Method for rapid base sequencing in DNA and RNA with two base labeling

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Posner, R.G.; Marrone, B.L.; Hammond, M.L.; Simpson, D.J.

1995-04-11

A method is described for rapid-base sequencing in DNA and RNA with two-base labeling and employing fluorescent detection of single molecules at two wavelengths. Bases modified to accept fluorescent labels are used to replicate a single DNA or RNA strand to be sequenced. The bases are then sequentially cleaved from the replicated strand, excited with a chosen spectrum of electromagnetic radiation, and the fluorescence from individual, tagged bases detected in the order of cleavage from the strand. 4 figures.

Method for rapid base sequencing in DNA and RNA with two base labeling

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Posner, Richard G.; Marrone, Babetta L.; Hammond, Mark L.; Simpson, Daniel J.

1995-01-01

Method for rapid-base sequencing in DNA and RNA with two-base labeling and employing fluorescent detection of single molecules at two wavelengths. Bases modified to accept fluorescent labels are used to replicate a single DNA or RNA strand to be sequenced. The bases are then sequentially cleaved from the replicated strand, excited with a chosen spectrum of electromagnetic radiation, and the fluorescence from individual, tagged bases detected in the order of cleavage from the strand.

Googling DNA sequences on the World Wide Web.

PubMed

Hajibabaei, Mehrdad; Singer, Gregory A C

2009-11-10

New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available for analyzing DNA sequence information, conventional web-based tools have not been utilized for bioinformatics applications. We have developed a novel algorithm and implemented it for searching species-specific genomic sequences, DNA barcodes, by using popular web-based methods such as Google. We developed an alignment independent character based algorithm based on dividing a sequence library (DNA barcodes) and query sequence to words. The actual search is conducted by conventional search tools such as freely available Google Desktop Search. We implemented our algorithm in two exemplar packages. We developed pre and post-processing software to provide customized input and output services, respectively. Our analysis of all publicly available DNA barcode sequences shows a high accuracy as well as rapid results. Our method makes use of conventional web-based technologies for specialized genetic data. It provides a robust and efficient solution for sequence search on the web. The integration of our search method for large-scale sequence libraries such as DNA barcodes provides an excellent web-based tool for accessing this information and linking it to other available categories of information on the web.

DNA Base-Calling from a Nanopore Using a Viterbi Algorithm

PubMed Central

Timp, Winston; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Nanopore-based DNA sequencing is the most promising third-generation sequencing method. It has superior read length, speed, and sample requirements compared with state-of-the-art second-generation methods. However, base-calling still presents substantial difficulty because the resolution of the technique is limited compared with the measured signal/noise ratio. Here we demonstrate a method to decode 3-bp-resolution nanopore electrical measurements into a DNA sequence using a Hidden Markov model. This method shows tremendous potential for accuracy (∼98%), even with a poor signal/noise ratio. PMID:22677395

Cluster-Based Multipolling Sequencing Algorithm for Collecting RFID Data in Wireless LANs

NASA Astrophysics Data System (ADS)

Choi, Woo-Yong; Chatterjee, Mainak

2015-03-01

With the growing use of RFID (Radio Frequency Identification), it is becoming important to devise ways to read RFID tags in real time. Access points (APs) of IEEE 802.11-based wireless Local Area Networks (LANs) are being integrated with RFID networks that can efficiently collect real-time RFID data. Several schemes, such as multipolling methods based on the dynamic search algorithm and random sequencing, have been proposed. However, as the number of RFID readers associated with an AP increases, it becomes difficult for the dynamic search algorithm to derive the multipolling sequence in real time. Though multipolling methods can eliminate the polling overhead, we still need to enhance the performance of the multipolling methods based on random sequencing. To that extent, we propose a real-time cluster-based multipolling sequencing algorithm that drastically eliminates more than 90% of the polling overhead, particularly so when the dynamic search algorithm fails to derive the multipolling sequence in real time.

Base-Calling Algorithm with Vocabulary (BCV) Method for Analyzing Population Sequencing Chromatograms

PubMed Central

Fantin, Yuri S.; Neverov, Alexey D.; Favorov, Alexander V.; Alvarez-Figueroa, Maria V.; Braslavskaya, Svetlana I.; Gordukova, Maria A.; Karandashova, Inga V.; Kuleshov, Konstantin V.; Myznikova, Anna I.; Polishchuk, Maya S.; Reshetov, Denis A.; Voiciehovskaya, Yana A.; Mironov, Andrei A.; Chulanov, Vladimir P.

2013-01-01

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3–14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing. PMID:23382983

SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform.

PubMed

Lin, Jie; Wei, Jing; Adjeroh, Donald; Jiang, Bing-Hua; Jiang, Yue

2018-05-02

Alignment-free sequence similarity analysis methods often lead to significant savings in computational time over alignment-based counterparts. A new alignment-free sequence similarity analysis method, called SSAW is proposed. SSAW stands for Sequence Similarity Analysis using the Stationary Discrete Wavelet Transform (SDWT). It extracts k-mers from a sequence, then maps each k-mer to a complex number field. Then, the series of complex numbers formed are transformed into feature vectors using the stationary discrete wavelet transform. After these steps, the original sequence is turned into a feature vector with numeric values, which can then be used for clustering and/or classification. Using two different types of applications, namely, clustering and classification, we compared SSAW against the the-state-of-the-art alignment free sequence analysis methods. SSAW demonstrates competitive or superior performance in terms of standard indicators, such as accuracy, F-score, precision, and recall. The running time was significantly better in most cases. These make SSAW a suitable method for sequence analysis, especially, given the rapidly increasing volumes of sequence data required by most modern applications.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

Towards predicting the encoding capability of MR fingerprinting sequences.

PubMed

Sommer, K; Amthor, T; Doneva, M; Koken, P; Meineke, J; Börnert, P

2017-09-01

Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance fingerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To find such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different flip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of an EMS-induced causal mutation in a gene required for boron-mediated root development by low-coverage genome re-sequencing in Arabidopsis

PubMed Central

Tabata, Ryo; Kamiya, Takehiro; Shigenobu, Shuji; Yamaguchi, Katsushi; Yamada, Masashi; Hasebe, Mitsuyasu; Fujiwara, Toru; Sawa, Shinichiro

2013-01-01

Next-generation sequencing (NGS) technologies enable the rapid production of an enormous quantity of sequence data. These powerful new technologies allow the identification of mutations by whole-genome sequencing. However, most reported NGS-based mapping methods, which are based on bulked segregant analysis, are costly and laborious. To address these limitations, we designed a versatile NGS-based mapping method that consists of a combination of low- to medium-coverage multiplex SOLiD (Sequencing by Oligonucleotide Ligation and Detection) and classical genetic rough mapping. Using only low to medium coverage reduces the SOLiD sequencing costs and, since just 10 to 20 mutant F2 plants are required for rough mapping, the operation is simple enough to handle in a laboratory with limited space and funding. As a proof of principle, we successfully applied this method to identify the CTR1, which is involved in boron-mediated root development, from among a population of high boron requiring Arabidopsis thaliana mutants. Our work demonstrates that this NGS-based mapping method is a moderately priced and versatile method that can readily be applied to other model organisms. PMID:23104114

Structure-preserving interpolation of temporal and spatial image sequences using an optical flow-based method.

PubMed

Ehrhardt, J; Säring, D; Handels, H

2007-01-01

Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. The behavior and capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

An Optimal Seed Based Compression Algorithm for DNA Sequences

PubMed Central

Gopalakrishnan, Gopakumar; Karunakaran, Muralikrishnan

2016-01-01

This paper proposes a seed based lossless compression algorithm to compress a DNA sequence which uses a substitution method that is similar to the LempelZiv compression scheme. The proposed method exploits the repetition structures that are inherent in DNA sequences by creating an offline dictionary which contains all such repeats along with the details of mismatches. By ensuring that only promising mismatches are allowed, the method achieves a compression ratio that is at par or better than the existing lossless DNA sequence compression algorithms. PMID:27555868

DNA base-calling from a nanopore using a Viterbi algorithm.

PubMed

Timp, Winston; Comer, Jeffrey; Aksimentiev, Aleksei

2012-05-16

Nanopore-based DNA sequencing is the most promising third-generation sequencing method. It has superior read length, speed, and sample requirements compared with state-of-the-art second-generation methods. However, base-calling still presents substantial difficulty because the resolution of the technique is limited compared with the measured signal/noise ratio. Here we demonstrate a method to decode 3-bp-resolution nanopore electrical measurements into a DNA sequence using a Hidden Markov model. This method shows tremendous potential for accuracy (~98%), even with a poor signal/noise ratio. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

PubMed Central

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-01-01

Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465

SELEX-Based Screening of Exosome-Tropic RNA.

PubMed

Yamashita, Takuma; Shinotsuka, Haruka; Takahashi, Yuki; Kato, Kana; Nishikawa, Makiya; Takakura, Yoshinobu

2017-01-01

Cell-derived nanosized vesicles or exosomes are expected to become delivery carriers for functional RNAs, such as small interfering RNA (siRNA). A method to efficiently load functional RNAs into exosomes is required for the development of exosome-based delivery carriers of functional RNAs. However, there is no method to find exosome-tropic exogenous RNA sequences. In this study, we used a systematic evolution of ligands by exponential enrichment (SELEX) method to screen exosome-tropic RNAs that can be used to load functional RNAs into exosomes by conjugation. Pooled single stranded 80-base RNAs, each of which contains a randomized 40-base sequence, were transfected into B16-BL6 murine melanoma cells and exosomes were collected from the cells. RNAs extracted from the exosomes were subjected to next round of SELEX. Cloning and sequencing of RNAs in SELEX-screened RNA pools showed that 29 of 56 clones had a typical RNA sequence. The sequence found by SELEX was enriched in exosomes after transfection to B16-BL6 cells. The results show that the SELEX-based method can be used for screening of exosome-tropic RNAs.

Exploring the sequence-structure protein landscape in the glycosyltransferase family

PubMed Central

Zhang, Ziding; Kochhar, Sunil; Grigorov, Martin

2003-01-01

To understand the molecular basis of glycosyltransferases’ (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family. PMID:14500887

PASTA for Proteins.

PubMed

Collins, Kodi; Warnow, Tandy

2018-06-19

PASTA is a multiple sequence method that uses divide-and-conquer plus iteration to enable base alignment methods to scale with high accuracy to large sequence datasets. By default, PASTA included MAFFT L-INS-i; our new extension of PASTA enables the use of MAFFT G-INS-i, MAFFT Homologs, CONTRAlign, and ProbCons. We analyzed the performance of each base method and PASTA using these base methods on 224 datasets from BAliBASE 4 with at least 50 sequences. We show that PASTA enables the most accurate base methods to scale to larger datasets at reduced computational effort, and generally improves alignment and tree accuracy on the largest BAliBASE datasets. PASTA is available at https://github.com/kodicollins/pasta and has also been integrated into the original PASTA repository at https://github.com/smirarab/pasta. Supplementary data are available at Bioinformatics online.

Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns

PubMed Central

2013-01-01

Background It is well known that the search for homologous RNAs is more effective if both sequence and structure information is incorporated into the search. However, current tools for searching with RNA sequence-structure patterns cannot fully handle mutations occurring on both these levels or are simply not fast enough for searching large sequence databases because of the high computational costs of the underlying sequence-structure alignment problem. Results We present new fast index-based and online algorithms for approximate matching of RNA sequence-structure patterns supporting a full set of edit operations on single bases and base pairs. Our methods efficiently compute semi-global alignments of structural RNA patterns and substrings of the target sequence whose costs satisfy a user-defined sequence-structure edit distance threshold. For this purpose, we introduce a new computing scheme to optimally reuse the entries of the required dynamic programming matrices for all substrings and combine it with a technique for avoiding the alignment computation of non-matching substrings. Our new index-based methods exploit suffix arrays preprocessed from the target database and achieve running times that are sublinear in the size of the searched sequences. To support the description of RNA molecules that fold into complex secondary structures with multiple ordered sequence-structure patterns, we use fast algorithms for the local or global chaining of approximate sequence-structure pattern matches. The chaining step removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our improved online algorithm is faster than the best previous method by up to factor 45. Our best new index-based algorithm achieves a speedup of factor 560. Conclusions The presented methods achieve considerable speedups compared to the best previous method. This, together with the expected sublinear running time of the presented index-based algorithms, allows for the first time approximate matching of RNA sequence-structure patterns in large sequence databases. Beyond the algorithmic contributions, we provide with RaligNAtor a robust and well documented open-source software package implementing the algorithms presented in this manuscript. The RaligNAtor software is available at http://www.zbh.uni-hamburg.de/ralignator. PMID:23865810

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

PubMed Central

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

A simple method for semi-random DNA amplicon fragmentation using the methylation-dependent restriction enzyme MspJI.

PubMed

Shinozuka, Hiroshi; Cogan, Noel O I; Shinozuka, Maiko; Marshall, Alexis; Kay, Pippa; Lin, Yi-Han; Spangenberg, German C; Forster, John W

2015-04-11

Fragmentation at random nucleotide locations is an essential process for preparation of DNA libraries to be used on massively parallel short-read DNA sequencing platforms. Although instruments for physical shearing, such as the Covaris S2 focused-ultrasonicator system, and products for enzymatic shearing, such as the Nextera technology and NEBNext dsDNA Fragmentase kit, are commercially available, a simple and inexpensive method is desirable for high-throughput sequencing library preparation. MspJI is a recently characterised restriction enzyme which recognises the sequence motif CNNR (where R = G or A) when the first base is modified to 5-methylcytosine or 5-hydroxymethylcytosine. A semi-random enzymatic DNA amplicon fragmentation method was developed based on the unique cleavage properties of MspJI. In this method, random incorporation of 5-methyl-2'-deoxycytidine-5'-triphosphate is achieved through DNA amplification with DNA polymerase, followed by DNA digestion with MspJI. Due to the recognition sequence of the enzyme, DNA amplicons are fragmented in a relatively sequence-independent manner. The size range of the resulting fragments was capable of control through optimisation of 5-methyl-2'-deoxycytidine-5'-triphosphate concentration in the reaction mixture. A library suitable for sequencing using the Illumina MiSeq platform was prepared and processed using the proposed method. Alignment of generated short reads to a reference sequence demonstrated a relatively high level of random fragmentation. The proposed method may be performed with standard laboratory equipment. Although the uniformity of coverage was slightly inferior to the Covaris physical shearing procedure, due to efficiencies of cost and labour, the method may be more suitable than existing approaches for implementation in large-scale sequencing activities, such as bacterial artificial chromosome (BAC)-based genome sequence assembly, pan-genomic studies and locus-targeted genotyping-by-sequencing.

Evolutionary profiles from the QR factorization of multiple sequence alignments

PubMed Central

Sethi, Anurag; O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-01-01

We present an algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of the homologous group. The method, based on the multidimensional QR factorization of numerically encoded multiple sequence 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. We observe a general trend that these smaller, more evolutionarily balanced profiles have comparable and, in many cases, better performance in database searches than conventional profiles containing hundreds of sequences, constructed in an iterative and computationally intensive procedure. For more diverse families or superfamilies, with sequence identity <30%, structural alignments, based purely on the geometry of the protein structures, provide better alignments than pure sequence-based methods. Merging the structure and sequence information allows the construction of accurate profiles for distantly related groups. These structure-based profiles outperformed other sequence-based methods for finding distant homologs and were used to identify a putative class II cysteinyl-tRNA synthetase (CysRS) in several archaea that eluded previous annotation studies. Phylogenetic analysis showed the putative class II CysRSs to be a monophyletic group and homology modeling revealed a constellation of active site residues similar to that in the known class I CysRS. PMID:15741270

Method for high-volume sequencing of nucleic acids: random and directed priming with libraries of oligonucleotides

DOEpatents

Studier, F. William

1995-04-18

Random and directed priming methods for determining nucleotide sequences by enzymatic sequencing techniques, using libraries of primers of lengths 8, 9 or 10 bases, are disclosed. These methods permit direct sequencing of nucleic acids as large as 45,000 base pairs or larger without the necessity for subcloning. Individual primers are used repeatedly to prime sequence reactions in many different nucleic acid molecules. Libraries containing as few as 10,000 octamers, 14,200 nonamers, or 44,000 decamers would have the capacity to determine the sequence of almost any cosmid DNA. Random priming with a fixed set of primers from a smaller library can also be used to initiate the sequencing of individual nucleic acid molecules, with the sequence being completed by directed priming with primers from the library. In contrast to random cloning techniques, a combined random and directed priming strategy is far more efficient.

Method for high-volume sequencing of nucleic acids: random and directed priming with libraries of oligonucleotides

DOEpatents

Studier, F.W.

1995-04-18

Random and directed priming methods for determining nucleotide sequences by enzymatic sequencing techniques, using libraries of primers of lengths 8, 9 or 10 bases, are disclosed. These methods permit direct sequencing of nucleic acids as large as 45,000 base pairs or larger without the necessity for subcloning. Individual primers are used repeatedly to prime sequence reactions in many different nucleic acid molecules. Libraries containing as few as 10,000 octamers, 14,200 nonamers, or 44,000 decamers would have the capacity to determine the sequence of almost any cosmid DNA. Random priming with a fixed set of primers from a smaller library can also be used to initiate the sequencing of individual nucleic acid molecules, with the sequence being completed by directed priming with primers from the library. In contrast to random cloning techniques, a combined random and directed priming strategy is far more efficient. 2 figs.

New encoded single-indicator sequences based on physico-chemical parameters for efficient exon identification.

PubMed

Meher, J K; Meher, P K; Dash, G N; Raval, M K

2012-01-01

The first step in gene identification problem based on genomic signal processing is to convert character strings into numerical sequences. These numerical sequences are then analysed spectrally or using digital filtering techniques for the period-3 peaks, which are present in exons (coding areas) and absent in introns (non-coding areas). In this paper, we have shown that single-indicator sequences can be generated by encoding schemes based on physico-chemical properties. Two new methods are proposed for generating single-indicator sequences based on hydration energy and dipole moments. The proposed methods produce high peak at exon locations and effectively suppress false exons (intron regions having greater peak than exon regions) resulting in high discriminating factor, sensitivity and specificity.

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

PubMed Central

2011-01-01

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

A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise

PubMed Central

Zhang, Wei; Zhang, Xiaolong; Qiang, Yan; Tian, Qi; Tang, Xiaoxian

2017-01-01

The fast and accurate segmentation of lung nodule image sequences is the basis of subsequent processing and diagnostic analyses. However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccurate and inefficient. To solve these problems, we propose a new method for the segmentation of lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise (DBSCAN). First, our method uses three-dimensional computed tomography image features of the average intensity projection combined with multi-scale dot enhancement for preprocessing. Hexagonal clustering and morphological optimized sequential linear iterative clustering (HMSLIC) for sequence image oversegmentation is then proposed to obtain superpixel blocks. The adaptive weight coefficient is then constructed to calculate the distance required between superpixels to achieve precise lung nodules positioning and to obtain the subsequent clustering starting block. Moreover, by fitting the distance and detecting the change in slope, an accurate clustering threshold is obtained. Thereafter, a fast DBSCAN superpixel sequence clustering algorithm, which is optimized by the strategy of only clustering the lung nodules and adaptive threshold, is then used to obtain lung nodule mask sequences. Finally, the lung nodule image sequences are obtained. The experimental results show that our method rapidly, completely and accurately segments various types of lung nodule image sequences. PMID:28880916

Exploring Dance Movement Data Using Sequence Alignment Methods

PubMed Central

Chavoshi, Seyed Hossein; De Baets, Bernard; Neutens, Tijs; De Tré, Guy; Van de Weghe, Nico

2015-01-01

Despite the abundance of research on knowledge discovery from moving object databases, only a limited number of studies have examined the interaction between moving point objects in space over time. This paper describes a novel approach for measuring similarity in the interaction between moving objects. The proposed approach consists of three steps. First, we transform movement data into sequences of successive qualitative relations based on the Qualitative Trajectory Calculus (QTC). Second, sequence alignment methods are applied to measure the similarity between movement sequences. Finally, movement sequences are grouped based on similarity by means of an agglomerative hierarchical clustering method. The applicability of this approach is tested using movement data from samba and tango dancers. PMID:26181435

Evaluating the protein coding potential of exonized transposable element sequences

PubMed Central

Piriyapongsa, Jittima; Rutledge, Mark T; Patel, Sanil; Borodovsky, Mark; Jordan, I King

2007-01-01

Background Transposable element (TE) sequences, once thought to be merely selfish or parasitic members of the genomic community, have been shown to contribute a wide variety of functional sequences to their host genomes. Analysis of complete genome sequences have turned up numerous cases where TE sequences have been incorporated as exons into mRNAs, and it is widely assumed that such 'exonized' TEs encode protein sequences. However, the extent to which TE-derived sequences actually encode proteins is unknown and a matter of some controversy. We have tried to address this outstanding issue from two perspectives: i-by evaluating ascertainment biases related to the search methods used to uncover TE-derived protein coding sequences (CDS) and ii-through a probabilistic codon-frequency based analysis of the protein coding potential of TE-derived exons. Results We compared the ability of three classes of sequence similarity search methods to detect TE-derived sequences among data sets of experimentally characterized proteins: 1-a profile-based hidden Markov model (HMM) approach, 2-BLAST methods and 3-RepeatMasker. Profile based methods are more sensitive and more selective than the other methods evaluated. However, the application of profile-based search methods to the detection of TE-derived sequences among well-curated experimentally characterized protein data sets did not turn up many more cases than had been previously detected and nowhere near as many cases as recent genome-wide searches have. We observed that the different search methods used were complementary in the sense that they yielded largely non-overlapping sets of hits and differed in their ability to recover known cases of TE-derived CDS. The probabilistic analysis of TE-derived exon sequences indicates that these sequences have low protein coding potential on average. In particular, non-autonomous TEs that do not encode protein sequences, such as Alu elements, are frequently exonized but unlikely to encode protein sequences. Conclusion The exaptation of the numerous TE sequences found in exons as bona fide protein coding sequences may prove to be far less common than has been suggested by the analysis of complete genomes. We hypothesize that many exonized TE sequences actually function as post-transcriptional regulators of gene expression, rather than coding sequences, which may act through a variety of double stranded RNA related regulatory pathways. Indeed, their relatively high copy numbers and similarity to sequences dispersed throughout the genome suggests that exonized TE sequences could serve as master regulators with a wide scope of regulatory influence. Reviewers: This article was reviewed by Itai Yanai, Kateryna D. Makova, Melissa Wilson (nominated by Kateryna D. Makova) and Cedric Feschotte (nominated by John M. Logsdon Jr.). PMID:18036258

Sequencing Cyclic Peptides by Multistage Mass Spectrometry

PubMed Central

Mohimani, Hosein; Yang, Yu-Liang; Liu, Wei-Ting; Hsieh, Pei-Wen; Dorrestein, Pieter C.; Pevzner, Pavel A.

2012-01-01

Some of the most effective antibiotics (e.g., Vancomycin and Daptomycin) are cyclic peptides produced by non-ribosomal biosynthetic pathways. While hundreds of biomedically important cyclic peptides have been sequenced, the computational techniques for sequencing cyclic peptides are still in their infancy. Previous methods for sequencing peptide antibiotics and other cyclic peptides are based on Nuclear Magnetic Resonance spectroscopy, and require large amount (miligrams) of purified materials that, for most compounds, are not possible to obtain. Recently, development of mass spectrometry based methods has provided some hope for accurate sequencing of cyclic peptides using picograms of materials. In this paper we develop a method for sequencing of cyclic peptides by multistage mass spectrometry, and show its advantages over single stage mass spectrometry. The method is tested on known and new cyclic peptides from Bacillus brevis, Dianthus superbus and Streptomyces griseus, as well as a new family of cyclic peptides produced by marine bacteria. PMID:21751357

An efficient study design to test parent-of-origin effects in family trios.

PubMed

Yu, Xiaobo; Chen, Gao; Feng, Rui

2017-11-01

Increasing evidence has shown that genes may cause prenatal, neonatal, and pediatric diseases depending on their parental origins. Statistical models that incorporate parent-of-origin effects (POEs) can improve the power of detecting disease-associated genes and help explain the missing heritability of diseases. In many studies, children have been sequenced for genome-wide association testing. But it may become unaffordable to sequence their parents and evaluate POEs. Motivated by the reality, we proposed a budget-friendly study design of sequencing children and only genotyping their parents through single nucleotide polymorphism array. We developed a powerful likelihood-based method, which takes into account both sequence reads and linkage disequilibrium to infer the parental origins of children's alleles and estimate their POEs on the outcome. We evaluated the performance of our proposed method and compared it with an existing method using only genotypes, through extensive simulations. Our method showed higher power than the genotype-based method. When either the mean read depth or the pair-end length was reasonably large, our method achieved ideal power. When single parents' genotypes were unavailable or parental genotypes at the testing locus were not typed, both methods lost power compared with when complete data were available; but the power loss from our method was smaller than the genotype-based method. We also extended our method to accommodate mixed genotype, low-, and high-coverage sequence data from children and their parents. At presence of sequence errors, low-coverage parental sequence data may lead to lower power than parental genotype data. © 2017 WILEY PERIODICALS, INC.

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.

Probabilistic topic modeling for the analysis and classification of genomic sequences

PubMed Central

2015-01-01

Background Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques. Methods The presented method is based on Probabilistic Topic Modeling, a statistical technique originally proposed for text documents. Probabilistic topic models are able to find in a document corpus the topics (recurrent themes) characterizing classes of documents. This technique, applied on DNA sequences representing the documents, exploits the frequency of fixed-length k-mers and builds a generative model for a training group of sequences. This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. Results and conclusions We performed classification of over 7000 16S DNA barcode sequences taken from Ribosomal Database Project (RDP) repository, training probabilistic topic models. The proposed method is compared to the RDP tool and Support Vector Machine (SVM) classification algorithm in a extensive set of trials using both complete sequences and short sequence snippets (from 400 bp to 25 bp). Our method reaches very similar results to RDP classifier and SVM for complete sequences. The most interesting results are obtained when short sequence snippets are considered. In these conditions the proposed method outperforms RDP and SVM with ultra short sequences and it exhibits a smooth decrease of performance, at every taxonomic level, when the sequence length is decreased. PMID:25916734

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

NASA Technical Reports Server (NTRS)

Robison-Cox, J. F.; Bateson, M. M.; Ward, D. M.

1995-01-01

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

Ancestry estimation and control of population stratification for sequence-based association studies.

PubMed

Wang, Chaolong; Zhan, Xiaowei; Bragg-Gresham, Jennifer; Kang, Hyun Min; Stambolian, Dwight; Chew, Emily Y; Branham, Kari E; Heckenlively, John; Fulton, Robert; Wilson, Richard K; Mardis, Elaine R; Lin, Xihong; Swaroop, Anand; Zöllner, Sebastian; Abecasis, Gonçalo R

2014-04-01

Estimating individual ancestry is important in genetic association studies where population structure leads to false positive signals, although assigning ancestry remains challenging with targeted sequence data. We propose a new method for the accurate estimation of individual genetic ancestry, based on direct analysis of off-target sequence reads, and implement our method in the publicly available LASER software. We validate the method using simulated and empirical data and show that the method can accurately infer worldwide continental ancestry when used with sequencing data sets with whole-genome shotgun coverage as low as 0.001×. For estimates of fine-scale ancestry within Europe, the method performs well with coverage of 0.1×. On an even finer scale, the method improves discrimination between exome-sequenced study participants originating from different provinces within Finland. Finally, we show that our method can be used to improve case-control matching in genetic association studies and to reduce the risk of spurious findings due to population structure.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Method for phosphorothioate antisense DNA sequencing by capillary electrophoresis with UV detection.

PubMed

Froim, D; Hopkins, C E; Belenky, A; Cohen, A S

1997-11-01

The progress of antisense DNA therapy demands development of reliable and convenient methods for sequencing short single-stranded oligonucleotides. A method of phosphorothioate antisense DNA sequencing analysis using UV detection coupled to capillary electrophoresis (CE) has been developed based on a modified chain termination sequencing method. The proposed method reduces the sequencing cost since it uses affordable CE-UV instrumentation and requires no labeling with minimal sample processing before analysis. Cycle sequencing with ThermoSequenase generates quantities of sequencing products that are readily detectable by UV. Discrimination of undesired components from sequencing products in the reaction mixture, previously accomplished by fluorescent or radioactive labeling, is now achieved by bringing concentrations of undesired components below the UV detection range which yields a 'clean', well defined sequence. UV detection coupled with CE offers additional conveniences for sequencing since it can be accomplished with commercially available CE-UV equipment and is readily amenable to automation.

Method for phosphorothioate antisense DNA sequencing by capillary electrophoresis with UV detection.

PubMed Central

Froim, D; Hopkins, C E; Belenky, A; Cohen, A S

1997-01-01

The progress of antisense DNA therapy demands development of reliable and convenient methods for sequencing short single-stranded oligonucleotides. A method of phosphorothioate antisense DNA sequencing analysis using UV detection coupled to capillary electrophoresis (CE) has been developed based on a modified chain termination sequencing method. The proposed method reduces the sequencing cost since it uses affordable CE-UV instrumentation and requires no labeling with minimal sample processing before analysis. Cycle sequencing with ThermoSequenase generates quantities of sequencing products that are readily detectable by UV. Discrimination of undesired components from sequencing products in the reaction mixture, previously accomplished by fluorescent or radioactive labeling, is now achieved by bringing concentrations of undesired components below the UV detection range which yields a 'clean', well defined sequence. UV detection coupled with CE offers additional conveniences for sequencing since it can be accomplished with commercially available CE-UV equipment and is readily amenable to automation. PMID:9336449

Haplotype estimation using sequencing reads.

PubMed

Delaneau, Olivier; Howie, Bryan; Cox, Anthony J; Zagury, Jean-François; Marchini, Jonathan

2013-10-03

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5-20 kb read with 4%-15% error per base), phasing performance was substantially improved. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Glutenite bodies sequence division of the upper Es4 in northern Minfeng zone of Dongying Sag, Bohai Bay Basin, China

NASA Astrophysics Data System (ADS)

Shao, Xupeng

2017-04-01

Glutenite bodies are widely developed in northern Minfeng zone of Dongying Sag. Their litho-electric relationship is not clear. In addition, as the conventional sequence stratigraphic research method drawbacks of involving too many subjective human factors, it has limited deepening of the regional sequence stratigraphic research. The wavelet transform technique based on logging data and the time-frequency analysis technique based on seismic data have advantages of dividing sequence stratigraphy quantitatively comparing with the conventional methods. Under the basis of the conventional sequence research method, this paper used the above techniques to divide the fourth-order sequence of the upper Es4 in northern Minfeng zone of Dongying Sag. The research shows that the wavelet transform technique based on logging data and the time-frequency analysis technique based on seismic data are essentially consistent, both of which divide sequence stratigraphy quantitatively in the frequency domain; wavelet transform technique has high resolutions. It is suitable for areas with wells. The seismic time-frequency analysis technique has wide applicability, but a low resolution. Both of the techniques should be combined; the upper Es4 in northern Minfeng zone of Dongying Sag is a complete set of third-order sequence, which can be further subdivided into 5 fourth-order sequences that has the depositional characteristics of fine-upward sequence in granularity. Key words: Dongying sag, northern Minfeng zone, wavelet transform technique, time-frequency analysis technique ,the upper Es4, sequence stratigraphy

Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications

PubMed Central

Harris, R. Alan; Wang, Ting; Coarfa, Cristian; Nagarajan, Raman P.; Hong, Chibo; Downey, Sara L.; Johnson, Brett E.; Fouse, Shaun D.; Delaney, Allen; Zhao, Yongjun; Olshen, Adam; Ballinger, Tracy; Zhou, Xin; Forsberg, Kevin J.; Gu, Junchen; Echipare, Lorigail; O’Geen, Henriette; Lister, Ryan; Pelizzola, Mattia; Xi, Yuanxin; Epstein, Charles B.; Bernstein, Bradley E.; Hawkins, R. David; Ren, Bing; Chung, Wen-Yu; Gu, Hongcang; Bock, Christoph; Gnirke, Andreas; Zhang, Michael Q.; Haussler, David; Ecker, Joseph; Li, Wei; Farnham, Peggy J.; Waterland, Robert A.; Meissner, Alexander; Marra, Marco A.; Hirst, Martin; Milosavljevic, Aleksandar; Costello, Joseph F.

2010-01-01

Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression. PMID:20852635

Small-target leak detection for a closed vessel via infrared image sequences

NASA Astrophysics Data System (ADS)

Zhao, Ling; Yang, Hongjiu

2017-03-01

This paper focus on a leak diagnosis and localization method based on infrared image sequences. Some problems on high probability of false warning and negative affect for marginal information are solved by leak detection. An experimental model is established for leak diagnosis and localization on infrared image sequences. The differential background prediction is presented to eliminate the negative affect of marginal information on test vessel based on a kernel regression method. A pipeline filter based on layering voting is designed to reduce probability of leak point false warning. A synthesize leak diagnosis and localization algorithm is proposed based on infrared image sequences. The effectiveness and potential are shown for developed techniques through experimental results.

A method for automatically extracting infectious disease-related primers and probes from the literature

PubMed Central

2010-01-01

Background Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1) convert each document into a tree of paper sections, (2) detect the candidate sequences using a set of finite state machine-based recognizers, (3) refine problem sequences using a rule-based expert system, and (4) annotate the extracted sequences with their related organism/gene information. Results We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. Conclusions We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch. PMID:20682041

An Accurate Scalable Template-based Alignment Algorithm

PubMed Central

Gardner, David P.; Xu, Weijia; Miranker, Daniel P.; Ozer, Stuart; Cannone, Jamie J.; Gutell, Robin R.

2013-01-01

The rapid determination of nucleic acid sequences is increasing the number of sequences that are available. Inherent in a template or seed alignment is the culmination of structural and functional constraints that are selecting those mutations that are viable during the evolution of the RNA. While we might not understand these structural and functional, template-based alignment programs utilize the patterns of sequence conservation to encapsulate the characteristics of viable RNA sequences that are aligned properly. We have developed a program that utilizes the different dimensions of information in rCAD, a large RNA informatics resource, to establish a profile for each position in an alignment. The most significant include sequence identity and column composition in different phylogenetic taxa. We have compared our methods with a maximum of eight alternative alignment methods on different sets of 16S and 23S rRNA sequences with sequence percent identities ranging from 50% to 100%. The results showed that CRWAlign outperformed the other alignment methods in both speed and accuracy. A web-based alignment server is available at http://www.rna.ccbb.utexas.edu/SAE/2F/CRWAlign. PMID:24772376

A Partial Least Squares Based Procedure for Upstream Sequence Classification in Prokaryotes.

PubMed

Mehmood, Tahir; Bohlin, Jon; Snipen, Lars

2015-01-01

The upstream region of coding genes is important for several reasons, for instance locating transcription factor, binding sites, and start site initiation in genomic DNA. Motivated by a recently conducted study, where multivariate approach was successfully applied to coding sequence modeling, we have introduced a partial least squares (PLS) based procedure for the classification of true upstream prokaryotic sequence from background upstream sequence. The upstream sequences of conserved coding genes over genomes were considered in analysis, where conserved coding genes were found by using pan-genomics concept for each considered prokaryotic species. PLS uses position specific scoring matrix (PSSM) to study the characteristics of upstream region. Results obtained by PLS based method were compared with Gini importance of random forest (RF) and support vector machine (SVM), which is much used method for sequence classification. The upstream sequence classification performance was evaluated by using cross validation, and suggested approach identifies prokaryotic upstream region significantly better to RF (p-value < 0.01) and SVM (p-value < 0.01). Further, the proposed method also produced results that concurred with known biological characteristics of the upstream region.

Fine-tuning structural RNA alignments in the twilight zone.

PubMed

Bremges, Andreas; Schirmer, Stefanie; Giegerich, Robert

2010-04-30

A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index.

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

PubMed

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

2017-01-25

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

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods.

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods. PMID:18452616

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1987-10-07

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1990-10-09

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Moyzis, Robert K.; Ratliff, Robert L.; Shera, E. Brooks; Stewart, Carleton C.

1990-01-01

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed.

Direct Detection and Sequencing of Damaged DNA Bases

PubMed Central

2011-01-01

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications. PMID:22185597

Direct detection and sequencing of damaged DNA bases.

PubMed

Clark, Tyson A; Spittle, Kristi E; Turner, Stephen W; Korlach, Jonas

2011-12-20

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications.

A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

NASA Astrophysics Data System (ADS)

Haijun, Xiong; Qi, Zhang

2016-08-01

Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

Preliminary Classification of Novel Hemorrhagic Fever-Causing Viruses Using Sequence-Based PAirwise Sequence Comparison (PASC) Analysis.

PubMed

Bào, Yīmíng; Kuhn, Jens H

2018-01-01

During the last decade, genome sequence-based classification of viruses has become increasingly prominent. Viruses can be even classified based on coding-complete genome sequence data alone. Nevertheless, classification remains arduous as experts are required to establish phylogenetic trees to depict the evolutionary relationships of such sequences for preliminary taxonomic placement. Pairwise sequence comparison (PASC) of genomes is one of several novel methods for establishing relationships among viruses. This method, provided by the US National Center for Biotechnology Information as an open-access tool, circumvents phylogenetics, and yet PASC results are often in agreement with those of phylogenetic analyses. Computationally inexpensive, PASC can be easily performed by non-taxonomists. Here we describe how to use the PASC tool for the preliminary classification of novel viral hemorrhagic fever-causing viruses.

Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information

PubMed Central

McDonald, Daniel; Gonzalez, Antonio; Navas-Molina, Jose A.; Jiang, Lingjing; Xu, Zhenjiang Zech; Winker, Kevin; Kado, Deborah M.; Orwoll, Eric; Manary, Mark; Mirarab, Siavash

2018-01-01

ABSTRACT Recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence fragments. These new methods enable the investigation of sub-operational taxonomic units (sOTU) by removing erroneous sequences. However, short (e.g., 150-nucleotide [nt]) DNA sequence fragments do not contain sufficient phylogenetic signal to reproduce a reasonable tree, introducing a barrier in the utilization of critical phylogenetically aware metrics such as Faith’s PD or UniFrac. Although fragment insertion methods do exist, those methods have not been tested for sOTUs from high-throughput amplicon studies in insertions against a broad reference phylogeny. We benchmarked the SATé-enabled phylogenetic placement (SEPP) technique explicitly against 16S V4 sequence fragments and showed that it outperforms the conceptually problematic but often-used practice of reconstructing de novo phylogenies. In addition, we provide a BSD-licensed QIIME2 plugin (https://github.com/biocore/q2-fragment-insertion) for SEPP and integration into the microbial study management platform QIITA. IMPORTANCE The move from OTU-based to sOTU-based analysis, while providing additional resolution, also introduces computational challenges. We demonstrate that one popular method of dealing with sOTUs (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with SEPP resolves this problem while also yielding other benefits over existing methods. PMID:29719869

Zseq: An Approach for Preprocessing Next-Generation Sequencing Data.

PubMed

Alkhateeb, Abedalrhman; Rueda, Luis

2017-08-01

Next-generation sequencing technology generates a huge number of reads (short sequences), which contain a vast amount of genomic data. The sequencing process, however, comes with artifacts. Preprocessing of sequences is mandatory for further downstream analysis. We present Zseq, a linear method that identifies the most informative genomic sequences and reduces the number of biased sequences, sequence duplications, and ambiguous nucleotides. Zseq finds the complexity of the sequences by counting the number of unique k-mers in each sequence as its corresponding score and also takes into the account other factors such as ambiguous nucleotides or high GC-content percentage in k-mers. Based on a z-score threshold, Zseq sweeps through the sequences again and filters those with a z-score less than the user-defined threshold. Zseq algorithm is able to provide a better mapping rate; it reduces the number of ambiguous bases significantly in comparison with other methods. Evaluation of the filtered reads has been conducted by aligning the reads and assembling the transcripts using the reference genome as well as de novo assembly. The assembled transcripts show a better discriminative ability to separate cancer and normal samples in comparison with another state-of-the-art method. Moreover, de novo assembled transcripts from the reads filtered by Zseq have longer genomic sequences than other tested methods. Estimating the threshold of the cutoff point is introduced using labeling rules with optimistic results.

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

PubMed

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

2017-01-01

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

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

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

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

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference.

PubMed

Krishnan, Neeraja M; Seligmann, Hervé; Stewart, Caro-Beth; De Koning, A P Jason; Pollock, David D

2004-10-01

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.

Correcting for Sample Contamination in Genotype Calling of DNA Sequence Data

PubMed Central

Flickinger, Matthew; Jun, Goo; Abecasis, Gonçalo R.; Boehnke, Michael; Kang, Hyun Min

2015-01-01

DNA sample contamination is a frequent problem in DNA sequencing studies and can result in genotyping errors and reduced power for association testing. We recently described methods to identify within-species DNA sample contamination based on sequencing read data, showed that our methods can reliably detect and estimate contamination levels as low as 1%, and suggested strategies to identify and remove contaminated samples from sequencing studies. Here we propose methods to model contamination during genotype calling as an alternative to removal of contaminated samples from further analyses. We compare our contamination-adjusted calls to calls that ignore contamination and to calls based on uncontaminated data. We demonstrate that, for moderate contamination levels (5%–20%), contamination-adjusted calls eliminate 48%–77% of the genotyping errors. For lower levels of contamination, our contamination correction methods produce genotypes nearly as accurate as those based on uncontaminated data. Our contamination correction methods are useful generally, but are particularly helpful for sample contamination levels from 2% to 20%. PMID:26235984

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

DOE PAGES

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

2015-03-09

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

GI-SVM: A sensitive method for predicting genomic islands based on unannotated sequence of a single genome.

PubMed

Lu, Bingxin; Leong, Hon Wai

2016-02-01

Genomic islands (GIs) are clusters of functionally related genes acquired by lateral genetic transfer (LGT), and they are present in many bacterial genomes. GIs are extremely important for bacterial research, because they not only promote genome evolution but also contain genes that enhance adaption and enable antibiotic resistance. Many methods have been proposed to predict GI. But most of them rely on either annotations or comparisons with other closely related genomes. Hence these methods cannot be easily applied to new genomes. As the number of newly sequenced bacterial genomes rapidly increases, there is a need for methods to detect GI based solely on sequences of a single genome. In this paper, we propose a novel method, GI-SVM, to predict GIs given only the unannotated genome sequence. GI-SVM is based on one-class support vector machine (SVM), utilizing composition bias in terms of k-mer content. From our evaluations on three real genomes, GI-SVM can achieve higher recall compared with current methods, without much loss of precision. Besides, GI-SVM allows flexible parameter tuning to get optimal results for each genome. In short, GI-SVM provides a more sensitive method for researchers interested in a first-pass detection of GI in newly sequenced genomes.

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

PubMed

Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

2015-07-01

In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

BiRen: predicting enhancers with a deep-learning-based model using the DNA sequence alone.

