Transcriptomic sequencing reveals a set of unique genes activated by butyrate-induced histone modification

USDA-ARS?s Scientific Manuscript database

Butyrate is a nutritional element with strong epigenetic regulatory activity as an inhibitor of histone deacetylases (HDACs). Based on the analysis of differentially expressed genes induced by butyrate in the bovine epithelial cell using deep RNA-sequencing technology (RNA-seq), a set of unique gen...

Deep ART Neural Model for Biologically Inspired Episodic Memory and Its Application to Task Performance of Robots.

PubMed

Park, Gyeong-Moon; Yoo, Yong-Ho; Kim, Deok-Hwa; Kim, Jong-Hwan; Gyeong-Moon Park; Yong-Ho Yoo; Deok-Hwa Kim; Jong-Hwan Kim; Yoo, Yong-Ho; Park, Gyeong-Moon; Kim, Jong-Hwan; Kim, Deok-Hwa

2018-06-01

Robots are expected to perform smart services and to undertake various troublesome or difficult tasks in the place of humans. Since these human-scale tasks consist of a temporal sequence of events, robots need episodic memory to store and retrieve the sequences to perform the tasks autonomously in similar situations. As episodic memory, in this paper we propose a novel Deep adaptive resonance theory (ART) neural model and apply it to the task performance of the humanoid robot, Mybot, developed in the Robot Intelligence Technology Laboratory at KAIST. Deep ART has a deep structure to learn events, episodes, and even more like daily episodes. Moreover, it can retrieve the correct episode from partial input cues robustly. To demonstrate the effectiveness and applicability of the proposed Deep ART, experiments are conducted with the humanoid robot, Mybot, for performing the three tasks of arranging toys, making cereal, and disposing of garbage.

Role of Mitochondrial Inheritance on Prostate Cancer Outcome in African American Men. Addendum

DTIC Science & Technology

2016-11-01

DNA sequencing technique developed by our collaborator using single amplicon long-range PCR that permits deep coverage (10,000-20,000X on average) of...the mitochondrial genome. We have sequenced 652 samples derived from frozen fully using this technology. The additional DNA samples derived from...paraffin embedded (FFPE) tissue were more challenging, but have now been sequenced . Mapping of DNA variants in our sequenced genomes to mitochondrial

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.

Characterization of microRNAs from goat (Capra hircus) by Solexa deep-sequencing technology.

PubMed

Ling, Y H; Ding, J P; Zhang, X D; Wang, L J; Zhang, Y H; Li, Y S; Zhang, Z J; Zhang, X R

2013-06-13

MicroRNAs (miRNAs) are an important class of small noncoding RNAs that are highly conserved in plants and animals. Many miRNAs are known to mediate a myriad of cell processes, including proliferation and differentiation, via the regulation of some transcription and signaling factors, which are closely related to muscle development and disease. In this study, small RNA cDNA libraries of Boer goats were constructed. In addition, we obtained the goat muscle miRNAs by using Solexa deep-sequencing technology and analyzed these miRNA characteristics by combining it with the bioinformatics technology. Based on Solexa sequencing and bioinformatics analysis, 562 species-conserved and 5 goat genome-specific miRNAs were identified, 322 of which exceeded 100 in the expression levels. The results of real-time quantitative polymerase chain reaction from 8 randomly selected miRNAs showed that the 8 miRNAs were expressed in goat muscle, and the expression patterns were consistent with the Solexa sequencing results. The identification and characterization of miRNAs in goat muscle provide important information on the role of miRNA regulation in muscle growth and development. These data will help to facilitate studies on the regulatory roles played by miRNAs during goat growth and development.

Detection of microRNAs in color space.

PubMed

Marco, Antonio; Griffiths-Jones, Sam

2012-02-01

Deep sequencing provides inexpensive opportunities to characterize the transcriptional diversity of known genomes. The AB SOLiD technology generates millions of short sequencing reads in color-space; that is, the raw data is a sequence of colors, where each color represents 2 nt and each nucleotide is represented by two consecutive colors. This strategy is purported to have several advantages, including increased ability to distinguish sequencing errors from polymorphisms. Several programs have been developed to map short reads to genomes in color space. However, a number of previously unexplored technical issues arise when using SOLiD technology to characterize microRNAs. Here we explore these technical difficulties. First, since the sequenced reads are longer than the biological sequences, every read is expected to contain linker fragments. The color-calling error rate increases toward the 3(') end of the read such that recognizing the linker sequence for removal becomes problematic. Second, mapping in color space may lead to the loss of the first nucleotide of each read. We propose a sequential trimming and mapping approach to map small RNAs. Using our strategy, we reanalyze three published insect small RNA deep sequencing datasets and characterize 22 new microRNAs. A bash shell script to perform the sequential trimming and mapping procedure, called SeqTrimMap, is available at: http://www.mirbase.org/tools/seqtrimmap/ antonio.marco@manchester.ac.uk Supplementary data are available at Bioinformatics online.

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.

Deep sequencing methods for protein engineering and design.

PubMed

Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora.

PubMed

Xiao, Bingbing; Niu, Xiaoxi; Han, Na; Wang, Ben; Du, Pengcheng; Na, Risu; Chen, Chen; Liao, Qinping

2016-06-02

Bacterial vaginosis (BV) is a highly prevalent disease in women, and increases the risk of pelvic inflammatory disease. It has been given wide attention because of the high recurrence rate. Traditional diagnostic methods based on microscope providing limited information on the vaginal microbiota increase the difficulty in tracing the development of the disease in bacteria resistance condition. In this study, we used deep-sequencing technology to observe dynamic variation of the vaginal microbiota at three major time points during treatment, at D0 (before treatment), D7 (stop using the antibiotics) and D30 (the 30-day follow-up visit). Sixty-five patients with BV were enrolled (48 were cured and 17 were not cured), and their bacterial composition of the vaginal microbiota was compared. Interestingly, we identified 9 patients might be recurrence. We also introduced a new measurement point of D7, although its microbiota were significantly inhabited by antibiotic and hard to be observed by traditional method. The vaginal microbiota in deep-sequencing-view present a strong correlation to the final outcome. Thus, coupled with detailed individual bioinformatics analysis and deep-sequencing technology, we may illustrate a more accurate map of vaginal microbial to BV patients, which provide a new opportunity to reduce the rate of recurrence of BV.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

PubMed

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Optimization of whole-transcriptome amplification from low cell density deep-sea microbial samples for metatranscriptomic analysis.

PubMed

Wu, Jieying; Gao, Weimin; Zhang, Weiwen; Meldrum, Deirdre R

2011-01-01

Limitation in sample quality and quantity is one of the big obstacles for applying metatranscriptomic technologies to explore gene expression and functionality of microbial communities in natural environments. In this study, several amplification methods were evaluated for whole-transcriptome amplification of deep-sea microbial samples, which are of low cell density and high impurity. The best amplification method was identified and incorporated into a complete protocol to isolate and amplify deep-sea microbial samples. In the protocol, total RNA was first isolated by a modified method combining Trizol (Invitrogen, CA) and RNeasy (QIAGEN, CA) method, amplified with a WT-Ovation™ Pico RNA Amplification System (NuGEN, CA), and then converted to double-strand DNA from single-strand cDNA with a WT-Ovation™ Exon Module (NuGEN, CA). The products from the whole-transcriptome amplification of deep-sea microbial samples were assessed first through random clone library sequencing. The BLAST search results showed that marine-based sequences are dominant in the libraries, consistent with the ecological source of the samples. The products were then used for next-generation Roche GS FLX Titanium sequencing to obtain metatranscriptome data. Preliminary analysis of the metatranscriptomic data showed good sequencing quality. Although the protocol was designed and demonstrated to be effective for deep-sea microbial samples, it should be applicable to similar samples from other extreme environments in exploring community structure and functionality of microbial communities. Copyright © 2010 Elsevier B.V. All rights reserved.

AMPLISAS: a web server for multilocus genotyping using next-generation amplicon sequencing data.

PubMed

Sebastian, Alvaro; Herdegen, Magdalena; Migalska, Magdalena; Radwan, Jacek

2016-03-01

Next-generation sequencing (NGS) technologies are revolutionizing the fields of biology and medicine as powerful tools for amplicon sequencing (AS). Using combinations of primers and barcodes, it is possible to sequence targeted genomic regions with deep coverage for hundreds, even thousands, of individuals in a single experiment. This is extremely valuable for the genotyping of gene families in which locus-specific primers are often difficult to design, such as the major histocompatibility complex (MHC). The utility of AS is, however, limited by the high intrinsic sequencing error rates of NGS technologies and other sources of error such as polymerase amplification or chimera formation. Correcting these errors requires extensive bioinformatic post-processing of NGS data. Amplicon Sequence Assignment (AMPLISAS) is a tool that performs analysis of AS results in a simple and efficient way, while offering customization options for advanced users. AMPLISAS is designed as a three-step pipeline consisting of (i) read demultiplexing, (ii) unique sequence clustering and (iii) erroneous sequence filtering. Allele sequences and frequencies are retrieved in excel spreadsheet format, making them easy to interpret. AMPLISAS performance has been successfully benchmarked against previously published genotyped MHC data sets obtained with various NGS technologies. © 2015 John Wiley & Sons Ltd.

Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora

PubMed Central

Xiao, Bingbing; Niu, Xiaoxi; Han, Na; Wang, Ben; Du, Pengcheng; Na, Risu; Chen, Chen; Liao, Qinping

2016-01-01

Bacterial vaginosis (BV) is a highly prevalent disease in women, and increases the risk of pelvic inflammatory disease. It has been given wide attention because of the high recurrence rate. Traditional diagnostic methods based on microscope providing limited information on the vaginal microbiota increase the difficulty in tracing the development of the disease in bacteria resistance condition. In this study, we used deep-sequencing technology to observe dynamic variation of the vaginal microbiota at three major time points during treatment, at D0 (before treatment), D7 (stop using the antibiotics) and D30 (the 30-day follow-up visit). Sixty-five patients with BV were enrolled (48 were cured and 17 were not cured), and their bacterial composition of the vaginal microbiota was compared. Interestingly, we identified 9 patients might be recurrence. We also introduced a new measurement point of D7, although its microbiota were significantly inhabited by antibiotic and hard to be observed by traditional method. The vaginal microbiota in deep-sequencing-view present a strong correlation to the final outcome. Thus, coupled with detailed individual bioinformatics analysis and deep-sequencing technology, we may illustrate a more accurate map of vaginal microbial to BV patients, which provide a new opportunity to reduce the rate of recurrence of BV. PMID:27253522

GenomeGems: evaluation of genetic variability from deep sequencing data

PubMed Central

2012-01-01

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

Sequence-of-events-driven automation of the deep space network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Sequence-of-Events-Driven Automation of the Deep Space Network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Deep sequencing in library selection projects: what insight does it bring?

PubMed

Glanville, J; D'Angelo, S; Khan, T A; Reddy, S T; Naranjo, L; Ferrara, F; Bradbury, A R M

2015-08-01

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deep sequencing in library selection projects: what insight does it bring?

PubMed Central

Glanville, J; D’Angelo, S; Khan, T.A.; Reddy, S. T.; Naranjo, L.; Ferrara, F.; Bradbury, A.R.M.

2015-01-01

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology. PMID:26451649

Cancer Deep Phenotyping Extraction from Electronic Medical Records | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

As sequencing costs continue to decline, a torrent of cancer genomic data is looming. Very soon, our ability to deeply investigate the cancer genome will outpace our ability to correlate these changes with the phenotypes that they produce. We propose the advanced development and extension of a software platform for performing deep phenotype extraction directly from clinical text of cancer patients, with the goal of enabling translational cancer research and precision medicine.

Iterative Correction of Reference Nucleotides (iCORN) using second generation sequencing technology.

PubMed

Otto, Thomas D; Sanders, Mandy; Berriman, Matthew; Newbold, Chris

2010-07-15

The accuracy of reference genomes is important for downstream analysis but a low error rate requires expensive manual interrogation of the sequence. Here, we describe a novel algorithm (Iterative Correction of Reference Nucleotides) that iteratively aligns deep coverage of short sequencing reads to correct errors in reference genome sequences and evaluate their accuracy. Using Plasmodium falciparum (81% A + T content) as an extreme example, we show that the algorithm is highly accurate and corrects over 2000 errors in the reference sequence. We give examples of its application to numerous other eukaryotic and prokaryotic genomes and suggest additional applications. The software is available at http://icorn.sourceforge.net

DSAP: deep-sequencing small RNA analysis pipeline.

PubMed

Huang, Po-Jung; Liu, Yi-Chung; Lee, Chi-Ching; Lin, Wei-Chen; Gan, Richie Ruei-Chi; Lyu, Ping-Chiang; Tang, Petrus

2010-07-01

DSAP is an automated multiple-task web service designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. DSAP uses a tab-delimited file as an input format, which holds the unique sequence reads (tags) and their corresponding number of copies generated by the Solexa sequencing platform. The input data will go through four analysis steps in DSAP: (i) cleanup: removal of adaptors and poly-A/T/C/G/N nucleotides; (ii) clustering: grouping of cleaned sequence tags into unique sequence clusters; (iii) non-coding RNA (ncRNA) matching: sequence homology mapping against a transcribed sequence library from the ncRNA database Rfam (http://rfam.sanger.ac.uk/); and (iv) known miRNA matching: detection of known miRNAs in miRBase (http://www.mirbase.org/) based on sequence homology. The expression levels corresponding to matched ncRNAs and miRNAs are summarized in multi-color clickable bar charts linked to external databases. DSAP is also capable of displaying miRNA expression levels from different jobs using a log(2)-scaled color matrix. Furthermore, a cross-species comparative function is also provided to show the distribution of identified miRNAs in different species as deposited in miRBase. DSAP is available at http://dsap.cgu.edu.tw.

Construction of Pseudomolecule Sequences of the aus Rice Cultivar Kasalath for Comparative Genomics of Asian Cultivated Rice

PubMed Central

Sakai, Hiroaki; Kanamori, Hiroyuki; Arai-Kichise, Yuko; Shibata-Hatta, Mari; Ebana, Kaworu; Oono, Youko; Kurita, Kanako; Fujisawa, Hiroko; Katagiri, Satoshi; Mukai, Yoshiyuki; Hamada, Masao; Itoh, Takeshi; Matsumoto, Takashi; Katayose, Yuichi; Wakasa, Kyo; Yano, Masahiro; Wu, Jianzhong

2014-01-01

Having a deep genetic structure evolved during its domestication and adaptation, the Asian cultivated rice (Oryza sativa) displays considerable physiological and morphological variations. Here, we describe deep whole-genome sequencing of the aus rice cultivar Kasalath by using the advanced next-generation sequencing (NGS) technologies to gain a better understanding of the sequence and structural changes among highly differentiated cultivars. The de novo assembled Kasalath sequences represented 91.1% (330.55 Mb) of the genome and contained 35 139 expressed loci annotated by RNA-Seq analysis. We detected 2 787 250 single-nucleotide polymorphisms (SNPs) and 7393 large insertion/deletion (indel) sites (>100 bp) between Kasalath and Nipponbare, and 2 216 251 SNPs and 3780 large indels between Kasalath and 93-11. Extensive comparison of the gene contents among these cultivars revealed similar rates of gene gain and loss. We detected at least 7.39 Mb of inserted sequences and 40.75 Mb of unmapped sequences in the Kasalath genome in comparison with the Nipponbare reference genome. Mapping of the publicly available NGS short reads from 50 rice accessions proved the necessity and the value of using the Kasalath whole-genome sequence as an additional reference to capture the sequence polymorphisms that cannot be discovered by using the Nipponbare sequence alone. PMID:24578372

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Novel method for high-throughput colony PCR screening in nanoliter-reactors

PubMed Central

Walser, Marcel; Pellaux, Rene; Meyer, Andreas; Bechtold, Matthias; Vanderschuren, Herve; Reinhardt, Richard; Magyar, Joseph; Panke, Sven; Held, Martin

2009-01-01

We introduce a technology for the rapid identification and sequencing of conserved DNA elements employing a novel suspension array based on nanoliter (nl)-reactors made from alginate. The reactors have a volume of 35 nl and serve as reaction compartments during monoseptic growth of microbial library clones, colony lysis, thermocycling and screening for sequence motifs via semi-quantitative fluorescence analyses. nl-Reactors were kept in suspension during all high-throughput steps which allowed performing the protocol in a highly space-effective fashion and at negligible expenses of consumables and reagents. As a first application, 11 high-quality microsatellites for polymorphism studies in cassava were isolated and sequenced out of a library of 20 000 clones in 2 days. The technology is widely scalable and we envision that throughputs for nl-reactor based screenings can be increased up to 100 000 and more samples per day thereby efficiently complementing protocols based on established deep-sequencing technologies. PMID:19282448

MicroRNAs play critical roles during plant development and in response to abiotic stresses.

PubMed

de Lima, Júlio César; Loss-Morais, Guilherme; Margis, Rogerio

2012-12-01

MicroRNAs (miRNAs) have been identified as key molecules in regulatory networks. The fine-tuning role of miRNAs in addition to the regulatory role of transcription factors has shown that molecular events during development are tightly regulated. In addition, several miRNAs play crucial roles in the response to abiotic stress induced by drought, salinity, low temperatures, and metals such as aluminium. Interestingly, several miRNAs have overlapping roles with regard to development, stress responses, and nutrient homeostasis. Moreover, in response to the same abiotic stresses, different expression patterns for some conserved miRNA families among different plant species revealed different metabolic adjustments. The use of deep sequencing technologies for the characterisation of miRNA frequency and the identification of new miRNAs adds complexity to regulatory networks in plants. In this review, we consider the regulatory role of miRNAs in plant development and abiotic stresses, as well as the impact of deep sequencing technologies on the generation of miRNA data.

De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

PubMed

Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

2016-01-01

Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

Studies of a biochemical factory: tomato trichome deep expressed sequence tag sequencing and proteomics.

PubMed

Schilmiller, Anthony L; Miner, Dennis P; Larson, Matthew; McDowell, Eric; Gang, David R; Wilkerson, Curtis; Last, Robert L

2010-07-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.

Studies of a Biochemical Factory: Tomato Trichome Deep Expressed Sequence Tag Sequencing and Proteomics1[W][OA

PubMed Central

Schilmiller, Anthony L.; Miner, Dennis P.; Larson, Matthew; McDowell, Eric; Gang, David R.; Wilkerson, Curtis; Last, Robert L.

2010-01-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces β-caryophyllene and α-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells. PMID:20431087

Noninvasive Prenatal Paternity Testing (NIPAT) through Maternal Plasma DNA Sequencing: A Pilot Study.

PubMed

Jiang, Haojun; Xie, Yifan; Li, Xuchao; Ge, Huijuan; Deng, Yongqiang; Mu, Haofang; Feng, Xiaoli; Yin, Lu; Du, Zhou; Chen, Fang; He, Nongyue

2016-01-01

Short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) have been already used to perform noninvasive prenatal paternity testing from maternal plasma DNA. The frequently used technologies were PCR followed by capillary electrophoresis and SNP typing array, respectively. Here, we developed a noninvasive prenatal paternity testing (NIPAT) based on SNP typing with maternal plasma DNA sequencing. We evaluated the influence factors (minor allele frequency (MAF), the number of total SNP, fetal fraction and effective sequencing depth) and designed three different selective SNP panels in order to verify the performance in clinical cases. Combining targeted deep sequencing of selective SNP and informative bioinformatics pipeline, we calculated the combined paternity index (CPI) of 17 cases to determine paternity. Sequencing-based NIPAT results fully agreed with invasive prenatal paternity test using STR multiplex system. Our study here proved that the maternal plasma DNA sequencing-based technology is feasible and accurate in determining paternity, which may provide an alternative in forensic application in the future.

Deep-sequencing to resolve complex diversity of apicomplexan parasites in platypuses and echidnas: Proof of principle for wildlife disease investigation.

PubMed

Šlapeta, Jan; Saverimuttu, Stefan; Vogelnest, Larry; Sangster, Cheryl; Hulst, Frances; Rose, Karrie; Thompson, Paul; Whittington, Richard

2017-11-01

The short-beaked echidna (Tachyglossus aculeatus) and the platypus (Ornithorhynchus anatinus) are iconic egg-laying monotremes (Mammalia: Monotremata) from Australasia. The aim of this study was to demonstrate the utility of diversity profiles in disease investigations of monotremes. Using small subunit (18S) rDNA amplicon deep-sequencing we demonstrated the presence of apicomplexan parasites and confirmed by direct and cloned amplicon gene sequencing Theileria ornithorhynchi, Theileria tachyglossi, Eimeria echidnae and Cryptosporidium fayeri. Using a combination of samples from healthy and diseased animals, we show a close evolutionary relationship between species of coccidia (Eimeria) and piroplasms (Theileria) from the echidna and platypus. The presence of E. echidnae was demonstrated in faeces and tissues affected by disseminated coccidiosis. Moreover, the presence of E. echidnae DNA in the blood of echidnas was associated with atoxoplasma-like stages in white blood cells, suggesting Hepatozoon tachyglossi blood stages are disseminated E. echidnae stages. These next-generation DNA sequencing technologies are suited to material and organisms that have not been previously characterised and for which the material is scarce. The deep sequencing approach supports traditional diagnostic methods, including microscopy, clinical pathology and histopathology, to better define the status quo. This approach is particularly suitable for wildlife disease investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep sequencing and flow cytometric characterization of expanded effector memory CD8+CD57+ T cells frequently reveals T-cell receptor Vβ oligoclonality and CDR3 homology in acquired aplastic anemia.

PubMed

Giudice, Valentina; Feng, Xingmin; Lin, Zenghua; Hu, Wei; Zhang, Fanmao; Qiao, Wangmin; Ibanez, Maria Del Pilar Fernandez; Rios, Olga; Young, Neal S

2018-05-01

Oligoclonal expansion of CD8 + CD28 - lymphocytes has been considered indirect evidence for a pathogenic immune response in acquired aplastic anemia. A subset of CD8 + CD28 - cells with CD57 expression, termed effector memory cells, is expanded in several immune-mediated diseases and may have a role in immune surveillance. We hypothesized that effector memory CD8 + CD28 - CD57 + cells may drive aberrant oligoclonal expansion in aplastic anemia. We found CD8 + CD57 + cells frequently expanded in the blood of aplastic anemia patients, with oligoclonal characteristics by flow cytometric Vβ usage analysis: skewing in 1-5 Vβ families and frequencies of immunodominant clones ranging from 1.98% to 66.5%. Oligoclonal characteristics were also observed in total CD8 + cells from aplastic anemia patients with CD8 + CD57 + cell expansion by T-cell receptor deep sequencing, as well as the presence of 1-3 immunodominant clones. Oligoclonality was confirmed by T-cell receptor repertoire deep sequencing of enriched CD8 + CD57 + cells, which also showed decreased diversity compared to total CD4 + and CD8 + cell pools. From analysis of complementarity-determining region 3 sequences in the CD8 + cell pool, a total of 29 sequences were shared between patients and controls, but these sequences were highly expressed in aplastic anemia subjects and also present in their immunodominant clones. In summary, expansion of effector memory CD8 + T cells is frequent in aplastic anemia and mirrors Vβ oligoclonal expansion. Flow cytometric Vβ usage analysis combined with deep sequencing technologies allows high resolution characterization of the T-cell receptor repertoire, and might represent a useful tool in the diagnosis and periodic evaluation of aplastic anemia patients. (Registered at clinicaltrials.gov identifiers: 00001620, 01623167, 00001397, 00071045, 00081523, 00961064 ). Copyright © 2018 Ferrata Storti Foundation.

Proteome-wide Identification of Novel Ceramide-binding Proteins by Yeast Surface cDNA Display and Deep Sequencing.

PubMed

Bidlingmaier, Scott; Ha, Kevin; Lee, Nam-Kyung; Su, Yang; Liu, Bin

2016-04-01

Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ∼60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Evidence for a persistent microbial seed bank throughout the global ocean

PubMed Central

Gibbons, Sean M.; Caporaso, J. Gregory; Pirrung, Meg; Field, Dawn; Knight, Rob; Gilbert, Jack A.

2013-01-01

Do bacterial taxa demonstrate clear endemism, like macroorganisms, or can one site’s bacterial community recapture the total phylogenetic diversity of the world’s oceans? Here we compare a deep bacterial community characterization from one site in the English Channel (L4-DeepSeq) with 356 datasets from the International Census of Marine Microbes (ICoMM) taken from around the globe (ranging from marine pelagic and sediment samples to sponge-associated environments). At the L4-DeepSeq site, increasing sequencing depth uncovers greater phylogenetic overlap with the global ICoMM data. This site contained 31.7–66.2% of operational taxonomic units identified in a given ICoMM biome. Extrapolation of this overlap suggests that 1.93 × 1011 sequences from the L4 site would capture all ICoMM bacterial phylogenetic diversity. Current technology trends suggest this limit may be attainable within 3 y. These results strongly suggest the marine biosphere maintains a previously undetected, persistent microbial seed bank. PMID:23487761

High-throughput sequencing and analysis of the gill tissue transcriptome from the deep-sea hydrothermal vent mussel Bathymodiolus azoricus

PubMed Central

2010-01-01

Background Bathymodiolus azoricus is a deep-sea hydrothermal vent mussel found in association with large faunal communities living in chemosynthetic environments at the bottom of the sea floor near the Azores Islands. Investigation of the exceptional physiological reactions that vent mussels have adopted in their habitat, including responses to environmental microbes, remains a difficult challenge for deep-sea biologists. In an attempt to reveal genes potentially involved in the deep-sea mussel innate immunity we carried out a high-throughput sequence analysis of freshly collected B. azoricus transcriptome using gills tissues as the primary source of immune transcripts given its strategic role in filtering the surrounding waterborne potentially infectious microorganisms. Additionally, a substantial EST data set was produced and from which a comprehensive collection of genes coding for putative proteins was organized in a dedicated database, "DeepSeaVent" the first deep-sea vent animal transcriptome database based on the 454 pyrosequencing technology. Results A normalized cDNA library from gills tissue was sequenced in a full 454 GS-FLX run, producing 778,996 sequencing reads. Assembly of the high quality reads resulted in 75,407 contigs of which 3,071 were singletons. A total of 39,425 transcripts were conceptually translated into amino-sequences of which 22,023 matched known proteins in the NCBI non-redundant protein database, 15,839 revealed conserved protein domains through InterPro functional classification and 9,584 were assigned with Gene Ontology terms. Queries conducted within the database enabled the identification of genes putatively involved in immune and inflammatory reactions which had not been previously evidenced in the vent mussel. Their physical counterpart was confirmed by semi-quantitative quantitative Reverse-Transcription-Polymerase Chain Reactions (RT-PCR) and their RNA transcription level by quantitative PCR (qPCR) experiments. Conclusions We have established the first tissue transcriptional analysis of a deep-sea hydrothermal vent animal and generated a searchable catalog of genes that provides a direct method of identifying and retrieving vast numbers of novel coding sequences which can be applied in gene expression profiling experiments from a non-conventional model organism. This provides the most comprehensive sequence resource for identifying novel genes currently available for a deep-sea vent organism, in particular, genes putatively involved in immune and inflammatory reactions in vent mussels. The characterization of the B. azoricus transcriptome will facilitate research into biological processes underlying physiological adaptations to hydrothermal vent environments and will provide a basis for expanding our understanding of genes putatively involved in adaptations processes during post-capture long term acclimatization experiments, at "sea-level" conditions, using B. azoricus as a model organism. PMID:20937131

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

PubMed

Yuan, Yuchen; Shi, Yi; Li, Changyang; Kim, Jinman; Cai, Weidong; Han, Zeguang; Feng, David Dagan

2016-12-23

With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types.

De novo characterization of Lentinula edodes C(91-3) transcriptome by deep Solexa sequencing.

PubMed

Zhong, Mintao; Liu, Ben; Wang, Xiaoli; Liu, Lei; Lun, Yongzhi; Li, Xingyun; Ning, Anhong; Cao, Jing; Huang, Min

2013-02-01

Lentinula edodes, has been utilized as food, as well as, in popular medicine, moreover, its extract isolated from its mycelium and fruiting body have shown several therapeutic properties. Yet little is understood about its genes involved in these properties, and the absence of L.edodes genomes has been a barrier to the development of functional genomics research. However, high throughput sequencing technologies are now being widely applied to non-model species. To facilitate research on L.edodes, we leveraged Solexa sequencing technology in de novo assembly of L.edodes C(91-3) transcriptome. In a single run, we produced more than 57 million sequencing reads. These reads were assembled into 28,923 unigene sequences (mean size=689bp) including 18,120 unigenes with coding sequence (CDS). Based on similarity search with known proteins, assembled unigene sequences were annotated with gene descriptions, gene ontology (GO) and clusters of orthologous group (COG) terms. Our data provides the first comprehensive sequence resource available for functional genomics studies in L.edodes, and demonstrates the utility of Illumina/Solexa sequencing for de novo transcriptome characterization and gene discovery in a non-model mushroom. Copyright © 2012 Elsevier Inc. All rights reserved.

Deep Sequencing Reveals the Complete Genome and Evidence for Transcriptional Activity of the First Virus-Like Sequences Identified in Aristotelia chilensis (Maqui Berry)

PubMed Central

Villacreses, Javier; Rojas-Herrera, Marcelo; Sánchez, Carolina; Hewstone, Nicole; Undurraga, Soledad F.; Alzate, Juan F.; Manque, Patricio; Maracaja-Coutinho, Vinicius; Polanco, Victor

2015-01-01

Here, we report the genome sequence and evidence for transcriptional activity of a virus-like element in the native Chilean berry tree Aristotelia chilensis. We propose to name the endogenous sequence as Aristotelia chilensis Virus 1 (AcV1). High-throughput sequencing of the genome of this tree uncovered an endogenous viral element, with a size of 7122 bp, corresponding to the complete genome of AcV1. Its sequence contains three open reading frames (ORFs): ORFs 1 and 2 shares 66%–73% amino acid similarity with members of the Caulimoviridae virus family, especially the Petunia vein clearing virus (PVCV), Petuvirus genus. ORF1 encodes a movement protein (MP); ORF2 a Reverse Transcriptase (RT) and a Ribonuclease H (RNase H) domain; and ORF3 showed no amino acid sequence similarity with any other known virus proteins. Analogous to other known endogenous pararetrovirus sequences (EPRVs), AcV1 is integrated in the genome of Maqui Berry and showed low viral transcriptional activity, which was detected by deep sequencing technology (DNA and RNA-seq). Phylogenetic analysis of AcV1 and other pararetroviruses revealed a closer resemblance with Petuvirus. Overall, our data suggests that AcV1 could be a new member of Caulimoviridae family, genus Petuvirus, and the first evidence of this kind of virus in a fruit plant. PMID:25855242

A Statistical Guide to the Design of Deep Mutational Scanning Experiments

PubMed Central

Matuszewski, Sebastian; Hildebrandt, Marcel E.; Ghenu, Ana-Hermina; Jensen, Jeffrey D.; Bank, Claudia

2016-01-01

The characterization of the distribution of mutational effects is a key goal in evolutionary biology. Recently developed deep-sequencing approaches allow for accurate and simultaneous estimation of the fitness effects of hundreds of engineered mutations by monitoring their relative abundance across time points in a single bulk competition. Naturally, the achievable resolution of the estimated fitness effects depends on the specific experimental setup, the organism and type of mutations studied, and the sequencing technology utilized, among other factors. By means of analytical approximations and simulations, we provide guidelines for optimizing time-sampled deep-sequencing bulk competition experiments, focusing on the number of mutants, the sequencing depth, and the number of sampled time points. Our analytical results show that sampling more time points together with extending the duration of the experiment improves the achievable precision disproportionately compared with increasing the sequencing depth or reducing the number of competing mutants. Even if the duration of the experiment is fixed, sampling more time points and clustering these at the beginning and the end of the experiment increase experimental power and allow for efficient and precise assessment of the entire range of selection coefficients. Finally, we provide a formula for calculating the 95%-confidence interval for the measurement error estimate, which we implement as an interactive web tool. This allows for quantification of the maximum expected a priori precision of the experimental setup, as well as for a statistical threshold for determining deviations from neutrality for specific selection coefficient estimates. PMID:27412710

Poly(A)-tag deep sequencing data processing to extract poly(A) sites.

PubMed

Wu, Xiaohui; Ji, Guoli; Li, Qingshun Quinn

2015-01-01

Polyadenylation [poly(A)] is an essential posttranscriptional processing step in the maturation of eukaryotic mRNA. The advent of next-generation sequencing (NGS) technology has offered feasible means to generate large-scale data and new opportunities for intensive study of polyadenylation, particularly deep sequencing of the transcriptome targeting the junction of 3'-UTR and the poly(A) tail of the transcript. To take advantage of this unprecedented amount of data, we present an automated workflow to identify polyadenylation sites by integrating NGS data cleaning, processing, mapping, normalizing, and clustering. In this pipeline, a series of Perl scripts are seamlessly integrated to iteratively map the single- or paired-end sequences to the reference genome. After mapping, the poly(A) tags (PATs) at the same genome coordinate are grouped into one cleavage site, and the internal priming artifacts removed. Then the ambiguous region is introduced to parse the genome annotation for cleavage site clustering. Finally, cleavage sites within a close range of 24 nucleotides and from different samples can be clustered into poly(A) clusters. This procedure could be used to identify thousands of reliable poly(A) clusters from millions of NGS sequences in different tissues or treatments.

Making sense of deep sequencing

PubMed Central

Goldman, D.; Domschke, K.

2016-01-01

This review, the first of an occasional series, tries to make sense of the concepts and uses of deep sequencing of polynucleic acids (DNA and RNA). Deep sequencing, synonymous with next-generation sequencing, high-throughput sequencing and massively parallel sequencing, includes whole genome sequencing but is more often and diversely applied to specific parts of the genome captured in different ways, for example the highly expressed portion of the genome known as the exome and portions of the genome that are epigenetically marked either by DNA methylation, the binding of proteins including histones, or that are in different configurations and thus more or less accessible to enzymes that cleave DNA. Deep sequencing of RNA (RNASeq) reverse-transcribed to complementary DNA is invaluable for measuring RNA expression and detecting changes in RNA structure. Important concepts in deep sequencing include the length and depth of sequence reads, mapping and assembly of reads, sequencing error, haplotypes, and the propensity of deep sequencing, as with other types of ‘big data’, to generate large numbers of errors, requiring monitoring for methodologic biases and strategies for replication and validation. Deep sequencing yields a unique genetic fingerprint that can be used to identify a person, and a trove of predictors of genetic medical diseases. Deep sequencing to identify epigenetic events including changes in DNA methylation and RNA expression can reveal the history and impact of environmental exposures. Because of the power of sequencing to identify and deliver biomedically significant information about a person and their blood relatives, it creates ethical dilemmas and practical challenges in research and clinical care, for example the decision and procedures to report incidental findings that will increasingly and frequently be discovered. PMID:24925306

Diversity of viruses detected by deep sequencing in pigs from a common background

USDA-ARS?s Scientific Manuscript database

The trial was successful in identifying a number of viruses in the feces of the pigs demonstrating the application of this technology to determine the background noise in the animals. The findings in this study are similar to the fecal virome in pigs from a typical commercial swine farm in the Unite...

Plastid Phylogenomics Resolve Deep Relationships among Eupolypod II Ferns with Rapid Radiation and Rate Heterogeneity

PubMed Central

Wei, Ran; Yan, Yue-Hong; Harris, AJ; Kang, Jong-Soo; Shen, Hui; Zhang, Xian-Chun

2017-01-01

Abstract The eupolypods II ferns represent a classic case of evolutionary radiation and, simultaneously, exhibit high substitution rate heterogeneity. These factors have been proposed to contribute to the contentious resolutions among clades within this fern group in multilocus phylogenetic studies. We investigated the deep phylogenetic relationships of eupolypod II ferns by sampling all major families and using 40 plastid genomes, or plastomes, of which 33 were newly sequenced with next-generation sequencing technology. We performed model-based analyses to evaluate the diversity of molecular evolutionary rates for these ferns. Our plastome data, with more than 26,000 informative characters, yielded good resolution for deep relationships within eupolypods II and unambiguously clarified the position of Rhachidosoraceae and the monophyly of Athyriaceae. Results of rate heterogeneity analysis revealed approximately 33 significant rate shifts in eupolypod II ferns, with the most heterogeneous rates (both accelerations and decelerations) occurring in two phylogenetically difficult lineages, that is, the Rhachidosoraceae–Aspleniaceae and Athyriaceae clades. These observations support the hypothesis that rate heterogeneity has previously constrained the deep phylogenetic resolution in eupolypods II. According to the plastome data, we propose that 14 chloroplast markers are particularly phylogenetically informative for eupolypods II both at the familial and generic levels. Our study demonstrates the power of a character-rich plastome data set and high-throughput sequencing for resolving the recalcitrant lineages, which have undergone rapid evolutionary radiation and dramatic changes in substitution rates. PMID:28854625

Same-day genomic and epigenomic diagnosis of brain tumors using real-time nanopore sequencing.

PubMed

Euskirchen, Philipp; Bielle, Franck; Labreche, Karim; Kloosterman, Wigard P; Rosenberg, Shai; Daniau, Mailys; Schmitt, Charlotte; Masliah-Planchon, Julien; Bourdeaut, Franck; Dehais, Caroline; Marie, Yannick; Delattre, Jean-Yves; Idbaih, Ahmed

2017-11-01

Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis, and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous system tumors, the current World Health Organization classification explicitly demands molecular testing, e.g., for 1p/19q-codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A, and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within 6 h and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas, and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2, and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations, and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource-restricted settings.

A Statistical Guide to the Design of Deep Mutational Scanning Experiments.

PubMed

Matuszewski, Sebastian; Hildebrandt, Marcel E; Ghenu, Ana-Hermina; Jensen, Jeffrey D; Bank, Claudia

2016-09-01

The characterization of the distribution of mutational effects is a key goal in evolutionary biology. Recently developed deep-sequencing approaches allow for accurate and simultaneous estimation of the fitness effects of hundreds of engineered mutations by monitoring their relative abundance across time points in a single bulk competition. Naturally, the achievable resolution of the estimated fitness effects depends on the specific experimental setup, the organism and type of mutations studied, and the sequencing technology utilized, among other factors. By means of analytical approximations and simulations, we provide guidelines for optimizing time-sampled deep-sequencing bulk competition experiments, focusing on the number of mutants, the sequencing depth, and the number of sampled time points. Our analytical results show that sampling more time points together with extending the duration of the experiment improves the achievable precision disproportionately compared with increasing the sequencing depth or reducing the number of competing mutants. Even if the duration of the experiment is fixed, sampling more time points and clustering these at the beginning and the end of the experiment increase experimental power and allow for efficient and precise assessment of the entire range of selection coefficients. Finally, we provide a formula for calculating the 95%-confidence interval for the measurement error estimate, which we implement as an interactive web tool. This allows for quantification of the maximum expected a priori precision of the experimental setup, as well as for a statistical threshold for determining deviations from neutrality for specific selection coefficient estimates. Copyright © 2016 by the Genetics Society of America.

Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

2016-10-01

The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

Metagenome sequencing and 98 microbial genomes from Juan de Fuca Ridge flank subsurface fluids

NASA Astrophysics Data System (ADS)

Jungbluth, Sean P.; Amend, Jan P.; Rappé, Michael S.

2017-03-01

The global deep subsurface biosphere is one of the largest reservoirs for microbial life on our planet. This study takes advantage of new sampling technologies and couples them with improvements to DNA sequencing and associated informatics tools to reconstruct the genomes of uncultivated Bacteria and Archaea from fluids collected deep within the Juan de Fuca Ridge subseafloor. Here, we generated two metagenomes from borehole observatories located 311 meters apart and, using binning tools, retrieved 98 genomes from metagenomes (GFMs). Of the GFMs, 31 were estimated to be >90% complete, while an additional 17 were >70% complete. Phylogenomic analysis revealed 53 bacterial and 45 archaeal GFMs, of which nearly all were distantly related to known cultivated isolates. In the GFMs, abundant Bacteria included Chloroflexi, Nitrospirae, Acetothermia (OP1), EM3, Aminicenantes (OP8), Gammaproteobacteria, and Deltaproteobacteria, while abundant Archaea included Archaeoglobi, Bathyarchaeota (MCG), and Marine Benthic Group E (MBG-E). These data are the first GFMs reconstructed from the deep basaltic subseafloor biosphere, and provide a dataset available for further interrogation.

Metagenome sequencing and 98 microbial genomes from Juan de Fuca Ridge flank subsurface fluids.

PubMed

Jungbluth, Sean P; Amend, Jan P; Rappé, Michael S

2017-03-28

The global deep subsurface biosphere is one of the largest reservoirs for microbial life on our planet. This study takes advantage of new sampling technologies and couples them with improvements to DNA sequencing and associated informatics tools to reconstruct the genomes of uncultivated Bacteria and Archaea from fluids collected deep within the Juan de Fuca Ridge subseafloor. Here, we generated two metagenomes from borehole observatories located 311 meters apart and, using binning tools, retrieved 98 genomes from metagenomes (GFMs). Of the GFMs, 31 were estimated to be >90% complete, while an additional 17 were >70% complete. Phylogenomic analysis revealed 53 bacterial and 45 archaeal GFMs, of which nearly all were distantly related to known cultivated isolates. In the GFMs, abundant Bacteria included Chloroflexi, Nitrospirae, Acetothermia (OP1), EM3, Aminicenantes (OP8), Gammaproteobacteria, and Deltaproteobacteria, while abundant Archaea included Archaeoglobi, Bathyarchaeota (MCG), and Marine Benthic Group E (MBG-E). These data are the first GFMs reconstructed from the deep basaltic subseafloor biosphere, and provide a dataset available for further interrogation.

Metagenome sequencing and 98 microbial genomes from Juan de Fuca Ridge flank subsurface fluids

PubMed Central

Jungbluth, Sean P.; Amend, Jan P.; Rappé, Michael S.

2017-01-01

The global deep subsurface biosphere is one of the largest reservoirs for microbial life on our planet. This study takes advantage of new sampling technologies and couples them with improvements to DNA sequencing and associated informatics tools to reconstruct the genomes of uncultivated Bacteria and Archaea from fluids collected deep within the Juan de Fuca Ridge subseafloor. Here, we generated two metagenomes from borehole observatories located 311 meters apart and, using binning tools, retrieved 98 genomes from metagenomes (GFMs). Of the GFMs, 31 were estimated to be >90% complete, while an additional 17 were >70% complete. Phylogenomic analysis revealed 53 bacterial and 45 archaeal GFMs, of which nearly all were distantly related to known cultivated isolates. In the GFMs, abundant Bacteria included Chloroflexi, Nitrospirae, Acetothermia (OP1), EM3, Aminicenantes (OP8), Gammaproteobacteria, and Deltaproteobacteria, while abundant Archaea included Archaeoglobi, Bathyarchaeota (MCG), and Marine Benthic Group E (MBG-E). These data are the first GFMs reconstructed from the deep basaltic subseafloor biosphere, and provide a dataset available for further interrogation. PMID:28350381

Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus.

PubMed

Zhang, Yan; An, Lin; Xu, Jie; Zhang, Bo; Zheng, W Jim; Hu, Ming; Tang, Jijun; Yue, Feng

2018-02-21

Although Hi-C technology is one of the most popular tools for studying 3D genome organization, due to sequencing cost, the resolution of most Hi-C datasets are coarse and cannot be used to link distal regulatory elements to their target genes. Here we develop HiCPlus, a computational approach based on deep convolutional neural network, to infer high-resolution Hi-C interaction matrices from low-resolution Hi-C data. We demonstrate that HiCPlus can impute interaction matrices highly similar to the original ones, while only using 1/16 of the original sequencing reads. We show that the models learned from one cell type can be applied to make predictions in other cell or tissue types. Our work not only provides a computational framework to enhance Hi-C data resolution but also reveals features underlying the formation of 3D chromatin interactions.

