topographic and hydrologic site conditions, and implemented into seismic hazard assessments, geotechnical engineering designs, palaeoseismic interpretations, and forecasts of the impacts of future earthquakes. The 2010-2011 Canterbury Earthquake Sequence (CES), including the moment magnitude (Mw) 7.1 Darfield earthquake and Mw 6.2, 6.0, 5.9, and 5.8 aftershocks, occurred on a suite of previously unidentified, primarily blind, active faults in the eastern South Island of New Zealand. The CES is one of Earth's best recorded historical earthquake sequences. The location of the CES proximal to and beneath a major urban centre enabled rapid and detailed collection of vast amounts of field, geospatial, geotechnical, hydrologic, biologic, and seismologic data, and allowed incremental and cumulative environmental responses to seismic forcing to be documented throughout a protracted earthquake sequence. The CES caused multiple instances of tectonic surface deformation (≥ 3 events), surface manifestations of liquefaction (≥ 11 events), lateral spreading (≥ 6 events), rockfall (≥ 6 events), cliff collapse (≥ 3 events), subsidence (≥ 4 events), and hydrological (10s of events) and biological shifts (≥ 3 events). The terrestrial area affected by strong shaking (e.g. peak ground acceleration (PGA) ≥ 0.1-0.3 g), and the maximum distances between earthquake rupture and environmental response (Rrup), both generally increased with increased earthquake Mw, but were also influenced by earthquake location and source characteristics. However, the severity of a given environmental response at any given site related predominantly to ground shaking characteristics (PGA, peak ground velocities) and site conditions (water table depth, soil type, geomorphic and topographic setting) rather than earthquake Mw. In most cases, the most severe liquefaction, rockfall, cliff collapse, subsidence, flooding, tree damage, and biologic habitat changes were triggered by proximal, moderate magnitude (Mw ≤ 6.2) earthquakes on blind faults. CES environmental effects will be incompletely preserved in the geologic record and variably diagnostic of spatial and temporal earthquake clustering. Liquefaction feeder dikes in areas of severe and recurrent liquefaction will provide the best preserved and potentially most diagnostic CES features. Rockfall talus deposits and boulders will be well preserved and potentially diagnostic of the strong intensity of CES shaking, but challenging to decipher in terms of single versus multiple events. Most other phenomena will be transient (e.g., distal groundwater responses), not uniquely diagnostic of earthquakes (e.g., flooding), or more ambiguous (e.g. biologic changes). Preliminary palaeoseismic investigations in the CES region indicate recurrence of liquefaction in susceptible sediments of 100 to 300 yr, recurrence of severe rockfall event(s) of ca. 6000 to 8000 yr, and recurrence of surface rupturing on the largest CES source fault of ca. 20,000 to 30,000 yr. These data highlight the importance of utilising multiple proxy datasets in palaeoearthquake studies. The severity of environmental effects triggered during the strongest CES earthquakes was as great as or equivalent to any historic or prehistoric effects recorded in the geologic record. We suggest that the shaking caused by rupture of local blind faults in the CES comprised a 'worst case' seismic shaking scenario for parts of the Christchurch urban area. Moderate Mw blind fault earthquakes may contribute the highest proportion of seismic hazard, be the most important drivers of landscape evolution, and dominate the palaeoseismic record in some locations on Earth, including locations distal from any identified active faults. A high scientific priority should be placed on improving the spatial extent and quality of 'off-fault' shaking records of strong earthquakes, particularly near major urban centres.

Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants.

PubMed

van Baren, Marijke J; Bachy, Charles; Reistetter, Emily Nahas; Purvine, Samuel O; Grimwood, Jane; Sudek, Sebastian; Yu, Hang; Poirier, Camille; Deerinck, Thomas J; Kuo, Alan; Grigoriev, Igor V; Wong, Chee-Hong; Smith, Richard D; Callister, Stephen J; Wei, Chia-Lin; Schmutz, Jeremy; Worden, Alexandra Z