PubMed

Yang, Bite; Liu, Feng; Ren, Chao; Ouyang, Zhangyi; Xie, Ziwei; Bo, Xiaochen; Shu, Wenjie

2017-07-01

Enhancer elements are noncoding stretches of DNA that play key roles in controlling gene expression programmes. Despite major efforts to develop accurate enhancer prediction methods, identifying enhancer sequences continues to be a challenge in the annotation of mammalian genomes. One of the major issues is the lack of large, sufficiently comprehensive and experimentally validated enhancers for humans or other species. Thus, the development of computational methods based on limited experimentally validated enhancers and deciphering the transcriptional regulatory code encoded in the enhancer sequences is urgent. We present a deep-learning-based hybrid architecture, BiRen, which predicts enhancers using the DNA sequence alone. Our results demonstrate that BiRen can learn common enhancer patterns directly from the DNA sequence and exhibits superior accuracy, robustness and generalizability in enhancer prediction relative to other state-of-the-art enhancer predictors based on sequence characteristics. Our BiRen will enable researchers to acquire a deeper understanding of the regulatory code of enhancer sequences. Our BiRen method can be freely accessed at https://github.com/wenjiegroup/BiRen . shuwj@bmi.ac.cn or boxc@bmi.ac.cn. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Metabarcoding of marine nematodes – evaluation of reference datasets used in tree-based taxonomy assignment approach

PubMed Central

2016-01-01

Abstract Background Metabarcoding is becoming a common tool used to assess and compare diversity of organisms in environmental samples. Identification of OTUs is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task. This publication evaluates the quality of reference datasets, alongside with several alignment and phylogeny inference methods used in one of the taxonomy assignment methods, called tree-based approach. This approach assigns anonymous OTUs to taxonomic categories based on relative placements of OTUs and reference sequences on the cladogram and support that these placements receive. New information In tree-based taxonomy assignment approach, reliable identification of anonymous OTUs is based on their placement in monophyletic and highly supported clades together with identified reference taxa. Therefore, it requires high quality reference dataset to be used. Resolution of phylogenetic trees is strongly affected by the presence of erroneous sequences as well as alignment and phylogeny inference methods used in the process. Two preparation steps are essential for the successful application of tree-based taxonomy assignment approach. Curated collections of genetic information do include erroneous sequences. These sequences have detrimental effect on the resolution of cladograms used in tree-based approach. They must be identified and excluded from the reference dataset beforehand. Various combinations of multiple sequence alignment and phylogeny inference methods provide cladograms with different topology and bootstrap support. These combinations of methods need to be tested in order to determine the one that gives highest resolution for the particular reference dataset. Completing the above mentioned preparation steps is expected to decrease the number of unassigned OTUs and thus improve the results of the tree-based taxonomy assignment approach. PMID:27932919

Metabarcoding of marine nematodes - evaluation of reference datasets used in tree-based taxonomy assignment approach.

PubMed

Holovachov, Oleksandr

2016-01-01

Metabarcoding is becoming a common tool used to assess and compare diversity of organisms in environmental samples. Identification of OTUs is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task. This publication evaluates the quality of reference datasets, alongside with several alignment and phylogeny inference methods used in one of the taxonomy assignment methods, called tree-based approach. This approach assigns anonymous OTUs to taxonomic categories based on relative placements of OTUs and reference sequences on the cladogram and support that these placements receive. In tree-based taxonomy assignment approach, reliable identification of anonymous OTUs is based on their placement in monophyletic and highly supported clades together with identified reference taxa. Therefore, it requires high quality reference dataset to be used. Resolution of phylogenetic trees is strongly affected by the presence of erroneous sequences as well as alignment and phylogeny inference methods used in the process. Two preparation steps are essential for the successful application of tree-based taxonomy assignment approach. Curated collections of genetic information do include erroneous sequences. These sequences have detrimental effect on the resolution of cladograms used in tree-based approach. They must be identified and excluded from the reference dataset beforehand.Various combinations of multiple sequence alignment and phylogeny inference methods provide cladograms with different topology and bootstrap support. These combinations of methods need to be tested in order to determine the one that gives highest resolution for the particular reference dataset.Completing the above mentioned preparation steps is expected to decrease the number of unassigned OTUs and thus improve the results of the tree-based taxonomy assignment approach.

Benchmarking of Methods for Genomic Taxonomy

DOE PAGES

Larsen, Mette V.; Cosentino, Salvatore; Lukjancenko, Oksana; ...

2014-02-26

One of the first issues that emerges when a prokaryotic organism of interest is encountered is the question of what it is—that is, which species it is. The 16S rRNA gene formed the basis of the first method for sequence-based taxonomy and has had a tremendous impact on the field of microbiology. Nevertheless, the method has been found to have a number of shortcomings. In this paper, we trained and benchmarked five methods for whole-genome sequence-based prokaryotic species identification on a common data set of complete genomes: (i) SpeciesFinder, which is based on the complete 16S rRNA gene; (ii) Reads2Typemore » that searches for species-specific 50-mers in either the 16S rRNA gene or the gyrB gene (for the Enterobacteraceae family); (iii) the ribosomal multilocus sequence typing (rMLST) method that samples up to 53 ribosomal genes; (iv) TaxonomyFinder, which is based on species-specific functional protein domain profiles; and finally (v) KmerFinder, which examines the number of cooccurring k-mers (substrings of k nucleotides in DNA sequence data). The performances of the methods were subsequently evaluated on three data sets of short sequence reads or draft genomes from public databases. In total, the evaluation sets constituted sequence data from more than 11,000 isolates covering 159 genera and 243 species. Our results indicate that methods that sample only chromosomal, core genes have difficulties in distinguishing closely related species which only recently diverged. Finally, the KmerFinder method had the overall highest accuracy and correctly identified from 93% to 97% of the isolates in the evaluations sets.« less

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

PubMed Central

2017-01-01

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

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

PubMed

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

2017-01-01

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

Phylogenetic Analysis of Shewanella Strains by DNA Relatedness Derived from Whole Genome Microarray DNA-DNA Hybridization and Comparison with Other Methods

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

Wu, Liyou; Yi, T. Y.; Van Nostrand, Joy

Phylogenetic analyses were done for the Shewanella strains isolated from Baltic Sea (38 strains), US DOE Hanford Uranium bioremediation site [Hanford Reach of the Columbia River (HRCR), 11 strains], Pacific Ocean and Hawaiian sediments (8 strains), and strains from other resources (16 strains) with three out group strains, Rhodopseudomonas palustris, Clostridium cellulolyticum, and Thermoanaerobacter ethanolicus X514, using DNA relatedness derived from WCGA-based DNA-DNA hybridizations, sequence similarities of 16S rRNA gene and gyrB gene, and sequence similarities of 6 loci of Shewanella genome selected from a shared gene list of the Shewanella strains with whole genome sequenced based on the averagemore » nucleotide identity of them (ANI). The phylogenetic trees based on 16S rRNA and gyrB gene sequences, and DNA relatedness derived from WCGA hybridizations of the tested Shewanella strains share exactly the same sub-clusters with very few exceptions, in which the strains were basically grouped by species. However, the phylogenetic analysis based on DNA relatedness derived from WCGA hybridizations dramatically increased the differentiation resolution at species and strains level within Shewanella genus. When the tree based on DNA relatedness derived from WCGA hybridizations was compared to the tree based on the combined sequences of the selected functional genes (6 loci), we found that the resolutions of both methods are similar, but the clustering of the tree based on DNA relatedness derived from WMGA hybridizations was clearer. These results indicate that WCGA-based DNA-DNA hybridization is an idea alternative of conventional DNA-DNA hybridization methods and it is superior to the phylogenetics methods based on sequence similarities of single genes. Detailed analysis is being performed for the re-classification of the strains examined.« less

Development of Mycoplasma synoviae (MS) core genome multilocus sequence typing (cgMLST) scheme.

PubMed

Ghanem, Mostafa; El-Gazzar, Mohamed

2018-05-01

Mycoplasma synoviae (MS) is a poultry pathogen with reported increased prevalence and virulence in recent years. MS strain identification is essential for prevention, control efforts and epidemiological outbreak investigations. Multiple multilocus based sequence typing schemes have been developed for MS, yet the resolution of these schemes could be limited for outbreak investigation. The cost of whole genome sequencing became close to that of sequencing the seven MLST targets; however, there is no standardized method for typing MS strains based on whole genome sequences. In this paper, we propose a core genome multilocus sequence typing (cgMLST) scheme as a standardized and reproducible method for typing MS based whole genome sequences. A diverse set of 25 MS whole genome sequences were used to identify 302 core genome genes as cgMLST targets (35.5% of MS genome) and 44 whole genome sequences of MS isolates from six countries in four continents were used for typing applying this scheme. cgMLST based phylogenetic trees displayed a high degree of agreement with core genome SNP based analysis and available epidemiological information. cgMLST allowed evaluation of two conventional MLST schemes of MS. The high discriminatory power of cgMLST allowed differentiation between samples of the same conventional MLST type. cgMLST represents a standardized, accurate, highly discriminatory, and reproducible method for differentiation between MS isolates. Like conventional MLST, it provides stable and expandable nomenclature, allowing for comparing and sharing the typing results between different laboratories worldwide. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2006-07-04

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2002-01-01

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

A novel model for DNA sequence similarity analysis based on graph theory.

PubMed

Qi, Xingqin; Wu, Qin; Zhang, Yusen; Fuller, Eddie; Zhang, Cun-Quan

2011-01-01

Determination of sequence similarity is one of the major steps in computational phylogenetic studies. As we know, during evolutionary history, not only DNA mutations for individual nucleotide but also subsequent rearrangements occurred. It has been one of major tasks of computational biologists to develop novel mathematical descriptors for similarity analysis such that various mutation phenomena information would be involved simultaneously. In this paper, different from traditional methods (eg, nucleotide frequency, geometric representations) as bases for construction of mathematical descriptors, we construct novel mathematical descriptors based on graph theory. In particular, for each DNA sequence, we will set up a weighted directed graph. The adjacency matrix of the directed graph will be used to induce a representative vector for DNA sequence. This new approach measures similarity based on both ordering and frequency of nucleotides so that much more information is involved. As an application, the method is tested on a set of 0.9-kb mtDNA sequences of twelve different primate species. All output phylogenetic trees with various distance estimations have the same topology, and are generally consistent with the reported results from early studies, which proves the new method's efficiency; we also test the new method on a simulated data set, which shows our new method performs better than traditional global alignment method when subsequent rearrangements happen frequently during evolutionary history.

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

PubMed Central

2017-01-01

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package. PMID:28100584

Phylogenetic analysis of a spontaneous cocoa bean fermentation metagenome reveals new insights into its bacterial and fungal community diversity.

PubMed

Illeghems, Koen; De Vuyst, Luc; Papalexandratou, Zoi; Weckx, Stefan

2012-01-01

This is the first report on the phylogenetic analysis of the community diversity of a single spontaneous cocoa bean box fermentation sample through a metagenomic approach involving 454 pyrosequencing. Several sequence-based and composition-based taxonomic profiling tools were used and evaluated to avoid software-dependent results and their outcome was validated by comparison with previously obtained culture-dependent and culture-independent data. Overall, this approach revealed a wider bacterial (mainly γ-Proteobacteria) and fungal diversity than previously found. Further, the use of a combination of different classification methods, in a software-independent way, helped to understand the actual composition of the microbial ecosystem under study. In addition, bacteriophage-related sequences were found. The bacterial diversity depended partially on the methods used, as composition-based methods predicted a wider diversity than sequence-based methods, and as classification methods based solely on phylogenetic marker genes predicted a more restricted diversity compared with methods that took all reads into account. The metagenomic sequencing analysis identified Hanseniaspora uvarum, Hanseniaspora opuntiae, Saccharomyces cerevisiae, Lactobacillus fermentum, and Acetobacter pasteurianus as the prevailing species. Also, the presence of occasional members of the cocoa bean fermentation process was revealed (such as Erwinia tasmaniensis, Lactobacillus brevis, Lactobacillus casei, Lactobacillus rhamnosus, Lactococcus lactis, Leuconostoc mesenteroides, and Oenococcus oeni). Furthermore, the sequence reads associated with viral communities were of a restricted diversity, dominated by Myoviridae and Siphoviridae, and reflecting Lactobacillus as the dominant host. To conclude, an accurate overview of all members of a cocoa bean fermentation process sample was revealed, indicating the superiority of metagenomic sequencing over previously used techniques.

PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods

PubMed Central

2012-01-01

Background With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it. Results PHYLOViZ is platform independent Java software that allows the integrated analysis of sequence-based typing methods, including SNP data generated from whole genome sequence approaches, and associated epidemiological data. goeBURST and its Minimum Spanning Tree expansion are used for visualizing the possible evolutionary relationships between isolates. The results can be displayed as an annotated graph overlaying the query results of any other epidemiological data available. Conclusions PHYLOViZ is a user-friendly software that allows the combined analysis of multiple data sources for microbial epidemiological and population studies. It is freely available at http://www.phyloviz.net. PMID:22568821

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data.

PubMed

Zhang, Yun; Baheti, Saurabh; Sun, Zhifu

2018-05-01

High-throughput bisulfite methylation sequencing such as reduced representation bisulfite sequencing (RRBS), Agilent SureSelect Human Methyl-Seq (Methyl-seq) or whole-genome bisulfite sequencing is commonly used for base resolution methylome research. These data are represented either by the ratio of methylated cytosine versus total coverage at a CpG site or numbers of methylated and unmethylated cytosines. Multiple statistical methods can be used to detect differentially methylated CpGs (DMCs) between conditions, and these methods are often the base for the next step of differentially methylated region identification. The ratio data have a flexibility of fitting to many linear models, but the raw count data take consideration of coverage information. There is an array of options in each datatype for DMC detection; however, it is not clear which is an optimal statistical method. In this study, we systematically evaluated four statistic methods on methylation ratio data and four methods on count-based data and compared their performances with regard to type I error control, sensitivity and specificity of DMC detection and computational resource demands using real RRBS data along with simulation. Our results show that the ratio-based tests are generally more conservative (less sensitive) than the count-based tests. However, some count-based methods have high false-positive rates and should be avoided. The beta-binomial model gives a good balance between sensitivity and specificity and is preferred method. Selection of methods in different settings, signal versus noise and sample size estimation are also discussed.

Skeleton-based human action recognition using multiple sequence alignment

NASA Astrophysics Data System (ADS)

Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

2015-05-01

Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

Fine-tuning structural RNA alignments in the twilight zone

PubMed Central

2010-01-01

Background A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Results Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Conclusions Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index. PMID:20433706

DNA and RNA sequencing by nanoscale reading through programmable electrophoresis and nanoelectrode-gated tunneling and dielectric detection

DOEpatents

Lee, James W.; Thundat, Thomas G.

2005-06-14

An apparatus and method for performing nucleic acid (DNA and/or RNA) sequencing on a single molecule. The genetic sequence information is obtained by probing through a DNA or RNA molecule base by base at nanometer scale as though looking through a strip of movie film. This DNA sequencing nanotechnology has the theoretical capability of performing DNA sequencing at a maximal rate of about 1,000,000 bases per second. This enhanced performance is made possible by a series of innovations including: novel applications of a fine-tuned nanometer gap for passage of a single DNA or RNA molecule; thin layer microfluidics for sample loading and delivery; and programmable electric fields for precise control of DNA or RNA movement. Detection methods include nanoelectrode-gated tunneling current measurements, dielectric molecular characterization, and atomic force microscopy/electrostatic force microscopy (AFM/EFM) probing for nanoscale reading of the nucleic acid sequences.

BEST: Improved Prediction of B-Cell Epitopes from Antigen Sequences

PubMed Central

Gao, Jianzhao; Faraggi, Eshel; Zhou, Yaoqi; Ruan, Jishou; Kurgan, Lukasz

2012-01-01

Accurate identification of immunogenic regions in a given antigen chain is a difficult and actively pursued problem. Although accurate predictors for T-cell epitopes are already in place, the prediction of the B-cell epitopes requires further research. We overview the available approaches for the prediction of B-cell epitopes and propose a novel and accurate sequence-based solution. Our BEST (B-cell Epitope prediction using Support vector machine Tool) method predicts epitopes from antigen sequences, in contrast to some method that predict only from short sequence fragments, using a new architecture based on averaging selected scores generated from sliding 20-mers by a Support Vector Machine (SVM). The SVM predictor utilizes a comprehensive and custom designed set of inputs generated by combining information derived from the chain, sequence conservation, similarity to known (training) epitopes, and predicted secondary structure and relative solvent accessibility. Empirical evaluation on benchmark datasets demonstrates that BEST outperforms several modern sequence-based B-cell epitope predictors including ABCPred, method by Chen et al. (2007), BCPred, COBEpro, BayesB, and CBTOPE, when considering the predictions from antigen chains and from the chain fragments. Our method obtains a cross-validated area under the receiver operating characteristic curve (AUC) for the fragment-based prediction at 0.81 and 0.85, depending on the dataset. The AUCs of BEST on the benchmark sets of full antigen chains equal 0.57 and 0.6, which is significantly and slightly better than the next best method we tested. We also present case studies to contrast the propensity profiles generated by BEST and several other methods. PMID:22761950

Methods for sequencing GC-rich and CCT repeat DNA templates

DOEpatents

Robinson, Donna L.

2007-02-20

The present invention is directed to a PCR-based method of cycle sequencing DNA and other polynucleotide sequences having high CG content and regions of high GC content, and includes for example DNA strands with a high Cytosine and/or Guanosine content and repeated motifs such as CCT repeats.

Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines

PubMed Central

Mentasti, Massimo; Tewolde, Rediat; Aslett, Martin; Harris, Simon R.; Afshar, Baharak; Underwood, Anthony; Harrison, Timothy G.

2016-01-01

Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current “gold standard” typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila. However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard “typing panel,” previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila. PMID:27280420

Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines.

PubMed

David, Sophia; Mentasti, Massimo; Tewolde, Rediat; Aslett, Martin; Harris, Simon R; Afshar, Baharak; Underwood, Anthony; Fry, Norman K; Parkhill, Julian; Harrison, Timothy G

2016-08-01

Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current "gold standard" typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard "typing panel," previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila. Copyright © 2016 David et al.

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

PubMed

He, Yan; Caporaso, J Gregory; Jiang, Xiao-Tao; Sheng, Hua-Fang; Huse, Susan M; Rideout, Jai Ram; Edgar, Robert C; Kopylova, Evguenia; Walters, William A; Knight, Rob; Zhou, Hong-Wei

2015-01-01

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

Use of the melting curve assay as a means for high-throughput quantification of Illumina sequencing libraries.

PubMed

Shinozuka, Hiroshi; Forster, John W

2016-01-01

Background. Multiplexed sequencing is commonly performed on massively parallel short-read sequencing platforms such as Illumina, and the efficiency of library normalisation can affect the quality of the output dataset. Although several library normalisation approaches have been established, none are ideal for highly multiplexed sequencing due to issues of cost and/or processing time. Methods. An inexpensive and high-throughput library quantification method has been developed, based on an adaptation of the melting curve assay. Sequencing libraries were subjected to the assay using the Bio-Rad Laboratories CFX Connect(TM) Real-Time PCR Detection System. The library quantity was calculated through summation of reduction of relative fluorescence units between 86 and 95 °C. Results.PCR-enriched sequencing libraries are suitable for this quantification without pre-purification of DNA. Short DNA molecules, which ideally should be eliminated from the library for subsequent processing, were differentiated from the target DNA in a mixture on the basis of differences in melting temperature. Quantification results for long sequences targeted using the melting curve assay were correlated with those from existing methods (R (2) > 0.77), and that observed from MiSeq sequencing (R (2) = 0.82). Discussion.The results of multiplexed sequencing suggested that the normalisation performance of the described method is equivalent to that of another recently reported high-throughput bead-based method, BeNUS. However, costs for the melting curve assay are considerably lower and processing times shorter than those of other existing methods, suggesting greater suitability for highly multiplexed sequencing applications.

Masking as an effective quality control method for next-generation sequencing data analysis.

PubMed

Yun, Sajung; Yun, Sijung

2014-12-13

Next generation sequencing produces base calls with low quality scores that can affect the accuracy of identifying simple nucleotide variation calls, including single nucleotide polymorphisms and small insertions and deletions. Here we compare the effectiveness of two data preprocessing methods, masking and trimming, and the accuracy of simple nucleotide variation calls on whole-genome sequence data from Caenorhabditis elegans. Masking substitutes low quality base calls with 'N's (undetermined bases), whereas trimming removes low quality bases that results in a shorter read lengths. We demonstrate that masking is more effective than trimming in reducing the false-positive rate in single nucleotide polymorphism (SNP) calling. However, both of the preprocessing methods did not affect the false-negative rate in SNP calling with statistical significance compared to the data analysis without preprocessing. False-positive rate and false-negative rate for small insertions and deletions did not show differences between masking and trimming. We recommend masking over trimming as a more effective preprocessing method for next generation sequencing data analysis since masking reduces the false-positive rate in SNP calling without sacrificing the false-negative rate although trimming is more commonly used currently in the field. The perl script for masking is available at http://code.google.com/p/subn/. The sequencing data used in the study were deposited in the Sequence Read Archive (SRX450968 and SRX451773).

A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2013-11-07

Protein-Protein interaction (PPI) is one of the most important data in understanding the cellular processes. Many interesting methods have been proposed in order to predict PPIs. However, the methods which are based on the sequence of proteins as a prior knowledge are more universal. In this paper, a sequence-based, fast, and adaptive PPI prediction method is introduced to assign two proteins to an interaction class (yes, no). First, in order to improve the presentation of the sequences, twelve physicochemical properties of amino acid have been used by different representation methods to transform the sequence of protein pairs into different feature vectors. Then, for speeding up the learning process and reducing the effect of noise PPI data, principal component analysis (PCA) is carried out as a proper feature extraction algorithm. Finally, a new and adaptive Learning Vector Quantization (LVQ) predictor is designed to deal with different models of datasets that are classified into balanced and imbalanced datasets. The accuracy of 93.88%, 90.03%, and 89.72% has been found on S. cerevisiae, H. pylori, and independent datasets, respectively. The results of various experiments indicate the efficiency and validity of the method. © 2013 Published by Elsevier Ltd.

Fingerprints of Modified RNA Bases from Deep Sequencing Profiles.

PubMed

Kietrys, Anna M; Velema, Willem A; Kool, Eric T

2017-11-29

Posttranscriptional modifications of RNA bases are not only found in many noncoding RNAs but have also recently been identified in coding (messenger) RNAs as well. They require complex and laborious methods to locate, and many still lack methods for localized detection. Here we test the ability of next-generation sequencing (NGS) to detect and distinguish between ten modified bases in synthetic RNAs. We compare ultradeep sequencing patterns of modified bases, including miscoding, insertions and deletions (indels), and truncations, to unmodified bases in the same contexts. The data show widely varied responses to modification, ranging from no response, to high levels of mutations, insertions, deletions, and truncations. The patterns are distinct for several of the modifications, and suggest the future use of ultradeep sequencing as a fingerprinting strategy for locating and identifying modifications in cellular RNAs.

A Shellcode Detection Method Based on Full Native API Sequence and Support Vector Machine

NASA Astrophysics Data System (ADS)

Cheng, Yixuan; Fan, Wenqing; Huang, Wei; An, Jing

2017-09-01

Dynamic monitoring the behavior of a program is widely used to discriminate between benign program and malware. It is usually based on the dynamic characteristics of a program, such as API call sequence or API call frequency to judge. The key innovation of this paper is to consider the full Native API sequence and use the support vector machine to detect the shellcode. We also use the Markov chain to extract and digitize Native API sequence features. Our experimental results show that the method proposed in this paper has high accuracy and low detection rate.

Applications of a Sequence of Points in Teaching Linear Algebra, Numerical Methods and Discrete Mathematics

ERIC Educational Resources Information Center

Shi, Yixun

2009-01-01

Based on a sequence of points and a particular linear transformation generalized from this sequence, two recent papers (E. Mauch and Y. Shi, "Using a sequence of number pairs as an example in teaching mathematics". Math. Comput. Educ., 39 (2005), pp. 198-205; Y. Shi, "Case study projects for college mathematics courses based on a particular…

Extracting DNA words based on the sequence features: non-uniform distribution and integrity.

PubMed

Li, Zhi; Cao, Hongyan; Cui, Yuehua; Zhang, Yanbo

2016-01-25

DNA sequence can be viewed as an unknown language with words as its functional units. Given that most sequence alignment algorithms such as the motif discovery algorithms depend on the quality of background information about sequences, it is necessary to develop an ab initio algorithm for extracting the "words" based only on the DNA sequences. We considered that non-uniform distribution and integrity were two important features of a word, based on which we developed an ab initio algorithm to extract "DNA words" that have potential functional meaning. A Kolmogorov-Smirnov test was used for consistency test of uniform distribution of DNA sequences, and the integrity was judged by the sequence and position alignment. Two random base sequences were adopted as negative control, and an English book was used as positive control to verify our algorithm. We applied our algorithm to the genomes of Saccharomyces cerevisiae and 10 strains of Escherichia coli to show the utility of the methods. The results provide strong evidences that the algorithm is a promising tool for ab initio building a DNA dictionary. Our method provides a fast way for large scale screening of important DNA elements and offers potential insights into the understanding of a genome.

Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences | Center for Cancer Research

Cancer.gov

A graphical method is presented for displaying how binding proteins and other macromolecules interact with individual bases of nucleotide sequences. Characters representing the sequence are either oriented normally and placed above a line indicating favorable contact, or upside-down and placed below the line indicating unfavorable contact. The positive or negative height of

An Alu-based, MGB Eclipse real-time PCR method for quantitation of human DNA in forensic samples.

PubMed

Nicklas, Janice A; Buel, Eric

2005-09-01

The forensic community needs quick, reliable methods to quantitate human DNA in crime scene samples to replace the laborious and imprecise slot blot method. A real-time PCR based method has the possibility of allowing development of a faster and more quantitative assay. Alu sequences are primate-specific and are found in many copies in the human genome, making these sequences an excellent target or marker for human DNA. This paper describes the development of a real-time Alu sequence-based assay using MGB Eclipse primers and probes. The advantages of this assay are simplicity, speed, less hands-on-time and automated quantitation, as well as a large dynamic range (128 ng/microL to 0.5 pg/microL).

ParticleCall: A particle filter for base calling in next-generation sequencing systems

PubMed Central

2012-01-01

Background Next-generation sequencing systems are capable of rapid and cost-effective DNA sequencing, thus enabling routine sequencing tasks and taking us one step closer to personalized medicine. Accuracy and lengths of their reads, however, are yet to surpass those provided by the conventional Sanger sequencing method. This motivates the search for computationally efficient algorithms capable of reliable and accurate detection of the order of nucleotides in short DNA fragments from the acquired data. Results In this paper, we consider Illumina’s sequencing-by-synthesis platform which relies on reversible terminator chemistry and describe the acquired signal by reformulating its mathematical model as a Hidden Markov Model. Relying on this model and sequential Monte Carlo methods, we develop a parameter estimation and base calling scheme called ParticleCall. ParticleCall is tested on a data set obtained by sequencing phiX174 bacteriophage using Illumina’s Genome Analyzer II. The results show that the developed base calling scheme is significantly more computationally efficient than the best performing unsupervised method currently available, while achieving the same accuracy. Conclusions The proposed ParticleCall provides more accurate calls than the Illumina’s base calling algorithm, Bustard. At the same time, ParticleCall is significantly more computationally efficient than other recent schemes with similar performance, rendering it more feasible for high-throughput sequencing data analysis. Improvement of base calling accuracy will have immediate beneficial effects on the performance of downstream applications such as SNP and genotype calling. ParticleCall is freely available at https://sourceforge.net/projects/particlecall. PMID:22776067

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods.

PubMed

Ahrenfeldt, Johanne; Skaarup, Carina; Hasman, Henrik; Pedersen, Anders Gorm; Aarestrup, Frank Møller; Lund, Ole

2017-01-05

Whole genome sequencing (WGS) is increasingly used in diagnostics and surveillance of infectious diseases. A major application for WGS is to use the data for identifying outbreak clusters, and there is therefore a need for methods that can accurately and efficiently infer phylogenies from sequencing reads. In the present study we describe a new dataset that we have created for the purpose of benchmarking such WGS-based methods for epidemiological data, and also present an analysis where we use the data to compare the performance of some current methods. Our aim was to create a benchmark data set that mimics sequencing data of the sort that might be collected during an outbreak of an infectious disease. This was achieved by letting an E. coli hypermutator strain grow in the lab for 8 consecutive days, each day splitting the culture in two while also collecting samples for sequencing. The result is a data set consisting of 101 whole genome sequences with known phylogenetic relationship. Among the sequenced samples 51 correspond to internal nodes in the phylogeny because they are ancestral, while the remaining 50 correspond to leaves. We also used the newly created data set to compare three different online available methods that infer phylogenies from whole-genome sequencing reads: NDtree, CSI Phylogeny and REALPHY. One complication when comparing the output of these methods with the known phylogeny is that phylogenetic methods typically build trees where all observed sequences are placed as leafs, even though some of them are in fact ancestral. We therefore devised a method for post processing the inferred trees by collapsing short branches (thus relocating some leafs to internal nodes), and also present two new measures of tree similarity that takes into account the identity of both internal and leaf nodes. Based on this analysis we find that, among the investigated methods, CSI Phylogeny had the best performance, correctly identifying 73% of all branches in the tree and 71% of all clades. We have made all data from this experiment (raw sequencing reads, consensus whole-genome sequences, as well as descriptions of the known phylogeny in a variety of formats) publicly available, with the hope that other groups may find this data useful for benchmarking and exploring the performance of epidemiological methods. All data is freely available at: https://cge.cbs.dtu.dk/services/evolution_data.php .

A Segmentation Method for Lung Parenchyma Image Sequences Based on Superpixels and a Self-Generating Neural Forest

PubMed Central

Liao, Xiaolei; Zhao, Juanjuan; Jiao, Cheng; Lei, Lei; Qiang, Yan; Cui, Qiang

2016-01-01

Background Lung parenchyma segmentation is often performed as an important pre-processing step in the computer-aided diagnosis of lung nodules based on CT image sequences. However, existing lung parenchyma image segmentation methods cannot fully segment all lung parenchyma images and have a slow processing speed, particularly for images in the top and bottom of the lung and the images that contain lung nodules. Method Our proposed method first uses the position of the lung parenchyma image features to obtain lung parenchyma ROI image sequences. A gradient and sequential linear iterative clustering algorithm (GSLIC) for sequence image segmentation is then proposed to segment the ROI image sequences and obtain superpixel samples. The SGNF, which is optimized by a genetic algorithm (GA), is then utilized for superpixel clustering. Finally, the grey and geometric features of the superpixel samples are used to identify and segment all of the lung parenchyma image sequences. Results Our proposed method achieves higher segmentation precision and greater accuracy in less time. It has an average processing time of 42.21 seconds for each dataset and an average volume pixel overlap ratio of 92.22 ± 4.02% for four types of lung parenchyma image sequences. PMID:27532214

Determining protein function and interaction from genome analysis

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Thompson, Michael J.; Pellegrini, Matteo; Yeates, Todd O.

2004-08-03

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Assigning protein functions by comparative genome analysis protein phylogenetic profiles

DOEpatents

Pellegrini, Matteo; Marcotte, Edward M.; Thompson, Michael J.; Eisenberg, David; Grothe, Robert; Yeates, Todd O.

2003-05-13

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

DOE PAGES

Rosen, Gail L.; Polikar, Robi; Caseiro, Diamantino A.; ...

2011-01-01

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for theirmore » ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.« less

Molecular testing for familial hypercholesterolaemia-associated mutations in a UK-based cohort: development of an NGS-based method and comparison with multiplex polymerase chain reaction and oligonucleotide arrays.

PubMed

Reiman, Anne; Pandey, Sarojini; Lloyd, Kate L; Dyer, Nigel; Khan, Mike; Crockard, Martin; Latten, Mark J; Watson, Tracey L; Cree, Ian A; Grammatopoulos, Dimitris K

2016-11-01

Background Detection of disease-associated mutations in patients with familial hypercholesterolaemia is crucial for early interventions to reduce risk of cardiovascular disease. Screening for these mutations represents a methodological challenge since more than 1200 different causal mutations in the low-density lipoprotein receptor has been identified. A number of methodological approaches have been developed for screening by clinical diagnostic laboratories. Methods Using primers targeting, the low-density lipoprotein receptor, apolipoprotein B, and proprotein convertase subtilisin/kexin type 9, we developed a novel Ion Torrent-based targeted re-sequencing method. We validated this in a West Midlands-UK small cohort of 58 patients screened in parallel with other mutation-targeting methods, such as multiplex polymerase chain reaction (Elucigene FH20), oligonucleotide arrays (Randox familial hypercholesterolaemia array) or the Illumina next-generation sequencing platform. Results In this small cohort, the next-generation sequencing method achieved excellent analytical performance characteristics and showed 100% and 89% concordance with the Randox array and the Elucigene FH20 assay. Investigation of the discrepant results identified two cases of mutation misclassification of the Elucigene FH20 multiplex polymerase chain reaction assay. A number of novel mutations not previously reported were also identified by the next-generation sequencing method. Conclusions Ion Torrent-based next-generation sequencing can deliver a suitable alternative for the molecular investigation of familial hypercholesterolaemia patients, especially when comprehensive mutation screening for rare or unknown mutations is required.

Improving the time efficiency of the Fourier synthesis method for slice selection in magnetic resonance imaging.

PubMed

Tahayori, B; Khaneja, N; Johnston, L A; Farrell, P M; Mareels, I M Y

2016-01-01

The design of slice selective pulses for magnetic resonance imaging can be cast as an optimal control problem. The Fourier synthesis method is an existing approach to solve these optimal control problems. In this method the gradient field as well as the excitation field are switched rapidly and their amplitudes are calculated based on a Fourier series expansion. Here, we provide a novel insight into the Fourier synthesis method via representing the Bloch equation in spherical coordinates. Based on the spherical Bloch equation, we propose an alternative sequence of pulses that can be used for slice selection which is more time efficient compared to the original method. Simulation results demonstrate that while the performance of both methods is approximately the same, the required time for the proposed sequence of pulses is half of the original sequence of pulses. Furthermore, the slice selectivity of both sequences of pulses changes with radio frequency field inhomogeneities in a similar way. We also introduce a measure, referred to as gradient complexity, to compare the performance of both sequences of pulses. This measure indicates that for a desired level of uniformity in the excited slice, the gradient complexity for the proposed sequence of pulses is less than the original sequence. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

UV-Visible Spectroscopy-Based Quantification of Unlabeled DNA Bound to Gold Nanoparticles.

PubMed

Baldock, Brandi L; Hutchison, James E

2016-12-20

DNA-functionalized gold nanoparticles have been increasingly applied as sensitive and selective analytical probes and biosensors. The DNA ligands bound to a nanoparticle dictate its reactivity, making it essential to know the type and number of DNA strands bound to the nanoparticle surface. Existing methods used to determine the number of DNA strands per gold nanoparticle (AuNP) require that the sequences be fluorophore-labeled, which may affect the DNA surface coverage and reactivity of the nanoparticle and/or require specialized equipment and other fluorophore-containing reagents. We report a UV-visible-based method to conveniently and inexpensively determine the number of DNA strands attached to AuNPs of different core sizes. When this method is used in tandem with a fluorescence dye assay, it is possible to determine the ratio of two unlabeled sequences of different lengths bound to AuNPs. Two sizes of citrate-stabilized AuNPs (5 and 12 nm) were functionalized with mixtures of short (5 base) and long (32 base) disulfide-terminated DNA sequences, and the ratios of sequences bound to the AuNPs were determined using the new method. The long DNA sequence was present as a lower proportion of the ligand shell than in the ligand exchange mixture, suggesting it had a lower propensity to bind the AuNPs than the short DNA sequence. The ratio of DNA sequences bound to the AuNPs was not the same for the large and small AuNPs, which suggests that the radius of curvature had a significant influence on the assembly of DNA strands onto the AuNPs.

The limits of protein sequence comparison?

PubMed Central

Pearson, William R; Sierk, Michael L

2010-01-01

Modern sequence alignment algorithms are used routinely to identify homologous proteins, proteins that share a common ancestor. Homologous proteins always share similar structures and often have similar functions. Over the past 20 years, sequence comparison has become both more sensitive, largely because of profile-based methods, and more reliable, because of more accurate statistical estimates. As sequence and structure databases become larger, and comparison methods become more powerful, reliable statistical estimates will become even more important for distinguishing similarities that are due to homology from those that are due to analogy (convergence). The newest sequence alignment methods are more sensitive than older methods, but more accurate statistical estimates are needed for their full power to be realized. PMID:15919194

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Whole genome sequence analysis of unidentified genetically modified papaya for development of a specific detection method.

PubMed

Nakamura, Kosuke; Kondo, Kazunari; Akiyama, Hiroshi; Ishigaki, Takumi; Noguchi, Akio; Katsumata, Hiroshi; Takasaki, Kazuto; Futo, Satoshi; Sakata, Kozue; Fukuda, Nozomi; Mano, Junichi; Kitta, Kazumi; Tanaka, Hidenori; Akashi, Ryo; Nishimaki-Mogami, Tomoko

2016-08-15

Identification of transgenic sequences in an unknown genetically modified (GM) papaya (Carica papaya L.) by whole genome sequence analysis was demonstrated. Whole genome sequence data were generated for a GM-positive fresh papaya fruit commodity detected in monitoring using real-time polymerase chain reaction (PCR). The sequences obtained were mapped against an open database for papaya genome sequence. Transgenic construct- and event-specific sequences were identified as a GM papaya developed to resist infection from a Papaya ringspot virus. Based on the transgenic sequences, a specific real-time PCR detection method for GM papaya applicable to various food commodities was developed. Whole genome sequence analysis enabled identifying unknown transgenic construct- and event-specific sequences in GM papaya and development of a reliable method for detecting them in papaya food commodities. Copyright © 2016 Elsevier Ltd. All rights reserved.

PSS-3D1D: an improved 3D1D profile method of protein fold recognition for the annotation of twilight zone sequences.

PubMed

Ganesan, K; Parthasarathy, S

2011-12-01

Annotation of any newly determined protein sequence depends on the pairwise sequence identity with known sequences. However, for the twilight zone sequences which have only 15-25% identity, the pair-wise comparison methods are inadequate and the annotation becomes a challenging task. Such sequences can be annotated by using methods that recognize their fold. Bowie et al. described a 3D1D profile method in which the amino acid sequences that fold into a known 3D structure are identified by their compatibility to that known 3D structure. We have improved the above method by using the predicted secondary structure information and employ it for fold recognition from the twilight zone sequences. In our Protein Secondary Structure 3D1D (PSS-3D1D) method, a score (w) for the predicted secondary structure of the query sequence is included in finding the compatibility of the query sequence to the known fold 3D structures. In the benchmarks, the PSS-3D1D method shows a maximum of 21% improvement in predicting correctly the α + β class of folds from the sequences with twilight zone level of identity, when compared with the 3D1D profile method. Hence, the PSS-3D1D method could offer more clues than the 3D1D method for the annotation of twilight zone sequences. The web based PSS-3D1D method is freely available in the PredictFold server at http://bioinfo.bdu.ac.in/servers/ .

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Wang, Xin; Hu, Chao

2016-10-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on POME(the principle of maximum entropy), target candidates are iteratively segmented. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

AmpliVar: mutation detection in high-throughput sequence from amplicon-based libraries.

PubMed

Hsu, Arthur L; Kondrashova, Olga; Lunke, Sebastian; Love, Clare J; Meldrum, Cliff; Marquis-Nicholson, Renate; Corboy, Greg; Pham, Kym; Wakefield, Matthew; Waring, Paul M; Taylor, Graham R

2015-04-01

Conventional means of identifying variants in high-throughput sequencing align each read against a reference sequence, and then call variants at each position. Here, we demonstrate an orthogonal means of identifying sequence variation by grouping the reads as amplicons prior to any alignment. We used AmpliVar to make key-value hashes of sequence reads and group reads as individual amplicons using a table of flanking sequences. Low-abundance reads were removed according to a selectable threshold, and reads above this threshold were aligned as groups, rather than as individual reads, permitting the use of sensitive alignment tools. We show that this approach is more sensitive, more specific, and more computationally efficient than comparable methods for the analysis of amplicon-based high-throughput sequencing data. The method can be extended to enable alignment-free confirmation of variants seen in hybridization capture target-enrichment data. © 2015 WILEY PERIODICALS, INC.

Comparison of base composition analysis and Sanger sequencing of mitochondrial DNA for four U.S. population groups.

PubMed

Kiesler, Kevin M; Coble, Michael D; Hall, Thomas A; Vallone, Peter M

2014-01-01

A set of 711 samples from four U.S. population groups was analyzed using a novel mass spectrometry based method for mitochondrial DNA (mtDNA) base composition profiling. Comparison of the mass spectrometry results with Sanger sequencing derived data yielded a concordance rate of 99.97%. Length heteroplasmy was identified in 46% of samples and point heteroplasmy was observed in 6.6% of samples in the combined mass spectral and Sanger data set. Using discrimination capacity as a metric, Sanger sequencing of the full control region had the highest discriminatory power, followed by the mass spectrometry base composition method, which was more discriminating than Sanger sequencing of just the hypervariable regions. This trend is in agreement with the number of nucleotides covered by each of the three assays. Published by Elsevier Ireland Ltd.

RNA-ID, a highly sensitive and robust method to identify cis-regulatory sequences using superfolder GFP and a fluorescence-based assay.

PubMed

Dean, Kimberly M; Grayhack, Elizabeth J

2012-12-01

We have developed a robust and sensitive method, called RNA-ID, to screen for cis-regulatory sequences in RNA using fluorescence-activated cell sorting (FACS) of yeast cells bearing a reporter in which expression of both superfolder green fluorescent protein (GFP) and yeast codon-optimized mCherry red fluorescent protein (RFP) is driven by the bidirectional GAL1,10 promoter. This method recapitulates previously reported progressive inhibition of translation mediated by increasing numbers of CGA codon pairs, and restoration of expression by introduction of a tRNA with an anticodon that base pairs exactly with the CGA codon. This method also reproduces effects of paromomycin and context on stop codon read-through. Five key features of this method contribute to its effectiveness as a selection for regulatory sequences: The system exhibits greater than a 250-fold dynamic range, a quantitative and dose-dependent response to known inhibitory sequences, exquisite resolution that allows nearly complete physical separation of distinct populations, and a reproducible signal between different cells transformed with the identical reporter, all of which are coupled with simple methods involving ligation-independent cloning, to create large libraries. Moreover, we provide evidence that there are sequences within a 9-nt library that cause reduced GFP fluorescence, suggesting that there are novel cis-regulatory sequences to be found even in this short sequence space. This method is widely applicable to the study of both RNA-mediated and codon-mediated effects on expression.

Methods for chromosome-specific staining

DOEpatents

Gray, Joe W.; Pinkel, Daniel

1995-01-01

Methods and compositions for chromosome-specific staining are provided. Compositions comprise heterogenous mixtures of labeled nucleic acid fragments having substantially complementary base sequences to unique sequence regions of the chromosomal DNA for which their associated staining reagent is specific. Methods include methods for making the chromosome-specific staining compositions of the invention, and methods for applying the staining compositions to chromosomes.