The salt-responsive transcriptome of chickpea roots and nodules via deepSuperSAGE

PubMed Central

2011-01-01

Background The combination of high-throughput transcript profiling and next-generation sequencing technologies is a prerequisite for genome-wide comprehensive transcriptome analysis. Our recent innovation of deepSuperSAGE is based on an advanced SuperSAGE protocol and its combination with massively parallel pyrosequencing on Roche's 454 sequencing platform. As a demonstration of the power of this combination, we have chosen the salt stress transcriptomes of roots and nodules of the third most important legume crop chickpea (Cicer arietinum L.). While our report is more technology-oriented, it nevertheless addresses a major world-wide problem for crops generally: high salinity. Together with low temperatures and water stress, high salinity is responsible for crop losses of millions of tons of various legume (and other) crops. Continuously deteriorating environmental conditions will combine with salinity stress to further compromise crop yields. As a good example for such stress-exposed crop plants, we started to characterize salt stress responses of chickpeas on the transcriptome level. Results We used deepSuperSAGE to detect early global transcriptome changes in salt-stressed chickpea. The salt stress responses of 86,919 transcripts representing 17,918 unique 26 bp deepSuperSAGE tags (UniTags) from roots of the salt-tolerant variety INRAT-93 two hours after treatment with 25 mM NaCl were characterized. Additionally, the expression of 57,281 transcripts representing 13,115 UniTags was monitored in nodules of the same plants. From a total of 144,200 analyzed 26 bp tags in roots and nodules together, 21,401 unique transcripts were identified. Of these, only 363 and 106 specific transcripts, respectively, were commonly up- or down-regulated (>3.0-fold) under salt stress in both organs, witnessing a differential organ-specific response to stress. Profiting from recent pioneer works on massive cDNA sequencing in chickpea, more than 9,400 UniTags were able to be linked to UniProt entries. Additionally, gene ontology (GO) categories over-representation analysis enabled to filter out enriched biological processes among the differentially expressed UniTags. Subsequently, the gathered information was further cross-checked with stress-related pathways. From several filtered pathways, here we focus exemplarily on transcripts associated with the generation and scavenging of reactive oxygen species (ROS), as well as on transcripts involved in Na+ homeostasis. Although both processes are already very well characterized in other plants, the information generated in the present work is of high value. Information on expression profiles and sequence similarity for several hundreds of transcripts of potential interest is now available. Conclusions This report demonstrates, that the combination of the high-throughput transcriptome profiling technology SuperSAGE with one of the next-generation sequencing platforms allows deep insights into the first molecular reactions of a plant exposed to salinity. Cross validation with recent reports enriched the information about the salt stress dynamics of more than 9,000 chickpea ESTs, and enlarged their pool of alternative transcripts isoforms. As an example for the high resolution of the employed technology that we coin deepSuperSAGE, we demonstrate that ROS-scavenging and -generating pathways undergo strong global transcriptome changes in chickpea roots and nodules already 2 hours after onset of moderate salt stress (25 mM NaCl). Additionally, a set of more than 15 candidate transcripts are proposed to be potential components of the salt overly sensitive (SOS) pathway in chickpea. Newly identified transcript isoforms are potential targets for breeding novel cultivars with high salinity tolerance. We demonstrate that these targets can be integrated into breeding schemes by micro-arrays and RT-PCR assays downstream of the generation of 26 bp tags by SuperSAGE. PMID:21320317

The salt-responsive transcriptome of chickpea roots and nodules via deepSuperSAGE.

PubMed

Molina, Carlos; Zaman-Allah, Mainassara; Khan, Faheema; Fatnassi, Nadia; Horres, Ralf; Rotter, Björn; Steinhauer, Diana; Amenc, Laurie; Drevon, Jean-Jacques; Winter, Peter; Kahl, Günter

2011-02-14

The combination of high-throughput transcript profiling and next-generation sequencing technologies is a prerequisite for genome-wide comprehensive transcriptome analysis. Our recent innovation of deepSuperSAGE is based on an advanced SuperSAGE protocol and its combination with massively parallel pyrosequencing on Roche's 454 sequencing platform. As a demonstration of the power of this combination, we have chosen the salt stress transcriptomes of roots and nodules of the third most important legume crop chickpea (Cicer arietinum L.). While our report is more technology-oriented, it nevertheless addresses a major world-wide problem for crops generally: high salinity. Together with low temperatures and water stress, high salinity is responsible for crop losses of millions of tons of various legume (and other) crops. Continuously deteriorating environmental conditions will combine with salinity stress to further compromise crop yields. As a good example for such stress-exposed crop plants, we started to characterize salt stress responses of chickpeas on the transcriptome level. We used deepSuperSAGE to detect early global transcriptome changes in salt-stressed chickpea. The salt stress responses of 86,919 transcripts representing 17,918 unique 26 bp deepSuperSAGE tags (UniTags) from roots of the salt-tolerant variety INRAT-93 two hours after treatment with 25 mM NaCl were characterized. Additionally, the expression of 57,281 transcripts representing 13,115 UniTags was monitored in nodules of the same plants. From a total of 144,200 analyzed 26 bp tags in roots and nodules together, 21,401 unique transcripts were identified. Of these, only 363 and 106 specific transcripts, respectively, were commonly up- or down-regulated (>3.0-fold) under salt stress in both organs, witnessing a differential organ-specific response to stress.Profiting from recent pioneer works on massive cDNA sequencing in chickpea, more than 9,400 UniTags were able to be linked to UniProt entries. Additionally, gene ontology (GO) categories over-representation analysis enabled to filter out enriched biological processes among the differentially expressed UniTags. Subsequently, the gathered information was further cross-checked with stress-related pathways. From several filtered pathways, here we focus exemplarily on transcripts associated with the generation and scavenging of reactive oxygen species (ROS), as well as on transcripts involved in Na+ homeostasis. Although both processes are already very well characterized in other plants, the information generated in the present work is of high value. Information on expression profiles and sequence similarity for several hundreds of transcripts of potential interest is now available. This report demonstrates, that the combination of the high-throughput transcriptome profiling technology SuperSAGE with one of the next-generation sequencing platforms allows deep insights into the first molecular reactions of a plant exposed to salinity. Cross validation with recent reports enriched the information about the salt stress dynamics of more than 9,000 chickpea ESTs, and enlarged their pool of alternative transcripts isoforms. As an example for the high resolution of the employed technology that we coin deepSuperSAGE, we demonstrate that ROS-scavenging and -generating pathways undergo strong global transcriptome changes in chickpea roots and nodules already 2 hours after onset of moderate salt stress (25 mM NaCl). Additionally, a set of more than 15 candidate transcripts are proposed to be potential components of the salt overly sensitive (SOS) pathway in chickpea. Newly identified transcript isoforms are potential targets for breeding novel cultivars with high salinity tolerance. We demonstrate that these targets can be integrated into breeding schemes by micro-arrays and RT-PCR assays downstream of the generation of 26 bp tags by SuperSAGE.

Deep Sequencing to Identify the Causes of Viral Encephalitis

PubMed Central

Chan, Benjamin K.; Wilson, Theodore; Fischer, Kael F.; Kriesel, John D.

2014-01-01

Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue. PMID:24699691

Water mass dynamics shape Ross Sea protist communities in mesopelagic and bathypelagic layers

NASA Astrophysics Data System (ADS)

Zoccarato, Luca; Pallavicini, Alberto; Cerino, Federica; Fonda Umani, Serena; Celussi, Mauro

2016-12-01

Deep-sea environments host the largest pool of microbes and represent the last largely unexplored and poorly known ecosystems on Earth. The Ross Sea is characterized by unique oceanographic dynamics and harbors several water masses deeply involved in cooling and ventilation of deep oceans. In this study the V9 region of the 18S rDNA was targeted and sequenced with the Ion Torrent high-throughput sequencing technology to unveil differences in protist communities (>2 μm) correlated with biogeochemical properties of the water masses. The analyzed samples were significantly different in terms of environmental parameters and community composition outlining significant structuring effects of temperature and salinity. Overall, Alveolata (especially Dinophyta), Stramenopiles and Excavata groups dominated mesopelagic and bathypelagic layers, and protist communities were shaped according to the biogeochemistry of the water masses (advection effect and mixing events). Newly-formed High Salinity Shelf Water (HSSW) was characterized by high relative abundance of phototrophic organisms that bloom at the surface during the austral summer. Oxygen-depleted Circumpolar Deep Water (CDW) showed higher abundance of Excavata, common bacterivores in deep water masses. At the shelf-break, Antarctic Bottom Water (AABW), formed by the entrainment of shelf waters in CDW, maintained the eukaryotic genetic signature typical of both parental water masses.

Bacterial and archaeal communities in the deep-sea sediments of inactive hydrothermal vents in the Southwest India Ridge

NASA Astrophysics Data System (ADS)

Zhang, Likui; Kang, Manyu; Xu, Jiajun; Xu, Jian; Shuai, Yinjie; Zhou, Xiaojian; Yang, Zhihui; Ma, Kesen

2016-05-01

Active deep-sea hydrothermal vents harbor abundant thermophilic and hyperthermophilic microorganisms. However, microbial communities in inactive hydrothermal vents have not been well documented. Here, we investigated bacterial and archaeal communities in the two deep-sea sediments (named as TVG4 and TVG11) collected from inactive hydrothermal vents in the Southwest India Ridge using the high-throughput sequencing technology of Illumina MiSeq2500 platform. Based on the V4 region of 16S rRNA gene, sequence analysis showed that bacterial communities in the two samples were dominated by Proteobacteria, followed by Bacteroidetes, Actinobacteria and Firmicutes. Furthermore, archaeal communities in the two samples were dominated by Thaumarchaeota and Euryarchaeota. Comparative analysis showed that (i) TVG4 displayed the higher bacterial richness and lower archaeal richness than TVG11; (ii) the two samples had more divergence in archaeal communities than bacterial communities. Bacteria and archaea that are potentially associated with nitrogen, sulfur metal and methane cycling were detected in the two samples. Overall, we first provided a comparative picture of bacterial and archaeal communities and revealed their potentially ecological roles in the deep-sea environments of inactive hydrothermal vents in the Southwest Indian Ridge, augmenting microbial communities in inactive hydrothermal vents.

Multimission Software Reuse in an Environment of Large Paradigm Shifts

NASA Technical Reports Server (NTRS)

Wilson, Robert K.

1996-01-01

The ground data systems provided for NASA space mission support are discussed. As space missions expand, the ground systems requirements become more complex. Current ground data systems provide for telemetry, command, and uplink and downlink processing capabilities. The new millennium project (NMP) technology testbed for 21st century NASA missions is discussed. The program demonstrates spacecraft and ground system technologies. The paradigm shift from detailed ground sequencing to a goal oriented planning approach is considered. The work carried out to meet this paradigm for the Deep Space-1 (DS-1) mission is outlined.

Single-virion sequencing of lamivudine-treated HBV populations reveal population evolution dynamics and demographic history.

PubMed

Zhu, Yuan O; Aw, Pauline P K; de Sessions, Paola Florez; Hong, Shuzhen; See, Lee Xian; Hong, Lewis Z; Wilm, Andreas; Li, Chen Hao; Hue, Stephane; Lim, Seng Gee; Nagarajan, Niranjan; Burkholder, William F; Hibberd, Martin

2017-10-27

Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients - once before antiviral treatment and once after viral rebound due to resistance. With single-virion sequencing, we obtained 248-8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

A Deep Insight Into the Sialotranscriptome of the Chagas Disease Vector, Panstrongylus megistus (Hemiptera: Heteroptera)

PubMed Central

Ribeiro, José M. C.; Schwarz, Alexandra; Francischetti, Ivo M. B.

2015-01-01

Saliva of blood-sucking arthropods contains a complex cocktail of pharmacologically active compounds that assists feeding by counteracting their hosts’ hemostatic and inflammatory reactions. Panstrongylus megistus (Burmeister) is an important vector of Chagas disease in South America, but despite its importance there is only one salivary protein sequence publicly deposited in GenBank. In the present work, we used Illumina technology to disclose and publicly deposit 3,703 coding sequences obtained from the assembly of >70 million reads. These sequences should assist proteomic experiments aimed at identifying pharmacologically active proteins and immunological markers of vector exposure. A supplemental file of the transcriptome and deducted protein sequences can be obtained from http://exon.niaid.nih.gov/transcriptome/P_megistus/Pmeg-web.xlsx. PMID:26334808

Planetary cubesats - mission architectures

NASA Astrophysics Data System (ADS)

Bousquet, Pierre W.; Ulamec, Stephan; Jaumann, Ralf; Vane, Gregg; Baker, John; Clark, Pamela; Komarek, Tomas; Lebreton, Jean-Pierre; Yano, Hajime

2016-07-01

Miniaturisation of technologies over the last decade has made cubesats a valid solution for deep space missions. For example, a spectacular set 13 cubesats will be delivered in 2018 to a high lunar orbit within the frame of SLS' first flight, referred to as Exploration Mission-1 (EM-1). Each of them will perform autonomously valuable scientific or technological investigations. Other situations are encountered, such as the auxiliary landers / rovers and autonomous camera that will be carried in 2018 to asteroid 1993 JU3 by JAXA's Hayabusas 2 probe, and will provide complementary scientific return to their mothership. In this case, cubesats depend on a larger spacecraft for deployment and other resources, such as telecommunication relay or propulsion. For both situations, we will describe in this paper how cubesats can be used as remote observatories (such as NEO detection missions), as technology demonstrators, and how they can perform or contribute to all steps in the Deep Space exploration sequence: Measurements during Deep Space cruise, Body Fly-bies, Body Orbiters, Atmospheric probes (Jupiter probe, Venus atmospheric probes, ..), Static Landers, Mobile landers (such as balloons, wheeled rovers, small body rovers, drones, penetrators, floating devices, …), Sample Return. We will elaborate on mission architectures for the most promising concepts where cubesat size devices offer an advantage in terms of affordability, feasibility, and increase of scientific return.

Combining Next Generation Sequencing with Bulked Segregant Analysis to Fine Map a Stem Moisture Locus in Sorghum (Sorghum bicolor L. Moench).

PubMed

Han, Yucui; Lv, Peng; Hou, Shenglin; Li, Suying; Ji, Guisu; Ma, Xue; Du, Ruiheng; Liu, Guoqing

2015-01-01

Sorghum is one of the most promising bioenergy crops. Stem juice yield, together with stem sugar concentration, determines sugar yield in sweet sorghum. Bulked segregant analysis (BSA) is a gene mapping technique for identifying genomic regions containing genetic loci affecting a trait of interest that when combined with deep sequencing could effectively accelerate the gene mapping process. In this study, a dry stem sorghum landrace was characterized and the stem water controlling locus, qSW6, was fine mapped using QTL analysis and the combined BSA and deep sequencing technologies. Results showed that: (i) In sorghum variety Jiliang 2, stem water content was around 80% before flowering stage. It dropped to 75% during grain filling with little difference between different internodes. In landrace G21, stem water content keeps dropping after the flag leaf stage. The drop from 71% at flowering time progressed to 60% at grain filling time. Large differences exist between different internodes with the lowest (51%) at the 7th and 8th internodes at dough stage. (ii) A quantitative trait locus (QTL) controlling stem water content mapped on chromosome 6 between SSR markers Ch6-2 and gpsb069 explained about 34.7-56.9% of the phenotypic variation for the 5th to 10th internodes, respectively. (iii) BSA and deep sequencing analysis narrowed the associated region to 339 kb containing 38 putative genes. The results could help reveal molecular mechanisms underlying juice yield of sorghum and thus to improve total sugar yield.

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

PubMed

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

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

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

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

Designing deep sequencing experiments: detecting structural variation and estimating transcript abundance.

PubMed

Bashir, Ali; Bansal, Vikas; Bafna, Vineet

2010-06-18

Massively parallel DNA sequencing technologies have enabled the sequencing of several individual human genomes. These technologies are also being used in novel ways for mRNA expression profiling, genome-wide discovery of transcription-factor binding sites, small RNA discovery, etc. The multitude of sequencing platforms, each with their unique characteristics, pose a number of design challenges, regarding the technology to be used and the depth of sequencing required for a particular sequencing application. Here we describe a number of analytical and empirical results to address design questions for two applications: detection of structural variations from paired-end sequencing and estimating mRNA transcript abundance. For structural variation, our results provide explicit trade-offs between the detection and resolution of rearrangement breakpoints, and the optimal mix of paired-read insert lengths. Specifically, we prove that optimal detection and resolution of breakpoints is achieved using a mix of exactly two insert library lengths. Furthermore, we derive explicit formulae to determine these insert length combinations, enabling a 15% improvement in breakpoint detection at the same experimental cost. On empirical short read data, these predictions show good concordance with Illumina 200 bp and 2 Kbp insert length libraries. For transcriptome sequencing, we determine the sequencing depth needed to detect rare transcripts from a small pilot study. With only 1 Million reads, we derive corrections that enable almost perfect prediction of the underlying expression probability distribution, and use this to predict the sequencing depth required to detect low expressed genes with greater than 95% probability. Together, our results form a generic framework for many design considerations related to high-throughput sequencing. We provide software tools http://bix.ucsd.edu/projects/NGS-DesignTools to derive platform independent guidelines for designing sequencing experiments (amount of sequencing, choice of insert length, mix of libraries) for novel applications of next generation sequencing.

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

PubMed

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

2017-10-01

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

Breaking the 1000-gene barrier for Mimivirus using ultra-deep genome and transcriptome sequencing.

PubMed

Legendre, Matthieu; Santini, Sébastien; Rico, Alain; Abergel, Chantal; Claverie, Jean-Michel

2011-03-04

Mimivirus, a giant dsDNA virus infecting Acanthamoeba, is the prototype of the mimiviridae family, the latest addition to the family of the nucleocytoplasmic large DNA viruses (NCLDVs). Its 1.2 Mb-genome was initially predicted to encode 917 genes. A subsequent RNA-Seq analysis precisely mapped many transcript boundaries and identified 75 new genes. We now report a much deeper analysis using the SOLiD™ technology combining RNA-Seq of the Mimivirus transcriptome during the infectious cycle (202.4 Million reads), and a complete genome re-sequencing (45.3 Million reads). This study corrected the genome sequence and identified several single nucleotide polymorphisms. Our results also provided clear evidence of previously overlooked transcription units, including an important RNA polymerase subunit distantly related to Euryarchea homologues. The total Mimivirus gene count is now 1018, 11% greater than the original annotation. This study highlights the huge progress brought about by ultra-deep sequencing for the comprehensive annotation of virus genomes, opening the door to a complete one-nucleotide resolution level description of their transcriptional activity, and to the realistic modeling of the viral genome expression at the ultimate molecular level. This work also illustrates the need to go beyond bioinformatics-only approaches for the annotation of short protein and non-coding genes in viral genomes.

Transcriptome and Small RNA Deep Sequencing Reveals Deregulation of miRNA Biogenesis in Human Glioma

PubMed Central

Moore, Lynette M.; Kivinen, Virpi; Liu, Yuexin; Annala, Matti; Cogdell, David; Liu, Xiuping; Liu, Chang-Gong; Sawaya, Raymond; Yli-Harja, Olli; Shmulevich, Ilya; Fuller, Gregory N.; Zhang, Wei; Nykter, Matti

2013-01-01

Altered expression of oncogenic and tumor-suppressing microRNAs (miRNAs) is widely associated with tumorigenesis. However, the regulatory mechanisms underlying these alterations are poorly understood. We sought to shed light on the deregulation of miRNA biogenesis promoting the aberrant miRNA expression profiles identified in these tumors. Using sequencing technology to perform both whole-transcriptome and small RNA sequencing of glioma patient samples, we examined precursor and mature miRNAs to directly evaluate the miRNA maturation process, and interrogated expression profiles for genes involved in the major steps of miRNA biogenesis. We found that ratios of mature to precursor forms of a large number of miRNAs increased with the progression from normal brain to low-grade and then to high-grade gliomas. The expression levels of genes involved in each of the three major steps of miRNA biogenesis (nuclear processing, nucleo-cytoplasmic transport, and cytoplasmic processing) were systematically altered in glioma tissues. Survival analysis of an independent data set demonstrated that the alteration of genes involved in miRNA maturation correlates with survival in glioma patients. Direct quantification of miRNA maturation with deep sequencing demonstrated that deregulation of the miRNA biogenesis pathway is a hallmark for glioma genesis and progression. PMID:23007860

DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

PubMed

You, Ronghui; Huang, Xiaodi; Zhu, Shanfeng

2018-06-06

As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to reduce this huge gap becomes increasingly important. The previous studies conclude that sequence homology based methods are highly effective in AFP. In addition, mining motif, domain, and functional information from protein sequences has been found very helpful for AFP. Other than sequences, alternative information sources such as text, however, may be useful for AFP as well. Instead of using BOW (bag of words) representation in traditional text-based AFP, we propose a new method called DeepText2GO that relies on deep semantic text representation, together with different kinds of available protein information such as sequence homology, families, domains, and motifs, to improve large-scale AFP. Furthermore, DeepText2GO integrates text-based methods with sequence-based ones by means of a consensus approach. Extensive experiments on the benchmark dataset extracted from UniProt/SwissProt have demonstrated that DeepText2GO significantly outperformed both text-based and sequence-based methods, validating its superiority. Copyright © 2018 Elsevier Inc. All rights reserved.

Application of Genomic Technologies to the Breeding of Trees

PubMed Central

Badenes, Maria L.; Fernández i Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J.

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species. PMID:27895664

Application of Genomic Technologies to the Breeding of Trees.

PubMed

Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

Insights into Deep-Sea Sediment Fungal Communities from the East Indian Ocean Using Targeted Environmental Sequencing Combined with Traditional Cultivation

PubMed Central

Zhang, Xiao-yong; Tang, Gui-ling; Xu, Xin-ya; Nong, Xu-hua; Qi, Shu-Hua

2014-01-01

The fungal diversity in deep-sea environments has recently gained an increasing amount attention. Our knowledge and understanding of the true fungal diversity and the role it plays in deep-sea environments, however, is still limited. We investigated the fungal community structure in five sediments from a depth of ∼4000 m in the East India Ocean using a combination of targeted environmental sequencing and traditional cultivation. This approach resulted in the recovery of a total of 45 fungal operational taxonomic units (OTUs) and 20 culturable fungal phylotypes. This finding indicates that there is a great amount of fungal diversity in the deep-sea sediments collected in the East Indian Ocean. Three fungal OTUs and one culturable phylotype demonstrated high divergence (89%–97%) from the existing sequences in the GenBank. Moreover, 44.4% fungal OTUs and 30% culturable fungal phylotypes are new reports for deep-sea sediments. These results suggest that the deep-sea sediments from the East India Ocean can serve as habitats for new fungal communities compared with other deep-sea environments. In addition, different fungal community could be detected when using targeted environmental sequencing compared with traditional cultivation in this study, which suggests that a combination of targeted environmental sequencing and traditional cultivation will generate a more diverse fungal community in deep-sea environments than using either targeted environmental sequencing or traditional cultivation alone. This study is the first to report new insights into the fungal communities in deep-sea sediments from the East Indian Ocean, which increases our knowledge and understanding of the fungal diversity in deep-sea environments. PMID:25272044

Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits.

PubMed

Adriaens, M E; Bezzina, C R

2018-06-22

Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.

Assessment of clinical analytical sensitivity and specificity of next-generation sequencing for detection of simple and complex mutations.

PubMed

Chin, Ephrem L H; da Silva, Cristina; Hegde, Madhuri

2013-02-19

Detecting mutations in disease genes by full gene sequence analysis is common in clinical diagnostic laboratories. Sanger dideoxy terminator sequencing allows for rapid development and implementation of sequencing assays in the clinical laboratory, but it has limited throughput, and due to cost constraints, only allows analysis of one or at most a few genes in a patient. Next-generation sequencing (NGS), on the other hand, has evolved rapidly, although to date it has mainly been used for large-scale genome sequencing projects and is beginning to be used in the clinical diagnostic testing. One advantage of NGS is that many genes can be analyzed easily at the same time, allowing for mutation detection when there are many possible causative genes for a specific phenotype. In addition, regions of a gene typically not tested for mutations, like deep intronic and promoter mutations, can also be detected. Here we use 20 previously characterized Sanger-sequenced positive controls in disease-causing genes to demonstrate the utility of NGS in a clinical setting using standard PCR based amplification to assess the analytical sensitivity and specificity of the technology for detecting all previously characterized changes (mutations and benign SNPs). The positive controls chosen for validation range from simple substitution mutations to complex deletion and insertion mutations occurring in autosomal dominant and recessive disorders. The NGS data was 100% concordant with the Sanger sequencing data identifying all 119 previously identified changes in the 20 samples. We have demonstrated that NGS technology is ready to be deployed in clinical laboratories. However, NGS and associated technologies are evolving, and clinical laboratories will need to invest significantly in staff and infrastructure to build the necessary foundation for success.

Planetary science and exploration in the deep subsurface: results from the MINAR Program, Boulby Mine, UK

NASA Astrophysics Data System (ADS)

Payler, Samuel J.; Biddle, Jennifer F.; Coates, Andrew J.; Cousins, Claire R.; Cross, Rachel E.; Cullen, David C.; Downs, Michael T.; Direito, Susana O. L.; Edwards, Thomas; Gray, Amber L.; Genis, Jac; Gunn, Matthew; Hansford, Graeme M.; Harkness, Patrick; Holt, John; Josset, Jean-Luc; Li, Xuan; Lees, David S.; Lim, Darlene S. S.; McHugh, Melissa; McLuckie, David; Meehan, Emma; Paling, Sean M.; Souchon, Audrey; Yeoman, Louise; Cockell, Charles S.

2017-04-01

The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research - MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining.

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

Virus Identification in Unknown Tropical Febrile Illness Cases Using Deep Sequencing

PubMed Central

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

2012-01-01

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

deepTools: a flexible platform for exploring deep-sequencing data.

PubMed

Ramírez, Fidel; Dündar, Friederike; Diehl, Sarah; Grüning, Björn A; Manke, Thomas

2014-07-01

We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg.de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of microRNAs from Amur grape (Vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics.

PubMed

Wang, Chen; Han, Jian; Liu, Chonghuai; Kibet, Korir Nicholas; Kayesh, Emrul; Shangguan, Lingfei; Li, Xiaoying; Fang, Jinggui

2012-03-29

MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved miRNAs, indicating that specific miRNAs exist in Amur grape. These results show that a number of regulatory miRNAs exist in Amur grape and play an important role in Amur grape growth, development, and response to abiotic or biotic stress.

Simultaneous detection of human mitochondrial DNA and nuclear-inserted mitochondrial-origin sequences (NumtS) using forensic mtDNA amplification strategies and pyrosequencing technology.

PubMed

Bintz, Brittania J; Dixon, Groves B; Wilson, Mark R

2014-07-01

Next-generation sequencing technologies enable the identification of minor mitochondrial DNA variants with higher sensitivity than Sanger methods, allowing for enhanced identification of minor variants. In this study, mixtures of human mtDNA control region amplicons were subjected to pyrosequencing to determine the detection threshold of the Roche GS Junior(®) instrument (Roche Applied Science, Indianapolis, IN). In addition to expected variants, a set of reproducible variants was consistently found in reads from one particular amplicon. A BLASTn search of the variant sequence revealed identity to a segment of a 611-bp nuclear insertion of the mitochondrial control region (NumtS) spanning the primer-binding sites of this amplicon (Nature 1995;378:489). Primers (Hum Genet 2012;131:757; Hum Biol 1996;68:847) flanking the insertion were used to confirm the presence or absence of the NumtS in buccal DNA extracts from twenty donors. These results further our understanding of human mtDNA variation and are expected to have a positive impact on the interpretation of mtDNA profiles using deep-sequencing methods in casework. © 2014 American Academy of Forensic Sciences.

Molecular methods for pathogen and microbial community detection and characterization: current and potential application in diagnostic microbiology.

PubMed

Sibley, Christopher D; Peirano, Gisele; Church, Deirdre L

2012-04-01

Clinical microbiology laboratories worldwide have historically relied on phenotypic methods (i.e., culture and biochemical tests) for detection, identification and characterization of virulence traits (e.g., antibiotic resistance genes, toxins) of human pathogens. However, limitations to implementation of molecular methods for human infectious diseases testing are being rapidly overcome allowing for the clinical evaluation and implementation of diverse technologies with expanding diagnostic capabilities. The advantages and limitation of molecular techniques including real-time polymerase chain reaction, partial or whole genome sequencing, molecular typing, microarrays, broad-range PCR and multiplexing will be discussed. Finally, terminal restriction fragment length polymorphism (T-RFLP) and deep sequencing are introduced as technologies at the clinical interface with the potential to dramatically enhance our ability to diagnose infectious diseases and better define the epidemiology and microbial ecology of a wide range of complex infections. Copyright © 2012 Elsevier B.V. All rights reserved.

How to Access and Sample the Deep Subsurface of Mars

NASA Technical Reports Server (NTRS)

Briggs, G.; Blacic, J.; Dreesen, D.; Mockler, T.

2000-01-01

We are developing a technology roadmap to support a series of Mars lander missions aimed at successively deeper and more comprehensive explorations of the Martian subsurface. The proposed mission sequence is outlined. Key to this approach is development of a drilling and sampling technology robust and flexible enough to successfully penetrate the presently unknown subsurface geology and structure. Martian environmental conditions, mission constraints of power and mass and a requirement for a high degree of automation all limit applicability of many proven terrestrial drilling technologies. Planetary protection and bioscience objectives further complicate selection of candidate systems. Nevertheless, recent advances in drilling technologies for the oil & gas, mining, underground utility and other specialty drilling industries convinces us that it will be possible to meet science and operational objectives of Mars subsurface exploration.

Noninvasive genome sampling in chimpanzees.

PubMed

Kohn, Michael H

2010-12-01

The inevitable has happened: genomic technologies have been added to our noninvasive genetic sampling repertoire. In this issue of Molecular Ecology, Perry et al. (2010) demonstrate how DNA extraction from chimpanzee faeces, followed by a series of steps to enrich for target loci, can be coupled with next-generation sequencing. These authors collected sequence and single-nucleotide polymorphism (SNP) data at more than 600 genomic loci (chromosome 21 and the X) and the complete mitochondrial DNA. By design, each locus was 'deep sequenced' to enable SNP identification. To demonstrate the reliability of their data, the work included samples from six captive chimps, which allowed for a comparison between presumably genuine SNPs obtained from blood and potentially flawed SNPs deduced from faeces. Thus, with this method, anyone with the resources, skills and ambition to do genome sequencing of wild, elusive, or protected mammals can enjoy all of the benefits of noninvasive sampling. © 2010 Blackwell Publishing Ltd.

Differential expression analysis of Paralichthys olivaceus microRNAs in adult ovary and testis by deep sequencing.

PubMed

Gu, Yifeng; Zhang, Lei; Chen, Xiaowu

2014-08-01

MicroRNAs (miRNAs) play an important role in gonadal development and differentiation in fish. However, understanding of the mechanism of this process is hindered by our poor knowledge of miRNA expression patterns in fish gonads. In this study, miRNA libraries derived from adult gonads of Paralichthys olivaceus were generated by using next-generation sequencing (NGS) technology. Bioinformatics analysis was performed to distinguish mature miRNA sequences from two classes of small RNAs represented in the sequencing data. A total of 141 mature miRNAs were identified, in which 21 miRNAs were found in P. olivaceus for the first time. Variance and preference of miRNAs expression were concluded from the deep sequencing reads. Some miRNAs, such as pol-miR-143, pol-miR-26a and pol-let-7a were found with quite high expression levels in both gonads, while some exhibited a clear sex-biased expression in different gonad. Approximate 20.0% and 13.1% of the isolated miRNAs were preferentially expressed in the testis (FC<0.5) or ovary (FC>2), respectively. The identification and the preliminary analysis of the sex-biased expression of miRNAs in P. olivaceus gonads in our work by using NGS will provide us a basic catalog of miRNAs to facilitate future improvement and exploitation of sexual regulatory mechanisms in P. olivaceus. Copyright © 2014. Published by Elsevier Inc.

Micropathogen Community Analysis in Hyalomma rufipes via High-Throughput Sequencing of Small RNAs

PubMed Central

Luo, Jin; Liu, Min-Xuan; Ren, Qiao-Yun; Chen, Ze; Tian, Zhan-Cheng; Hao, Jia-Wei; Wu, Feng; Liu, Xiao-Cui; Luo, Jian-Xun; Yin, Hong; Wang, Hui; Liu, Guang-Yuan

2017-01-01

Ticks are important vectors in the transmission of a broad range of micropathogens to vertebrates, including humans. Because of the role of ticks in disease transmission, identifying and characterizing the micropathogen profiles of tick populations have become increasingly important. The objective of this study was to survey the micropathogens of Hyalomma rufipes ticks. Illumina HiSeq2000 technology was utilized to perform deep sequencing of small RNAs (sRNAs) extracted from field-collected H. rufipes ticks in Gansu Province, China. The resultant sRNA library data revealed that the surveyed tick populations produced reads that were homologous to St. Croix River Virus (SCRV) sequences. We also observed many reads that were homologous to microbial and/or pathogenic isolates, including bacteria, protozoa, and fungi. As part of this analysis, a phylogenetic tree was constructed to display the relationships among the homologous sequences that were identified. The study offered a unique opportunity to gain insight into the micropathogens of H. rufipes ticks. The effective control of arthropod vectors in the future will require knowledge of the micropathogen composition of vectors harboring infectious agents. Understanding the ecological factors that regulate vector propagation in association with the prevalence and persistence of micropathogen lineages is also imperative. These interactions may affect the evolution of micropathogen lineages, especially if the micropathogens rely on the vector or host for dispersal. The sRNA deep-sequencing approach used in this analysis provides an intuitive method to survey micropathogen prevalence in ticks and other vector species. PMID:28861401

Low-Latency Telerobotic Sample Return and Biomolecular Sequencing for Deep Space Gateway

NASA Astrophysics Data System (ADS)

Lupisella, M.; Bleacher, J.; Lewis, R.; Dworkin, J.; Wright, M.; Burton, A.; Rubins, K.; Wallace, S.; Stahl, S.; John, K.; Archer, D.; Niles, P.; Regberg, A.; Smith, D.; Race, M.; Chiu, C.; Russell, J.; Rampe, E.; Bywaters, K.

2018-02-01

Low-latency telerobotics, crew-assisted sample return, and biomolecular sequencing can be used to acquire and analyze lunar farside and/or Apollo landing site samples. Sequencing can also be used to monitor and study Deep Space Gateway environment and crew health.

The Evolution of Deep Space Navigation: 1989-1999

NASA Technical Reports Server (NTRS)

Wood, Lincoln J.

2008-01-01

The exploration of the planets of the solar system using robotic vehicles has been underway since the early 1960s. During this time the navigational capabilities employed have increased greatly in accuracy, as required by the scientific objectives of the missions and as enabled by improvements in technology. This paper is the second in a chronological sequence dealing with the evolution of deep space navigation. The time interval covered extends from the 1989 launch of the Magellan spacecraft to Venus through a multiplicity of planetary exploration activities in 1999. The paper focuses on the observational techniques that have been used to obtain navigational information, propellant-efficient means for modifying spacecraft trajectories, and the computational methods that have been employed, tracing their evolution through a dozen planetary missions.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-11-20

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

IODP Expedition 337: Deep Coalbed Biosphere off Shimokita - Microbial processes and hydrocarbon system associated with deeply buried coalbed in the ocean

NASA Astrophysics Data System (ADS)

Inagaki, Fumio; Hinrichs, Kai-Uwe; Kubo, Yusuke; IODP Expedition 337 Scientists

2016-06-01

The Integrated Ocean Drilling Program (IODP) Expedition 337 was the first expedition dedicated to subseafloor microbiology that used riser-drilling technology with the drilling vessel Chikyu. The drilling Site C0020 is located in a forearc basin formed by the subduction of the Pacific Plate off the Shimokita Peninsula, Japan, at a water depth of 1180 m. Primary scientific objectives during Expedition 337 were to study the relationship between the deep microbial biosphere and a series of ˜ 2 km deep subseafloor coalbeds and to explore the limits of life in the deepest horizons ever probed by scientific ocean drilling. To address these scientific objectives, we penetrated a 2.466 km deep sedimentary sequence with a series of lignite layers buried around 2 km below the seafloor. The cored sediments, as well as cuttings and logging data, showed a record of dynamically changing depositional environments in the former forearc basin off the Shimokita Peninsula during the late Oligocene and Miocene, ranging from warm-temperate coastal backswamps to a cool water continental shelf. The occurrence of small microbial populations and their methanogenic activity were confirmed down to the bottom of the hole by microbiological and biogeochemical analyses. The factors controlling the size and viability of ultra-deep microbial communities in those warm sedimentary habitats could be the increase in demand of energy and water expended on the enzymatic repair of biomolecules as a function of the burial depth. Expedition 337 provided a test ground for the use of riser-drilling technology to address geobiological and biogeochemical objectives and was therefore a crucial step toward the next phase of deep scientific ocean drilling.

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.

The 1000 Genomes Project: data management and community access.

PubMed

Clarke, Laura; Zheng-Bradley, Xiangqun; Smith, Richard; Kulesha, Eugene; Xiao, Chunlin; Toneva, Iliana; Vaughan, Brendan; Preuss, Don; Leinonen, Rasko; Shumway, Martin; Sherry, Stephen; Flicek, Paul

2012-04-27

The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access.

Emerging patterns of somatic mutations in cancer

PubMed Central

Watson, Ian R.; Takahashi, Koichi; Futreal, P. Andrew; Chin, Lynda

2014-01-01

The advance in technological tools for massively parallel, high-throughput sequencing of DNA has enabled the comprehensive characterization of somatic mutations in large number of tumor samples. Here, we review recent cancer genomic studies that have assembled emerging views of the landscapes of somatic mutations through deep sequencing analyses of the coding exomes and whole genomes in various cancer types. We discuss the comparative genomics of different cancers, including mutation rates, spectrums, and roles of environmental insults that influence these processes. We highlight the developing statistical approaches used to identify significantly mutated genes, and discuss the emerging biological and clinical insights from such analyses as well as the challenges ahead translating these genomic data into clinical impacts. PMID:24022702

Population-genomic variation within RNA viruses of the Western honey bee, Apis mellifera, inferred from deep sequencing

USDA-ARS?s Scientific Manuscript database

Deep sequencing of viruses isolated from infected hosts is an efficient way to measure population-genetic variation and can reveal patterns of dispersal and natural selection. In this study, we mined existing Illumina sequence reads to investigate single-nucleotide polymorphisms (SNPs) within two RN...

Geoseq: a tool for dissecting deep-sequencing datasets.

PubMed

Gurtowski, James; Cancio, Anthony; Shah, Hardik; Levovitz, Chaya; George, Ajish; Homann, Robert; Sachidanandam, Ravi

2010-10-12

Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO), Sequence Read Archive (SRA) hosted by the NCBI, or the DNA Data Bank of Japan (ddbj). Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a) identify differential isoform expression in mRNA-seq datasets, b) identify miRNAs (microRNAs) in libraries, and identify mature and star sequences in miRNAS and c) to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

Bi-PROF

PubMed Central

Gries, Jasmin; Schumacher, Dirk; Arand, Julia; Lutsik, Pavlo; Markelova, Maria Rivera; Fichtner, Iduna; Walter, Jörn; Sers, Christine; Tierling, Sascha

2013-01-01

The use of next generation sequencing has expanded our view on whole mammalian methylome patterns. In particular, it provides a genome-wide insight of local DNA methylation diversity at single nucleotide level and enables the examination of single chromosome sequence sections at a sufficient statistical power. We describe a bisulfite-based sequence profiling pipeline, Bi-PROF, which is based on the 454 GS-FLX Titanium technology that allows to obtain up to one million sequence stretches at single base pair resolution without laborious subcloning. To illustrate the performance of the experimental workflow connected to a bioinformatics program pipeline (BiQ Analyzer HT) we present a test analysis set of 68 different epigenetic marker regions (amplicons) in five individual patient-derived xenograft tissue samples of colorectal cancer and one healthy colon epithelium sample as a control. After the 454 GS-FLX Titanium run, sequence read processing and sample decoding, the obtained alignments are quality controlled and statistically evaluated. Comprehensive methylation pattern interpretation (profiling) assessed by analyzing 102-104 sequence reads per amplicon allows an unprecedented deep view on pattern formation and methylation marker heterogeneity in tissues concerned by complex diseases like cancer. PMID:23803588

Detection of Emerging Vaccine-Related Polioviruses by Deep Sequencing.

PubMed

Sahoo, Malaya K; Holubar, Marisa; Huang, ChunHong; Mohamed-Hadley, Alisha; Liu, Yuanyuan; Waggoner, Jesse J; Troy, Stephanie B; Garcia-Garcia, Lourdes; Ferreyra-Reyes, Leticia; Maldonado, Yvonne; Pinsky, Benjamin A

2017-07-01

Oral poliovirus vaccine can mutate to regain neurovirulence. To date, evaluation of these mutations has been performed primarily on culture-enriched isolates by using conventional Sanger sequencing. We therefore developed a culture-independent, deep-sequencing method targeting the 5' untranslated region (UTR) and P1 genomic region to characterize vaccine-related poliovirus variants. Error analysis of the deep-sequencing method demonstrated reliable detection of poliovirus mutations at levels of <1%, depending on read depth. Sequencing of viral nucleic acids from the stool of vaccinated, asymptomatic children and their close contacts collected during a prospective cohort study in Veracruz, Mexico, revealed no vaccine-derived polioviruses. This was expected given that the longest duration between sequenced sample collection and the end of the most recent national immunization week was 66 days. However, we identified many low-level variants (<5%) distributed across the 5' UTR and P1 genomic region in all three Sabin serotypes, as well as vaccine-related viruses with multiple canonical mutations associated with phenotypic reversion present at high levels (>90%). These results suggest that monitoring emerging vaccine-related poliovirus variants by deep sequencing may aid in the poliovirus endgame and efforts to ensure global polio eradication. Copyright © 2017 Sahoo et al.

Clonal evolution of acute myeloid leukemia highlighted by latest genome sequencing studies.

PubMed

Zhang, Xuehong; Lv, Dekang; Zhang, Yu; Liu, Quentin; Li, Zhiguang

2016-09-06

Decades of years might be required for an initiated cell to become a fully-pledged, metastasized tumor. DNA mutations are accumulated during this process including background mutations that emerge scholastically, as well as driver mutations that selectively occur in a handful of cancer genes and confer the cell a growth advantage over its neighbors. A clone of tumor cells could be superseded by another clone that acquires new mutations and grows more aggressively. Tumor evolutional patterns have been studied for years using conventional approaches that focus on the investigation of a single or a couple of genes. Latest deep sequencing technology enables a global view of tumor evolution by deciphering almost all genome aberrations in a tumor. Tumor clones and the fate of each clone during tumor evolution can be depicted with the help of the concept of variant allele frequency. Here, we summarize the new insights of cancer evolutional progression in acute myeloid leukemia. Cancer evolution is currently thought to start from a clone that has accumulated the requisite somatically-acquired genetic aberrations through a series of increasingly disordered clinical and pathological phases, eventually leading to malignant transformation [1-3]. The observations in invasive colorectal cancer that usually emerges from an antecedent benign adenomatous polyp and in cervical cancer that proceeds through intraepithelial neoplasia support the idea of stepwise or linear cancerous progression [3-5]. Genetically, such progression is achieved by successive waves of clonal expansion during which cells acquire novel genomic alterations including single nucleotide variants (SNVs), small insertions and deletions (indels), and/or copy number variations (CNVs) [6]. The latest improvement in sequencing technology has allowed the deciphering of the whole exome or genome in different types of tumor and normal tissue pairs, providing detailed catalogue about genome aberrations during tumor initiation and progression, which have been reviewed in several papers [7-10]. Here, we focus on demonstrating the cancer clonal evolution pattern revealed by recent deep sequencing studies of samples from acute myeloid leukemia (AML) patients.

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing.