2016-03-31

Prasinophytes are widespread marine green algae that are related to plants. Cellular abundance of the prasinophyte Micromonas has reportedly increased in the Arctic due to climate-induced changes. Thus, studies of these unicellular eukaryotes are important for marine ecology and for understanding Viridiplantae evolution and diversification. We generated evidence-based Micromonas gene models using proteomics and RNA-Seq to improve prasinophyte genomic resources. First, sequences of four chromosomes in the 22 Mb Micromonas pusilla (CCMP1545) genome were finished. Comparison with the finished 21 Mb genome of Micromonas commoda (RCC299; named herein) shows they share ≤8,141 of ~10,000 protein-encoding genes, depending on the analysis method. Unlike RCC299 and other sequenced eukaryotes, CCMP1545 has two abundant repetitive intron types and a high percent (26 %) GC splice donors. Micromonas has more genus-specific protein families (19 %) than other genome sequenced prasinophytes (11 %). Comparative analyses using predicted proteomes from other prasinophytes reveal proteins likely related to scale formation and ancestral photosynthesis. Our studies also indicate that peptidoglycan (PG) biosynthesis enzymes have been lost in multiple independent events in select prasinophytes and plants. However, CCMP1545, polar Micromonas CCMP2099 and prasinophytes from other classes retain the entire PG pathway, like moss and glaucophyte algae. Surprisingly, multiple vascular plants also have the PG pathway, except the Penicillin-Binding Protein, and share a unique bi-domain protein potentially associated with the pathway. Alongside Micromonas experiments using antibiotics that halt bacterial PG biosynthesis, the findings highlight unrecognized phylogenetic complexity in PG-pathway retention and implicate a role in chloroplast structure or division in several extant Viridiplantae lineages. Extensive differences in gene loss and architecture between related prasinophytes underscore their divergence. PG biosynthesis genes from the cyanobacterial endosymbiont that became the plastid, have been selectively retained in multiple plants and algae, implying a biological function. Our studies provide robust genomic resources for emerging model algae, advancing knowledge of marine phytoplankton and plant evolution.

Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment

PubMed Central

Kam, Alfred; Kwak, Daniel; Leung, Clarence; Wu, Chu; Zarour, Eleyine; Sarmenta, Luis; Blanchette, Mathieu; Waldispühl, Jérôme

2012-01-01

Background Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server. Methodology/Principal Findings We introduce Phylo, a human-based computing framework applying “crowd sourcing” techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. Conclusions/Significance We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of “human-brain peta-flops” of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca. PMID:22412834

BM-Map: Bayesian Mapping of Multireads for Next-Generation Sequencing Data

PubMed Central

Ji, Yuan; Xu, Yanxun; Zhang, Qiong; Tsui, Kam-Wah; Yuan, Yuan; Norris, Clift; Liang, Shoudan; Liang, Han

2011-01-01

Summary Next-generation sequencing (NGS) technology generates millions of short reads, which provide valuable information for various aspects of cellular activities and biological functions. A key step in NGS applications (e.g., RNA-Seq) is to map short reads to correct genomic locations within the source genome. While most reads are mapped to a unique location, a significant proportion of reads align to multiple genomic locations with equal or similar numbers of mismatches; these are called multireads. The ambiguity in mapping the multireads may lead to bias in downstream analyses. Currently, most practitioners discard the multireads in their analysis, resulting in a loss of valuable information, especially for the genes with similar sequences. To refine the read mapping, we develop a Bayesian model that computes the posterior probability of mapping a multiread to each competing location. The probabilities are used for downstream analyses, such as the quantification of gene expression. We show through simulation studies and RNA-Seq analysis of real life data that the Bayesian method yields better mapping than the current leading methods. We provide a C++ program for downloading that is being packaged into a user-friendly software. PMID:21517792

Residue selective 15N CEST and CPMG experiments for studies of millisecond timescale protein dynamics.

PubMed

Niu, Xiaogang; Ding, Jienv; Zhang, Wenbo; Li, Qianwen; Hu, Yunfei; Jin, Changwen

2018-06-01

Proteins are intrinsically dynamic molecules and undergo exchanges among multiple conformations to perform biological functions. The CPMG relaxation dispersion and CEST experiments are two important solution NMR techniques for characterizing the conformational exchange processes on the millisecond timescale. Traditional pseudo 3D 15 N CEST and CPMG experiments have certain limitations in their applications. For example, both experiments have low sensitivity for broadened resonances, and the process of optimizing sample conditions and experimental parameters are often time consuming. To overcome these limitations, we herein present a new set of residue selective 15 N CEST and CPMG pulse sequences by employing the Hartmann-Hahn cross-polarization transfer of magnetization in both 1D and 2D schemes. Combined with frequency labeling in the indirect dimension using only a small number of increments, the pulse sequences in the 2D scheme can be applied on resonances in overlapped regions of the 1 H- 15 N HSQC spectrum. The pulse sequences were further applied on several proteins, demonstrating their advantages over the traditional CEST and CPMG experiments under specific circumstances. Copyright © 2018 Elsevier Inc. All rights reserved.

Spectrum of mutations in leiomyosarcomas identified by clinical targeted next-generation sequencing.