Overcoming Sequence Misalignments with Weighted Structural Superposition

PubMed Central

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

2012-01-01

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

Molecular Strain Typing of Mycobacterium tuberculosis: a Review of Frequently Used Methods

PubMed Central

2016-01-01

Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, remains one of the most serious global health problems. Molecular typing of M. tuberculosis has been used for various epidemiologic purposes as well as for clinical management. Currently, many techniques are available to type M. tuberculosis. Choosing the most appropriate technique in accordance with the existing laboratory conditions and the specific features of the geographic region is important. Insertion sequence IS6110-based restriction fragment length polymorphism (RFLP) analysis is considered the gold standard for the molecular epidemiologic investigations of tuberculosis. However, other polymerase chain reaction-based methods such as spacer oligonucleotide typing (spoligotyping), which detects 43 spacer sequence-interspersing direct repeats (DRs) in the genomic DR region; mycobacterial interspersed repetitive units–variable number tandem repeats, (MIRU-VNTR), which determines the number and size of tandem repetitive DNA sequences; repetitive-sequence-based PCR (rep-PCR), which provides high-throughput genotypic fingerprinting of multiple Mycobacterium species; and the recently developed genome-based whole genome sequencing methods demonstrate similar discriminatory power and greater convenience. This review focuses on techniques frequently used for the molecular typing of M. tuberculosis and discusses their general aspects and applications. PMID:27709842

Molecular Strain Typing of Mycobacterium tuberculosis: a Review of Frequently Used Methods.

PubMed

Ei, Phyu Win; Aung, Wah Wah; Lee, Jong Seok; Choi, Go Eun; Chang, Chulhun L

2016-11-01

Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, remains one of the most serious global health problems. Molecular typing of M. tuberculosis has been used for various epidemiologic purposes as well as for clinical management. Currently, many techniques are available to type M. tuberculosis. Choosing the most appropriate technique in accordance with the existing laboratory conditions and the specific features of the geographic region is important. Insertion sequence IS6110-based restriction fragment length polymorphism (RFLP) analysis is considered the gold standard for the molecular epidemiologic investigations of tuberculosis. However, other polymerase chain reaction-based methods such as spacer oligonucleotide typing (spoligotyping), which detects 43 spacer sequence-interspersing direct repeats (DRs) in the genomic DR region; mycobacterial interspersed repetitive units-variable number tandem repeats, (MIRU-VNTR), which determines the number and size of tandem repetitive DNA sequences; repetitive-sequence-based PCR (rep-PCR), which provides high-throughput genotypic fingerprinting of multiple Mycobacterium species; and the recently developed genome-based whole genome sequencing methods demonstrate similar discriminatory power and greater convenience. This review focuses on techniques frequently used for the molecular typing of M. tuberculosis and discusses their general aspects and applications.

Detecting the borders between coding and non-coding DNA regions in prokaryotes based on recursive segmentation and nucleotide doublets statistics

PubMed Central

2012-01-01

Background Detecting the borders between coding and non-coding regions is an essential step in the genome annotation. And information entropy measures are useful for describing the signals in genome sequence. However, the accuracies of previous methods of finding borders based on entropy segmentation method still need to be improved. Methods In this study, we first applied a new recursive entropic segmentation method on DNA sequences to get preliminary significant cuts. A 22-symbol alphabet is used to capture the differential composition of nucleotide doublets and stop codon patterns along three phases in both DNA strands. This process requires no prior training datasets. Results Comparing with the previous segmentation methods, the experimental results on three bacteria genomes, Rickettsia prowazekii, Borrelia burgdorferi and E.coli, show that our approach improves the accuracy for finding the borders between coding and non-coding regions in DNA sequences. Conclusions This paper presents a new segmentation method in prokaryotes based on Jensen-Rényi divergence with a 22-symbol alphabet. For three bacteria genomes, comparing to A12_JR method, our method raised the accuracy of finding the borders between protein coding and non-coding regions in DNA sequences. PMID:23282225

Automatic prediction of protein domains from sequence information using a hybrid learning system.

PubMed

Nagarajan, Niranjan; Yona, Golan

2004-06-12

We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using a neural network. The output is further smoothed and post-processed using a probabilistic model to predict the most likely transition positions between domains. The method was assessed using the domain definitions in SCOP and CATH for proteins of known structure and was compared with several other existing methods. Our method performs well both in terms of accuracy and sensitivity. It improves significantly over the best methods available, even some of the semi-manual ones, while being fully automatic. Our method can also be used to suggest and verify domain partitions based on structural data. A few examples of predicted domain definitions and alternative partitions, as suggested by our method, are also discussed. An online domain-prediction server is available at http://biozon.org/tools/domains/

Physical-chemical property based sequence motifs and methods regarding same

DOEpatents

Braun, Werner [Friendswood, TX; Mathura, Venkatarajan S [Sarasota, FL; Schein, Catherine H [Friendswood, TX

2008-09-09

A data analysis system, program, and/or method, e.g., a data mining/data exploration method, using physical-chemical property motifs. For example, a sequence database may be searched for identifying segments thereof having physical-chemical properties similar to the physical-chemical property motifs.

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

PubMed

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

2009-01-01

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

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

PubMed Central

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

2010-01-01

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

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

PubMed

Yin, Changchuan

2015-04-01

To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

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

Using structure to explore the sequence alignment space of remote homologs.

PubMed

Kuziemko, Andrew; Honig, Barry; Petrey, Donald

2011-10-01

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is "optimal" in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are "suboptimal" in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for "modelability", we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended.

Iterative pass optimization of sequence data

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

PubMed Central

Freitas, Tracey Allen K.; Li, Po-E; Scholz, Matthew B.; Chain, Patrick S. G.

2015-01-01

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. PMID:25765641

Species Identification of Bovine, Ovine and Porcine Type 1 Collagen; Comparing Peptide Mass Fingerprinting and LC-Based Proteomics Methods.

PubMed

Buckley, Mike

2016-03-24

Collagen is one of the most ubiquitous proteins in the animal kingdom and the dominant protein in extracellular tissues such as bone, skin and other connective tissues in which it acts primarily as a supporting scaffold. It has been widely investigated scientifically, not only as a biomedical material for regenerative medicine, but also for its role as a food source for both humans and livestock. Due to the long-term stability of collagen, as well as its abundance in bone, it has been proposed as a source of biomarkers for species identification not only for heat- and pressure-rendered animal feed but also in ancient archaeological and palaeontological specimens, typically carried out by peptide mass fingerprinting (PMF) as well as in-depth liquid chromatography (LC)-based tandem mass spectrometric methods. Through the analysis of the three most common domesticates species, cow, sheep, and pig, this research investigates the advantages of each approach over the other, investigating sites of sequence variation with known functional properties of the collagen molecule. Results indicate that the previously identified species biomarkers through PMF analysis are not among the most variable type 1 collagen peptides present in these tissues, the latter of which can be detected by LC-based methods. However, it is clear that the highly repetitive sequence motif of collagen throughout the molecule, combined with the variability of the sites and relative abundance levels of hydroxylation, can result in high scoring false positive peptide matches using these LC-based methods. Additionally, the greater alpha 2(I) chain sequence variation, in comparison to the alpha 1(I) chain, did not appear to be specific to any particular functional properties, implying that intra-chain functional constraints on sequence variation are not as great as inter-chain constraints. However, although some of the most variable peptides were only observed in LC-based methods, until the range of publicly available collagen sequences improves, the simplicity of the PMF approach and suitable range of peptide sequence variation observed makes it the ideal method for initial taxonomic identification prior to further analysis by LC-based methods only when required.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode

NASA Astrophysics Data System (ADS)

Zhang, Ji; Li, Tao; Zheng, Shiqiang; Li, Yiyong

2015-03-01

To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48+/-42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.

SeqRate: sequence-based protein folding type classification and rates prediction

PubMed Central

2010-01-01

Background Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Most previous methods of predicting protein folding rate require the tertiary structure of a protein as an input. And most methods do not distinguish the different kinetic nature (two-state folding or multi-state folding) of the proteins. Here we developed a method, SeqRate, to predict both protein folding kinetic type (two-state versus multi-state) and real-value folding rate using sequence length, amino acid composition, contact order, contact number, and secondary structure information predicted from only protein sequence with support vector machines. Results We systematically studied the contributions of individual features to folding rate prediction. On a standard benchmark dataset, the accuracy of folding kinetic type classification is 80%. The Pearson correlation coefficient and the mean absolute difference between predicted and experimental folding rates (sec-1) in the base-10 logarithmic scale are 0.81 and 0.79 for two-state protein folders, and 0.80 and 0.68 for three-state protein folders. SeqRate is the first sequence-based method for protein folding type classification and its accuracy of fold rate prediction is improved over previous sequence-based methods. Its performance can be further enhanced with additional information, such as structure-based geometric contacts, as inputs. Conclusions Both the web server and software of predicting folding rate are publicly available at http://casp.rnet.missouri.edu/fold_rate/index.html. PMID:20438647

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

PubMed Central

Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David

2001-01-01

Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681

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.

Single-Molecule Electrical Random Resequencing of DNA and RNA

NASA Astrophysics Data System (ADS)

Ohshiro, Takahito; Matsubara, Kazuki; Tsutsui, Makusu; Furuhashi, Masayuki; Taniguchi, Masateru; Kawai, Tomoji

2012-07-01

Two paradigm shifts in DNA sequencing technologies--from bulk to single molecules and from optical to electrical detection--are expected to realize label-free, low-cost DNA sequencing that does not require PCR amplification. It will lead to development of high-throughput third-generation sequencing technologies for personalized medicine. Although nanopore devices have been proposed as third-generation DNA-sequencing devices, a significant milestone in these technologies has been attained by demonstrating a novel technique for resequencing DNA using electrical signals. Here we report single-molecule electrical resequencing of DNA and RNA using a hybrid method of identifying single-base molecules via tunneling currents and random sequencing. Our method reads sequences of nine types of DNA oligomers. The complete sequence of 5'-UGAGGUA-3' from the let-7 microRNA family was also identified by creating a composite of overlapping fragment sequences, which was randomly determined using tunneling current conducted by single-base molecules as they passed between a pair of nanoelectrodes.

Genealogy-based methods for inference of historical recombination and gene flow and their application in Saccharomyces cerevisiae.

PubMed

Jenkins, Paul A; Song, Yun S; Brem, Rachel B

2012-01-01

Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance.

Genealogy-Based Methods for Inference of Historical Recombination and Gene Flow and Their Application in Saccharomyces cerevisiae

PubMed Central

Jenkins, Paul A.; Song, Yun S.; Brem, Rachel B.

2012-01-01

Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance. PMID:23226196

Flow cytometric detection method for DNA samples

DOEpatents

Nasarabadi, Shanavaz [Livermore, CA; Langlois, Richard G [Livermore, CA; Venkateswaran, Kodumudi S [Round Rock, TX

2011-07-05

Disclosed herein are two methods for rapid multiplex analysis to determine the presence and identity of target DNA sequences within a DNA sample. Both methods use reporting DNA sequences, e.g., modified conventional Taqman.RTM. probes, to combine multiplex PCR amplification with microsphere-based hybridization using flow cytometry means of detection. Real-time PCR detection can also be incorporated. The first method uses a cyanine dye, such as, Cy3.TM., as the reporter linked to the 5' end of a reporting DNA sequence. The second method positions a reporter dye, e.g., FAM.TM. on the 3' end of the reporting DNA sequence and a quencher dye, e.g., TAMRA.TM., on the 5' end.

Flow cytometric detection method for DNA samples

DOEpatents

Nasarabadi, Shanavaz [Livermore, CA; Langlois, Richard G [Livermore, CA; Venkateswaran, Kodumudi S [Livermore, CA

2006-08-01

Disclosed herein are two methods for rapid multiplex analysis to determine the presence and identity of target DNA sequences within a DNA sample. Both methods use reporting DNA sequences, e.g., modified conventional Taqman.RTM. probes, to combine multiplex PCR amplification with microsphere-based hybridization using flow cytometry means of detection. Real-time PCR detection can also be incorporated. The first method uses a cyanine dye, such as, Cy3.TM., as the reporter linked to the 5' end of a reporting DNA sequence. The second method positions a reporter dye, e.g., FAM, on the 3' end of the reporting DNA sequence and a quencher dye, e.g., TAMRA, on the 5' end.

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

PubMed

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

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

PubMed

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

2017-01-01

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

Methods and compositions for chromosome-specific staining

DOEpatents

Gray, Joe W.; Pinkel, Daniel

2003-07-22

Methods and compositions for chromosome-specific staining are provided. Compositions comprise heterogenous mixtures of labeled nucleic acid fragments having substantially complementary base sequences to unique sequence regions of the chromosomal DNA for which their associated staining reagent is specific. Methods include methods for making the chromosome-specific staining compositions of the invention, and methods for applying the staining compositions to chromosomes.

A novel alignment-free method for detection of lateral genetic transfer based on TF-IDF.

PubMed

Cong, Yingnan; Chan, Yao-Ban; Ragan, Mark A

2016-07-25

Lateral genetic transfer (LGT) plays an important role in the evolution of microbes. Existing computational methods for detecting genomic regions of putative lateral origin scale poorly to large data. Here, we propose a novel method based on TF-IDF (Term Frequency-Inverse Document Frequency) statistics to detect not only regions of lateral origin, but also their origin and direction of transfer, in sets of hierarchically structured nucleotide or protein sequences. This approach is based on the frequency distributions of k-mers in the sequences. If a set of contiguous k-mers appears sufficiently more frequently in another phyletic group than in its own, we infer that they have been transferred from the first group to the second. We performed rigorous tests of TF-IDF using simulated and empirical datasets. With the simulated data, we tested our method under different parameter settings for sequence length, substitution rate between and within groups and post-LGT, deletion rate, length of transferred region and k size, and found that we can detect LGT events with high precision and recall. Our method performs better than an established method, ALFY, which has high recall but low precision. Our method is efficient, with runtime increasing approximately linearly with sequence length.

Mapping the binding site of aflatoxin B/sub 1/ in DNA: systematic analysis of the reactivity of aflatoxin B/sub 1/ with guanines in different DNA sequences

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

Benasutti, M.; Ejadi, S.; Whitlow, M.D.

The mutagenic and carcinogenic chemical aflatoxin B/sub 1/ (AFB/sub 1/) reacts almost exclusively at the N(7)-position of guanine following activation to its reactive form, the 8,9-epoxide (AFB/sub 1/ oxide). In general N(7)-guanine adducts yield DNA strand breaks when heated in base, a property that serves as the basis for the Maxam-Gilbert DNA sequencing reaction specific for guanine. Using DNA sequencing methods, other workers have shown that AFB/sub 1/ oxide gives strand breaks at positions of guanines; however, the guanine bands varied in intensity. This phenomenon has been used to infer that AFB/sub 1/ oxide prefers to react with guanines inmore » some sequence contexts more than in others and has been referred to as sequence specificity of binding. Herein, data on the reaction of AFB/sub 1/ oxide with several synthetic DNA polymers with different sequences are presented, and (following hydrolysis) adduct levels are determine by high-pressure liquid chromatography. These results reveal that for AFB/sub 1/ oxide (1) the N(7)-guanine adduct is the major adduct found in all of the DNA polymers, (2) adduct levels vary in different sequences, and, thus, sequence specificity is also observed by this more direct method, and (3) the intensity of bands in DNA sequencing gels is likely to reflect adduct levels formed at the N(7)-position of guanine. Knowing this, a reinvestigation of the reactivity of guanines in different DNA sequences using DNA sequencing methods was undertaken. Methods are developed to determine the X (5'-side) base and the Y (3'-side) base are most influential in determining guanine reactivity. These rules in conjunction with molecular modeling studies were used to assess the binding sites that might be utilized by AFB/sub 1/ oxide in its reaction with DNA.« less

Parametric and non-parametric masking of randomness in sequence alignments can be improved and leads to better resolved trees.

PubMed

Kück, Patrick; Meusemann, Karen; Dambach, Johannes; Thormann, Birthe; von Reumont, Björn M; Wägele, Johann W; Misof, Bernhard

2010-03-31

Methods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective. ALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict. Alignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Fast alignment-free sequence comparison using spaced-word frequencies.

PubMed

Leimeister, Chris-Andre; Boden, Marcus; Horwege, Sebastian; Lindner, Sebastian; Morgenstern, Burkhard

2014-07-15

Alignment-free methods for sequence comparison are increasingly used for genome analysis and phylogeny reconstruction; they circumvent various difficulties of traditional alignment-based approaches. In particular, alignment-free methods are much faster than pairwise or multiple alignments. They are, however, less accurate than methods based on sequence alignment. Most alignment-free approaches work by comparing the word composition of sequences. A well-known problem with these methods is that neighbouring word matches are far from independent. To reduce the statistical dependency between adjacent word matches, we propose to use 'spaced words', defined by patterns of 'match' and 'don't care' positions, for alignment-free sequence comparison. We describe a fast implementation of this approach using recursive hashing and bit operations, and we show that further improvements can be achieved by using multiple patterns instead of single patterns. To evaluate our approach, we use spaced-word frequencies as a basis for fast phylogeny reconstruction. Using real-world and simulated sequence data, we demonstrate that our multiple-pattern approach produces better phylogenies than approaches relying on contiguous words. Our program is freely available at http://spaced.gobics.de/. © The Author 2014. Published by Oxford University Press.

Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags.

PubMed

Wu, Gary D; Lewis, James D; Hoffmann, Christian; Chen, Ying-Yu; Knight, Rob; Bittinger, Kyle; Hwang, Jennifer; Chen, Jun; Berkowsky, Ronald; Nessel, Lisa; Li, Hongzhe; Bushman, Frederic D

2010-07-30

Intense interest centers on the role of the human gut microbiome in health and disease, but optimal methods for analysis are still under development. Here we present a study of methods for surveying bacterial communities in human feces using 454/Roche pyrosequencing of 16S rRNA gene tags. We analyzed fecal samples from 10 individuals and compared methods for storage, DNA purification and sequence acquisition. To assess reproducibility, we compared samples one cm apart on a single stool specimen for each individual. To analyze storage methods, we compared 1) immediate freezing at -80 degrees C, 2) storage on ice for 24 or 3) 48 hours. For DNA purification methods, we tested three commercial kits and bead beating in hot phenol. Variations due to the different methodologies were compared to variation among individuals using two approaches--one based on presence-absence information for bacterial taxa (unweighted UniFrac) and the other taking into account their relative abundance (weighted UniFrac). In the unweighted analysis relatively little variation was associated with the different analytical procedures, and variation between individuals predominated. In the weighted analysis considerable variation was associated with the purification methods. Particularly notable was improved recovery of Firmicutes sequences using the hot phenol method. We also carried out surveys of the effects of different 454 sequencing methods (FLX versus Titanium) and amplification of different 16S rRNA variable gene segments. Based on our findings we present recommendations for protocols to collect, process and sequence bacterial 16S rDNA from fecal samples--some major points are 1) if feasible, bead-beating in hot phenol or use of the PSP kit improves recovery; 2) storage methods can be adjusted based on experimental convenience; 3) unweighted (presence-absence) comparisons are less affected by lysis method.

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens

PubMed Central

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-01-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue® mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents. PMID:22735701

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens.

PubMed

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-08-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents.

Molecular beacon sequence design algorithm.

PubMed

Monroe, W Todd; Haselton, Frederick R

2003-01-01

A method based on Web-based tools is presented to design optimally functioning molecular beacons. Molecular beacons, fluorogenic hybridization probes, are a powerful tool for the rapid and specific detection of a particular nucleic acid sequence. However, their synthesis costs can be considerable. Since molecular beacon performance is based on its sequence, it is imperative to rationally design an optimal sequence before synthesis. The algorithm presented here uses simple Microsoft Excel formulas and macros to rank candidate sequences. This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.

Method for sequencing DNA base pairs

DOEpatents

Sessler, Andrew M.; Dawson, John

1993-01-01

The base pairs of a DNA structure are sequenced with the use of a scanning tunneling microscope (STM). The DNA structure is scanned by the STM probe tip, and, as it is being scanned, the DNA structure is separately subjected to a sequence of infrared radiation from four different sources, each source being selected to preferentially excite one of the four different bases in the DNA structure. Each particular base being scanned is subjected to such sequence of infrared radiation from the four different sources as that particular base is being scanned. The DNA structure as a whole is separately imaged for each subjection thereof to radiation from one only of each source.

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L. (Inventor); Howard, Andrew B. (Inventor); Reinhart, Rene Felix (Inventor); Aghazarian, Hrand (Inventor); Rankin, Arturo (Inventor)

2017-01-01

Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

NASA Technical Reports Server (NTRS)

Aghazarian, Hrand (Inventor); Reinhart, Rene Felix (Inventor); Huntsberger, Terrance L. (Inventor); Rankin, Arturo (Inventor); Howard, Andrew B. (Inventor)

2015-01-01

Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

PubMed

Bastien, Olivier; Ortet, Philippe; Roy, Sylvaine; Maréchal, Eric

2005-03-10

Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

Degree sequence in message transfer

NASA Astrophysics Data System (ADS)

Yamuna, M.

2017-11-01

Message encryption is always an issue in current communication scenario. Methods are being devised using various domains. Graphs satisfy numerous unique properties which can be used for message transfer. In this paper, I propose a message encryption method based on degree sequence of graphs.

Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

PubMed

Garrido-Martín, Diego; Pazos, Florencio

2018-02-27

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.

SPlinted Ligation Adapter Tagging (SPLAT), a novel library preparation method for whole genome bisulphite sequencing

PubMed Central

Manlig, Erika; Wahlberg, Per

2017-01-01

Abstract Sodium bisulphite treatment of DNA combined with next generation sequencing (NGS) is a powerful combination for the interrogation of genome-wide DNA methylation profiles. Library preparation for whole genome bisulphite sequencing (WGBS) is challenging due to side effects of the bisulphite treatment, which leads to extensive DNA damage. Recently, a new generation of methods for bisulphite sequencing library preparation have been devised. They are based on initial bisulphite treatment of the DNA, followed by adaptor tagging of single stranded DNA fragments, and enable WGBS using low quantities of input DNA. In this study, we present a novel approach for quick and cost effective WGBS library preparation that is based on splinted adaptor tagging (SPLAT) of bisulphite-converted single-stranded DNA. Moreover, we validate SPLAT against three commercially available WGBS library preparation techniques, two of which are based on bisulphite treatment prior to adaptor tagging and one is a conventional WGBS method. PMID:27899585

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

HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

PubMed

Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

2014-08-01

As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

Reducing false positive incidental findings with ensemble genotyping and logistic regression-based variant filtering methods

PubMed Central

Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choi, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B.; Gupta, Neha; Kohane, Isaac S.; Green, Robert C.; Kong, Sek Won

2014-01-01

As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous SNVs; 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and ensemble genotyping would be essential to minimize false positive DNM candidates. PMID:24829188

Characterization and prediction of residues determining protein functional specificity.

PubMed

Capra, John A; Singh, Mona

2008-07-01

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

Software for pre-processing Illumina next-generation sequencing short read sequences

PubMed Central

2014-01-01

Background When compared to Sanger sequencing technology, next-generation sequencing (NGS) technologies are hindered by shorter sequence read length, higher base-call error rate, non-uniform coverage, and platform-specific sequencing artifacts. These characteristics lower the quality of their downstream analyses, e.g. de novo and reference-based assembly, by introducing sequencing artifacts and errors that may contribute to incorrect interpretation of data. Although many tools have been developed for quality control and pre-processing of NGS data, none of them provide flexible and comprehensive trimming options in conjunction with parallel processing to expedite pre-processing of large NGS datasets. Methods We developed ngsShoRT (next-generation sequencing Short Reads Trimmer), a flexible and comprehensive open-source software package written in Perl that provides a set of algorithms commonly used for pre-processing NGS short read sequences. We compared the features and performance of ngsShoRT with existing tools: CutAdapt, NGS QC Toolkit and Trimmomatic. We also compared the effects of using pre-processed short read sequences generated by different algorithms on de novo and reference-based assembly for three different genomes: Caenorhabditis elegans, Saccharomyces cerevisiae S288c, and Escherichia coli O157 H7. Results Several combinations of ngsShoRT algorithms were tested on publicly available Illumina GA II, HiSeq 2000, and MiSeq eukaryotic and bacteria genomic short read sequences with the focus on removing sequencing artifacts and low-quality reads and/or bases. Our results show that across three organisms and three sequencing platforms, trimming improved the mean quality scores of trimmed sequences. Using trimmed sequences for de novo and reference-based assembly improved assembly quality as well as assembler performance. In general, ngsShoRT outperformed comparable trimming tools in terms of trimming speed and improvement of de novo and reference-based assembly as measured by assembly contiguity and correctness. Conclusions Trimming of short read sequences can improve the quality of de novo and reference-based assembly and assembler performance. The parallel processing capability of ngsShoRT reduces trimming time and improves the memory efficiency when dealing with large datasets. We recommend combining sequencing artifacts removal, and quality score based read filtering and base trimming as the most consistent method for improving sequence quality and downstream assemblies. ngsShoRT source code, user guide and tutorial are available at http://research.bioinformatics.udel.edu/genomics/ngsShoRT/. ngsShoRT can be incorporated as a pre-processing step in genome and transcriptome assembly projects. PMID:24955109

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

PubMed

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

2010-02-01

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

Application of Quaternion in improving the quality of global sequence alignment scores for an ambiguous sequence target in Streptococcus pneumoniae DNA

NASA Astrophysics Data System (ADS)

Lestari, D.; Bustamam, A.; Novianti, T.; Ardaneswari, G.

2017-07-01

DNA sequence can be defined as a succession of letters, representing the order of nucleotides within DNA, using a permutation of four DNA base codes including adenine (A), guanine (G), cytosine (C), and thymine (T). The precise code of the sequences is determined using DNA sequencing methods and technologies, which have been developed since the 1970s and currently become highly developed, advanced and highly throughput sequencing technologies. So far, DNA sequencing has greatly accelerated biological and medical research and discovery. However, in some cases DNA sequencing could produce any ambiguous and not clear enough sequencing results that make them quite difficult to be determined whether these codes are A, T, G, or C. To solve these problems, in this study we can introduce other representation of DNA codes namely Quaternion Q = (PA, PT, PG, PC), where PA, PT, PG, PC are the probability of A, T, G, C bases that could appear in Q and PA + PT + PG + PC = 1. Furthermore, using Quaternion representations we are able to construct the improved scoring matrix for global sequence alignment processes, by applying a dot product method. Moreover, this scoring matrix produces better and higher quality of the match and mismatch score between two DNA base codes. In implementation, we applied the Needleman-Wunsch global sequence alignment algorithm using Octave, to analyze our target sequence which contains some ambiguous sequence data. The subject sequences are the DNA sequences of Streptococcus pneumoniae families obtained from the Genebank, meanwhile the target DNA sequence are received from our collaborator database. As the results we found the Quaternion representations improve the quality of the sequence alignment score and we can conclude that DNA sequence target has maximum similarity with Streptococcus pneumoniae.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Identification of Bacillus Probiotics Isolated from Soil Rhizosphere Using 16S rRNA, recA, rpoB Gene Sequencing and RAPD-PCR.

PubMed

Mohkam, Milad; Nezafat, Navid; Berenjian, Aydin; Mobasher, Mohammad Ali; Ghasemi, Younes

2016-03-01

Some Bacillus species, especially Bacillus subtilis and Bacillus pumilus groups, have highly similar 16S rRNA gene sequences, which are hard to identify based on 16S rDNA sequence analysis. To conquer this drawback, rpoB, recA sequence analysis along with randomly amplified polymorphic (RAPD) fingerprinting was examined as an alternative method for differentiating Bacillus species. The 16S rRNA, rpoB and recA genes were amplified via a polymerase chain reaction using their specific primers. The resulted PCR amplicons were sequenced, and phylogenetic analysis was employed by MEGA 6 software. Identification based on 16S rRNA gene sequencing was underpinned by rpoB and recA gene sequencing as well as RAPD-PCR technique. Subsequently, concatenation and phylogenetic analysis showed that extent of diversity and similarity were better obtained by rpoB and recA primers, which are also reinforced by RAPD-PCR methods. However, in one case, these approaches failed to identify one isolate, which in combination with the phenotypical method offsets this issue. Overall, RAPD fingerprinting, rpoB and recA along with concatenated genes sequence analysis discriminated closely related Bacillus species, which highlights the significance of the multigenic method in more precisely distinguishing Bacillus strains. This research emphasizes the benefit of RAPD fingerprinting, rpoB and recA sequence analysis superior to 16S rRNA gene sequence analysis for suitable and effective identification of Bacillus species as recommended for probiotic products.

A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA.

PubMed

Ludgate, Jackie L; Wright, James; Stockwell, Peter A; Morison, Ian M; Eccles, Michael R; Chatterjee, Aniruddha

2017-08-31

Formalin fixed paraffin embedded (FFPE) tumor samples are a major source of DNA from patients in cancer research. However, FFPE is a challenging material to work with due to macromolecular fragmentation and nucleic acid crosslinking. FFPE tissue particularly possesses challenges for methylation analysis and for preparing sequencing-based libraries relying on bisulfite conversion. Successful bisulfite conversion is a key requirement for sequencing-based methylation analysis. Here we describe a complete and streamlined workflow for preparing next generation sequencing libraries for methylation analysis from FFPE tissues. This includes, counting cells from FFPE blocks and extracting DNA from FFPE slides, testing bisulfite conversion efficiency with a polymerase chain reaction (PCR) based test, preparing reduced representation bisulfite sequencing libraries and massively parallel sequencing. The main features and advantages of this protocol are: An optimized method for extracting good quality DNA from FFPE tissues. An efficient bisulfite conversion and next generation sequencing library preparation protocol that uses 50 ng DNA from FFPE tissue. Incorporation of a PCR-based test to assess bisulfite conversion efficiency prior to sequencing. We provide a complete workflow and an integrated protocol for performing DNA methylation analysis at the genome-scale and we believe this will facilitate clinical epigenetic research that involves the use of FFPE tissue.

Sequence comparison alignment-free approach based on suffix tree and L-words frequency.

PubMed

Soares, Inês; Goios, Ana; Amorim, António

2012-01-01

The vast majority of methods available for sequence comparison rely on a first sequence alignment step, which requires a number of assumptions on evolutionary history and is sometimes very difficult or impossible to perform due to the abundance of gaps (insertions/deletions). In such cases, an alternative alignment-free method would prove valuable. Our method starts by a computation of a generalized suffix tree of all sequences, which is completed in linear time. Using this tree, the frequency of all possible words with a preset length L-L-words--in each sequence is rapidly calculated. Based on the L-words frequency profile of each sequence, a pairwise standard Euclidean distance is then computed producing a symmetric genetic distance matrix, which can be used to generate a neighbor joining dendrogram or a multidimensional scaling graph. We present an improvement to word counting alignment-free approaches for sequence comparison, by determining a single optimal word length and combining suffix tree structures to the word counting tasks. Our approach is, thus, a fast and simple application that proved to be efficient and powerful when applied to mitochondrial genomes. The algorithm was implemented in Python language and is freely available on the web.

Research and Implementation of Tibetan Word Segmentation Based on Syllable Methods

NASA Astrophysics Data System (ADS)

Jiang, Jing; Li, Yachao; Jiang, Tao; Yu, Hongzhi

2018-03-01

Tibetan word segmentation (TWS) is an important problem in Tibetan information processing, while abbreviated word recognition is one of the key and most difficult problems in TWS. Most of the existing methods of Tibetan abbreviated word recognition are rule-based approaches, which need vocabulary support. In this paper, we propose a method based on sequence tagging model for abbreviated word recognition, and then implement in TWS systems with sequence labeling models. The experimental results show that our abbreviated word recognition method is fast and effective and can be combined easily with the segmentation model. This significantly increases the effect of the Tibetan word segmentation.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

Historical feature pattern extraction based network attack situation sensing algorithm.

PubMed

Zeng, Yong; Liu, Dacheng; Lei, Zhou

2014-01-01

The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

PubMed Central

Zeng, Yong; Liu, Dacheng; Lei, Zhou

2014-01-01

The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously. PMID:24892054

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

PubMed

Zhao, Zijian; Voros, Sandrine; Weng, Ying; Chang, Faliang; Li, Ruijian

2017-12-01

Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

PubMed Central

de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C. W.; Petersen, Esben T.; De Vis, Jill B.

2018-01-01

Objective In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Materials and methods Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). Results The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson’s correlation coefficients >0.83, R2 .67–.97). The results from the downsampled data and the high-resolution data were similar. Conclusion Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed. PMID:29672584

Dissecting enzyme function with microfluidic-based deep mutational scanning.

PubMed

Romero, Philip A; Tran, Tuan M; Abate, Adam R

2015-06-09

Natural enzymes are incredibly proficient catalysts, but engineering them to have new or improved functions is challenging due to the complexity of how an enzyme's sequence relates to its biochemical properties. Here, we present an ultrahigh-throughput method for mapping enzyme sequence-function relationships that combines droplet microfluidic screening with next-generation DNA sequencing. We apply our method to map the activity of millions of glycosidase sequence variants. Microfluidic-based deep mutational scanning provides a comprehensive and unbiased view of the enzyme function landscape. The mapping displays expected patterns of mutational tolerance and a strong correspondence to sequence variation within the enzyme family, but also reveals previously unreported sites that are crucial for glycosidase function. We modified the screening protocol to include a high-temperature incubation step, and the resulting thermotolerance landscape allowed the discovery of mutations that enhance enzyme thermostability. Droplet microfluidics provides a general platform for enzyme screening that, when combined with DNA-sequencing technologies, enables high-throughput mapping of enzyme sequence space.

Methods for chromosome-specific staining

DOEpatents

Gray, J.W.; Pinkel, D.

1995-09-05

Methods and compositions for chromosome-specific staining are provided. Compositions comprise heterogeneous mixtures of labeled nucleic acid fragments having substantially complementary base sequences to unique sequence regions of the chromosomal DNA for which their associated staining reagent is specific. Methods include ways for making the chromosome-specific staining compositions of the invention, and methods for applying the staining compositions to chromosomes. 3 figs.

Elman RNN based classification of proteins sequences on account of their mutual information.

PubMed

Mishra, Pooja; Nath Pandey, Paras

2012-10-21

In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

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

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Molecular taxonomy of phytopathogenic fungi: a case study in Peronospora.

PubMed

Göker, Markus; García-Blázquez, Gema; Voglmayr, Hermann; Tellería, M Teresa; Martín, María P

2009-07-29

Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms. Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews. A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence.

Molecular Taxonomy of Phytopathogenic Fungi: A Case Study in Peronospora

PubMed Central

Göker, Markus; García-Blázquez, Gema; Voglmayr, Hermann; Tellería, M. Teresa; Martín, María P.

2009-01-01

Background Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms. Methodology Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews. Conclusions A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence. PMID:19641601

SCMPSP: Prediction and characterization of photosynthetic proteins based on a scoring card method.

PubMed

Vasylenko, Tamara; Liou, Yi-Fan; Chen, Hong-An; Charoenkwan, Phasit; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Photosynthetic proteins (PSPs) greatly differ in their structure and function as they are involved in numerous subprocesses that take place inside an organelle called a chloroplast. Few studies predict PSPs from sequences due to their high variety of sequences and structues. This work aims to predict and characterize PSPs by establishing the datasets of PSP and non-PSP sequences and developing prediction methods. A novel bioinformatics method of predicting and characterizing PSPs based on scoring card method (SCMPSP) was used. First, a dataset consisting of 649 PSPs was established by using a Gene Ontology term GO:0015979 and 649 non-PSPs from the SwissProt database with sequence identity <= 25%.- Several prediction methods are presented based on support vector machine (SVM), decision tree J48, Bayes, BLAST, and SCM. The SVM method using dipeptide features-performed well and yielded - a test accuracy of 72.31%. The SCMPSP method uses the estimated propensity scores of 400 dipeptides - as PSPs and has a test accuracy of 71.54%, which is comparable to that of the SVM method. The derived propensity scores of 20 amino acids were further used to identify informative physicochemical properties for characterizing PSPs. The analytical results reveal the following four characteristics of PSPs: 1) PSPs favour hydrophobic side chain amino acids; 2) PSPs are composed of the amino acids prone to form helices in membrane environments; 3) PSPs have low interaction with water; and 4) PSPs prefer to be composed of the amino acids of electron-reactive side chains. The SCMPSP method not only estimates the propensity of a sequence to be PSPs, it also discovers characteristics that further improve understanding of PSPs. The SCMPSP source code and the datasets used in this study are available at http://iclab.life.nctu.edu.tw/SCMPSP/.

Cyanine-based probe\\tag-peptide pair fluorescence protein imaging and fluorescence protein imaging methods

DOEpatents

Mayer-Cumblidge, M. Uljana; Cao, Haishi

2013-01-15

A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

Cyanine-based probe\\tag-peptide pair for fluorescence protein imaging and fluorescence protein imaging methods

DOEpatents

Mayer-Cumblidge, M Uljana [Richland, WA; Cao, Haishi [Richland, WA

2010-08-17

A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

Haplotype-Based Genotyping in Polyploids.

PubMed

Clevenger, Josh P; Korani, Walid; Ozias-Akins, Peggy; Jackson, Scott

2018-01-01

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids. To test this method, a large-scale 48K SNP array (Axiom Arachis2) was developed for Arachis hypogaea (peanut), an allotetraploid, in which 1,674 haplotype-based SNPs were included. Results of the array show that 74% of the haplotype-based SNP markers could be validated, which is considerably higher than previous methods used for peanut. The haplotype method has been implemented in a standalone program, HAPLOSWEEP, which takes as input bam files and a vcf file and identifies haplotype-based markers. Haplotype discovery can be made within single reads or span paired reads, and can leverage long read technology by targeting any length of haplotype. Haplotype-based genotyping is applicable in all allopolyploid genomes and provides confidence in marker identification and in silico-based genotyping for polyploid genomics.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

PubMed

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.

PubMed

Yehdego, Daniel T; Zhang, Boyu; Kodimala, Vikram K R; Johnson, Kyle L; Taufer, Michela; Leung, Ming-Ying

2013-05-01

Secondary structures of ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Experimental observations and computing limitations suggest that we can approach the secondary structure prediction problem for long RNA sequences by segmenting them into shorter chunks, predicting the secondary structures of each chunk individually using existing prediction programs, and then assembling the results to give the structure of the original sequence. The selection of cutting points is a crucial component of the segmenting step. Noting that stem-loops and pseudoknots always contain an inversion, i.e., a stretch of nucleotides followed closely by its inverse complementary sequence, we developed two cutting methods for segmenting long RNA sequences based on inversion excursions: the centered and optimized method. Each step of searching for inversions, chunking, and predictions can be performed in parallel. In this paper we use a MapReduce framework, i.e., Hadoop, to extensively explore meaningful inversion stem lengths and gap sizes for the segmentation and identify correlations between chunking methods and prediction accuracy. We show that for a set of long RNA sequences in the RFAM database, whose secondary structures are known to contain pseudoknots, our approach predicts secondary structures more accurately than methods that do not segment the sequence, when the latter predictions are possible computationally. We also show that, as sequences exceed certain lengths, some programs cannot computationally predict pseudoknots while our chunking methods can. Overall, our predicted structures still retain the accuracy level of the original prediction programs when compared with known experimental secondary structure.

Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures.

PubMed

Vallat, Brinda; Madrid-Aliste, Carlos; Fiser, Andras

2015-08-01

Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling.

A novel HLA-B allele, B*5214, detected in a Taiwanese volunteer bone marrow donor using a sequence-based typing method.

PubMed

Chen, M J; Chu, C C; Shyr, M H; Lin, C L; Lin, P Y; Yang, K L

2010-02-01

HLA-B*5214, a novel rare allele of HLA-B*52 variant, was found in a Taiwanese volunteer bone marrow donor by sequence-based typing method. The sequence of B*5214 is identical to that of B*520101 in exon 2 but differs from B*520101 in exon 3 at nucleotide positions 419 A-->T and 435 A-->G. Alteration of these two nucleotides resulted an amino acid substitution at amino acid residue 116 Y-->F ( TAC-->TTC) and a silent exchange at residue 121 K-->K (AAA-->AAG).

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

PubMed Central

Jespersen, Martin Closter; Peters, Bjoern

2017-01-01

Abstract Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy and non-expert users. We believe that BepiPred-2.0 will be a valuable tool for the bioinformatics and immunology community. PMID:28472356

Iterative dictionary construction for compression of large DNA data sets.

PubMed

Kuruppu, Shanika; Beresford-Smith, Bryan; Conway, Thomas; Zobel, Justin

2012-01-01

Genomic repositories increasingly include individual as well as reference sequences, which tend to share long identical and near-identical strings of nucleotides. However, the sequential processing used by most compression algorithms, and the volumes of data involved, mean that these long-range repetitions are not detected. An order-insensitive, disk-based dictionary construction method can detect this repeated content and use it to compress collections of sequences. We explore a dictionary construction method that improves repeat identification in large DNA data sets. Our adaptation, COMRAD, of an existing disk-based method identifies exact repeated content in collections of sequences with similarities within and across the set of input sequences. COMRAD compresses the data over multiple passes, which is an expensive process, but allows COMRAD to compress large data sets within reasonable time and space. COMRAD allows for random access to individual sequences and subsequences without decompressing the whole data set. COMRAD has no competitor in terms of the size of data sets that it can compress (extending to many hundreds of gigabytes) and, even for smaller data sets, the results are competitive compared to alternatives; as an example, 39 S. cerevisiae genomes compressed to 0.25 bits per base.

MIG-seq: an effective PCR-based method for genome-wide single-nucleotide polymorphism genotyping using the next-generation sequencing platform

PubMed Central

Suyama, Yoshihisa; Matsuki, Yu

2015-01-01

Restriction-enzyme (RE)-based next-generation sequencing methods have revolutionized marker-assisted genetic studies; however, the use of REs has limited their widespread adoption, especially in field samples with low-quality DNA and/or small quantities of DNA. Here, we developed a PCR-based procedure to construct reduced representation libraries without RE digestion steps, representing de novo single-nucleotide polymorphism discovery, and its genotyping using next-generation sequencing. Using multiplexed inter-simple sequence repeat (ISSR) primers, thousands of genome-wide regions were amplified effectively from a wide variety of genomes, without prior genetic information. We demonstrated: 1) Mendelian gametic segregation of the discovered variants; 2) reproducibility of genotyping by checking its applicability for individual identification; and 3) applicability in a wide variety of species by checking standard population genetic analysis. This approach, called multiplexed ISSR genotyping by sequencing, should be applicable to many marker-assisted genetic studies with a wide range of DNA qualities and quantities. PMID:26593239

Patterns and Sequences: Interactive Exploration of Clickstreams to Understand Common Visitor Paths.

PubMed

Liu, Zhicheng; Wang, Yang; Dontcheva, Mira; Hoffman, Matthew; Walker, Seth; Wilson, Alan

2017-01-01

Modern web clickstream data consists of long, high-dimensional sequences of multivariate events, making it difficult to analyze. Following the overarching principle that the visual interface should provide information about the dataset at multiple levels of granularity and allow users to easily navigate across these levels, we identify four levels of granularity in clickstream analysis: patterns, segments, sequences and events. We present an analytic pipeline consisting of three stages: pattern mining, pattern pruning and coordinated exploration between patterns and sequences. Based on this approach, we discuss properties of maximal sequential patterns, propose methods to reduce the number of patterns and describe design considerations for visualizing the extracted sequential patterns and the corresponding raw sequences. We demonstrate the viability of our approach through an analysis scenario and discuss the strengths and limitations of the methods based on user feedback.

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Li, Yuanyuan; Wang, Liqiang

2015-12-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

Fast and secure encryption-decryption method based on chaotic dynamics

DOEpatents

Protopopescu, Vladimir A.; Santoro, Robert T.; Tolliver, Johnny S.