PubMed

Stiffler, Michael A; Subramanian, Subu K; Salinas, Victor H; Ranganathan, Rama

2016-07-03

Site-directed mutagenesis has long been used as a method to interrogate protein structure, function and evolution. Recent advances in massively-parallel sequencing technology have opened up the possibility of assessing the functional or fitness effects of large numbers of mutations simultaneously. Here, we present a protocol for experimentally determining the effects of all possible single amino acid mutations in a protein of interest utilizing high-throughput sequencing technology, using the 263 amino acid antibiotic resistance enzyme TEM-1 β-lactamase as an example. In this approach, a whole-protein saturation mutagenesis library is constructed by site-directed mutagenic PCR, randomizing each position individually to all possible amino acids. The library is then transformed into bacteria, and selected for the ability to confer resistance to β-lactam antibiotics. The fitness effect of each mutation is then determined by deep sequencing of the library before and after selection. Importantly, this protocol introduces methods which maximize sequencing read depth and permit the simultaneous selection of the entire mutation library, by mixing adjacent positions into groups of length accommodated by high-throughput sequencing read length and utilizing orthogonal primers to barcode each group. Representative results using this protocol are provided by assessing the fitness effects of all single amino acid mutations in TEM-1 at a clinically relevant dosage of ampicillin. The method should be easily extendable to other proteins for which a high-throughput selection assay is in place.

Identification of microRNAs from Amur grape (vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics

PubMed Central

2012-01-01

Background MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. Results A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Conclusions Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved miRNAs, indicating that specific miRNAs exist in Amur grape. These results show that a number of regulatory miRNAs exist in Amur grape and play an important role in Amur grape growth, development, and response to abiotic or biotic stress. PMID:22455456

DNA Replication Profiling Using Deep Sequencing.

PubMed

Saayman, Xanita; Ramos-Pérez, Cristina; Brown, Grant W

2018-01-01

Profiling of DNA replication during progression through S phase allows a quantitative snap-shot of replication origin usage and DNA replication fork progression. We present a method for using deep sequencing data to profile DNA replication in S. cerevisiae.

A deep transcriptomic analysis of pod development in the vanilla orchid (Vanilla planifolia).

PubMed

Rao, Xiaolan; Krom, Nick; Tang, Yuhong; Widiez, Thomas; Havkin-Frenkel, Daphna; Belanger, Faith C; Dixon, Richard A; Chen, Fang

2014-11-07

Pods of the vanilla orchid (Vanilla planifolia) accumulate large amounts of the flavor compound vanillin (3-methoxy, 4-hydroxy-benzaldehyde) as a glucoside during the later stages of their development. At earlier stages, the developing seeds within the pod synthesize a novel lignin polymer, catechyl (C) lignin, in their coats. Genomic resources for determining the biosynthetic routes to these compounds and other flavor components in V. planifolia are currently limited. Using next-generation sequencing technologies, we have generated very large gene sequence datasets from vanilla pods at different times of development, and representing different tissue types, including the seeds, hairs, placental and mesocarp tissues. This developmental series was chosen as being the most informative for interrogation of pathways of vanillin and C-lignin biosynthesis in the pod and seed, respectively. The combined 454/Illumina RNA-seq platforms provide both deep sequence coverage and high quality de novo transcriptome assembly for this non-model crop species. The annotated sequence data provide a foundation for understanding multiple aspects of the biochemistry and development of the vanilla bean, as exemplified by the identification of candidate genes involved in lignin biosynthesis. Our transcriptome data indicate that C-lignin formation in the seed coat involves coordinate expression of monolignol biosynthetic genes with the exception of those encoding the caffeoyl coenzyme A 3-O-methyltransferase for conversion of caffeoyl to feruloyl moieties. This database provides a general resource for further studies on this important flavor species.

A new method for enhancer prediction based on deep belief network.

PubMed

Bu, Hongda; Gan, Yanglan; Wang, Yang; Zhou, Shuigeng; Guan, Jihong

2017-10-16

Studies have shown that enhancers are significant regulatory elements to play crucial roles in gene expression regulation. Since enhancers are unrelated to the orientation and distance to their target genes, it is a challenging mission for scholars and researchers to accurately predicting distal enhancers. In the past years, with the high-throughout ChiP-seq technologies development, several computational techniques emerge to predict enhancers using epigenetic or genomic features. Nevertheless, the inconsistency of computational models across different cell-lines and the unsatisfactory prediction performance call for further research in this area. Here, we propose a new Deep Belief Network (DBN) based computational method for enhancer prediction, which is called EnhancerDBN. This method combines diverse features, composed of DNA sequence compositional features, DNA methylation and histone modifications. Our computational results indicate that 1) EnhancerDBN outperforms 13 existing methods in prediction, and 2) GC content and DNA methylation can serve as relevant features for enhancer prediction. Deep learning is effective in boosting the performance of enhancer prediction.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

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

PubMed

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

2018-02-01

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

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

PubMed

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2017-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence's saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them.

Single-Cell Sequencing for Drug Discovery and Drug Development.

PubMed

Wu, Hongjin; Wang, Charles; Wu, Shixiu

2017-01-01

Next-generation sequencing (NGS), particularly single-cell sequencing, has revolutionized the scale and scope of genomic and biomedical research. Recent technological advances in NGS and singlecell studies have made the deep whole-genome (DNA-seq), whole epigenome and whole-transcriptome sequencing (RNA-seq) at single-cell level feasible. NGS at the single-cell level expands our view of genome, epigenome and transcriptome and allows the genome, epigenome and transcriptome of any organism to be explored without a priori assumptions and with unprecedented throughput. And it does so with single-nucleotide resolution. NGS is also a very powerful tool for drug discovery and drug development. In this review, we describe the current state of single-cell sequencing techniques, which can provide a new, more powerful and precise approach for analyzing effects of drugs on treated cells and tissues. Our review discusses single-cell whole genome/exome sequencing (scWGS/scWES), single-cell transcriptome sequencing (scRNA-seq), single-cell bisulfite sequencing (scBS), and multiple omics of single-cell sequencing. We also highlight the advantages and challenges of each of these approaches. Finally, we describe, elaborate and speculate the potential applications of single-cell sequencing for drug discovery and drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Task 1.5 Genomic Shift and Drift Trends of Emerging Pathogens

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

Borucki, M

2010-01-05

The Lawrence Livermore National Laboratory (LLNL) Bioinformatics group has recently taken on a role in DTRA's Transformation Medical Technologies Initiative (TMTI). The high-level goal of TMTI is to accelerate the development of broad-spectrum countermeasures. To achieve those goals, TMTI has a near term need to conduct analyses of genomic shift and drift trends of emerging pathogens, with a focused eye on select agent pathogens, as well as antibiotic and virulence markers. Most emerging human pathogens are zoonotic viruses with a genome composed of RNA. The high mutation rate of the replication enzymes of RNA viruses contributes to sequence drift andmore » provides one mechanism for these viruses to adapt to diverse hosts (interspecies transmission events) and cause new human and zoonotic diseases. Additionally, new viral pathogens frequently emerge due to genetic shift (recombination and segment reassortment) which allows for dramatic genotypic and phenotypic changes to occur rapidly. Bacterial pathogens also evolve via genetic drift and shift, although sequence drift generally occurs at a much slower rate for bacteria as compared to RNA viruses. However, genetic shift such as lateral gene transfer and inter- and intragenomic recombination enables bacteria to rapidly acquire new mechanisms of survival and antibiotic resistance. New technologies such as rapid whole genome sequencing of bacterial genomes, ultra-deep sequencing of RNA virus populations, metagenomic studies of environments rich in antibiotic resistance genes, and the use of microarrays for the detection and characterization of emerging pathogens provide mechanisms to address the challenges posed by the rapid emergence of pathogens. Bioinformatic algorithms that enable efficient analysis of the massive amounts of data generated by these technologies as well computational modeling of protein structures and evolutionary processes need to be developed to allow the technology to fulfill its potential.« less

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.

Deep sequencing of the Trypanosoma cruzi GP63 surface proteases reveals diversity and diversifying selection among chronic and congenital Chagas disease patients.

PubMed

Llewellyn, Martin S; Messenger, Louisa A; Luquetti, Alejandro O; Garcia, Lineth; Torrico, Faustino; Tavares, Suelene B N; Cheaib, Bachar; Derome, Nicolas; Delepine, Marc; Baulard, Céline; Deleuze, Jean-Francois; Sauer, Sascha; Miles, Michael A

2015-04-01

Chagas disease results from infection with the diploid protozoan parasite Trypanosoma cruzi. T. cruzi is highly genetically diverse, and multiclonal infections in individual hosts are common, but little studied. In this study, we explore T. cruzi infection multiclonality in the context of age, sex and clinical profile among a cohort of chronic patients, as well as paired congenital cases from Cochabamba, Bolivia and Goias, Brazil using amplicon deep sequencing technology. A 450bp fragment of the trypomastigote TcGP63I surface protease gene was amplified and sequenced across 70 chronic and 22 congenital cases on the Illumina MiSeq platform. In addition, a second, mitochondrial target--ND5--was sequenced across the same cohort of cases. Several million reads were generated, and sequencing read depths were normalized within patient cohorts (Goias chronic, n = 43, Goias congenital n = 2, Bolivia chronic, n = 27; Bolivia congenital, n = 20), Among chronic cases, analyses of variance indicated no clear correlation between intra-host sequence diversity and age, sex or symptoms, while principal coordinate analyses showed no clustering by symptoms between patients. Between congenital pairs, we found evidence for the transmission of multiple sequence types from mother to infant, as well as widespread instances of novel genotypes in infants. Finally, non-synonymous to synonymous (dn:ds) nucleotide substitution ratios among sequences of TcGP63Ia and TcGP63Ib subfamilies within each cohort provided powerful evidence of strong diversifying selection at this locus. Our results shed light on the diversity of parasite DTUs within each patient, as well as the extent to which parasite strains pass between mother and foetus in congenital cases. Although we were unable to find any evidence that parasite diversity accumulates with age in our study cohorts, putative diversifying selection within members of the TcGP63I gene family suggests a link between genetic diversity within this gene family and survival in the mammalian host.

HSA: a heuristic splice alignment tool.

PubMed

Bu, Jingde; Chi, Xuebin; Jin, Zhong

2013-01-01

RNA-Seq methodology is a revolutionary transcriptomics sequencing technology, which is the representative of Next generation Sequencing (NGS). With the high throughput sequencing of RNA-Seq, we can acquire much more information like differential expression and novel splice variants from deep sequence analysis and data mining. But the short read length brings a great challenge to alignment, especially when the reads span two or more exons. A two steps heuristic splice alignment tool is generated in this investigation. First, map raw reads to reference with unspliced aligner--BWA; second, split initial unmapped reads into three equal short reads (seeds), align each seed to the reference, filter hits, search possible split position of read and extend hits to a complete match. Compare with other splice alignment tools like SOAPsplice and Tophat2, HSA has a better performance in call rate and efficiency, but its results do not as accurate as the other software to some extent. HSA is an effective spliced aligner of RNA-Seq reads mapping, which is available at https://github.com/vlcc/HSA.

Exploring single nucleotide polymorphism (SNP), microsatellite (SSR) and differentially expressed genes in the jellyfish (Rhopilema esculentum) by transcriptome sequencing.

PubMed

Li, Yunfeng; Zhou, Zunchun; Tian, Meilin; Tian, Yi; Dong, Ying; Li, Shilei; Liu, Weidong; He, Chongbo

2017-08-01

In this study, single nucleotide polymorphism (SNP), microsatellite (SSR) and differentially expressed genes (DEGs) in the oral parts, gonads, and umbrella parts of the jellyfish Rhopilema esculentum were analyzed by RNA-Seq technology. A total of 76.4 million raw reads and 72.1 million clean reads were generated from deep sequencing. Approximately 119,874 tentative unigenes and 149,239 transcripts were obtained. A total of 1,034,708 SNP markers were detected in the three tissues. For microsatellite mining, 5088 SSRs were identified from the unigene sequences. The most frequent repeat motifs were mononucleotide repeats, which accounted for 61.93%. Transcriptome comparison of the three tissues yielded a total of 8841 DEGs, of which 3560 were up-regulated and 5281 were down-regulated. This study represents the greatest sequencing effort carried out for a jellyfish and provides the first high-throughput transcriptomic resource for jellyfish. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Prediction of novel pre-microRNAs with high accuracy through boosting and SVM.

PubMed

Zhang, Yuanwei; Yang, Yifan; Zhang, Huan; Jiang, Xiaohua; Xu, Bo; Xue, Yu; Cao, Yunxia; Zhai, Qian; Zhai, Yong; Xu, Mingqing; Cooke, Howard J; Shi, Qinghua

2011-05-15

High-throughput deep-sequencing technology has generated an unprecedented number of expressed short sequence reads, presenting not only an opportunity but also a challenge for prediction of novel microRNAs. To verify the existence of candidate microRNAs, we have to show that these short sequences can be processed from candidate pre-microRNAs. However, it is laborious and time consuming to verify these using existing experimental techniques. Therefore, here, we describe a new method, miRD, which is constructed using two feature selection strategies based on support vector machines (SVMs) and boosting method. It is a high-efficiency tool for novel pre-microRNA prediction with accuracy up to 94.0% among different species. miRD is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/rpg/mird/mird.php.

Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.

PubMed

Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S

2012-01-01

RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

Evolution of simeprevir-resistant variants over time by ultra-deep sequencing in HCV genotype 1b.

PubMed

Akuta, Norio; Suzuki, Fumitaka; Sezaki, Hitomi; Suzuki, Yoshiyuki; Hosaka, Tetsuya; Kobayashi, Masahiro; Kobayashi, Mariko; Saitoh, Satoshi; Ikeda, Kenji; Kumada, Hiromitsu

2014-08-01

Using ultra-deep sequencing technology, the present study was designed to investigate the evolution of simeprevir-resistant variants (amino acid substitutions of aa80, aa155, aa156, and aa168 positions in HCV NS3 region) over time. In Toranomon Hospital, 18 Japanese patients infected with HCV genotype 1b, received triple therapy of simeprevir/PEG-IFN/ribavirin (DRAGON or CONCERT study). Sustained virological response rate was 67%, and that was significantly higher in patients with IL28B rs8099917 TT than in those with non-TT. Six patients, who did not achieve sustained virological response, were tested for resistant variants by ultra-deep sequencing, at the baseline, at the time of re-elevation of viral loads, and at 96 weeks after the completion of treatment. Twelve of 18 resistant variants, detected at re-elevation of viral load, were de novo resistant variants. Ten of 12 de novo resistant variants become undetectable over time, and that five of seven resistant variants, detected at baseline, persisted over time. In one patient, variants of Q80R at baseline (0.3%) increased at 96-week after the cessation of treatment (10.2%), and de novo resistant variants of D168E (0.3%) also increased at 96-week after the cessation of treatment (9.7%). In conclusion, the present study indicates that the emergence of simeprevir-resistant variants after the start of treatment could not be predicted at baseline, and the majority of de novo resistant variants become undetectable over time. Further large-scale prospective studies should be performed to investigate the clinical utility in detecting simeprevir-resistant variants. © 2014 Wiley Periodicals, Inc.

High-Throughput Sequencing Reveals Differential Expression of miRNAs in Intestine from Sea Cucumber during Aestivation

PubMed Central

Chen, Muyan; Zhang, Xiumei; Liu, Jianning; Storey, Kenneth B.

2013-01-01

The regulatory role of miRNA in gene expression is an emerging hot new topic in the control of hypometabolism. Sea cucumber aestivation is a complicated physiological process that includes obvious hypometabolism as evidenced by a decrease in the rates of oxygen consumption and ammonia nitrogen excretion, as well as a serious degeneration of the intestine into a very tiny filament. To determine whether miRNAs play regulatory roles in this process, the present study analyzed profiles of miRNA expression in the intestine of the sea cucumber (Apostichopus japonicus), using Solexa deep sequencing technology. We identified 308 sea cucumber miRNAs, including 18 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA) after at least 15 days of continuous torpor, were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to the active state). We identified 42 differentially expressed miRNAs [RPM (reads per million) >10, |FC| (|fold change|) ≥1, FDR (false discovery rate) <0.01] during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-200-3p, miR-2004, miR-2010, miR-22, miR-252a, miR-252a-3p and miR-92 were significantly over-expressed during deep aestivation compared with non-aestivation animals. Preliminary analyses of their putative target genes and GO analysis suggest that these miRNAs could play important roles in global transcriptional depression and cell differentiation during aestivation. High-throughput sequencing data and microarray data have been submitted to GEO database. PMID:24143179

Application of viromics: a new approach to the understanding of viral infections in humans.

PubMed

Ramamurthy, Mageshbabu; Sankar, Sathish; Kannangai, Rajesh; Nandagopal, Balaji; Sridharan, Gopalan

2017-12-01

This review is focused at exploring the strengths of modern technology driven data compiled in the areas of virus gene sequencing, virus protein structures and their implication to viral diagnosis and therapy. The information for virome analysis (viromics) is generated by the study of viral genomes (entire nucleotide sequence) and viral genes (coding for protein). Presently, the study of viral infectious diseases in terms of etiopathogenesis and development of newer therapeutics is undergoing rapid changes. Currently, viromics relies on deep sequencing, next generation sequencing (NGS) data and public domain databases like GenBank and unique virus specific databases. Two commonly used NGS platforms: Illumina and Ion Torrent, recommend maximum fragment lengths of about 300 and 400 nucleotides for analysis respectively. Direct detection of viruses in clinical samples is now evolving using these methods. Presently, there are a considerable number of good treatment options for HBV/HIV/HCV. These viruses however show development of drug resistance. The drug susceptibility regions of the genomes are sequenced and the prediction of drug resistance is now possible from 3 public domains available on the web. This has been made possible through advances in the technology with the advent of high throughput sequencing and meta-analysis through sophisticated and easy to use software and the use of high speed computers for bioinformatics. More recently NGS technology has been improved with single-molecule real-time sequencing. Here complete long reads can be obtained with less error overcoming a limitation of the NGS which is inherently prone to software anomalies that arise in the hands of personnel without adequate training. The development in understanding the viruses in terms of their genome, pathobiology, transcriptomics and molecular epidemiology constitutes viromics. It could be stated that these developments will bring about radical changes and advancement especially in the field of antiviral therapy and diagnostic virology.

Resequencing of the common marmoset genome improves genome assemblies and gene-coding sequence analysis.

PubMed

Sato, Kengo; Kuroki, Yoko; Kumita, Wakako; Fujiyama, Asao; Toyoda, Atsushi; Kawai, Jun; Iriki, Atsushi; Sasaki, Erika; Okano, Hideyuki; Sakakibara, Yasubumi

2015-11-20

The first draft of the common marmoset (Callithrix jacchus) genome was published by the Marmoset Genome Sequencing and Analysis Consortium. The draft was based on whole-genome shotgun sequencing, and the current assembly version is Callithrix_jacches-3.2.1, but there still exist 187,214 undetermined gap regions and supercontigs and relatively short contigs that are unmapped to chromosomes in the draft genome. We performed resequencing and assembly of the genome of common marmoset by deep sequencing with high-throughput sequencing technology. Several different sequence runs using Illumina sequencing platforms were executed, and 181 Gbp of high-quality bases including mate-pairs with long insert lengths of 3, 8, 20, and 40 Kbp were obtained, that is, approximately 60× coverage. The resequencing significantly improved the MGSAC draft genome sequence. The N50 of the contigs, which is a statistical measure used to evaluate assembly quality, doubled. As a result, 51% of the contigs (total length: 299 Mbp) that were unmapped to chromosomes in the MGSAC draft were merged with chromosomal contigs, and the improved genome sequence helped to detect 5,288 new genes that are homologous to human cDNAs and the gaps in 5,187 transcripts of the Ensembl gene annotations were completely filled.

Draft Genome Sequence of Deep-Sea Alteromonas sp. Strain V450 Isolated from the Marine Sponge Leiodermatium sp.

PubMed Central

Barrett, Nolan H.; McCarthy, Peter J.

2017-01-01

ABSTRACT The proteobacterium Alteromonas sp. strain V450 was isolated from the Atlantic deep-sea sponge Leiodermatium sp. Here, we report the draft genome sequence of this strain, with a genome size of approx. 4.39 Mb and a G+C content of 44.01%. The results will aid deep-sea microbial ecology, evolution, and sponge-microbe association studies. PMID:28153886

Identification of Prostate Cancer-Specific microDNAs

DTIC Science & Technology

2016-02-01

circular DNA by rolling circle amplification (RCA) and then amplified DNA fragments were subject to deep sequencing. Deep sequencing of the...demonstrate the existence of microDNAs in prostate cancer. We adopted multiple displacement amplification (MDA) with random 2 primers for enriched...prostate cancer cells through multiple displacement amplification and next generation sequencing. R e la ti v e c e ll g ro w th ( % ) 0 20

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.

An Efficient Strategy of Screening for Pathogens in Wild-Caught Ticks and Mosquitoes by Reusing Small RNA Deep Sequencing Data

PubMed Central

An, Xiaoping; Fan, Hang; Ma, Maijuan; Anderson, Benjamin D.; Jiang, Jiafu; Liu, Wei; Cao, Wuchun; Tong, Yigang

2014-01-01

This paper explored our hypothesis that sRNA (18∼30 bp) deep sequencing technique can be used as an efficient strategy to identify microorganisms other than viruses, such as prokaryotic and eukaryotic pathogens. In the study, the clean reads derived from the sRNA deep sequencing data of wild-caught ticks and mosquitoes were compared against the NCBI nucleotide collection (non-redundant nt database) using Blastn. The blast results were then analyzed with in-house Python scripts. An empirical formula was proposed to identify the putative pathogens. Results showed that not only viruses but also prokaryotic and eukaryotic species of interest can be screened out and were subsequently confirmed with experiments. Specially, a novel Rickettsia spp. was indicated to exist in Haemaphysalis longicornis ticks collected in Beijing. Our study demonstrated the reuse of sRNA deep sequencing data would have the potential to trace the origin of pathogens or discover novel agents of emerging/re-emerging infectious diseases. PMID:24618575

Draft Genome Sequence of Deep-Sea Alteromonas sp. Strain V450 Isolated from the Marine Sponge Leiodermatium sp.

PubMed

Wang, Guojun; Barrett, Nolan H; McCarthy, Peter J

2017-02-02

The proteobacterium Alteromonas sp. strain V450 was isolated from the Atlantic deep-sea sponge Leiodermatium sp. Here, we report the draft genome sequence of this strain, with a genome size of approx. 4.39 Mb and a G+C content of 44.01%. The results will aid deep-sea microbial ecology, evolution, and sponge-microbe association studies. Copyright © 2017 Wang et al.

The minimal amount of starting DNA for Agilent’s hybrid capture-based targeted massively parallel sequencing

PubMed Central

Chung, Jongsuk; Son, Dae-Soon; Jeon, Hyo-Jeong; Kim, Kyoung-Mee; Park, Gahee; Ryu, Gyu Ha; Park, Woong-Yang; Park, Donghyun

2016-01-01

Targeted capture massively parallel sequencing is increasingly being used in clinical settings, and as costs continue to decline, use of this technology may become routine in health care. However, a limited amount of tissue has often been a challenge in meeting quality requirements. To offer a practical guideline for the minimum amount of input DNA for targeted sequencing, we optimized and evaluated the performance of targeted sequencing depending on the input DNA amount. First, using various amounts of input DNA, we compared commercially available library construction kits and selected Agilent’s SureSelect-XT and KAPA Biosystems’ Hyper Prep kits as the kits most compatible with targeted deep sequencing using Agilent’s SureSelect custom capture. Then, we optimized the adapter ligation conditions of the Hyper Prep kit to improve library construction efficiency and adapted multiplexed hybrid selection to reduce the cost of sequencing. In this study, we systematically evaluated the performance of the optimized protocol depending on the amount of input DNA, ranging from 6.25 to 200 ng, suggesting the minimal input DNA amounts based on coverage depths required for specific applications. PMID:27220682

Status of duckweed genomics and transcriptomics.

PubMed

Wang, W; Messing, J

2015-01-01

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

Transcriptome sequences resolve deep relationships of the grape family.

PubMed

Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M; Gerrath, Jean; Zimmer, Elizabeth A; Fang, Xiao-Dong

2013-01-01

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

Discovery of a Novel Periodontal Disease-Associated Bacterium.

PubMed

Torres, Pedro J; Thompson, John; McLean, Jeffrey S; Kelley, Scott T; Edlund, Anna

2018-06-02

One of the world's most common infectious disease, periodontitis (PD), derives from largely uncharacterized communities of oral bacteria growing as biofilms (a.k.a. plaque) on teeth and gum surfaces in periodontal pockets. Bacteria associated with periodontal disease trigger inflammatory responses in immune cells, which in later stages of the disease cause loss of both soft and hard tissue structures supporting teeth. Thus far, only a handful of bacteria have been characterized as infectious agents of PD. Although deep sequencing technologies, such as whole community shotgun sequencing have the potential to capture a detailed picture of highly complex bacterial communities in any given environment, we still lack major reference genomes for the oral microbiome associated with PD and other diseases. In recent work, by using a combination of supervised machine learning and genome assembly, we identified a genome from a novel member of the Bacteroidetes phylum in periodontal samples. Here, by applying a comparative metagenomics read-classification approach, including 272 metagenomes from various human body sites, and our previously assembled draft genome of the uncultivated Candidatus Bacteroides periocalifornicus (CBP) bacterium, we show CBP's ubiquitous distribution in dental plaque, as well as its strong association with the well-known pathogenic "red complex" that resides in deep periodontal pockets.

Draft Genome Sequence of Pseudomonas oceani DSM 100277T, a Deep-Sea Bacterium

PubMed Central

2018-01-01

ABSTRACT Pseudomonas oceani DSM 100277T was isolated from deep seawater in the Okinawa Trough at 1390 m. P. oceani belongs to the Pseudomonas pertucinogena group. Here, we report the draft genome sequence of P. oceani, which has an estimated size of 4.1 Mb and exhibits 3,790 coding sequences, with a G+C content of 59.94 mol%. PMID:29650573

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks

PubMed Central

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2018-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence’s saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them. PMID:27896980

Aftershock occurrence rate decay for individual sequences and catalogs

NASA Astrophysics Data System (ADS)

Nyffenegger, Paul A.

One of the earliest observations of the Earth's seismicity is that the rate of aftershock occurrence decays with time according to a power law commonly known as modified Omori-law (MOL) decay. However, the physical reasons for aftershock occurrence and the empirical decay in rate remain unclear despite numerous models that yield similar rate decay behavior. Key problems in relating the observed empirical relationship to the physical conditions of the mainshock and fault are the lack of studies including small magnitude mainshocks and the lack of uniformity between studies. We use simulated aftershock sequences to investigate the factors which influence the maximum likelihood (ML) estimate of the Omori-law p value, the parameter describing aftershock occurrence rate decay, for both individual aftershock sequences and "stacked" or superposed sequences. Generally the ML estimate of p is accurate, but since the ML estimated uncertainty is unaffected by whether the sequence resembles an MOL model, a goodness-of-fit test such as the Anderson-Darling statistic is necessary. While stacking aftershock sequences permits the study of entire catalogs and sequences with small aftershock populations, stacking introduces artifacts. The p value for stacked sequences is approximately equal to the mean of the individual sequence p values. We apply single-link cluster analysis to identify all aftershock sequences from eleven regional seismicity catalogs. We observe two new mathematically predictable empirical relationships for the distribution of aftershock sequence populations. The average properties of aftershock sequences are not correlated with tectonic environment, but aftershock populations and p values do show a depth dependence. The p values show great variability with time, and large values or changes in p sometimes precedes major earthquakes. Studies of teleseismic earthquake catalogs over the last twenty years have led seismologists to question seismicity models and aftershock sequence decay for deep sequences. For seven exceptional deep sequences, we conclude that MOL decay adequately describes these sequences, and little difference exists compared to shallow sequences. However, they do include larger aftershock populations compared to most deep sequences. These results imply that p values for deep sequences are larger than those for intermediate depth sequences.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

PubMed

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

NASA Astrophysics Data System (ADS)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-01

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

PubMed

Jones, David T; Kandathil, Shaun M

2018-04-26

In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-residue contacts, such as solvent accessibility, predicted secondary structure, and scores from other contact prediction methods. It is unclear how much of this information is needed to achieve state-of-the-art results. Here, we show that using deep neural network models, simple alignment statistics contain sufficient information to achieve state-of-the-art precision. Our prediction method, DeepCov, uses fully convolutional neural networks operating on amino-acid pair frequency or covariance data derived directly from sequence alignments, without using global statistical methods such as sparse inverse covariance or pseudolikelihood estimation. Comparisons against CCMpred and MetaPSICOV2 show that using pairwise covariance data calculated from raw alignments as input allows us to match or exceed the performance of both of these methods. Almost all of the achieved precision is obtained when considering relatively local windows (around 15 residues) around any member of a given residue pairing; larger window sizes have comparable performance. Assessment on a set of shallow sequence alignments (fewer than 160 effective sequences) indicates that the new method is substantially more precise than CCMpred and MetaPSICOV2 in this regime, suggesting that improved precision is attainable on smaller sequence families. Overall, the performance of DeepCov is competitive with the state of the art, and our results demonstrate that global models, which employ features from all parts of the input alignment when predicting individual contacts, are not strictly needed in order to attain precise contact predictions. DeepCov is freely available at https://github.com/psipred/DeepCov. d.t.jones@ucl.ac.uk.

Deep Impact Sequence Planning Using Multi-Mission Adaptable Planning Tools With Integrated Spacecraft Models

NASA Technical Reports Server (NTRS)

Wissler, Steven S.; Maldague, Pierre; Rocca, Jennifer; Seybold, Calina

2006-01-01

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

Transcriptome Sequences Resolve Deep Relationships of the Grape Family

PubMed Central

Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M.; Gerrath, Jean; Zimmer, Elizabeth A.; Fang, Xiao-Dong

2013-01-01

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated. PMID:24069307

Mars Exploration 2003 to 2013 - An Integrated Perspective: Time Sequencing the Missions

NASA Technical Reports Server (NTRS)

Briggs, G.; McKay, C.

2000-01-01

The science goals for the Mars exploration program, together with the HEDS precursor environmental and technology needs, serve as a solid starting point for re-planning the program in an orderly way. Most recently, the community has recognized the significance of subsurface sampling as a key component in "following the water". Accessing samples from hundreds and even thousands of meters beneath the surface is a challenge that will call for technology development and for one or more demonstration missions. Recent mission failures and concerns about the complexity of the previously planned MSR missions indicate that, before we are ready to undertake sample return and deep sampling, the Mars exploration program needs to include: 1) technology development missions; and 2) basic landing site assessment missions. These precursor missions should demonstrate the capability for reliable & accurate soft landing and in situ propellant production. The precursor missions will need to carry out close-up site observations, ground-penetrating radar mapping from orbit and conduct seismic surveys. Clearly the programs should be planned as a single, continuous exploration effort. A prudent minimum list of missions, including surface rovers with ranges of more than 10 km, can be derived from the numerous goals and requirements; they can be sequenced in an orderly way to ensure that time is available to feed forward the results of the precursor missions. One such sequence of missions is proposed for the decade beginning in 2003.

Emergent HIV-1 Drug Resistance Mutations Were Not Present at Low-Frequency at Baseline in Non-Nucleoside Reverse Transcriptase Inhibitor-Treated Subjects in the STaR Study

PubMed Central

Porter, Danielle P.; Daeumer, Martin; Thielen, Alexander; Chang, Silvia; Martin, Ross; Cohen, Cal; Miller, Michael D.; White, Kirsten L.

2015-01-01

At Week 96 of the Single-Tablet Regimen (STaR) study, more treatment-naïve subjects that received rilpivirine/emtricitabine/tenofovir DF (RPV/FTC/TDF) developed resistance mutations compared to those treated with efavirenz (EFV)/FTC/TDF by population sequencing. Furthermore, more RPV/FTC/TDF-treated subjects with baseline HIV-1 RNA >100,000 copies/mL developed resistance compared to subjects with baseline HIV-1 RNA ≤100,000 copies/mL. Here, deep sequencing was utilized to assess the presence of pre-existing low-frequency variants in subjects with and without resistance development in the STaR study. Deep sequencing (Illumina MiSeq) was performed on baseline and virologic failure samples for all subjects analyzed for resistance by population sequencing during the clinical study (n = 33), as well as baseline samples from control subjects with virologic response (n = 118). Primary NRTI or NNRTI drug resistance mutations present at low frequency (≥2% to 20%) were detected in 6.6% of baseline samples by deep sequencing, all of which occurred in control subjects. Deep sequencing results were generally consistent with population sequencing but detected additional primary NNRTI and NRTI resistance mutations at virologic failure in seven samples. HIV-1 drug resistance mutations emerging while on RPV/FTC/TDF or EFV/FTC/TDF treatment were not present at low frequency at baseline in the STaR study. PMID:26690199

Emergent HIV-1 Drug Resistance Mutations Were Not Present at Low-Frequency at Baseline in Non-Nucleoside Reverse Transcriptase Inhibitor-Treated Subjects in the STaR Study.

PubMed

Porter, Danielle P; Daeumer, Martin; Thielen, Alexander; Chang, Silvia; Martin, Ross; Cohen, Cal; Miller, Michael D; White, Kirsten L

2015-12-07

At Week 96 of the Single-Tablet Regimen (STaR) study, more treatment-naïve subjects that received rilpivirine/emtricitabine/tenofovir DF (RPV/FTC/TDF) developed resistance mutations compared to those treated with efavirenz (EFV)/FTC/TDF by population sequencing. Furthermore, more RPV/FTC/TDF-treated subjects with baseline HIV-1 RNA >100,000 copies/mL developed resistance compared to subjects with baseline HIV-1 RNA ≤100,000 copies/mL. Here, deep sequencing was utilized to assess the presence of pre-existing low-frequency variants in subjects with and without resistance development in the STaR study. Deep sequencing (Illumina MiSeq) was performed on baseline and virologic failure samples for all subjects analyzed for resistance by population sequencing during the clinical study (n = 33), as well as baseline samples from control subjects with virologic response (n = 118). Primary NRTI or NNRTI drug resistance mutations present at low frequency (≥2% to 20%) were detected in 6.6% of baseline samples by deep sequencing, all of which occurred in control subjects. Deep sequencing results were generally consistent with population sequencing but detected additional primary NNRTI and NRTI resistance mutations at virologic failure in seven samples. HIV-1 drug resistance mutations emerging while on RPV/FTC/TDF or EFV/FTC/TDF treatment were not present at low frequency at baseline in the STaR study.

VirusDetect: An automated pipeline for efficient virus discovery using deep sequencing of small RNAs

USDA-ARS?s Scientific Manuscript database

Accurate detection of viruses in plants and animals is critical for agriculture production and human health. Deep sequencing and assembly of virus-derived siRNAs has proven to be a highly efficient approach for virus discovery. However, to date no computational tools specifically designed for both k...

Natural Variation in Brachypodium disctachyon: Deep Sequencing of Highly Diverse Natural Accessions (2013 DOE JGI Genomics of Energy and Environment 8th Annual User Meeting)

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

Gordon, Sean

2013-03-01

Sean Gordon of the USDA on Natural variation in Brachypodium disctachyon: Deep Sequencing of Highly Diverse Natural Accessions at the 8th Annual Genomics of Energy Environment Meeting on March 27, 2013 in Walnut Creek, CA.

Microbial Diversity in Deep-sea Methane Seep Sediments Presented by SSU rRNA Gene Tag Sequencing

PubMed Central

Nunoura, Takuro; Takaki, Yoshihiro; Kazama, Hiromi; Hirai, Miho; Ashi, Juichiro; Imachi, Hiroyuki; Takai, Ken

2012-01-01

Microbial community structures in methane seep sediments in the Nankai Trough were analyzed by tag-sequencing analysis for the small subunit (SSU) rRNA gene using a newly developed primer set. The dominant members of Archaea were Deep-sea Hydrothermal Vent Euryarchaeotic Group 6 (DHVEG 6), Marine Group I (MGI) and Deep Sea Archaeal Group (DSAG), and those in Bacteria were Alpha-, Gamma-, Delta- and Epsilonproteobacteria, Chloroflexi, Bacteroidetes, Planctomycetes and Acidobacteria. Diversity and richness were examined by 8,709 and 7,690 tag-sequences from sediments at 5 and 25 cm below the seafloor (cmbsf), respectively. The estimated diversity and richness in the methane seep sediment are as high as those in soil and deep-sea hydrothermal environments, although the tag-sequences obtained in this study were not sufficient to show whole microbial diversity in this analysis. We also compared the diversity and richness of each taxon/division between the sediments from the two depths, and found that the diversity and richness of some taxa/divisions varied significantly along with the depth. PMID:22510646

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Draft Genome Sequence of Pseudomonas oceani DSM 100277T, a Deep-Sea Bacterium.

PubMed

García-Valdés, Elena; Gomila, Margarita; Mulet, Magdalena; Lalucat, Jorge

2018-04-12

Pseudomonas oceani DSM 100277 T was isolated from deep seawater in the Okinawa Trough at 1390 m. P. oceani belongs to the Pseudomonas pertucinogena group. Here, we report the draft genome sequence of P. oceani , which has an estimated size of 4.1 Mb and exhibits 3,790 coding sequences, with a G+C content of 59.94 mol%. Copyright © 2018 García-Valdés et al.

Deep Ion Torrent sequencing identifies soil fungal community shifts after frequent prescribed fires in a southeastern US forest ecosystem.

PubMed

Brown, Shawn P; Callaham, Mac A; Oliver, Alena K; Jumpponen, Ari

2013-12-01

Prescribed burning is a common management tool to control fuel loads, ground vegetation, and facilitate desirable game species. We evaluated soil fungal community responses to long-term prescribed fire treatments in a loblolly pine forest on the Piedmont of Georgia and utilized deep Internal Transcribed Spacer Region 1 (ITS1) amplicon sequencing afforded by the recent Ion Torrent Personal Genome Machine (PGM). These deep sequence data (19,000 + reads per sample after subsampling) indicate that frequent fires (3-year fire interval) shift soil fungus communities, whereas infrequent fires (6-year fire interval) permit system resetting to a state similar to that without prescribed fire. Furthermore, in nonmetric multidimensional scaling analyses, primarily ectomycorrhizal taxa were correlated with axes associated with long fire intervals, whereas soil saprobes tended to be correlated with the frequent fire recurrence. We conclude that (1) multiplexed Ion Torrent PGM analyses allow deep cost effective sequencing of fungal communities but may suffer from short read lengths and inconsistent sequence quality adjacent to the sequencing adaptor; (2) frequent prescribed fires elicit a shift in soil fungal communities; and (3) such shifts do not occur when fire intervals are longer. Our results emphasize the general responsiveness of these forests to management, and the importance of fire return intervals in meeting management objectives. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

RNA-Seq analysis to capture the transcriptome landscape of a single cell

PubMed Central

Tang, Fuchou; Barbacioru, Catalin; Nordman, Ellen; Xu, Nanlan; Bashkirov, Vladimir I; Lao, Kaiqin; Surani, M. Azim

2013-01-01

We describe here a protocol for digital transcriptome analysis in a single mouse blastomere using a deep sequencing approach. An individual blastomere was first isolated and put into lysate buffer by mouth pipette. Reverse transcription was then performed directly on the whole cell lysate. After this, the free primers were removed by Exonuclease I and a poly(A) tail was added to the 3′ end of the first-strand cDNA by Terminal Deoxynucleotidyl Transferase. Then the single cell cDNAs were amplified by 20 plus 9 cycles of PCR. Then 100-200 ng of these amplified cDNAs were used to construct a sequencing library. The sequencing library can be used for deep sequencing using the SOLiD system. Compared with the cDNA microarray technique, our assay can capture up to 75% more genes expressed in early embryos. The protocol can generate deep sequencing libraries within 6 days for 16 single cell samples. PMID:20203668

Deep sequencing reveals double mutations in cis of MPL exon 10 in myeloproliferative neoplasms.

PubMed

Pietra, Daniela; Brisci, Angela; Rumi, Elisa; Boggi, Sabrina; Elena, Chiara; Pietrelli, Alessandro; Bordoni, Roberta; Ferrari, Maurizio; Passamonti, Francesco; De Bellis, Gianluca; Cremonesi, Laura; Cazzola, Mario

2011-04-01

Somatic mutations of MPL exon 10, mainly involving a W515 substitution, have been described in JAK2 (V617F)-negative patients with essential thrombocythemia and primary myelofibrosis. We used direct sequencing and high-resolution melt analysis to identify mutations of MPL exon 10 in 570 patients with myeloproliferative neoplasms, and allele specific PCR and deep sequencing to further characterize a subset of mutated patients. Somatic mutations were detected in 33 of 221 patients (15%) with JAK2 (V617F)-negative essential thrombocythemia or primary myelofibrosis. Only one patient with essential thrombocythemia carried both JAK2 (V617F) and MPL (W515L). High-resolution melt analysis identified abnormal patterns in all the MPL mutated cases, while direct sequencing did not detect the mutant MPL in one fifth of them. In 3 cases carrying double MPL mutations, deep sequencing analysis showed identical load and location in cis of the paired lesions, indicating their simultaneous occurrence on the same chromosome.

A growth path for deep space communications

NASA Technical Reports Server (NTRS)

Layland, J. W.; Smith, J. G.

1987-01-01

Increased Deep Space Network (DPN) receiving capability far beyond that now available for Voyager is achievable through a mix of increased antenna aperture and increased frequency of operation. In this note a sequence of options are considered: adding midsized antennas for arraying with the existing network at X-band; converting to Ka-band and adding array elements; augmenting the DSN with an orbiting Ka-band station; and augmenting the DSN with an optical receiving capability, either on the ground or in space. Costs of these options are compared as means of achieving significantly increased receiving capability. The envelope of lowest costs projects a possible path for moving from X-band to Ka-band and thence to optical frequencies, and potentially for moving from ground-based to space-based apertures. The move to Ka-band is clearly of value now, with development of optical communications technology a good investment for the future.

2016 Year in Review Video- NASA’s Marshall Space Flight Center

NASA Image and Video Library

2016-12-22

The work underway today at NASA’s Marshall Space Flight Center is making it possible to send humans beyond Earth’s orbit and into deep space on bold new missions of space exploration. Marshall teams are designing and building NASA’s Space Launch System, the most powerful rocket ever built and the only launch vehicle capable of launching human explorers to Mars. Using the International Space Station’s orbiting lab, Marshall flight controllers provided round-the-clock oversight of science experiments, supporting the first-ever DNA sequencing in space, pioneering 3-D printing capabilities and advancing human health research. Several successful New Frontiers deep-space robotic missions including OSIRIS-REx, New Horizons and Juno, made new discoveries and refined theories of the solar system. And Marshall collaborations with outside partners are yielding innovative technologies and solving technical challenges that are making the Journey to Mars a reality.

Context and Deep Learning Design

ERIC Educational Resources Information Center

Boyle, Tom; Ravenscroft, Andrew

2012-01-01

Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across…

A Phylogenomic Perspective on the Radiation of Ray-Finned Fishes Based upon Targeted Sequencing of Ultraconserved Elements (UCEs)

PubMed Central

Sorenson, Laurie; Santini, Francesco

2013-01-01

Ray-finned fishes constitute the dominant radiation of vertebrates with over 32,000 species. Although molecular phylogenetics has begun to disentangle major evolutionary relationships within this vast section of the Tree of Life, there is no widely available approach for efficiently collecting phylogenomic data within fishes, leaving much of the enormous potential of massively parallel sequencing technologies for resolving major radiations in ray-finned fishes unrealized. Here, we provide a genomic perspective on longstanding questions regarding the diversification of major groups of ray-finned fishes through targeted enrichment of ultraconserved nuclear DNA elements (UCEs) and their flanking sequence. Our workflow efficiently and economically generates data sets that are orders of magnitude larger than those produced by traditional approaches and is well-suited to working with museum specimens. Analysis of the UCE data set recovers a well-supported phylogeny at both shallow and deep time-scales that supports a monophyletic relationship between Amia and Lepisosteus (Holostei) and reveals elopomorphs and then osteoglossomorphs to be the earliest diverging teleost lineages. Our approach additionally reveals that sequence capture of UCE regions and their flanking sequence offers enormous potential for resolving phylogenetic relationships within ray-finned fishes. PMID:23824177

Deep Sequencing of the Trypanosoma cruzi GP63 Surface Proteases Reveals Diversity and Diversifying Selection among Chronic and Congenital Chagas Disease Patients

PubMed Central

Llewellyn, Martin S.; Messenger, Louisa A.; Luquetti, Alejandro O.; Garcia, Lineth; Torrico, Faustino; Tavares, Suelene B. N.; Cheaib, Bachar; Derome, Nicolas; Delepine, Marc; Baulard, Céline; Deleuze, Jean-Francois; Sauer, Sascha; Miles, Michael A.