PubMed

Lee, Paul J; Yoo, Naomi S; Hagemann, Ian S; Pfeifer, John D; Cottrell, Catherine E; Abel, Haley J; Duncavage, Eric J

2017-02-01

Recurrent genomic mutations in uterine and non-uterine leiomyosarcomas have not been well established. Using a next generation sequencing (NGS) panel of common cancer-associated genes, 25 leiomyosarcomas arising from multiple sites were examined to explore genetic alterations, including single nucleotide variants (SNV), small insertions/deletions (indels), and copy number alterations (CNA). Sequencing showed 86 non-synonymous, coding region somatic variants within 151 gene targets in 21 cases, with a mean of 4.1 variants per case; 4 cases had no putative mutations in the panel of genes assayed. The most frequently altered genes were TP53 (36%), ATM and ATRX (16%), and EGFR and RB1 (12%). CNA were identified in 85% of cases, with the most frequent copy number losses observed in chromosomes 10 and 13 including PTEN and RB1; the most frequent gains were seen in chromosomes 7 and 17. Our data show that deletions in canonical cancer-related genes are common in leiomyosarcomas. Further, the spectrum of gene mutations observed shows that defects in DNA repair and chromosomal maintenance are central to the biology of leiomyosarcomas, and that activating mutations observed in other common cancer types are rare in leiomyosarcomas. Copyright © 2017 Elsevier Inc. All rights reserved.

Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment

PubMed Central

2011-01-01

Background Many Bioinformatics studies begin with a multiple sequence alignment as the foundation for their research. This is because multiple sequence alignment can be a useful technique for studying molecular evolution and analyzing sequence structure relationships. Results In this paper, we have proposed a Vertical Decomposition with Genetic Algorithm (VDGA) for Multiple Sequence Alignment (MSA). In VDGA, we divide the sequences vertically into two or more subsequences, and then solve them individually using a guide tree approach. Finally, we combine all the subsequences to generate a new multiple sequence alignment. This technique is applied on the solutions of the initial generation and of each child generation within VDGA. We have used two mechanisms to generate an initial population in this research: the first mechanism is to generate guide trees with randomly selected sequences and the second is shuffling the sequences inside such trees. Two different genetic operators have been implemented with VDGA. To test the performance of our algorithm, we have compared it with existing well-known methods, namely PRRP, CLUSTALX, DIALIGN, HMMT, SB_PIMA, ML_PIMA, MULTALIGN, and PILEUP8, and also other methods, based on Genetic Algorithms (GA), such as SAGA, MSA-GA and RBT-GA, by solving a number of benchmark datasets from BAliBase 2.0. Conclusions The experimental results showed that the VDGA with three vertical divisions was the most successful variant for most of the test cases in comparison to other divisions considered with VDGA. The experimental results also confirmed that VDGA outperformed the other methods considered in this research. PMID:21867510

Analysis of plant microbe interactions in the era of next generation sequencing technologies

PubMed Central

Knief, Claudia

2014-01-01

Next generation sequencing (NGS) technologies have impressively accelerated research in biological science during the last years by enabling the production of large volumes of sequence data to a drastically lower price per base, compared to traditional sequencing methods. The recent and ongoing developments in the field allow addressing research questions in plant-microbe biology that were not conceivable just a few years ago. The present review provides an overview of NGS technologies and their usefulness for the analysis of microorganisms that live in association with plants. Possible limitations of the different sequencing systems, in particular sources of errors and bias, are critically discussed and methods are disclosed that help to overcome these shortcomings. A focus will be on the application of NGS methods in metagenomic studies, including the analysis of microbial communities by amplicon sequencing, which can be considered as a targeted metagenomic approach. Different applications of NGS technologies are exemplified by selected research articles that address the biology of the plant associated microbiota to demonstrate the worth of the new methods. PMID:24904612

Novel genomic findings in multiple myeloma identified through routine diagnostic sequencing.

PubMed

Ryland, Georgina L; Jones, Kate; Chin, Melody; Markham, John; Aydogan, Elle; Kankanige, Yamuna; Caruso, Marisa; Guinto, Jerick; Dickinson, Michael; Prince, H Miles; Yong, Kwee; Blombery, Piers