1995-01-01

A method and system for the secure encryption of information. The method comprises the steps of dividing a message of length L into its character components; generating m chaotic iterates from m independent chaotic maps; producing an "initial" value based upon the m chaotic iterates; transforming the "initial" value to create a pseudo-random integer; repeating the steps of generating, producing and transforming until a pseudo-random integer sequence of length L is created; and encrypting the message as ciphertext based upon the pseudo random integer sequence. A system for accomplishing the invention is also provided.

Molecular epidemiologic analysis of a Pneumocystis pneumonia outbreak among renal transplant patients.

PubMed

Urabe, N; Ishii, Y; Hyodo, Y; Aoki, K; Yoshizawa, S; Saga, T; Murayama, S Y; Sakai, K; Homma, S; Tateda, K

2016-04-01

Between 18 November and 3 December 2011, five renal transplant patients at the Department of Nephrology, Toho University Omori Medical Centre, Tokyo, were diagnosed with Pneumocystis pneumonia (PCP). We used molecular epidemiologic methods to determine whether the patients were infected with the same strain of Pneumocystis jirovecii. DNA extracted from the residual bronchoalveolar lavage fluid from the five outbreak cases and from another 20 cases of PCP between 2007 and 2014 were used for multilocus sequence typing to compare the genetic similarity of the P. jirovecii. DNA base sequencing by the Sanger method showed some regions where two bases overlapped and could not be defined. A next-generation sequencer was used to analyse the types and ratios of these overlapping bases. DNA base sequences of P. jirovecii in the bronchoalveolar lavage fluid from four of the five PCP patients in the 2011 outbreak and from another two renal transplant patients who developed PCP in 2013 were highly homologous. The Sanger method revealed 14 genomic regions where two differing DNA bases overlapped and could not be identified. Analyses of the overlapping bases by a next-generation sequencer revealed that the differing types of base were present in almost identical ratios. There is a strong possibility that the PCP outbreak at the Toho University Omori Medical Centre was caused by the same strain of P. jirovecii. Two different types of base present in some regions may be due to P. jirovecii's being a diploid species. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

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

PubMed

Bansal, Vikas

2010-06-15

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

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

PubMed

Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2014-09-07

Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Electrophoretic mobility shift scanning using an automated infrared DNA sequencer.

PubMed

Sano, M; Ohyama, A; Takase, K; Yamamoto, M; Machida, M

2001-11-01

Electrophoretic mobility shift assay (EMSA) is widely used in the study of sequence-specific DNA-binding proteins, including transcription factors and mismatch binding proteins. We have established a non-radioisotope-based protocol for EMSA that features an automated DNA sequencer with an infrared fluorescent dye (IRDye) detection unit. Our modification of the elec- trophoresis unit, which includes cooling the gel plates with a reduced well-to-read length, has made it possible to detect shifted bands within 1 h. Further, we have developed a rapid ligation-based method for generating IRDye-labeled probes with an approximately 60% cost reduction. This method has the advantages of real-time scanning, stability of labeled probes, and better safety associated with nonradioactive methods of detection. Analysis of a promoter from an industrially important filamentous fungus, Aspergillus oryzae, in a prototype experiment revealed that the method we describe has potential for use in systematic scanning and identification of the functionally important elements to which cellular factors bind in a sequence-specific manner.

Use of simulated data sets to evaluate the fidelity of metagenomic processing methods

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

Mavromatis, K; Ivanova, N; Barry, Kerrie

2007-01-01

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity-based ( blast hit distribution) and twomore » sequence composition-based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.« less

Use of simulated data sets to evaluate the fidelity of Metagenomicprocessing methods

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

Mavromatis, Konstantinos; Ivanova, Natalia; Barry, Kerri

2006-12-01

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity--based (blast hit distribution) and twomore » sequence composition--based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.« less

Method for sequencing DNA base pairs

DOEpatents

Sessler, A.M.; Dawson, J.

1993-12-14

The base pairs of a DNA structure are sequenced with the use of a scanning tunneling microscope (STM). The DNA structure is scanned by the STM probe tip, and, as it is being scanned, the DNA structure is separately subjected to a sequence of infrared radiation from four different sources, each source being selected to preferentially excite one of the four different bases in the DNA structure. Each particular base being scanned is subjected to such sequence of infrared radiation from the four different sources as that particular base is being scanned. The DNA structure as a whole is separately imaged for each subjection thereof to radiation from one only of each source. 6 figures.

Miniprimer PCR, a New Lens for Viewing the Microbial World▿ †

PubMed Central

Isenbarger, Thomas A.; Finney, Michael; Ríos-Velázquez, Carlos; Handelsman, Jo; Ruvkun, Gary

2008-01-01

Molecular methods based on the 16S rRNA gene sequence are used widely in microbial ecology to reveal the diversity of microbial populations in environmental samples. Here we show that a new PCR method using an engineered polymerase and 10-nucleotide “miniprimers” expands the scope of detectable sequences beyond those detected by standard methods using longer primers and Taq polymerase. After testing the method in silico to identify divergent ribosomal genes in previously cloned environmental sequences, we applied the method to soil and microbial mat samples, which revealed novel 16S rRNA gene sequences that would not have been detected with standard primers. Deeply divergent sequences were discovered with high frequency and included representatives that define two new division-level taxa, designated CR1 and CR2, suggesting that miniprimer PCR may reveal new dimensions of microbial diversity. PMID:18083877

Introduction of the hybcell-based compact sequencing technology and comparison to state-of-the-art methodologies for KRAS mutation detection.

PubMed

Zopf, Agnes; Raim, Roman; Danzer, Martin; Niklas, Norbert; Spilka, Rita; Pröll, Johannes; Gabriel, Christian; Nechansky, Andreas; Roucka, Markus

2015-03-01

The detection of KRAS mutations in codons 12 and 13 is critical for anti-EGFR therapy strategies; however, only those methodologies with high sensitivity, specificity, and accuracy as well as the best cost and turnaround balance are suitable for routine daily testing. Here we compared the performance of compact sequencing using the novel hybcell technology with 454 next-generation sequencing (454-NGS), Sanger sequencing, and pyrosequencing, using an evaluation panel of 35 specimens. A total of 32 mutations and 10 wild-type cases were reported using 454-NGS as the reference method. Specificity ranged from 100% for Sanger sequencing to 80% for pyrosequencing. Sanger sequencing and hybcell-based compact sequencing achieved a sensitivity of 96%, whereas pyrosequencing had a sensitivity of 88%. Accuracy was 97% for Sanger sequencing, 85% for pyrosequencing, and 94% for hybcell-based compact sequencing. Quantitative results were obtained for 454-NGS and hybcell-based compact sequencing data, resulting in a significant correlation (r = 0.914). Whereas pyrosequencing and Sanger sequencing were not able to detect multiple mutated cell clones within one tumor specimen, 454-NGS and the hybcell-based compact sequencing detected multiple mutations in two specimens. Our comparison shows that the hybcell-based compact sequencing is a valuable alternative to state-of-the-art methodologies used for detection of clinically relevant point mutations.

nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data.

PubMed

Zhang, Changsheng; Cai, Hongmin; Huang, Jingying; Song, Yan

2016-09-17

Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genomic heterogeneity at the single-cell level, thereby providing important evolutionary information about cancer cells. In contrast to traditional bulk sequencing, single-cell sequencing requires the amplification of the whole genome of a single cell to accumulate enough samples for sequencing. However, the amplification process inevitably introduces amplification bias, resulting in an over-dispersing portion of the sequencing data. Recent study has manifested that the over-dispersed portion of the single-cell sequencing data could be well modelled by negative binomial distributions. We developed a read-depth based method, nbCNV to detect the copy number variants (CNVs). The nbCNV method uses two constraints-sparsity and smoothness to fit the CNV patterns under the assumption that the read signals are negatively binomially distributed. The problem of CNV detection was formulated as a quadratic optimization problem, and was solved by an efficient numerical solution based on the classical alternating direction minimization method. Extensive experiments to compare nbCNV with existing benchmark models were conducted on both simulated data and empirical single-cell sequencing data. The results of those experiments demonstrate that nbCNV achieves superior performance and high robustness for the detection of CNVs in single-cell sequencing data.

DNA Barcodes for Species Identification in the Hyperdiverse Ant Genus Pheidole (Formicidae: Myrmicinae)

PubMed Central

Ng'endo, R.N.; Osiemo, Z.B.; Brandl, R.

2013-01-01

DNA sequencing is increasingly being used to assist in species identification in order to overcome taxonomic impediment. However, few studies attempt to compare the results of these molecular studies with a more traditional species delineation approach based on morphological characters. Mitochondrial DNA Cytochrome oxidase subunit 1 (CO1) gene was sequenced, measuring 636 base pairs, from 47 ants of the genus Pheidole (Formicidae: Myrmicinae) collected in the Brazilian Atlantic Forest to test whether the morphology-based assignment of individuals into species is supported by DNA-based species delimitation. Twenty morphospecies were identified, whereas the barcoding analysis identified 19 Molecular Operational Taxonomic Units (MOTUs). Fifteen out of the 19 DNA-based clusters allocated, using sequence divergence thresholds of 2% and 3%, matched with morphospecies. Both thresholds yielded the same number of MOTUs. Only one MOTU was successfully identified to species level using the CO1 sequences of Pheidole species already in the Genbank. The average pairwise sequence divergence for all 47 sequences was 19%, ranging between 0–25%. In some cases, however, morphology and molecular based methods differed in their assignment of individuals to morphospecies or MOTUs. The occurrence of distinct mitochondrial lineages within morphological species highlights groups for further detailed genetic and morphological studies, and therefore a pluralistic approach using several methods to understand the taxonomy of difficult lineages is advocated. PMID:23902257

Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data.

PubMed

Liu, Zhenqiu; Hsiao, William; Cantarel, Brandi L; Drábek, Elliott Franco; Fraser-Liggett, Claire

2011-12-01

Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota. By combining instance-based and model-based learning, we propose a novel sparse distance-based learning method for simultaneous class prediction and feature (variable or taxa, which is used interchangeably) selection from multiple treatment populations on the basis of 16S rRNA sequence count data. Our proposed method simultaneously minimizes the intraclass distance and maximizes the interclass distance with many fewer estimated parameters than other methods. It is very efficient for problems with small sample sizes and unbalanced classes, which are common in metagenomic studies. We implemented this method in a MATLAB toolbox called MetaDistance. We also propose several approaches for data normalization and variance stabilization transformation in MetaDistance. We validate this method on several real and simulated 16S rRNA datasets to show that it outperforms existing methods for classifying metagenomic data. This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data. The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/. zliu@umm.edu Supplementary data are available at Bioinformatics online.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-01-01

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

An automatic and efficient pipeline for disease gene identification through utilizing family-based sequencing data.

PubMed

Song, Dandan; Li, Ning; Liao, Lejian

2015-01-01

Due to the generation of enormous amounts of data at both lower costs as well as in shorter times, whole-exome sequencing technologies provide dramatic opportunities for identifying disease genes implicated in Mendelian disorders. Since upwards of thousands genomic variants can be sequenced in each exome, it is challenging to filter pathogenic variants in protein coding regions and reduce the number of missing true variants. Therefore, an automatic and efficient pipeline for finding disease variants in Mendelian disorders is designed by exploiting a combination of variants filtering steps to analyze the family-based exome sequencing approach. Recent studies on the Freeman-Sheldon disease are revisited and show that the proposed method outperforms other existing candidate gene identification methods.

Massively parallel pyrosequencing of the mitochondrial genome with the 454 methodology in forensic genetics.

PubMed

Mikkelsen, Martin; Frank-Hansen, Rune; Hansen, Anders J; Morling, Niels

2014-09-01

of sequencing of whole mitochondrial genome, HV1 and HV2 DNA with the second generation system (SGS) Roche 454 GS Junior were compared with results of Sanger sequencing and SNP typing with SNaPshot single base extension detected with MALDI-TOF and capillary electrophoresis. We investigated the performance of the software analysis of the data, reproducibility, ability to sequence homopolymeric regions, detection of mixtures and heteroplasmy as well as the implications of the depth of coverage. We found full reproducibility between samples sequenced twice with SGS. We found close to full concordance between the mtDNA sequences of 26 samples obtained with (1) the 454 SGS method using a depth of coverage above 100 and (2) Sanger sequencing and SNP typing. The discrepancies were primarily observed in homopolymeric regions. The 454 SGS method was able to sequence 95% of the reads correctly in homopolymers up to 4 bases, and up to 6 bases could be sequenced with similar success if the results were carefully, visually inspected. The 454 technology was able to detect mixtures or heteroplasmy of approximately 10%. We detected previously unreported heteroplasmy in the GM9947A component of the NIST human mitochondrial DNA SRM-2392 standard reference material. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo

NASA Astrophysics Data System (ADS)

Kohigashi, Satoru; Nakamae, Koji; Fujioka, Hiromu

2005-04-01

We develop the image based computer assisted diagnosis system for benign paroxysmal positional vertigo (BPPV) that consists of the balance control system simulator, the 3D eye movement simulator, and the extraction method of nystagmus response directly from an eye movement image sequence. In the system, the causes and conditions of BPPV are estimated by searching the database for record matching with the nystagmus response for the observed eye image sequence of the patient with BPPV. The database includes the nystagmus responses for simulated eye movement sequences. The eye movement velocity is obtained by using the balance control system simulator that allows us to simulate BPPV under various conditions such as canalithiasis, cupulolithiasis, number of otoconia, otoconium size, and so on. Then the eye movement image sequence is displayed on the CRT by the 3D eye movement simulator. The nystagmus responses are extracted from the image sequence by the proposed method and are stored in the database. In order to enhance the diagnosis accuracy, the nystagmus response for a newly simulated sequence is matched with that for the observed sequence. From the matched simulation conditions, the causes and conditions of BPPV are estimated. We apply our image based computer assisted diagnosis system to two real eye movement image sequences for patients with BPPV to show its validity.

Comparison between rpoB and 16S rRNA Gene Sequencing for Molecular Identification of 168 Clinical Isolates of Corynebacterium

PubMed Central

Khamis, Atieh; Raoult, Didier; La Scola, Bernard

2005-01-01

Higher proportions (91%) of 168 corynebacterial isolates were positively identified by partial rpoB gene determination than by that based on 16S rRNA gene sequences. This method is thus a simple, molecular-analysis-based method for identification of corynebacteria, but it should be used in conjunction with other tests for definitive identification. PMID:15815024

Nanopore sequencing in microgravity

PubMed Central

McIntyre, Alexa B R; Rizzardi, Lindsay; Yu, Angela M; Alexander, Noah; Rosen, Gail L; Botkin, Douglas J; Stahl, Sarah E; John, Kristen K; Castro-Wallace, Sarah L; McGrath, Ken; Burton, Aaron S; Feinberg, Andrew P; Mason, Christopher E

2016-01-01

Rapid DNA sequencing and analysis has been a long-sought goal in remote research and point-of-care medicine. In microgravity, DNA sequencing can facilitate novel astrobiological research and close monitoring of crew health, but spaceflight places stringent restrictions on the mass and volume of instruments, crew operation time, and instrument functionality. The recent emergence of portable, nanopore-based tools with streamlined sample preparation protocols finally enables DNA sequencing on missions in microgravity. As a first step toward sequencing in space and aboard the International Space Station (ISS), we tested the Oxford Nanopore Technologies MinION during a parabolic flight to understand the effects of variable gravity on the instrument and data. In a successful proof-of-principle experiment, we found that the instrument generated DNA reads over the course of the flight, including the first ever sequenced in microgravity, and additional reads measured after the flight concluded its parabolas. Here we detail modifications to the sample-loading procedures to facilitate nanopore sequencing aboard the ISS and in other microgravity environments. We also evaluate existing analysis methods and outline two new approaches, the first based on a wave-fingerprint method and the second on entropy signal mapping. Computationally light analysis methods offer the potential for in situ species identification, but are limited by the error profiles (stays, skips, and mismatches) of older nanopore data. Higher accuracies attainable with modified sample processing methods and the latest version of flow cells will further enable the use of nanopore sequencers for diagnostics and research in space. PMID:28725742

An efficient approach to BAC based assembly of complex genomes.

PubMed

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

2016-01-01

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

Differentially Private Frequent Sequence Mining via Sampling-based Candidate Pruning

PubMed Central

Xu, Shengzhi; Cheng, Xiang; Li, Zhengyi; Xiong, Li

2016-01-01

In this paper, we study the problem of mining frequent sequences under the rigorous differential privacy model. We explore the possibility of designing a differentially private frequent sequence mining (FSM) algorithm which can achieve both high data utility and a high degree of privacy. We found, in differentially private FSM, the amount of required noise is proportionate to the number of candidate sequences. If we could effectively reduce the number of unpromising candidate sequences, the utility and privacy tradeoff can be significantly improved. To this end, by leveraging a sampling-based candidate pruning technique, we propose a novel differentially private FSM algorithm, which is referred to as PFS2. The core of our algorithm is to utilize sample databases to further prune the candidate sequences generated based on the downward closure property. In particular, we use the noisy local support of candidate sequences in the sample databases to estimate which sequences are potentially frequent. To improve the accuracy of such private estimations, a sequence shrinking method is proposed to enforce the length constraint on the sample databases. Moreover, to decrease the probability of misestimating frequent sequences as infrequent, a threshold relaxation method is proposed to relax the user-specified threshold for the sample databases. Through formal privacy analysis, we show that our PFS2 algorithm is ε-differentially private. Extensive experiments on real datasets illustrate that our PFS2 algorithm can privately find frequent sequences with high accuracy. PMID:26973430

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative performance of high-density oligonucleotide sequencing and dideoxynucleotide sequencing of HIV type 1 pol from clinical samples.

PubMed

Günthard, H F; Wong, J K; Ignacio, C C; Havlir, D V; Richman, D D

1998-07-01

The performance of the high-density oligonucleotide array methodology (GeneChip) in detecting drug resistance mutations in HIV-1 pol was compared with that of automated dideoxynucleotide sequencing (ABI) of clinical samples, viral stocks, and plasmid-derived NL4-3 clones. Sequences from 29 clinical samples (plasma RNA, n = 17; lymph node RNA, n = 5; lymph node DNA, n = 7) from 12 patients, from 6 viral stock RNA samples, and from 13 NL4-3 clones were generated by both methods. Editing was done independently by a different investigator for each method before comparing the sequences. In addition, NL4-3 wild type (WT) and mutants were mixed in varying concentrations and sequenced by both methods. Overall, a concordance of 99.1% was found for a total of 30,865 bases compared. The comparison of clinical samples (plasma RNA and lymph node RNA and DNA) showed a slightly lower match of base calls, 98.8% for 19,831 nucleotides compared (protease region, 99.5%, n = 8272; RT region, 98.3%, n = 11,316), than for viral stocks and NL4-3 clones (protease region, 99.8%; RT region, 99.5%). Artificial mixing experiments showed a bias toward calling wild-type bases by GeneChip. Discordant base calls are most likely due to differential detection of mixtures. The concordance between GeneChip and ABI was high and appeared dependent on the nature of the templates (directly amplified versus cloned) and the complexity of mixes.

RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.

PubMed

Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-01-01

Protein-RNA interactions are central to essential cellular processes such as protein synthesis and regulation of gene expression and play roles in human infectious and genetic diseases. Reliable identification of protein-RNA interfaces is critical for understanding the structural bases and functional implications of such interactions and for developing effective approaches to rational drug design. Sequence-based computational methods offer a viable, cost-effective way to identify putative RNA-binding residues in RNA-binding proteins. Here we report two novel approaches: (i) HomPRIP, a sequence homology-based method for predicting RNA-binding sites in proteins; (ii) RNABindRPlus, a new method that combines predictions from HomPRIP with those from an optimized Support Vector Machine (SVM) classifier trained on a benchmark dataset of 198 RNA-binding proteins. Although highly reliable, HomPRIP cannot make predictions for the unaligned parts of query proteins and its coverage is limited by the availability of close sequence homologs of the query protein with experimentally determined RNA-binding sites. RNABindRPlus overcomes these limitations. We compared the performance of HomPRIP and RNABindRPlus with that of several state-of-the-art predictors on two test sets, RB44 and RB111. On a subset of proteins for which homologs with experimentally determined interfaces could be reliably identified, HomPRIP outperformed all other methods achieving an MCC of 0.63 on RB44 and 0.83 on RB111. RNABindRPlus was able to predict RNA-binding residues of all proteins in both test sets, achieving an MCC of 0.55 and 0.37, respectively, and outperforming all other methods, including those that make use of structure-derived features of proteins. More importantly, RNABindRPlus outperforms all other methods for any choice of tradeoff between precision and recall. An important advantage of both HomPRIP and RNABindRPlus is that they rely on readily available sequence and sequence-derived features of RNA-binding proteins. A webserver implementation of both methods is freely available at http://einstein.cs.iastate.edu/RNABindRPlus/.

Improving prokaryotic transposable elements identification using a combination of de novo and profile HMM methods.

PubMed

Kamoun, Choumouss; Payen, Thibaut; Hua-Van, Aurélie; Filée, Jonathan

2013-10-11

Insertion Sequences (ISs) and their non-autonomous derivatives (MITEs) are important components of prokaryotic genomes inducing duplication, deletion, rearrangement or lateral gene transfers. Although ISs and MITEs are relatively simple and basic genetic elements, their detection remains a difficult task due to their remarkable sequence diversity. With the advent of high-throughput genome and metagenome sequencing technologies, the development of fast, reliable and sensitive methods of ISs and MITEs detection become an important challenge. So far, almost all studies dealing with prokaryotic transposons have used classical BLAST-based detection methods against reference libraries. Here we introduce alternative methods of detection either taking advantages of the structural properties of the elements (de novo methods) or using an additional library-based method using profile HMM searches. In this study, we have developed three different work flows dedicated to ISs and MITEs detection: the first two use de novo methods detecting either repeated sequences or presence of Inverted Repeats; the third one use 28 in-house transposase alignment profiles with HMM search methods. We have compared the respective performances of each method using a reference dataset of 30 archaeal and 30 bacterial genomes in addition to simulated and real metagenomes. Compared to a BLAST-based method using ISFinder as library, de novo methods significantly improve ISs and MITEs detection. For example, in the 30 archaeal genomes, we discovered 30 new elements (+20%) in addition to the 141 multi-copies elements already detected by the BLAST approach. Many of the new elements correspond to ISs belonging to unknown or highly divergent families. The total number of MITEs has even doubled with the discovery of elements displaying very limited sequence similarities with their respective autonomous partners (mainly in the Inverted Repeats of the elements). Concerning metagenomes, with the exception of short reads data (<300 bp) for which both techniques seem equally limited, profile HMM searches considerably ameliorate the detection of transposase encoding genes (up to +50%) generating low level of false positives compare to BLAST-based methods. Compared to classical BLAST-based methods, the sensitivity of de novo and profile HMM methods developed in this study allow a better and more reliable detection of transposons in prokaryotic genomes and metagenomes. We believed that future studies implying ISs and MITEs identification in genomic data should combine at least one de novo and one library-based method, with optimal results obtained by running the two de novo methods in addition to a library-based search. For metagenomic data, profile HMM search should be favored, a BLAST-based step is only useful to the final annotation into groups and families.

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

PubMed

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

2017-10-01

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

Sequence-invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, Sterling R.; Manjunath, Shamanna K.; Maki, Gary K.

1991-01-01

A synthesis method and an MOS VLSI architecture are presented to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. The design method utilizes binary tree structured (BTS) logic to implement regular and dense circuits. The desired state sequence can be hardwired with power supply connections or can be dynamically reallocated if stored in a register. This allows programmable VLSI controllers to be designed with a compact size and performance approaching that of dedicated logic. Results of ICV implementations are reported and an example sequence-invariant state machine is contrasted with implementations based on traditional methods.

Determination of a mutational spectrum

DOEpatents

Thilly, William G.; Keohavong, Phouthone

1991-01-01

A method of resolving (physically separating) mutant DNA from nonmutant DNA and a method of defining or establishing a mutational spectrum or profile of alterations present in nucleic acid sequences from a sample to be analyzed, such as a tissue or body fluid. The present method is based on the fact that it is possible, through the use of DGGE, to separate nucleic acid sequences which differ by only a single base change and on the ability to detect the separate mutant molecules. The present invention, in another aspect, relates to a method for determining a mutational spectrum in a DNA sequence of interest present in a population of cells. The method of the present invention is useful as a diagnostic or analytical tool in forensic science in assessing environmental and/or occupational exposures to potentially genetically toxic materials (also referred to as potential mutagens); in biotechnology, particularly in the study of the relationship between the amino acid sequence of enzymes and other biologically-active proteins or protein-containing substances and their respective functions; and in determining the effects of drugs, cosmetics and other chemicals for which toxicity data must be obtained.

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.

BASiNET-BiologicAl Sequences NETwork: a case study on coding and non-coding RNAs identification.

PubMed

Ito, Eric Augusto; Katahira, Isaque; Vicente, Fábio Fernandes da Rocha; Pereira, Luiz Filipe Protasio; Lopes, Fabrício Martins

2018-06-05

With the emergence of Next Generation Sequencing (NGS) technologies, a large volume of sequence data in particular de novo sequencing was rapidly produced at relatively low costs. In this context, computational tools are increasingly important to assist in the identification of relevant information to understand the functioning of organisms. This work introduces BASiNET, an alignment-free tool for classifying biological sequences based on the feature extraction from complex network measurements. The method initially transform the sequences and represents them as complex networks. Then it extracts topological measures and constructs a feature vector that is used to classify the sequences. The method was evaluated in the classification of coding and non-coding RNAs of 13 species and compared to the CNCI, PLEK and CPC2 methods. BASiNET outperformed all compared methods in all adopted organisms and datasets. BASiNET have classified sequences in all organisms with high accuracy and low standard deviation, showing that the method is robust and non-biased by the organism. The proposed methodology is implemented in open source in R language and freely available for download at https://cran.r-project.org/package=BASiNET.

DendroBLAST: approximate phylogenetic trees in the absence of multiple sequence alignments.

PubMed

Kelly, Steven; Maini, Philip K

2013-01-01

The rapidly growing availability of genome information has created considerable demand for both fast and accurate phylogenetic inference algorithms. We present a novel method called DendroBLAST for reconstructing phylogenetic dendrograms/trees from protein sequences using BLAST. This method differs from other methods by incorporating a simple model of sequence evolution to test the effect of introducing sequence changes on the reliability of the bipartitions in the inferred tree. Using realistic simulated sequence data we demonstrate that this method produces phylogenetic trees that are more accurate than other commonly-used distance based methods though not as accurate as maximum likelihood methods from good quality multiple sequence alignments. In addition to tests on simulated data, we use DendroBLAST to generate input trees for a supertree reconstruction of the phylogeny of the Archaea. This independent analysis produces an approximate phylogeny of the Archaea that has both high precision and recall when compared to previously published analysis of the same dataset using conventional methods. Taken together these results demonstrate that approximate phylogenetic trees can be produced in the absence of multiple sequence alignments, and we propose that these trees will provide a platform for improving and informing downstream bioinformatic analysis. A web implementation of the DendroBLAST method is freely available for use at http://www.dendroblast.com/.

EAPhy: A Flexible Tool for High-throughput Quality Filtering of Exon-alignments and Data Processing for Phylogenetic Methods.

PubMed

Blom, Mozes P K

2015-08-05

Recently developed molecular methods enable geneticists to target and sequence thousands of orthologous loci and infer evolutionary relationships across the tree of life. Large numbers of genetic markers benefit species tree inference but visual inspection of alignment quality, as traditionally conducted, is challenging with thousands of loci. Furthermore, due to the impracticality of repeated visual inspection with alternative filtering criteria, the potential consequences of using datasets with different degrees of missing data remain nominally explored in most empirical phylogenomic studies. In this short communication, I describe a flexible high-throughput pipeline designed to assess alignment quality and filter exonic sequence data for subsequent inference. The stringency criteria for alignment quality and missing data can be adapted based on the expected level of sequence divergence. Each alignment is automatically evaluated based on the stringency criteria specified, significantly reducing the number of alignments that require visual inspection. By developing a rapid method for alignment filtering and quality assessment, the consistency of phylogenetic estimation based on exonic sequence alignments can be further explored across distinct inference methods, while accounting for different degrees of missing data.

Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives.

PubMed

Zhao, Min; Wang, Qingguo; Wang, Quan; Jia, Peilin; Zhao, Zhongming

2013-01-01

Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development.

Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives

PubMed Central

2013-01-01

Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development. PMID:24564169

GENETIC-BASED ANALYTICAL METHODS FOR BACTERIA AND FUNGI

EPA Science Inventory

In the past two decades, advances in high-throughput sequencing technologies have lead to a veritable explosion in the generation of nucleic acid sequence information (1). While these advances are illustrated most prominently by the successful sequencing of the human genome, they...

On the design of henon and logistic map-based random number generator

NASA Astrophysics Data System (ADS)

Magfirawaty; Suryadi, M. T.; Ramli, Kalamullah

2017-10-01

The key sequence is one of the main elements in the cryptosystem. True Random Number Generators (TRNG) method is one of the approaches to generating the key sequence. The randomness source of the TRNG divided into three main groups, i.e. electrical noise based, jitter based and chaos based. The chaos based utilizes a non-linear dynamic system (continuous time or discrete time) as an entropy source. In this study, a new design of TRNG based on discrete time chaotic system is proposed, which is then simulated in LabVIEW. The principle of the design consists of combining 2D and 1D chaotic systems. A mathematical model is implemented for numerical simulations. We used comparator process as a harvester method to obtain the series of random bits. Without any post processing, the proposed design generated random bit sequence with high entropy value and passed all NIST 800.22 statistical tests.

Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect

NASA Astrophysics Data System (ADS)

Artyukhin, S. G.; Mestetskiy, L. M.

2015-05-01

This paper presents an efficient framework for solving the problem of static gesture recognition based on data obtained from the web cameras and depth sensor Kinect (RGB-D - data). Each gesture given by a pair of images: color image and depth map. The database store gestures by it features description, genereated by frame for each gesture of the alphabet. Recognition algorithm takes as input a video sequence (a sequence of frames) for marking, put in correspondence with each frame sequence gesture from the database, or decide that there is no suitable gesture in the database. First, classification of the frame of the video sequence is done separately without interframe information. Then, a sequence of successful marked frames in equal gesture is grouped into a single static gesture. We propose a method combined segmentation of frame by depth map and RGB-image. The primary segmentation is based on the depth map. It gives information about the position and allows to get hands rough border. Then, based on the color image border is specified and performed analysis of the shape of the hand. Method of continuous skeleton is used to generate features. We propose a method of skeleton terminal branches, which gives the opportunity to determine the position of the fingers and wrist. Classification features for gesture is description of the position of the fingers relative to the wrist. The experiments were carried out with the developed algorithm on the example of the American Sign Language. American Sign Language gesture has several components, including the shape of the hand, its orientation in space and the type of movement. The accuracy of the proposed method is evaluated on the base of collected gestures consisting of 2700 frames.

A knowledge engineering approach to recognizing and extracting sequences of nucleic acids from scientific literature.

PubMed

García-Remesal, Miguel; Maojo, Victor; Crespo, José

2010-01-01

In this paper we present a knowledge engineering approach to automatically recognize and extract genetic sequences from scientific articles. To carry out this task, we use a preliminary recognizer based on a finite state machine to extract all candidate DNA/RNA sequences. The latter are then fed into a knowledge-based system that automatically discards false positives and refines noisy and incorrectly merged sequences. We created the knowledge base by manually analyzing different manuscripts containing genetic sequences. Our approach was evaluated using a test set of 211 full-text articles in PDF format containing 3134 genetic sequences. For such set, we achieved 87.76% precision and 97.70% recall respectively. This method can facilitate different research tasks. These include text mining, information extraction, and information retrieval research dealing with large collections of documents containing genetic sequences.

Linear and exponential TAIL-PCR: a method for efficient and quick amplification of flanking sequences adjacent to Tn5 transposon insertion sites.

PubMed

Jia, Xianbo; Lin, Xinjian; Chen, Jichen

2017-11-02

Current genome walking methods are very time consuming, and many produce non-specific amplification products. To amplify the flanking sequences that are adjacent to Tn5 transposon insertion sites in Serratia marcescens FZSF02, we developed a genome walking method based on TAIL-PCR. This PCR method added a 20-cycle linear amplification step before the exponential amplification step to increase the concentration of the target sequences. Products of the linear amplification and the exponential amplification were diluted 100-fold to decrease the concentration of the templates that cause non-specific amplification. Fast DNA polymerase with a high extension speed was used in this method, and an amplification program was used to rapidly amplify long specific sequences. With this linear and exponential TAIL-PCR (LETAIL-PCR), we successfully obtained products larger than 2 kb from Tn5 transposon insertion mutant strains within 3 h. This method can be widely used in genome walking studies to amplify unknown sequences that are adjacent to known sequences.

Improved serial analysis of V1 ribosomal sequence tags (SARST-V1) provides a rapid, comprehensive, sequence-based characterization of bacterial diversity and community composition.

PubMed

Yu, Zhongtang; Yu, Marie; Morrison, Mark

2006-04-01

Serial analysis of ribosomal sequence tags (SARST) is a recently developed technology that can generate large 16S rRNA gene (rrs) sequence data sets from microbiomes, but there are numerous enzymatic and purification steps required to construct the ribosomal sequence tag (RST) clone libraries. We report here an improved SARST method, which still targets the V1 hypervariable region of rrs genes, but reduces the number of enzymes, oligonucleotides, reagents, and technical steps needed to produce the RST clone libraries. The new method, hereafter referred to as SARST-V1, was used to examine the eubacterial diversity present in community DNA recovered from the microbiome resident in the ovine rumen. The 190 sequenced clones contained 1055 RSTs and no less than 236 unique phylotypes (based on > or = 95% sequence identity) that were assigned to eight different eubacterial phyla. Rarefaction and monomolecular curve analyses predicted that the complete RST clone library contains 99% of the 353 unique phylotypes predicted to exist in this microbiome. When compared with ribosomal intergenic spacer analysis (RISA) of the same community DNA sample, as well as a compilation of nine previously published conventional rrs clone libraries prepared from the same type of samples, the RST clone library provided a more comprehensive characterization of the eubacterial diversity present in rumen microbiomes. As such, SARST-V1 should be a useful tool applicable to comprehensive examination of diversity and composition in microbiomes and offers an affordable, sequence-based method for diversity analysis.

Development and in-house validation of the event-specific polymerase chain reaction detection methods for genetically modified soybean MON89788 based on the cloned integration flanking sequence.

PubMed

Liu, Jia; Guo, Jinchao; Zhang, Haibo; Li, Ning; Yang, Litao; Zhang, Dabing

2009-11-25

Various polymerase chain reaction (PCR) methods were developed for the execution of genetically modified organism (GMO) labeling policies, of which an event-specific PCR detection method based on the flanking sequence of exogenous integration is the primary trend in GMO detection due to its high specificity. In this study, the 5' and 3' flanking sequences of the exogenous integration of MON89788 soybean were revealed by thermal asymmetric interlaced PCR. The event-specific PCR primers and TaqMan probe were designed based upon the revealed 5' flanking sequence, and the qualitative and quantitative PCR assays were established employing these designed primers and probes. In qualitative PCR, the limit of detection (LOD) was about 0.01 ng of genomic DNA corresponding to 10 copies of haploid soybean genomic DNA. In the quantitative PCR assay, the LOD was as low as two haploid genome copies, and the limit of quantification was five haploid genome copies. Furthermore, the developed PCR methods were in-house validated by five researchers, and the validated results indicated that the developed event-specific PCR methods can be used for identification and quantification of MON89788 soybean and its derivates.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Thermodynamically balanced inside-out (TBIO) PCR-based gene synthesis: a novel method of primer design for high-fidelity assembly of longer gene sequences

PubMed Central

Gao, Xinxin; Yo, Peggy; Keith, Andrew; Ragan, Timothy J.; Harris, Thomas K.

2003-01-01

A novel thermodynamically-balanced inside-out (TBIO) method of primer design was developed and compared with a thermodynamically-balanced conventional (TBC) method of primer design for PCR-based gene synthesis of codon-optimized gene sequences for the human protein kinase B-2 (PKB2; 1494 bp), p70 ribosomal S6 subunit protein kinase-1 (S6K1; 1622 bp) and phosphoinositide-dependent protein kinase-1 (PDK1; 1712 bp). Each of the 60mer TBIO primers coded for identical nucleotide regions that the 60mer TBC primers covered, except that half of the TBIO primers were reverse complement sequences. In addition, the TBIO and TBC primers contained identical regions of temperature- optimized primer overlaps. The TBC method was optimized to generate sequential overlapping fragments (∼0.4–0.5 kb) for each of the gene sequences, and simultaneous and sequential combinations of overlapping fragments were tested for their ability to be assembled under an array of PCR conditions. However, no fully synthesized gene sequences could be obtained by this approach. In contrast, the TBIO method generated an initial central fragment (∼0.4–0.5 kb), which could be gel purified and used for further inside-out bidirectional elongation by additional increments of 0.4–0.5 kb. By using the newly developed TBIO method of PCR-based gene synthesis, error-free synthetic genes for the human protein kinases PKB2, S6K1 and PDK1 were obtained with little or no corrective mutagenesis. PMID:14602936

Quantum Point Contact Single-Nucleotide Conductance for DNA and RNA Sequence Identification.

PubMed

Afsari, Sepideh; Korshoj, Lee E; Abel, Gary R; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-11-28

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve >99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.

Heart rate measurement based on face video sequence

NASA Astrophysics Data System (ADS)

Xu, Fang; Zhou, Qin-Wu; Wu, Peng; Chen, Xing; Yang, Xiaofeng; Yan, Hong-jian

2015-03-01

This paper proposes a new non-contact heart rate measurement method based on photoplethysmography (PPG) theory. With this method we can measure heart rate remotely with a camera and ambient light. We collected video sequences of subjects, and detected remote PPG signals through video sequences. Remote PPG signals were analyzed with two methods, Blind Source Separation Technology (BSST) and Cross Spectral Power Technology (CSPT). BSST is a commonly used method, and CSPT is used for the first time in the study of remote PPG signals in this paper. Both of the methods can acquire heart rate, but compared with BSST, CSPT has clearer physical meaning, and the computational complexity of CSPT is lower than that of BSST. Our work shows that heart rates detected by CSPT method have good consistency with the heart rates measured by a finger clip oximeter. With good accuracy and low computational complexity, the CSPT method has a good prospect for the application in the field of home medical devices and mobile health devices.

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

Protein binding hot spots prediction from sequence only by a new ensemble learning method.

PubMed

Hu, Shan-Shan; Chen, Peng; Wang, Bing; Li, Jinyan

2017-10-01

Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods have been widely used for hot spot prediction through sequence or structure characterization. As the structural information of proteins is not always solved, and thus hot spot identification from amino acid sequences only is more useful for real-life applications. This work proposes a new sequence-based model that combines physicochemical features with the relative accessible surface area of amino acid sequences for hot spot prediction. The model consists of 83 classifiers involving the IBk (Instance-based k means) algorithm, where instances are encoded by important properties extracted from a total of 544 properties in the AAindex1 (Amino Acid Index) database. Then top-performance classifiers are selected to form an ensemble by a majority voting technique. The ensemble classifier outperforms the state-of-the-art computational methods, yielding an F1 score of 0.80 on the benchmark binding interface database (BID) test set. http://www2.ahu.edu.cn/pchen/web/HotspotEC.htm .

Performance Comparison of Bench-Top Next Generation Sequencers Using Microdroplet PCR-Based Enrichment for Targeted Sequencing in Patients with Autism Spectrum Disorder

PubMed Central

Okamoto, Nobuhiko; Nakashima, Mitsuko; Tsurusaki, Yoshinori; Miyake, Noriko; Saitsu, Hirotomo; Matsumoto, Naomichi

2013-01-01

Next-generation sequencing (NGS) combined with enrichment of target genes enables highly efficient and low-cost sequencing of multiple genes for genetic diseases. The aim of this study was to validate the accuracy and sensitivity of our method for comprehensive mutation detection in autism spectrum disorder (ASD). We assessed the performance of the bench-top Ion Torrent PGM and Illumina MiSeq platforms as optimized solutions for mutation detection, using microdroplet PCR-based enrichment of 62 ASD associated genes. Ten patients with known mutations were sequenced using NGS to validate the sensitivity of our method. The overall read quality was better with MiSeq, largely because of the increased indel-related error associated with PGM. The sensitivity of SNV detection was similar between the two platforms, suggesting they are both suitable for SNV detection in the human genome. Next, we used these methods to analyze 28 patients with ASD, and identified 22 novel variants in genes associated with ASD, with one mutation detected by MiSeq only. Thus, our results support the combination of target gene enrichment and NGS as a valuable molecular method for investigating rare variants in ASD. PMID:24066114

Registration of Panoramic/Fish-Eye Image Sequence and LiDAR Points Using Skyline Features

PubMed Central

Zhu, Ningning; Jia, Yonghong; Ji, Shunping

2018-01-01

We propose utilizing a rigorous registration model and a skyline-based method for automatic registration of LiDAR points and a sequence of panoramic/fish-eye images in a mobile mapping system (MMS). This method can automatically optimize original registration parameters and avoid the use of manual interventions in control point-based registration methods. First, the rigorous registration model between the LiDAR points and the panoramic/fish-eye image was built. Second, skyline pixels from panoramic/fish-eye images and skyline points from the MMS’s LiDAR points were extracted, relying on the difference in the pixel values and the registration model, respectively. Third, a brute force optimization method was used to search for optimal matching parameters between skyline pixels and skyline points. In the experiments, the original registration method and the control point registration method were used to compare the accuracy of our method with a sequence of panoramic/fish-eye images. The result showed: (1) the panoramic/fish-eye image registration model is effective and can achieve high-precision registration of the image and the MMS’s LiDAR points; (2) the skyline-based registration method can automatically optimize the initial attitude parameters, realizing a high-precision registration of a panoramic/fish-eye image and the MMS’s LiDAR points; and (3) the attitude correction values of the sequences of panoramic/fish-eye images are different, and the values must be solved one by one. PMID:29883431

Ariadne: a database search engine for identification and chemical analysis of RNA using tandem mass spectrometry data.

PubMed

Nakayama, Hiroshi; Akiyama, Misaki; Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-04-01

We present here a method to correlate tandem mass spectra of sample RNA nucleolytic fragments with an RNA nucleotide sequence in a DNA/RNA sequence database, thereby allowing tandem mass spectrometry (MS/MS)-based identification of RNA in biological samples. Ariadne, a unique web-based database search engine, identifies RNA by two probability-based evaluation steps of MS/MS data. In the first step, the software evaluates the matches between the masses of product ions generated by MS/MS of an RNase digest of sample RNA and those calculated from a candidate nucleotide sequence in a DNA/RNA sequence database, which then predicts the nucleotide sequences of these RNase fragments. In the second step, the candidate sequences are mapped for all RNA entries in the database, and each entry is scored for a function of occurrences of the candidate sequences to identify a particular RNA. Ariadne can also predict post-transcriptional modifications of RNA, such as methylation of nucleotide bases and/or ribose, by estimating mass shifts from the theoretical mass values. The method was validated with MS/MS data of RNase T1 digests of in vitro transcripts. It was applied successfully to identify an unknown RNA component in a tRNA mixture and to analyze post-transcriptional modification in yeast tRNA(Phe-1).

A MAP-based image interpolation method via Viterbi decoding of Markov chains of interpolation functions.