2015-01-01

Background Chagas disease results from infection with the diploid protozoan parasite Trypanosoma cruzi. T. cruzi is highly genetically diverse, and multiclonal infections in individual hosts are common, but little studied. In this study, we explore T. cruzi infection multiclonality in the context of age, sex and clinical profile among a cohort of chronic patients, as well as paired congenital cases from Cochabamba, Bolivia and Goias, Brazil using amplicon deep sequencing technology. Methodology/ Principal Findings A 450bp fragment of the trypomastigote TcGP63I surface protease gene was amplified and sequenced across 70 chronic and 22 congenital cases on the Illumina MiSeq platform. In addition, a second, mitochondrial target—ND5—was sequenced across the same cohort of cases. Several million reads were generated, and sequencing read depths were normalized within patient cohorts (Goias chronic, n = 43, Goias congenital n = 2, Bolivia chronic, n = 27; Bolivia congenital, n = 20), Among chronic cases, analyses of variance indicated no clear correlation between intra-host sequence diversity and age, sex or symptoms, while principal coordinate analyses showed no clustering by symptoms between patients. Between congenital pairs, we found evidence for the transmission of multiple sequence types from mother to infant, as well as widespread instances of novel genotypes in infants. Finally, non-synonymous to synonymous (dn:ds) nucleotide substitution ratios among sequences of TcGP63Ia and TcGP63Ib subfamilies within each cohort provided powerful evidence of strong diversifying selection at this locus. Conclusions/Significance Our results shed light on the diversity of parasite DTUs within each patient, as well as the extent to which parasite strains pass between mother and foetus in congenital cases. Although we were unable to find any evidence that parasite diversity accumulates with age in our study cohorts, putative diversifying selection within members of the TcGP63I gene family suggests a link between genetic diversity within this gene family and survival in the mammalian host. PMID:25849488

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

PubMed

Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei

2017-09-01

Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.

RaptorX-Property: a web server for protein structure property prediction.

PubMed

Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo

2016-07-08

RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of ribonucleotide reductase mutation causing temperature-sensitivity of herpes simplex virus isolates from whitlow by deep sequencing.

PubMed

Daikoku, Tohru; Oyama, Yukari; Yajima, Misako; Sekizuka, Tsuyoshi; Kuroda, Makoto; Shimada, Yuka; Takehara, Kazuhiko; Miwa, Naoko; Okuda, Tomoko; Sata, Tetsutaro; Shiraki, Kimiyasu

2015-06-01

Herpes simplex virus 2 caused a genital ulcer, and a secondary herpetic whitlow appeared during acyclovir therapy. The secondary and recurrent whitlow isolates were acyclovir-resistant and temperature-sensitive in contrast to a genital isolate. We identified the ribonucleotide reductase mutation responsible for temperature-sensitivity by deep-sequencing analysis.

Comparative genomics approach to detecting split-coding regions in a low-coverage genome: lessons from the chimaera Callorhinchus milii (Holocephali, Chondrichthyes).

PubMed

Dessimoz, Christophe; Zoller, Stefan; Manousaki, Tereza; Qiu, Huan; Meyer, Axel; Kuraku, Shigehiro

2011-09-01

Recent development of deep sequencing technologies has facilitated de novo genome sequencing projects, now conducted even by individual laboratories. However, this will yield more and more genome sequences that are not well assembled, and will hinder thorough annotation when no closely related reference genome is available. One of the challenging issues is the identification of protein-coding sequences split into multiple unassembled genomic segments, which can confound orthology assignment and various laboratory experiments requiring the identification of individual genes. In this study, using the genome of a cartilaginous fish, Callorhinchus milii, as test case, we performed gene prediction using a model specifically trained for this genome. We implemented an algorithm, designated ESPRIT, to identify possible linkages between multiple protein-coding portions derived from a single genomic locus split into multiple unassembled genomic segments. We developed a validation framework based on an artificially fragmented human genome, improvements between early and recent mouse genome assemblies, comparison with experimentally validated sequences from GenBank, and phylogenetic analyses. Our strategy provided insights into practical solutions for efficient annotation of only partially sequenced (low-coverage) genomes. To our knowledge, our study is the first formulation of a method to link unassembled genomic segments based on proteomes of relatively distantly related species as references.

Comparative genomics approach to detecting split-coding regions in a low-coverage genome: lessons from the chimaera Callorhinchus milii (Holocephali, Chondrichthyes)

PubMed Central

Zoller, Stefan; Manousaki, Tereza; Qiu, Huan; Meyer, Axel; Kuraku, Shigehiro

2011-01-01

Recent development of deep sequencing technologies has facilitated de novo genome sequencing projects, now conducted even by individual laboratories. However, this will yield more and more genome sequences that are not well assembled, and will hinder thorough annotation when no closely related reference genome is available. One of the challenging issues is the identification of protein-coding sequences split into multiple unassembled genomic segments, which can confound orthology assignment and various laboratory experiments requiring the identification of individual genes. In this study, using the genome of a cartilaginous fish, Callorhinchus milii, as test case, we performed gene prediction using a model specifically trained for this genome. We implemented an algorithm, designated ESPRIT, to identify possible linkages between multiple protein-coding portions derived from a single genomic locus split into multiple unassembled genomic segments. We developed a validation framework based on an artificially fragmented human genome, improvements between early and recent mouse genome assemblies, comparison with experimentally validated sequences from GenBank, and phylogenetic analyses. Our strategy provided insights into practical solutions for efficient annotation of only partially sequenced (low-coverage) genomes. To our knowledge, our study is the first formulation of a method to link unassembled genomic segments based on proteomes of relatively distantly related species as references. PMID:21712341

Strain-Level Diversity of Secondary Metabolism in Streptomyces albus

PubMed Central

Seipke, Ryan F.

2015-01-01

Streptomyces spp. are robust producers of medicinally-, industrially- and agriculturally-important small molecules. Increased resistance to antibacterial agents and the lack of new antibiotics in the pipeline have led to a renaissance in natural product discovery. This endeavor has benefited from inexpensive high quality DNA sequencing technology, which has generated more than 140 genome sequences for taxonomic type strains and environmental Streptomyces spp. isolates. Many of the sequenced streptomycetes belong to the same species. For instance, Streptomyces albus has been isolated from diverse environmental niches and seven strains have been sequenced, consequently this species has been sequenced more than any other streptomycete, allowing valuable analyses of strain-level diversity in secondary metabolism. Bioinformatics analyses identified a total of 48 unique biosynthetic gene clusters harboured by Streptomyces albus strains. Eighteen of these gene clusters specify the core secondary metabolome of the species. Fourteen of the gene clusters are contained by one or more strain and are considered auxiliary, while 16 of the gene clusters encode the production of putative strain-specific secondary metabolites. Analysis of Streptomyces albus strains suggests that each strain of a Streptomyces species likely harbours at least one strain-specific biosynthetic gene cluster. Importantly, this implies that deep sequencing of a species will not exhaust gene cluster diversity and will continue to yield novelty. PMID:25635820

Low Gravity Issues of Deep Space Refueling

NASA Technical Reports Server (NTRS)

Chato, David J.

2005-01-01

This paper discusses the technologies required to develop deep space refueling of cryogenic propellants and low cost flight experiments to develop them. Key technologies include long term storage, pressure control, mass gauging, liquid acquisition, and fluid transfer. Prior flight experiments used to mature technologies are discussed. A plan is presented to systematically study the deep space refueling problem and devise low-cost experiments to further mature technologies and prepare for full scale flight demonstrations.

The gut microbiota, environment and diseases of modern society

PubMed Central

Kelsen, Judith R.; Wu, Gary D.

2012-01-01

The human gut microbiota is a complex community that provides important metabolic functions to the host. Consequently, alterations in the gut microbiota have been associated with the pathogenesis of several human diseases associated with a disturbance in metabolism, particularly those that have been increasing in incidence over the last several decades including obesity, diabetes and atherosclerosis. In this review, we explore how advances in deep DNA sequencing technology have provided us a greater understanding of the factors that influence that composition of the gut microbiota and its possible links to the pathogenesis of these diseases. PMID:22825455

The gut microbiota, environment and diseases of modern society.

PubMed

Kelsen, Judith R; Wu, Gary D

2012-01-01

The human gut microbiota is a complex community that provides important metabolic functions to the host. Consequently, alterations in the gut microbiota have been associated with the pathogenesis of several human diseases associated with a disturbance in metabolism, particularly those that have been increasing in incidence over the last several decades including obesity, diabetes and atherosclerosis. In this review, we explore how advances in deep DNA sequencing technology have provided us a greater understanding of the factors that influence that composition of the gut microbiota and its possible links to the pathogenesis of these diseases.

Expedition 48/49 crew visit to MSFC

NASA Image and Video Library

2017-04-06

NASA astronaut Kate Rubins presents highlights from Expedition 48/49, her mission to the International Space Station, to team members and Space Camp students from the U.S. Space & Rocket Center in Huntsville, April 6 at NASA's Marshall Space Flight Center. During her mission, Rubins became the first person to sequence DNA in space, researching technology development for deep-space exploration by humans, Earth and space science. She also conducted two spacewalks, in which she and NASA astronaut Jeff Williams installed an International Docking Adapter and performed maintenance of the station's external thermal control system and installed high-definition cameras.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

PubMed

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A; Larsen, Martin Jakob

2016-01-01

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data

PubMed Central

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A.; Larsen, Martin Jakob

2016-01-01

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths. PMID:27002637

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

PubMed Central

Avsec, Žiga; Cheng, Jun; Gagneur, Julien

2018-01-01

Abstract Motivation Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the approach of choice for modeling regulatory sequences because of its strength to learn complex sequence features. However, modeling relative distances to genomic landmarks in deep neural networks has not been addressed. Results Here we developed spline transformation, a neural network module based on splines to flexibly and robustly model distances. Modeling distances to various genomic landmarks with spline transformations significantly increased state-of-the-art prediction accuracy of in vivo RNA-binding protein binding sites for 120 out of 123 proteins. We also developed a deep neural network for human splice branchpoint based on spline transformations that outperformed the current best, already distance-based, machine learning model. Compared to piecewise linear transformation, as obtained by composition of rectified linear units, spline transformation yields higher prediction accuracy as well as faster and more robust training. As spline transformation can be applied to further quantities beyond distances, such as methylation or conservation, we foresee it as a versatile component in the genomics deep learning toolbox. Availability and implementation Spline transformation is implemented as a Keras layer in the CONCISE python package: https://github.com/gagneurlab/concise. Analysis code is available at https://github.com/gagneurlab/Manuscript_Avsec_Bioinformatics_2017. Contact avsec@in.tum.de or gagneur@in.tum.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29155928

Autonomous Science Operations Technologies for Deep Space Gateway

NASA Astrophysics Data System (ADS)

Barnes, P. K.; Haddock, A. T.; Cruzen, C. A.

2018-02-01

Autonomous Science Operations Technologies for Deep Space Gateway (DSG) is an overview of how the DSG would benefit from autonomous systems utilizing proven technologies performing telemetry monitoring and science operations.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

PubMed

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Large-scale identification and comparative analysis of miRNA expression profile in the respiratory tree of the sea cucumber Apostichopus japonicus during aestivation.

PubMed

Chen, Muyan; Storey, Kenneth B

2014-02-01

The sea cucumber Apostichopus japonicus withstands high water temperatures in the summer by suppressing its metabolic rate and entering a state of aestivation. We hypothesized that changes in the expression of miRNAs could provide important post-transcriptional regulation of gene expression during hypometabolism via control over mRNA translation. The present study analyzed profiles of miRNA expression in the sea cucumber respiratory tree using Solexa deep sequencing technology. We identified 279 sea cucumber miRNAs, including 15 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA; after at least 15 days of continuous torpor) were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to an active state). We identified 30 differentially expressed miRNAs ([RPM (reads per million) >10, |FC| (|fold change|)≥1, FDR (false discovery rate)<0.01]) during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-124, miR-124-3p, miR-79, miR-9 and miR-2010 were significantly over-expressed during deep aestivation compared with non-aestivation animals, suggesting that these miRNAs may play important roles in metabolic rate suppression during aestivation. High-throughput sequencing data and microarray data have been submitted to the GEO database with accession number: 16902695. Copyright © 2014 Elsevier B.V. All rights reserved.

Genome-Wide Identification of miRNAs Responsive to Drought in Peach (Prunus persica) by High-Throughput Deep Sequencing

PubMed Central

Eldem, Vahap; Çelikkol Akçay, Ufuk; Ozhuner, Esma; Bakır, Yakup; Uranbey, Serkan; Unver, Turgay

2012-01-01

Peach (Prunus persica L.) is one of the most important worldwide fresh fruits. Since fruit growth largely depends on adequate water supply, drought stress is considered as the most important abiotic stress limiting fleshy fruit production and quality in peach. Plant responses to drought stress are regulated both at transcriptional and post-transcriptional level. As post-transcriptional gene regulators, miRNAs (miRNAs) are small (19–25 nucleotides in length), endogenous, non-coding RNAs. Recent studies indicate that miRNAs are involved in plant responses to drought. Therefore, Illumina deep sequencing technology was used for genome-wide identification of miRNAs and their expression profile in response to drought in peach. In this study, four sRNA libraries were constructed from leaf control (LC), leaf stress (LS), root control (RC) and root stress (RS) samples. We identified a total of 531, 471, 535 and 487 known mature miRNAs in LC, LS, RC and RS libraries, respectively. The expression level of 262 (104 up-regulated, 158 down-regulated) of the 453 miRNAs changed significantly in leaf tissue, whereas 368 (221 up-regulated, 147 down-regulated) of the 465 miRNAs had expression levels that changed significantly in root tissue upon drought stress. Additionally, a total of 197, 221, 238 and 265 novel miRNA precursor candidates were identified from LC, LS, RC and RS libraries, respectively. Target transcripts (137 for LC, 133 for LS, 148 for RC and 153 for RS) generated significant Gene Ontology (GO) terms related to DNA binding and catalytic activites. Genome-wide miRNA expression analysis of peach by deep sequencing approach helped to expand our understanding of miRNA function in response to drought stress in peach and Rosaceae. A set of differentially expressed miRNAs could pave the way for developing new strategies to alleviate the adverse effects of drought stress on plant growth and development. PMID:23227166

Fungal diversity in deep-sea sediments of a hydrothermal vent system in the Southwest Indian Ridge

NASA Astrophysics Data System (ADS)

Xu, Wei; Gong, Lin-feng; Pang, Ka-Lai; Luo, Zhu-Hua

2018-01-01

Deep-sea hydrothermal sediment is known to support remarkably diverse microbial consortia. In deep sea environments, fungal communities remain less studied despite their known taxonomic and functional diversity. High-throughput sequencing methods have augmented our capacity to assess eukaryotic diversity and their functions in microbial ecology. Here we provide the first description of the fungal community diversity found in deep sea sediments collected at the Southwest Indian Ridge (SWIR) using culture-dependent and high-throughput sequencing approaches. A total of 138 fungal isolates were cultured from seven different sediment samples using various nutrient media, and these isolates were identified to 14 fungal taxa, including 11 Ascomycota taxa (7 genera) and 3 Basidiomycota taxa (2 genera) based on internal transcribed spacers (ITS1, ITS2 and 5.8S) of rDNA. Using illumina HiSeq sequencing, a total of 757,467 fungal ITS2 tags were recovered from the samples and clustered into 723 operational taxonomic units (OTUs) belonging to 79 taxa (Ascomycota and Basidiomycota contributed to 99% of all samples) based on 97% sequence similarity. Results from both approaches suggest that there is a high fungal diversity in the deep-sea sediments collected in the SWIR and fungal communities were shown to be slightly different by location, although all were collected from adjacent sites at the SWIR. This study provides baseline data of the fungal diversity and biogeography, and a glimpse to the microbial ecology associated with the deep-sea sediments of the hydrothermal vent system of the Southwest Indian Ridge.

Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape.

PubMed

Dai, Hanjun; Umarov, Ramzan; Kuwahara, Hiroyuki; Li, Yu; Song, Le; Gao, Xin

2017-11-15

An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these hidden Markov models into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA datasets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods. Our program is freely available at https://github.com/ramzan1990/sequence2vec. xin.gao@kaust.edu.sa or lsong@cc.gatech.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Advanced Microelectronics Technologies for Future Small Satellite Systems

NASA Technical Reports Server (NTRS)

Alkalai, Leon

1999-01-01

Future small satellite systems for both Earth observation as well as deep-space exploration are greatly enabled by the technological advances in deep sub-micron microelectronics technologies. Whereas these technological advances are being fueled by the commercial (non-space) industries, more recently there has been an exciting new synergism evolving between the two otherwise disjointed markets. In other words, both the commercial and space industries are enabled by advances in low-power, highly integrated, miniaturized (low-volume), lightweight, and reliable real-time embedded systems. Recent announcements by commercial semiconductor manufacturers to introduce Silicon On Insulator (SOI) technology into their commercial product lines is driven by the need for high-performance low-power integrated devices. Moreover, SOI has been the technology of choice for many space semiconductor manufacturers where radiation requirements are critical. This technology has inherent radiation latch-up immunity built into the process, which makes it very attractive to space applications. In this paper, we describe the advanced microelectronics and avionics technologies under development by NASA's Deep Space Systems Technology Program (also known as X2000). These technologies are of significant benefit to both the commercial satellite as well as the deep-space and Earth orbiting science missions. Such a synergistic technology roadmap may truly enable quick turn-around, low-cost, and highly capable small satellite systems for both Earth observation as well as deep-space missions.

No Substantial Evidence for Sexual Transmission of Minority HIV Drug Resistance Mutations in Men Who Have Sex with Men.

PubMed

Chaillon, Antoine; Nakazawa, Masato; Wertheim, Joel O; Little, Susan J; Smith, Davey M; Mehta, Sanjay R; Gianella, Sara

2017-11-01

During primary HIV infection, the presence of minority drug resistance mutations (DRM) may be a consequence of sexual transmission, de novo mutations, or technical errors in identification. Baseline blood samples were collected from 24 HIV-infected antiretroviral-naive, genetically and epidemiologically linked source and recipient partners shortly after the recipient's estimated date of infection. An additional 32 longitudinal samples were available from 11 recipients. Deep sequencing of HIV reverse transcriptase (RT) was performed (Roche/454), and the sequences were screened for nucleoside and nonnucleoside RT inhibitor DRM. The likelihood of sexual transmission and persistence of DRM was assessed using Bayesian-based statistical modeling. While the majority of DRM (>20%) were consistently transmitted from source to recipient, the probability of detecting a minority DRM in the recipient was not increased when the same minority DRM was detected in the source (Bayes factor [BF] = 6.37). Longitudinal analyses revealed an exponential decay of DRM (BF = 0.05) while genetic diversity increased. Our analysis revealed no substantial evidence for sexual transmission of minority DRM (BF = 0.02). The presence of minority DRM during early infection, followed by a rapid decay, is consistent with the "mutation-selection balance" hypothesis, in which deleterious mutations are more efficiently purged later during HIV infection when the larger effective population size allows more efficient selection. Future studies using more recent sequencing technologies that are less prone to single-base errors should confirm these results by applying a similar Bayesian framework in other clinical settings. IMPORTANCE The advent of sensitive sequencing platforms has led to an increased identification of minority drug resistance mutations (DRM), including among antiretroviral therapy-naive HIV-infected individuals. While transmission of DRM may impact future therapy options for newly infected individuals, the clinical significance of the detection of minority DRM remains controversial. In the present study, we applied deep-sequencing techniques within a Bayesian hierarchical framework to a cohort of 24 transmission pairs to investigate whether minority DRM detected shortly after transmission were the consequence of (i) sexual transmission from the source, (ii) de novo emergence shortly after infection followed by viral selection and evolution, or (iii) technical errors/limitations of deep-sequencing methods. We found no clear evidence to support the sexual transmission of minority resistant variants, and our results suggested that minor resistant variants may emerge de novo shortly after transmission, when the small effective population size limits efficient purge by natural selection. Copyright © 2017 American Society for Microbiology.

The Deep Space Network

NASA Technical Reports Server (NTRS)

1979-01-01

Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations.

Sensitive Deep-Sequencing-Based HIV-1 Genotyping Assay To Simultaneously Determine Susceptibility to Protease, Reverse Transcriptase, Integrase, and Maturation Inhibitors, as Well as HIV-1 Coreceptor Tropism

PubMed Central

Gibson, Richard M.; Meyer, Ashley M.; Winner, Dane; Archer, John; Feyertag, Felix; Ruiz-Mateos, Ezequiel; Leal, Manuel; Robertson, David L.; Schmotzer, Christine L.

2014-01-01

With 29 individual antiretroviral drugs available from six classes that are approved for the treatment of HIV-1 infection, a combination of different phenotypic and genotypic tests is currently needed to monitor HIV-infected individuals. In this study, we developed a novel HIV-1 genotypic assay based on deep sequencing (DeepGen HIV) to simultaneously assess HIV-1 susceptibilities to all drugs targeting the three viral enzymes and to predict HIV-1 coreceptor tropism. Patient-derived gag-p2/NCp7/p1/p6/pol-PR/RT/IN- and env-C2V3 PCR products were sequenced using the Ion Torrent Personal Genome Machine. Reads spanning the 3′ end of the Gag, protease (PR), reverse transcriptase (RT), integrase (IN), and V3 regions were extracted, truncated, translated, and assembled for genotype and HIV-1 coreceptor tropism determination. DeepGen HIV consistently detected both minority drug-resistant viruses and non-R5 HIV-1 variants from clinical specimens with viral loads of ≥1,000 copies/ml and from B and non-B subtypes. Additional mutations associated with resistance to PR, RT, and IN inhibitors, previously undetected by standard (Sanger) population sequencing, were reliably identified at frequencies as low as 1%. DeepGen HIV results correlated with phenotypic (original Trofile, 92%; enhanced-sensitivity Trofile assay [ESTA], 80%; TROCAI, 81%; and VeriTrop, 80%) and genotypic (population sequencing/Geno2Pheno with a 10% false-positive rate [FPR], 84%) HIV-1 tropism test results. DeepGen HIV (83%) and Trofile (85%) showed similar concordances with the clinical response following an 8-day course of maraviroc monotherapy (MCT). In summary, this novel all-inclusive HIV-1 genotypic and coreceptor tropism assay, based on deep sequencing of the PR, RT, IN, and V3 regions, permits simultaneous multiplex detection of low-level drug-resistant and/or non-R5 viruses in up to 96 clinical samples. This comprehensive test, the first of its class, will be instrumental in the development of new antiretroviral drugs and, more importantly, will aid in the treatment and management of HIV-infected individuals. PMID:24468782

Dendrites, deep learning, and sequences in the hippocampus.

PubMed

Bhalla, Upinder S

2017-10-12

The hippocampus places us both in time and space. It does so over remarkably large spans: milliseconds to years, and centimeters to kilometers. This works for sensory representations, for memory, and for behavioral context. How does it fit in such wide ranges of time and space scales, and keep order among the many dimensions of stimulus context? A key organizing principle for a wide sweep of scales and stimulus dimensions is that of order in time, or sequences. Sequences of neuronal activity are ubiquitous in sensory processing, in motor control, in planning actions, and in memory. Against this strong evidence for the phenomenon, there are currently more models than definite experiments about how the brain generates ordered activity. The flip side of sequence generation is discrimination. Discrimination of sequences has been extensively studied at the behavioral, systems, and modeling level, but again physiological mechanisms are fewer. It is against this backdrop that I discuss two recent developments in neural sequence computation, that at face value share little beyond the label "neural." These are dendritic sequence discrimination, and deep learning. One derives from channel physiology and molecular signaling, the other from applied neural network theory - apparently extreme ends of the spectrum of neural circuit detail. I suggest that each of these topics has deep lessons about the possible mechanisms, scales, and capabilities of hippocampal sequence computation. © 2017 Wiley Periodicals, Inc.

A robust and cost-effective approach to sequence and analyze complete genomes of small RNA viruses

USDA-ARS?s Scientific Manuscript database

Background: Next-generation sequencing (NGS) allows ultra-deep sequencing of nucleic acids. The use of sequence-independent amplification of viral nucleic acids without utilization of target-specific primers provides advantages over traditional sequencing methods and allows detection of unsuspected ...

De novo transcriptome assembly and positive selection analysis of an individual deep-sea fish.

PubMed

Lan, Yi; Sun, Jin; Xu, Ting; Chen, Chong; Tian, Renmao; Qiu, Jian-Wen; Qian, Pei-Yuan

2018-05-24

High hydrostatic pressure and low temperatures make the deep sea a harsh environment for life forms. Actin organization and microtubules assembly, which are essential for intracellular transport and cell motility, can be disrupted by high hydrostatic pressure. High hydrostatic pressure can also damage DNA. Nucleic acids exposed to low temperatures can form secondary structures that hinder genetic information processing. To study how deep-sea creatures adapt to such a hostile environment, one of the most straightforward ways is to sequence and compare their genes with those of their shallow-water relatives. We captured an individual of the fish species Aldrovandia affinis, which is a typical deep-sea inhabitant, from the Okinawa Trough at a depth of 1550 m using a remotely operated vehicle (ROV). We sequenced its transcriptome and analyzed its molecular adaptation. We obtained 27,633 protein coding sequences using an Illumina platform and compared them with those of several shallow-water fish species. Analysis of 4918 single-copy orthologs identified 138 positively selected genes in A. affinis, including genes involved in microtubule regulation. Particularly, functional domains related to cold shock as well as DNA repair are exposed to positive selection pressure in both deep-sea fish and hadal amphipod. Overall, we have identified a set of positively selected genes related to cytoskeleton structures, DNA repair and genetic information processing, which shed light on molecular adaptation to the deep sea. These results suggest that amino acid substitutions of these positively selected genes may contribute crucially to the adaptation of deep-sea animals. Additionally, we provide a high-quality transcriptome of a deep-sea fish for future deep-sea studies.

A deep learning-based multi-model ensemble method for cancer prediction.

PubMed

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

Revealing the unexplored fungal communities in deep groundwater of crystalline bedrock fracture zones in Olkiluoto, Finland.

PubMed

Sohlberg, Elina; Bomberg, Malin; Miettinen, Hanna; Nyyssönen, Mari; Salavirta, Heikki; Vikman, Minna; Itävaara, Merja

2015-01-01

The diversity and functional role of fungi, one of the ecologically most important groups of eukaryotic microorganisms, remains largely unknown in deep biosphere environments. In this study we investigated fungal communities in packer-isolated bedrock fractures in Olkiluoto, Finland at depths ranging from 296 to 798 m below surface level. DNA- and cDNA-based high-throughput amplicon sequencing analysis of the fungal internal transcribed spacer (ITS) gene markers was used to examine the total fungal diversity and to identify the active members in deep fracture zones at different depths. Results showed that fungi were present in fracture zones at all depths and fungal diversity was higher than expected. Most of the observed fungal sequences belonged to the phylum Ascomycota. Phyla Basidiomycota and Chytridiomycota were only represented as a minor part of the fungal community. Dominating fungal classes in the deep bedrock aquifers were Sordariomycetes, Eurotiomycetes, and Dothideomycetes from the Ascomycota phylum and classes Microbotryomycetes and Tremellomycetes from the Basidiomycota phylum, which are the most frequently detected fungal taxa reported also from deep sea environments. In addition some fungal sequences represented potentially novel fungal species. Active fungi were detected in most of the fracture zones, which proves that fungi are able to maintain cellular activity in these oligotrophic conditions. Possible roles of fungi and their origin in deep bedrock groundwater can only be speculated in the light of current knowledge but some species may be specifically adapted to deep subsurface environment and may play important roles in the utilization and recycling of nutrients and thus sustaining the deep subsurface microbial community.

Ultra-deep mutant spectrum profiling: improving sequencing accuracy using overlapping read pairs.

PubMed

Chen-Harris, Haiyin; Borucki, Monica K; Torres, Clinton; Slezak, Tom R; Allen, Jonathan E

2013-02-12

High throughput sequencing is beginning to make a transformative impact in the area of viral evolution. Deep sequencing has the potential to reveal the mutant spectrum within a viral sample at high resolution, thus enabling the close examination of viral mutational dynamics both within- and between-hosts. The challenge however, is to accurately model the errors in the sequencing data and differentiate real viral mutations, particularly those that exist at low frequencies, from sequencing errors. We demonstrate that overlapping read pairs (ORP) -- generated by combining short fragment sequencing libraries and longer sequencing reads -- significantly reduce sequencing error rates and improve rare variant detection accuracy. Using this sequencing protocol and an error model optimized for variant detection, we are able to capture a large number of genetic mutations present within a viral population at ultra-low frequency levels (<0.05%). Our rare variant detection strategies have important implications beyond viral evolution and can be applied to any basic and clinical research area that requires the identification of rare mutations.

Deep RNNs for video denoising

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Song, Li; Yang, Xiaokang

2016-09-01

Video denoising can be described as the problem of mapping from a specific length of noisy frames to clean one. We propose a deep architecture based on Recurrent Neural Network (RNN) for video denoising. The model learns a patch-based end-to-end mapping between the clean and noisy video sequences. It takes the corrupted video sequences as the input and outputs the clean one. Our deep network, which we refer to as deep Recurrent Neural Networks (deep RNNs or DRNNs), stacks RNN layers where each layer receives the hidden state of the previous layer as input. Experiment shows (i) the recurrent architecture through temporal domain extracts motion information and does favor to video denoising, and (ii) deep architecture have large enough capacity for expressing mapping relation between corrupted videos as input and clean videos as output, furthermore, (iii) the model has generality to learned different mappings from videos corrupted by different types of noise (e.g., Poisson-Gaussian noise). By training on large video databases, we are able to compete with some existing video denoising methods.

Next-generation sequencing reveals low-dose effects of cationic dendrimers in primary human bronchial epithelial cells.

PubMed

Feliu, Neus; Kohonen, Pekka; Ji, Jie; Zhang, Yuning; Karlsson, Hanna L; Palmberg, Lena; Nyström, Andreas; Fadeel, Bengt

2015-01-27

Gene expression profiling has developed rapidly in recent years with the advent of deep sequencing technologies such as RNA sequencing (RNA Seq) and could be harnessed to predict and define mechanisms of toxicity of chemicals and nanomaterials. However, the full potential of these technologies in (nano)toxicology is yet to be realized. Here, we show that systems biology approaches can uncover mechanisms underlying cellular responses to nanomaterials. Using RNA Seq and computational approaches, we found that cationic poly(amidoamine) dendrimers (PAMAM-NH2) are capable of triggering down-regulation of cell-cycle-related genes in primary human bronchial epithelial cells at doses that do not elicit acute cytotoxicity, as demonstrated using conventional cell viability assays, while gene transcription was not affected by neutral PAMAM-OH dendrimers. The PAMAMs were internalized in an active manner by lung cells and localized mainly in lysosomes; amine-terminated dendrimers were internalized more efficiently when compared to the hydroxyl-terminated dendrimers. Upstream regulator analysis implicated NF-κB as a putative transcriptional regulator, and subsequent cell-based assays confirmed that PAMAM-NH2 caused NF-κB-dependent cell cycle arrest. However, PAMAM-NH2 did not affect cell cycle progression in the human A549 adenocarcinoma cell line. These results demonstrate the feasibility of applying systems biology approaches to predict cellular responses to nanomaterials and highlight the importance of using relevant (primary) cell models.

deepTools2: a next generation web server for deep-sequencing data analysis.

PubMed

Ramírez, Fidel; Ryan, Devon P; Grüning, Björn; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S; Heyne, Steffen; Dündar, Friederike; Manke, Thomas

2016-07-08

We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

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

2016-12-01

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

Construction and EST sequencing of full-length, drought stress cDNA libraries for common beans (Phaseolus vulgaris L.)

PubMed Central

2011-01-01

Background Common bean is an important legume crop with only a moderate number of short expressed sequence tags (ESTs) made with traditional methods. The goal of this research was to use full-length cDNA technology to develop ESTs that would overlap with the beginning of open reading frames and therefore be useful for gene annotation of genomic sequences. The library was also constructed to represent genes expressed under drought, low soil phosphorus and high soil aluminum toxicity. We also undertook comparisons of the full-length cDNA library to two previous non-full clone EST sets for common bean. Results Two full-length cDNA libraries were constructed: one for the drought tolerant Mesoamerican genotype BAT477 and the other one for the acid-soil tolerant Andean genotype G19833 which has been selected for genome sequencing. Plants were grown in three soil types using deep rooting cylinders subjected to drought and non-drought stress and tissues were collected from both roots and above ground parts. A total of 20,000 clones were selected robotically, half from each library. Then, nearly 10,000 clones from the G19833 library were sequenced with an average read length of 850 nucleotides. A total of 4,219 unigenes were identified consisting of 2,981 contigs and 1,238 singletons. These were functionally annotated with gene ontology terms and placed into KEGG pathways. Compared to other EST sequencing efforts in common bean, about half of the sequences were novel or represented the 5' ends of known genes. Conclusions The present full-length cDNA libraries add to the technological toolbox available for common bean and our sequencing of these clones substantially increases the number of unique EST sequences available for the common bean genome. All of this should be useful for both functional gene annotation, analysis of splice site variants and intron/exon boundary determination by comparison to soybean genes or with common bean whole-genome sequences. In addition the library has a large number of transcription factors and will be interesting for discovery and validation of drought or abiotic stress related genes in common bean. PMID:22118559

Novel Degenerate PCR Method for Whole-Genome Amplification Applied to Peru Margin (ODP Leg 201) Subsurface Samples

PubMed Central

Martino, Amanda J.; Rhodes, Matthew E.; Biddle, Jennifer F.; Brandt, Leah D.; Tomsho, Lynn P.; House, Christopher H.

2011-01-01

A degenerate polymerase chain reaction (PCR)-based method of whole-genome amplification, designed to work fluidly with 454 sequencing technology, was developed and tested for use on deep marine subsurface DNA samples. While optimized here for use with Roche 454 technology, the general framework presented may be applicable to other next generation sequencing systems as well (e.g., Illumina, Ion Torrent). The method, which we have called random amplification metagenomic PCR (RAMP), involves the use of specific primers from Roche 454 amplicon sequencing, modified by the addition of a degenerate region at the 3′ end. It utilizes a PCR reaction, which resulted in no amplification from blanks, even after 50 cycles of PCR. After efforts to optimize experimental conditions, the method was tested with DNA extracted from cultured E. coli cells, and genome coverage was estimated after sequencing on three different occasions. Coverage did not vary greatly with the different experimental conditions tested, and was around 62% with a sequencing effort equivalent to a theoretical genome coverage of 14.10×. The GC content of the sequenced amplification product was within 2% of the predicted values for this strain of E. coli. The method was also applied to DNA extracted from marine subsurface samples from ODP Leg 201 site 1229 (Peru Margin), and results of a taxonomic analysis revealed microbial communities dominated by Proteobacteria, Chloroflexi, Firmicutes, Euryarchaeota, and Crenarchaeota, among others. These results were similar to those obtained previously for those samples; however, variations in the proportions of taxa identified illustrates well the generally accepted view that community analysis is sensitive to both the amplification technique used and the method of assigning sequences to taxonomic groups. Overall, we find that RAMP represents a valid methodology for amplifying metagenomes from low-biomass samples. PMID:22319519

Integration of deep transcriptome and proteome analyses reveals the components of alkaloid metabolism in opium poppy cell cultures

PubMed Central

2010-01-01

Background Papaver somniferum (opium poppy) is the source for several pharmaceutical benzylisoquinoline alkaloids including morphine, the codeine and sanguinarine. In response to treatment with a fungal elicitor, the biosynthesis and accumulation of sanguinarine is induced along with other plant defense responses in opium poppy cell cultures. The transcriptional induction of alkaloid metabolism in cultured cells provides an opportunity to identify components of this process via the integration of deep transcriptome and proteome databases generated using next-generation technologies. Results A cDNA library was prepared for opium poppy cell cultures treated with a fungal elicitor for 10 h. Using 454 GS-FLX Titanium pyrosequencing, 427,369 expressed sequence tags (ESTs) with an average length of 462 bp were generated. Assembly of these sequences yielded 93,723 unigenes, of which 23,753 were assigned Gene Ontology annotations. Transcripts encoding all known sanguinarine biosynthetic enzymes were identified in the EST database, 5 of which were represented among the 50 most abundant transcripts. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of total protein extracts from cell cultures treated with a fungal elicitor for 50 h facilitated the identification of 1,004 proteins. Proteins were fractionated by one-dimensional SDS-PAGE and digested with trypsin prior to LC-MS/MS analysis. Query of an opium poppy-specific EST database substantially enhanced peptide identification. Eight out of 10 known sanguinarine biosynthetic enzymes and many relevant primary metabolic enzymes were represented in the peptide database. Conclusions The integration of deep transcriptome and proteome analyses provides an effective platform to catalogue the components of secondary metabolism, and to identify genes encoding uncharacterized enzymes. The establishment of corresponding transcript and protein databases generated by next-generation technologies in a system with a well-defined metabolite profile facilitates an improved linkage between genes, enzymes, and pathway components. The proteome database represents the most relevant alkaloid-producing enzymes, compared with the much deeper and more complete transcriptome library. The transcript database contained full-length mRNAs encoding most alkaloid biosynthetic enzymes, which is a key requirement for the functional characterization of novel gene candidates. PMID:21083930

Identification of microRNAs differentially expressed involved in male flower development.

PubMed

Wang, Zhengjia; Huang, Jianqin; Sun, Zhichao; Zheng, Bingsong

2015-03-01

Hickory (Carya cathayensis Sarg.) is one of the most economically important woody trees in eastern China, but its long flowering phase delays yield. Our understanding of the regulatory roles of microRNAs (miRNAs) in male flower development in hickory remains poor. Using high-throughput sequencing technology, we have pyrosequenced two small RNA libraries from two male flower differentiation stages in hickory. Analysis of the sequencing data identified 114 conserved miRNAs that belonged to 23 miRNA families, five novel miRNAs including their corresponding miRNA*s, and 22 plausible miRNA candidates. Differential expression analysis revealed 12 miRNA sequences that were upregulated in the later (reproductive) stage of male flower development. Quantitative real-time PCR showed similar expression trends as that of the deep sequencing. Novel miRNAs and plausible miRNA candidates were predicted using bioinformatic analysis methods. The miRNAs newly identified in this study have increased the number of known miRNAs in hickory, and the identification of differentially expressed miRNAs will provide new avenues for studies into miRNAs involved in the process of male flower development in hickory and other related trees.

The complete mitochondrial genome of the deep-sea sponge Poecillastra laminaris (Astrophorida, Vulcanellidae).

PubMed

Zeng, Cong; Thomas, Leighton J; Kelly, Michelle; Gardner, Jonathan P A

2016-05-01

The complete mitochondrial genome of a New Zealand specimen of the deep-sea sponge Poecillastra laminaris (Sollas, 1886) (Astrophorida, Vulcanellidae), from the Colville Ridge, New Zealand, was sequenced using the 454 Life Science pyrosequencing system. To identify homologous mitochondrial sequences, the 454 reads were mapped to the complete mitochondrial genome sequence of Geodia neptuni (GeneBank No. NC_006990). The P. laminaris genome is 18,413 bp in length and includes 14 protein-coding genes, 24 transfer RNA genes and 2 ribosomal RNA genes. Gene order resembled that of other demosponges. The base composition of the genome is A (29.1%), T (35.2%), C (14.0%) and G (21.7%). This is the second published mitogenome for a sponge of the order Astrophorida and will be useful in future phylogenetic analysis of deep-sea sponges.

Bacterial Pathogens and Community Composition in Advanced Sewage Treatment Systems Revealed by Metagenomics Analysis Based on High-Throughput Sequencing

PubMed Central

Lu, Xin; Zhang, Xu-Xiang; Wang, Zhu; Huang, Kailong; Wang, Yuan; Liang, Weigang; Tan, Yunfei; Liu, Bo; Tang, Junying

2015-01-01

This study used 454 pyrosequencing, Illumina high-throughput sequencing and metagenomic analysis to investigate bacterial pathogens and their potential virulence in a sewage treatment plant (STP) applying both conventional and advanced treatment processes. Pyrosequencing and Illumina sequencing consistently demonstrated that Arcobacter genus occupied over 43.42% of total abundance of potential pathogens in the STP. At species level, potential pathogens Arcobacter butzleri, Aeromonas hydrophila and Klebsiella pneumonia dominated in raw sewage, which was also confirmed by quantitative real time PCR. Illumina sequencing also revealed prevalence of various types of pathogenicity islands and virulence proteins in the STP. Most of the potential pathogens and virulence factors were eliminated in the STP, and the removal efficiency mainly depended on oxidation ditch. Compared with sand filtration, magnetic resin seemed to have higher removals in most of the potential pathogens and virulence factors. However, presence of the residual A. butzleri in the final effluent still deserves more concerns. The findings indicate that sewage acts as an important source of environmental pathogens, but STPs can effectively control their spread in the environment. Joint use of the high-throughput sequencing technologies is considered a reliable method for deep and comprehensive overview of environmental bacterial virulence. PMID:25938416

Phage display screening without repetitious selection rounds.

PubMed

't Hoen, Peter A C; Jirka, Silvana M G; Ten Broeke, Bradley R; Schultes, Erik A; Aguilera, Begoña; Pang, Kar Him; Heemskerk, Hans; Aartsma-Rus, Annemieke; van Ommen, Gertjan J; den Dunnen, Johan T

2012-02-15

Phage display screenings are frequently employed to identify high-affinity peptides or antibodies. Although successful, phage display is a laborious technology and is notorious for identification of false positive hits. To accelerate and improve the selection process, we have employed Illumina next generation sequencing to deeply characterize the Ph.D.-7 M13 peptide phage display library before and after several rounds of biopanning on KS483 osteoblast cells. Sequencing of the naive library after one round of amplification in bacteria identifies propagation advantage as an important source of false positive hits. Most important, our data show that deep sequencing of the phage pool after a first round of biopanning is already sufficient to identify positive phages. Whereas traditional sequencing of a limited number of clones after one or two rounds of selection is uninformative, the required additional rounds of biopanning are associated with the risk of losing promising clones propagating slower than nonbinding phages. Confocal and live cell imaging confirms that our screen successfully selected a peptide with very high binding and uptake in osteoblasts. We conclude that next generation sequencing can significantly empower phage display screenings by accelerating the finding of specific binders and restraining the number of false positive hits. Copyright © 2011 Elsevier Inc. All rights reserved.