2018-05-14

Multiple myeloma is a genomically complex haematological malignancy with many genomic alterations recognised as important in diagnosis, prognosis and therapeutic decision making. Here, we provide a summary of genomic findings identified through routine diagnostic next-generation sequencing at our centre. A cohort of 86 patients with multiple myeloma underwent diagnostic sequencing using a custom hybridisation-based panel targeting 104 genes. Sequence variants, genome-wide copy number changes and structural rearrangements were detected using an inhouse-developed bioinformatics pipeline. At least one mutation was found in 69 (80%) patients. Frequently mutated genes included TP53 (36%), KRAS (22.1%), NRAS (15.1%), FAM46C/DIS3 (8.1%) and TET2/FGFR3 (5.8%), including multiple mutations not previously described in myeloma. Importantly we observed TP53 mutations in the absence of a 17 p deletion in 8% of the cohort, highlighting the need for sequencing-based assessment in addition to cytogenetics to identify these high-risk patients. Multiple novel copy number changes and immunoglobulin heavy chain translocations are also discussed. Our results demonstrate that many clinically relevant genomic findings remain in multiple myeloma which have not yet been identified through large-scale sequencing efforts, and provide important mechanistic insights into plasma cell pathobiology. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Function-Based Algorithms for Biological Sequences

ERIC Educational Resources Information Center

Mohanty, Pragyan Sheela P.

2015-01-01

Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…

Finding the missing honey bee genes: lessons learned from a genome upgrade

USDA-ARS?s Scientific Manuscript database

The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. ...

Normal and compound poisson approximations for pattern occurrences in NGS reads.

PubMed

Zhai, Zhiyuan; Reinert, Gesine; Song, Kai; Waterman, Michael S; Luan, Yihui; Sun, Fengzhu

2012-06-01

Next generation sequencing (NGS) technologies are now widely used in many biological studies. In NGS, sequence reads are randomly sampled from the genome sequence of interest. Most computational approaches for NGS data first map the reads to the genome and then analyze the data based on the mapped reads. Since many organisms have unknown genome sequences and many reads cannot be uniquely mapped to the genomes even if the genome sequences are known, alternative analytical methods are needed for the study of NGS data. Here we suggest using word patterns to analyze NGS data. Word pattern counting (the study of the probabilistic distribution of the number of occurrences of word patterns in one or multiple long sequences) has played an important role in molecular sequence analysis. However, no studies are available on the distribution of the number of occurrences of word patterns in NGS reads. In this article, we build probabilistic models for the background sequence and the sampling process of the sequence reads from the genome. Based on the models, we provide normal and compound Poisson approximations for the number of occurrences of word patterns from the sequence reads, with bounds on the approximation error. The main challenge is to consider the randomness in generating the long background sequence, as well as in the sampling of the reads using NGS. We show the accuracy of these approximations under a variety of conditions for different patterns with various characteristics. Under realistic assumptions, the compound Poisson approximation seems to outperform the normal approximation in most situations. These approximate distributions can be used to evaluate the statistical significance of the occurrence of patterns from NGS data. The theory and the computational algorithm for calculating the approximate distributions are then used to analyze ChIP-Seq data using transcription factor GABP. Software is available online (www-rcf.usc.edu/∼fsun/Programs/NGS_motif_power/NGS_motif_power.html). In addition, Supplementary Material can be found online (www.liebertonline.com/cmb).

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

PubMed

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

2016-11-01

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

MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets

PubMed Central

Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

2016-01-01

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder. PMID:27684958

MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets.

PubMed

Jurtz, Vanessa Isabell; Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

NASA Astrophysics Data System (ADS)

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A. A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-12-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool.

Synonymous Mutations at the Beginning of the Influenza A Virus Hemagglutinin Gene Impact Experimental Fitness.

PubMed

Canale, Aneth S; Venev, Sergey V; Whitfield, Troy W; Caffrey, Daniel R; Marasco, Wayne A; Schiffer, Celia A; Kowalik, Timothy F; Jensen, Jeffrey D; Finberg, Robert W; Zeldovich, Konstantin B; Wang, Jennifer P; Bolon, Daniel N A

2018-04-13

The fitness effects of synonymous mutations can provide insights into biological and evolutionary mechanisms. We analyzed the experimental fitness effects of all single-nucleotide mutations, including synonymous substitutions, at the beginning of the influenza A virus hemagglutinin (HA) gene. Many synonymous substitutions were deleterious both in bulk competition and for individually isolated clones. Investigating protein and RNA levels of a subset of individually expressed HA variants revealed that multiple biochemical properties contribute to the observed experimental fitness effects. Our results indicate that a structural element in the HA segment viral RNA may influence fitness. Examination of naturally evolved sequences in human hosts indicates a preference for the unfolded state of this structural element compared to that found in swine hosts. Our overall results reveal that synonymous mutations may have greater fitness consequences than indicated by simple models of sequence conservation, and we discuss the implications of this finding for commonly used evolutionary tests and analyses. Copyright © 2018. Published by Elsevier Ltd.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

PubMed Central

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A.A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-01-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool. PMID:27995928