PubMed

Vedadi, Farhang; Shirani, Shahram

2014-01-01

A new method of image resolution up-conversion (image interpolation) based on maximum a posteriori sequence estimation is proposed. Instead of making a hard decision about the value of each missing pixel, we estimate the missing pixels in groups. At each missing pixel of the high resolution (HR) image, we consider an ensemble of candidate interpolation methods (interpolation functions). The interpolation functions are interpreted as states of a Markov model. In other words, the proposed method undergoes state transitions from one missing pixel position to the next. Accordingly, the interpolation problem is translated to the problem of estimating the optimal sequence of interpolation functions corresponding to the sequence of missing HR pixel positions. We derive a parameter-free probabilistic model for this to-be-estimated sequence of interpolation functions. Then, we solve the estimation problem using a trellis representation and the Viterbi algorithm. Using directional interpolation functions and sequence estimation techniques, we classify the new algorithm as an adaptive directional interpolation using soft-decision estimation techniques. Experimental results show that the proposed algorithm yields images with higher or comparable peak signal-to-noise ratios compared with some benchmark interpolation methods in the literature while being efficient in terms of implementation and complexity considerations.

Community detection in sequence similarity networks based on attribute clustering

DOE PAGES

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

2017-07-24

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Regularized rare variant enrichment analysis for case-control exome sequencing data.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2014-02-01

Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research. © 2013 WILEY PERIODICALS, INC.

Community detection in sequence similarity networks based on attribute clustering

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

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Improvements on a privacy-protection algorithm for DNA sequences with generalization lattices.

PubMed

Li, Guang; Wang, Yadong; Su, Xiaohong

2012-10-01

When developing personal DNA databases, there must be an appropriate guarantee of anonymity, which means that the data cannot be related back to individuals. DNA lattice anonymization (DNALA) is a successful method for making personal DNA sequences anonymous. However, it uses time-consuming multiple sequence alignment and a low-accuracy greedy clustering algorithm. Furthermore, DNALA is not an online algorithm, and so it cannot quickly return results when the database is updated. This study improves the DNALA method. Specifically, we replaced the multiple sequence alignment in DNALA with global pairwise sequence alignment to save time, and we designed a hybrid clustering algorithm comprised of a maximum weight matching (MWM)-based algorithm and an online algorithm. The MWM-based algorithm is more accurate than the greedy algorithm in DNALA and has the same time complexity. The online algorithm can process data quickly when the database is updated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A rapid, generally applicable method to engineer zinc fingers illustrated by targeting the HIV-1 promoter.

PubMed

Isalan, M; Klug, A; Choo, Y

2001-07-01

DNA-binding domains with predetermined sequence specificity are engineered by selection of zinc finger modules using phage display, allowing the construction of customized transcription factors. Despite remarkable progress in this field, the available protein-engineering methods are deficient in many respects, thus hampering the applicability of the technique. Here we present a rapid and convenient method that can be used to design zinc finger proteins against a variety of DNA-binding sites. This is based on a pair of pre-made zinc finger phage-display libraries, which are used in parallel to select two DNA-binding domains each of which recognizes given 5 base pair sequences, and whose products are recombined to produce a single protein that recognizes a composite (9 base pair) site of predefined sequence. Engineering using this system can be completed in less than two weeks and yields proteins that bind sequence-specifically to DNA with Kd values in the nanomolar range. To illustrate the technique, we have selected seven different proteins to bind various regions of the human immunodeficiency virus 1 (HIV-1) promoter.

Development of a screening method for genetically modified soybean by plasmid-based quantitative competitive polymerase chain reaction.

PubMed

Shimizu, Eri; Kato, Hisashi; Nakagawa, Yuki; Kodama, Takashi; Futo, Satoshi; Minegishi, Yasutaka; Watanabe, Takahiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

2008-07-23

A novel type of quantitative competitive polymerase chain reaction (QC-PCR) system for the detection and quantification of the Roundup Ready soybean (RRS) was developed. This system was designed based on the advantage of a fully validated real-time PCR method used for the quantification of RRS in Japan. A plasmid was constructed as a competitor plasmid for the detection and quantification of genetically modified soy, RRS. The plasmid contained the construct-specific sequence of RRS and the taxon-specific sequence of lectin1 (Le1), and both had 21 bp oligonucleotide insertion in the sequences. The plasmid DNA was used as a reference molecule instead of ground seeds, which enabled us to precisely and stably adjust the copy number of targets. The present study demonstrated that the novel plasmid-based QC-PCR method could be a simple and feasible alternative to the real-time PCR method used for the quantification of genetically modified organism contents.

Inferring Short-Range Linkage Information from Sequencing Chromatograms

PubMed Central

Beggel, Bastian; Neumann-Fraune, Maria; Kaiser, Rolf; Verheyen, Jens; Lengauer, Thomas

2013-01-01

Direct Sanger sequencing of viral genome populations yields multiple ambiguous sequence positions. It is not straightforward to derive linkage information from sequencing chromatograms, which in turn hampers the correct interpretation of the sequence data. We present a method for determining the variants existing in a viral quasispecies in the case of two nearby ambiguous sequence positions by exploiting the effect of sequence context-dependent incorporation of dideoxynucleotides. The computational model was trained on data from sequencing chromatograms of clonal variants and was evaluated on two test sets of in vitro mixtures. The approach achieved high accuracies in identifying the mixture components of 97.4% on a test set in which the positions to be analyzed are only one base apart from each other, and of 84.5% on a test set in which the ambiguous positions are separated by three bases. In silico experiments suggest two major limitations of our approach in terms of accuracy. First, due to a basic limitation of Sanger sequencing, it is not possible to reliably detect minor variants with a relative frequency of no more than 10%. Second, the model cannot distinguish between mixtures of two or four clonal variants, if one of two sets of linear constraints is fulfilled. Furthermore, the approach requires repetitive sequencing of all variants that might be present in the mixture to be analyzed. Nevertheless, the effectiveness of our method on the two in vitro test sets shows that short-range linkage information of two ambiguous sequence positions can be inferred from Sanger sequencing chromatograms without any further assumptions on the mixture composition. Additionally, our model provides new insights into the established and widely used Sanger sequencing technology. The source code of our method is made available at http://bioinf.mpi-inf.mpg.de/publications/beggel/linkageinformation.zip. PMID:24376502

Investigation of a Sybr-Green-Based Method to Validate DNA Sequences for DNA Computing

DTIC Science & Technology

2005-05-01

OF A SYBR-GREEN-BASED METHOD TO VALIDATE DNA SEQUENCES FOR DNA COMPUTING 6. AUTHOR(S) Wendy Pogozelski, Salvatore Priore, Matthew Bernard ...simulated annealing. Biochemistry, 35, 14077-14089. 15 Pogozelski, W.K., Bernard , M.P. and Macula, A. (2004) DNA code validation using...and Clark, B.F.C. (eds) In RNA Biochemistry and Biotechnology, NATO ASI Series, Kluwer Academic Publishers. Zucker, M. and Stiegler , P. (1981

Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

NASA Astrophysics Data System (ADS)

Seto, Donald

The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

Histoimmunogenetics Markup Language 1.0: Reporting next generation sequencing-based HLA and KIR genotyping.

PubMed

Milius, Robert P; Heuer, Michael; Valiga, Daniel; Doroschak, Kathryn J; Kennedy, Caleb J; Bolon, Yung-Tsi; Schneider, Joel; Pollack, Jane; Kim, Hwa Ran; Cereb, Nezih; Hollenbach, Jill A; Mack, Steven J; Maiers, Martin

2015-12-01

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and Sequence Based Typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The multilocus sequence typing network: mlst.net.

PubMed

Aanensen, David M; Spratt, Brian G

2005-07-01

The unambiguous characterization of strains of a pathogen is crucial for addressing questions relating to its epidemiology, population and evolutionary biology. Multilocus sequence typing (MLST), which defines strains from the sequences at seven house-keeping loci, has become the method of choice for molecular typing of many bacterial and fungal pathogens (and non-pathogens), and MLST schemes and strain databases are available for a growing number of prokaryotic and eukaryotic organisms. Sequence data are ideal for strain characterization as they are unambiguous, meaning strains can readily be compared between laboratories via the Internet. Laboratories undertaking MLST can quickly progress from sequencing the seven gene fragments to characterizing their strains and relating them to those submitted by others and to the population as a whole. We provide the gateway to a number of MLST schemes, each of which contain a set of tools for the initial characterization of strains, and methods for relating query strains to other strains of the species, including clustering based on differences in allelic profiles, phylogenetic trees based on concatenated sequences, and a recently developed method (eBURST) for identifying clonal complexes within a species and displaying the overall structure of the population. This network of MLST websites is available at http://www.mlst.net.

Evaluating imputation algorithms for low-depth genotyping-by-sequencing (GBS) data

USDA-ARS?s Scientific Manuscript database

Well-powered genomic studies require genome-wide marker coverage across many individuals. For non-model species with few genomic resources, high-throughput sequencing (HTS) methods, such as Genotyping-By-Sequencing (GBS), offer an inexpensive alternative to array-based genotyping. Although affordabl...

Extracting flat-field images from scene-based image sequences using phase correlation

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

Caron, James N., E-mail: Caron@RSImd.com; Montes, Marcos J.; Obermark, Jerome L.

Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method usesmore » sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.« less

Sequence signatures of allosteric proteins towards rational design.

PubMed

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

2010-12-01

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

Development and application of a multilocus sequence analysis method for the identification of genotypes within genus Bradyrhizobium and for establishing nodule occupancy of soybean (Glycine max L. Merr)

USDA-ARS?s Scientific Manuscript database

A Multilocus Sequence Typing (MLST) method based on allelic variation of 7 chromosomal loci was developed for characterizing genotypes within the genus Bradyrhizobium. With the method 29 distinct multilocus genotypes (GTs) were identified among 191 culture collection soybean strains. The occupancy ...

Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

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

Andreasen, Daniel, E-mail: dana@dtu.dk; Van Leemput, Koen; Hansen, Rasmus H.

Purpose: In radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, the information on electron density must be derived from the MRI scan by creating a so-called pseudo computed tomography (pCT). This is a nontrivial task, since the voxel-intensities in an MRI scan are not uniquely related to electron density. To solve the task, voxel-based or atlas-based models have typically been used. The voxel-based models require a specialized dual ultrashort echo time MRI sequence for bone visualization and the atlas-based models require deformable registrations of conventional MRI scans. In this study, we investigate the potential of amore » patch-based method for creating a pCT based on conventional T{sub 1}-weighted MRI scans without using deformable registrations. We compare this method against two state-of-the-art methods within the voxel-based and atlas-based categories. Methods: The data consisted of CT and MRI scans of five cranial RT patients. To compare the performance of the different methods, a nested cross validation was done to find optimal model parameters for all the methods. Voxel-wise and geometric evaluations of the pCTs were done. Furthermore, a radiologic evaluation based on water equivalent path lengths was carried out, comparing the upper hemisphere of the head in the pCT and the real CT. Finally, the dosimetric accuracy was tested and compared for a photon treatment plan. Results: The pCTs produced with the patch-based method had the best voxel-wise, geometric, and radiologic agreement with the real CT, closely followed by the atlas-based method. In terms of the dosimetric accuracy, the patch-based method had average deviations of less than 0.5% in measures related to target coverage. Conclusions: We showed that a patch-based method could generate an accurate pCT based on conventional T{sub 1}-weighted MRI sequences and without deformable registrations. In our evaluations, the method performed better than existing voxel-based and atlas-based methods and showed a promising potential for RT of the brain based only on MRI.« less

DNA capture and next-generation sequencing can recover whole mitochondrial genomes from highly degraded samples for human identification

PubMed Central

2013-01-01

Background Mitochondrial DNA (mtDNA) typing can be a useful aid for identifying people from compromised samples when nuclear DNA is too damaged, degraded or below detection thresholds for routine short tandem repeat (STR)-based analysis. Standard mtDNA typing, focused on PCR amplicon sequencing of the control region (HVS I and HVS II), is limited by the resolving power of this short sequence, which misses up to 70% of the variation present in the mtDNA genome. Methods We used in-solution hybridisation-based DNA capture (using DNA capture probes prepared from modern human mtDNA) to recover mtDNA from post-mortem human remains in which the majority of DNA is both highly fragmented (<100 base pairs in length) and chemically damaged. The method ‘immortalises’ the finite quantities of DNA in valuable extracts as DNA libraries, which is followed by the targeted enrichment of endogenous mtDNA sequences and characterisation by next-generation sequencing (NGS). Results We sequenced whole mitochondrial genomes for human identification from samples where standard nuclear STR typing produced only partial profiles or demonstrably failed and/or where standard mtDNA hypervariable region sequences lacked resolving power. Multiple rounds of enrichment can substantially improve coverage and sequencing depth of mtDNA genomes from highly degraded samples. The application of this method has led to the reliable mitochondrial sequencing of human skeletal remains from unidentified World War Two (WWII) casualties approximately 70 years old and from archaeological remains (up to 2,500 years old). Conclusions This approach has potential applications in forensic science, historical human identification cases, archived medical samples, kinship analysis and population studies. In particular the methodology can be applied to any case, involving human or non-human species, where whole mitochondrial genome sequences are required to provide the highest level of maternal lineage discrimination. Multiple rounds of in-solution hybridisation-based DNA capture can retrieve whole mitochondrial genome sequences from even the most challenging samples. PMID:24289217

Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags

PubMed Central

2010-01-01

Intense interest centers on the role of the human gut microbiome in health and disease, but optimal methods for analysis are still under development. Here we present a study of methods for surveying bacterial communities in human feces using 454/Roche pyrosequencing of 16S rRNA gene tags. We analyzed fecal samples from 10 individuals and compared methods for storage, DNA purification and sequence acquisition. To assess reproducibility, we compared samples one cm apart on a single stool specimen for each individual. To analyze storage methods, we compared 1) immediate freezing at -80°C, 2) storage on ice for 24 or 3) 48 hours. For DNA purification methods, we tested three commercial kits and bead beating in hot phenol. Variations due to the different methodologies were compared to variation among individuals using two approaches--one based on presence-absence information for bacterial taxa (unweighted UniFrac) and the other taking into account their relative abundance (weighted UniFrac). In the unweighted analysis relatively little variation was associated with the different analytical procedures, and variation between individuals predominated. In the weighted analysis considerable variation was associated with the purification methods. Particularly notable was improved recovery of Firmicutes sequences using the hot phenol method. We also carried out surveys of the effects of different 454 sequencing methods (FLX versus Titanium) and amplification of different 16S rRNA variable gene segments. Based on our findings we present recommendations for protocols to collect, process and sequence bacterial 16S rDNA from fecal samples--some major points are 1) if feasible, bead-beating in hot phenol or use of the PSP kit improves recovery; 2) storage methods can be adjusted based on experimental convenience; 3) unweighted (presence-absence) comparisons are less affected by lysis method. PMID:20673359

Detection of nucleic acid sequences by invader-directed cleavage

DOEpatents

Brow, Mary Ann D.; Hall, Jeff Steven Grotelueschen; Lyamichev, Victor; Olive, David Michael; Prudent, James Robert

1999-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The 5' nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based by charge.

Multi person detection and tracking based on hierarchical level-set method

NASA Astrophysics Data System (ADS)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

A complexity measure based method for studying the dependance of 222Rn concentration time series on indoor air temperature and humidity.

PubMed

Mihailovic, D T; Udovičić, V; Krmar, M; Arsenić, I

2014-02-01

We have suggested a complexity measure based method for studying the dependence of measured (222)Rn concentration time series on indoor air temperature and humidity. This method is based on the Kolmogorov complexity (KL). We have introduced (i) the sequence of the KL, (ii) the Kolmogorov complexity highest value in the sequence (KLM) and (iii) the KL of the product of time series. The noticed loss of the KLM complexity of (222)Rn concentration time series can be attributed to the indoor air humidity that keeps the radon daughters in air. © 2013 Published by Elsevier Ltd.

Functional interrogation of non-coding DNA through CRISPR genome editing

PubMed Central

Canver, Matthew C.; Bauer, Daniel E.; Orkin, Stuart H.

2017-01-01

Methodologies to interrogate non-coding regions have lagged behind coding regions despite comprising the vast majority of the genome. However, the rapid evolution of clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing has provided a multitude of novel techniques for laboratory investigation including significant contributions to the toolbox for studying non-coding DNA. CRISPR-mediated loss-of-function strategies rely on direct disruption of the underlying sequence or repression of transcription without modifying the targeted DNA sequence. CRISPR-mediated gain-of-function approaches similarly benefit from methods to alter the targeted sequence through integration of customized sequence into the genome as well as methods to activate transcription. Here we review CRISPR-based loss- and gain-of-function techniques for the interrogation of non-coding DNA. PMID:28288828

[Study on ITS sequences of Aconitum vilmorinianum and its medicinal adulterant].

PubMed

Zhang, Xiao-nan; Du, Chun-hua; Fu, De-huan; Gao, Li; Zhou, Pei-jun; Wang, Li

2012-09-01

To analyze and compare the ITS sequences of Aconitum vilmorinianum and its medicinal adulterant Aconitum austroyunnanense. Total genomic DNA were extracted from sample materials by improved CTAB method, ITS sequences of samples were amplified using PCR systems, directly sequenced and analyzed using software DNAStar, ClustalX1.81 and MEGA 4.0. 299 consistent sites, 19 variable sites and 13 informative sites were found in ITS1 sequences, 162 consistent sites, 2 variable sites and 1 informative sites were found in 5.8S sequences, 217 consistent sites, 3 variable sites and 1 informative site were found in ITS2 sequences. Base transition and transversion was not found only in 5.8S sequences, 2 sites transition and 1 site transversion were found in ITS1 sequences, only 1 site transversion was found in ITS2 sequences comparting the ITS sequences data matrix. By analyzing the ITS sequences data matrix from 2 population of Aconitum vilmorinianum and 3 population of Aconitum austroyunnanense, we found a stable informative site at the 596th base in ITS2 sequences, in all the samples of Aconitum vilmorinianum the base was C, and in all the samples of Aconitum austroyunnanense the base was A. Aconitum vilmorinianum and Aconitum austroyunnanense can be identified by their characters of ITS sequences, and the variable sites in ITS1 sequences are more than in ITS2 sequences.

SU-F-J-112: Clinical Feasibility Test of An RF Pulse-Based MRI Method for the Quantitative Fat-Water Segmentation

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

Yee, S; Wloch, J; Pirkola, M

Purpose: Quantitative fat-water segmentation is important not only because of the clinical utility of fat-suppressed MRI images in better detecting lesions of clinical significance (in the midst of bright fat signal) but also because of the possible physical need, in which CT-like images based on the materials’ photon attenuation properties may have to be generated from MR images; particularly, as in the case of MR-only radiation oncology environment to obtain radiation dose calculation or as in the case of hybrid PET/MR modality to obtain attenuation correction map for the quantitative PET reconstruction. The majority of such fat-water quantitative segmentations havemore » been performed by utilizing the Dixon’s method and its variations, which have to enforce the proper settings (often predefined) of echo time (TE) in the pulse sequences. Therefore, such methods have been unable to be directly combined with those ultrashort TE (UTE) sequences that, taking the advantage of very low TE values (∼ 10’s microsecond), might be beneficial to directly detect bones. Recently, an RF pulse-based method (http://dx.doi.org/10.1016/j.mri.2015.11.006), termed as PROD pulse method, was introduced as a method of quantitative fat-water segmentation that does not have to depend on predefined TE settings. Here, the clinical feasibility of this method is verified in brain tumor patients by combining the PROD pulse with several sequences. Methods: In a clinical 3T MRI, the PROD pulse was combined with turbo spin echo (e.g. TR=1500, TE=16 or 60, ETL=15) or turbo field echo (e.g. TR=5.6, TE=2.8, ETL=12) sequences without specifying TE values. Results: The fat-water segmentation was possible without having to set specific TE values. Conclusion: The PROD pulse method is clinically feasible. Although not yet combined with UTE sequences in our laboratory, the method is potentially compatible with UTE sequences, and thus, might be useful to directly segment fat, water, bone and air.« less

Evaluation and integration of existing methods for computational prediction of allergens

PubMed Central

2013-01-01

Background Allergy involves a series of complex reactions and factors that contribute to the development of the disease and triggering of the symptoms, including rhinitis, asthma, atopic eczema, skin sensitivity, even acute and fatal anaphylactic shock. Prediction and evaluation of the potential allergenicity is of importance for safety evaluation of foods and other environment factors. Although several computational approaches for assessing the potential allergenicity of proteins have been developed, their performance and relative merits and shortcomings have not been compared systematically. Results To evaluate and improve the existing methods for allergen prediction, we collected an up-to-date definitive dataset consisting of 989 known allergens and massive putative non-allergens. The three most widely used allergen computational prediction approaches including sequence-, motif- and SVM-based (Support Vector Machine) methods were systematically compared using the defined parameters and we found that SVM-based method outperformed the other two methods with higher accuracy and specificity. The sequence-based method with the criteria defined by FAO/WHO (FAO: Food and Agriculture Organization of the United Nations; WHO: World Health Organization) has higher sensitivity of over 98%, but having a low specificity. The advantage of motif-based method is the ability to visualize the key motif within the allergen. Notably, the performances of the sequence-based method defined by FAO/WHO and motif eliciting strategy could be improved by the optimization of parameters. To facilitate the allergen prediction, we integrated these three methods in a web-based application proAP, which provides the global search of the known allergens and a powerful tool for allergen predication. Flexible parameter setting and batch prediction were also implemented. The proAP can be accessed at http://gmobl.sjtu.edu.cn/proAP/main.html. Conclusions This study comprehensively evaluated sequence-, motif- and SVM-based computational prediction approaches for allergens and optimized their parameters to obtain better performance. These findings may provide helpful guidance for the researchers in allergen-prediction. Furthermore, we integrated these methods into a web application proAP, greatly facilitating users to do customizable allergen search and prediction. PMID:23514097

Evaluation and integration of existing methods for computational prediction of allergens.

PubMed

Wang, Jing; Yu, Yabin; Zhao, Yunan; Zhang, Dabing; Li, Jing

2013-01-01

Allergy involves a series of complex reactions and factors that contribute to the development of the disease and triggering of the symptoms, including rhinitis, asthma, atopic eczema, skin sensitivity, even acute and fatal anaphylactic shock. Prediction and evaluation of the potential allergenicity is of importance for safety evaluation of foods and other environment factors. Although several computational approaches for assessing the potential allergenicity of proteins have been developed, their performance and relative merits and shortcomings have not been compared systematically. To evaluate and improve the existing methods for allergen prediction, we collected an up-to-date definitive dataset consisting of 989 known allergens and massive putative non-allergens. The three most widely used allergen computational prediction approaches including sequence-, motif- and SVM-based (Support Vector Machine) methods were systematically compared using the defined parameters and we found that SVM-based method outperformed the other two methods with higher accuracy and specificity. The sequence-based method with the criteria defined by FAO/WHO (FAO: Food and Agriculture Organization of the United Nations; WHO: World Health Organization) has higher sensitivity of over 98%, but having a low specificity. The advantage of motif-based method is the ability to visualize the key motif within the allergen. Notably, the performances of the sequence-based method defined by FAO/WHO and motif eliciting strategy could be improved by the optimization of parameters. To facilitate the allergen prediction, we integrated these three methods in a web-based application proAP, which provides the global search of the known allergens and a powerful tool for allergen predication. Flexible parameter setting and batch prediction were also implemented. The proAP can be accessed at http://gmobl.sjtu.edu.cn/proAP/main.html. This study comprehensively evaluated sequence-, motif- and SVM-based computational prediction approaches for allergens and optimized their parameters to obtain better performance. These findings may provide helpful guidance for the researchers in allergen-prediction. Furthermore, we integrated these methods into a web application proAP, greatly facilitating users to do customizable allergen search and prediction.

On the value of Mendelian laws of segregation in families: data quality control, imputation and beyond

PubMed Central

Blue, Elizabeth Marchani; Sun, Lei; Tintle, Nathan L.; Wijsman, Ellen M.

2014-01-01

When analyzing family data, we dream of perfectly informative data, even whole genome sequences (WGS) for all family members. Reality intervenes, and we find next-generation sequence (NGS) data have error, and are often too expensive or impossible to collect on everyone. Genetic Analysis Workshop 18 groups “Quality Control” and “Dropping WGS through families using GWAS framework” focused on finding, correcting, and using errors within the available sequence and family data, developing methods to infer and analyze missing sequence data among relatives, and testing for linkage and association with simulated blood pressure. We found that single nucleotide polymorphisms, NGS, and imputed data are generally concordant, but that errors are particularly likely at rare variants, homozygous genotypes, within regions with repeated sequences or structural variants, and within sequence data imputed from unrelateds. Admixture complicated identification of cryptic relatedness, but information from Mendelian transmission improved error detection and provided an estimate of the de novo mutation rate. Both genotype and pedigree errors had an adverse effect on subsequent analyses. Computationally fast rules-based imputation was accurate, but could not cover as many loci or subjects as more computationally demanding probability-based methods. Incorporating population-level data into pedigree-based imputation methods improved results. Observed data outperformed imputed data in association testing, but imputed data were also useful. We discuss the strengths and weaknesses of existing methods, and suggest possible future directions. Topics include improving communication between those performing data collection and analysis, establishing thresholds for and improving imputation quality, and incorporating error into imputation and analytical models. PMID:25112184

Genotype calling from next-generation sequencing data using haplotype information of reads

PubMed Central

Zhi, Degui; Wu, Jihua; Liu, Nianjun; Zhang, Kui

2012-01-01

Motivation: Low coverage sequencing provides an economic strategy for whole genome sequencing. When sequencing a set of individuals, genotype calling can be challenging due to low sequencing coverage. Linkage disequilibrium (LD) based refinement of genotyping calling is essential to improve the accuracy. Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods. Results: In this article, we introduce a new Hidden Markov Model (HMM)-based method that can take into account jumping reads information across adjacent PPSs and implement it in the HapSeq program. Our method extends the HMM in Thunder and explicitly models jumping reads information as emission probabilities conditional on the states of adjacent PPSs. Our simulation results show that, compared to Thunder, HapSeq reduces the genotyping error rate by 30%, from 0.86% to 0.60%. The results from the 1000 Genomes Project show that HapSeq reduces the genotyping error rate by 12 and 9%, from 2.24% and 2.76% to 1.97% and 2.50% for individuals with European and African ancestry, respectively. We expect our program can improve genotyping qualities of the large number of ongoing and planned whole genome sequencing projects. Contact: dzhi@ms.soph.uab.edu; kzhang@ms.soph.uab.edu Availability: The software package HapSeq and its manual can be found and downloaded at www.ssg.uab.edu/hapseq/. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22285565

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

Simultaneous digital quantification and fluorescence-based size characterization of massively parallel sequencing libraries.

PubMed

Laurie, Matthew T; Bertout, Jessica A; Taylor, Sean D; Burton, Joshua N; Shendure, Jay A; Bielas, Jason H

2013-08-01

Due to the high cost of failed runs and suboptimal data yields, quantification and determination of fragment size range are crucial steps in the library preparation process for massively parallel sequencing (or next-generation sequencing). Current library quality control methods commonly involve quantification using real-time quantitative PCR and size determination using gel or capillary electrophoresis. These methods are laborious and subject to a number of significant limitations that can make library calibration unreliable. Herein, we propose and test an alternative method for quality control of sequencing libraries using droplet digital PCR (ddPCR). By exploiting a correlation we have discovered between droplet fluorescence and amplicon size, we achieve the joint quantification and size determination of target DNA with a single ddPCR assay. We demonstrate the accuracy and precision of applying this method to the preparation of sequencing libraries.

Next generation sequencing (NGS): a golden tool in forensic toolkit.

PubMed

Aly, S M; Sabri, D M

The DNA analysis is a cornerstone in contemporary forensic sciences. DNA sequencing technologies are powerful tools that enrich molecular sciences in the past based on Sanger sequencing and continue to glowing these sciences based on Next generation sequencing (NGS). Next generation sequencing has excellent potential to flourish and increase the molecular applications in forensic sciences by jumping over the pitfalls of the conventional method of sequencing. The main advantages of NGS compared to conventional method that it utilizes simultaneously a large number of genetic markers with high-resolution of genetic data. These advantages will help in solving several challenges such as mixture analysis and dealing with minute degraded samples. Based on these new technologies, many markers could be examined to get important biological data such as age, geographical origins, tissue type determination, external visible traits and monozygotic twins identification. It also could get data related to microbes, insects, plants and soil which are of great medico-legal importance. Despite the dozens of forensic research involving NGS, there are requirements before using this technology routinely in forensic cases. Thus, there is a great need to more studies that address robustness of these techniques. Therefore, this work highlights the applications of forensic sciences in the era of massively parallel sequencing.

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

PubMed

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

2018-07-01

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

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

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

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

Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

PubMed

Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

2016-09-07

Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning predictive models that use pattern discovery--a bootstrap evaluative approach applied in organ functioning sequences.

PubMed

Toma, Tudor; Bosman, Robert-Jan; Siebes, Arno; Peek, Niels; Abu-Hanna, Ameen

2010-08-01

An important problem in the Intensive Care is how to predict on a given day of stay the eventual hospital mortality for a specific patient. A recent approach to solve this problem suggested the use of frequent temporal sequences (FTSs) as predictors. Methods following this approach were evaluated in the past by inducing a model from a training set and validating the prognostic performance on an independent test set. Although this evaluative approach addresses the validity of the specific models induced in an experiment, it falls short of evaluating the inductive method itself. To achieve this, one must account for the inherent sources of variation in the experimental design. The main aim of this work is to demonstrate a procedure based on bootstrapping, specifically the .632 bootstrap procedure, for evaluating inductive methods that discover patterns, such as FTSs. A second aim is to apply this approach to find out whether a recently suggested inductive method that discovers FTSs of organ functioning status is superior over a traditional method that does not use temporal sequences when compared on each successive day of stay at the Intensive Care Unit. The use of bootstrapping with logistic regression using pre-specified covariates is known in the statistical literature. Using inductive methods of prognostic models based on temporal sequence discovery within the bootstrap procedure is however novel at least in predictive models in the Intensive Care. Our results of applying the bootstrap-based evaluative procedure demonstrate the superiority of the FTS-based inductive method over the traditional method in terms of discrimination as well as accuracy. In addition we illustrate the insights gained by the analyst into the discovered FTSs from the bootstrap samples. Copyright 2010 Elsevier Inc. All rights reserved.

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods.

PubMed

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson's correlation coefficients >0.83, R2 .67-.97). The results from the downsampled data and the high-resolution data were similar. Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed.

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

PubMed

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

2007-12-01

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

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes.

PubMed

Jespersen, Martin Closter; Peters, Bjoern; Nielsen, Morten; Marcatili, Paolo

2017-07-03

Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy and non-expert users. We believe that BepiPred-2.0 will be a valuable tool for the bioinformatics and immunology community. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Long-PCR based next generation sequencing of the whole mitochondrial genome of the peacock skate Pavoraja nitida (Elasmobranchii: Arhynchobatidae).

PubMed

Yang, Lei; Naylor, Gavin J P

2016-01-01

We determined the complete mitochondrial genome sequence (16,760 bp) of the peacock skate Pavoraja nitida using a long-PCR based next generation sequencing method. It has 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and 1 control region in the typical vertebrate arrangement. Primers, protocols, and procedures used to obtain this mitogenome are provided. We anticipate that this approach will facilitate rapid collection of mitogenome sequences for studies on phylogenetic relationships, population genetics, and conservation of cartilaginous fishes.

Computational approaches for identification of conserved/unique binding pockets in the A chain of ricin

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

Ecale Zhou, C L; Zemla, A T; Roe, D

2005-01-29

Specific and sensitive ligand-based protein detection assays that employ antibodies or small molecules such as peptides, aptamers, or other small molecules require that the corresponding surface region of the protein be accessible and that there be minimal cross-reactivity with non-target proteins. To reduce the time and cost of laboratory screening efforts for diagnostic reagents, we developed new methods for evaluating and selecting protein surface regions for ligand targeting. We devised combined structure- and sequence-based methods for identifying 3D epitopes and binding pockets on the surface of the A chain of ricin that are conserved with respect to a set ofmore » ricin A chains and unique with respect to other proteins. We (1) used structure alignment software to detect structural deviations and extracted from this analysis the residue-residue correspondence, (2) devised a method to compare corresponding residues across sets of ricin structures and structures of closely related proteins, (3) devised a sequence-based approach to determine residue infrequency in local sequence context, and (4) modified a pocket-finding algorithm to identify surface crevices in close proximity to residues determined to be conserved/unique based on our structure- and sequence-based methods. In applying this combined informatics approach to ricin A we identified a conserved/unique pocket in close proximity (but not overlapping) the active site that is suitable for bi-dentate ligand development. These methods are generally applicable to identification of surface epitopes and binding pockets for development of diagnostic reagents, therapeutics, and vaccines.« less

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.

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

PubMed Central

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

2015-01-01

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

The complete genome sequences of 65 Campylobacter jejuni and C. coli strains

USDA-ARS?s Scientific Manuscript database

Campylobacter jejuni (Cj) and C. coli (Cc) are genetically highly diverse based on various molecular methods including MLST, microarray-based comparisons and the whole genome sequences of a few strains. Cj and Cc diversity is also exhibited by variable capsular polysaccharides (CPS) that are the maj...

Image encryption using random sequence generated from generalized information domain

NASA Astrophysics Data System (ADS)

Xia-Yan, Zhang; Guo-Ji, Zhang; Xuan, Li; Ya-Zhou, Ren; Jie-Hua, Wu

2016-05-01

A novel image encryption method based on the random sequence generated from the generalized information domain and permutation-diffusion architecture is proposed. The random sequence is generated by reconstruction from the generalized information file and discrete trajectory extraction from the data stream. The trajectory address sequence is used to generate a P-box to shuffle the plain image while random sequences are treated as keystreams. A new factor called drift factor is employed to accelerate and enhance the performance of the random sequence generator. An initial value is introduced to make the encryption method an approximately one-time pad. Experimental results show that the random sequences pass the NIST statistical test with a high ratio and extensive analysis demonstrates that the new encryption scheme has superior security.

Estimation of the genome sizes of the chigger mites Leptotrombidium pallidum and Leptotrombidium scutellare based on quantitative PCR and k-mer analysis

PubMed Central

2014-01-01

Background Leptotrombidium pallidum and Leptotrombidium scutellare are the major vector mites for Orientia tsutsugamushi, the causative agent of scrub typhus. Before these organisms can be subjected to whole-genome sequencing, it is necessary to estimate their genome sizes to obtain basic information for establishing the strategies that should be used for genome sequencing and assembly. Method The genome sizes of L. pallidum and L. scutellare were estimated by a method based on quantitative real-time PCR. In addition, a k-mer analysis of the whole-genome sequences obtained through Illumina sequencing was conducted to verify the mutual compatibility and reliability of the results. Results The genome sizes estimated using qPCR were 191 ± 7 Mb for L. pallidum and 262 ± 13 Mb for L. scutellare. The k-mer analysis-based genome lengths were estimated to be 175 Mb for L. pallidum and 286 Mb for L. scutellare. The estimates from these two independent methods were mutually complementary and within a similar range to those of other Acariform mites. Conclusions The estimation method based on qPCR appears to be a useful alternative when the standard methods, such as flow cytometry, are impractical. The relatively small estimated genome sizes should facilitate whole-genome analysis, which could contribute to our understanding of Arachnida genome evolution and provide key information for scrub typhus prevention and mite vector competence. PMID:24947244

High resolution identity testing of inactivated poliovirus vaccines

PubMed Central

Mee, Edward T.; Minor, Philip D.; Martin, Javier

2015-01-01

Background Definitive identification of poliovirus strains in vaccines is essential for quality control, particularly where multiple wild-type and Sabin strains are produced in the same facility. Sequence-based identification provides the ultimate in identity testing and would offer several advantages over serological methods. Methods We employed random RT-PCR and high throughput sequencing to recover full-length genome sequences from monovalent and trivalent poliovirus vaccine products at various stages of the manufacturing process. Results All expected strains were detected in previously characterised products and the method permitted identification of strains comprising as little as 0.1% of sequence reads. Highly similar Mahoney and Sabin 1 strains were readily discriminated on the basis of specific variant positions. Analysis of a product known to contain incorrect strains demonstrated that the method correctly identified the contaminants. Conclusion Random RT-PCR and shotgun sequencing provided high resolution identification of vaccine components. In addition to the recovery of full-length genome sequences, the method could also be easily adapted to the characterisation of minor variant frequencies and distinction of closely related products on the basis of distinguishing consensus and low frequency polymorphisms. PMID:26049003

Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding.

PubMed

Nguyen, Dang; Luo, Wei; Venkatesh, Svetha; Phung, Dinh

2018-04-11

Evidence-based medicine often involves the identification of patients with similar conditions, which are often captured in ICD (International Classification of Diseases (World Health Organization 2013)) code sequences. With no satisfying prior solutions for matching ICD-10 code sequences, this paper presents a method which effectively captures the clinical similarity among routine patients who have multiple comorbidities and complex care needs. Our method leverages the recent progress in representation learning of individual ICD-10 codes, and it explicitly uses the sequential order of codes for matching. Empirical evaluation on a state-wide cancer data collection shows that our proposed method achieves significantly higher matching performance compared with state-of-the-art methods ignoring the sequential order. Our method better identifies similar patients in a number of clinical outcomes including readmission and mortality outlook. Although this paper focuses on ICD-10 diagnosis code sequences, our method can be adapted to work with other codified sequence data.

Lossy compression of quality scores in genomic data.

PubMed

Cánovas, Rodrigo; Moffat, Alistair; Turpin, Andrew

2014-08-01

Next-generation sequencing technologies are revolutionizing medicine. Data from sequencing technologies are typically represented as a string of bases, an associated sequence of per-base quality scores and other metadata, and in aggregate can require a large amount of space. The quality scores show how accurate the bases are with respect to the sequencing process, that is, how confident the sequencer is of having called them correctly, and are the largest component in datasets in which they are retained. Previous research has examined how to store sequences of bases effectively; here we add to that knowledge by examining methods for compressing quality scores. The quality values originate in a continuous domain, and so if a fidelity criterion is introduced, it is possible to introduce flexibility in the way these values are represented, allowing lossy compression over the quality score data. We present existing compression options for quality score data, and then introduce two new lossy techniques. Experiments measuring the trade-off between compression ratio and information loss are reported, including quantifying the effect of lossy representations on a downstream application that carries out single nucleotide polymorphism and insert/deletion detection. The new methods are demonstrably superior to other techniques when assessed against the spectrum of possible trade-offs between storage required and fidelity of representation. An implementation of the methods described here is available at https://github.com/rcanovas/libCSAM. rcanovas@student.unimelb.edu.au Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Zepto-molar electrochemical detection of Brucella genome based on gold nanoribbons covered by gold nanoblooms

NASA Astrophysics Data System (ADS)

Rahi, Amid; Sattarahmady, Naghmeh; Heli, Hossein

2015-12-01

Gold nanoribbons covered by gold nanoblooms were sonoelectrodeposited on a polycrystalline gold surface at -1800 mV (vs. AgCl) with the assistance of ultrasound and co-occurrence of the hydrogen evolution reaction. The nanostructure, as a transducer, was utilized to immobilize a Brucella-specific probe and fabrication of a genosensor, and the process of immobilization and hybridization was detected by electrochemical methods, using methylene blue as a redox marker. The proposed method for detection of the complementary sequence, sequences with base-mismatched (one-, two- and three-base mismatches), and the sequence of non-complementary sequence was assayed. The fabricated genosensor was evaluated for the assay of the bacteria in the cultured and human samples without polymerase chain reactions (PCR). The genosensor could detect the complementary sequence with a calibration sensitivity of 0.40 μA dm3 mol-1, a linear concentration range of 10 zmol dm-3 to 10 pmol dm-3, and a detection limit of 1.71 zmol dm-3.

Primer-independent RNA sequencing with bacteriophage phi6 RNA polymerase and chain terminators.

PubMed

Makeyev, E V; Bamford, D H

2001-05-01

Here we propose a new general method for directly determining RNA sequence based on the use of the RNA-dependent RNA polymerase from bacteriophage phi6 and the chain terminators (RdRP sequencing). The following properties of the polymerase render it appropriate for this application: (1) the phi6 polymerase can replicate a number of single-stranded RNA templates in vitro. (2) In contrast to the primer-dependent DNA polymerases utilized in the sequencing procedure by Sanger et al. (Proc Natl Acad Sci USA, 1977, 74:5463-5467), it initiates nascent strand synthesis without a primer, starting the polymerization on the very 3'-terminus of the template. (3) The polymerase can incorporate chain-terminating nucleotide analogs into the nascent RNA chain to produce a set of base-specific termination products. Consequently, 3' proximal or even complete sequence of many target RNA molecules can be rapidly deduced without prior sequence information. The new technique proved useful for sequencing several synthetic ssRNA templates. Furthermore, using genomic segments of the bluetongue virus we show that RdRP sequencing can also be applied to naturally occurring dsRNA templates. This suggests possible uses of the method in the RNA virus research and diagnostics.

Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation sequencing.

PubMed

Watanabe, Manabu; Kusano, Junko; Ohtaki, Shinsaku; Ishikura, Takashi; Katayama, Jin; Koguchi, Akira; Paumen, Michael; Hayashi, Yoshiharu

2014-09-01

Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line) were used as a model. Single-cell capture was performed using laser capture microdissection (LCM) with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈ 10(6) cells) were subjected to whole genome amplification (WGA). For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel) was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 10(31-35). For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100 × were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100 × were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.

`Inter-Arrival Time' Inspired Algorithm and its Application in Clustering and Molecular Phylogeny

NASA Astrophysics Data System (ADS)

Kolekar, Pandurang S.; Kale, Mohan M.; Kulkarni-Kale, Urmila

2010-10-01

Bioinformatics, being multidisciplinary field, involves applications of various methods from allied areas of Science for data mining using computational approaches. Clustering and molecular phylogeny is one of the key areas in Bioinformatics, which help in study of classification and evolution of organisms. Molecular phylogeny algorithms can be divided into distance based and character based methods. But most of these methods are dependent on pre-alignment of sequences and become computationally intensive with increase in size of data and hence demand alternative efficient approaches. `Inter arrival time distribution' (IATD) is a popular concept in the theory of stochastic system modeling but its potential in molecular data analysis has not been fully explored. The present study reports application of IATD in Bioinformatics for clustering and molecular phylogeny. The proposed method provides IATDs of nucleotides in genomic sequences. The distance function based on statistical parameters of IATDs is proposed and distance matrix thus obtained is used for the purpose of clustering and molecular phylogeny. The method is applied on a dataset of 3' non-coding region sequences (NCR) of Dengue virus type 3 (DENV-3), subtype III, reported in 2008. The phylogram thus obtained revealed the geographical distribution of DENV-3 isolates. Sri Lankan DENV-3 isolates were further observed to be clustered in two sub-clades corresponding to pre and post Dengue hemorrhagic fever emergence groups. These results are consistent with those reported earlier, which are obtained using pre-aligned sequence data as an input. These findings encourage applications of the IATD based method in molecular phylogenetic analysis in particular and data mining in general.