A novel process of viral vector barcoding and library preparation enables high-diversity library generation and recombination-free paired-end sequencing

PubMed Central

Davidsson, Marcus; Diaz-Fernandez, Paula; Schwich, Oliver D.; Torroba, Marcos; Wang, Gang; Björklund, Tomas

2016-01-01

Detailed characterization and mapping of oligonucleotide function in vivo is generally a very time consuming effort that only allows for hypothesis driven subsampling of the full sequence to be analysed. Recent advances in deep sequencing together with highly efficient parallel oligonucleotide synthesis and cloning techniques have, however, opened up for entirely new ways to map genetic function in vivo. Here we present a novel, optimized protocol for the generation of universally applicable, barcode labelled, plasmid libraries. The libraries are designed to enable the production of viral vector preparations assessing coding or non-coding RNA function in vivo. When generating high diversity libraries, it is a challenge to achieve efficient cloning, unambiguous barcoding and detailed characterization using low-cost sequencing technologies. With the presented protocol, diversity of above 3 million uniquely barcoded adeno-associated viral (AAV) plasmids can be achieved in a single reaction through a process achievable in any molecular biology laboratory. This approach opens up for a multitude of in vivo assessments from the evaluation of enhancer and promoter regions to the optimization of genome editing. The generated plasmid libraries are also useful for validation of sequencing clustering algorithms and we here validate the newly presented message passing clustering process named Starcode. PMID:27874090

Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

PubMed

Wen, Yalu; Shen, Xiaoxi; Lu, Qing

2018-05-31

With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

PubMed

Wang, Duolin; Zeng, Shuai; Xu, Chunhui; Qiu, Wangren; Liang, Yanchun; Joshi, Trupti; Xu, Dong

2017-12-15

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction. We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data. MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep. xudong@missouri.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Fungal diversity in deep-sea sediments associated with asphalt seeps at the Sao Paulo Plateau

NASA Astrophysics Data System (ADS)

Nagano, Yuriko; Miura, Toshiko; Nishi, Shinro; Lima, Andre O.; Nakayama, Cristina; Pellizari, Vivian H.; Fujikura, Katsunori

2017-12-01

We investigated the fungal diversity in a total of 20 deep-sea sediment samples (of which 14 samples were associated with natural asphalt seeps and 6 samples were not associated) collected from two different sites at the Sao Paulo Plateau off Brazil by Ion Torrent PGM targeting ITS region of ribosomal RNA. Our results suggest that diverse fungi (113 operational taxonomic units (OTUs) based on clustering at 97% sequence similarity assigned into 9 classes and 31 genus) are present in deep-sea sediment samples collected at the Sao Paulo Plateau, dominated by Ascomycota (74.3%), followed by Basidiomycota (11.5%), unidentified fungi (7.1%), and sequences with no affiliation to any organisms in the public database (7.1%). However, it was revealed that only three species, namely Penicillium sp., Cadophora malorum and Rhodosporidium diobovatum, were dominant, with the majority of OTUs remaining a minor community. Unexpectedly, there was no significant difference in major fungal community structure between the asphalt seep and non-asphalt seep sites, despite the presence of mass hydrocarbon deposits and the high amount of macro organisms surrounding the asphalt seeps. However, there were some differences in the minor fungal communities, with possible asphalt degrading fungi present specifically in the asphalt seep sites. In contrast, some differences were found between the two different sampling sites. Classification of OTUs revealed that only 47 (41.6%) fungal OTUs exhibited >97% sequence similarity, in comparison with pre-existing ITS sequences in public databases, indicating that a majority of deep-sea inhabiting fungal taxa still remain undescribed. Although our knowledge on fungi and their role in deep-sea environments is still limited and scarce, this study increases our understanding of fungal diversity and community structure in deep-sea environments.

Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions.

PubMed

Brannon, A Rose; Vakiani, Efsevia; Sylvester, Brooke E; Scott, Sasinya N; McDermott, Gregory; Shah, Ronak H; Kania, Krishan; Viale, Agnes; Oschwald, Dayna M; Vacic, Vladimir; Emde, Anne-Katrin; Cercek, Andrea; Yaeger, Rona; Kemeny, Nancy E; Saltz, Leonard B; Shia, Jinru; D'Angelica, Michael I; Weiser, Martin R; Solit, David B; Berger, Michael F

2014-08-28

Colorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors. We performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations. Colorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications.

LookSeq: a browser-based viewer for deep sequencing data.

PubMed

Manske, Heinrich Magnus; Kwiatkowski, Dominic P

2009-11-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an overview of a genomic region to fine details such as heterogeneity within the sample. A specific problem, particularly if the sample is heterogeneous, is how to depict information about structural variation. LookSeq provides a simple graphical representation of paired sequence reads that is more revealing about potential insertions and deletions than are conventional methods.

EHR Big Data Deep Phenotyping

PubMed Central

Lenert, L.; Lopez-Campos, G.

2014-01-01

Summary Objectives Given the quickening speed of discovery of variant disease drivers from combined patient genotype and phenotype data, the objective is to provide methodology using big data technology to support the definition of deep phenotypes in medical records. Methods As the vast stores of genomic information increase with next generation sequencing, the importance of deep phenotyping increases. The growth of genomic data and adoption of Electronic Health Records (EHR) in medicine provides a unique opportunity to integrate phenotype and genotype data into medical records. The method by which collections of clinical findings and other health related data are leveraged to form meaningful phenotypes is an active area of research. Longitudinal data stored in EHRs provide a wealth of information that can be used to construct phenotypes of patients. We focus on a practical problem around data integration for deep phenotype identification within EHR data. The use of big data approaches are described that enable scalable markup of EHR events that can be used for semantic and temporal similarity analysis to support the identification of phenotype and genotype relationships. Conclusions Stead and colleagues’ 2005 concept of using light standards to increase the productivity of software systems by riding on the wave of hardware/processing power is described as a harbinger for designing future healthcare systems. The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research. PMID:25123744

Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

PubMed Central

2015-01-01

Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects should be carefully taken into account before using metabarcoding in quantitative ecological research and monitoring programmes of marine biodiversity. PMID:26701112

Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

PubMed

Dell'Anno, Antonio; Carugati, Laura; Corinaldesi, Cinzia; Riccioni, Giulia; Danovaro, Roberto

2015-01-01

Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects should be carefully taken into account before using metabarcoding in quantitative ecological research and monitoring programmes of marine biodiversity.

Molecular Phylogenetic Analysis of Archaeal Intron-Containing Genes Coding for rRNA Obtained from a Deep-Subsurface Geothermal Water Pool

PubMed Central

Takai, Ken; Horikoshi, Koki

1999-01-01

Molecular phylogenetic analysis of a naturally occurring microbial community in a deep-subsurface geothermal environment indicated that the phylogenetic diversity of the microbial population in the environment was extremely limited and that only hyperthermophilic archaeal members closely related to Pyrobaculum were present. All archaeal ribosomal DNA sequences contained intron-like sequences, some of which had open reading frames with repeated homing-endonuclease motifs. The sequence similarity analysis and the phylogenetic analysis of these homing endonucleases suggested the possible phylogenetic relationship among archaeal rRNA-encoded homing endonucleases. PMID:10584021

Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety 'Amrapali' (Mangifera indica L.).

PubMed

Mahato, Ajay Kumar; Sharma, Nimisha; Singh, Akshay; Srivastav, Manish; Jaiprakash; Singh, Sanjay Kumar; Singh, Anand Kumar; Sharma, Tilak Raj; Singh, Nagendra Kumar

2016-01-01

Mango (Mangifera indica L.) is called "king of fruits" due to its sweetness, richness of taste, diversity, large production volume and a variety of end usage. Despite its huge economic importance genomic resources in mango are scarce and genetics of useful horticultural traits are poorly understood. Here we generated deep coverage leaf RNA sequence data for mango parental varieties 'Neelam', 'Dashehari' and their hybrid 'Amrapali' using next generation sequencing technologies. De-novo sequence assembly generated 27,528, 20,771 and 35,182 transcripts for the three genotypes, respectively. The transcripts were further assembled into a non-redundant set of 70,057 unigenes that were used for SSR and SNP identification and annotation. Total 5,465 SSR loci were identified in 4,912 unigenes with 288 type I SSR (n ≥ 20 bp). One hundred type I SSR markers were randomly selected of which 43 yielded PCR amplicons of expected size in the first round of validation and were designated as validated genic-SSR markers. Further, 22,306 SNPs were identified by aligning high quality sequence reads of the three mango varieties to the reference unigene set, revealing significantly enhanced SNP heterozygosity in the hybrid Amrapali. The present study on leaf RNA sequencing of mango varieties and their hybrid provides useful genomic resource for genetic improvement of mango.

Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety ‘Amrapali’ (Mangifera indica L.)

PubMed Central

Mahato, Ajay Kumar; Sharma, Nimisha; Singh, Akshay; Srivastav, Manish; Jaiprakash; Singh, Sanjay Kumar; Singh, Anand Kumar; Sharma, Tilak Raj; Singh, Nagendra Kumar

2016-01-01

Mango (Mangifera indica L.) is called “king of fruits” due to its sweetness, richness of taste, diversity, large production volume and a variety of end usage. Despite its huge economic importance genomic resources in mango are scarce and genetics of useful horticultural traits are poorly understood. Here we generated deep coverage leaf RNA sequence data for mango parental varieties ‘Neelam’, ‘Dashehari’ and their hybrid ‘Amrapali’ using next generation sequencing technologies. De-novo sequence assembly generated 27,528, 20,771 and 35,182 transcripts for the three genotypes, respectively. The transcripts were further assembled into a non-redundant set of 70,057 unigenes that were used for SSR and SNP identification and annotation. Total 5,465 SSR loci were identified in 4,912 unigenes with 288 type I SSR (n ≥ 20 bp). One hundred type I SSR markers were randomly selected of which 43 yielded PCR amplicons of expected size in the first round of validation and were designated as validated genic-SSR markers. Further, 22,306 SNPs were identified by aligning high quality sequence reads of the three mango varieties to the reference unigene set, revealing significantly enhanced SNP heterozygosity in the hybrid Amrapali. The present study on leaf RNA sequencing of mango varieties and their hybrid provides useful genomic resource for genetic improvement of mango. PMID:27736892

Deep sequencing is an appropriate tool for the selection of unique Hepatitis C virus (HCV) variants after single genomic amplification.

PubMed

Guinoiseau, Thibault; Moreau, Alain; Hohnadel, Guillaume; Ngo-Giang-Huong, Nicole; Brulard, Celine; Vourc'h, Patrick; Goudeau, Alain; Gaudy-Graffin, Catherine

2017-01-01

Hepatitis C virus (HCV) evolves rapidly in a single host and circulates as a quasispecies wich is a complex mixture of genetically distinct virus's but closely related namely variants. To identify intra-individual diversity and investigate their functional properties in vitro, it is necessary to define their quasispecies composition and isolate the HCV variants. This is possible using single genome amplification (SGA). This technique, based on serially diluted cDNA to amplify a single cDNA molecule (clonal amplicon), has already been used to determine individual HCV diversity. In these studies, positive PCR reactions from SGA were directly sequenced using Sanger technology. The detection of non-clonal amplicons is necessary for excluding them to facilitate further functional analysis. Here, we compared Next Generation Sequencing (NGS) with De Novo assembly and Sanger sequencing for their ability to distinguish clonal and non-clonal amplicons after SGA on one plasma specimen. All amplicons (n = 42) classified as clonal by NGS were also classified as clonal by Sanger sequencing. No double peaks were seen on electropherograms for non-clonal amplicons with position-specific nucleotide variation below 15% by NGS. Altogether, NGS circumvented many of the difficulties encountered when using Sanger sequencing after SGA and is an appropriate tool to reliability select clonal amplicons for further functional studies.

Deep sequencing is an appropriate tool for the selection of unique Hepatitis C virus (HCV) variants after single genomic amplification

PubMed Central

Guinoiseau, Thibault; Moreau, Alain; Hohnadel, Guillaume; Ngo-Giang-Huong, Nicole; Brulard, Celine; Vourc’h, Patrick; Goudeau, Alain; Gaudy-Graffin, Catherine

2017-01-01

Hepatitis C virus (HCV) evolves rapidly in a single host and circulates as a quasispecies wich is a complex mixture of genetically distinct virus’s but closely related namely variants. To identify intra-individual diversity and investigate their functional properties in vitro, it is necessary to define their quasispecies composition and isolate the HCV variants. This is possible using single genome amplification (SGA). This technique, based on serially diluted cDNA to amplify a single cDNA molecule (clonal amplicon), has already been used to determine individual HCV diversity. In these studies, positive PCR reactions from SGA were directly sequenced using Sanger technology. The detection of non-clonal amplicons is necessary for excluding them to facilitate further functional analysis. Here, we compared Next Generation Sequencing (NGS) with De Novo assembly and Sanger sequencing for their ability to distinguish clonal and non-clonal amplicons after SGA on one plasma specimen. All amplicons (n = 42) classified as clonal by NGS were also classified as clonal by Sanger sequencing. No double peaks were seen on electropherograms for non-clonal amplicons with position-specific nucleotide variation below 15% by NGS. Altogether, NGS circumvented many of the difficulties encountered when using Sanger sequencing after SGA and is an appropriate tool to reliability select clonal amplicons for further functional studies. PMID:28362878

Discovery and profiling of novel and conserved microRNAs during flower development in Carya cathayensis via deep sequencing.

PubMed

Wang, Zheng Jia; Huang, Jian Qin; Huang, You Jun; Li, Zheng; Zheng, Bing Song

2012-08-01

Hickory (Carya cathayensis Sarg.) is an economically important woody plant in China, but its long juvenile phase delays yield. MicroRNAs (miRNAs) are critical regulators of genes and important for normal plant development and physiology, including flower development. We used Solexa technology to sequence two small RNA libraries from two floral differentiation stages in hickory to identify miRNAs related to flower development. We identified 39 conserved miRNA sequences from 114 loci belonging to 23 families as well as two novel and ten potential novel miRNAs belonging to nine families. Moreover, 35 conserved miRNA*s and two novel miRNA*s were detected. Twenty miRNA sequences from 49 loci belonging to 11 families were differentially expressed; all were up-regulated at the later stage of flower development in hickory. Quantitative real-time PCR of 12 conserved miRNA sequences, five novel miRNA families, and two novel miRNA*s validated that all were expressed during hickory flower development, and the expression patterns were similar to those detected with Solexa sequencing. Finally, a total of 146 targets of the novel and conserved miRNAs were predicted. This study identified a diverse set of miRNAs that were closely related to hickory flower development and that could help in plant floral induction.

A first insight into the occurrence and expression of functional amoA and accA genes of autotrophic and ammonia-oxidizing bathypelagic Crenarchaeota of Tyrrhenian Sea

NASA Astrophysics Data System (ADS)

Yakimov, Michail M.; Cono, Violetta La; Denaro, Renata

2009-05-01

The autotrophic and ammonia-oxidizing crenarchaeal assemblage at offshore site located in the deep Mediterranean (Tyrrhenian Sea, depth 3000 m) water was studied by PCR amplification of the key functional genes involved in energy (ammonia mono-oxygenase alpha subunit, amoA) and central metabolism (acetyl-CoA carboxylase alpha subunit, accA). Using two recently annotated genomes of marine crenarchaeons, an initial set of primers targeting archaeal accA-like genes was designed. Approximately 300 clones were analyzed, of which 100% of amoA library and almost 70% of accA library were unambiguously related to the corresponding genes from marine Crenarchaeota. Even though the acetyl-CoA carboxylase is phylogenetically not well conserved and the remaining clones were affiliated to various bacterial acetyl-CoA/propionyl-CoA carboxylase genes, the pool of archaeal sequences was applied for development of quantitative PCR analysis of accA-like distribution using TaqMan ® methodolgy. The archaeal accA gene fragments, together with alignable gene fragments from the Sargasso Sea and North Pacific Subtropical Gyre (ALOHA Station) metagenome databases, were analyzed by multiple sequence alignment. Two accA-like sequences, found in ALOHA Station at the depth of 4000 m, formed a deeply branched clade with 64% of all archaeal Tyrrhenian clones. No close relatives for residual 36% of clones, except of those recovered from Eastern Mediterranean, was found, suggesting the existence of a specific lineage of the crenarchaeal accA genes in deep Mediterranean water. Alignment of Mediterranean amoA sequences defined four cosmopolitan phylotypes of Crenarchaeota putative ammonia mono-oxygenase subunit A gene occurring in the water sample from the 3000 m depth. Without exception all phylotypes fell into Deep Marine Group I cluster that contain the vast majority of known sequences recovered from global deep-sea environment. Remarkably, three phylotypes accounted for 91% of all Mediterranean amoA clones and corresponded to the sequences retrieved from the less deep compartments of the world's ocean, most likely reflecting the higher temperature at the depth of the Mediterranean Sea. In order to verify whether these phylotypes might represent important Crenarchaeota in the functioning of the Mediterranean bathypelagic ecosystem, expression of crenarchaeal amoA gene was monitored by direct RNA retrieval and following analysis of amoA-related mRNA transcripts. Surprisingly, all mRNA-derived sequences formed a tight monophyletic group, which fell into large Shallow Marine Group I cluster with sequences retrieved from shallow (up to 200 m) waters, sediments and corals. This group was not detected in DNA-based clone library, obviously, due to an overwhelming dominance of the Deep Marine Group I. The failure to recover the amoA transcripts, related to Deep Marine Group I of Crenarchaeota, was unanticipated and likely resulted from the physiology of these strongly adapted deep-sea organisms. As far as all seawater samples were treated on-board under atmospheric pressure conditions and sunlight, the decompression and/or photoinhibition likely affected their metabolic activity, followed by the strong decay of gene expression.

Genomic variation in macrophage-cultured European porcine reproductive and respiratory syndrome virus Olot/91 revealed using ultra-deep next generation sequencing.

PubMed

Lu, Zen H; Brown, Alexander; Wilson, Alison D; Calvert, Jay G; Balasch, Monica; Fuentes-Utrilla, Pablo; Loecherbach, Julia; Turner, Frances; Talbot, Richard; Archibald, Alan L; Ait-Ali, Tahar

2014-03-04

Porcine Reproductive and Respiratory Syndrome (PRRS) is a disease of major economic impact worldwide. The etiologic agent of this disease is the PRRS virus (PRRSV). Increasing evidence suggest that microevolution within a coexisting quasispecies population can give rise to high sequence heterogeneity in PRRSV. We developed a pipeline based on the ultra-deep next generation sequencing approach to first construct the complete genome of a European PRRSV, strain Olot/9, cultured on macrophages and then capture the rare variants representative of the mixed quasispecies population. Olot/91 differs from the reference Lelystad strain by about 5% and a total of 88 variants, with frequencies as low as 1%, were detected in the mixed population. These variants included 16 non-synonymous variants concentrated in the genes encoding structural and nonstructural proteins; including Glycoprotein 2a and 5. Using an ultra-deep sequencing methodology, the complete genome of Olot/91 was constructed without any prior knowledge of the sequence. Rare variants that constitute minor fractions of the heterogeneous PRRSV population could successfully be detected to allow further exploration of microevolutionary events.

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

PubMed Central

Wang, Ruijia; Nambiar, Ram; Zheng, Dinghai

2018-01-01

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

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

PubMed

Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

2013-09-01

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.

Direct evidence of 1,900 years of indigenous silver production in the Lake Titicaca Basin of Southern Peru.

PubMed

Schultze, Carol A; Stanish, Charles; Scott, David A; Rehren, Thilo; Kuehner, Scott; Feathers, James K

2009-10-13

Archaeological excavations at a U-shaped pyramid in the northern Lake Titicaca Basin of Peru have documented a continuous 5-m-deep stratigraphic sequence of metalworking remains. The sequence begins in the first millennium AD and ends in the Spanish Colonial period ca. AD 1600. The earliest dates associated with silver production are 1960 + or - 40 BP (2-sigma cal. 40 BC to AD 120) and 1870 + or - 40 BP (2-sigma cal. AD 60 to 240) representing the oldest known silver smelting in South America. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis of production debris indicate a complex, multistage, high temperature technology for producing silver throughout the archaeological sequence. These data hold significant theoretical implications including the following: (i) silver production occurred before the development of the first southern Andean state of Tiwanaku, (ii) the location and process of silverworking remained consistent for 1,500 years even though political control of the area cycled between expansionist states and smaller chiefly polities, and (iii) that U-shaped structures were the location of ceremonial, residential, and industrial activities.

Deep whole-genome sequencing of 90 Han Chinese genomes.

PubMed

Lan, Tianming; Lin, Haoxiang; Zhu, Wenjuan; Laurent, Tellier Christian Asker Melchior; Yang, Mengcheng; Liu, Xin; Wang, Jun; Wang, Jian; Yang, Huanming; Xu, Xun; Guo, Xiaosen

2017-09-01

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency < 5%), including 5 813 503 single nucleotide polymorphisms, 1 169 199 InDels, and 17 927 structural variants. Using deep sequencing data, we have built a greatly expanded spectrum of genetic variation for the Han Chinese genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000 Genomes Project, as well as to other human genome projects. © The Authors 2017. Published by Oxford University Press.

Novel Lipolytic Enzymes Identified from Metagenomic Library of Deep-Sea Sediment

PubMed Central

Jeon, Jeong Ho; Kim, Jun Tae; Lee, Hyun Sook; Kim, Sang-Jin; Kang, Sung Gyun; Choi, Sang Ho; Lee, Jung-Hyun

2011-01-01

Metagenomic library was constructed from a deep-sea sediment sample and screened for lipolytic activity. Open-reading frames of six positive clones showed only 33–58% amino acid identities to the known proteins. One of them was assigned to a new group while others were grouped into Families I and V or EstD Family. By employing a combination of approaches such as removing the signal sequence, coexpression of chaperone genes, and low temperature induction, we obtained five soluble recombinant proteins in Escherichia coli. The purified enzymes had optimum temperatures of 30–35°C and the cold-activity property. Among them, one enzyme showed lipase activity by preferentially hydrolyzing p-nitrophenyl palmitate and p-nitrophenyl stearate and high salt resistance with up to 4 M NaCl. Our research demonstrates the feasibility of developing novel lipolytic enzymes from marine environments by the combination of functional metagenomic approach and protein expression technology. PMID:21845199

Optimization of conditions to sequence long cDNAs from viruses

USDA-ARS?s Scientific Manuscript database

Fourth generation sequencing with the Minion nanopore sequencer provides opportunity to obtain deep coverage and long read for single molecules. This will benefit studies on RNA viruses. In the past, Sanger, Illumina, and Ion Torrent sequencing have been utilized to study RNA viruses. Both technique...

Flexible-Path Human Exploration

NASA Technical Reports Server (NTRS)

Sherwood, B.; Adler, M.; Alkalai, L.; Burdick, G.; Coulter, D.; Jordan, F.; Naderi, F.; Graham, L.; Landis, R.; Drake, B.;

MRI markers of small vessel disease in lobar and deep hemispheric intracerebral hemorrhage.

PubMed

Smith, Eric E; Nandigam, Kaveer R N; Chen, Yu-Wei; Jeng, Jed; Salat, David; Halpin, Amy; Frosch, Matthew; Wendell, Lauren; Fazen, Louis; Rosand, Jonathan; Viswanathan, Anand; Greenberg, Steven M

2010-09-01

MRI evidence of small vessel disease is common in intracerebral hemorrhage (ICH). We hypothesized that ICH caused by cerebral amyloid angiopathy (CAA) or hypertensive vasculopathy would have different distributions of MRI T2 white matter hyperintensity (WMH) and microbleeds. Data were analyzed from 133 consecutive patients with primary supratentorial ICH and adequate MRI sequences. CAA was diagnosed using the Boston criteria. WMH segmentation was performed using a validated semiautomated method. WMH and microbleeds were compared according to site of symptomatic hematoma origin (lobar versus deep) or by pattern of hemorrhages, including both hematomas and microbleeds, on MRI gradient recalled echo sequence (grouped as lobar only-probable CAA, lobar only-possible CAA, deep hemispheric only, or mixed lobar and deep hemorrhages). Patients with lobar and deep hemispheric hematoma had similar median normalized WMH volumes (19.5 cm versus 19.9 cm(3), P=0.74) and prevalence of >or=1 microbleed (54% versus 52%, P=0.99). The supratentorial WMH distribution was similar according to hemorrhage location category; however, the prevalence of brain stem T2 hyperintensity was lower in lobar hematoma versus deep hematoma (54% versus 70%, P=0.004). Mixed ICH was common (23%). Patients with mixed ICH had large normalized WMH volumes and a posterior distribution of cortical hemorrhages similar to that seen in CAA. WMH distribution is largely similar between CAA-related and non-CAA-related ICH. Mixed lobar and deep hemorrhages are seen on MRI gradient recalled echo sequence in up to one fourth of patients; in these patients, both hypertension and CAA may be contributing to the burden of WMH.

Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability.

PubMed

Dudding-Byth, Tracy; Baxter, Anne; Holliday, Elizabeth G; Hackett, Anna; O'Donnell, Sheridan; White, Susan M; Attia, John; Brunner, Han; de Vries, Bert; Koolen, David; Kleefstra, Tjitske; Ratwatte, Seshika; Riveros, Carlos; Brain, Steve; Lovell, Brian C

2017-12-19

Massively parallel genetic sequencing allows rapid testing of known intellectual disability (ID) genes. However, the discovery of novel syndromic ID genes requires molecular confirmation in at least a second or a cluster of individuals with an overlapping phenotype or similar facial gestalt. Using computer face-matching technology we report an automated approach to matching the faces of non-identical individuals with the same genetic syndrome within a database of 3681 images [1600 images of one of 10 genetic syndrome subgroups together with 2081 control images]. Using the leave-one-out method, two research questions were specified: 1) Using two-dimensional (2D) photographs of individuals with one of 10 genetic syndromes within a database of images, did the technology correctly identify more than expected by chance: i) a top match? ii) at least one match within the top five matches? or iii) at least one in the top 10 with an individual from the same syndrome subgroup? 2) Was there concordance between correct technology-based matches and whether two out of three clinical geneticists would have considered the diagnosis based on the image alone? The computer face-matching technology correctly identifies a top match, at least one correct match in the top five and at least one in the top 10 more than expected by chance (P < 0.00001). There was low agreement between the technology and clinicians, with higher accuracy of the technology when results were discordant (P < 0.01) for all syndromes except Kabuki syndrome. Although the accuracy of the computer face-matching technology was tested on images of individuals with known syndromic forms of intellectual disability, the results of this pilot study illustrate the potential utility of face-matching technology within deep phenotyping platforms to facilitate the interpretation of DNA sequencing data for individuals who remain undiagnosed despite testing the known developmental disorder genes.

Deep Sequencing Analysis of Apple Infecting Viruses in Korea

PubMed Central

Cho, In-Sook; Igori, Davaajargal; Lim, Seungmo; Choi, Gug-Seoun; Hammond, John; Lim, Hyoun-Sub; Moon, Jae Sun

2016-01-01

Deep sequencing has generated 52 contigs derived from five viruses; Apple chlorotic leaf spot virus (ACLSV), Apple stem grooving virus (ASGV), Apple stem pitting virus (ASPV), Apple green crinkle associated virus (AGCaV), and Apricot latent virus (ApLV) were identified from eight apple samples showing small leaves and/or growth retardation. Nucleotide (nt) sequence identity of the assembled contigs was from 68% to 99% compared to the reference sequences of the five respective viral genomes. Sequences of ASPV and ASGV were the most abundantly represented by the 52 contigs assembled. The presence of the five viruses in the samples was confirmed by RT-PCR using specific primers based on the sequences of each assembled contig. All five viruses were detected in three of the samples, whereas all samples had mixed infections with at least two viruses. The most frequently detected virus was ASPV, followed by ASGV, ApLV, ACLSV, and AGCaV which were withal found in mixed infections in the tested samples. AGCaV was identified in assembled contigs ID 1012480 and 93549, which showed 82% and 78% nt sequence identity with ORF1 of AGCaV isolate Aurora-1. ApLV was identified in three assembled contigs, ID 65587, 1802365, and 116777, which showed 77%, 78%, and 76% nt sequence identity respectively with ORF1 of ApLV isolate LA2. Deep sequencing assay was shown to be a valuable and powerful tool for detection and identification of known and unknown virome in infected apple trees, here identifying ApLV and AGCaV in commercial orchards in Korea for the first time. PMID:27721694

Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics.

PubMed

James, Katherine; Cockell, Simon J; Zenkin, Nikolay

2017-05-01

The identification of the protein-coding regions of a genome is straightforward due to the universality of start and stop codons. However, the boundaries of the transcribed regions, conditional operon structures, non-coding RNAs and the dynamics of transcription, such as pausing of elongation, are non-trivial to identify, even in the comparatively simple genomes of prokaryotes. Traditional methods for the study of these areas, such as tiling arrays, are noisy, labour-intensive and lack the resolution required for densely-packed bacterial genomes. Recently, deep sequencing has become increasingly popular for the study of the transcriptome due to its lower costs, higher accuracy and single nucleotide resolution. These methods have revolutionised our understanding of prokaryotic transcriptional dynamics. Here, we review the deep sequencing and data analysis techniques that are available for the study of transcription in prokaryotes, and discuss the bioinformatic considerations of these analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Insertion sequences enrichment in extreme Red sea brine pool vent.

PubMed

Elbehery, Ali H A; Aziz, Ramy K; Siam, Rania

2017-03-01

Mobile genetic elements are major agents of genome diversification and evolution. Limited studies addressed their characteristics, including abundance, and role in extreme habitats. One of the rare natural habitats exposed to multiple-extreme conditions, including high temperature, salinity and concentration of heavy metals, are the Red Sea brine pools. We assessed the abundance and distribution of different mobile genetic elements in four Red Sea brine pools including the world's largest known multiple-extreme deep-sea environment, the Red Sea Atlantis II Deep. We report a gradient in the abundance of mobile genetic elements, dramatically increasing in the harshest environment of the pool. Additionally, we identified a strong association between the abundance of insertion sequences and extreme conditions, being highest in the harshest and deepest layer of the Red Sea Atlantis II Deep. Our comparative analyses of mobile genetic elements in secluded, extreme and relatively non-extreme environments, suggest that insertion sequences predominantly contribute to polyextremophiles genome plasticity.

The Port Isabel Fold Belt: Salt enhanced Neogene Gravitational Spreading in the East Breaks, Western Gulf of Mexico

NASA Astrophysics Data System (ADS)

Lebit, Hermann; Clavaud, Marie; Whitehead, Sam; Opdyke, Scott; Luneburg, Catalina

2017-04-01

The Port Isabel fold belt is situated at the northwestern corner of the deep water Gulf of Mexico where the regional E-W trending Texas-Louisiana shelf bends into the NNE-SSW trend of the East Mexico Shelf. The fold belt forms an allochthonous wedge that ramps up from West to East with its front occupied by shallow salt complexes (local canopies). It is assumed that the belt predominantly comprises Oligocene siliciclastic sequences which reveal eastward facing folds and thrusts with a NE-SW regional trend. The structural architecture of the fold belt is very well imaged on recently processed 3D seismic volumes. Crystal III is a wide-azimuth survey acquired in 2011 and reprocessed in 2016 leveraging newly developed state-of-the-art technology. 3D deghosting, directional designature and multi-model 3D SRME resulted in broader frequency spectrum. The new image benefits from unique implementation of FWI, combined with classic tomographic updates. Seismically transparent zones indicating over-pressured shales are limited to the core of anticlines or to the footwall of internal thrust. Mobile shales associated with diapirs are absent in the study area. In contrast, salt is mobile and apparently forms the major decollement of the PIFB as indicated by remnant salt preferentially located in triangles along the major thrusts and fault intersections or at the core of anticlines. Shallow salt diapirs seam to root in the fold belt, while lacking evidence for salt feeders being connected to the deep salt underlying the Mesozoic to Paleogene substratum of the fold belt. Towards the WNW the fold belt is transient into a extensional regime, characterized by roll-over structures associated with deep reaching normal faults which form ultra-deep mini basins filled with Neogene deposits. Kinematic restorations confirm the simultaneous evolution of the deep mini basins and the outboard fold belt. This resembles a gravitational spreading system with the extensional tectonics of the deep Neogene mini basin balanced by the outboard compressional domains of the displaced Paleogene sediment sequence. In this context the role of salt is enigmatic, as the system's concave, deep reaching major detachment conflicts with the interpretation of a destabilized former salt canopy. It rather indicates syn-kinematic salt extrusion from a deeper source along the major frontal thrust ramp. A syn-kinematic (Poiseuille) salt flow along the major decollement (channel flow) is required to feed the salt accumulations at the frontal section of the fold belt and the shallow salt diapirs.

Analysis of Variability in HIV-1 Subtype A Strains in Russia Suggests a Combination of Deep Sequencing and Multitarget RNA Interference for Silencing of the Virus.

PubMed

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

2017-02-01

Any method for silencing the activity of the HIV-1 retrovirus should tackle the extremely high variability of HIV-1 sequences and mutational escape. We studied sequence variability in the vicinity of selected RNA interference (RNAi) targets from isolates of HIV-1 subtype A in Russia, and we propose that using artificial RNAi is a potential alternative to traditional antiretroviral therapy. We prove that using multiple RNAi targets overcomes the variability in HIV-1 isolates. The optimal number of targets critically depends on the conservation of the target sequences. The total number of targets that are conserved with a probability of 0.7-0.8 should exceed at least 2. Combining deep sequencing and multitarget RNAi may provide an efficient approach to cure HIV/AIDS.

DeepLoc: prediction of protein subcellular localization using deep learning.

PubMed

Almagro Armenteros, José Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae; Nielsen, Henrik; Winther, Ole

2017-11-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. jjalma@dtu.dk. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

PubMed

Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

2017-09-01

Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein structure prediction in practice. Despite progresses in the past decade on protein targets with abundant homologous sequences, accurate contact prediction for proteins with limited sequence information is still far from satisfaction. Methodologies for these hard targets still need further improvement. We presented a computational program DeepConPred, which includes a pipeline of two novel deep-learning-based methods (DeepCCon and DeepRCon) as well as a contact refinement step, to improve the prediction of long-range residue contacts from primary sequences. When compared with previous prediction approaches, our framework employed an effective scheme to identify optimal and important features for contact prediction, and was only trained with coevolutionary information derived from a limited number of homologous sequences to ensure robustness and usefulness for hard targets. Independent tests showed that 59.33%/49.97%, 64.39%/54.01% and 70.00%/59.81% of the top L/5, top L/10 and top 5 predictions were correct for CASP10/CASP11 proteins, respectively. In general, our algorithm ranked as one of the best methods for CASP targets. All source data and codes are available at http://166.111.152.91/Downloads.html . hgong@tsinghua.edu.cn or zengjy321@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

High-throughput sequencing of the entire genomic regions of CCM1/KRIT1, CCM2 and CCM3/PDCD10 to search for pathogenic deep-intronic splice mutations in cerebral cavernous malformations.

PubMed

Rath, Matthias; Jenssen, Sönke E; Schwefel, Konrad; Spiegler, Stefanie; Kleimeier, Dana; Sperling, Christian; Kaderali, Lars; Felbor, Ute

2017-09-01

Cerebral cavernous malformations (CCM) are vascular lesions of the central nervous system that can cause headaches, seizures and hemorrhagic stroke. Disease-associated mutations have been identified in three genes: CCM1/KRIT1, CCM2 and CCM3/PDCD10. The precise proportion of deep-intronic variants in these genes and their clinical relevance is yet unknown. Here, a long-range PCR (LR-PCR) approach for target enrichment of the entire genomic regions of the three genes was combined with next generation sequencing (NGS) to screen for coding and non-coding variants. NGS detected all six CCM1/KRIT1, two CCM2 and four CCM3/PDCD10 mutations that had previously been identified by Sanger sequencing. Two of the pathogenic variants presented here are novel. Additionally, 20 stringently selected CCM index cases that had remained mutation-negative after conventional sequencing and exclusion of copy number variations were screened for deep-intronic mutations. The combination of bioinformatics filtering and transcript analyses did not reveal any deep-intronic splice mutations in these cases. Our results demonstrate that target enrichment by LR-PCR combined with NGS can be used for a comprehensive analysis of the entire genomic regions of the CCM genes in a research context. However, its clinical utility is limited as deep-intronic splice mutations in CCM1/KRIT1, CCM2 and CCM3/PDCD10 seem to be rather rare. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Musculoskeletal MRI findings of juvenile localized scleroderma.

PubMed

Eutsler, Eric P; Horton, Daniel B; Epelman, Monica; Finkel, Terri; Averill, Lauren W

2017-04-01

Juvenile localized scleroderma comprises a group of autoimmune conditions often characterized clinically by an area of skin hardening. In addition to superficial changes in the skin and subcutaneous tissues, juvenile localized scleroderma may involve the deep soft tissues, bones and joints, possibly resulting in functional impairment and pain in addition to cosmetic changes. There is literature documenting the spectrum of findings for deep involvement of localized scleroderma (fascia, muscles, tendons, bones and joints) in adults, but there is limited literature for the condition in children. We aimed to document the spectrum of musculoskeletal magnetic resonance imaging (MRI) findings of both superficial and deep juvenile localized scleroderma involvement in children and to evaluate the utility of various MRI sequences for detecting those findings. Two radiologists retrospectively evaluated 20 MRI studies of the extremities in 14 children with juvenile localized scleroderma. Each imaging sequence was also given a subjective score of 0 (not useful), 1 (somewhat useful) or 2 (most useful for detecting the findings). Deep tissue involvement was detected in 65% of the imaged extremities. Fascial thickening and enhancement were seen in 50% of imaged extremities. Axial T1, axial T1 fat-suppressed (FS) contrast-enhanced and axial fluid-sensitive sequences were rated most useful. Fascial thickening and enhancement were the most commonly encountered deep tissue findings in extremity MRIs of children with juvenile localized scleroderma. Because abnormalities of the skin, subcutaneous tissues and fascia tend to run longitudinally in an affected limb, axial T1, axial fluid-sensitive and axial T1-FS contrast-enhanced sequences should be included in the imaging protocol.

Molecular Technique to Understand Deep Microbial Diversity

NASA Technical Reports Server (NTRS)

Vaishampayan, Parag A.; Venkateswaran, Kasthuri J.

2012-01-01

Current sequencing-based and DNA microarray techniques to study microbial diversity are based on an initial PCR (polymerase chain reaction) amplification step. However, a number of factors are known to bias PCR amplification and jeopardize the true representation of bacterial diversity. PCR amplification of the minor template appears to be suppressed by the exponential amplification of the more abundant template. It is widely acknowledged among environmental molecular microbiologists that genetic biosignatures identified from an environment only represent the most dominant populations. The technological bottleneck has overlooked the presence of the less abundant minority population, and underestimated their role in the ecosystem maintenance. To generate PCR amplicons for subsequent diversity analysis, bacterial l6S rRNA genes are amplified by PCR using universal primers. Two distinct PCR regimes are employed in parallel: one using normal and the other using biotinlabeled universal primers. PCR products obtained with biotin-labeled primers are mixed with streptavidin-labeled magnetic beads and selectively captured in the presence of a magnetic field. Less-abundant DNA templates that fail to amplify in this first round of PCR amplification are subjected to a second round of PCR using normal universal primers. These PCR products are then subjected to downstream diversity analyses such as conventional cloning and sequencing. A second round of PCR amplified the minority population and completed the deep diversity picture of the environmental sample.

Complete genome sequence of Southern tomato virus naturally infecting tomatoes in Bangladesh using small RNA deep sequencing

USDA-ARS?s Scientific Manuscript database

The complete genome sequence of a Southern tomato virus (STV) isolate on tomato plants in a seed production field in Bangladesh was obtained for the first time using next generation sequencing. The identified isolate STV_BD-13 shares high degree of sequence identity (99%) with several known STV isol...

Complete genome sequence of southern tomato virus identified from China using next generation sequencing

USDA-ARS?s Scientific Manuscript database

Complete genome sequence of a double-stranded RNA (dsRNA) virus, southern tomato virus (STV), on tomatoes in China, was elucidated using small RNAs deep sequencing. The identified STV_CN12 shares 99% sequence identity to other isolates from Mexico, France, Spain, and U.S. This is the first report ...

Deep whole-genome sequencing of 100 southeast Asian Malays.

PubMed

Wong, Lai-Ping; Ong, Rick Twee-Hee; Poh, Wan-Ting; Liu, Xuanyao; Chen, Peng; Li, Ruoying; Lam, Kevin Koi-Yau; Pillai, Nisha Esakimuthu; Sim, Kar-Seng; Xu, Haiyan; Sim, Ngak-Leng; Teo, Shu-Mei; Foo, Jia-Nee; Tan, Linda Wei-Lin; Lim, Yenly; Koo, Seok-Hwee; Gan, Linda Seo-Hwee; Cheng, Ching-Yu; Wee, Sharon; Yap, Eric Peng-Huat; Ng, Pauline Crystal; Lim, Wei-Yen; Soong, Richie; Wenk, Markus Rene; Aung, Tin; Wong, Tien-Yin; Khor, Chiea-Chuen; Little, Peter; Chia, Kee-Seng; Teo, Yik-Ying

2013-01-10

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Deep Whole-Genome Sequencing of 100 Southeast Asian Malays

PubMed Central

Wong, Lai-Ping; Ong, Rick Twee-Hee; Poh, Wan-Ting; Liu, Xuanyao; Chen, Peng; Li, Ruoying; Lam, Kevin Koi-Yau; Pillai, Nisha Esakimuthu; Sim, Kar-Seng; Xu, Haiyan; Sim, Ngak-Leng; Teo, Shu-Mei; Foo, Jia-Nee; Tan, Linda Wei-Lin; Lim, Yenly; Koo, Seok-Hwee; Gan, Linda Seo-Hwee; Cheng, Ching-Yu; Wee, Sharon; Yap, Eric Peng-Huat; Ng, Pauline Crystal; Lim, Wei-Yen; Soong, Richie; Wenk, Markus Rene; Aung, Tin; Wong, Tien-Yin; Khor, Chiea-Chuen; Little, Peter; Chia, Kee-Seng; Teo, Yik-Ying

2013-01-01

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies. PMID:23290073

Transcriptome analysis and identification of induced genes in the response of Harmonia axyridis to cold hardiness.

PubMed

Tang, Bin; Liu, Xiao-Jun; Shi, Zuo-Kun; Shen, Qi-Da; Xu, Yan-Xia; Wang, Su; Zhang, Fan; Wang, Shi-Gui

2017-06-01

Harmonia axyridis is an important predatory lady beetle that is a natural enemy of agricultural and forestry pests. In this research, the cold hardiness induced genes and their expression changes in H. axyridis were screened and detected by the way of the transcriptome and qualitative real-time PCR under normal and low temperatures, using high-throughput transcriptome and digital gene-expression-tag technologies. We obtained a 10Gb transcriptome and an 8Mb gene expression tag pool using Illumina deep sequencing technology and RNA-Seq analysis (accession number SRX540102). Of the 46,980 non-redundant unigenes identified, 28,037 (59.7%) were matched to known genes in GenBank, 21,604 (46.0%) in Swiss-Prot, 19,482 (41.5%) in Kyoto Encyclopedia of Genes and Genomes and 13,193 (28.1%) in Gene Ontology databases. Seventy-five percent of the unigene sequences had top matches with gene sequences from Tribolium castaneum. Results indicated that 60 genes regulated the entire cold-acclimation response, and, of these, seven genes were always up-regulated and five genes always down-regulated. Further screening revealed that six cold-resistant genes, E3 ubiquitin-protein ligase, transketolase, trehalase, serine/arginine repetitive matrix protein 2, glycerol kinase and sugar transporter SWEET1-like, play key roles in the response. Expression from a number of the differentially expressed genes was confirmed with quantitative real-time PCR (HaCS_Trans). The paper attempted to identify cold-resistance response genes, and study the potential mechanism by which cold acclimation enhances the insect's cold endurance. Information on these cold-resistance response genes will improve the development of low-temperature storage technology of natural enemy insects for future use in biological control. Copyright © 2017 Elsevier Inc. All rights reserved.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling

PubMed Central

Wang, Sheng; Sun, Siqi

2017-01-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC. PMID:28884168

Modeling genome coverage in single-cell sequencing

PubMed Central

Daley, Timothy; Smith, Andrew D.