Magnetic bead purification of labeled DNA fragments forhigh-throughput capillary electrophoresis sequencing

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

Elkin, Christopher; Kapur, Hitesh; Smith, Troy

2001-09-15

We have developed an automated purification method for terminator sequencing products based on a magnetic bead technology. This 384-well protocol generates labeled DNA fragments that are essentially free of contaminates for less than $0.005 per reaction. In comparison to laborious ethanol precipitation protocols, this method increases the phred20 read length by forty bases with various DNA templates such as PCR fragments, Plasmids, Cosmids and RCA products. Our method eliminates centrifugation and is compatible with both the MegaBACE 1000 and ABIPrism 3700 capillary instruments. As of September 2001, this method has produced over 1.6 million samples with 93 percent averaging 620more » phred20 bases as part of Joint Genome Institutes Production Process.« less

Development of an ELA-DRA gene typing method based on pyrosequencing technology.

PubMed

Díaz, S; Echeverría, M G; It, V; Posik, D M; Rogberg-Muñoz, A; Pena, N L; Peral-García, P; Vega-Pla, J L; Giovambattista, G

2008-11-01

The polymorphism of equine lymphocyte antigen (ELA) class II DRA gene had been detected by polymerase chain reaction-single-strand conformational polymorphism (PCR-SSCP) and reference strand-mediated conformation analysis. These methodologies allowed to identify 11 ELA-DRA exon 2 sequences, three of which are widely distributed among domestic horse breeds. Herein, we describe the development of a pyrosequencing-based method applicable to ELA-DRA typing, by screening samples from eight different horse breeds previously typed by PCR-SSCP. This sequence-based method would be useful in high-throughput genotyping of major histocompatibility complex genes in horses and other animal species, making this system interesting as a rapid screening method for animal genotyping of immune-related genes.

BPP: a sequence-based algorithm for branch point prediction.

PubMed

Zhang, Qing; Fan, Xiaodan; Wang, Yejun; Sun, Ming-An; Shao, Jianlin; Guo, Dianjing

2017-10-15

Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research. We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods. Availability and implementation: https://github.com/zhqingit/BPP. djguo@cuhk.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

DECIPHER, a Search-Based Approach to Chimera Identification for 16S rRNA Sequences

PubMed Central

Wright, Erik S.; Yilmaz, L. Safak

2012-01-01

DECIPHER is a new method for finding 16S rRNA chimeric sequences by the use of a search-based approach. The method is based upon detecting short fragments that are uncommon in the phylogenetic group where a query sequence is classified but frequently found in another phylogenetic group. The algorithm was calibrated for full sequences (fs_DECIPHER) and short sequences (ss_DECIPHER) and benchmarked against WigeoN (Pintail), ChimeraSlayer, and Uchime using artificially generated chimeras. Overall, ss_DECIPHER and Uchime provided the highest chimera detection for sequences 100 to 600 nucleotides long (79% and 81%, respectively), but Uchime's performance deteriorated for longer sequences, while ss_DECIPHER maintained a high detection rate (89%). Both methods had low false-positive rates (1.3% and 1.6%). The more conservative fs_DECIPHER, benchmarked only for sequences longer than 600 nucleotides, had an overall detection rate lower than that of ss_DECIPHER (75%) but higher than those of the other programs. In addition, fs_DECIPHER had the lowest false-positive rate among all the benchmarked programs (<0.20%). DECIPHER was outperformed only by ChimeraSlayer and Uchime when chimeras were formed from closely related parents (less than 10% divergence). Given the differences in the programs, it was possible to detect over 89% of all chimeras with just the combination of ss_DECIPHER and Uchime. Using fs_DECIPHER, we detected between 1% and 2% additional chimeras in the RDP, SILVA, and Greengenes databases from which chimeras had already been removed with Pintail or Bellerophon. DECIPHER was implemented in the R programming language and is directly accessible through a webpage or by downloading the program as an R package (http://DECIPHER.cee.wisc.edu). PMID:22101057

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

PubMed

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

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

Monitoring Arthrobacter protophormiae RKJ100 in a 'tag and chase' method during p-nitrophenol bio-remediation in soil microcosms.

PubMed

Pandey, Gunjan; Pandey, Janmejay; Jain, Rakesh K

2006-05-01

Monitoring of micro-organisms released deliberately into the environment is essential to assess their movement during the bio-remediation process. During the last few years, DNA-based genetic methods have emerged as the preferred method for such monitoring; however, their use is restricted in cases where organisms used for bio-remediation are not well characterized or where the public domain databases do not provide sufficient information regarding their sequence. For monitoring of such micro-organisms, alternate approaches have to be undertaken. In this study, we have specifically monitored a p-nitrophenol (PNP)-degrading organism, Arthrobacter protophormiae RKJ100, using molecular methods during PNP degradation in soil microcosm. Cells were tagged with a transposon-based foreign DNA sequence prior to their introduction into PNP-contaminated microcosms. Later, this artificially introduced DNA sequence was PCR-amplified to distinguish the bio-augmented organism from the indigenous microflora during PNP bio-remediation.

Polymerase Chain Reaction (PCR)-based methods for detection and identification of mycotoxigenic Penicillium species using conserved genes

USDA-ARS?s Scientific Manuscript database

Polymerase chain reaction amplification of conserved genes and sequence analysis provides a very powerful tool for the identification of toxigenic as well as non-toxigenic Penicillium species. Sequences are obtained by amplification of the gene fragment, sequencing via capillary electrophoresis of d...

Using distances between Top-n-gram and residue pairs for protein remote homology detection.

PubMed

Liu, Bin; Xu, Jinghao; Zou, Quan; Xu, Ruifeng; Wang, Xiaolong; Chen, Qingcai

2014-01-01

Protein remote homology detection is one of the central problems in bioinformatics, which is important for both basic research and practical application. Currently, discriminative methods based on Support Vector Machines (SVMs) achieve the state-of-the-art performance. Exploring feature vectors incorporating the position information of amino acids or other protein building blocks is a key step to improve the performance of the SVM-based methods. Two new methods for protein remote homology detection were proposed, called SVM-DR and SVM-DT. SVM-DR is a sequence-based method, in which the feature vector representation for protein is based on the distances between residue pairs. SVM-DT is a profile-based method, which considers the distances between Top-n-gram pairs. Top-n-gram can be viewed as a profile-based building block of proteins, which is calculated from the frequency profiles. These two methods are position dependent approaches incorporating the sequence-order information of protein sequences. Various experiments were conducted on a benchmark dataset containing 54 families and 23 superfamilies. Experimental results showed that these two new methods are very promising. Compared with the position independent methods, the performance improvement is obvious. Furthermore, the proposed methods can also provide useful insights for studying the features of protein families. The better performance of the proposed methods demonstrates that the position dependant approaches are efficient for protein remote homology detection. Another advantage of our methods arises from the explicit feature space representation, which can be used to analyze the characteristic features of protein families. The source code of SVM-DT and SVM-DR is available at http://bioinformatics.hitsz.edu.cn/DistanceSVM/index.jsp.

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

PubMed

Mizianty, Marcin J; Kurgan, Lukasz

2009-12-13

Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/.

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

PubMed Central

2009-01-01

Background Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. Results The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. Conclusions The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/. PMID:20003388

Towards fully automated structure-based function prediction in structural genomics: a case study.

PubMed

Watson, James D; Sanderson, Steve; Ezersky, Alexandra; Savchenko, Alexei; Edwards, Aled; Orengo, Christine; Joachimiak, Andrzej; Laskowski, Roman A; Thornton, Janet M

2007-04-13

As the global Structural Genomics projects have picked up pace, the number of structures annotated in the Protein Data Bank as hypothetical protein or unknown function has grown significantly. A major challenge now involves the development of computational methods to assign functions to these proteins accurately and automatically. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI), we review the success of the pipeline and the importance of structure-based function prediction. As a dataset, we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity that is difficult to identify using current sequence-based methods. No one method is successful in all cases, so, through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chances that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology (GO) schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment.

Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics.

PubMed

Ren, Jie; Song, Kai; Deng, Minghua; Reinert, Gesine; Cannon, Charles H; Sun, Fengzhu

2016-04-01

Next-generation sequencing (NGS) technologies generate large amounts of short read data for many different organisms. The fact that NGS reads are generally short makes it challenging to assemble the reads and reconstruct the original genome sequence. For clustering genomes using such NGS data, word-count based alignment-free sequence comparison is a promising approach, but for this approach, the underlying expected word counts are essential.A plausible model for this underlying distribution of word counts is given through modeling the DNA sequence as a Markov chain (MC). For single long sequences, efficient statistics are available to estimate the order of MCs and the transition probability matrix for the sequences. As NGS data do not provide a single long sequence, inference methods on Markovian properties of sequences based on single long sequences cannot be directly used for NGS short read data. Here we derive a normal approximation for such word counts. We also show that the traditional Chi-square statistic has an approximate gamma distribution ,: using the Lander-Waterman model for physical mapping. We propose several methods to estimate the order of the MC based on NGS reads and evaluate those using simulations. We illustrate the applications of our results by clustering genomic sequences of several vertebrate and tree species based on NGS reads using alignment-free sequence dissimilarity measures. We find that the estimated order of the MC has a considerable effect on the clustering results ,: and that the clustering results that use a N: MC of the estimated order give a plausible clustering of the species. Our implementation of the statistics developed here is available as R package 'NGS.MC' at http://www-rcf.usc.edu/∼fsun/Programs/NGS-MC/NGS-MC.html fsun@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Alignment methods: strategies, challenges, benchmarking, and comparative overview.

PubMed

Löytynoja, Ari

2012-01-01

Comparative evolutionary analyses of molecular sequences are solely based on the identities and differences detected between homologous characters. Errors in this homology statement, that is errors in the alignment of the sequences, are likely to lead to errors in the downstream analyses. Sequence alignment and phylogenetic inference are tightly connected and many popular alignment programs use the phylogeny to divide the alignment problem into smaller tasks. They then neglect the phylogenetic tree, however, and produce alignments that are not evolutionarily meaningful. The use of phylogeny-aware methods reduces the error but the resulting alignments, with evolutionarily correct representation of homology, can challenge the existing practices and methods for viewing and visualising the sequences. The inter-dependency of alignment and phylogeny can be resolved by joint estimation of the two; methods based on statistical models allow for inferring the alignment parameters from the data and correctly take into account the uncertainty of the solution but remain computationally challenging. Widely used alignment methods are based on heuristic algorithms and unlikely to find globally optimal solutions. The whole concept of one correct alignment for the sequences is questionable, however, as there typically exist vast numbers of alternative, roughly equally good alignments that should also be considered. This uncertainty is hidden by many popular alignment programs and is rarely correctly taken into account in the downstream analyses. The quest for finding and improving the alignment solution is complicated by the lack of suitable measures of alignment goodness. The difficulty of comparing alternative solutions also affects benchmarks of alignment methods and the results strongly depend on the measure used. As the effects of alignment error cannot be predicted, comparing the alignments' performance in downstream analyses is recommended.

Reproducible segmentation of white matter hyperintensities using a new statistical definition.

PubMed

Damangir, Soheil; Westman, Eric; Simmons, Andrew; Vrenken, Hugo; Wahlund, Lars-Olof; Spulber, Gabriela

2017-06-01

We present a method based on a proposed statistical definition of white matter hyperintensities (WMH), which can work with any combination of conventional magnetic resonance (MR) sequences without depending on manually delineated samples. T1-weighted, T2-weighted, FLAIR, and PD sequences acquired at 1.5 Tesla from 119 subjects from the Kings Health Partners-Dementia Case Register (healthy controls, mild cognitive impairment, Alzheimer's disease) were used. The segmentation was performed using a proposed definition for WMH based on the one-tailed Kolmogorov-Smirnov test. The presented method was verified, given all possible combinations of input sequences, against manual segmentations and a high similarity (Dice 0.85-0.91) was observed. Comparing segmentations with different input sequences to one another also yielded a high similarity (Dice 0.83-0.94) that exceeded intra-rater similarity (Dice 0.75-0.91). We compared the results with those of other available methods and showed that the segmentation based on the proposed definition has better accuracy and reproducibility in the test dataset used. Overall, the presented definition is shown to produce accurate results with higher reproducibility than manual delineation. This approach can be an alternative to other manual or automatic methods not only because of its accuracy, but also due to its good reproducibility.

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

PubMed

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

2014-11-01

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

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

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

Feng, Shihai; Lo, Chien-Chi; Li, Po-E

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

DOE PAGES

Feng, Shihai; Lo, Chien-Chi; Li, Po-E; ...

2016-02-29

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

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.

Quantification of the methylation status of the PWS/AS imprinted region: comparison of two approaches based on bisulfite sequencing and methylation-sensitive MLPA.

PubMed

Dikow, Nicola; Nygren, Anders Oh; Schouten, Jan P; Hartmann, Carolin; Krämer, Nikola; Janssen, Bart; Zschocke, Johannes

2007-06-01

Standard methods used for genomic methylation analysis allow the detection of complete absence of either methylated or non-methylated alleles but are usually unable to detect changes in the proportion of methylated and unmethylated alleles. We compare two methods for quantitative methylation analysis, using the chromosome 15q11-q13 imprinted region as model. Absence of the non-methylated paternal allele in this region leads to Prader-Willi syndrome (PWS) whilst absence of the methylated maternal allele results in Angelman syndrome (AS). A proportion of AS is caused by mosaic imprinting defects which may be missed with standard methods and require quantitative analysis for their detection. Sequence-based quantitative methylation analysis (SeQMA) involves quantitative comparison of peaks generated through sequencing reactions after bisulfite treatment. It is simple, cost-effective and can be easily established for a large number of genes. However, our results support previous suggestions that methods based on bisulfite treatment may be problematic for exact quantification of methylation status. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) avoids bisulfite treatment. It detects changes in both CpG methylation as well as copy number of up to 40 chromosomal sequences in one simple reaction. Once established in a laboratory setting, the method is more accurate, reliable and less time consuming.

An automated genotyping tool for enteroviruses and noroviruses.

PubMed

Kroneman, A; Vennema, H; Deforche, K; v d Avoort, H; Peñaranda, S; Oberste, M S; Vinjé, J; Koopmans, M

2011-06-01

Molecular techniques are established as routine in virological laboratories and virus typing through (partial) sequence analysis is increasingly common. Quality assurance for the use of typing data requires harmonization of genotype nomenclature, and agreement on target genes, depending on the level of resolution required, and robustness of methods. To develop and validate web-based open-access typing-tools for enteroviruses and noroviruses. An automated web-based typing algorithm was developed, starting with BLAST analysis of the query sequence against a reference set of sequences from viruses in the family Picornaviridae or Caliciviridae. The second step is phylogenetic analysis of the query sequence and a sub-set of the reference sequences, to assign the enterovirus type or norovirus genotype and/or variant, with profile alignment, construction of phylogenetic trees and bootstrap validation. Typing is performed on VP1 sequences of Human enterovirus A to D, and ORF1 and ORF2 sequences of genogroup I and II noroviruses. For validation, we used the tools to automatically type sequences in the RIVM and CDC enterovirus databases and the FBVE norovirus database. Using the typing-tools, 785(99%) of 795 Enterovirus VP1 sequences, and 8154(98.5%) of 8342 norovirus sequences were typed in accordance with previously used methods. Subtyping into variants was achieved for 4439(78.4%) of 5838 NoV GII.4 sequences. The online typing-tools reliably assign genotypes for enteroviruses and noroviruses. The use of phylogenetic methods makes these tools robust to ongoing evolution. This should facilitate standardized genotyping and nomenclature in clinical and public health laboratories, thus supporting inter-laboratory comparisons. Copyright © 2011 Elsevier B.V. All rights reserved.

Alignment-free genome tree inference by learning group-specific distance metrics.

PubMed

Patil, Kaustubh R; McHardy, Alice C

2013-01-01

Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

Functional interrogation of non-coding DNA through CRISPR genome editing.

PubMed

Canver, Matthew C; Bauer, Daniel E; Orkin, Stuart H

2017-05-15

Methodologies to interrogate non-coding regions have lagged behind coding regions despite comprising the vast majority of the genome. However, the rapid evolution of clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing has provided a multitude of novel techniques for laboratory investigation including significant contributions to the toolbox for studying non-coding DNA. CRISPR-mediated loss-of-function strategies rely on direct disruption of the underlying sequence or repression of transcription without modifying the targeted DNA sequence. CRISPR-mediated gain-of-function approaches similarly benefit from methods to alter the targeted sequence through integration of customized sequence into the genome as well as methods to activate transcription. Here we review CRISPR-based loss- and gain-of-function techniques for the interrogation of non-coding DNA. Copyright © 2017 Elsevier Inc. All rights reserved.

Detecting and Analyzing Genetic Recombination Using RDP4.

PubMed

Martin, Darren P; Murrell, Ben; Khoosal, Arjun; Muhire, Brejnev

2017-01-01

Recombination between nucleotide sequences is a major process influencing the evolution of most species on Earth. The evolutionary value of recombination has been widely debated and so too has its influence on evolutionary analysis methods that assume nucleotide sequences replicate without recombining. When nucleic acids recombine, the evolution of the daughter or recombinant molecule cannot be accurately described by a single phylogeny. This simple fact can seriously undermine the accuracy of any phylogenetics-based analytical approach which assumes that the evolutionary history of a set of recombining sequences can be adequately described by a single phylogenetic tree. There are presently a large number of available methods and associated computer programs for analyzing and characterizing recombination in various classes of nucleotide sequence datasets. Here we examine the use of some of these methods to derive and test recombination hypotheses using multiple sequence alignments.

Multilocus sequence typing reveals a novel subspeciation of Lactobacillus delbrueckii.

PubMed

Tanigawa, Kana; Watanabe, Koichi

2011-03-01

Currently, the species Lactobacillus delbrueckii is divided into four subspecies, L. delbrueckii subsp. delbrueckii, L. delbrueckii subsp. bulgaricus, L. delbrueckii subsp. indicus and L. delbrueckii subsp. lactis. These classifications were based mainly on phenotypic identification methods and few studies have used genotypic identification methods. As a result, these subspecies have not yet been reliably delineated. In this study, the four subspecies of L. delbrueckii were discriminated by phenotype and by genotypic identification [amplified-fragment length polymorphism (AFLP) and multilocus sequence typing (MLST)] methods. The MLST method developed here was based on the analysis of seven housekeeping genes (fusA, gyrB, hsp60, ileS, pyrG, recA and recG). The MLST method had good discriminatory ability: the 41 strains of L. delbrueckii examined were divided into 34 sequence types, with 29 sequence types represented by only a single strain. The sequence types were divided into eight groups. These groups could be discriminated as representing different subspecies. The results of the AFLP and MLST analyses were consistent. The type strain of L. delbrueckii subsp. delbrueckii, YIT 0080(T), was clearly discriminated from the other strains currently classified as members of this subspecies, which were located close to strains of L. delbrueckii subsp. lactis. The MLST scheme developed in this study should be a useful tool for the identification of strains of L. delbrueckii to the subspecies level.

Face recognition based on matching of local features on 3D dynamic range sequences

NASA Astrophysics Data System (ADS)

Echeagaray-Patrón, B. A.; Kober, Vitaly

2016-09-01

3D face recognition has attracted attention in the last decade due to improvement of technology of 3D image acquisition and its wide range of applications such as access control, surveillance, human-computer interaction and biometric identification systems. Most research on 3D face recognition has focused on analysis of 3D still data. In this work, a new method for face recognition using dynamic 3D range sequences is proposed. Experimental results are presented and discussed using 3D sequences in the presence of pose variation. The performance of the proposed method is compared with that of conventional face recognition algorithms based on descriptors.

Ribosomal DNA intergenic spacer sequence in foxtail millet, Setaria italica (L.) P. Beauv. and its characterization and application to typing of foxtail millet landraces.

PubMed

Fukunaga, Kenji; Ichitani, Katsuyuki; Taura, Satoru; Sato, Muneharu; Kawase, Makoto

2005-02-01

We determined the sequence of ribosomal DNA (rDNA) intergenic spacer (IGS) of foxtail millet isolated in our previous study, and identified subrepeats in the polymorphic region. We also developed a PCR-based method for identifying rDNA types based on sequence information and assessed 153 accessions of foxtail millet. Results were congruent with our previous works. This study provides new findings regarding the geographical distribution of rDNA variants. This new method facilitates analyses of numerous foxtail millet accessions. It is helpful for typing of foxtail millet germplasms and elucidating the evolution of this millet.

Training set extension for SVM ensemble in P300-speller with familiar face paradigm.

PubMed

Li, Qi; Shi, Kaiyang; Gao, Ning; Li, Jian; Bai, Ou

2018-03-27

P300-spellers are brain-computer interface (BCI)-based character input systems. Support vector machine (SVM) ensembles are trained with large-scale training sets and used as classifiers in these systems. However, the required large-scale training data necessitate a prolonged collection time for each subject, which results in data collected toward the end of the period being contaminated by the subject's fatigue. This study aimed to develop a method for acquiring more training data based on a collected small training set. A new method was developed in which two corresponding training datasets in two sequences are superposed and averaged to extend the training set. The proposed method was tested offline on a P300-speller with the familiar face paradigm. The SVM ensemble with extended training set achieved 85% classification accuracy for the averaged results of four sequences, and 100% for 11 sequences in the P300-speller. In contrast, the conventional SVM ensemble with non-extended training set achieved only 65% accuracy for four sequences, and 92% for 11 sequences. The SVM ensemble with extended training set achieves higher classification accuracies than the conventional SVM ensemble, which verifies that the proposed method effectively improves the classification performance of BCI P300-spellers, thus enhancing their practicality.

A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems.

PubMed

Kheiri, Ahmed; Keedwell, Ed

2017-01-01

Operations research is a well-established field that uses computational systems to support decisions in business and public life. Good solutions to operations research problems can make a large difference to the efficient running of businesses and organisations and so the field often searches for new methods to improve these solutions. The high school timetabling problem is an example of an operations research problem and is a challenging task which requires assigning events and resources to time slots subject to a set of constraints. In this article, a new sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling problems. In this study, we present an easy-to-implement, easy-to-maintain, and effective sequence-based selection hyper-heuristic to solve high school timetabling problems using a benchmark of unified real-world instances collected from different countries. We show that with sequence-based methods, it is possible to discover new best known solutions for a number of the problems in the timetabling domain. Through this investigation, the usefulness of sequence-based selection hyper-heuristics has been demonstrated and the capability of these methods has been shown to exceed the state of the art.

G-CNV: A GPU-Based Tool for Preparing Data to Detect CNVs with Read-Depth Methods.

PubMed

Manconi, Andrea; Manca, Emanuele; Moscatelli, Marco; Gnocchi, Matteo; Orro, Alessandro; Armano, Giuliano; Milanesi, Luciano

2015-01-01

Copy number variations (CNVs) are the most prevalent types of structural variations (SVs) in the human genome and are involved in a wide range of common human diseases. Different computational methods have been devised to detect this type of SVs and to study how they are implicated in human diseases. Recently, computational methods based on high-throughput sequencing (HTS) are increasingly used. The majority of these methods focus on mapping short-read sequences generated from a donor against a reference genome to detect signatures distinctive of CNVs. In particular, read-depth based methods detect CNVs by analyzing genomic regions with significantly different read-depth from the other ones. The pipeline analysis of these methods consists of four main stages: (i) data preparation, (ii) data normalization, (iii) CNV regions identification, and (iv) copy number estimation. However, available tools do not support most of the operations required at the first two stages of this pipeline. Typically, they start the analysis by building the read-depth signal from pre-processed alignments. Therefore, third-party tools must be used to perform most of the preliminary operations required to build the read-depth signal. These data-intensive operations can be efficiently parallelized on graphics processing units (GPUs). In this article, we present G-CNV, a GPU-based tool devised to perform the common operations required at the first two stages of the analysis pipeline. G-CNV is able to filter low-quality read sequences, to mask low-quality nucleotides, to remove adapter sequences, to remove duplicated read sequences, to map the short-reads, to resolve multiple mapping ambiguities, to build the read-depth signal, and to normalize it. G-CNV can be efficiently used as a third-party tool able to prepare data for the subsequent read-depth signal generation and analysis. Moreover, it can also be integrated in CNV detection tools to generate read-depth signals.

Identification of Genomic Insertion and Flanking Sequence of G2-EPSPS and GAT Transgenes in Soybean Using Whole Genome Sequencing Method.

PubMed

Guo, Bingfu; Guo, Yong; Hong, Huilong; Qiu, Li-Juan

2016-01-01

Molecular characterization of sequence flanking exogenous fragment insertion is essential for safety assessment and labeling of genetically modified organism (GMO). In this study, the T-DNA insertion sites and flanking sequences were identified in two newly developed transgenic glyphosate-tolerant soybeans GE-J16 and ZH10-6 based on whole genome sequencing (WGS) method. More than 22.4 Gb sequence data (∼21 × coverage) for each line was generated on Illumina HiSeq 2500 platform. The junction reads mapped to boundaries of T-DNA and flanking sequences in these two events were identified by comparing all sequencing reads with soybean reference genome and sequence of transgenic vector. The putative insertion loci and flanking sequences were further confirmed by PCR amplification, Sanger sequencing, and co-segregation analysis. All these analyses supported that exogenous T-DNA fragments were integrated in positions of Chr19: 50543767-50543792 and Chr17: 7980527-7980541 in these two transgenic lines. Identification of genomic insertion sites of G2-EPSPS and GAT transgenes will facilitate the utilization of their glyphosate-tolerant traits in soybean breeding program. These results also demonstrated that WGS was a cost-effective and rapid method for identifying sites of T-DNA insertions and flanking sequences in soybean.

Gene and translation initiation site prediction in metagenomic sequences

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

Hyatt, Philip Douglas; LoCascio, Philip F; Hauser, Loren John

2012-01-01

Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translationmore » initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.« less

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

Population Based Assessment of MHC Class 1 Antigens Down Regulation as Marker in Increased Risk for Development and Progression of Breast Cancer From Benign Breast Lesions

DTIC Science & Technology

2006-01-01

isolated using a routine salting-out method (DNA E-Z Prepkit, Orchid Diagnostics Europe, St Katelijne Waver, Belgium). Sequence based typing In...electrophoresis using ethidiumbromide to show the single 2 KB band before sequencing. Next, sequencing reactions were performed separately for exons 2, 3...Multiplex reverse transcription-polymerase chain reaction for simultaneous screening of 29 translocations and chromosomal aberrations in acute

Gene sequence analyses and other DNA-based methods for yeast species recognition

USDA-ARS?s Scientific Manuscript database

DNA sequence analyses, as well as other DNA-based methodologies, have transformed the way in which yeasts are identified. The focus of this chapter will be on the resolution of species using various types of DNA comparisons. In other chapters in this book, Rozpedowska, Piškur and Wolfe discuss mul...

Teaching Research Methodology Using a Project-Based Three Course Sequence Critical Reflections on Practice

ERIC Educational Resources Information Center

Braguglia, Kay H.; Jackson, Kanata A.

2012-01-01

This article presents a reflective analysis of teaching research methodology through a three course sequence using a project-based approach. The authors reflect critically on their experiences in teaching research methods courses in an undergraduate business management program. The introduction of a range of specific techniques including student…

Homology and the optimization of DNA sequence data

NASA Technical Reports Server (NTRS)

Wheeler, W.

2001-01-01

Three methods of nucleotide character analysis are discussed. Their implications for molecular sequence homology and phylogenetic analysis are compared. The criterion of inter-data set congruence, both character based and topological, are applied to two data sets to elucidate and potentially discriminate among these parsimony-based ideas. c2001 The Willi Hennig Society.

Sequence similarity is more relevant than species specificity in probabilistic backtranslation.

PubMed

Ferro, Alfredo; Giugno, Rosalba; Pigola, Giuseppe; Pulvirenti, Alfredo; Di Pietro, Cinzia; Purrello, Michele; Ragusa, Marco

2007-02-21

Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species. This paper describes EasyBack, a new parameter-free, fully-automated software for backtranslation using Hidden Markov Models. EasyBack is not based on imitation of codon usage within the target species, but instead uses a sequence-similarity criterion. The model is trained with a set of proteins with known cDNA coding sequences, constructed from the input protein by querying the NCBI databases with BLAST. Unlike existing software, the proposed method allows the quality of prediction to be estimated. When tested on a group of proteins that show different degrees of sequence conservation, EasyBack outperforms other published methods in terms of precision. The prediction quality of a protein backtranslation methis markedly increased by replacing the criterion of most used codon in the same species with a Hidden Markov Model trained with a set of most similar sequences from all species. Moreover, the proposed method allows the quality of prediction to be estimated probabilistically.

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.

Efficient alignment-free DNA barcode analytics.

PubMed

Kuksa, Pavel; Pavlovic, Vladimir

2009-11-10

In this work we consider barcode DNA analysis problems and address them using alternative, alignment-free methods and representations which model sequences as collections of short sequence fragments (features). The methods use fixed-length representations (spectrum) for barcode sequences to measure similarities or dissimilarities between sequences coming from the same or different species. The spectrum-based representation not only allows for accurate and computationally efficient species classification, but also opens possibility for accurate clustering analysis of putative species barcodes and identification of critical within-barcode loci distinguishing barcodes of different sample groups. New alignment-free methods provide highly accurate and fast DNA barcode-based identification and classification of species with substantial improvements in accuracy and speed over state-of-the-art barcode analysis methods. We evaluate our methods on problems of species classification and identification using barcodes, important and relevant analytical tasks in many practical applications (adverse species movement monitoring, sampling surveys for unknown or pathogenic species identification, biodiversity assessment, etc.) On several benchmark barcode datasets, including ACG, Astraptes, Hesperiidae, Fish larvae, and Birds of North America, proposed alignment-free methods considerably improve prediction accuracy compared to prior results. We also observe significant running time improvements over the state-of-the-art methods. Our results show that newly developed alignment-free methods for DNA barcoding can efficiently and with high accuracy identify specimens by examining only few barcode features, resulting in increased scalability and interpretability of current computational approaches to barcoding.

Comparison and Evaluation of the Molecular Typing Methods for Toxigenic Vibrio cholerae in Southwest China.

PubMed

Liao, Feng; Mo, Zhishuo; Chen, Meiling; Pang, Bo; Fu, Xiaoqing; Xu, Wen; Jing, Huaiqi; Kan, Biao; Gu, Wenpeng

2018-01-01

Vibrio cholerae O1 strains taken from the repository of Yunnan province, southwest China, were abundant and special. We selected 70 typical toxigenic V. cholerae (69 O1 and one O139 serogroup strains) isolated from Yunnan province, performed the pulsed field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and MLST of virulence gene (V-MLST) methods, and evaluated the resolution abilities for typing methods. The ctxB subunit sequence analysis for all strains have shown that cholera between 1986 and 1995 was associated with mixed infections with El Tor and El Tor variants, while infections after 1996 were all caused by El Tor variant strains. Seventy V. cholerae obtained 50 PFGE patterns, with a high resolution. The strains could be divided into three groups with predominance of strains isolated during 1980s, 1990s, and 2000s, respectively, showing a good consistency with the epidemiological investigation. We also evaluated two MLST method for V. cholerae , one was used seven housekeeping genes ( adk , gyrB , metE , pntA , mdh , purM , and pyrC ), and all the isolates belonged to ST69; another was used nine housekeeping genes ( cat , chi , dnaE , gyrB , lap , pgm , recA , rstA , and gmd ). A total of seven sequence types (STs) were found by using this method for all the strains; among them, rstA gene had five alleles, recA and gmd have two alleles, and others had only one allele. The virulence gene sequence typing method ( ctxAB , tcpA , and toxR ) showed that 70 strains were divided into nine STs; among them, tcpA gene had six alleles, toxR had five alleles, while ctxAB was identical for all the strains. The latter two sequences based typing methods also had consistency with epidemiology of the strains. PFGE had a higher resolution ability compared with the sequence based typing method, and MLST used seven housekeeping genes showed the lower resolution power than nine housekeeping genes and virulence genes methods. These two sequence typing methods could distinguish some epidemiological special strains in local area.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

A branch-migration based fluorescent probe for straightforward, sensitive and specific discrimination of DNA mutations

PubMed Central

Xiao, Xianjin; Wu, Tongbo; Xu, Lei; Chen, Wei

2017-01-01

Abstract Genetic mutations are important biomarkers for cancer diagnostics and surveillance. Preferably, the methods for mutation detection should be straightforward, highly specific and sensitive to low-level mutations within various sequence contexts, fast and applicable at room-temperature. Though some of the currently available methods have shown very encouraging results, their discrimination efficiency is still very low. Herein, we demonstrate a branch-migration based fluorescent probe (BM probe) which is able to identify the presence of known or unknown single-base variations at abundances down to 0.3%-1% within 5 min, even in highly GC-rich sequence regions. The discrimination factors between the perfect-match target and single-base mismatched target are determined to be 89–311 by measurement of their respective branch-migration products via polymerase elongation reactions. The BM probe not only enabled sensitive detection of two types of EGFR-associated point mutations located in GC-rich regions, but also successfully identified the BRAF V600E mutation in the serum from a thyroid cancer patient which could not be detected by the conventional sequencing method. The new method would be an ideal choice for high-throughput in vitro diagnostics and precise clinical treatment. PMID:28201758

Mapping Base Modifications in DNA by Transverse-Current Sequencing

NASA Astrophysics Data System (ADS)

Alvarez, Jose R.; Skachkov, Dmitry; Massey, Steven E.; Kalitsov, Alan; Velev, Julian P.

2018-02-01

Sequencing DNA modifications and lesions, such as methylation of cytosine and oxidation of guanine, is even more important and challenging than sequencing the genome itself. The traditional methods for detecting DNA modifications are either insensitive to these modifications or require additional processing steps to identify a particular type of modification. Transverse-current sequencing in nanopores can potentially identify the canonical bases and base modifications in the same run. In this work, we demonstrate that the most common DNA epigenetic modifications and lesions can be detected with any predefined accuracy based on their tunneling current signature. Our results are based on simulations of the nanopore tunneling current through DNA molecules, calculated using nonequilibrium electron-transport methodology within an effective multiorbital model derived from first-principles calculations, followed by a base-calling algorithm accounting for neighbor current-current correlations. This methodology can be integrated with existing experimental techniques to improve base-calling fidelity.

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

Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies.

PubMed

Wu, Jiaxin; Li, Yanda; Jiang, Rui

2014-03-01

Exome sequencing has been widely used in detecting pathogenic nonsynonymous single nucleotide variants (SNVs) for human inherited diseases. However, traditional statistical genetics methods are ineffective in analyzing exome sequencing data, due to such facts as the large number of sequenced variants, the presence of non-negligible fraction of pathogenic rare variants or de novo mutations, and the limited size of affected and normal populations. Indeed, prevalent applications of exome sequencing have been appealing for an effective computational method for identifying causative nonsynonymous SNVs from a large number of sequenced variants. Here, we propose a bioinformatics approach called SPRING (Snv PRioritization via the INtegration of Genomic data) for identifying pathogenic nonsynonymous SNVs for a given query disease. Based on six functional effect scores calculated by existing methods (SIFT, PolyPhen2, LRT, MutationTaster, GERP and PhyloP) and five association scores derived from a variety of genomic data sources (gene ontology, protein-protein interactions, protein sequences, protein domain annotations and gene pathway annotations), SPRING calculates the statistical significance that an SNV is causative for a query disease and hence provides a means of prioritizing candidate SNVs. With a series of comprehensive validation experiments, we demonstrate that SPRING is valid for diseases whose genetic bases are either partly known or completely unknown and effective for diseases with a variety of inheritance styles. In applications of our method to real exome sequencing data sets, we show the capability of SPRING in detecting causative de novo mutations for autism, epileptic encephalopathies and intellectual disability. We further provide an online service, the standalone software and genome-wide predictions of causative SNVs for 5,080 diseases at http://bioinfo.au.tsinghua.edu.cn/spring.

Ultra-barcoding in cacao (Theobroma spp.; malvaceae) using whole chloroplast genomes and nuclear ribosomal DNA

USDA-ARS?s Scientific Manuscript database

High-throughput next-generation sequencing was used to scan the genome and generate reliable sequence of high copy number regions. Using this method, we examined whole plastid genomes as well as nearly 6000 bases of nuclear ribosomal DNA sequences for nine genotypes of Theobroma cacao and an indivi...

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

PubMed

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

2004-01-01

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

Array-based detection of genetic alterations associated with disease

DOEpatents

Pinkel, Daniel; Albertson, Donna G.; Gray, Joe W.

2017-09-05

The present invention relates to DNA sequences from regions of copy number change on chromosome 20. The sequences can be used in hybridization methods for the identification of chromosomal abnormalities associated with various diseases.

Array-based detection of genetic alterations associated with disease

DOEpatents

Pinkel, Daniel; Albertson, Donna G.; Gray, Joe W.

2007-09-11

The present invention relates to DNA sequences from regions of copy number change on chromosome 20. The sequences can be used in hybridization methods for the identification of chromosomal abnormalities associated with various diseases.

Amplicon Sequencing of the slpH Locus Permits Culture-Independent Strain Typing of Lactobacillus helveticus in Dairy Products

PubMed Central

Moser, Aline; Wüthrich, Daniel; Bruggmann, Rémy; Eugster-Meier, Elisabeth; Meile, Leo; Irmler, Stefan

2017-01-01

The advent of massive parallel sequencing technologies has opened up possibilities for the study of the bacterial diversity of ecosystems without the need for enrichment or single strain isolation. By exploiting 78 genome data-sets from Lactobacillus helveticus strains, we found that the slpH locus that encodes a putative surface layer protein displays sufficient genetic heterogeneity to be a suitable target for strain typing. Based on high-throughput slpH gene sequencing and the detection of single-base DNA sequence variations, we established a culture-independent method to assess the biodiversity of the L. helveticus strains present in fermented dairy food. When we applied the method to study the L. helveticus strain composition in 15 natural whey cultures (NWCs) that were collected at different Gruyère, a protected designation of origin (PDO) production facilities, we detected a total of 10 sequence types (STs). In addition, we monitored the development of a three-strain mix in raclette cheese for 17 weeks. PMID:28775722

Visual attention distracter insertion for improved EEG rapid serial visual presentation (RSVP) target stimuli detection

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Huber, David J.; Martin, Kevin

2017-05-01

This paper† describes a technique in which we improve upon the prior performance of the Rapid Serial Visual Presentation (RSVP) EEG paradigm for image classification though the insertion of visual attention distracters and overall sequence reordering based upon the expected ratio of rare to common "events" in the environment and operational context. Inserting distracter images maintains the ratio of common events to rare events at an ideal level, maximizing the rare event detection via P300 EEG response to the RSVP stimuli. The method has two steps: first, we compute the optimal number of distracters needed for an RSVP stimuli based on the desired sequence length and expected number of targets and insert the distracters into the RSVP sequence, and then we reorder the RSVP sequence to maximize P300 detection. We show that by reducing the ratio of target events to nontarget events using this method, we can allow RSVP sequences with more targets without sacrificing area under the ROC curve (azimuth).

Faster sequence homology searches by clustering subsequences.

PubMed

Suzuki, Shuji; Kakuta, Masanori; Ishida, Takashi; Akiyama, Yutaka

2015-04-15

Sequence homology searches are used in various fields. New sequencing technologies produce huge amounts of sequence data, which continuously increase the size of sequence databases. As a result, homology searches require large amounts of computational time, especially for metagenomic analysis. We developed a fast homology search method based on database subsequence clustering, and implemented it as GHOSTZ. This method clusters similar subsequences from a database to perform an efficient seed search and ungapped extension by reducing alignment candidates based on triangle inequality. The database subsequence clustering technique achieved an ∼2-fold increase in speed without a large decrease in search sensitivity. When we measured with metagenomic data, GHOSTZ is ∼2.2-2.8 times faster than RAPSearch and is ∼185-261 times faster than BLASTX. The source code is freely available for download at http://www.bi.cs.titech.ac.jp/ghostz/ akiyama@cs.titech.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

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).

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

PubMed

Kuhn, Alexandre; Ong, Yao Min; Quake, Stephen R; Burkholder, William F

2015-07-08

Like other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed. We describe a high-throughput method for genotyping transposable element insertions and other types of structural variants that can be assayed by breakpoint PCR. The method relies on next-generation sequencing of multiplex, site-specific PCR amplification products and read count-based genotype calls. We show that this method is flexible, efficient (it does not require rounds of optimization), cost-effective and highly accurate. This method can benefit a wide range of applications from the routine genotyping of animal and plant populations to the functional study of structural variants in humans.

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences.

PubMed

Bonizzoni, Paola; Rizzi, Raffaella; Pesole, Graziano

2005-10-05

Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems--hence the need to develop novel strategies. We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at http://aspic.algo.disco.unimib.it/aspic-devel/.

3D knee segmentation based on three MRI sequences from different planes.

PubMed

Zhou, L; Chav, R; Cresson, T; Chartrand, G; de Guise, J

2016-08-01

In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

Multicenter validation of cancer gene panel-based next-generation sequencing for translational research and molecular diagnostics.

PubMed

Hirsch, B; Endris, V; Lassmann, S; Weichert, W; Pfarr, N; Schirmacher, P; Kovaleva, V; Werner, M; Bonzheim, I; Fend, F; Sperveslage, J; Kaulich, K; Zacher, A; Reifenberger, G; Köhrer, K; Stepanow, S; Lerke, S; Mayr, T; Aust, D E; Baretton, G; Weidner, S; Jung, A; Kirchner, T; Hansmann, M L; Burbat, L; von der Wall, E; Dietel, M; Hummel, M

2018-04-01

The simultaneous detection of multiple somatic mutations in the context of molecular diagnostics of cancer is frequently performed by means of amplicon-based targeted next-generation sequencing (NGS). However, only few studies are available comparing multicenter testing of different NGS platforms and gene panels. Therefore, seven partner sites of the German Cancer Consortium (DKTK) performed a multicenter interlaboratory trial for targeted NGS using the same formalin-fixed, paraffin-embedded (FFPE) specimen of molecularly pre-characterized tumors (n = 15; each n = 5 cases of Breast, Lung, and Colon carcinoma) and a colorectal cancer cell line DNA dilution series. Detailed information regarding pre-characterized mutations was not disclosed to the partners. Commercially available and custom-designed cancer gene panels were used for library preparation and subsequent sequencing on several devices of two NGS different platforms. For every case, centrally extracted DNA and FFPE tissue sections for local processing were delivered to each partner site to be sequenced with the commercial gene panel and local bioinformatics. For cancer-specific panel-based sequencing, only centrally extracted DNA was analyzed at seven sequencing sites. Subsequently, local data were compiled and bioinformatics was performed centrally. We were able to demonstrate that all pre-characterized mutations were re-identified correctly, irrespective of NGS platform or gene panel used. However, locally processed FFPE tissue sections disclosed that the DNA extraction method can affect the detection of mutations with a trend in favor of magnetic bead-based DNA extraction methods. In conclusion, targeted NGS is a very robust method for simultaneous detection of various mutations in FFPE tissue specimens if certain pre-analytical conditions are carefully considered.

Evaluation of an automated repetitive sequence-based PCR system for subtyping Enterobacter sakazakii.