2014-01-01

Motivation: Single-cell DNA sequencing is necessary for examining genetic variation at the cellular level, which remains hidden in bulk sequencing experiments. But because they begin with such small amounts of starting material, the amount of information that is obtained from single-cell sequencing experiment is highly sensitive to the choice of protocol employed and variability in library preparation. In particular, the fraction of the genome represented in single-cell sequencing libraries exhibits extreme variability due to quantitative biases in amplification and loss of genetic material. Results: We propose a method to predict the genome coverage of a deep sequencing experiment using information from an initial shallow sequencing experiment mapped to a reference genome. The observed coverage statistics are used in a non-parametric empirical Bayes Poisson model to estimate the gain in coverage from deeper sequencing. This approach allows researchers to know statistical features of deep sequencing experiments without actually sequencing deeply, providing a basis for optimizing and comparing single-cell sequencing protocols or screening libraries. Availability and implementation: The method is available as part of the preseq software package. Source code is available at http://smithlabresearch.org/preseq. Contact: andrewds@usc.edu Supplementary information: Supplementary material is available at Bioinformatics online. PMID:25107873

De novo Transcriptome Analysis of Portunus trituberculatus Ovary and Testis by RNA-Seq: Identification of Genes Involved in Gonadal Development

PubMed Central

Meng, Xian-liang; Liu, Ping; Jia, Fu-long; Li, Jian; Gao, Bao-Quan

2015-01-01

The swimming crab Portunus trituberculatus is a commercially important crab species in East Asia countries. Gonadal development is a physiological process of great significance to the reproduction as well as commercial seed production for P. trituberculatus. However, little is currently known about the molecular mechanisms governing the developmental processes of gonads in this species. To open avenues of molecular research on P. trituberculatus gonadal development, Illumina paired-end sequencing technology was employed to develop deep-coverage transcriptome sequencing data for its gonads. Illumina sequencing generated 58,429,148 and 70,474,978 high-quality reads from the ovary and testis cDNA library, respectively. All these reads were assembled into 54,960 unigenes with an average sequence length of 879 bp, of which 12,340 unigenes (22.45% of the total) matched sequences in GenBank non-redundant database. Based on our transcriptome analysis as well as published literature, a number of candidate genes potentially involved in the regulation of gonadal development of P. trituberculatus were identified, such as FAOMeT, mPRγ, PGMRC1, PGDS, PGER4, 3β-HSD and 17β-HSDs. Differential expression analysis generated 5,919 differentially expressed genes between ovary and testis, among which many genes related to gametogenesis and several genes previously reported to be critical in differentiation and development of gonads were found, including Foxl2, Wnt4, Fst, Fem-1 and Sox9. Furthermore, 28,534 SSRs and 111,646 high-quality SNPs were identified in this transcriptome dataset. This work represents the first transcriptome analysis of P. trituberculatus gonads using the next generation sequencing technology and provides a valuable dataset for understanding molecular mechanisms controlling development of gonads and facilitating future investigation of reproductive biology in this species. The molecular markers obtained in this study will provide a fundamental basis for population genetics and functional genomics in P. trituberculatus and other closely related species. PMID:26042806

Transcriptome sequencing and identification of cold tolerance genes in hardy Corylus species (C. heterophylla Fisch) floral buds.

PubMed

Chen, Xin; Zhang, Jin; Liu, Qingzhong; Guo, Wei; Zhao, Tiantian; Ma, Qinghua; Wang, Guixi

2014-01-01

The genus Corylus is an important woody species in Northeast China. Its products, hazelnuts, constitute one of the most important raw materials for the pastry and chocolate industry. However, limited genetic research has focused on Corylus because of the lack of genomic resources. The advent of high-throughput sequencing technologies provides a turning point for Corylus research. In the present study, we performed de novo transcriptome sequencing for the first time to produce a comprehensive database for the Corylus heterophylla Fisch floral buds. The C. heterophylla Fisch floral buds transcriptome was sequenced using the Illumina paired-end sequencing technology. We produced 28,930,890 raw reads and assembled them into 82,684 contigs. A total of 40,941 unigenes were identified, among which 30,549 were annotated in the NCBI Non-redundant (Nr) protein database and 18,581 were annotated in the Swiss-Prot database. Of these annotated unigenes, 25,311 and 10,514 unigenes were assigned to gene ontology (GO) categories and clusters of orthologous groups (COG), respectively. We could map 17,207 unigenes onto 128 pathways using the Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) database. Additionally, based on the transcriptome, we constructed a candidate cold tolerance gene set of C. heterophylla Fisch floral buds. The expression patterns of selected genes during four stages of cold acclimation suggested that these genes might be involved in different cold responsive stages in C. heterophylla Fisch floral buds. The transcriptome of C. heterophylla Fisch floral buds was deep sequenced, de novo assembled, and annotated, providing abundant data to better understand the C. heterophylla Fisch floral buds transcriptome. Candidate genes potentially involved in cold tolerance were identified, providing a material basis for future molecular mechanism analysis of C. heterophylla Fisch floral buds tolerant to cold stress.

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

PubMed

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

PubMed

Zhang, Buzhong; Li, Linqing; Lü, Qiang

2018-05-25

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson's correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.

PubMed

Hohman, Fred; Hodas, Nathan; Chau, Duen Horng

2017-05-01

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

INSPIRE and MarCO - Technology Development for the First Deep Space CubeSats

NASA Astrophysics Data System (ADS)

Klesh, Andrew

2016-07-01

INSPIRE (Interplanetary NanoSpacecraft Pathfinder In a Relevant Environment) and MarCO (Mars Cube One) will open the door for tiny spacecraft to explore the solar system. INSPIRE serves as a trailblazer, designed to demonstrate new technology needed for deep space. MarCO will open the door for NanoSpacecraft to serve in support roles for much larger primary missions - in this case, providing a real-time relay of for the InSight project and will likely be the first CubeSats to reach deep space. Together, these four spacecraft (two for each mission) enable fundamental science objectives to be met with tiny vehicles. Originally designed for a March, 2016 launch with the InSight mission to Mars, the MarCO spacecraft are now complete and in storage. When launched with the InSight lander from Vandenberg Air Force Base, the spacecraft will begin a 6.5 month cruise to Mars. Soon after InSight itself separates from the upper stage of the launch vehicle, the two MarCO CubeSats will deploy and independently fly to Mars to support telecommunications relay for InSight's entry, descent, and landing sequence. These spacecraft will have onboard capability for deep space trajectory correction maneuvers; high-speed direct-to-Earth & DSN-compatible communications; an advanced navigation transponder; a large deployable reflect-array high gain antenna; and a robust software suite. This talk will present an overview of the INSPIRE and MarCO projects, including a concept of operations, details of the spacecraft and subsystem design, and lessons learned from integration and test. Finally, the talk will outline how lessons from these spacecraft are already being utilized in the next generation of interplanetary CubeSats, as well as a brief vision of their applicability for solar system exploration. The research described here was carried out at the Jet Propulsion Laboratory, Caltech, under a contract with the National Aeronautics and Space Administration (NASA).

Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma

PubMed Central

Lahuerta, Juan J.; Pepin, François; González, Marcos; Barrio, Santiago; Ayala, Rosa; Puig, Noemí; Montalban, María A.; Paiva, Bruno; Weng, Li; Jiménez, Cristina; Sopena, María; Moorhead, Martin; Cedena, Teresa; Rapado, Immaculada; Mateos, María Victoria; Rosiñol, Laura; Oriol, Albert; Blanchard, María J.; Martínez, Rafael; Bladé, Joan; San Miguel, Jesús; Faham, Malek; García-Sanz, Ramón

2014-01-01

We assessed the prognostic value of minimal residual disease (MRD) detection in multiple myeloma (MM) patients using a sequencing-based platform in bone marrow samples from 133 MM patients in at least very good partial response (VGPR) after front-line therapy. Deep sequencing was carried out in patients in whom a high-frequency myeloma clone was identified and MRD was assessed using the IGH-VDJH, IGH-DJH, and IGK assays. The results were contrasted with those of multiparametric flow cytometry (MFC) and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR). The applicability of deep sequencing was 91%. Concordance between sequencing and MFC and ASO-PCR was 83% and 85%, respectively. Patients who were MRD– by sequencing had a significantly longer time to tumor progression (TTP) (median 80 vs 31 months; P < .0001) and overall survival (median not reached vs 81 months; P = .02), compared with patients who were MRD+. When stratifying patients by different levels of MRD, the respective TTP medians were: MRD ≥10−3 27 months, MRD 10−3 to 10−5 48 months, and MRD <10−5 80 months (P = .003 to .0001). Ninety-two percent of VGPR patients were MRD+. In complete response patients, the TTP remained significantly longer for MRD– compared with MRD+ patients (131 vs 35 months; P = .0009). PMID:24646471

Strategic Technologies for Deep Space Transport

NASA Technical Reports Server (NTRS)

Litchford, Ronald J.

2016-01-01

Deep space transportation capability for science and exploration is fundamentally limited by available propulsion technologies. Traditional chemical systems are performance plateaued and require enormous Initial Mass in Low Earth Orbit (IMLEO) whereas solar electric propulsion systems are power limited and unable to execute rapid transits. Nuclear based propulsion and alternative energetic methods, on the other hand, represent potential avenues, perhaps the only viable avenues, to high specific power space transport evincing reduced trip time, reduced IMLEO, and expanded deep space reach. Here, key deep space transport mission capability objectives are reviewed in relation to STMD technology portfolio needs, and the advanced propulsion technology solution landscape is examined including open questions, technical challenges, and developmental prospects. Options for potential future investment across the full compliment of STMD programs are presented based on an informed awareness of complimentary activities in industry, academia, OGAs, and NASA mission directorates.

Complete genome sequence of a tomato infecting tomato mottle mosaic virus in New York

USDA-ARS?s Scientific Manuscript database

Complete genome sequence of an emerging isolate of tomato mottle mosaic virus (ToMMV) infecting experimental nicotianan benthamiana plants in up-state New York was obtained using small RNA deep sequencing. ToMMV_NY-13 shared 99% sequence identity to ToMMV isolates from Mexico and Florida. Broader d...

Technical-economical analysis of selected decentralized technologies for municipal wastewater treatment in the city of Rome.

PubMed

Gavasci, Renato; Chiavola, Agostina; Spizzirri, Massimo

2010-01-01

Several wastewater treatment technologies were evaluated as alternative systems to the more traditional centralized continuous flow system to serve decentralized areas of the city of Rome (Italy). For instance, the following technologies were selected: (1) Constructed wetlands, (2) Membrane Biological Reactor, (3) Deep Shaft, (4) Sequencing Batch Reactor, and (5) Combined Filtration and UV-disinfection. Such systems were distinguished based on the limits they are potentially capable of accomplishing on the effluent. Consequently, the SBR and DS were grouped together for their capability to comply with the standards for the discharge into surface waters (according to the Italian D.Lgs. 152/06, Table 1, All. 5), whereas the MBR and tertiary system (Filtration+UVc-disinfection) were considered together as they should be able to allow effluent discharge into soil (according to the Italian D.Lgs. 152/06, Table 4, All. 5) and/or reuse (according to the Italian D.M. 185/03). Both groups of technologies were evaluated in comparison with the more common continuous flow treatment sequence consisting of a biological activated sludge tank followed by the secondary settlement, with final chlorination. CWs were studied separately as a solution for decentralized urban areas with limited population. After the analysis of the main technical features, an economical estimate was carried out taking into account the investment, operation and maintenance costs as a function of the plant's capacity. The analysis was based on real data provided by the Company who manages the entire water system of the City of Rome (Acea Ato 2 S.p.A.). A preliminary design of the treatment plants using some of the selected technologies was finally carried out.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine.

PubMed

Heuckmann, J M; Thomas, R K

2015-09-01

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Molecular Definition of Vaginal Microbiota in East African Commercial Sex Workers ▿ †

PubMed Central

Schellenberg, John J.; Links, Matthew G.; Hill, Janet E.; Dumonceaux, Tim J.; Kimani, Joshua; Jaoko, Walter; Wachihi, Charles; Mungai, Jane Njeri; Peters, Geoffrey A.; Tyler, Shaun; Graham, Morag; Severini, Alberto; Fowke, Keith R.; Ball, T. Blake; Plummer, Francis A.

2011-01-01

Resistance to HIV infection in a cohort of commercial sex workers living in Nairobi, Kenya, is linked to mucosal and antiinflammatory factors that may be influenced by the vaginal microbiota. Since bacterial vaginosis (BV), a polymicrobial dysbiosis characterized by low levels of protective Lactobacillus organisms, is an established risk factor for HIV infection, we investigated whether vaginal microbiology was associated with HIV-exposed seronegative (HESN) or HIV-seropositive (HIV+) status in this cohort. A subset of 44 individuals was selected for deep-sequencing analysis based on the chaperonin 60 (cpn60) universal target (UT), including HESN individuals (n = 16), other HIV-seronegative controls (HIV-N, n = 16), and HIV+ individuals (n = 12). Our findings indicate exceptionally high phylogenetic resolution of the cpn60 UT using reads as short as 200 bp, with 54 species in 29 genera detected in this group. Contrary to our initial hypothesis, few differences between HESN and HIV-N women were observed. Several HIV+ women had distinct profiles dominated by Escherichia coli. The deep-sequencing phylogenetic profile of the vaginal microbiota corresponds closely to BV+ and BV− diagnoses by microscopy, elucidating BV at the molecular level. A cluster of samples with intermediate abundance of Lactobacillus and dominant Gardnerella was identified, defining a distinct BV phenotype that may represent a transitional stage between BV+ and BV−. Several alpha- and betaproteobacteria, including the recently described species Variovorax paradoxus, were found to correlate positively with increased Lactobacillus levels that define the BV− (“normal”) phenotype. We conclude that cpn60 UT is ideally suited to next-generation sequencing technologies for further investigation of microbial community dynamics and mucosal immunity underlying HIV resistance in this cohort. PMID:21531840

Identification and Removal of Contaminant Sequences From Ribosomal Gene Databases: Lessons From the Census of Deep Life

PubMed Central

Sheik, Cody S.; Reese, Brandi Kiel; Twing, Katrina I.; Sylvan, Jason B.; Grim, Sharon L.; Schrenk, Matthew O.; Sogin, Mitchell L.; Colwell, Frederick S.

2018-01-01

Earth’s subsurface environment is one of the largest, yet least studied, biomes on Earth, and many questions remain regarding what microorganisms are indigenous to the subsurface. Through the activity of the Census of Deep Life (CoDL) and the Deep Carbon Observatory, an open access 16S ribosomal RNA gene sequence database from diverse subsurface environments has been compiled. However, due to low quantities of biomass in the deep subsurface, the potential for incorporation of contaminants from reagents used during sample collection, processing, and/or sequencing is high. Thus, to understand the ecology of subsurface microorganisms (i.e., the distribution, richness, or survival), it is necessary to minimize, identify, and remove contaminant sequences that will skew the relative abundances of all taxa in the sample. In this meta-analysis, we identify putative contaminants associated with the CoDL dataset, recommend best practices for removing contaminants from samples, and propose a series of best practices for subsurface microbiology sampling. The most abundant putative contaminant genera observed, independent of evenness across samples, were Propionibacterium, Aquabacterium, Ralstonia, and Acinetobacter. While the top five most frequently observed genera were Pseudomonas, Propionibacterium, Acinetobacter, Ralstonia, and Sphingomonas. The majority of the most frequently observed genera (high evenness) were associated with reagent or potential human contamination. Additionally, in DNA extraction blanks, we observed potential archaeal contaminants, including methanogens, which have not been discussed in previous contamination studies. Such contaminants would directly affect the interpretation of subsurface molecular studies, as methanogenesis is an important subsurface biogeochemical process. Utilizing previously identified contaminant genera, we found that ∼27% of the total dataset were identified as contaminant sequences that likely originate from DNA extraction and DNA cleanup methods. Thus, controls must be taken at every step of the collection and processing procedure when working with low biomass environments such as, but not limited to, portions of Earth’s deep subsurface. Taken together, we stress that the CoDL dataset is an incredible resource for the broader research community interested in subsurface life, and steps to remove contamination derived sequences must be taken prior to using this dataset. PMID:29780369

Low-abundance HIV drug-resistant viral variants in treatment-experienced persons correlate with historical antiretroviral use.

PubMed

Le, Thuy; Chiarella, Jennifer; Simen, Birgitte B; Hanczaruk, Bozena; Egholm, Michael; Landry, Marie L; Dieckhaus, Kevin; Rosen, Marc I; Kozal, Michael J

2009-06-29

It is largely unknown how frequently low-abundance HIV drug-resistant variants at levels under limit of detection of conventional genotyping (<20% of quasi-species) are present in antiretroviral-experienced persons experiencing virologic failure. Further, the clinical implications of low-abundance drug-resistant variants at time of virologic failure are unknown. Plasma samples from 22 antiretroviral-experienced subjects collected at time of virologic failure (viral load 1380 to 304,000 copies/mL) were obtained from a specimen bank (from 2004-2007). The prevalence and profile of drug-resistant mutations were determined using Sanger sequencing and ultra-deep pyrosequencing. Genotypes were interpreted using Stanford HIV database algorithm. Antiretroviral treatment histories were obtained by chart review and correlated with drug-resistant mutations. Low-abundance drug-resistant mutations were detected in all 22 subjects by deep sequencing and only in 3 subjects by Sanger sequencing. In total they accounted for 90 of 247 mutations (36%) detected by deep sequencing; the majority of these (95%) were not detected by standard genotyping. A mean of 4 additional mutations per subject were detected by deep sequencing (p<0.0001, 95%CI: 2.85-5.53). The additional low-abundance drug-resistant mutations increased a subject's genotypic resistance to one or more antiretrovirals in 17 of 22 subjects (77%). When correlated with subjects' antiretroviral treatment histories, the additional low-abundance drug-resistant mutations correlated with the failing antiretroviral drugs in 21% subjects and correlated with historical antiretroviral use in 79% subjects (OR, 13.73; 95% CI, 2.5-74.3, p = 0.0016). Low-abundance HIV drug-resistant mutations in antiretroviral-experienced subjects at time of virologic failure can increase a subject's overall burden of resistance, yet commonly go unrecognized by conventional genotyping. The majority of unrecognized resistant mutations correlate with historical antiretroviral use. Ultra-deep sequencing can provide important historical resistance information for clinicians when planning subsequent antiretroviral regimens for highly treatment-experienced patients, particularly when their prior treatment histories and longitudinal genotypes are not available.

Low-Abundance HIV Drug-Resistant Viral Variants in Treatment-Experienced Persons Correlate with Historical Antiretroviral Use

PubMed Central

Le, Thuy; Chiarella, Jennifer; Simen, Birgitte B.; Hanczaruk, Bozena; Egholm, Michael; Landry, Marie L.; Dieckhaus, Kevin; Rosen, Marc I.; Kozal, Michael J.

2009-01-01

Background It is largely unknown how frequently low-abundance HIV drug-resistant variants at levels under limit of detection of conventional genotyping (<20% of quasi-species) are present in antiretroviral-experienced persons experiencing virologic failure. Further, the clinical implications of low-abundance drug-resistant variants at time of virologic failure are unknown. Methodology/Principal Findings Plasma samples from 22 antiretroviral-experienced subjects collected at time of virologic failure (viral load 1380 to 304,000 copies/mL) were obtained from a specimen bank (from 2004–2007). The prevalence and profile of drug-resistant mutations were determined using Sanger sequencing and ultra-deep pyrosequencing. Genotypes were interpreted using Stanford HIV database algorithm. Antiretroviral treatment histories were obtained by chart review and correlated with drug-resistant mutations. Low-abundance drug-resistant mutations were detected in all 22 subjects by deep sequencing and only in 3 subjects by Sanger sequencing. In total they accounted for 90 of 247 mutations (36%) detected by deep sequencing; the majority of these (95%) were not detected by standard genotyping. A mean of 4 additional mutations per subject were detected by deep sequencing (p<0.0001, 95%CI: 2.85–5.53). The additional low-abundance drug-resistant mutations increased a subject's genotypic resistance to one or more antiretrovirals in 17 of 22 subjects (77%). When correlated with subjects' antiretroviral treatment histories, the additional low-abundance drug-resistant mutations correlated with the failing antiretroviral drugs in 21% subjects and correlated with historical antiretroviral use in 79% subjects (OR, 13.73; 95% CI, 2.5–74.3, p = 0.0016). Conclusions/Significance Low-abundance HIV drug-resistant mutations in antiretroviral-experienced subjects at time of virologic failure can increase a subject's overall burden of resistance, yet commonly go unrecognized by conventional genotyping. The majority of unrecognized resistant mutations correlate with historical antiretroviral use. Ultra-deep sequencing can provide important historical resistance information for clinicians when planning subsequent antiretroviral regimens for highly treatment-experienced patients, particularly when their prior treatment histories and longitudinal genotypes are not available. PMID:19562031

Identification and Removal of Contaminant Sequences From Ribosomal Gene Databases: Lessons From the Census of Deep Life.

PubMed

Sheik, Cody S; Reese, Brandi Kiel; Twing, Katrina I; Sylvan, Jason B; Grim, Sharon L; Schrenk, Matthew O; Sogin, Mitchell L; Colwell, Frederick S

2018-01-01

Earth's subsurface environment is one of the largest, yet least studied, biomes on Earth, and many questions remain regarding what microorganisms are indigenous to the subsurface. Through the activity of the Census of Deep Life (CoDL) and the Deep Carbon Observatory, an open access 16S ribosomal RNA gene sequence database from diverse subsurface environments has been compiled. However, due to low quantities of biomass in the deep subsurface, the potential for incorporation of contaminants from reagents used during sample collection, processing, and/or sequencing is high. Thus, to understand the ecology of subsurface microorganisms (i.e., the distribution, richness, or survival), it is necessary to minimize, identify, and remove contaminant sequences that will skew the relative abundances of all taxa in the sample. In this meta-analysis, we identify putative contaminants associated with the CoDL dataset, recommend best practices for removing contaminants from samples, and propose a series of best practices for subsurface microbiology sampling. The most abundant putative contaminant genera observed, independent of evenness across samples, were Propionibacterium , Aquabacterium , Ralstonia , and Acinetobacter . While the top five most frequently observed genera were Pseudomonas , Propionibacterium , Acinetobacter , Ralstonia , and Sphingomonas . The majority of the most frequently observed genera (high evenness) were associated with reagent or potential human contamination. Additionally, in DNA extraction blanks, we observed potential archaeal contaminants, including methanogens, which have not been discussed in previous contamination studies. Such contaminants would directly affect the interpretation of subsurface molecular studies, as methanogenesis is an important subsurface biogeochemical process. Utilizing previously identified contaminant genera, we found that ∼27% of the total dataset were identified as contaminant sequences that likely originate from DNA extraction and DNA cleanup methods. Thus, controls must be taken at every step of the collection and processing procedure when working with low biomass environments such as, but not limited to, portions of Earth's deep subsurface. Taken together, we stress that the CoDL dataset is an incredible resource for the broader research community interested in subsurface life, and steps to remove contamination derived sequences must be taken prior to using this dataset.

Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish

PubMed Central

2010-01-01

Background Systematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE) are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish. Results RNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution. Conclusion This study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host-pathogen interactions and evolutionary history of immunogenetics from fish to mammals. PMID:20707909

Implementing Distributed Operations: A Comparison of Two Deep Space Missions

NASA Technical Reports Server (NTRS)

Mishkin, Andrew; Larsen, Barbara

2006-01-01

Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.

Using pyrosequencing to shed light on deep mine microbial ecology

PubMed Central

Edwards, Robert A; Rodriguez-Brito, Beltran; Wegley, Linda; Haynes, Matthew; Breitbart, Mya; Peterson, Dean M; Saar, Martin O; Alexander, Scott; Alexander, E Calvin; Rohwer, Forest

2006-01-01

Background Contrasting biological, chemical and hydrogeological analyses highlights the fundamental processes that shape different environments. Generating and interpreting the biological sequence data was a costly and time-consuming process in defining an environment. Here we have used pyrosequencing, a rapid and relatively inexpensive sequencing technology, to generate environmental genome sequences from two sites in the Soudan Mine, Minnesota, USA. These sites were adjacent to each other, but differed significantly in chemistry and hydrogeology. Results Comparisons of the microbes and the subsystems identified in the two samples highlighted important differences in metabolic potential in each environment. The microbes were performing distinct biochemistry on the available substrates, and subsystems such as carbon utilization, iron acquisition mechanisms, nitrogen assimilation, and respiratory pathways separated the two communities. Although the correlation between much of the microbial metabolism occurring and the geochemical conditions from which the samples were isolated could be explained, the reason for the presence of many pathways in these environments remains to be determined. Despite being physically close, these two communities were markedly different from each other. In addition, the communities were also completely different from other microbial communities sequenced to date. Conclusion We anticipate that pyrosequencing will be widely used to sequence environmental samples because of the speed, cost, and technical advantages. Furthermore, subsystem comparisons rapidly identify the important metabolisms employed by the microbes in different environments. PMID:16549033

Graphical classification of DNA sequences of HLA alleles by deep learning.

PubMed

Miyake, Jun; Kaneshita, Yuhei; Asatani, Satoshi; Tagawa, Seiichi; Niioka, Hirohiko; Hirano, Takashi

2018-04-01

Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence "Deep Learning (Stacked autoencoder)". Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno Polymorphism Database, were compressed to 2-dimensional representation and were plotted. Profiles of the two-dimensional plots indicate that the alleles can be classified as clusters are formed. The two-dimensional plot of HLA-A DNAs gives a clear outlook for characterizing the various alleles.

Enhanced arbovirus surveillance with deep sequencing: Identification of novel rhabdoviruses and bunyaviruses in Australian mosquitoes.

PubMed

Coffey, Lark L; Page, Brady L; Greninger, Alexander L; Herring, Belinda L; Russell, Richard C; Doggett, Stephen L; Haniotis, John; Wang, Chunlin; Deng, Xutao; Delwart, Eric L

2014-01-05

Viral metagenomics characterizes known and identifies unknown viruses based on sequence similarities to any previously sequenced viral genomes. A metagenomics approach was used to identify virus sequences in Australian mosquitoes causing cytopathic effects in inoculated mammalian cell cultures. Sequence comparisons revealed strains of Liao Ning virus (Reovirus, Seadornavirus), previously detected only in China, livestock-infecting Stretch Lagoon virus (Reovirus, Orbivirus), two novel dimarhabdoviruses, named Beaumont and North Creek viruses, and two novel orthobunyaviruses, named Murrumbidgee and Salt Ash viruses. The novel virus proteomes diverged by ≥ 50% relative to their closest previously genetically characterized viral relatives. Deep sequencing also generated genomes of Warrego and Wallal viruses, orbiviruses linked to kangaroo blindness, whose genomes had not been fully characterized. This study highlights viral metagenomics in concert with traditional arbovirus surveillance to characterize known and new arboviruses in field-collected mosquitoes. Follow-up epidemiological studies are required to determine whether the novel viruses infect humans. © 2013 Elsevier Inc. All rights reserved.

3' terminal diversity of MRP RNA and other human noncoding RNAs revealed by deep sequencing.

PubMed

Goldfarb, Katherine C; Cech, Thomas R

2013-09-21

Post-transcriptional 3' end processing is a key component of RNA regulation. The abundant and essential RNA subunit of RNase MRP has been proposed to function in three distinct cellular compartments and therefore may utilize this mode of regulation. Here we employ 3' RACE coupled with high-throughput sequencing to characterize the 3' terminal sequences of human MRP RNA and other noncoding RNAs that form RNP complexes. The 3' terminal sequence of MRP RNA from HEK293T cells has a distinctive distribution of genomically encoded termini (including an assortment of U residues) with a portion of these selectively tagged by oligo(A) tails. This profile contrasts with the relatively homogenous 3' terminus of an in vitro transcribed MRP RNA control and the differing 3' terminal profiles of U3 snoRNA, RNase P RNA, and telomerase RNA (hTR). 3' RACE coupled with deep sequencing provides a valuable framework for the functional characterization of 3' terminal sequences of noncoding RNAs.

Multiplicity and molecular epidemiology of Plasmodium vivax and Plasmodium falciparum infections in East Africa.

PubMed

Zhong, Daibin; Lo, Eugenia; Wang, Xiaoming; Yewhalaw, Delenasaw; Zhou, Guofa; Atieli, Harrysone E; Githeko, Andrew; Hemming-Schroeder, Elizabeth; Lee, Ming-Chieh; Afrane, Yaw; Yan, Guiyun

2018-05-02

Parasite genetic diversity and multiplicity of infection (MOI) affect clinical outcomes, response to drug treatment and naturally-acquired or vaccine-induced immunity. Traditional methods often underestimate the frequency and diversity of multiclonal infections due to technical sensitivity and specificity. Next-generation sequencing techniques provide a novel opportunity to study complexity of parasite populations and molecular epidemiology. Symptomatic and asymptomatic Plasmodium vivax samples were collected from health centres/hospitals and schools, respectively, from 2011 to 2015 in Ethiopia. Similarly, both symptomatic and asymptomatic Plasmodium falciparum samples were collected, respectively, from hospitals and schools in 2005 and 2015 in Kenya. Finger-pricked blood samples were collected and dried on filter paper. Long amplicon (> 400 bp) deep sequencing of merozoite surface protein 1 (msp1) gene was conducted to determine multiplicity and molecular epidemiology of P. vivax and P. falciparum infections. The results were compared with those based on short amplicon (117 bp) deep sequencing. A total of 139 P. vivax and 222 P. falciparum samples were pyro-sequenced for pvmsp1 and pfmsp1, yielding a total of 21 P. vivax and 99 P. falciparum predominant haplotypes. The average MOI for P. vivax and P. falciparum were 2.16 and 2.68, respectively, which were significantly higher than that of microsatellite markers and short amplicon (117 bp) deep sequencing. Multiclonal infections were detected in 62.2% of the samples for P. vivax and 74.8% of the samples for P. falciparum. Four out of the five subjects with recurrent P. vivax malaria were found to be a relapse 44-65 days after clearance of parasites. No difference was observed in MOI among P. vivax patients of different symptoms, ages and genders. Similar patterns were also observed in P. falciparum except for one study site in Kenyan lowland areas with significantly higher MOI. The study used a novel method to evaluate Plasmodium MOI and molecular epidemiological patterns by long amplicon ultra-deep sequencing. The complexity of infections were similar among age groups, symptoms, genders, transmission settings (spatial heterogeneity), as well as over years (pre- vs. post-scale-up interventions). This study demonstrated that long amplicon deep sequencing is a useful tool to investigate multiplicity and molecular epidemiology of Plasmodium parasite infections.

Persistence and evolution of allergen-specific IgE repertoires during subcutaneous specific immunotherapy

PubMed Central

Levin, Mattias; King, Jasmine J.; Glanville, Jacob; Jackson, Katherine J. L.; Looney, Timothy J.; Hoh, Ramona A.; Mari, Adriano; Andersson, Morgan; Greiff, Lennart; Fire, Andrew Z.; Boyd, Scott D.; Ohlin, Mats

2016-01-01

Background Specific immunotherapy (SIT) is the only treatment with proven long-term curative potential in allergic disease. Allergen-specific IgE is the causative agent of allergic disease, and antibodies contribute to SIT, but the effects of SIT on aeroallergen-specific B cell repertoires are not well understood. Objective To characterize the IgE sequences expressed by allergen-specific B cells, and track the fate of these B cell clones during SIT. Methods We have used high-throughput antibody gene sequencing and identification of allergen-specific IgE using combinatorial antibody fragment library technology to analyze immunoglobulin repertoires of blood and nasal mucosa of aeroallergen-sensitized individuals before and during the first year of subcutaneous SIT. Results Of 52 distinct allergen-specific IgE heavy chains from eight allergic donors, 37 were also detected by high-throughput antibody gene sequencing of blood, nasal mucosa, or both sample types. The allergen-specific clones had increased persistence, higher likelihood of belonging to clones expressing other switched isotypes, and possibly larger clone size than the rest of the IgE repertoire. Clone members in nasal tissue showed close mutational relationships. Conclusion Combining functional binding studies, deep antibody repertoire sequencing, and information on clinical outcomes in larger studies may in the future aid assessment of SIT mechanisms and efficacy. PMID:26559321

MicroRNA repertoire for functional genome research in tilapia identified by deep sequencing.

PubMed

Yan, Biao; Wang, Zhen-Hua; Zhu, Chang-Dong; Guo, Jin-Tao; Zhao, Jin-Liang

2014-08-01

The Nile tilapia (Oreochromis niloticus; Cichlidae) is an economically important species in aquaculture and occupies a prominent position in the aquaculture industry. MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression involved in diverse biological and metabolic processes. To increase the repertoire of miRNAs characterized in tilapia, we used the Illumina/Solexa sequencing technology to sequence a small RNA library using pooled RNA sample isolated from the different developmental stages of tilapia. Bioinformatic analyses suggest that 197 conserved and 27 novel miRNAs are expressed in tilapia. Sequence alignments indicate that all tested miRNAs and miRNAs* are highly conserved across many species. In addition, we characterized the tissue expression patterns of five miRNAs using real-time quantitative PCR. We found that miR-1/206, miR-7/9, and miR-122 is abundantly expressed in muscle, brain, and liver, respectively, implying a potential role in the regulation of tissue differentiation or the maintenance of tissue identity. Overall, our results expand the number of tilapia miRNAs, and the discovery of miRNAs in tilapia genome contributes to a better understanding the role of miRNAs in regulating diverse biological processes.

Antisense Transcription Is Pervasive but Rarely Conserved in Enteric Bacteria

PubMed Central

Raghavan, Rahul; Sloan, Daniel B.; Ochman, Howard

2012-01-01

ABSTRACT Noncoding RNAs, including antisense RNAs (asRNAs) that originate from the complementary strand of protein-coding genes, are involved in the regulation of gene expression in all domains of life. Recent application of deep-sequencing technologies has revealed that the transcription of asRNAs occurs genome-wide in bacteria. Although the role of the vast majority of asRNAs remains unknown, it is often assumed that their presence implies important regulatory functions, similar to those of other noncoding RNAs. Alternatively, many antisense transcripts may be produced by chance transcription events from promoter-like sequences that result from the degenerate nature of bacterial transcription factor binding sites. To investigate the biological relevance of antisense transcripts, we compared genome-wide patterns of asRNA expression in closely related enteric bacteria, Escherichia coli and Salmonella enterica serovar Typhimurium, by performing strand-specific transcriptome sequencing. Although antisense transcripts are abundant in both species, less than 3% of asRNAs are expressed at high levels in both species, and only about 14% appear to be conserved among species. And unlike the promoters of protein-coding genes, asRNA promoters show no evidence of sequence conservation between, or even within, species. Our findings suggest that many or even most bacterial asRNAs are nonadaptive by-products of the cell’s transcription machinery. PMID:22872780

From museums to genomics: old herbarium specimens shed light on a C3 to C4 transition.

PubMed

Besnard, Guillaume; Christin, Pascal-Antoine; Malé, Pierre-Jean G; Lhuillier, Emeline; Lauzeral, Christine; Coissac, Eric; Vorontsova, Maria S

2014-12-01

Collections of specimens held by natural history museums are invaluable material for biodiversity inventory and evolutionary studies, with specimens accumulated over 300 years readily available for sampling. Unfortunately, most museum specimens yield low-quality DNA. Recent advances in sequencing technologies, so called next-generation sequencing, are revolutionizing phylogenetic investigations at a deep level. Here, the Illumina technology (HiSeq) was used on herbarium specimens of Sartidia (subfamily Aristidoideae, Poaceae), a small African-Malagasy grass lineage (six species) characteristic of wooded savannas, which is the C3 sister group of Stipagrostis, an important C4 genus from Africa and SW Asia. Complete chloroplast and nuclear ribosomal sequences were assembled for two Sartidia species, one of which (S. perrieri) is only known from a single specimen collected in Madagascar 100 years ago. Partial sequences of a few single-copy genes encoding phosphoenolpyruvate carboxylases (ppc) and malic enzymes (nadpme) were also assembled. Based on these data, the phylogenetic position of Malagasy Sartidia in the subfamily Aristidoideae was investigated and the biogeographical history of this genus was analysed with full species sampling. The evolutionary history of two genes for C4 photosynthesis (ppc-aL1b and nadpme-IV) in the group was also investigated. The gene encoding the C4 phosphoenolpyruvate caroxylase of Stipagrostis is absent from S. dewinteri suggesting that it is not essential in C3 members of the group, which might have favoured its recruitment into a new metabolic pathway. Altogether, the inclusion of historical museum specimens in phylogenomic analyses of biodiversity opens new avenues for evolutionary studies. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Biology of lung cancer: genetic mutation, epithelial-mesenchymal transition, and cancer stem cells.

PubMed

Aoi, Takashi

2016-09-01

At present, most cases of unresectable cancer cannot be cured. Genetic mutations, EMT, and cancer stem cells are three major issues linked to poor prognosis in such cases, all connected by inter- and intra-tumor heterogeneity. Issues on inter-/intra-tumor heterogeneity of genetic mutation could be resolved with recent and future technologies of deep sequencers, whereas, regarding such issues as the "same genome, different epigenome/phenotype", we expect to solve many of these problems in the future through further research in stem cell biology. We herein review and discuss the three major issues in the biology of cancers, especially from the standpoint of stem cell biology.

Flight Software Implementation of the Beacon Monitor Expreiment On the NASA New Millennium Deep Space 1 (DS-1) Mission

NASA Technical Reports Server (NTRS)

Foster, R.; Schlutsmeyer, A.

1997-01-01

A new technology that can lower the cost of mission operations on future spacecraft will be tested on the NASA New Millennium Deep Space 1 (DS-1) Mission. This technology, the Beacon Monitor Experiment (BMOX), can be used to reduce the Deep Space Network (DSN) tracking time and its associated costs on future missions.

Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification

PubMed Central

2013-01-01

Background Next-generation-sequencing (NGS) technologies combined with a classic DNA barcoding approach have enabled fast and credible measurement for biodiversity of mixed environmental samples. However, the PCR amplification involved in nearly all existing NGS protocols inevitably introduces taxonomic biases. In the present study, we developed new Illumina pipelines without PCR amplifications to analyze terrestrial arthropod communities. Results Mitochondrial enrichment directly followed by Illumina shotgun sequencing, at an ultra-high sequence volume, enabled the recovery of Cytochrome c Oxidase subunit 1 (COI) barcode sequences, which allowed for the estimation of species composition at high fidelity for a terrestrial insect community. With 15.5 Gbp Illumina data, approximately 97% and 92% were detected out of the 37 input Operational Taxonomic Units (OTUs), whether the reference barcode library was used or not, respectively, while only 1 novel OTU was found for the latter. Additionally, relatively strong correlation between the sequencing volume and the total biomass was observed for species from the bulk sample, suggesting a potential solution to reveal relative abundance. Conclusions The ability of the new Illumina PCR-free pipeline for DNA metabarcoding to detect small arthropod specimens and its tendency to avoid most, if not all, false positives suggests its great potential in biodiversity-related surveillance, such as in biomonitoring programs. However, further improvement for mitochondrial enrichment is likely needed for the application of the new pipeline in analyzing arthropod communities at higher diversity. PMID:23587339

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

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

Hohman, Frederick M.; Hodas, Nathan O.; Chau, Duen Horng

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

Complete genome sequence of a novel genotype of squash mosaic virus

USDA-ARS?s Scientific Manuscript database

Complete genome sequence of a novel genotype of Squash mosaic virus (SqMV) infecting squash plants in Spain was obtained using deep sequencing of small ribonucleic acids and assembly. The low nucleotide sequence identities, with 87-88% on RNA1 and 84-86% on RNA2 to known SqMV isolates, suggest a new...

First complete genome sequence of an emerging cucumber green mottle mosaic virus isolate in North America

USDA-ARS?s Scientific Manuscript database

The complete genome sequence (6,423 nt) of an emerging Cucumber green mottle mosaic virus (CGMMV) isolate on cucumber in North America was determined through deep sequencing of sRNA and rapid amplification of cDNA ends. It shares 99% nucleotide sequence identity to the Asian genotype, but only 90% t...

A Comprehensive Phylogenetic Analysis of the Scleractinia (Cnidaria, Anthozoa) Based on Mitochondrial CO1 Sequence Data

PubMed Central

Kitahara, Marcelo V.; Cairns, Stephen D.; Stolarski, Jarosław; Blair, David; Miller, David J.

2010-01-01

Background Classical morphological taxonomy places the approximately 1400 recognized species of Scleractinia (hard corals) into 27 families, but many aspects of coral evolution remain unclear despite the application of molecular phylogenetic methods. In part, this may be a consequence of such studies focusing on the reef-building (shallow water and zooxanthellate) Scleractinia, and largely ignoring the large number of deep-sea species. To better understand broad patterns of coral evolution, we generated molecular data for a broad and representative range of deep sea scleractinians collected off New Caledonia and Australia during the last decade, and conducted the most comprehensive molecular phylogenetic analysis to date of the order Scleractinia. Methodology Partial (595 bp) sequences of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene were determined for 65 deep-sea (azooxanthellate) scleractinians and 11 shallow-water species. These new data were aligned with 158 published sequences, generating a 234 taxon dataset representing 25 of the 27 currently recognized scleractinian families. Principal Findings/Conclusions There was a striking discrepancy between the taxonomic validity of coral families consisting predominantly of deep-sea or shallow-water species. Most families composed predominantly of deep-sea azooxanthellate species were monophyletic in both maximum likelihood and Bayesian analyses but, by contrast (and consistent with previous studies), most families composed predominantly of shallow-water zooxanthellate taxa were polyphyletic, although Acroporidae, Poritidae, Pocilloporidae, and Fungiidae were exceptions to this general pattern. One factor contributing to this inconsistency may be the greater environmental stability of deep-sea environments, effectively removing taxonomic “noise” contributed by phenotypic plasticity. Our phylogenetic analyses imply that the most basal extant scleractinians are azooxanthellate solitary corals from deep-water, their divergence predating that of the robust and complex corals. Deep-sea corals are likely to be critical to understanding anthozoan evolution and the origins of the Scleractinia. PMID:20628613

Comprehensive discovery of noncoding RNAs in acute myeloid leukemia cell transcriptomes.

PubMed

Zhang, Jin; Griffith, Malachi; Miller, Christopher A; Griffith, Obi L; Spencer, David H; Walker, Jason R; Magrini, Vincent; McGrath, Sean D; Ly, Amy; Helton, Nichole M; Trissal, Maria; Link, Daniel C; Dang, Ha X; Larson, David E; Kulkarni, Shashikant; Cordes, Matthew G; Fronick, Catrina C; Fulton, Robert S; Klco, Jeffery M; Mardis, Elaine R; Ley, Timothy J; Wilson, Richard K; Maher, Christopher A

2017-11-01

To detect diverse and novel RNA species comprehensively, we compared deep small RNA and RNA sequencing (RNA-seq) methods applied to a primary acute myeloid leukemia (AML) sample. We were able to discover previously unannotated small RNAs using deep sequencing of a library method using broader insert size selection. We analyzed the long noncoding RNA (lncRNA) landscape in AML by comparing deep sequencing from multiple RNA-seq library construction methods for the sample that we studied and then integrating RNA-seq data from 179 AML cases. This identified lncRNAs that are completely novel, differentially expressed, and associated with specific AML subtypes. Our study revealed the complexity of the noncoding RNA transcriptome through a combined strategy of strand-specific small RNA and total RNA-seq. This dataset will serve as an invaluable resource for future RNA-based analyses. Copyright © 2017 ISEH – Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

Development of a candidate reference material for adventitious virus detection in vaccine and biologicals manufacturing by deep sequencing

PubMed Central

Mee, Edward T.; Preston, Mark D.; Minor, Philip D.; Schepelmann, Silke; Huang, Xuening; Nguyen, Jenny; Wall, David; Hargrove, Stacey; Fu, Thomas; Xu, George; Li, Li; Cote, Colette; Delwart, Eric; Li, Linlin; Hewlett, Indira; Simonyan, Vahan; Ragupathy, Viswanath; Alin, Voskanian-Kordi; Mermod, Nicolas; Hill, Christiane; Ottenwälder, Birgit; Richter, Daniel C.; Tehrani, Arman; Jacqueline, Weber-Lehmann; Cassart, Jean-Pol; Letellier, Carine; Vandeputte, Olivier; Ruelle, Jean-Louis; Deyati, Avisek; La Neve, Fabio; Modena, Chiara; Mee, Edward; Schepelmann, Silke; Preston, Mark; Minor, Philip; Eloit, Marc; Muth, Erika; Lamamy, Arnaud; Jagorel, Florence; Cheval, Justine; Anscombe, Catherine; Misra, Raju; Wooldridge, David; Gharbia, Saheer; Rose, Graham; Ng, Siemon H.S.; Charlebois, Robert L.; Gisonni-Lex, Lucy; Mallet, Laurent; Dorange, Fabien; Chiu, Charles; Naccache, Samia; Kellam, Paul; van der Hoek, Lia; Cotten, Matt; Mitchell, Christine; Baier, Brian S.; Sun, Wenping; Malicki, Heather D.

2016-01-01

Background Unbiased deep sequencing offers the potential for improved adventitious virus screening in vaccines and biotherapeutics. Successful implementation of such assays will require appropriate control materials to confirm assay performance and sensitivity. Methods A common reference material containing 25 target viruses was produced and 16 laboratories were invited to process it using their preferred adventitious virus detection assay. Results Fifteen laboratories returned results, obtained using a wide range of wet-lab and informatics methods. Six of 25 target viruses were detected by all laboratories, with the remaining viruses detected by 4–14 laboratories. Six non-target viruses were detected by three or more laboratories. Conclusion The study demonstrated that a wide range of methods are currently used for adventitious virus detection screening in biological products by deep sequencing and that they can yield significantly different results. This underscores the need for common reference materials to ensure satisfactory assay performance and enable comparisons between laboratories. PMID:26709640

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

NASA Astrophysics Data System (ADS)

Jiang, Hongkai; Li, Xingqiu; Shao, Haidong; Zhao, Ke

2018-06-01

Traditional intelligent fault diagnosis methods for rolling bearings heavily depend on manual feature extraction and feature selection. For this purpose, an intelligent deep learning method, named the improved deep recurrent neural network (DRNN), is proposed in this paper. Firstly, frequency spectrum sequences are used as inputs to reduce the input size and ensure good robustness. Secondly, DRNN is constructed by the stacks of the recurrent hidden layer to automatically extract the features from the input spectrum sequences. Thirdly, an adaptive learning rate is adopted to improve the training performance of the constructed DRNN. The proposed method is verified with experimental rolling bearing data, and the results confirm that the proposed method is more effective than traditional intelligent fault diagnosis methods.

Position-specific binding of FUS to nascent RNA regulates mRNA length

PubMed Central

Masuda, Akio; Takeda, Jun-ichi; Okuno, Tatsuya; Okamoto, Takaaki; Ohkawara, Bisei; Ito, Mikako; Ishigaki, Shinsuke; Sobue, Gen

2015-01-01

More than half of all human genes produce prematurely terminated polyadenylated short mRNAs. However, the underlying mechanisms remain largely elusive. CLIP-seq (cross-linking immunoprecipitation [CLIP] combined with deep sequencing) of FUS (fused in sarcoma) in neuronal cells showed that FUS is frequently clustered around an alternative polyadenylation (APA) site of nascent RNA. ChIP-seq (chromatin immunoprecipitation [ChIP] combined with deep sequencing) of RNA polymerase II (RNAP II) demonstrated that FUS stalls RNAP II and prematurely terminates transcription. When an APA site is located upstream of an FUS cluster, FUS enhances polyadenylation by recruiting CPSF160 and up-regulates the alternative short transcript. In contrast, when an APA site is located downstream from an FUS cluster, polyadenylation is not activated, and the RNAP II-suppressing effect of FUS leads to down-regulation of the alternative short transcript. CAGE-seq (cap analysis of gene expression [CAGE] combined with deep sequencing) and PolyA-seq (a strand-specific and quantitative method for high-throughput sequencing of 3' ends of polyadenylated transcripts) revealed that position-specific regulation of mRNA lengths by FUS is operational in two-thirds of transcripts in neuronal cells, with enrichment in genes involved in synaptic activities. PMID:25995189

Deep sequencing detects very-low-grade somatic mosaicism in the unaffected mother of siblings with nemaline myopathy.

PubMed

Miyatake, Satoko; Koshimizu, Eriko; Hayashi, Yukiko K; Miya, Kazushi; Shiina, Masaaki; Nakashima, Mitsuko; Tsurusaki, Yoshinori; Miyake, Noriko; Saitsu, Hirotomo; Ogata, Kazuhiro; Nishino, Ichizo; Matsumoto, Naomichi

2014-07-01

When an expected mutation in a particular disease-causing gene is not identified in a suspected carrier, it is usually assumed to be due to germline mosaicism. We report here very-low-grade somatic mosaicism in ACTA1 in an unaffected mother of two siblings affected with a neonatal form of nemaline myopathy. The mosaicism was detected by deep resequencing using a next-generation sequencer. We identified a novel heterozygous mutation in ACTA1, c.448A>G (p.Thr150Ala), in the affected siblings. Three-dimensional structural modeling suggested that this mutation may affect polymerization and/or actin's interactions with other proteins. In this family, we expected autosomal dominant inheritance with either parent demonstrating germline or somatic mosaicism. Sanger sequencing identified no mutation. However, further deep resequencing of this mutation on a next-generation sequencer identified very-low-grade somatic mosaicism in the mother: 0.4%, 1.1%, and 8.3% in the saliva, blood leukocytes, and nails, respectively. Our study demonstrates the possibility of very-low-grade somatic mosaicism in suspected carriers, rather than germline mosaicism. Copyright © 2014 Elsevier B.V. All rights reserved.

Insights about minority HIV-1 strains in transmitted drug resistance mutation dynamics and disease progression.

PubMed

Leda, Ana Rachel; Hunter, James; Oliveira, Ursula Castro; Azevedo, Inacio Junqueira; Sucupira, Maria Cecilia Araripe; Diaz, Ricardo Sobhie

2018-04-19

The presence of minority transmitted drug resistance mutations was assessed using ultra-deep sequencing and correlated with disease progression among recently HIV-1-infected individuals from Brazil. Samples at baseline during recent infection and 1 year after the establishment of the infection were analysed. Viral RNA and proviral DNA from 25 individuals were subjected to ultra-deep sequencing of the reverse transcriptase and protease regions of HIV-1. Viral strains carrying transmitted drug resistance mutations were detected in 9 out of the 25 patients, for all major antiretroviral classes, ranging from one to five mutations per patient. Ultra-deep sequencing detected strains with frequencies as low as 1.6% and only strains with frequencies >20% were detected by population plasma sequencing (three patients). Transmitted drug resistance strains with frequencies <14.8% did not persist upon established infection. The presence of transmitted drug resistance mutations was negatively correlated with the viral load and with CD4+ T cell count decay. Transmitted drug resistance mutations representing small percentages of the viral population do not persist during infection because they are negatively selected in the first year after HIV-1 seroconversion.

Feasibility of 3.0T pelvic MR imaging in the evaluation of endometriosis.

PubMed

Manganaro, L; Fierro, F; Tomei, A; Irimia, D; Lodise, P; Sergi, M E; Vinci, V; Sollazzo, P; Porpora, M G; Delfini, R; Vittori, G; Marini, M

2012-06-01

Endometriosis represents an important clinical problem in women of reproductive age with high impact on quality of life, work productivity and health care management. The aim of this study is to define the role of 3T magnetom system MRI in the evaluation of endometriosis. Forty-six women, with transvaginal (TV) ultrasound examination positive for endometriosis, with pelvic pain, or infertile underwent an MR 3.0T examination with the following protocol: T2 weighted FRFSE HR sequences, T2 weighted FRFSE HR CUBE 3D sequences, T1 w FSE sequences, LAVA-flex sequences. Pelvic anatomy, macroscopic endometriosis implants, deep endometriosis implants, fallopian tube involvement, adhesions presence, fluid effusion in Douglas pouch, uterus and kidney pathologies or anomalies associated and sacral nervous routes were considered by two radiologists in consensus. Laparoscopy was considered the gold standard. MRI imaging diagnosed deep endometriosis in 22/46 patients, endometriomas not associated to deep implants in 9/46 patients, 15/46 patients resulted negative for endometriosis, 11 of 22 patients with deep endometriosis reported ovarian endometriosis cyst. We obtained high percentages of sensibility (96.97%), specificity (100.00%), VPP (100.00%), VPN (92.86%). Pelvic MRI performed with 3T system guarantees high spatial and contrast resolution, providing accurate information about endometriosis implants, with a good pre-surgery mapping of the lesions involving both bowels and bladder surface and recto-uterine ligaments. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Involving Minority High School Students in Cutting Edge Research through C-DEBI, an NSF-National Science and Technology Center

NASA Astrophysics Data System (ADS)

Singer, E.; Edwards, K. J.

2012-12-01

The Center for Dark Energy Biosphere Investigations (C-DEBI) was established as a National Science and Technology Center (NTC) funded by NSF in 2009. Its mission is to explore life beneath the seafloor and make transformative discoveries that advance science, benefit society, and inspire people of all ages and origins. Thanks to the multi-institutional character of C-DEBI, the Center has not only started a collaborative framework for experimental and exploratory research, but also targets education programs at the K-12, undergraduate, graduate and postdoctoral levels involving biogeochemists, microbiologists, geochemists and geologists. An example for this is the introduction of deep biosphere research into the K-12 classroom. In this context, C-DEBI has collaborated with teachers from the Animo Leadership High School in Inglewood, which is ranked 27th within California and has a total minority enrollment of 99%, to adapt Marine Biology classes and introduce latest Deep Biosphere Science discoveries. Three high school students participated in a pilot project over 6 months to gain hands-on experience in an ongoing study in a Marine Microbiology laboratory at University of Southern California. Graduate and postdoctoral students from the Departments of Biological and Earth Sciences supervised theory, praxis and project design, which was aimed at culturing strains of Marinobacter, one of the most ubiquitous marine microbial genera, and preparing extracted DNA for sequencing using the latest Ion Torrent Technology. Students learned about the interdisciplinary global context of the study and gained experience in laboratory procedures, including basic aseptical techniques, molecular biology methods, and cutting-edge sequencing Technology, as well as problem-solving and creative thinking in project preparation and conduction. This hands-on training included discussions about the 'Whys' and 'Hows' in today's research with respect to their specific project, but also from a broader and more interdisciplinary angle. This all-round form of education is usually not readily available in K-12 school curricula, but helps students, especially those with minority background, to envision their secondary education and embrace new career goals. Entering a large network, like C-DEBI has helped our high school students to participate in additional workshops and trainings across the United States, further fueling their enthusiasm in Science and providing new future directions. Communicating Science and Technology has become an essential part in the everyday life of today's researchers. Using infrastructure from networks like C-DEBI has proven extremely valuable and expedient to both, young research mentors and students, who may become the next generation of scientists.

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

PubMed

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

2018-05-22

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

Mixed heterolobosean and novel gregarine lineage genes from culture ATCC 50646: Long-branch artefacts, not lateral gene transfer, distort α-tubulin phylogeny.

PubMed

Cavalier-Smith, Thomas

2015-04-01

Contradictory and confusing results can arise if sequenced 'monoprotist' samples really contain DNA of very different species. Eukaryote-wide phylogenetic analyses using five genes from the amoeboflagellate culture ATCC 50646 previously implied it was an undescribed percolozoan related to percolatean flagellates (Stephanopogon, Percolomonas). Contrastingly, three phylogenetic analyses of 18S rRNA alone, did not place it within Percolozoa, but as an isolated deep-branching excavate. I resolve that contradiction by sequence phylogenies for all five genes individually, using up to 652 taxa. Its 18S rRNA sequence (GQ377652) is near-identical to one from stained-glass windows, somewhat more distant from one from cooling-tower water, all three related to terrestrial actinocephalid gregarines Hoplorhynchus and Pyxinia. All four protein-gene sequences (Hsp90; α-tubulin; β-tubulin; actin) are from an amoeboflagellate heterolobosean percolozoan, not especially deeply branching. Contrary to previous conclusions from trees combining protein and rRNA sequences or rDNA trees including Eozoa only, this culture does not represent a major novel deep-branching eukaryote lineage distinct from Heterolobosea, and thus lacks special significance for deep eukaryote phylogeny, though the rDNA sequence is important for gregarine phylogeny. α-Tubulin trees for over 250 eukaryotes refute earlier suggestions of lateral gene transfer within eukaryotes, being largely congruent with morphology and other gene trees. Copyright © 2015. Published by Elsevier GmbH.

The Making of Deep Impact

NASA Image and Video Library

2006-10-19

This image shows NASA Deep Impact spacecraft being built at Ball Aerospace & Technologies Corporation, Boulder, Colo. on July 2, 2005. The spacecraft impactor was released from Deep Impact flyby spacecraft.

Toward a real-time system for temporal enhanced ultrasound-guided prostate biopsy.

PubMed

Azizi, Shekoofeh; Van Woudenberg, Nathan; Sojoudi, Samira; Li, Ming; Xu, Sheng; Abu Anas, Emran M; Yan, Pingkun; Tahmasebi, Amir; Kwak, Jin Tae; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Wood, Bradford; Mousavi, Parvin; Abolmaesumi, Purang

2018-03-27

We have previously proposed temporal enhanced ultrasound (TeUS) as a new paradigm for tissue characterization. TeUS is based on analyzing a sequence of ultrasound data with deep learning and has been demonstrated to be successful for detection of cancer in ultrasound-guided prostate biopsy. Our aim is to enable the dissemination of this technology to the community for large-scale clinical validation. In this paper, we present a unified software framework demonstrating near-real-time analysis of ultrasound data stream using a deep learning solution. The system integrates ultrasound imaging hardware, visualization and a deep learning back-end to build an accessible, flexible and robust platform. A client-server approach is used in order to run computationally expensive algorithms in parallel. We demonstrate the efficacy of the framework using two applications as case studies. First, we show that prostate cancer detection using near-real-time analysis of RF and B-mode TeUS data and deep learning is feasible. Second, we present real-time segmentation of ultrasound prostate data using an integrated deep learning solution. The system is evaluated for cancer detection accuracy on ultrasound data obtained from a large clinical study with 255 biopsy cores from 157 subjects. It is further assessed with an independent dataset with 21 biopsy targets from six subjects. In the first study, we achieve area under the curve, sensitivity, specificity and accuracy of 0.94, 0.77, 0.94 and 0.92, respectively, for the detection of prostate cancer. In the second study, we achieve an AUC of 0.85. Our results suggest that TeUS-guided biopsy can be potentially effective for the detection of prostate cancer.

Intraterrestrial life in igneous ocean crust: advances, technologies, and the future (Invited)

NASA Astrophysics Data System (ADS)

Edwards, K. J.; Wheat, C. G.

2010-12-01

The “next frontier” of scientific investigation in the deep sub-seafloor microbial biosphere lies in a realm that has been a completely unexplored until just the past decade: the igneous oceanic crust. Problems that have hampered exploration of the “hard rock” marine deep biosphere have revolved around sample access (hard rock drilling is technologically complex), contamination (a major hurdle), momentum (why take on this challenge when the relatively “easier” marine muds also have been a frontier) and suspicion that microbes in more readily accessed using (simpler) non-drilling technologies - like vents - are truly are endemic of subsurface clades/activities. Since the late 1990’s, however, technologies and resultant studies on microbes in the igneous ocean crust deep biosphere have risen sharply, and offer a new and distinct view on this biome. Moreover, microbiologists are now taking leading roles in technological developments that are critically required to address this biosphere - interfacing and collaborating closely with engineers, genomic biologists, geologists, seismologists, and geochemists to accomplish logistically complex and long-term studies that bring observatory research to this deep realm. The future of this field for the least decade is rich - opportunities abound for microbiologists to play new roles in how we study microbiology in the deep subsurface in an oceanographic and Earth system science perspective.

Advances for Studying Clonal Evolution in Cancer

PubMed Central

Raphael, Benjamin J.; Chen, Feng; Wendl, Michael C.

2013-01-01

The “clonal evolution” model of cancer emerged and “evolved” amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other’s survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient. PMID:23353056

Advances for studying clonal evolution in cancer.

PubMed

Ding, Li; Raphael, Benjamin J; Chen, Feng; Wendl, Michael C

2013-11-01

The "clonal evolution" model of cancer emerged and "evolved" amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other's survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

TEA: the epigenome platform for Arabidopsis methylome study.

PubMed

Su, Sheng-Yao; Chen, Shu-Hwa; Lu, I-Hsuan; Chiang, Yih-Shien; Wang, Yu-Bin; Chen, Pao-Yang; Lin, Chung-Yen

2016-12-22

Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw .

The small RNA profile in latex from Hevea brasiliensis trees is affected by tapping panel dryness.

PubMed

Gébelin, Virginie; Leclercq, Julie; Kuswanhadi; Argout, Xavier; Chaidamsari, Tetty; Hu, Songnian; Tang, Chaorong; Sarah, Gautier; Yang, Meng; Montoro, Pascal

2013-10-01

Natural rubber is harvested by tapping Hevea brasiliensis (Willd. ex A. Juss.) Müll. Arg. Harvesting stress can lead to tapping panel dryness (TPD). MicroRNAs (miRNAs) are induced by abiotic stress and regulate gene expression by targeting the cleavage or translational inhibition of target messenger RNAs. This study set out to sequence miRNAs expressed in latex cells and to identify TPD-related putative targets. Deep sequencing of small RNAs was carried out on latex from trees affected by TPD using Solexa technology. The most abundant small RNA class size was 21 nucleotides for TPD trees compared with 24 nucleotides in healthy trees. By combining the LeARN pipeline, data from the Plant MicroRNA database and Hevea EST sequences, we identified 19 additional conserved and four putative species-specific miRNA families not found in previous studies on rubber. The relative transcript abundance of the Hbpre-MIR159b gene increased with TPD. This study revealed a small RNA-specific signature of TPD-affected trees. Both RNA degradation and a shift in miRNA biogenesis are suggested to explain the general decline in small RNAs and, particularly, in miRNAs.

Assessing the Gene Content of the Megagenome: Sugar Pine (Pinus lambertiana)

PubMed Central

Gonzalez-Ibeas, Daniel; Martinez-Garcia, Pedro J.; Famula, Randi A.; Delfino-Mix, Annette; Stevens, Kristian A.; Loopstra, Carol A.; Langley, Charles H.; Neale, David B.; Wegrzyn, Jill L.

2016-01-01

Sugar pine (Pinus lambertiana Douglas) is within the subgenus Strobus with an estimated genome size of 31 Gbp. Transcriptomic resources are of particular interest in conifers due to the challenges presented in their megagenomes for gene identification. In this study, we present the first comprehensive survey of the P. lambertiana transcriptome through deep sequencing of a variety of tissue types to generate more than 2.5 billion short reads. Third generation, long reads generated through PacBio Iso-Seq have been included for the first time in conifers to combat the challenges associated with de novo transcriptome assembly. A technology comparison is provided here to contribute to the otherwise scarce comparisons of second and third generation transcriptome sequencing approaches in plant species. In addition, the transcriptome reference was essential for gene model identification and quality assessment in the parallel project responsible for sequencing and assembly of the entire genome. In this study, the transcriptomic data were also used to address questions surrounding lineage-specific Dicer-like proteins in conifers. These proteins play a role in the control of transposable element proliferation and the related genome expansion in conifers. PMID:27799338

Direct evidence of 1,900 years of indigenous silver production in the Lake Titicaca Basin of Southern Peru

PubMed Central

Schultze, Carol A.; Stanish, Charles; Scott, David A.; Rehren, Thilo; Kuehner, Scott; Feathers, James K.

2009-01-01

Archaeological excavations at a U-shaped pyramid in the northern Lake Titicaca Basin of Peru have documented a continuous 5-m-deep stratigraphic sequence of metalworking remains. The sequence begins in the first millennium AD and ends in the Spanish Colonial period ca. AD 1600. The earliest dates associated with silver production are 1960 ± 40 BP (2-sigma cal. 40 BC to AD 120) and 1870 ± 40 BP (2-sigma cal. AD 60 to 240) representing the oldest known silver smelting in South America. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis of production debris indicate a complex, multistage, high temperature technology for producing silver throughout the archaeological sequence. These data hold significant theoretical implications including the following: (i) silver production occurred before the development of the first southern Andean state of Tiwanaku, (ii) the location and process of silverworking remained consistent for 1,500 years even though political control of the area cycled between expansionist states and smaller chiefly polities, and (iii) that U-shaped structures were the location of ceremonial, residential, and industrial activities. PMID:19805127

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

PubMed

Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

2018-03-01

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

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

2017-10-09

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

Nanopore Technology: A Simple, Inexpensive, Futuristic Technology for DNA Sequencing.

PubMed

Gupta, P D

2016-10-01

In health care, importance of DNA sequencing has been fully established. Sanger's Capillary Electrophoresis DNA sequencing methodology is time consuming, cumbersome, hence become more expensive. Lately, because of its versatility DNA sequencing became house hold name, and therefore, there is an urgent need of simple, fast, inexpensive, DNA sequencing technology. In the beginning of this century efforts were made, and Nanopore DNA sequencing technology was developed; still it is infancy, nevertheless, it is the futuristic technology.

MR fingerprinting Deep RecOnstruction NEtwork (DRONE).

PubMed

Cohen, Ouri; Zhu, Bo; Rosen, Matthew S

2018-09-01

Demonstrate a novel fast method for reconstruction of multi-dimensional MR fingerprinting (MRF) data using deep learning methods. A neural network (NN) is defined using the TensorFlow framework and trained on simulated MRF data computed with the extended phase graph formalism. The NN reconstruction accuracy for noiseless and noisy data is compared to conventional MRF template matching as a function of training data size and is quantified in simulated numerical brain phantom data and International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom data measured on 1.5T and 3T scanners with an optimized MRF EPI and MRF fast imaging with steady state precession (FISP) sequences with spiral readout. The utility of the method is demonstrated in a healthy subject in vivo at 1.5T. Network training required 10 to 74 minutes; once trained, data reconstruction required approximately 10 ms for the MRF EPI and 76 ms for the MRF FISP sequence. Reconstruction of simulated, noiseless brain data using the NN resulted in a RMS error (RMSE) of 2.6 ms for T 1 and 1.9 ms for T 2 . The reconstruction error in the presence of noise was less than 10% for both T 1 and T 2 for SNR greater than 25 dB. Phantom measurements yielded good agreement (R 2  = 0.99/0.99 for MRF EPI T 1 /T 2 and 0.94/0.98 for MRF FISP T 1 /T 2 ) between the T 1 and T 2 estimated by the NN and reference values from the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom. Reconstruction of MRF data with a NN is accurate, 300- to 5000-fold faster, and more robust to noise and dictionary undersampling than conventional MRF dictionary-matching. © 2018 International Society for Magnetic Resonance in Medicine.

Phylogenetic and Genome-Wide Deep-Sequencing Analyses of Canine Parvovirus Reveal Co-Infection with Field Variants and Emergence of a Recent Recombinant Strain

PubMed Central

Pérez, Ruben; Calleros, Lucía; Marandino, Ana; Sarute, Nicolás; Iraola, Gregorio; Grecco, Sofia; Blanc, Hervé; Vignuzzi, Marco; Isakov, Ofer; Shomron, Noam; Carrau, Lucía; Hernández, Martín; Francia, Lourdes; Sosa, Katia; Tomás, Gonzalo; Panzera, Yanina

2014-01-01

Canine parvovirus (CPV), a fast-evolving single-stranded DNA virus, comprises three antigenic variants (2a, 2b, and 2c) with different frequencies and genetic variability among countries. The contribution of co-infection and recombination to the genetic variability of CPV is far from being fully elucidated. Here we took advantage of a natural CPV population, recently formed by the convergence of divergent CPV-2c and CPV-2a strains, to study co-infection and recombination. Complete sequences of the viral coding region of CPV-2a and CPV-2c strains from 40 samples were generated and analyzed using phylogenetic tools. Two samples showed co-infection and were further analyzed by deep sequencing. The sequence profile of one of the samples revealed the presence of CPV-2c and CPV-2a strains that differed at 29 nucleotides. The other sample included a minor CPV-2a strain (13.3% of the viral population) and a major recombinant strain (86.7%). The recombinant strain arose from inter-genotypic recombination between CPV-2c and CPV-2a strains within the VP1/VP2 gene boundary. Our findings highlight the importance of deep-sequencing analysis to provide a better understanding of CPV molecular diversity. PMID:25365348

Evidence for thermal convection in the deep carbonate aquifer of the eastern sector of the Po Plain, Italy

NASA Astrophysics Data System (ADS)

Pasquale, V.; Chiozzi, P.; Verdoya, M.

2013-05-01

Temperatures recorded in wells as deep as 6 km drilled for hydrocarbon prospecting were used together with geological information to depict the thermal regime of the sedimentary sequence of the eastern sector of the Po Plain. After correction for drilling disturbance, temperature data were analyzed through an inversion technique based on a laterally constant thermal gradient model. The obtained thermal gradient is quite low within the deep carbonate unit (14 mK m- 1), while it is larger (53 mK m- 1) in the overlying impermeable formations. In the uppermost sedimentary layers, the thermal gradient is close to the regional average (21 mK m- 1). We argue that such a vertical change cannot be ascribed to thermal conductivity variation within the sedimentary sequence, but to deep groundwater flow. Since the hydrogeological characteristics (including litho-stratigraphic sequence and structural setting) hardly permit forced convection, we suggest that thermal convection might occur within the deep carbonate aquifer. The potential of this mechanism was evaluated by means of the Rayleigh number analysis. It turned out that permeability required for convection to occur must be larger than 3 10- 15 m2. The average over-heat ratio is 0.45. The lateral variation of hydrothermal regime was tested by using temperature data representing the aquifer thermal conditions. We found that thermal convection might be more developed and variable at the Ferrara High and its surroundings, where widespread fracturing may have increased permeability.

"First generation" automated DNA sequencing technology.

PubMed

Slatko, Barton E; Kieleczawa, Jan; Ju, Jingyue; Gardner, Andrew F; Hendrickson, Cynthia L; Ausubel, Frederick M

2011-10-01

Beginning in the 1980s, automation of DNA sequencing has greatly increased throughput, reduced costs, and enabled large projects to be completed more easily. The development of automation technology paralleled the development of other aspects of DNA sequencing: better enzymes and chemistry, separation and imaging technology, sequencing protocols, robotics, and computational advancements (including base-calling algorithms with quality scores, database developments, and sequence analysis programs). Despite the emergence of high-throughput sequencing platforms, automated Sanger sequencing technology remains useful for many applications. This unit provides background and a description of the "First-Generation" automated DNA sequencing technology. It also includes protocols for using the current Applied Biosystems (ABI) automated DNA sequencing machines. © 2011 by John Wiley & Sons, Inc.

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.

Deep sequencing of the viral phoH gene reveals temporal variation, depth-specific composition, and persistent dominance of the same viral phoH genes in the Sargasso Sea

PubMed Central

Goldsmith, Dawn B.; Parsons, Rachel J.; Beyene, Damitu; Salamon, Peter

2015-01-01

Deep sequencing of the viral phoH gene, a host-derived auxiliary metabolic gene, was used to track viral diversity throughout the water column at the Bermuda Atlantic Time-series Study (BATS) site in the summer (September) and winter (March) of three years. Viral phoH sequences reveal differences in the viral communities throughout a depth profile and between seasons in the same year. Variation was also detected between the same seasons in subsequent years, though these differences were not as great as the summer/winter distinctions. Over 3,600 phoH operational taxonomic units (OTUs; 97% sequence identity) were identified. Despite high richness, most phoH sequences belong to a few large, common OTUs whereas the majority of the OTUs are small and rare. While many OTUs make sporadic appearances at just a few times or depths, a small number of OTUs dominate the community throughout the seasons, depths, and years. PMID:26157645

Comparison of magnetic resonance imaging sequences for depicting the subthalamic nucleus for deep brain stimulation.

PubMed

Nagahama, Hiroshi; Suzuki, Kengo; Shonai, Takaharu; Aratani, Kazuki; Sakurai, Yuuki; Nakamura, Manami; Sakata, Motomichi

2015-01-01

Electrodes are surgically implanted into the subthalamic nucleus (STN) of Parkinson's disease patients to provide deep brain stimulation. For ensuring correct positioning, the anatomic location of the STN must be determined preoperatively. Magnetic resonance imaging has been used for pinpointing the location of the STN. To identify the optimal imaging sequence for identifying the STN, we compared images produced with T2 star-weighted angiography (SWAN), gradient echo T2*-weighted imaging, and fast spin echo T2-weighted imaging in 6 healthy volunteers. Our comparison involved measurement of the contrast-to-noise ratio (CNR) for the STN and substantia nigra and a radiologist's interpretations of the images. Of the sequences examined, the CNR and qualitative scores were significantly higher on SWAN images than on other images (p < 0.01) for STN visualization. Kappa value (0.74) on SWAN images was the highest in three sequences for visualizing the STN. SWAN is the sequence best suited for identifying the STN at the present time.

Development of genic-SSR markers by deep transcriptome sequencing in pigeonpea [Cajanus cajan (L.) Millspaugh].

PubMed

Dutta, Sutapa; Kumawat, Giriraj; Singh, Bikram P; Gupta, Deepak K; Singh, Sangeeta; Dogra, Vivek; Gaikwad, Kishor; Sharma, Tilak R; Raje, Ranjeet S; Bandhopadhya, Tapas K; Datta, Subhojit; Singh, Mahendra N; Bashasab, Fakrudin; Kulwal, Pawan; Wanjari, K B; K Varshney, Rajeev; Cook, Douglas R; Singh, Nagendra K

2011-01-20

Pigeonpea [Cajanus cajan (L.) Millspaugh], one of the most important food legumes of semi-arid tropical and subtropical regions, has limited genomic resources, particularly expressed sequence based (genic) markers. We report a comprehensive set of validated genic simple sequence repeat (SSR) markers using deep transcriptome sequencing, and its application in genetic diversity analysis and mapping. In this study, 43,324 transcriptome shotgun assembly unigene contigs were assembled from 1.696 million 454 GS-FLX sequence reads of separate pooled cDNA libraries prepared from leaf, root, stem and immature seed of two pigeonpea varieties, Asha and UPAS 120. A total of 3,771 genic-SSR loci, excluding homopolymeric and compound repeats, were identified; of which 2,877 PCR primer pairs were designed for marker development. Dinucleotide was the most common repeat motif with a frequency of 60.41%, followed by tri- (34.52%), hexa- (2.62%), tetra- (1.67%) and pentanucleotide (0.76%) repeat motifs. Primers were synthesized and tested for 772 of these loci with repeat lengths of ≥ 18 bp. Of these, 550 markers were validated for consistent amplification in eight diverse pigeonpea varieties; 71 were found to be polymorphic on agarose gel electrophoresis. Genetic diversity analysis was done on 22 pigeonpea varieties and eight wild species using 20 highly polymorphic genic-SSR markers. The number of alleles at these loci ranged from 4-10 and the polymorphism information content values ranged from 0.46 to 0.72. Neighbor-joining dendrogram showed distinct separation of the different groups of pigeonpea cultivars and wild species. Deep transcriptome sequencing of the two parental lines helped in silico identification of polymorphic genic-SSR loci to facilitate the rapid development of an intra-species reference genetic map, a subset of which was validated for expected allelic segregation in the reference mapping population. We developed 550 validated genic-SSR markers in pigeonpea using deep transcriptome sequencing. From these, 20 highly polymorphic markers were used to evaluate the genetic relationship among species of the genus Cajanus. A comprehensive set of genic-SSR markers was developed as an important genomic resource for diversity analysis and genetic mapping in pigeonpea.

Development of genic-SSR markers by deep transcriptome sequencing in pigeonpea [Cajanus cajan (L.) Millspaugh

PubMed Central

2011-01-01

Background Pigeonpea [Cajanus cajan (L.) Millspaugh], one of the most important food legumes of semi-arid tropical and subtropical regions, has limited genomic resources, particularly expressed sequence based (genic) markers. We report a comprehensive set of validated genic simple sequence repeat (SSR) markers using deep transcriptome sequencing, and its application in genetic diversity analysis and mapping. Results In this study, 43,324 transcriptome shotgun assembly unigene contigs were assembled from 1.696 million 454 GS-FLX sequence reads of separate pooled cDNA libraries prepared from leaf, root, stem and immature seed of two pigeonpea varieties, Asha and UPAS 120. A total of 3,771 genic-SSR loci, excluding homopolymeric and compound repeats, were identified; of which 2,877 PCR primer pairs were designed for marker development. Dinucleotide was the most common repeat motif with a frequency of 60.41%, followed by tri- (34.52%), hexa- (2.62%), tetra- (1.67%) and pentanucleotide (0.76%) repeat motifs. Primers were synthesized and tested for 772 of these loci with repeat lengths of ≥18 bp. Of these, 550 markers were validated for consistent amplification in eight diverse pigeonpea varieties; 71 were found to be polymorphic on agarose gel electrophoresis. Genetic diversity analysis was done on 22 pigeonpea varieties and eight wild species using 20 highly polymorphic genic-SSR markers. The number of alleles at these loci ranged from 4-10 and the polymorphism information content values ranged from 0.46 to 0.72. Neighbor-joining dendrogram showed distinct separation of the different groups of pigeonpea cultivars and wild species. Deep transcriptome sequencing of the two parental lines helped in silico identification of polymorphic genic-SSR loci to facilitate the rapid development of an intra-species reference genetic map, a subset of which was validated for expected allelic segregation in the reference mapping population. Conclusion We developed 550 validated genic-SSR markers in pigeonpea using deep transcriptome sequencing. From these, 20 highly polymorphic markers were used to evaluate the genetic relationship among species of the genus Cajanus. A comprehensive set of genic-SSR markers was developed as an important genomic resource for diversity analysis and genetic mapping in pigeonpea. PMID:21251263

Using DSP technology to simplify deep space ranging

NASA Technical Reports Server (NTRS)

Bryant, S.

2000-01-01

Commercially available Digital Signal Processing (DSP) technology has enabled a new spacecraft ranging design. The new design reduces overall size, parts count, and complexity. The design implementation will also meet the Jet Propulsion Laboratory (JPL) requirements for both near-Earth and deep space ranging.

Culturable prokaryotic diversity of deep, gas hydrate sediments: first use of a continuous high-pressure, anaerobic, enrichment and isolation system for subseafloor sediments (DeepIsoBUG)

PubMed Central

Parkes, R John; Sellek, Gerard; Webster, Gordon; Martin, Derek; Anders, Erik; Weightman, Andrew J; Sass, Henrik

2009-01-01

Deep subseafloor sediments may contain depressurization-sensitive, anaerobic, piezophilic prokaryotes. To test this we developed the DeepIsoBUG system, which when coupled with the HYACINTH pressure-retaining drilling and core storage system and the PRESS core cutting and processing system, enables deep sediments to be handled without depressurization (up to 25 MPa) and anaerobic prokaryotic enrichments and isolation to be conducted up to 100 MPa. Here, we describe the system and its first use with subsurface gas hydrate sediments from the Indian Continental Shelf, Cascadia Margin and Gulf of Mexico. Generally, highest cell concentrations in enrichments occurred close to in situ pressures (14 MPa) in a variety of media, although growth continued up to at least 80 MPa. Predominant sequences in enrichments were Carnobacterium, Clostridium, Marinilactibacillus and Pseudomonas, plus Acetobacterium and Bacteroidetes in Indian samples, largely independent of media and pressures. Related 16S rRNA gene sequences for all of these Bacteria have been detected in deep, subsurface environments, although isolated strains were piezotolerant, being able to grow at atmospheric pressure. Only the Clostridium and Acetobacterium were obligate anaerobes. No Archaea were enriched. It may be that these sediment samples were not deep enough (total depth 1126–1527 m) to obtain obligate piezophiles. PMID:19694787

3′ terminal diversity of MRP RNA and other human noncoding RNAs revealed by deep sequencing

PubMed Central

2013-01-01

Background Post-transcriptional 3′ end processing is a key component of RNA regulation. The abundant and essential RNA subunit of RNase MRP has been proposed to function in three distinct cellular compartments and therefore may utilize this mode of regulation. Here we employ 3′ RACE coupled with high-throughput sequencing to characterize the 3′ terminal sequences of human MRP RNA and other noncoding RNAs that form RNP complexes. Results The 3′ terminal sequence of MRP RNA from HEK293T cells has a distinctive distribution of genomically encoded termini (including an assortment of U residues) with a portion of these selectively tagged by oligo(A) tails. This profile contrasts with the relatively homogenous 3′ terminus of an in vitro transcribed MRP RNA control and the differing 3′ terminal profiles of U3 snoRNA, RNase P RNA, and telomerase RNA (hTR). Conclusions 3′ RACE coupled with deep sequencing provides a valuable framework for the functional characterization of 3′ terminal sequences of noncoding RNAs. PMID:24053768

Optical Communications Channel Combiner

NASA Technical Reports Server (NTRS)

Quirk, Kevin J.; Quirk, Kevin J.; Nguyen, Danh H.; Nguyen, Huy

2012-01-01

NASA has identified deep-space optical communications links as an integral part of a unified space communication network in order to provide data rates in excess of 100 Mb/s. The distances and limited power inherent in a deep-space optical downlink necessitate the use of photon-counting detectors and a power-efficient modulation such as pulse position modulation (PPM). For the output of each photodetector, whether from a separate telescope or a portion of the detection area, a communication receiver estimates a log-likelihood ratio for each PPM slot. To realize the full effective aperture of these receivers, their outputs must be combined prior to information decoding. A channel combiner was developed to synchronize the log-likelihood ratio (LLR) sequences of multiple receivers, and then combines these into a single LLR sequence for information decoding. The channel combiner synchronizes the LLR sequences of up to three receivers and then combines these into a single LLR sequence for output. The channel combiner has three channel inputs, each of which takes as input a sequence of four-bit LLRs for each PPM slot in a codeword via a XAUI 10 Gb/s quad optical fiber interface. The cross-correlation between the channels LLR time series are calculated and used to synchronize the sequences prior to combining. The output of the channel combiner is a sequence of four-bit LLRs for each PPM slot in a codeword via a XAUI 10 Gb/s quad optical fiber interface. The unit is controlled through a 1 Gb/s Ethernet UDP/IP interface. A deep-space optical communication link has not yet been demonstrated. This ground-station channel combiner was developed to demonstrate this capability and is unique in its ability to process such a signal.

The 3-D aftershock distribution of three recent M5~5.5 earthquakes in the Anza region,California

NASA Astrophysics Data System (ADS)

Zhang, Q.; Wdowinski, S.; Lin, G.

2011-12-01

The San Jacinto fault zone (SJFZ) exhibits the highest level of seismicity compared to other regions in southern California. On average, it produces four earthquakes per day, most of them at depth of 10-17 km. Over the past decade, an increasing seismic activity occurred in the Anza region, which included three M5~5.5 events and their aftershock sequences. These events occurred in 2001, 2005, and 2010. In this research we map the 3-D distribution of these three events to evaluate their rupture geometry and better understand the unusual deep seismic pattern along the SJFZ, which was termed "deep creep" (Wdowinski, 2009). We relocated 97,562 events from 1981 to 2011 in Anza region by applying the Source-Specific Station Term (SSST) method (Lin et al., 2006) and used an accurate 1-D velocity model derived from 3-D model of Lin et al (2007) and used In order to separate the aftershock sequence from background seismicity, we characterized each of the three aftershock sequences using Omori's law. Preliminary results show that all three sequences had a similar geometry of deep elongated aftershock distribution. Most aftershocks occurred at depth of 10-17 km and extended over a 70 km long segments of the SJFZ, centered at the mainshock hypocenters. A comparative study of other M5~5.5 mainshocks and their aftershock sequences in southern California reveals very different geometrical pattern, suggesting that the three Anza M5~5.5 events are unique and can be indicative of "deep creep" deformation processes. Reference 1.Lin, G.and Shearer,P.M.,2006, The COMPLOC earthquake location package,Seism. Res. Lett.77, pp.440-444. 2.Lin, G. and Shearer, P.M., Hauksson, E., and Thurber C.H.,2007, A three-dimensional crustal seismic velocity model for southern California from a composite event method,J. Geophys.Res.112, B12306, doi: 10.1029/ 2007JB004977. 3.Wdowinski, S. ,2009, Deep creep as a cause for the excess seismicity along the San Jacinto fault, Nat. Geosci.,doi:10.1038/NGEO684.

Deep Space Systems Technology Program (DSST-X2000) Future Deliveries

NASA Technical Reports Server (NTRS)

Salvo, Christopher G.

1999-01-01

The number of deep space missions is increasing as we embark on a new era of exploration. New missions are "faster-better-cheaper" and cannot afford large individual investments in technology. A new process is needed fo allow these missions to take advantage of the technological breakthroughs that are critical to getting the cost down while increasing the science. The key is multimission technology development. NASA will make institutional investments in technology to benefit sets of missions. Continuous investment will provide a series of revolutions in technology to address common challenges in mission design and execution.

Effects of hydrostatic pressure on yeasts isolated from deep-sea hydrothermal vents.

PubMed

Burgaud, Gaëtan; Hué, Nguyen Thi Minh; Arzur, Danielle; Coton, Monika; Perrier-Cornet, Jean-Marie; Jebbar, Mohamed; Barbier, Georges

2015-11-01

Hydrostatic pressure plays a significant role in the distribution of life in the biosphere. Knowledge of deep-sea piezotolerant and (hyper)piezophilic bacteria and archaea diversity has been well documented, along with their specific adaptations to cope with high hydrostatic pressure (HHP). Recent investigations of deep-sea microbial community compositions have shown unexpected micro-eukaryotic communities, mainly dominated by fungi. Molecular methods such as next-generation sequencing have been used for SSU rRNA gene sequencing to reveal fungal taxa. Currently, a difficult but fascinating challenge for marine mycologists is to create deep-sea marine fungus culture collections and assess their ability to cope with pressure. Indeed, although there is no universal genetic marker for piezoresistance, physiological analyses provide concrete relevant data for estimating their adaptations and understanding the role of fungal communities in the abyss. The present study investigated morphological and physiological responses of fungi to HHP using a collection of deep-sea yeasts as a model. The aim was to determine whether deep-sea yeasts were able to tolerate different HHP and if they were metabolically active. Here we report an unexpected taxonomic-based dichotomic response to pressure with piezosensitve ascomycetes and piezotolerant basidiomycetes, and distinct morphological switches triggered by pressure for certain strains. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Deep Space Telecommunications

NASA Technical Reports Server (NTRS)

Kuiper, T. B. H.; Resch, G. M.

2000-01-01

The increasing load on NASA's deep Space Network, the new capabilities for deep space missions inherent in a next-generation radio telescope, and the potential of new telescope technology for reducing construction and operation costs suggest a natural marriage between radio astronomy and deep space telecommunications in developing advanced radio telescope concepts.

When less is more: 'slicing' sequencing data improves read decoding accuracy and de novo assembly quality.

PubMed

Lonardi, Stefano; Mirebrahim, Hamid; Wanamaker, Steve; Alpert, Matthew; Ciardo, Gianfranco; Duma, Denisa; Close, Timothy J

2015-09-15

As the invention of DNA sequencing in the 70s, computational biologists have had to deal with the problem of de novo genome assembly with limited (or insufficient) depth of sequencing. In this work, we investigate the opposite problem, that is, the challenge of dealing with excessive depth of sequencing. We explore the effect of ultra-deep sequencing data in two domains: (i) the problem of decoding reads to bacterial artificial chromosome (BAC) clones (in the context of the combinatorial pooling design we have recently proposed), and (ii) the problem of de novo assembly of BAC clones. Using real ultra-deep sequencing data, we show that when the depth of sequencing increases over a certain threshold, sequencing errors make these two problems harder and harder (instead of easier, as one would expect with error-free data), and as a consequence the quality of the solution degrades with more and more data. For the first problem, we propose an effective solution based on 'divide and conquer': we 'slice' a large dataset into smaller samples of optimal size, decode each slice independently, and then merge the results. Experimental results on over 15 000 barley BACs and over 4000 cowpea BACs demonstrate a significant improvement in the quality of the decoding and the final assembly. For the second problem, we show for the first time that modern de novo assemblers cannot take advantage of ultra-deep sequencing data. Python scripts to process slices and resolve decoding conflicts are available from http://goo.gl/YXgdHT; software Hashfilter can be downloaded from http://goo.gl/MIyZHs stelo@cs.ucr.edu or timothy.close@ucr.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.

Unique microbial community in drilling fluids from Chinese continental scientific drilling

USGS Publications Warehouse

Zhang, Gengxin; Dong, Hailiang; Jiang, Hongchen; Xu, Zhiqin; Eberl, Dennis D.