PubMed

Healy, B; Mullane, N; Collin, V; Mailler, S; Iversen, C; Chatellier, S; Storrs, M; Fanning, S

2008-07-01

Enterobacter sakazakii is regarded as a ubiquitous organism that can be isolated from a wide range of foods and environments. Infection in at-risk infants has been epidemiologically linked to the consumption of contaminated powdered infant formula. Preventing the dissemination of this pathogen in a powdered infant formula manufacturing facility is an important step in ensuring consumer confidence in a given brand together with the protection of the health status of a vulnerable population. In this study we report the application of a repetitive sequence-based PCR typing method to subtype a previously well-characterized collection of E. sakazakii isolates of diverse origin. While both methods successfully discriminated between the collection of isolates, repetitive sequence-based PCR identified 65 types, whereas pulsed-field gel electrophoresis identified 110 types showing > or =95% similarity. The method was quick and easy to perform, and our data demonstrated the utility and value of this approach to monitor in-process contamination, which could potentially contribute to a reduction in the transmission of E. sakazakii.

Methods of DNA sequencing by hybridization based on optimizing concentration of matrix-bound oligonucleotide and device for carrying out same

DOEpatents

Khrapko, Konstantin R [Moscow, RU; Khorlin, Alexandr A [Moscow, RU; Ivanov, Igor B [Moskovskaya, RU; Ershov, Gennady M [Moscow, RU; Lysov, Jury P [Moscow, RU; Florentiev, Vladimir L [Moscow, RU; Mirzabekov, Andrei D [Moscow, RU

1996-09-03

A method for sequencing DNA by hybridization that includes the following steps: forming an array of oligonucleotides at such concentrations that either ensure the same dissociation temperature for all fully complementary duplexes or allows hybridization and washing of such duplexes to be conducted at the same temperature; hybridizing said oligonucleotide array with labeled test DNA; washing in duplex dissociation conditions; identifying single-base substitutions in the test DNA by analyzing the distribution of the dissociation temperatures and reconstructing the DNA nucleotide sequence based on the above analysis. A device for carrying out the method comprises a solid substrate and a matrix rigidly bound to the substrate. The matrix contains the oligonucleotide array and consists of a multiplicity of gel portions. Each gel portion contains one oligonucleotide of desired length. The gel portions are separated from one another by interstices and have a thickness not exceeding 30 .mu.m.

Comparison of next generation sequencing technologies for transcriptome characterization

PubMed Central

2009-01-01

Background We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis. Results The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. Conclusion NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms. PMID:19646272

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

Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing

PubMed Central

Hykin, Sarah M.; Bi, Ke; McGuire, Jimmy A.

2015-01-01

For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles), attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens—particularly for use in phylogenetic analyses—has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp). We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens available for genetic analysis. PMID:26505622

Fixing Formalin: A Method to Recover Genomic-Scale DNA Sequence Data from Formalin-Fixed Museum Specimens Using High-Throughput Sequencing.

PubMed

Hykin, Sarah M; Bi, Ke; McGuire, Jimmy A

2015-01-01

For 150 years or more, specimens were routinely collected and deposited in natural history collections without preserving fresh tissue samples for genetic analysis. In the case of most herpetological specimens (i.e. amphibians and reptiles), attempts to extract and sequence DNA from formalin-fixed, ethanol-preserved specimens-particularly for use in phylogenetic analyses-has been laborious and largely ineffective due to the highly fragmented nature of the DNA. As a result, tens of thousands of specimens in herpetological collections have not been available for sequence-based phylogenetic studies. Massively parallel High-Throughput Sequencing methods and the associated bioinformatics, however, are particularly suited to recovering meaningful genetic markers from severely degraded/fragmented DNA sequences such as DNA damaged by formalin-fixation. In this study, we compared previously published DNA extraction methods on three tissue types subsampled from formalin-fixed specimens of Anolis carolinensis, followed by sequencing. Sufficient quality DNA was recovered from liver tissue, making this technique minimally destructive to museum specimens. Sequencing was only successful for the more recently collected specimen (collected ~30 ybp). We suspect this could be due either to the conditions of preservation and/or the amount of tissue used for extraction purposes. For the successfully sequenced sample, we found a high rate of base misincorporation. After rigorous trimming, we successfully mapped 27.93% of the cleaned reads to the reference genome, were able to reconstruct the complete mitochondrial genome, and recovered an accurate phylogenetic placement for our specimen. We conclude that the amount of DNA available, which can vary depending on specimen age and preservation conditions, will determine if sequencing will be successful. The technique described here will greatly improve the value of museum collections by making many formalin-fixed specimens available for genetic analysis.

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

PubMed

Zhang, Zhongyang; Hao, Ke

2015-11-01

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data

PubMed Central

Zhang, Zhongyang; Hao, Ke

2015-01-01

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity. PMID:26583378

Targeted gene enrichment and high-throughput sequencing for environmental biomonitoring: a case study using freshwater macroinvertebrates.

PubMed

Dowle, Eddy J; Pochon, Xavier; C Banks, Jonathan; Shearer, Karen; Wood, Susanna A

2016-09-01

Recent studies have advocated biomonitoring using DNA techniques. In this study, two high-throughput sequencing (HTS)-based methods were evaluated: amplicon metabarcoding of the cytochrome C oxidase subunit I (COI) mitochondrial gene and gene enrichment using MYbaits (targeting nine different genes including COI). The gene-enrichment method does not require PCR amplification and thus avoids biases associated with universal primers. Macroinvertebrate samples were collected from 12 New Zealand rivers. Macroinvertebrates were morphologically identified and enumerated, and their biomass determined. DNA was extracted from all macroinvertebrate samples and HTS undertaken using the illumina miseq platform. Macroinvertebrate communities were characterized from sequence data using either six genes (three of the original nine were not used) or just the COI gene in isolation. The gene-enrichment method (all genes) detected the highest number of taxa and obtained the strongest Spearman rank correlations between the number of sequence reads, abundance and biomass in 67% of the samples. Median detection rates across rare (<1% of the total abundance or biomass), moderately abundant (1-5%) and highly abundant (>5%) taxa were highest using the gene-enrichment method (all genes). Our data indicated primer biases occurred during amplicon metabarcoding with greater than 80% of sequence reads originating from one taxon in several samples. The accuracy and sensitivity of both HTS methods would be improved with more comprehensive reference sequence databases. The data from this study illustrate the challenges of using PCR amplification-based methods for biomonitoring and highlight the potential benefits of using approaches, such as gene enrichment, which circumvent the need for an initial PCR step. © 2015 John Wiley & Sons Ltd.

A mass spectrometry-based multiplex SNP genotyping by utilizing allele-specific ligation and strand displacement amplification.

PubMed

Park, Jung Hun; Jang, Hyowon; Jung, Yun Kyung; Jung, Ye Lim; Shin, Inkyung; Cho, Dae-Yeon; Park, Hyun Gyu

2017-05-15

We herein describe a new mass spectrometry-based method for multiplex SNP genotyping by utilizing allele-specific ligation and strand displacement amplification (SDA) reaction. In this method, allele-specific ligation is first performed to discriminate base sequence variations at the SNP site within the PCR-amplified target DNA. The primary ligation probe is extended by a universal primer annealing site while the secondary ligation probe has base sequences as an overhang with a nicking enzyme recognition site and complementary mass marker sequence. The ligation probe pairs are ligated by DNA ligase only at specific allele in the target DNA and the resulting ligated product serves as a template to promote the SDA reaction using a universal primer. This process isothermally amplifies short DNA fragments, called mass markers, to be analyzed by mass spectrometry. By varying the sizes of the mass markers, we successfully demonstrated the multiplex SNP genotyping capability of this method by reliably identifying several BRCA mutations in a multiplex manner with mass spectrometry. Copyright © 2016 Elsevier B.V. All rights reserved.

A family-based probabilistic method for capturing de novo mutations from high-throughput short-read sequencing data.

PubMed

Cartwright, Reed A; Hussin, Julie; Keebler, Jonathan E M; Stone, Eric A; Awadalla, Philip

2012-01-06

Recent advances in high-throughput DNA sequencing technologies and associated statistical analyses have enabled in-depth analysis of whole-genome sequences. As this technology is applied to a growing number of individual human genomes, entire families are now being sequenced. Information contained within the pedigree of a sequenced family can be leveraged when inferring the donors' genotypes. The presence of a de novo mutation within the pedigree is indicated by a violation of Mendelian inheritance laws. Here, we present a method for probabilistically inferring genotypes across a pedigree using high-throughput sequencing data and producing the posterior probability of de novo mutation at each genomic site examined. This framework can be used to disentangle the effects of germline and somatic mutational processes and to simultaneously estimate the effect of sequencing error and the initial genetic variation in the population from which the founders of the pedigree arise. This approach is examined in detail through simulations and areas for method improvement are noted. By applying this method to data from members of a well-defined nuclear family with accurate pedigree information, the stage is set to make the most direct estimates of the human mutation rate to date.

Kidney segmentation in CT sequences using graph cuts based active contours model and contextual continuity.

PubMed

Zhang, Pin; Liang, Yanmei; Chang, Shengjiang; Fan, Hailun

2013-08-01

Accurate segmentation of renal tissues in abdominal computed tomography (CT) image sequences is an indispensable step for computer-aided diagnosis and pathology detection in clinical applications. In this study, the goal is to develop a radiology tool to extract renal tissues in CT sequences for the management of renal diagnosis and treatments. In this paper, the authors propose a new graph-cuts-based active contours model with an adaptive width of narrow band for kidney extraction in CT image sequences. Based on graph cuts and contextual continuity, the segmentation is carried out slice-by-slice. In the first stage, the middle two adjacent slices in a CT sequence are segmented interactively based on the graph cuts approach. Subsequently, the deformable contour evolves toward the renal boundaries by the proposed model for the kidney extraction of the remaining slices. In this model, the energy function combining boundary with regional information is optimized in the constructed graph and the adaptive search range is determined by contextual continuity and the object size. In addition, in order to reduce the complexity of the min-cut computation, the nodes in the graph only have n-links for fewer edges. The total 30 CT images sequences with normal and pathological renal tissues are used to evaluate the accuracy and effectiveness of our method. The experimental results reveal that the average dice similarity coefficient of these image sequences is from 92.37% to 95.71% and the corresponding standard deviation for each dataset is from 2.18% to 3.87%. In addition, the average automatic segmentation time for one kidney in each slice is about 0.36 s. Integrating the graph-cuts-based active contours model with contextual continuity, the algorithm takes advantages of energy minimization and the characteristics of image sequences. The proposed method achieves effective results for kidney segmentation in CT sequences.

ECHO: A reference-free short-read error correction algorithm

PubMed Central

Kao, Wei-Chun; Chan, Andrew H.; Song, Yun S.

2011-01-01

Developing accurate, scalable algorithms to improve data quality is an important computational challenge associated with recent advances in high-throughput sequencing technology. In this study, a novel error-correction algorithm, called ECHO, is introduced for correcting base-call errors in short-reads, without the need of a reference genome. Unlike most previous methods, ECHO does not require the user to specify parameters of which optimal values are typically unknown a priori. ECHO automatically sets the parameters in the assumed model and estimates error characteristics specific to each sequencing run, while maintaining a running time that is within the range of practical use. ECHO is based on a probabilistic model and is able to assign a quality score to each corrected base. Furthermore, it explicitly models heterozygosity in diploid genomes and provides a reference-free method for detecting bases that originated from heterozygous sites. On both real and simulated data, ECHO is able to improve the accuracy of previous error-correction methods by several folds to an order of magnitude, depending on the sequence coverage depth and the position in the read. The improvement is most pronounced toward the end of the read, where previous methods become noticeably less effective. Using a whole-genome yeast data set, it is demonstrated here that ECHO is capable of coping with nonuniform coverage. Also, it is shown that using ECHO to perform error correction as a preprocessing step considerably facilitates de novo assembly, particularly in the case of low-to-moderate sequence coverage depth. PMID:21482625

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

PubMed

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

2007-10-01

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

GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data.

PubMed

Chen, Li; Reeve, James; Zhang, Lujun; Huang, Shengbing; Wang, Xuefeng; Chen, Jun

2018-01-01

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero-inflation remain largely undeveloped. Here we propose geometric mean of pairwise ratios-a simple but effective normalization method-for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

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.

Comparison of Three Different Hepatitis C Virus Genotyping Methods: 5'NCR PCR-RFLP, Core Type-Specific PCR, and NS5b Sequencing in a Tertiary Care Hospital in South India.

PubMed

Daniel, Hubert D-J; David, Joel; Raghuraman, Sukanya; Gnanamony, Manu; Chandy, George M; Sridharan, Gopalan; Abraham, Priya

2017-05-01

Based on genetic heterogeneity, hepatitis C virus (HCV) is classified into seven major genotypes and 64 subtypes. In spite of the sequence heterogeneity, all genotypes share an identical complement of colinear genes within the large open reading frame. The genetic interrelationships between these genes are consistent among genotypes. Due to this property, complete sequencing of the HCV genome is not required. HCV genotypes along with subtypes are critical for planning antiviral therapy. Certain genotypes are also associated with higher progression to liver cirrhosis. In this study, 100 blood samples were collected from individuals who came for routine HCV genotype identification. These samples were used for the comparison of two different genotyping methods (5'NCR PCR-RFLP and HCV core type-specific PCR) with NS5b sequencing. Of the 100 samples genotyped using 5'NCR PCR-RFLP and HCV core type-specific PCR, 90% (κ = 0.913, P < 0.00) and 96% (κ = 0.794, P < 0.00) correlated with NS5b sequencing, respectively. Sixty percent and 75% of discordant samples by 5'NCR PCR-RFLP and HCV core type-specific PCR, respectively, belonged to genotype 6. All the HCV genotype 1 subtypes were classified accurately by both the methods. This study shows that the 5'NCR-based PCR-RFLP and the HCV core type-specific PCR-based assays correctly identified HCV genotypes except genotype 6 from this region. Direct sequencing of the HCV core region was able to identify all the genotype 6 from this region and serves as an alternative to NS5b sequencing. © 2016 Wiley Periodicals, Inc.

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

PubMed

You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only <1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multilabel classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-called difficult proteins, which have <60% sequence identity to proteins with annotations already. Thus the vital and challenging problem now is how to develop a method for SAFP, particularly for difficult proteins. The key of this method is to extract not only homology information but also diverse, deep- rooted information/evidence from sequence inputs and integrate them into a predictor in a both effective and efficient manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a paradigm of machine learning, especially powerful for multilabel classification. The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

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

PubMed

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

2014-12-01

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

A simple, rapid, high-fidelity and cost-effective PCR-based two-step DNA synthesis method for long gene sequences.

PubMed

Xiong, Ai-Sheng; Yao, Quan-Hong; Peng, Ri-He; Li, Xian; Fan, Hui-Qin; Cheng, Zong-Ming; Li, Yi

2004-07-07

Chemical synthesis of DNA sequences provides a powerful tool for modifying genes and for studying gene function, structure and expression. Here, we report a simple, high-fidelity and cost-effective PCR-based two-step DNA synthesis (PTDS) method for synthesis of long segments of DNA. The method involves two steps. (i) Synthesis of individual fragments of the DNA of interest: ten to twelve 60mer oligonucleotides with 20 bp overlap are mixed and a PCR reaction is carried out with high-fidelity DNA polymerase Pfu to produce DNA fragments that are approximately 500 bp in length. (ii) Synthesis of the entire sequence of the DNA of interest: five to ten PCR products from the first step are combined and used as the template for a second PCR reaction using high-fidelity DNA polymerase pyrobest, with the two outermost oligonucleotides as primers. Compared with the previously published methods, the PTDS method is rapid (5-7 days) and suitable for synthesizing long segments of DNA (5-6 kb) with high G + C contents, repetitive sequences or complex secondary structures. Thus, the PTDS method provides an alternative tool for synthesizing and assembling long genes with complex structures. Using the newly developed PTDS method, we have successfully obtained several genes of interest with sizes ranging from 1.0 to 5.4 kb.

A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data.

PubMed

Park, Doori; Park, Su-Hyun; Ban, Yong Wook; Kim, Youn Shic; Park, Kyoung-Cheul; Kim, Nam-Soo; Kim, Ju-Kon; Choi, Ik-Young

2017-08-15

Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms. To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment. Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9-5, SNU-Bt9-30, and SNU-Bt9-109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses. NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.

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

PubMed

Kim, Kyung In; Simon, Richard

2014-01-24

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

Recombination of polynucleotide sequences using random or defined primers

DOEpatents

Arnold, Frances H.; Shao, Zhixin; Affholter, Joseph A.; Zhao, Huimin H; Giver, Lorraine J.

2000-01-01

A method for in vitro mutagenesis and recombination of polynucleotide sequences based on polymerase-catalyzed extension of primer oligonucleotides is disclosed. The method involves priming template polynucleotide(s) with random-sequences or defined-sequence primers to generate a pool of short DNA fragments with a low level of point mutations. The DNA fragments are subjected to denaturization followed by annealing and further enzyme-catalyzed DNA polymerization. This procedure is repeated a sufficient number of times to produce full-length genes which comprise mutants of the original template polynucleotides. These genes can be further amplified by the polymerase chain reaction and cloned into a vector for expression of the encoded proteins.

Recombination of polynucleotide sequences using random or defined primers

DOEpatents

Arnold, Frances H.; Shao, Zhixin; Affholter, Joseph A.; Zhao, Huimin; Giver, Lorraine J.

2001-01-01

A method for in vitro mutagenesis and recombination of polynucleotide sequences based on polymerase-catalyzed extension of primer oligonucleotides is disclosed. The method involves priming template polynucleotide(s) with random-sequences or defined-sequence primers to generate a pool of short DNA fragments with a low level of point mutations. The DNA fragments are subjected to denaturization followed by annealing and further enzyme-catalyzed DNA polymerization. This procedure is repeated a sufficient number of times to produce full-length genes which comprise mutants of the original template polynucleotides. These genes can be further amplified by the polymerase chain reaction and cloned into a vector for expression of the encoded proteins.

Phylogenetic position of parabasalid symbionts from the termite Calotermes flavicollis based on small subunit rRNA sequences.

PubMed

Gerbod, D; Edgcomb, V P; Noël, C; Delgado-Viscogliosi, P; Viscogliosi, E

2000-09-01

Small subunit rDNA genes were amplified by polymerase chain reaction using specific primers from mixed-population DNA obtained from the whole hindgut of the termite Calotermes flavicollis. Comparative sequence analysis of the clones revealed two kinds of sequences that were both from parabasalid symbionts. In a molecular tree inferred by distance, parsimony and likelihood methods, and including 27 parabasalid sequences retrieved from the data bases, the sequences of the group II (clones Cf5 and Cf6) were closely related to the Devescovinidae/Calonymphidae species and thus were assigned to the Devescovinidae Foaina. The sequence of the group I (clone Cf1) emerged within the Trichomonadinae and strongly clustered with Tetratrichomonas gallinarum. On the basis of morphological data, the Monocercomonadidae Hexamastix termitis might be the most likely origin of this sequence.

The Impact of Different Instructions on Vietnamese EFL Students' Acquisition of Formulaic Sequences

ERIC Educational Resources Information Center

Ha, Do Thi

2017-01-01

The paper explores how various teaching methods, namely Phonology-Based Instruction (PBI) and Translation-Based Instruction (TBI), have an effect on students' acquisition of formulaic sequences. 20 multiword expressions were taught to 48 Vietnamese EFL students from three intact classes as 2 treatment groups (PBI and TBI) and 1 control group.…

Genetic diversity assessment of anoxygenic photosynthetic bacteria by distance-based grouping analysis of pufM sequences.

PubMed

Zeng, Y H; Chen, X H; Jiao, N Z

2007-12-01

To assess how completely the diversity of anoxygenic phototrophic bacteria (APB) was sampled in natural environments. All nucleotide sequences of the APB marker gene pufM from cultures and environmental clones were retrieved from the GenBank database. A set of cutoff values (sequence distances 0.06, 0.15 and 0.48 for species, genus, and (sub)phylum levels, respectively) was established using a distance-based grouping program. Analysis of the environmental clones revealed that current efforts on APB isolation and sampling in natural environments are largely inadequate. Analysis of the average distance between each identified genus and an uncultured environmental pufM sequence indicated that the majority of cultured APB genera lack environmental representatives. The distance-based grouping method is fast and efficient for bulk functional gene sequences analysis. The results clearly show that we are at a relatively early stage in sampling the global richness of APB species. Periodical assessment will undoubtedly facilitate in-depth analysis of potential biogeographical distribution pattern of APB. This is the first attempt to assess the present understanding of APB diversity in natural environments. The method used is also useful for assessing the diversity of other functional genes.

Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database

PubMed Central

2017-01-01

Image encryption technology is one of the main means to ensure the safety of image information. Using the characteristics of chaos, such as randomness, regularity, ergodicity, and initial value sensitiveness, combined with the unique space conformation of DNA molecules and their unique information storage and processing ability, an efficient method for image encryption based on the chaos theory and a DNA sequence database is proposed. In this paper, digital image encryption employs a process of transforming the image pixel gray value by using chaotic sequence scrambling image pixel location and establishing superchaotic mapping, which maps quaternary sequences and DNA sequences, and by combining with the logic of the transformation between DNA sequences. The bases are replaced under the displaced rules by using DNA coding in a certain number of iterations that are based on the enhanced quaternary hyperchaotic sequence; the sequence is generated by Chen chaos. The cipher feedback mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion properties of the algorithm. Theoretical analysis and experimental results show that the proposed scheme not only demonstrates excellent encryption but also effectively resists chosen-plaintext attack, statistical attack, and differential attack. PMID:28392799

Wireless autonomous device data transmission

NASA Technical Reports Server (NTRS)

Sammel, Jr., David W. (Inventor); Mickle, Marlin H. (Inventor); Cain, James T. (Inventor); Mi, Minhong (Inventor)

2013-01-01

A method of communicating information from a wireless autonomous device (WAD) to a base station. The WAD has a data element having a predetermined profile having a total number of sequenced possible data element combinations. The method includes receiving at the WAD an RF profile transmitted by the base station that includes a triggering portion having a number of pulses, wherein the number is at least equal to the total number of possible data element combinations. The method further includes keeping a count of received pulses and wirelessly transmitting a piece of data, preferably one bit, to the base station when the count reaches a value equal to the stored data element's particular number in the sequence. Finally, the method includes receiving the piece of data at the base station and using the receipt thereof to determine which of the possible data element combinations the stored data element is.

Identification of Medically Important Yeasts Using PCR-Based Detection of DNA Sequence Polymorphisms in the Internal Transcribed Spacer 2 Region of the rRNA Genes

PubMed Central

Chen, Y. C.; Eisner, J. D.; Kattar, M. M.; Rassoulian-Barrett, S. L.; LaFe, K.; Yarfitz, S. L.; Limaye, A. P.; Cookson, B. T.

2000-01-01

Identification of medically relevant yeasts can be time-consuming and inaccurate with current methods. We evaluated PCR-based detection of sequence polymorphisms in the internal transcribed spacer 2 (ITS2) region of the rRNA genes as a means of fungal identification. Clinical isolates (401), reference strains (6), and type strains (27), representing 34 species of yeasts were examined. The length of PCR-amplified ITS2 region DNA was determined with single-base precision in less than 30 min by using automated capillary electrophoresis. Unique, species-specific PCR products ranging from 237 to 429 bp were obtained from 92% of the clinical isolates. The remaining 8%, divided into groups with ITS2 regions which differed by ≤2 bp in mean length, all contained species-specific DNA sequences easily distinguishable by restriction enzyme analysis. These data, and the specificity of length polymorphisms for identifying yeasts, were confirmed by DNA sequence analysis of the ITS2 region from 93 isolates. Phenotypic and ITS2-based identification was concordant for 427 of 434 yeast isolates examined using sequence identity of ≥99%. Seven clinical isolates contained ITS2 sequences that did not agree with their phenotypic identification, and ITS2-based phylogenetic analyses indicate the possibility of new or clinically unusual species in the Rhodotorula and Candida genera. This work establishes an initial database, validated with over 400 clinical isolates, of ITS2 length and sequence polymorphisms for 34 species of yeasts. We conclude that size and restriction analysis of PCR-amplified ITS2 region DNA is a rapid and reliable method to identify clinically significant yeasts, including potentially new or emerging pathogenic species. PMID:10834993

Winnowing DNA for rare sequences: highly specific sequence and methylation based enrichment.

PubMed

Thompson, Jason D; Shibahara, Gosuke; Rajan, Sweta; Pel, Joel; Marziali, Andre

2012-01-01

Rare mutations in cell populations are known to be hallmarks of many diseases and cancers. Similarly, differential DNA methylation patterns arise in rare cell populations with diagnostic potential such as fetal cells circulating in maternal blood. Unfortunately, the frequency of alleles with diagnostic potential, relative to wild-type background sequence, is often well below the frequency of errors in currently available methods for sequence analysis, including very high throughput DNA sequencing. We demonstrate a DNA preparation and purification method that through non-linear electrophoretic separation in media containing oligonucleotide probes, achieves 10,000 fold enrichment of target DNA with single nucleotide specificity, and 100 fold enrichment of unmodified methylated DNA differing from the background by the methylation of a single cytosine residue.

Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

PubMed

Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

2017-05-01

Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

Evolution of EF-hand calcium-modulated proteins. IV. Exon shuffling did not determine the domain compositions of EF-hand proteins

NASA Technical Reports Server (NTRS)

Kretsinger, R. H.; Nakayama, S.

1993-01-01

In the previous three reports in this series we demonstrated that the EF-hand family of proteins evolved by a complex pattern of gene duplication, transposition, and splicing. The dendrograms based on exon sequences are nearly identical to those based on protein sequences for troponin C, the essential light chain myosin, the regulatory light chain, and calpain. This validates both the computational methods and the dendrograms for these subfamilies. The proposal of congruence for calmodulin, troponin C, essential light chain, and regulatory light chain was confirmed. There are, however, significant differences in the calmodulin dendrograms computed from DNA and from protein sequences. In this study we find that introns are distributed throughout the EF-hand domain and the interdomain regions. Further, dendrograms based on intron type and distribution bear little resemblance to those based on protein or on DNA sequences. We conclude that introns are inserted, and probably deleted, with relatively high frequency. Further, in the EF-hand family exons do not correspond to structural domains and exon shuffling played little if any role in the evolution of this widely distributed homolog family. Calmodulin has had a turbulent evolution. Its dendrograms based on protein sequence, exon sequence, 3'-tail sequence, intron sequences, and intron positions all show significant differences.

Genome sequencing in microfabricated high-density picolitre reactors.

PubMed

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

2005-09-15

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

Motion magnification using the Hermite transform

NASA Astrophysics Data System (ADS)

Brieva, Jorge; Moya-Albor, Ernesto; Gomez-Coronel, Sandra L.; Escalante-Ramírez, Boris; Ponce, Hiram; Mora Esquivel, Juan I.

2015-12-01

We present an Eulerian motion magnification technique with a spatial decomposition based on the Hermite Transform (HT). We compare our results to the approach presented in.1 We test our method in one sequence of the breathing of a newborn baby and on an MRI left ventricle sequence. Methods are compared using quantitative and qualitative metrics after the application of the motion magnification algorithm.

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

PubMed Central

Steele, Joe; Bastola, Dhundy

2014-01-01

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

Collaborative Filtering Recommendation on Users' Interest Sequences.

PubMed

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS) that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS) and the count of users' total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

Collaborative Filtering Recommendation on Users’ Interest Sequences

PubMed Central

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users’ dynamic preferences in many papers. However, the sequence of users’ behaviour is rarely studied in recommender systems. Due to the users’ unique behavior evolution patterns and personalized interest transitions among items, users’ similarity in sequential dimension should be introduced to further distinguish users’ preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users’ interest sequences (IS) that rank users’ ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users’ longest common sub-IS (LCSIS) and the count of users’ total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users’ IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users’ preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction. PMID:27195787

Method for sequencing nucleic acid molecules

DOEpatents

Korlach, Jonas; Webb, Watt W.; Levene, Michael; Turner, Stephen; Craighead, Harold G.; Foquet, Mathieu

2006-06-06

The present invention is directed to a method of sequencing a target nucleic acid molecule having a plurality of bases. In its principle, the temporal order of base additions during the polymerization reaction is measured on a molecule of nucleic acid, i.e. the activity of a nucleic acid polymerizing enzyme on the template nucleic acid molecule to be sequenced is followed in real time. The sequence is deduced by identifying which base is being incorporated into the growing complementary strand of the target nucleic acid by the catalytic activity of the nucleic acid polymerizing enzyme at each step in the sequence of base additions. A polymerase on the target nucleic acid molecule complex is provided in a position suitable to move along the target nucleic acid molecule and extend the oligonucleotide primer at an active site. A plurality of labelled types of nucleotide analogs are provided proximate to the active site, with each distinguishable type of nucleotide analog being complementary to a different nucleotide in the target nucleic acid sequence. The growing nucleic acid strand is extended by using the polymerase to add a nucleotide analog to the nucleic acid strand at the active site, where the nucleotide analog being added is complementary to the nucleotide of the target nucleic acid at the active site. The nucleotide analog added to the oligonucleotide primer as a result of the polymerizing step is identified. The steps of providing labelled nucleotide analogs, polymerizing the growing nucleic acid strand, and identifying the added nucleotide analog are repeated so that the nucleic acid strand is further extended and the sequence of the target nucleic acid is determined.

Method for sequencing nucleic acid molecules

DOEpatents

Korlach, Jonas; Webb, Watt W.; Levene, Michael; Turner, Stephen; Craighead, Harold G.; Foquet, Mathieu

2006-05-30

The present invention is directed to a method of sequencing a target nucleic acid molecule having a plurality of bases. In its principle, the temporal order of base additions during the polymerization reaction is measured on a molecule of nucleic acid, i.e. the activity of a nucleic acid polymerizing enzyme on the template nucleic acid molecule to be sequenced is followed in real time. The sequence is deduced by identifying which base is being incorporated into the growing complementary strand of the target nucleic acid by the catalytic activity of the nucleic acid polymerizing enzyme at each step in the sequence of base additions. A polymerase on the target nucleic acid molecule complex is provided in a position suitable to move along the target nucleic acid molecule and extend the oligonucleotide primer at an active site. A plurality of labelled types of nucleotide analogs are provided proximate to the active site, with each distinguishable type of nucleotide analog being complementary to a different nucleotide in the target nucleic acid sequence. The growing nucleic acid strand is extended by using the polymerase to add a nucleotide analog to the nucleic acid strand at the active site, where the nucleotide analog being added is complementary to the nucleotide of the target nucleic acid at the active site. The nucleotide analog added to the oligonucleotide primer as a result of the polymerizing step is identified. The steps of providing labelled nucleotide analogs, polymerizing the growing nucleic acid strand, and identifying the added nucleotide analog are repeated so that the nucleic acid strand is further extended and the sequence of the target nucleic acid is determined.

An efficient and high fidelity method for amplification, cloning and sequencing of complete tospovirus genomic RNA segments

USDA-ARS?s Scientific Manuscript database

Amplification and sequencing of the complete M- and S-RNA segments of Tomato spotted wilt virus and Impatiens necrotic spot virus as a single fragment is useful for whole genome sequencing of tospoviruses co-infecting a single host plant. It avoids issues associated with overlapping amplicon-based ...

Modeling and prediction of peptide drift times in ion mobility spectrometry using sequence-based and structure-based approaches.

PubMed

Zhang, Yiming; Jin, Quan; Wang, Shuting; Ren, Ren

2011-05-01

The mobile behavior of 1481 peptides in ion mobility spectrometry (IMS), which are generated by protease digestion of the Drosophila melanogaster proteome, is modeled and predicted based on two different types of characterization methods, i.e. sequence-based approach and structure-based approach. In this procedure, the sequence-based approach considers both the amino acid composition of a peptide and the local environment profile of each amino acid in the peptide; the structure-based approach is performed with the CODESSA protocol, which regards a peptide as a common organic compound and generates more than 200 statistically significant variables to characterize the whole structure profile of a peptide molecule. Subsequently, the nonlinear support vector machine (SVM) and Gaussian process (GP) as well as linear partial least squares (PLS) regression is employed to correlate the structural parameters of the characterizations with the IMS drift times of these peptides. The obtained quantitative structure-spectrum relationship (QSSR) models are evaluated rigorously and investigated systematically via both one-deep and two-deep cross-validations as well as the rigorous Monte Carlo cross-validation (MCCV). We also give a comprehensive comparison on the resulting statistics arising from the different combinations of variable types with modeling methods and find that the sequence-based approach can give the QSSR models with better fitting ability and predictive power but worse interpretability than the structure-based approach. In addition, though the QSSR modeling using sequence-based approach is not needed for the preparation of the minimization structures of peptides before the modeling, it would be considerably efficient as compared to that using structure-based approach. Copyright © 2011 Elsevier Ltd. All rights reserved.

ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering.

PubMed

Verbist, Bie; Clement, Lieven; Reumers, Joke; Thys, Kim; Vapirev, Alexander; Talloen, Willem; Wetzels, Yves; Meys, Joris; Aerssens, Jeroen; Bijnens, Luc; Thas, Olivier

2015-02-22

Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second best base calls for identifying and quantifying viral variants. ViVaMBC is optimized to call variants at the codon level (nucleotide triplets) which enables immediate biological interpretation of the variants with respect to their antiviral drug responses. Using mixtures of HCV plasmids we show that our method accurately estimates frequencies down to 0.5%. The estimates are unbiased when average coverages of 25,000 are reached. A comparison with the SNP-callers V-Phaser2, ShoRAH, and LoFreq shows that ViVaMBC has a superb sensitivity and specificity for variants with frequencies above 0.4%. Unlike the competitors, ViVaMBC reports a higher number of false-positive findings with frequencies below 0.4% which might partially originate from picking up artificial variants introduced by errors in the sample and library preparation step. ViVaMBC is the first method to call viral variants directly at the codon level. The strength of the approach lies in modeling the error probabilities based on the quality scores. Although the use of second best base calls appeared very promising in our data exploration phase, their utility was limited. They provided a slight increase in sensitivity, which however does not warrant the additional computational cost of running the offline base caller. Apparently a lot of information is already contained in the quality scores enabling the model based clustering procedure to adjust the majority of the sequencing errors. Overall the sensitivity of ViVaMBC is such that technical constraints like PCR errors start to form the bottleneck for low frequency variant detection.

Implied alignment: a synapomorphy-based multiple-sequence alignment method and its use in cladogram search

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Shotgun metagenomic data streams: surfing without fear

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

Berendzen, Joel R

2010-12-06

Timely information about bio-threat prevalence, consequence, propagation, attribution, and mitigation is needed to support decision-making, both routinely and in a crisis. One DNA sequencer can stream 25 Gbp of information per day, but sampling strategies and analysis techniques are needed to turn raw sequencing power into actionable knowledge. Shotgun metagenomics can enable biosurveillance at the level of a single city, hospital, or airplane. Metagenomics characterizes viruses and bacteria from complex environments such as soil, air filters, or sewage. Unlike targeted-primer-based sequencing, shotgun methods are not blind to sequences that are truly novel, and they can measure absolute prevalence. Shotgun metagenomicmore » sampling can be non-invasive, efficient, and inexpensive while being informative. We have developed analysis techniques for shotgun metagenomic sequencing that rely upon phylogenetic signature patterns. They work by indexing local sequence patterns in a manner similar to web search engines. Our methods are laptop-fast and favorable scaling properties ensure they will be sustainable as sequencing methods grow. We show examples of application to soil metagenomic samples.« less

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI).

A coevolution analysis for identifying protein-protein interactions by Fourier transform

PubMed Central

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

Multimodal RNA-seq using single-strand, double-strand, and CircLigase-based capture yields a refined and extended description of the C. elegans transcriptome.

PubMed

Lamm, Ayelet T; Stadler, Michael R; Zhang, Huibin; Gent, Jonathan I; Fire, Andrew Z

2011-02-01

We have used a combination of three high-throughput RNA capture and sequencing methods to refine and augment the transcriptome map of a well-studied genetic model, Caenorhabditis elegans. The three methods include a standard (non-directional) library preparation protocol relying on cDNA priming and foldback that has been used in several previous studies for transcriptome characterization in this species, and two directional protocols, one involving direct capture of single-stranded RNA fragments and one involving circular-template PCR (CircLigase). We find that each RNA-seq approach shows specific limitations and biases, with the application of multiple methods providing a more complete map than was obtained from any single method. Of particular note in the analysis were substantial advantages of CircLigase-based and ssRNA-based capture for defining sequences and structures of the precise 5' ends (which were lost using the double-strand cDNA capture method). Of the three methods, ssRNA capture was most effective in defining sequences to the poly(A) junction. Using data sets from a spectrum of C. elegans strains and stages and the UCSC Genome Browser, we provide a series of tools, which facilitate rapid visualization and assignment of gene structures.

Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure.

PubMed

Kono, H; Saven, J G

2001-02-23

Combinatorial experiments provide new ways to probe the determinants of protein folding and to identify novel folding amino acid sequences. These types of experiments, however, are complicated both by enormous conformational complexity and by large numbers of possible sequences. Therefore, a quantitative computational theory would be helpful in designing and interpreting these types of experiment. Here, we present and apply a statistically based, computational approach for identifying the properties of sequences compatible with a given main-chain structure. Protein side-chain conformations are included in an atom-based fashion. Calculations are performed for a variety of similar backbone structures to identify sequence properties that are robust with respect to minor changes in main-chain structure. Rather than specific sequences, the method yields the likelihood of each of the amino acids at preselected positions in a given protein structure. The theory may be used to quantify the characteristics of sequence space for a chosen structure without explicitly tabulating sequences. To account for hydrophobic effects, we introduce an environmental energy that it is consistent with other simple hydrophobicity scales and show that it is effective for side-chain modeling. We apply the method to calculate the identity probabilities of selected positions of the immunoglobulin light chain-binding domain of protein L, for which many variant folding sequences are available. The calculations compare favorably with the experimentally observed identity probabilities.

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

PubMed

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

2018-04-16

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

Discovery of a bovine enterovirus in alpaca.

PubMed

McClenahan, Shasta D; Scherba, Gail; Borst, Luke; Fredrickson, Richard L; Krause, Philip R; Uhlenhaut, Christine

2013-01-01

A cytopathic virus was isolated using Madin-Darby bovine kidney (MDBK) cells from lung tissue of alpaca that died of a severe respiratory infection. To identify the virus, the infected cell culture supernatant was enriched for virus particles and a generic, PCR-based method was used to amplify potential viral sequences. Genomic sequence data of the alpaca isolate was obtained and compared with sequences of known viruses. The new alpaca virus sequence was most similar to recently designated Enterovirus species F, previously bovine enterovirus (BEVs), viruses that are globally prevalent in cattle, although they appear not to cause significant disease. Because bovine enteroviruses have not been previously reported in U.S. alpaca, we suspect that this type of infection is fairly rare, and in this case appeared not to spread beyond the original outbreak. The capsid sequence of the detected virus had greatest homology to Enterovirus F type 1 (indicating that the virus should be considered a member of serotype 1), but the virus had greater homology in 2A protease sequence to type 3, suggesting that it may have been a recombinant. Identifying pathogens that infect a new host species for the first time can be challenging. As the disease in a new host species may be quite different from that in the original or natural host, the pathogen may not be suspected based on the clinical presentation, delaying diagnosis. Although this virus replicated in MDBK cells, existing standard culture and molecular methods could not identify it. In this case, a highly sensitive generic PCR-based pathogen-detection method was used to identify this pathogen.

Discovery of a Bovine Enterovirus in Alpaca

PubMed Central

McClenahan, Shasta D.; Scherba, Gail; Borst, Luke; Fredrickson, Richard L.; Krause, Philip R.; Uhlenhaut, Christine

2013-01-01

A cytopathic virus was isolated using Madin-Darby bovine kidney (MDBK) cells from lung tissue of alpaca that died of a severe respiratory infection. To identify the virus, the infected cell culture supernatant was enriched for virus particles and a generic, PCR-based method was used to amplify potential viral sequences. Genomic sequence data of the alpaca isolate was obtained and compared with sequences of known viruses. The new alpaca virus sequence was most similar to recently designated Enterovirus species F, previously bovine enterovirus (BEVs), viruses that are globally prevalent in cattle, although they appear not to cause significant disease. Because bovine enteroviruses have not been previously reported in U.S. alpaca, we suspect that this type of infection is fairly rare, and in this case appeared not to spread beyond the original outbreak. The capsid sequence of the detected virus had greatest homology to Enterovirus F type 1 (indicating that the virus should be considered a member of serotype 1), but the virus had greater homology in 2A protease sequence to type 3, suggesting that it may have been a recombinant. Identifying pathogens that infect a new host species for the first time can be challenging. As the disease in a new host species may be quite different from that in the original or natural host, the pathogen may not be suspected based on the clinical presentation, delaying diagnosis. Although this virus replicated in MDBK cells, existing standard culture and molecular methods could not identify it. In this case, a highly sensitive generic PCR-based pathogen-detection method was used to identify this pathogen. PMID:23950875

Multiplexed microsatellite recovery using massively parallel sequencing

USGS Publications Warehouse

Jennings, T.N.; Knaus, B.J.; Mullins, T.D.; Haig, S.M.; Cronn, R.C.

2011-01-01

Conservation and management of natural populations requires accurate and inexpensive genotyping methods. Traditional microsatellite, or simple sequence repeat (SSR), marker analysis remains a popular genotyping method because of the comparatively low cost of marker development, ease of analysis and high power of genotype discrimination. With the availability of massively parallel sequencing (MPS), it is now possible to sequence microsatellite-enriched genomic libraries in multiplex pools. To test this approach, we prepared seven microsatellite-enriched, barcoded genomic libraries from diverse taxa (two conifer trees, five birds) and sequenced these on one lane of the Illumina Genome Analyzer using paired-end 80-bp reads. In this experiment, we screened 6.1 million sequences and identified 356958 unique microreads that contained di- or trinucleotide microsatellites. Examination of four species shows that our conversion rate from raw sequences to polymorphic markers compares favourably to Sanger- and 454-based methods. The advantage of multiplexed MPS is that the staggering capacity of modern microread sequencing is spread across many libraries; this reduces sample preparation and sequencing costs to less than $400 (USD) per species. This price is sufficiently low that microsatellite libraries could be prepared and sequenced for all 1373 organisms listed as 'threatened' and 'endangered' in the United States for under $0.5M (USD).

An Adaptive Method for Switching between Pedestrian/Car Indoor Positioning Algorithms based on Multilayer Time Sequences

PubMed Central

Gu, Zhining; Guo, Wei; Li, Chaoyang; Zhu, Xinyan; Guo, Tao

2018-01-01

Pedestrian dead reckoning (PDR) positioning algorithms can be used to obtain a target’s location only for movement with step features and not for driving, for which the trilateral Bluetooth indoor positioning method can be used. In this study, to obtain the precise locations of different states (pedestrian/car) using the corresponding positioning algorithms, we propose an adaptive method for switching between the PDR and car indoor positioning algorithms based on multilayer time sequences (MTSs). MTSs, which consider the behavior context, comprise two main aspects: filtering of noisy data in small-scale time sequences and using a state chain to reduce the time delay of algorithm switching in large-scale time sequences. The proposed method can be expected to realize the recognition of stationary, walking, driving, or other states; switch to the correct indoor positioning algorithm; and improve the accuracy of localization compared to using a single positioning algorithm. Our experiments show that the recognition of static, walking, driving, and other states improves by 5.5%, 45.47%, 26.23%, and 21% on average, respectively, compared with convolutional neural network (CNN) method. The time delay decreases by approximately 0.5–8.5 s for the transition between states and by approximately 24 s for the entire process. PMID:29495503

Hypoxia-induced oxidative base modifications in the VEGF hypoxia-response element are associated with transcriptionally active nucleosomes.

PubMed

Ruchko, Mykhaylo V; Gorodnya, Olena M; Pastukh, Viktor M; Swiger, Brad M; Middleton, Natavia S; Wilson, Glenn L; Gillespie, Mark N

2009-02-01

Reactive oxygen species (ROS) generated in hypoxic pulmonary artery endothelial cells cause transient oxidative base modifications in the hypoxia-response element (HRE) of the VEGF gene that bear a conspicuous relationship to induction of VEGF mRNA expression (K.A. Ziel et al., FASEB J. 19, 387-394, 2005). If such base modifications are indeed linked to transcriptional regulation, then they should be detected in HRE sequences associated with transcriptionally active nucleosomes. Southern blot analysis of the VEGF HRE associated with nucleosome fractions prepared by micrococcal nuclease digestion indicated that hypoxia redistributed some HRE sequences from multinucleosomes to transcriptionally active mono- and dinucleosome fractions. A simple PCR method revealed that VEGF HRE sequences harboring oxidative base modifications were found exclusively in mononucleosomes. Inhibition of hypoxia-induced ROS generation with myxathiozol prevented formation of oxidative base modifications but not the redistribution of HRE sequences into mono- and dinucleosome fractions. The histone deacetylase inhibitor trichostatin A caused retention of HRE sequences in compacted nucleosome fractions and prevented formation of oxidative base modifications. These findings suggest that the hypoxia-induced oxidant stress directed at the VEGF HRE requires the sequence to be repositioned into mononucleosomes and support the prospect that oxidative modifications in this sequence are an important step in transcriptional activation.

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

PubMed

Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

2018-02-01

Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

A combined emitter threat assessment method based on ICW-RCM

NASA Astrophysics Data System (ADS)

Zhang, Ying; Wang, Hongwei; Guo, Xiaotao; Wang, Yubing

2017-08-01

Considering that the tradition al emitter threat assessment methods are difficult to intuitively reflect the degree of target threaten and the deficiency of real-time and complexity, on the basis of radar chart method(RCM), an algorithm of emitter combined threat assessment based on ICW-RCM (improved combination weighting method, ICW) is proposed. The coarse sorting is integrated with fine sorting in emitter combined threat assessment, sequencing the emitter threat level roughly accordance to radar operation mode, and reducing task priority of the low-threat emitter; On the basis of ICW-RCM, sequencing the same radar operation mode emitter roughly, finally, obtain the results of emitter threat assessment through coarse and fine sorting. Simulation analyses show the correctness and effectiveness of this algorithm. Comparing with classical method of emitter threat assessment based on CW-RCM, the algorithm is visual in image and can work quickly with lower complexity.

Enhancing the detection of barcoded reads in high throughput DNA sequencing data by controlling the false discovery rate.

PubMed

Buschmann, Tilo; Zhang, Rong; Brash, Douglas E; Bystrykh, Leonid V

2014-08-07

DNA barcodes are short unique sequences used to label DNA or RNA-derived samples in multiplexed deep sequencing experiments. During the demultiplexing step, barcodes must be detected and their position identified. In some cases (e.g., with PacBio SMRT), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives.For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements. In our analysis, barcode sequences showed high rates of coincidental similarities with the Mus musculus reference DNA. This problem became more acute when the length of the barcode sequence decreased and the number of barcodes in the set increased. The method presented in this paper controls the tail area-based false discovery rate to distinguish between barcoded and unbarcoded reads. This method helps to establish the highest acceptable minimal distance between reads and barcode sequences. In a proof of concept experiment we correctly detected barcodes in 83% of the reads with a precision of 89%. Sensitivity improved to 99% at 99% precision when the adjacent primer sequence was incorporated in the analysis. The analysis was further improved using a paired end strategy. Following an analysis of the data for sequence variants induced in the Atp1a1 gene of C57BL/6 murine melanocytes by ultraviolet light and conferring resistance to ouabain, we found no evidence of cross-contamination of DNA material between samples. Our method offers a proper quantitative treatment of the problem of detecting barcoded reads in a noisy sequencing environment. It is based on the false discovery rate statistics that allows a proper trade-off between sensitivity and precision to be chosen.

MISTICA: Minimum Spanning Tree-based Coarse Image Alignment for Microscopy Image Sequences

PubMed Central

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T.

2016-01-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to re-order the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries. PMID:26415193

MISTICA: Minimum Spanning Tree-Based Coarse Image Alignment for Microscopy Image Sequences.

PubMed

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T

2016-11-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to reorder the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by the way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries.

Detection of nucleic acids by multiple sequential invasive cleavages

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann D.

1999-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Nucleic acid detection kits

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann; Kwiatkowski, Robert W.; Vavra, Stephanie H.

2005-03-29

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of nucleic acid from various viruses in a sample.

Detection of nucleic acids by multiple sequential invasive cleavages 02

DOEpatents

Hall, Jeff G.; Lyamichev, Victor I.; Mast, Andrea L.; Brow, Mary Ann D.

2002-01-01

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Detection of nucleic acids by multiple sequential invasive cleavages

DOEpatents

Hall, Jeff G; Lyamichev, Victor I; Mast, Andrea L; Brow, Mary Ann D

2012-10-16

The present invention relates to means for the detection and characterization of nucleic acid sequences, as well as variations in nucleic acid sequences. The present invention also relates to methods for forming a nucleic acid cleavage structure on a target sequence and cleaving the nucleic acid cleavage structure in a site-specific manner. The structure-specific nuclease activity of a variety of enzymes is used to cleave the target-dependent cleavage structure, thereby indicating the presence of specific nucleic acid sequences or specific variations thereof. The present invention further relates to methods and devices for the separation of nucleic acid molecules based on charge. The present invention also provides methods for the detection of non-target cleavage products via the formation of a complete and activated protein binding region. The invention further provides sensitive and specific methods for the detection of human cytomegalovirus nucleic acid in a sample.

Molecular Identification and Databases in Fusarium

USDA-ARS?s Scientific Manuscript database

DNA sequence-based methods for identifying pathogenic and mycotoxigenic Fusarium isolates have become the gold standard worldwide. Moreover, fusarial DNA sequence data are increasing rapidly in several web-accessible databases for comparative purposes. Unfortunately, the use of Basic Alignment Sea...

Connection method of separated luminal regions of intestine from CT volumes

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kitasaka, Takayuki; Furukawa, Kazuhiro; Watanabe, Osamu; Ando, Takafumi; Hirooka, Yoshiki; Goto, Hidemi; Mori, Kensaku

2015-03-01

This paper proposes a connection method of separated luminal regions of the intestine for Crohn's disease diagnosis. Crohn's disease is an inflammatory disease of the digestive tract. Capsule or conventional endoscopic diagnosis is performed for Crohn's disease diagnosis. However, parts of the intestines may not be observed in the endoscopic diagnosis if intestinal stenosis occurs. Endoscopes cannot pass through the stenosed parts. CT image-based diagnosis is developed as an alternative choice of the Crohn's disease. CT image-based diagnosis enables physicians to observe the entire intestines even if stenosed parts exist. CAD systems for Crohn's disease using CT volumes are recently developed. Such CAD systems need to reconstruct separated luminal regions of the intestines to analyze intestines. We propose a connection method of separated luminal regions of the intestines segmented from CT volumes. The luminal regions of the intestines are segmented from a CT volume. The centerlines of the luminal regions are calculated by using a thinning process. We enumerate all the possible sequences of the centerline segments. In this work, we newly introduce a condition using distance between connected ends points of the centerline segments. This condition eliminates unnatural connections of the centerline segments. Also, this condition reduces processing time. After generating a sequence list of the centerline segments, the correct sequence is obtained by using an evaluation function. We connect the luminal regions based on the correct sequence. Our experiments using four CT volumes showed that our method connected 6.5 out of 8.0 centerline segments per case. Processing times of the proposed method were reduced from the previous method.

Phase-based motion magnification video for monitoring of vital signals using the Hermite transform

NASA Astrophysics Data System (ADS)

Brieva, Jorge; Moya-Albor, Ernesto

2017-11-01

In this paper we present a new Eulerian phase-based motion magnification technique using the Hermite Transform (HT) decomposition that is inspired in the Human Vision System (HVS). We test our method in one sequence of the breathing of a newborn baby and on a video sequence that shows the heartbeat on the wrist. We detect and magnify the heart pulse applying our technique. Our motion magnification approach is compared to the Laplacian phase based approach by means of quantitative metrics (based on the RMS error and the Fourier transform) to measure the quality of both reconstruction and magnification. In addition a noise robustness analysis is performed for the two methods.

Application of next-generation sequencing for rapid marker development in molecular plant breeding: a case study on anthracnose disease resistance in Lupinus angustifolius L.

PubMed Central

2012-01-01

Background In the last 30 years, a number of DNA fingerprinting methods such as RFLP, RAPD, AFLP, SSR, DArT, have been extensively used in marker development for molecular plant breeding. However, it remains a daunting task to identify highly polymorphic and closely linked molecular markers for a target trait for molecular marker-assisted selection. The next-generation sequencing (NGS) technology is far more powerful than any existing generic DNA fingerprinting methods in generating DNA markers. In this study, we employed a grain legume crop Lupinus angustifolius (lupin) as a test case, and examined the utility of an NGS-based method of RAD (restriction-site associated DNA) sequencing as DNA fingerprinting for rapid, cost-effective marker development tagging a disease resistance gene for molecular breeding. Results Twenty informative plants from a cross of RxS (disease resistant x susceptible) in lupin were subjected to RAD single-end sequencing by multiplex identifiers. The entire RAD sequencing products were resolved in two lanes of the 16-lanes per run sequencing platform Solexa HiSeq2000. A total of 185 million raw reads, approximately 17 Gb of sequencing data, were collected. Sequence comparison among the 20 test plants discovered 8207 SNP markers. Filtration of DNA sequencing data with marker identification parameters resulted in the discovery of 38 molecular markers linked to the disease resistance gene Lanr1. Five randomly selected markers were converted into cost-effective, simple PCR-based markers. Linkage analysis using marker genotyping data and disease resistance phenotyping data on a F8 population consisting of 186 individual plants confirmed that all these five markers were linked to the R gene. Two of these newly developed sequence-specific PCR markers, AnSeq3 and AnSeq4, flanked the target R gene at a genetic distance of 0.9 centiMorgan (cM), and are now replacing the markers previously developed by a traditional DNA fingerprinting method for marker-assisted selection in the Australian national lupin breeding program. Conclusions We demonstrated that more than 30 molecular markers linked to a target gene of agronomic trait of interest can be identified from a small portion (1/8) of one sequencing run on HiSeq2000 by applying NGS based RAD sequencing in marker development. The markers developed by the strategy described in this study are all co-dominant SNP markers, which can readily be converted into high throughput multiplex format or low-cost, simple PCR-based markers desirable for large scale marker implementation in plant breeding programs. The high density and closely linked molecular markers associated with a target trait help to overcome a major bottleneck for implementation of molecular markers on a wide range of germplasm in breeding programs. We conclude that application of NGS based RAD sequencing as DNA fingerprinting is a very rapid and cost-effective strategy for marker development in molecular plant breeding. The strategy does not require any prior genome knowledge or molecular information for the species under investigation, and it is applicable to other plant species. PMID:22805587

Application of next-generation sequencing for rapid marker development in molecular plant breeding: a case study on anthracnose disease resistance in Lupinus angustifolius L.

PubMed

Yang, Huaan; Tao, Ye; Zheng, Zequn; Li, Chengdao; Sweetingham, Mark W; Howieson, John G

2012-07-17

In the last 30 years, a number of DNA fingerprinting methods such as RFLP, RAPD, AFLP, SSR, DArT, have been extensively used in marker development for molecular plant breeding. However, it remains a daunting task to identify highly polymorphic and closely linked molecular markers for a target trait for molecular marker-assisted selection. The next-generation sequencing (NGS) technology is far more powerful than any existing generic DNA fingerprinting methods in generating DNA markers. In this study, we employed a grain legume crop Lupinus angustifolius (lupin) as a test case, and examined the utility of an NGS-based method of RAD (restriction-site associated DNA) sequencing as DNA fingerprinting for rapid, cost-effective marker development tagging a disease resistance gene for molecular breeding. Twenty informative plants from a cross of RxS (disease resistant x susceptible) in lupin were subjected to RAD single-end sequencing by multiplex identifiers. The entire RAD sequencing products were resolved in two lanes of the 16-lanes per run sequencing platform Solexa HiSeq2000. A total of 185 million raw reads, approximately 17 Gb of sequencing data, were collected. Sequence comparison among the 20 test plants discovered 8207 SNP markers. Filtration of DNA sequencing data with marker identification parameters resulted in the discovery of 38 molecular markers linked to the disease resistance gene Lanr1. Five randomly selected markers were converted into cost-effective, simple PCR-based markers. Linkage analysis using marker genotyping data and disease resistance phenotyping data on a F8 population consisting of 186 individual plants confirmed that all these five markers were linked to the R gene. Two of these newly developed sequence-specific PCR markers, AnSeq3 and AnSeq4, flanked the target R gene at a genetic distance of 0.9 centiMorgan (cM), and are now replacing the markers previously developed by a traditional DNA fingerprinting method for marker-assisted selection in the Australian national lupin breeding program. We demonstrated that more than 30 molecular markers linked to a target gene of agronomic trait of interest can be identified from a small portion (1/8) of one sequencing run on HiSeq2000 by applying NGS based RAD sequencing in marker development. The markers developed by the strategy described in this study are all co-dominant SNP markers, which can readily be converted into high throughput multiplex format or low-cost, simple PCR-based markers desirable for large scale marker implementation in plant breeding programs. The high density and closely linked molecular markers associated with a target trait help to overcome a major bottleneck for implementation of molecular markers on a wide range of germplasm in breeding programs. We conclude that application of NGS based RAD sequencing as DNA fingerprinting is a very rapid and cost-effective strategy for marker development in molecular plant breeding. The strategy does not require any prior genome knowledge or molecular information for the species under investigation, and it is applicable to other plant species.

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

PubMed

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

2005-11-15

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

Sequence-independent construction of ordered combinatorial libraries with predefined crossover points.

PubMed

Jézéquel, Laetitia; Loeper, Jacqueline; Pompon, Denis

2008-11-01

Combinatorial libraries coding for mosaic enzymes with predefined crossover points constitute useful tools to address and model structure-function relationships and for functional optimization of enzymes based on multivariate statistics. The presented method, called sequence-independent generation of a chimera-ordered library (SIGNAL), allows easy shuffling of any predefined amino acid segment between two or more proteins. This method is particularly well adapted to the exchange of protein structural modules. The procedure could also be well suited to generate ordered combinatorial libraries independent of sequence similarities in a robotized manner. Sequence segments to be recombined are first extracted by PCR from a single-stranded template coding for an enzyme of interest using a biotin-avidin-based method. This technique allows the reduction of parental template contamination in the final library. Specific PCR primers allow amplification of two complementary mosaic DNA fragments, overlapping in the region to be exchanged. Fragments are finally reassembled using a fusion PCR. The process is illustrated via the construction of a set of mosaic CYP2B enzymes using this highly modular approach.

Pseudomonas sp. strain CA5 (a selenite-reducing bacterium) 16S rRNA gene complete sequence. National Institute of Health, National Center for Biotechnology Information, GenBank sequence. Accession FJ422810.1.

USDA-ARS?s Scientific Manuscript database

This study used 1321 base pair 16S rRNA gene sequence methods to confirm the phylogenetic position of a soil isolate as a bacterium belonging to the genus Pesudomonas sp. Morphological, biochemical characteristics, and fatty acid profiles are consistent with the 16S rRNA gene sequence identification...

Sanger sequencing as a first-line approach for molecular diagnosis of Andersen-Tawil syndrome.

PubMed

Totomoch-Serra, Armando; Marquez, Manlio F; Cervantes-Barragán, David E

2017-01-01

In 1977, Frederick Sanger developed a new method for DNA sequencing based on the chain termination method, now known as the Sanger sequencing method (SSM).  Recently, massive parallel sequencing, better known as next-generation sequencing (NGS),  is replacing the SSM for detecting mutations in cardiovascular diseases with a genetic background. The present opinion article wants to remark that "targeted" SSM is still effective as a first-line approach for the molecular diagnosis of some specific conditions, as is the case for Andersen-Tawil syndrome (ATS). ATS is described as a rare multisystemic autosomal dominant channelopathy syndrome caused mainly by a heterozygous mutation in the KCNJ2 gene . KCJN2 has particular characteristics that make it attractive for "directed" SSM. KCNJ2 has a sequence of 17,510 base pairs (bp), and a short coding region with two exons (exon 1=166 bp and exon 2=5220 bp), half of the mutations are located in the C-terminal cytosolic domain, a mutational hotspot has been described in residue Arg218, and this gene explains the phenotype in 60% of ATS cases that fulfill all the clinical criteria of the disease. In order to increase the diagnosis of ATS we urge cardiologists to search for facial and muscular abnormalities in subjects with frequent ventricular arrhythmias (especially bigeminy) and prominent U waves on the electrocardiogram.

Sanger sequencing as a first-line approach for molecular diagnosis of Andersen-Tawil syndrome

PubMed Central

Totomoch-Serra, Armando; Marquez, Manlio F.; Cervantes-Barragán, David E.

2017-01-01

In 1977, Frederick Sanger developed a new method for DNA sequencing based on the chain termination method, now known as the Sanger sequencing method (SSM).  Recently, massive parallel sequencing, better known as next-generation sequencing (NGS),  is replacing the SSM for detecting mutations in cardiovascular diseases with a genetic background. The present opinion article wants to remark that “targeted” SSM is still effective as a first-line approach for the molecular diagnosis of some specific conditions, as is the case for Andersen-Tawil syndrome (ATS). ATS is described as a rare multisystemic autosomal dominant channelopathy syndrome caused mainly by a heterozygous mutation in the KCNJ2 gene . KCJN2 has particular characteristics that make it attractive for “directed” SSM. KCNJ2 has a sequence of 17,510 base pairs (bp), and a short coding region with two exons (exon 1=166 bp and exon 2=5220 bp), half of the mutations are located in the C-terminal cytosolic domain, a mutational hotspot has been described in residue Arg218, and this gene explains the phenotype in 60% of ATS cases that fulfill all the clinical criteria of the disease. In order to increase the diagnosis of ATS we urge cardiologists to search for facial and muscular abnormalities in subjects with frequent ventricular arrhythmias (especially bigeminy) and prominent U waves on the electrocardiogram. PMID:29093808

Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical Structures.

PubMed

Meng, Fan-Rong; You, Zhu-Hong; Chen, Xing; Zhou, Yong; An, Ji-Yong

2017-07-05

Knowledge of drug-target interaction (DTI) plays an important role in discovering new drug candidates. Unfortunately, there are unavoidable shortcomings; including the time-consuming and expensive nature of the experimental method to predict DTI. Therefore, it motivates us to develop an effective computational method to predict DTI based on protein sequence. In the paper, we proposed a novel computational approach based on protein sequence, namely PDTPS (Predicting Drug Targets with Protein Sequence) to predict DTI. The PDTPS method combines Bi-gram probabilities (BIGP), Position Specific Scoring Matrix (PSSM), and Principal Component Analysis (PCA) with Relevance Vector Machine (RVM). In order to evaluate the prediction capacity of the PDTPS, the experiment was carried out on enzyme, ion channel, GPCR, and nuclear receptor datasets by using five-fold cross-validation tests. The proposed PDTPS method achieved average accuracy of 97.73%, 93.12%, 86.78%, and 87.78% on enzyme, ion channel, GPCR and nuclear receptor datasets, respectively. The experimental results showed that our method has good prediction performance. Furthermore, in order to further evaluate the prediction performance of the proposed PDTPS method, we compared it with the state-of-the-art support vector machine (SVM) classifier on enzyme and ion channel datasets, and other exiting methods on four datasets. The promising comparison results further demonstrate that the efficiency and robust of the proposed PDTPS method. This makes it a useful tool and suitable for predicting DTI, as well as other bioinformatics tasks.

Efficient alignment-free DNA barcode analytics

PubMed Central

Kuksa, Pavel; Pavlovic, Vladimir

2009-01-01

Background In this work we consider barcode DNA analysis problems and address them using alternative, alignment-free methods and representations which model sequences as collections of short sequence fragments (features). The methods use fixed-length representations (spectrum) for barcode sequences to measure similarities or dissimilarities between sequences coming from the same or different species. The spectrum-based representation not only allows for accurate and computationally efficient species classification, but also opens possibility for accurate clustering analysis of putative species barcodes and identification of critical within-barcode loci distinguishing barcodes of different sample groups. Results New alignment-free methods provide highly accurate and fast DNA barcode-based identification and classification of species with substantial improvements in accuracy and speed over state-of-the-art barcode analysis methods. We evaluate our methods on problems of species classification and identification using barcodes, important and relevant analytical tasks in many practical applications (adverse species movement monitoring, sampling surveys for unknown or pathogenic species identification, biodiversity assessment, etc.) On several benchmark barcode datasets, including ACG, Astraptes, Hesperiidae, Fish larvae, and Birds of North America, proposed alignment-free methods considerably improve prediction accuracy compared to prior results. We also observe significant running time improvements over the state-of-the-art methods. Conclusion Our results show that newly developed alignment-free methods for DNA barcoding can efficiently and with high accuracy identify specimens by examining only few barcode features, resulting in increased scalability and interpretability of current computational approaches to barcoding. PMID:19900305

Nanopore-CMOS Interfaces for DNA Sequencing

PubMed Central

Magierowski, Sebastian; Huang, Yiyun; Wang, Chengjie; Ghafar-Zadeh, Ebrahim

2016-01-01

DNA sequencers based on nanopore sensors present an opportunity for a significant break from the template-based incumbents of the last forty years. Key advantages ushered by nanopore technology include a simplified chemistry and the ability to interface to CMOS technology. The latter opportunity offers substantial promise for improvement in sequencing speed, size and cost. This paper reviews existing and emerging means of interfacing nanopores to CMOS technology with an emphasis on massively-arrayed structures. It presents this in the context of incumbent DNA sequencing techniques, reviews and quantifies nanopore characteristics and models and presents CMOS circuit methods for the amplification of low-current nanopore signals in such interfaces. PMID:27509529

Nanopore-CMOS Interfaces for DNA Sequencing.

PubMed

Magierowski, Sebastian; Huang, Yiyun; Wang, Chengjie; Ghafar-Zadeh, Ebrahim

2016-08-06

DNA sequencers based on nanopore sensors present an opportunity for a significant break from the template-based incumbents of the last forty years. Key advantages ushered by nanopore technology include a simplified chemistry and the ability to interface to CMOS technology. The latter opportunity offers substantial promise for improvement in sequencing speed, size and cost. This paper reviews existing and emerging means of interfacing nanopores to CMOS technology with an emphasis on massively-arrayed structures. It presents this in the context of incumbent DNA sequencing techniques, reviews and quantifies nanopore characteristics and models and presents CMOS circuit methods for the amplification of low-current nanopore signals in such interfaces.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

PubMed

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

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.

Plasmid Flux in Escherichia coli ST131 Sublineages, Analyzed by Plasmid Constellation Network (PLACNET), a New Method for Plasmid Reconstruction from Whole Genome Sequences

PubMed Central

Garcillán-Barcia, M. Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M.; de la Cruz, Fernando

2014-01-01

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages. PMID:25522143

Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.

PubMed

Lanza, Val F; de Toro, María; Garcillán-Barcia, M Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M; de la Cruz, Fernando

2014-12-01

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

Identification and characterization of unrecognized viruses in stool samples of non-polio acute flaccid paralysis children by simplified VIDISCA.

PubMed

Shaukat, Shahzad; Angez, Mehar; Alam, Muhammad Masroor; Jebbink, Maarten F; Deijs, Martin; Canuti, Marta; Sharif, Salmaan; de Vries, Michel; Khurshid, Adnan; Mahmood, Tariq; van der Hoek, Lia; Zaidi, Syed Sohail Zahoor

2014-08-12

The use of sequence independent methods combined with next generation sequencing for identification purposes in clinical samples appears promising and exciting results have been achieved to understand unexplained infections. One sequence independent method, Virus Discovery based on cDNA Amplified Fragment Length Polymorphism (VIDISCA) is capable of identifying viruses that would have remained unidentified in standard diagnostics or cell cultures. VIDISCA is normally combined with next generation sequencing, however, we set up a simplified VIDISCA which can be used in case next generation sequencing is not possible. Stool samples of 10 patients with unexplained acute flaccid paralysis showing cytopathic effect in rhabdomyosarcoma cells and/or mouse cells were used to test the efficiency of this method. To further characterize the viruses, VIDISCA-positive samples were amplified and sequenced with gene specific primers. Simplified VIDISCA detected seven viruses (70%) and the proportion of eukaryotic viral sequences from each sample ranged from 8.3 to 45.8%. Human enterovirus EV-B97, EV-B100, echovirus-9 and echovirus-21, human parechovirus type-3, human astrovirus probably a type-3/5 recombinant, and tetnovirus-1 were identified. Phylogenetic analysis based on the VP1 region demonstrated that the human enteroviruses are more divergent isolates circulating in the community. Our data support that a simplified VIDISCA protocol can efficiently identify unrecognized viruses grown in cell culture with low cost, limited time without need of advanced technical expertise. Also complex data interpretation is avoided thus the method can be used as a powerful diagnostic tool in limited resources. Redesigning the routine diagnostics might lead to additional detection of previously undiagnosed viruses in clinical samples of patients.

Variation block-based genomics method for crop plants.

PubMed

Kim, Yul Ho; Park, Hyang Mi; Hwang, Tae-Young; Lee, Seuk Ki; Choi, Man Soo; Jho, Sungwoong; Hwang, Seungwoo; Kim, Hak-Min; Lee, Dongwoo; Kim, Byoung-Chul; Hong, Chang Pyo; Cho, Yun Sung; Kim, Hyunmin; Jeong, Kwang Ho; Seo, Min Jung; Yun, Hong Tai; Kim, Sun Lim; Kwon, Young-Up; Kim, Wook Han; Chun, Hye Kyung; Lim, Sang Jong; Shin, Young-Ah; Choi, Ik-Young; Kim, Young Sun; Yoon, Ho-Sung; Lee, Suk-Ha; Lee, Sunghoon

2014-06-15

In contrast with wild species, cultivated crop genomes consist of reshuffled recombination blocks, which occurred by crossing and selection processes. Accordingly, recombination block-based genomics analysis can be an effective approach for the screening of target loci for agricultural traits. We propose the variation block method, which is a three-step process for recombination block detection and comparison. The first step is to detect variations by comparing the short-read DNA sequences of the cultivar to the reference genome of the target crop. Next, sequence blocks with variation patterns are examined and defined. The boundaries between the variation-containing sequence blocks are regarded as recombination sites. All the assumed recombination sites in the cultivar set are used to split the genomes, and the resulting sequence regions are termed variation blocks. Finally, the genomes are compared using the variation blocks. The variation block method identified recurring recombination blocks accurately and successfully represented block-level diversities in the publicly available genomes of 31 soybean and 23 rice accessions. The practicality of this approach was demonstrated by the identification of a putative locus determining soybean hilum color. We suggest that the variation block method is an efficient genomics method for the recombination block-level comparison of crop genomes. We expect that this method will facilitate the development of crop genomics by bringing genomics technologies to the field of crop breeding.

Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment

NASA Astrophysics Data System (ADS)

Yang, Hongxin; Su, Fulin

2018-01-01

We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.

Improved detection of CXCR4-using HIV by V3 genotyping: application of population-based and "deep" sequencing to plasma RNA and proviral DNA.

PubMed

Swenson, Luke C; Moores, Andrew; Low, Andrew J; Thielen, Alexander; Dong, Winnie; Woods, Conan; Jensen, Mark A; Wynhoven, Brian; Chan, Dennison; Glascock, Christopher; Harrigan, P Richard

2010-08-01

Tropism testing should rule out CXCR4-using HIV before treatment with CCR5 antagonists. Currently, the recombinant phenotypic Trofile assay (Monogram) is most widely utilized; however, genotypic tests may represent alternative methods. Independent triplicate amplifications of the HIV gp120 V3 region were made from either plasma HIV RNA or proviral DNA. These underwent standard, population-based sequencing with an ABI3730 (RNA n = 63; DNA n = 40), or "deep" sequencing with a Roche/454 Genome Sequencer-FLX (RNA n = 12; DNA n = 12). Position-specific scoring matrices (PSSMX4/R5) (-6.96 cutoff) and geno2pheno[coreceptor] (5% false-positive rate) inferred tropism from V3 sequence. These methods were then independently validated with a separate, blinded dataset (n = 278) of screening samples from the maraviroc MOTIVATE trials. Standard sequencing of HIV RNA with PSSM yielded 69% sensitivity and 91% specificity, relative to Trofile. The validation dataset gave 75% sensitivity and 83% specificity. Proviral DNA plus PSSM gave 77% sensitivity and 71% specificity. "Deep" sequencing of HIV RNA detected >2% inferred-CXCR4-using virus in 8/8 samples called non-R5 by Trofile, and <2% in 4/4 samples called R5. Triplicate analyses of V3 standard sequence data detect greater proportions of CXCR4-using samples than previously achieved. Sequencing proviral DNA and "deep" V3 sequencing may also be useful tools for assessing tropism.

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica

PubMed Central

Guard, Jean; Sanchez-Ingunza, Roxana; Morales, Cesar; Stewart, Tod; Liljebjelke, Karen; Kessel, JoAnn; Ingram, Kim; Jones, Deana; Jackson, Charlene; Fedorka-Cray, Paula; Frye, Jonathan; Gast, Richard; Hinton, Arthur

2012-01-01

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research. PMID:22998607

Optimisation of DNA extraction from the crustacean Daphnia

PubMed Central

Athanasio, Camila Gonçalves; Chipman, James K.; Viant, Mark R.

2016-01-01

Daphnia are key model organisms for mechanistic studies of phenotypic plasticity, adaptation and microevolution, which have led to an increasing demand for genomics resources. A key step in any genomics analysis, such as high-throughput sequencing, is the availability of sufficient and high quality DNA. Although commercial kits exist to extract genomic DNA from several species, preparation of high quality DNA from Daphnia spp. and other chitinous species can be challenging. Here, we optimise methods for tissue homogenisation, DNA extraction and quantification customised for different downstream analyses (e.g., LC-MS/MS, Hiseq, mate pair sequencing or Nanopore). We demonstrate that if Daphnia magna are homogenised as whole animals (including the carapace), absorbance-based DNA quantification methods significantly over-estimate the amount of DNA, resulting in using insufficient starting material for experiments, such as preparation of sequencing libraries. This is attributed to the high refractive index of chitin in Daphnia’s carapace at 260 nm. Therefore, unless the carapace is removed by overnight proteinase digestion, the extracted DNA should be quantified with fluorescence-based methods. However, overnight proteinase digestion will result in partial fragmentation of DNA therefore the prepared DNA is not suitable for downstream methods that require high molecular weight DNA, such as PacBio, mate pair sequencing and Nanopore. In conclusion, we found that the MasterPure DNA purification kit, coupled with grinding of frozen tissue, is the best method for extraction of high molecular weight DNA as long as the extracted DNA is quantified with fluorescence-based methods. This method generated high yield and high molecular weight DNA (3.10 ± 0.63 ng/µg dry mass, fragments >60 kb), free of organic contaminants (phenol, chloroform) and is suitable for large number of downstream analyses. PMID:27190714

Molecular phylogeny of 21 tropical bamboo species reconstructed by integrating non-coding internal transcribed spacer (ITS1 and 2) sequences and their consensus secondary structure.

PubMed

Ghosh, Jayadri Sekhar; Bhattacharya, Samik; Pal, Amita

2017-06-01

The unavailability of the reproductive structure and unpredictability of vegetative characters for the identification and phylogenetic study of bamboo prompted the application of molecular techniques for greater resolution and consensus. We first employed internal transcribed spacer (ITS1, 5.8S rRNA and ITS2) sequences to construct the phylogenetic tree of 21 tropical bamboo species. While the sequence alone could grossly reconstruct the traditional phylogeny amongst the 21-tropical species studied, some anomalies were encountered that prompted a further refinement of the phylogenetic analyses. Therefore, we integrated the secondary structure of the ITS sequences to derive individual sequence-structure matrix to gain more resolution on the phylogenetic reconstruction. The results showed that ITS sequence-structure is the reliable alternative to the conventional phenotypic method for the identification of bamboo species. The best-fit topology obtained by the sequence-structure based phylogeny over the sole sequence based one underscores closer clustering of all the studied Bambusa species (Sub-tribe Bambusinae), while Melocanna baccifera, which belongs to Sub-Tribe Melocanneae, disjointedly clustered as an out-group within the consensus phylogenetic tree. In this study, we demonstrated the dependability of the combined (ITS sequence+structure-based) approach over the only sequence-based analysis for phylogenetic relationship assessment of bamboo.

Identification of Active Bacterial Communities in Drinking Water Using 16S rRNA-Based Sequence Analyses

EPA Science Inventory

DNA-based methods have considerably increased our understanding of the bacterial diversity of water distribution systems (WDS). However, as DNA may persist after cell death, the use of DNA-based methods cannot be used to describe metabolically-active microbes. In contrast, intra...

Using expected sequence features to improve basecalling accuracy of amplicon pyrosequencing data.

PubMed

Rask, Thomas S; Petersen, Bent; Chen, Donald S; Day, Karen P; Pedersen, Anders Gorm

2016-04-22

Amplicon pyrosequencing targets a known genetic region and thus inherently produces reads highly anticipated to have certain features, such as conserved nucleotide sequence, and in the case of protein coding DNA, an open reading frame. Pyrosequencing errors, consisting mainly of nucleotide insertions and deletions, are on the other hand likely to disrupt open reading frames. Such an inverse relationship between errors and expectation based on prior knowledge can be used advantageously to guide the process known as basecalling, i.e. the inference of nucleotide sequence from raw sequencing data. The new basecalling method described here, named Multipass, implements a probabilistic framework for working with the raw flowgrams obtained by pyrosequencing. For each sequence variant Multipass calculates the likelihood and nucleotide sequence of several most likely sequences given the flowgram data. This probabilistic approach enables integration of basecalling into a larger model where other parameters can be incorporated, such as the likelihood for observing a full-length open reading frame at the targeted region. We apply the method to 454 amplicon pyrosequencing data obtained from a malaria virulence gene family, where Multipass generates 20 % more error-free sequences than current state of the art methods, and provides sequence characteristics that allow generation of a set of high confidence error-free sequences. This novel method can be used to increase accuracy of existing and future amplicon sequencing data, particularly where extensive prior knowledge is available about the obtained sequences, for example in analysis of the immunoglobulin VDJ region where Multipass can be combined with a model for the known recombining germline genes. Multipass is available for Roche 454 data at http://www.cbs.dtu.dk/services/MultiPass-1.0 , and the concept can potentially be implemented for other sequencing technologies as well.

Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.

PubMed

Liu, Xuejun; Shi, Xinxin; Chen, Chunlin; Zhang, Li

2015-10-16

The high-throughput sequencing technology, RNA-Seq, has been widely used to quantify gene and isoform expression in the study of transcriptome in recent years. Accurate expression measurement from the millions or billions of short generated reads is obstructed by difficulties. One is ambiguous mapping of reads to reference transcriptome caused by alternative splicing. This increases the uncertainty in estimating isoform expression. The other is non-uniformity of read distribution along the reference transcriptome due to positional, sequencing, mappability and other undiscovered sources of biases. This violates the uniform assumption of read distribution for many expression calculation approaches, such as the direct RPKM calculation and Poisson-based models. Many methods have been proposed to address these difficulties. Some approaches employ latent variable models to discover the underlying pattern of read sequencing. However, most of these methods make bias correction based on surrounding sequence contents and share the bias models by all genes. They therefore cannot estimate gene- and isoform-specific biases as revealed by recent studies. We propose a latent variable model, NLDMseq, to estimate gene and isoform expression. Our method adopts latent variables to model the unknown isoforms, from which reads originate, and the underlying percentage of multiple spliced variants. The isoform- and exon-specific read sequencing biases are modeled to account for the non-uniformity of read distribution, and are identified by utilizing the replicate information of multiple lanes of a single library run. We employ simulation and real data to verify the performance of our method in terms of accuracy in the calculation of gene and isoform expression. Results show that NLDMseq obtains competitive gene and isoform expression compared to popular alternatives. Finally, the proposed method is applied to the detection of differential expression (DE) to show its usefulness in the downstream analysis. The proposed NLDMseq method provides an approach to accurately estimate gene and isoform expression from RNA-Seq data by modeling the isoform- and exon-specific read sequencing biases. It makes use of a latent variable model to discover the hidden pattern of read sequencing. We have shown that it works well in both simulations and real datasets, and has competitive performance compared to popular methods. The method has been implemented as a freely available software which can be found at https://github.com/PUGEA/NLDMseq.

Event-specific qualitative and quantitative PCR detection of the GMO carnation (Dianthus caryophyllus) variety Moonlite based upon the 5'-transgene integration sequence.

PubMed

Li, P; Jia, J W; Jiang, L X; Zhu, H; Bai, L; Wang, J B; Tang, X M; Pan, A H

2012-04-27

To ensure the implementation of genetically modified organism (GMO)-labeling regulations, an event-specific detection method was developed based on the junction sequence of an exogenous integrant in the transgenic carnation variety Moonlite. The 5'-transgene integration sequence was isolated by thermal asymmetric interlaced PCR. Based upon the 5'-transgene integration sequence, the event-specific primers and TaqMan probe were designed to amplify the fragments, which spanned the exogenous DNA and carnation genomic DNA. Qualitative and quantitative PCR assays were developed employing the designed primers and probe. The detection limit of the qualitative PCR assay was 0.05% for Moonlite in 100 ng total carnation genomic DNA, corresponding to about 79 copies of the carnation haploid genome; the limit of detection and quantification of the quantitative PCR assay were estimated to be 38 and 190 copies of haploid carnation genomic DNA, respectively. Carnation samples with different contents of genetically modified components were quantified and the bias between the observed and true values of three samples were lower than the acceptance criterion (<25%) of the GMO detection method. These results indicated that these event-specific methods would be useful for the identification and quantification of the GMO carnation Moonlite.

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

CNV-seq, a new method to detect copy number variation using high-throughput sequencing.

PubMed

Xie, Chao; Tammi, Martti T

2009-03-06

DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads. Simulation of various sequencing methods with coverage between 0.1x to 8x show overall specificity between 91.7 - 99.9%, and sensitivity between 72.2 - 96.5%. We also show the results for assessment of CNV between two individual human genomes.

Effective Feature Selection for Classification of Promoter Sequences.

PubMed

K, Kouser; P G, Lavanya; Rangarajan, Lalitha; K, Acharya Kshitish

2016-01-01

Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM) features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine), KNN (K Nearest Neighbor) and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method) but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

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.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

PubMed Central

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

PubMed

Ramkissoon, Kevin R; Miller, Jennifer K; Ojha, Sunil; Watson, Douglas S; Bomar, Martha G; Galande, Amit K; Shearer, Alexander G

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

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

PubMed

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

2012-01-03

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

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

Pyrosequencing®-Based Identification of Low-Frequency Mutations Enriched Through Enhanced-ice-COLD-PCR.

PubMed

How-Kit, Alexandre; Tost, Jörg

2015-01-01

A number of molecular diagnostic assays have been developed in the last years for mutation detection. Although these methods have become increasingly sensitive, most of them are incompatible with a sequencing-based readout and require prior knowledge of the mutation present in the sample. Consequently, coamplification at low denaturation (COLD)-PCR-based methods have been developed and combine a high analytical sensitivity due to mutation enrichment in the sample with the identification of known or unknown mutations by downstream sequencing experiments. Among these methods, the recently developed Enhanced-ice-COLD-PCR appeared as the most powerful method as it outperformed the other COLD-PCR-based methods in terms of the mutation enrichment and due to the simplicity of the experimental setup of the assay. Indeed, E-ice-COLD-PCR is very versatile as it can be used on all types of PCR platforms and is applicable to different types of samples including fresh frozen, FFPE, and plasma samples. The technique relies on the incorporation of an LNA containing blocker probe in the PCR reaction followed by selective heteroduplex denaturation enabling amplification of the mutant allele while amplification of the wild-type allele is prevented. Combined with Pyrosequencing(®), which is a very quantitative high-resolution sequencing technology, E-ice-COLD-PCR can detect and identify mutations with a limit of detection down to 0.01 %.

A reference bacterial genome dataset generated on the MinION™ portable single-molecule nanopore sequencer.

PubMed

Quick, Joshua; Quinlan, Aaron R; Loman, Nicholas J

2014-01-01

The MinION™ is a new, portable single-molecule sequencer developed by Oxford Nanopore Technologies. It measures four inches in length and is powered from the USB 3.0 port of a laptop computer. The MinION™ measures the change in current resulting from DNA strands interacting with a charged protein nanopore. These measurements can then be used to deduce the underlying nucleotide sequence. We present a read dataset from whole-genome shotgun sequencing of the model organism Escherichia coli K-12 substr. MG1655 generated on a MinION™ device during the early-access MinION™ Access Program (MAP). Sequencing runs of the MinION™ are presented, one generated using R7 chemistry (released in July 2014) and one using R7.3 (released in September 2014). Base-called sequence data are provided to demonstrate the nature of data produced by the MinION™ platform and to encourage the development of customised methods for alignment, consensus and variant calling, de novo assembly and scaffolding. FAST5 files containing event data within the HDF5 container format are provided to assist with the development of improved base-calling methods.

Clustering and visualizing similarity networks of membrane proteins.

PubMed

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.

PubMed

Lane, William J; Westhoff, Connie M; Gleadall, Nicholas S; Aguad, Maria; Smeland-Wagman, Robin; Vege, Sunitha; Simmons, Daimon P; Mah, Helen H; Lebo, Matthew S; Walter, Klaudia; Soranzo, Nicole; Di Angelantonio, Emanuele; Danesh, John; Roberts, David J; Watkins, Nick A; Ouwehand, Willem H; Butterworth, Adam S; Kaufman, Richard M; Rehm, Heidi L; Silberstein, Leslie E; Green, Robert C

2018-06-01

There are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens. This whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons. We iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage). By enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine. National Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genomic signal processing methods for computation of alignment-free distances from DNA sequences.

PubMed

Borrayo, Ernesto; Mendizabal-Ruiz, E Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P; Morales, J Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments.

Winnowing DNA for Rare Sequences: Highly Specific Sequence and Methylation Based Enrichment

PubMed Central

Thompson, Jason D.; Shibahara, Gosuke; Rajan, Sweta; Pel, Joel; Marziali, Andre

2012-01-01

Rare mutations in cell populations are known to be hallmarks of many diseases and cancers. Similarly, differential DNA methylation patterns arise in rare cell populations with diagnostic potential such as fetal cells circulating in maternal blood. Unfortunately, the frequency of alleles with diagnostic potential, relative to wild-type background sequence, is often well below the frequency of errors in currently available methods for sequence analysis, including very high throughput DNA sequencing. We demonstrate a DNA preparation and purification method that through non-linear electrophoretic separation in media containing oligonucleotide probes, achieves 10,000 fold enrichment of target DNA with single nucleotide specificity, and 100 fold enrichment of unmodified methylated DNA differing from the background by the methylation of a single cytosine residue. PMID:22355378