2006-01-01

Circulating drilling fluid is often regarded as a contamination source in investigations of subsurface microbiology. However, it also provides an opportunity to sample geological fluids at depth and to study contained microbial communities. During our study of deep subsurface microbiology of the Chinese Continental Scientific Deep drilling project, we collected 6 drilling fluid samples from a borehole from 2290 to 3350 m below the land surface. Microbial communities in these samples were characterized with cultivation-dependent and -independent techniques. Characterization of 16S rRNA genes indicated that the bacterial clone sequences related to Firmicutes became progressively dominant with increasing depth. Most sequences were related to anaerobic, thermophilic, halophilic or alkaliphilic bacteria. These habitats were consistent with the measured geochemical characteristics of the drilling fluids that have incorporated geological fluids and partly reflected the in-situ conditions. Several clone types were closely related to Thermoanaerobacter ethanolicus, Caldicellulosiruptor lactoaceticus, and Anaerobranca gottschalkii, an anaerobic metal-reducer, an extreme thermophile, and an anaerobic chemoorganotroph, respectively, with an optimal growth temperature of 50–68°C. Seven anaerobic, thermophilic Fe(III)-reducing bacterial isolates were obtained and they were capable of reducing iron oxide and clay minerals to produce siderite, vivianite, and illite. The archaeal diversity was low. Most archaeal sequences were not related to any known cultivated species, but rather to environmental clone sequences recovered from subsurface environments. We infer that the detected microbes were derived from geological fluids at depth and their growth habitats reflected the deep subsurface conditions. These findings have important implications for microbial survival and their ecological functions in the deep subsurface.

Full genome virus detection in fecal samples using sensitive nucleic acid preparation, deep sequencing, and a novel iterative sequence classification algorithm.

PubMed

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis.

Full Genome Virus Detection in Fecal Samples Using Sensitive Nucleic Acid Preparation, Deep Sequencing, and a Novel Iterative Sequence Classification Algorithm

PubMed Central

Cotten, Matthew; Oude Munnink, Bas; Canuti, Marta; Deijs, Martin; Watson, Simon J.; Kellam, Paul; van der Hoek, Lia

2014-01-01

We have developed a full genome virus detection process that combines sensitive nucleic acid preparation optimised for virus identification in fecal material with Illumina MiSeq sequencing and a novel post-sequencing virus identification algorithm. Enriched viral nucleic acid was converted to double-stranded DNA and subjected to Illumina MiSeq sequencing. The resulting short reads were processed with a novel iterative Python algorithm SLIM for the identification of sequences with homology to known viruses. De novo assembly was then used to generate full viral genomes. The sensitivity of this process was demonstrated with a set of fecal samples from HIV-1 infected patients. A quantitative assessment of the mammalian, plant, and bacterial virus content of this compartment was generated and the deep sequencing data were sufficient to assembly 12 complete viral genomes from 6 virus families. The method detected high levels of enteropathic viruses that are normally controlled in healthy adults, but may be involved in the pathogenesis of HIV-1 infection and will provide a powerful tool for virus detection and for analyzing changes in the fecal virome associated with HIV-1 progression and pathogenesis. PMID:24695106

Evolution of multi-drug resistant HCV clones from pre-existing resistant-associated variants during direct-acting antiviral therapy determined by third-generation sequencing

NASA Astrophysics Data System (ADS)

Takeda, Haruhiko; Ueda, Yoshihide; Inuzuka, Tadashi; Yamashita, Yukitaka; Osaki, Yukio; Nasu, Akihiro; Umeda, Makoto; Takemura, Ryo; Seno, Hiroshi; Sekine, Akihiro; Marusawa, Hiroyuki

2017-03-01

Resistance-associated variant (RAV) is one of the most significant clinical challenges in treating HCV-infected patients with direct-acting antivirals (DAAs). We investigated the viral dynamics in patients receiving DAAs using third-generation sequencing technology. Among 283 patients with genotype-1b HCV receiving daclatasvir + asunaprevir (DCV/ASV), 32 (11.3%) failed to achieve sustained virological response (SVR). Conventional ultra-deep sequencing of HCV genome was performed in 104 patients (32 non-SVR, 72 SVR), and detected representative RAVs in all non-SVR patients at baseline, including Y93H in 28 (87.5%). Long contiguous sequences spanning NS3 to NS5A regions of each viral clone in 12 sera from 6 representative non-SVR patients were determined by third-generation sequencing, and showed the concurrent presence of several synonymous mutations linked to resistance-associated substitutions in a subpopulation of pre-existing RAVs and dominant isolates at treatment failure. Phylogenetic analyses revealed close genetic distances between pre-existing RAVs and dominant RAVs at treatment failure. In addition, multiple drug-resistant mutations developed on pre-existing RAVs after DCV/ASV in all non-SVR cases. In conclusion, multi-drug resistant viral clones at treatment failure certainly originated from a subpopulation of pre-existing RAVs in HCV-infected patients. Those RAVs were selected for and became dominant with the acquisition of multiple resistance-associated substitutions under DAA treatment pressure.

Ultra Deep Sequencing of Listeria monocytogenes sRNA Transcriptome Revealed New Antisense RNAs

PubMed Central

Behrens, Sebastian; Widder, Stefanie; Mannala, Gopala Krishna; Qing, Xiaoxing; Madhugiri, Ramakanth; Kefer, Nathalie; Mraheil, Mobarak Abu; Rattei, Thomas; Hain, Torsten

2014-01-01

Listeria monocytogenes, a gram-positive pathogen, and causative agent of listeriosis, has become a widely used model organism for intracellular infections. Recent studies have identified small non-coding RNAs (sRNAs) as important factors for regulating gene expression and pathogenicity of L. monocytogenes. Increased speed and reduced costs of high throughput sequencing (HTS) techniques have made RNA sequencing (RNA-Seq) the state-of-the-art method to study bacterial transcriptomes. We created a large transcriptome dataset of L. monocytogenes containing a total of 21 million reads, using the SOLiD sequencing technology. The dataset contained cDNA sequences generated from L. monocytogenes RNA collected under intracellular and extracellular condition and additionally was size fractioned into three different size ranges from <40 nt, 40–150 nt and >150 nt. We report here, the identification of nine new sRNAs candidates of L. monocytogenes and a reevaluation of known sRNAs of L. monocytogenes EGD-e. Automatic comparison to known sRNAs revealed a high recovery rate of 55%, which was increased to 90% by manual revision of the data. Moreover, thorough classification of known sRNAs shed further light on their possible biological functions. Interestingly among the newly identified sRNA candidates are antisense RNAs (asRNAs) associated to the housekeeping genes purA, fumC and pgi and potentially their regulation, emphasizing the significance of sRNAs for metabolic adaptation in L. monocytogenes. PMID:24498259

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.

A comprehensive survey of 3' animal miRNA modification events and a possible role for 3' adenylation in modulating miRNA targeting effectiveness.

PubMed

Burroughs, A Maxwell; Ando, Yoshinari; de Hoon, Michiel J L; Tomaru, Yasuhiro; Nishibu, Takahiro; Ukekawa, Ryo; Funakoshi, Taku; Kurokawa, Tsutomu; Suzuki, Harukazu; Hayashizaki, Yoshihide; Daub, Carsten O

2010-10-01

Animal microRNA sequences are subject to 3' nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3' adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1-EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3' addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3' adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake.

HomozygosityMapper2012--bridging the gap between homozygosity mapping and deep sequencing.

PubMed

Seelow, Dominik; Schuelke, Markus

2012-07-01

Homozygosity mapping is a common method to map recessive traits in consanguineous families. To facilitate these analyses, we have developed HomozygosityMapper, a web-based approach to homozygosity mapping. HomozygosityMapper allows researchers to directly upload the genotype files produced by the major genotyping platforms as well as deep sequencing data. It detects stretches of homozygosity shared by the affected individuals and displays them graphically. Users can interactively inspect the underlying genotypes, manually refine these regions and eventually submit them to our candidate gene search engine GeneDistiller to identify the most promising candidate genes. Here, we present the new version of HomozygosityMapper. The most striking new feature is the support of Next Generation Sequencing *.vcf files as input. Upon users' requests, we have implemented the analysis of common experimental rodents as well as of important farm animals. Furthermore, we have extended the options for single families and loss of heterozygosity studies. Another new feature is the export of *.bed files for targeted enrichment of the potential disease regions for deep sequencing strategies. HomozygosityMapper also generates files for conventional linkage analyses which are already restricted to the possible disease regions, hence superseding CPU-intensive genome-wide analyses. HomozygosityMapper is freely available at http://www.homozygositymapper.org/.

Maximum entropy methods for extracting the learned features of deep neural networks.

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

Unravelling the complexity of microRNA-mediated gene regulation in black pepper (Piper nigrum L.) using high-throughput small RNA profiling.

PubMed

Asha, Srinivasan; Sreekumar, Sweda; Soniya, E V

2016-01-01

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

Electro-thermo-mechanical coupling analysis of deep drawing with resistance heating for aluminum matrix composites sheet

NASA Astrophysics Data System (ADS)

Zhang, Kaifeng; Zhang, Tuoda; Wang, Bo

2013-05-01

Recently, electro-plastic forming to be a focus of attention in materials hot processing research area, because it is a sort of energy-saving, high efficient and green manufacturing technology. An electro-thermo-mechanical model can be adopted to carry out the sequence simulation of aluminum matrix composites sheet deep drawing via electro-thermal coupling and thermal-mechanical coupling method. The first step of process is resistance heating of sheet, then turn off the power, and the second step is deep drawing. Temperature distribution of SiCp/2024Al composite sheet by resistance heating and sheet deep drawing deformation were analyzed. During the simulation, effect of contact resistances, temperature coefficient of resistance for electrode material and SiCp/2024Al composite on temperature distribution were integrally considered. The simulation results demonstrate that Sicp/2024Al composite sheet can be rapidly heated to 400° in 30s using resistances heating and the sheet temperature can be controlled by adjusting the current density. Physical properties of the electrode materials can significantly affect the composite sheet temperature distribution. The temperature difference between the center and the side of the sheet is proportional to the thermal conductivity of the electrode, the principal cause of which is that the heat transfers from the sheet to the electrode. SiCp/2024Al thin-wall part can be intactly manufactured at strain rate of 0.08s-1 and the sheet thickness thinning rate is limited within 20%, which corresponds well to the experimental result.

The mitochondrial genome of Ifremeria nautilei and the phylogenetic position of the enigmatic deep-sea Abyssochrysoidea (Mollusca: Gastropoda).

PubMed

Osca, David; Templado, José; Zardoya, Rafael

2014-09-01

The complete nucleotide sequence of the mitochondrial (mt) genome of the deep-sea vent snail Ifremeria nautilei (Gastropoda: Abyssochrysoidea) was determined. The double stranded circular molecule is 15,664 pb in length and encodes for the typical 37 metazoan mitochondrial genes. The gene arrangement of the Ifremeria mt genome is most similar to genome organization of caenogastropods and differs only on the relative position of the trnW gene. The deduced amino acid sequences of the mt protein coding genes of Ifremeria mt genome were aligned with orthologous sequences from representatives of the main lineages of gastropods and phylogenetic relationships were inferred. The reconstructed phylogeny supports that Ifremeria belongs to Caenogastropoda and that it is closely related to hypsogastropod superfamilies. Results were compared with a reconstructed nuclear-based phylogeny. Moreover, a relaxed molecular-clock timetree calibrated with fossils dated the divergence of Abyssochrysoidea in the Late Jurassic-Early Cretaceous indicating a relatively modern colonization of deep-sea environments by these snails. Copyright © 2014 Elsevier B.V. All rights reserved.

[Current applications of high-throughput DNA sequencing technology in antibody drug research].

PubMed

Yu, Xin; Liu, Qi-Gang; Wang, Ming-Rong

2012-03-01

Since the publication of a high-throughput DNA sequencing technology based on PCR reaction was carried out in oil emulsions in 2005, high-throughput DNA sequencing platforms have been evolved to a robust technology in sequencing genomes and diverse DNA libraries. Antibody libraries with vast numbers of members currently serve as a foundation of discovering novel antibody drugs, and high-throughput DNA sequencing technology makes it possible to rapidly identify functional antibody variants with desired properties. Herein we present a review of current applications of high-throughput DNA sequencing technology in the analysis of antibody library diversity, sequencing of CDR3 regions, identification of potent antibodies based on sequence frequency, discovery of functional genes, and combination with various display technologies, so as to provide an alternative approach of discovery and development of antibody drugs.

Characterization of Tensile Properties, Limiting Strains, and Deep Drawing Behavior of AA5754-H22 Sheet at Elevated Temperature

NASA Astrophysics Data System (ADS)

Panicker, Sudhy S.; Singh, Har Govind; Panda, Sushanta Kumar; Dashwood, Richard

2015-11-01

Automotive industries are very much interested in characterization of formability improvement of aluminum alloys at elevated temperatures before designing tools, heating systems, and processing sequences for fabrication of auto-body panels by warm forming technology. In this study, tensile tests of AA5754-H22 aluminum alloy were carried out at five different temperatures and three different strain rates to investigate the deformation behavior correlating with Cowper-Symonds constitutive equation. Laboratory scale warm forming facilities were designed and fabricated to perform limiting dome height and deep drawing tests to evaluate forming limit strains and drawability of sheet metal at different tool temperatures. The forming limit strain and dome height improved significantly when both the die and punch were heated to 200 °C. Remarkable improvement in deep drawn cup depth was observed when die and punch temperatures were maintained at 200 and 30 °C, respectively, producing a non-isothermal temperature gradient of approximately 93 °C across the blank from flange to center. The forming behavior at different isothermal and non-isothermal conditions were predicted successfully using a thermo-mechanical FE model incorporating temperature-dependent properties in Barlat-89 yield criterion coupled with Cowper-Symonds hardening model, and the thinning/failure location in deformed cups were validated implementing the experimental limiting strains as damage model.

First Investigation of the Microbiology of the Deepest Layer of Ocean Crust

PubMed Central

Mason, Olivia U.; Nakagawa, Tatsunori; Rosner, Martin; Van Nostrand, Joy D.; Zhou, Jizhong; Maruyama, Akihiko; Fisk, Martin R.; Giovannoni, Stephen J.

2010-01-01

The gabbroic layer comprises the majority of ocean crust. Opportunities to sample this expansive crustal environment are rare because of the technological demands of deep ocean drilling; thus, gabbroic microbial communities have not yet been studied. During the Integrated Ocean Drilling Program Expeditions 304 and 305, igneous rock samples were collected from 0.45-1391.01 meters below seafloor at Hole 1309D, located on the Atlantis Massif (30 °N, 42 °W). Microbial diversity in the rocks was analyzed by denaturing gradient gel electrophoresis and sequencing (Expedition 304), and terminal restriction fragment length polymorphism, cloning and sequencing, and functional gene microarray analysis (Expedition 305). The gabbroic microbial community was relatively depauperate, consisting of a low diversity of proteobacterial lineages closely related to Bacteria from hydrocarbon-dominated environments and to known hydrocarbon degraders, and there was little evidence of Archaea. Functional gene diversity in the gabbroic samples was analyzed with a microarray for metabolic genes (“GeoChip”), producing further evidence of genomic potential for hydrocarbon degradation - genes for aerobic methane and toluene oxidation. Genes coding for anaerobic respirations, such as nitrate reduction, sulfate reduction, and metal reduction, as well as genes for carbon fixation, nitrogen fixation, and ammonium-oxidation, were also present. Our results suggest that the gabbroic layer hosts a microbial community that can degrade hydrocarbons and fix carbon and nitrogen, and has the potential to employ a diversity of non-oxygen electron acceptors. This rare glimpse of the gabbroic ecosystem provides further support for the recent finding of hydrocarbons in deep ocean gabbro from Hole 1309D. It has been hypothesized that these hydrocarbons might originate abiotically from serpentinization reactions that are occurring deep in the Earth's crust, raising the possibility that the lithic microbial community reported here might utilize carbon sources produced independently of the surface biosphere. PMID:21079766

Population genetic structure and phylogeographical pattern of rice grasshopper, Oxya hyla intricata, across Southeast Asia.

PubMed

Li, Tao; Zhang, Min; Qu, Yanhua; Ren, Zhumei; Zhang, Jianzhen; Guo, Yaping; Heong, K L; Villareal, Bong; Zhong, Yang; Ma, Enbo

2011-04-01

The rice grasshopper, Oxya hyla intricata, is a rice pest in Southeast Asia. In this study, population genetic diversity and structure of this Oxya species was examined using both DNA sequences and AFLP technology. The samples of 12 populations were collected from four Southeast Asian countries, among which 175 individuals were analysed using mitochondrial DNA cytochrome c oxidase subunit I (COI) sequences, and 232 individuals were examined using amplified fragment length polymorphisms (AFLP) to test whether the phylogeographical pattern and population genetics of this species are related to past geological events and/or climatic oscillations. No obvious trend of genetic diversity was found along a latitude/longitude gradient among different geographical groups. Phylogenetic analysis indicated three deep monophyletic clades that approximately correspond to three geographical regions separated by high mountains and a deep strait, and TCS analysis also revealed three disconnected networks, suggesting that spatial and temporal separations by vicariance, which were also supported by AMOVA as a source of the molecular variance presented among groups. Gene flow analysis showed that there had been frequent historical gene flow among local populations in different regions, but the networks exhibited no shared haplotype among populations. In conclusion, the past geological events and climatic fluctuations are the most important factor on the phylogeographical structure and genetic patterns of O. hyla intricata in Southeast Asia. Habitat, vegetation, and anthropogenic effect may also contribute to gene flow and introgression of this species. Moreover, temperature, abundant rainfall and a diversity of graminaceous species are beneficial for the migration of O. hyla intricata. High haplotype diversity, deep phylogenetic division, negative Fu's F (s) values and unimodal and multimodal distribution shapes all suggest a complicated demographic expansion pattern of these O. hyla intricata populations, which might have been caused by climatic oscillations during glacial periods in the Quaternary.

First investigation of the microbiology of the deepest layer of ocean crust.

PubMed

Mason, Olivia U; Nakagawa, Tatsunori; Rosner, Martin; Van Nostrand, Joy D; Zhou, Jizhong; Maruyama, Akihiko; Fisk, Martin R; Giovannoni, Stephen J

2010-11-05

The gabbroic layer comprises the majority of ocean crust. Opportunities to sample this expansive crustal environment are rare because of the technological demands of deep ocean drilling; thus, gabbroic microbial communities have not yet been studied. During the Integrated Ocean Drilling Program Expeditions 304 and 305, igneous rock samples were collected from 0.45-1391.01 meters below seafloor at Hole 1309D, located on the Atlantis Massif (30 °N, 42 °W). Microbial diversity in the rocks was analyzed by denaturing gradient gel electrophoresis and sequencing (Expedition 304), and terminal restriction fragment length polymorphism, cloning and sequencing, and functional gene microarray analysis (Expedition 305). The gabbroic microbial community was relatively depauperate, consisting of a low diversity of proteobacterial lineages closely related to Bacteria from hydrocarbon-dominated environments and to known hydrocarbon degraders, and there was little evidence of Archaea. Functional gene diversity in the gabbroic samples was analyzed with a microarray for metabolic genes ("GeoChip"), producing further evidence of genomic potential for hydrocarbon degradation--genes for aerobic methane and toluene oxidation. Genes coding for anaerobic respirations, such as nitrate reduction, sulfate reduction, and metal reduction, as well as genes for carbon fixation, nitrogen fixation, and ammonium-oxidation, were also present. Our results suggest that the gabbroic layer hosts a microbial community that can degrade hydrocarbons and fix carbon and nitrogen, and has the potential to employ a diversity of non-oxygen electron acceptors. This rare glimpse of the gabbroic ecosystem provides further support for the recent finding of hydrocarbons in deep ocean gabbro from Hole 1309D. It has been hypothesized that these hydrocarbons might originate abiotically from serpentinization reactions that are occurring deep in the Earth's crust, raising the possibility that the lithic microbial community reported here might utilize carbon sources produced independently of the surface biosphere.

ViDiT-CACTUS: an inexpensive and versatile library preparation and sequence analysis method for virus discovery and other microbiology applications.

PubMed

Verhoeven, Joost Theo Petra; Canuti, Marta; Munro, Hannah J; Dufour, Suzanne C; Lang, Andrew S

2018-04-19

High-throughput sequencing (HTS) technologies are becoming increasingly important within microbiology research, but aspects of library preparation, such as high cost per sample or strict input requirements, make HTS difficult to implement in some niche applications and for research groups on a budget. To answer these necessities, we developed ViDiT, a customizable, PCR-based, extremely low-cost (<5 US dollars per sample) and versatile library preparation method, and CACTUS, an analysis pipeline designed to rely on cloud computing power to generate high-quality data from ViDiT-based experiments without the need of expensive servers. We demonstrate here the versatility and utility of these methods within three fields of microbiology: virus discovery, amplicon-based viral genome sequencing and microbiome profiling. ViDiT-CACTUS allowed the identification of viral fragments from 25 different viral families from 36 oropharyngeal-cloacal swabs collected from wild birds, the sequencing of three almost complete genomes of avian influenza A viruses (>90% coverage), and the characterization and functional profiling of the complete microbial diversity (bacteria, archaea, viruses) within a deep-sea carnivorous sponge. ViDiT-CACTUS demonstrated its validity in a wide range of microbiology applications and its simplicity and modularity make it easily implementable in any molecular biology laboratory, towards various research goals.

Telepresence-Enabled Remote Fieldwork: Undergraduate Research in the Deep Sea

ERIC Educational Resources Information Center

Stephens, A. Lynn; Pallant, Amy; McIntyre, Cynthia

2016-01-01

Deep-sea research is rarely available to undergraduate students. However, as telepresence technology becomes more available, doors may open for more undergraduates to pursue research that includes remote fieldwork. This descriptive case study is an initial investigation into whether such technology might provide a feasible opportunity for…

The deep space network, Volume 11

NASA Technical Reports Server (NTRS)

1972-01-01

Deep Space Network progress in flight project support, Tracking and Data Acquisition research and technology, network engineering, hardware and software implementation, and operations are presented. Material is presented in each of the following categories: description of DSN; mission support; radio science; support research and technology; network engineering and implementation; and operations and facilities.

Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library.

PubMed

Sánchez, Cecilia Castaño; Smith, Timothy P L; Wiedmann, Ralph T; Vallejo, Roger L; Salem, Mohamed; Yao, Jianbo; Rexroad, Caird E

2009-11-25

To enhance capabilities for genomic analyses in rainbow trout, such as genomic selection, a large suite of polymorphic markers that are amenable to high-throughput genotyping protocols must be identified. Expressed Sequence Tags (ESTs) have been used for single nucleotide polymorphism (SNP) discovery in salmonids. In those strategies, the salmonid semi-tetraploid genomes often led to assemblies of paralogous sequences and therefore resulted in a high rate of false positive SNP identification. Sequencing genomic DNA using primers identified from ESTs proved to be an effective but time consuming methodology of SNP identification in rainbow trout, therefore not suitable for high throughput SNP discovery. In this study, we employed a high-throughput strategy that used pyrosequencing technology to generate data from a reduced representation library constructed with genomic DNA pooled from 96 unrelated rainbow trout that represent the National Center for Cool and Cold Water Aquaculture (NCCCWA) broodstock population. The reduced representation library consisted of 440 bp fragments resulting from complete digestion with the restriction enzyme HaeIII; sequencing produced 2,000,000 reads providing an average 6 fold coverage of the estimated 150,000 unique genomic restriction fragments (300,000 fragment ends). Three independent data analyses identified 22,022 to 47,128 putative SNPs on 13,140 to 24,627 independent contigs. A set of 384 putative SNPs, randomly selected from the sets produced by the three analyses were genotyped on individual fish to determine the validation rate of putative SNPs among analyses, distinguish apparent SNPs that actually represent paralogous loci in the tetraploid genome, examine Mendelian segregation, and place the validated SNPs on the rainbow trout linkage map. Approximately 48% (183) of the putative SNPs were validated; 167 markers were successfully incorporated into the rainbow trout linkage map. In addition, 2% of the sequences from the validated markers were associated with rainbow trout transcripts. The use of reduced representation libraries and pyrosequencing technology proved to be an effective strategy for the discovery of a high number of putative SNPs in rainbow trout; however, modifications to the technique to decrease the false discovery rate resulting from the evolutionary recent genome duplication would be desirable.

Innovations in deep brain stimulation methodology.

PubMed

Kühn, Andrea A; Volkmann, Jens

2017-01-01

Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

What are Whole Exome Sequencing and Whole Genome Sequencing?

MedlinePlus

... the future. For more information about DNA sequencing technologies and their use: Genetics Home Reference discusses whether ... University in St. Louis describes the different sequencing technologies and what the new technologies have meant for ...

Deep RNA-Seq to unlock the gene bank of floral development in Sinapis arvensis.

PubMed

Liu, Jia; Mei, Desheng; Li, Yunchang; Huang, Shunmou; Hu, Qiong

2014-01-01

Sinapis arvensis is a weed with strong biological activity. Despite being a problematic annual weed that contaminates agricultural crop yield, it is a valuable alien germplasm resource. It can be utilized for broadening the genetic background of Brassica crops with desirable agricultural traits like resistance to blackleg (Leptosphaeria maculans), stem rot (Sclerotinia sclerotium) and pod shatter (caused by FRUITFULL gene). However, few genetic studies of S. arvensis were reported because of the lack of genomic resources. In the present study, we performed de novo transcriptome sequencing to produce a comprehensive dataset for S. arvensis for the first time. We used Illumina paired-end sequencing technology to sequence the S. arvensis flower transcriptome and generated 40,981,443 reads that were assembled into 131,278 transcripts. We de novo assembled 96,562 high quality unigenes with an average length of 832 bp. A total of 33,662 full-length ORF complete sequences were identified, and 41,415 unigenes were mapped onto 128 pathways using the KEGG Pathway database. The annotated unigenes were compared against Brassica rapa, B. oleracea, B. napus and Arabidopsis thaliana. Among these unigenes, 76,324 were identified as putative homologs of annotated sequences in the public protein databases, of which 1194 were associated with plant hormone signal transduction and 113 were related to gibberellin homeostasis/signaling. Unigenes that did not match any of those sequence datasets were considered to be unique to S. arvensis. Furthermore, 21,321 simple sequence repeats were found. Our study will enhance the currently available resources for Brassicaceae and will provide a platform for future genomic studies for genetic improvement of Brassica crops.

Deep RNA-Seq to Unlock the Gene Bank of Floral Development in Sinapis arvensis

PubMed Central

Liu, Jia; Mei, Desheng; Li, Yunchang; Huang, Shunmou; Hu, Qiong

2014-01-01

Sinapis arvensis is a weed with strong biological activity. Despite being a problematic annual weed that contaminates agricultural crop yield, it is a valuable alien germplasm resource. It can be utilized for broadening the genetic background of Brassica crops with desirable agricultural traits like resistance to blackleg (Leptosphaeria maculans), stem rot (Sclerotinia sclerotium) and pod shatter (caused by FRUITFULL gene). However, few genetic studies of S. arvensis were reported because of the lack of genomic resources. In the present study, we performed de novo transcriptome sequencing to produce a comprehensive dataset for S. arvensis for the first time. We used Illumina paired-end sequencing technology to sequence the S. arvensis flower transcriptome and generated 40,981,443 reads that were assembled into 131,278 transcripts. We de novo assembled 96,562 high quality unigenes with an average length of 832 bp. A total of 33,662 full-length ORF complete sequences were identified, and 41,415 unigenes were mapped onto 128 pathways using the KEGG Pathway database. The annotated unigenes were compared against Brassica rapa, B. oleracea, B. napus and Arabidopsis thaliana. Among these unigenes, 76,324 were identified as putative homologs of annotated sequences in the public protein databases, of which 1194 were associated with plant hormone signal transduction and 113 were related to gibberellin homeostasis/signaling. Unigenes that did not match any of those sequence datasets were considered to be unique to S. arvensis. Furthermore, 21,321 simple sequence repeats were found. Our study will enhance the currently available resources for Brassicaceae and will provide a platform for future genomic studies for genetic improvement of Brassica crops. PMID:25192023

The Gateway Garden — A Prototype Food Production Facility for Deep Space Exploration

NASA Astrophysics Data System (ADS)

Fritsche, R. F.; Romeyn, M. W.; Massa, G.

2018-02-01

CIS-lunar space provides a unique opportunity to perform deep space microgravity crop science research while also addressing and advancing food production technologies that will be deployed on the Deep Space Transport.

Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing

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

Whitehead, Timothy A.; Chevalier, Aaron; Song, Yifan

2012-06-19

We show that comprehensive sequence-function maps obtained by deep sequencing can be used to reprogram interaction specificity and to leapfrog over bottlenecks in affinity maturation by combining many individually small contributions not detectable in conventional approaches. We use this approach to optimize two computationally designed inhibitors against H1N1 influenza hemagglutinin and, in both cases, obtain variants with subnanomolar binding affinity. The most potent of these, a 51-residue protein, is broadly cross-reactive against all influenza group 1 hemagglutinins, including human H2, and neutralizes H1N1 viruses with a potency that rivals that of several human monoclonal antibodies, demonstrating that computational design followedmore » by comprehensive energy landscape mapping can generate proteins with potential therapeutic utility.« less

Dissecting genetic and environmental mutation signatures with model organisms.

PubMed

Segovia, Romulo; Tam, Annie S; Stirling, Peter C

2015-08-01

Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon. Copyright © 2015 Elsevier Ltd. All rights reserved.

A ruby-colored Pseudobaeospora species is described as new from material collected on the island of Hawaii.

PubMed

Desjardin, Dennis E; Hemmes, Don E; Perry, Brian A

2014-01-01

Pseudobaeospora wipapatiae is described as new based on material collected in alien wet habitats on the island of Hawaii. Unique features of this beautiful species include deep ruby-colored basidiomes with two-spored basidia, amyloid cheilocystidia and a hymeniderm pileipellis with abundant pileocystidia that is initially deep ruby in KOH then changes to lilac gray. Phylogenetic analysis of nuclear large ribosomal subunit sequence data suggest a close relationship between Pseudobaeospora and Tricholoma. BLAST comparisons of internal transcribed spacer and 5.8S nuclear ribosomal subunit regions sequence data reveal greatest similarity with existing sequences of Pseudobaeospora species. A comprehensive description, color photograph, illustrations of salient micromorphological features and comparisons with phenetically similar taxa are provided. © 2014 by The Mycological Society of America.

Advanced technologies demonstrated by the miniature integrated camera and spectrometer (MICAS) aboard deep space 1

USGS Publications Warehouse

Rodgers, D.H.; Beauchamp, P.M.; Soderblom, L.A.; Brown, R.H.; Chen, G.-S.; Lee, M.; Sandel, B.R.; Thomas, D.A.; Benoit, R.T.; Yelle, R.V.

2007-01-01

MICAS is an integrated multi-channel instrument that includes an ultraviolet imaging spectrometer (80-185 nm), two high-resolution visible imagers (10-20 ??rad/pixel, 400-900 nm), and a short-wavelength infrared imaging spectrometer (1250-2600 nm). The wavelength ranges were chosen to maximize the science data that could be collected using existing semiconductor technologies and avoiding the need for multi-octave spectrometers. It was flown on DS1 to validate technologies derived from the development of PICS (Planetary Imaging Camera Spectrometer). These technologies provided a novel systems approach enabling the miniaturization and integration of four instruments into one entity, spanning a wavelength range from the UV to IR, and from ambient to cryogenic temperatures with optical performance at a fraction of a wavelength. The specific technologies incorporated were: a built-in fly-by sequence; lightweight and ultra-stable, monolithic silicon-carbide construction, which enabled room-temperature alignment for cryogenic (85-140 K) performance, and provided superb optical performance and immunity to thermal distortion; diffraction-limited, shared optics operating from 80 to 2600 nm; advanced detector technologies for the UV, visible and short-wavelength IR; high-performance thermal radiators coupled directly to the short-wave infrared (SWIR) detector optical bench, providing an instrument with a mass less than 10 kg, instrument power less than 10 W, and total instrument cost of less than ten million dollars. The design allows the wavelength range to be extended by at least an octave at the short wavelength end and to 50 microns at the long wavelength end. Testing of the completed instrument demonstrated excellent optical performance down to 77 K, which would enable a greatly reduced background for longer wavelength detectors. During the Deep Space 1 Mission, MICAS successfully collected images and spectra for asteroid 9969 Braille, Mars, and comet 19/P Borrelly. The Borrelly encounter was a scientific hallmark providing the first clear, high resolution images and excellent, short-wavelength infrared spectra of the surface of an active comet's nucleus. ?? 2007 Springer Science+Business Media, Inc.

Sequencing Technologies Panel at SFAF

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

Turner, Steve; Fiske, Haley; Knight, Jim

2010-06-02

From left to right: Steve Turner of Pacific Biosciences, Haley Fiske of Illumina, Jim Knight of Roche, Michael Rhodes of Life Technologies and Peter Vander Horn of Life Technologies' Single Molecule Sequencing group discuss new sequencing technologies and applications on June 2, 2010 at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM

Development of levees on deep-sea channels: Insights from high-resolution AUV exploration of the Lucia Chica system, offshore central California

NASA Astrophysics Data System (ADS)

Maier, K. L.; Fildani, A.; Romans, B.; Paull, C. K.; McHargue, T.; Graham, S. A.; Caress, D. W.

2010-12-01

The Lucia Chica, a tributary channel system of the Lucia Canyon, offshore central California, was imaged using the Monterey Bay Aquarium Research Institute’s (MBARI) Autonomous Underwater Vehicle (AUV) in order to investigate seafloor and subsurface morphologies associated with low-relief submarine channels. In larger, previously investigated seafloor channel-levee systems, initial deposits are either eroded, compacted, or below the resolution of available imaging. In this dataset from the Lucia Chica, the unprecedented high-resolution multibeam bathymetry (1 m lateral resolution) and chirp sub-bottom profiles (11 cm vertical resolution) reveal a highly irregular seafloor with scours, depressions, and discontinuous low-relief conduits over an area of ~70 km2. Sediment packages associated with channels, levees, and deposits related to less confined flows are correlated between chirp profiles and with the multibeam bathymetric image to determine the stratigraphic evolution of the Lucia Chica and the sequence of channel-levee development. In the Lucia Chica, channels appear to have initiated as trains of scours that eventually coalesced into continuous channel thalwegs carved by erosional turbidity currents. Channel incision and stepped lateral migration led to the development of terraces, complex levee stratigraphy, and distinct morphologies associated with inner and outer bends of sinuous channels. The inner bend levee stratigraphy indicates that the channel position migrated in discrete shifts, as opposed to continuous channel migration associated with lateral accretion. Discrete levee packages, formed from flow-stripped turbidity currents, later infilled abandoned portions of the channel and overbank areas. While processes of initial channel and levee development are well established in fluvial settings, detailed examples are lacking for deep-sea systems. These results highlight the differences in initiation between submarine channel systems, their fluvial counterparts, and larger submarine channel-levee systems imaged only with lower-resolution technologies. High-resolution imaging and detailed mapping made possible by cutting-edge oceanographic technology provide an unprecedented examination of deep-water channel-levee morphology and improve understanding of deep-water channel migration and levee development.

The dating and interpretation of a Mode 1 site in the Luangwa Valley, Zambia.

PubMed

Barham, Lawrence; Phillips, William M; Maher, Barbara A; Karloukovski, Vassil; Duller, Geoff A T; Jain, Mayank; Wintle, Ann G

2011-05-01

Flake based assemblages (Mode 1) comprise the earliest stone technologies known, with well-dated Oldowan sites occurring in eastern Africa between ~2.6-1.7 Ma, and in less securely dated contexts in central, southern and northern Africa. Our understanding of the spread and local development of this technology outside East Africa remains hampered by the lack of reliable numerical dating techniques applicable to non-volcanic deposits. This study applied the still relatively new technique of cosmogenic nuclide burial dating ((10)Be/(26)Al) to calculate burial ages for fluvial gravels containing Mode 1 artefacts in the Luangwa Valley, Zambia. The Manzi River, a tributary of the Luangwa River, has exposed a 4.7 m deep section of fluvial sands with discontinuous but stratified gravel layers bearing Mode 1, possibly Oldowan, artefacts in the basal layers. An unconformity divides the Manzi section, separating Mode 1 deposits from overlying gravels containing Mode 3 (Middle Stone Age) artefacts. No diagnostic Mode 2 (Acheulean) artefacts were found. Cosmogenic nuclide burial dating was attempted for the basal gravels as well as exposure ages for the upper Mode 3 gravels, but was unsuccessful. The complex depositional history of the site prevented the calculation of reliable age models. A relative chronology for the full Manzi sequence was constructed, however, from the magnetostratigraphy of the deposit (N>R>N sequence). Isothermal thermoluminescence (ITL) dating of the upper Mode 3 layers also provided consistent results (~78 ka). A coarse but chronologically coherent sequence now exists for the Manzi section with the unconformity separating probable mid- or early Pleistocene deposits below from late Pleistocene deposits above. The results suggest Mode 1 technology in the Luangwa Valley may post-date the Oldowan in eastern and southern Africa. The dating programme has contributed to a clearer understanding of the geomorphological processes that have shaped the valley and structured its archaeological record. Copyright © 2010 Elsevier Ltd. All rights reserved.

The dating and interpretation of a Mode 1 site in the Luangwa Valley, Zambia

USGS Publications Warehouse

Barham, L.; Phillips, W.M.; Maher, B.A.; Karloukovski, V.; Duller, G.A.T.; Jain, M.; Wintle, A.G.

2011-01-01

Flake based assemblages (Mode 1) comprise the earliest stone technologies known, with well-dated Oldowan sites occurring in eastern Africa between ??? 2.6-1.7 Ma, and in less securely dated contexts in central, southern and northern Africa. Our understanding of the spread and local development of this technology outside East Africa remains hampered by the lack of reliable numerical dating techniques applicable to non-volcanic deposits. This study applied the still relatively new technique of cosmogenic nuclide burial dating (10Be/26Al) to calculate burial ages for fluvial gravels containing Mode 1 artefacts in the Luangwa Valley, Zambia. The Manzi River, a tributary of the Luangwa River, has exposed a 4.7 m deep section of fluvial sands with discontinuous but stratified gravel layers bearing Mode 1, possibly Oldowan, artefacts in the basal layers. An unconformity divides the Manzi section, separating Mode 1 deposits from overlying gravels containing Mode 3 (Middle Stone Age) artefacts. No diagnostic Mode 2 (Acheulean) artefacts were found. Cosmogenic nuclide burial dating was attempted for the basal gravels as well as exposure ages for the upper Mode 3 gravels, but was unsuccessful. The complex depositional history of the site prevented the calculation of reliable age models. A relative chronology for the full Manzi sequence was constructed, however, from the magnetostratigraphy of the deposit (N>R>N sequence). Isothermal thermoluminescence (ITL) dating of the upper Mode 3 layers also provided consistent results (???78 ka). A coarse but chronologically coherent sequence now exists for the Manzi section with the unconformity separating probable mid- or early Pleistocene deposits below from late Pleistocene deposits above. The results suggest Mode 1 technology in the Luangwa Valley may post-date the Oldowan in eastern and southern Africa. The dating programme has contributed to a clearer understanding of the geomorphological processes that have shaped the valley and structured its archaeological record. ?? 2010 Elsevier Ltd.

Architectural Options for a Future Deep Space Optical Communications Network

NASA Technical Reports Server (NTRS)

Edwards, B. L.; Benjamin, T.; Scozzafava, J.; Khatri, F.; Sharma, J.; Parvin, B.; Liebrecht, P. E.; Fitzgerald, R. J.

2004-01-01

This paper provides an overview of different options at Earth to provide Deep Space optical communication services. It is based mainly on work done for the Mars Laser Communications Demonstration (MLCD) Project, a joint project between NASA's Goddard Space Flight Center (GSFC), the Jet Propulsion Laboratory, California Institute of Technology (JPL), and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL). It also reports preliminary conclusions from the Tracking and Data Relay Satellite System Continuation Study at GSFC. A lasercom flight terminal will be flown on the Mars Telecommunications Orbiter (MTO) to be launched by NASA in 2009, and will be the first high rate deep space demonstration of this revolutionary technology.

Dive Europa: a search-for-life initiative.

PubMed

Naganuma, T; Uematsu, H

1998-06-01

Liquid water, underwater volcanoes and possibly life forms have been suggested to be present beneath the estimated 10 km-thick ice shell of Europa the Jovian satellite J2. Europa's possible ocean is estimated to be 100-200km deep. Despite the great depth of the Europa's ocean, hydrostatic pressure at the seafloor would be 130-260 MPa, corresponding to 13-26 km depth of a theoretical Earth's ocean. The hydrostatic pressure is not beyond the edge of existing deep-sea technology. Here we propose exploration of Europa's deep-sea by the use of current technologies, taking a symbolic example of a deep submergence vehicle Shinkai 6500 which dives to a depth of 6.5 km deep (50 km depth of Europa's ocean). Shinkai 6500 is embarkable in the payload bay of the Space Shuttles in terms of size and weight for the transportation to a Low Earth Orbit (LEO). Secondary boost is needed for interplanetary flight from the LEO. On-orbit assembly of the secondary booster is a technological challenge. The International Space Station (ISS) and ISS-related technologies will facilitate the secondary boost. Also, ice shell drilling is a challenge and is needed before the dive into Europa's ocean. These challenges should be overcome during a certain leading time for matured experience in the ISS operation.

Deep Web video

ScienceCinema

None Available

2018-02-06

To make the web work better for science, OSTI has developed state-of-the-art technologies and services including a deep web search capability. The deep web includes content in searchable databases available to web users but not accessible by popular search engines, such as Google. This video provides an introduction to the deep web search engine.

Evaluation of 16S Rrna amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers

USDA-ARS?s Scientific Manuscript database

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplificatio...

Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers

USDA-ARS?s Scientific Manuscript database

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplificatio...

DeepSig: deep learning improves signal peptide detection in proteins.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita

2018-05-15

The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. pierluigi.martelli@unibo.it. Supplementary data are available at Bioinformatics online.

A Diverse Repertoire of Human Immunoglobulin Variable Genes in a Chicken B Cell Line is Generated by Both Gene Conversion and Somatic Hypermutation.

PubMed

Leighton, Philip A; Schusser, Benjamin; Yi, Henry; Glanville, Jacob; Harriman, William

2015-01-01

Chicken immune responses to human proteins are often more robust than rodent responses because of the phylogenetic relationship between the different species. For discovery of a diverse panel of unique therapeutic antibody candidates, chickens therefore represent an attractive host for human-derived targets. Recent advances in monoclonal antibody technology, specifically new methods for the molecular cloning of antibody genes directly from primary B cells, has ushered in a new era of generating monoclonal antibodies from non-traditional host animals that were previously inaccessible through hybridoma technology. However, such monoclonals still require post-discovery humanization in order to be developed as therapeutics. To obviate the need for humanization, a modified strain of chickens could be engineered to express a human-sequence immunoglobulin variable region repertoire. Here, human variable genes introduced into the chicken immunoglobulin loci through gene targeting were evaluated for their ability to be recognized and diversified by the native chicken recombination machinery that is present in the B-lineage cell line DT40. After expansion in culture the DT40 population accumulated genetic mutants that were detected via deep sequencing. Bioinformatic analysis revealed that the human targeted constructs are performing as expected in the cell culture system, and provide a measure of confidence that they will be functional in transgenic animals.

Beyond public perceptions of gene technology: community participation in public policy in Australia.

PubMed

Dietrich, Heather; Schibeci, Renato

2003-10-01

Public policy assumptions, which view "the public" as passive consumers, are deeply flawed. "The public" are, in fact, active citizens, who constitute the innovation end of the seamless web of relationships, running from research and development laboratory to shop, hospital or farm, or local neighborhood. "The public" do not receive the impact of technology; they are the impact, in that they determine with gene technology (GT) developers and sellers what happens to the technology in our society. In doing so, they, or more rightly we, exercise particular, contextual knowledges and actions. We suggest that it is the ignorance of this aspect of innovation in policy processes that produces the distrust and resentment that we found in our interviews with "publics" interested in gene technology. This is consistent with Beck's description of the deep structural states of risk and fear in modern advanced societies with respect to new technologies, such as gene technology. Only policy processes that recognize the particular, local and contextual knowledges of "the public", which co-construct innovation, can achieve deep, social structural consideration of gene technology. And only such a deep consideration can avoid the polarized attitudes and deep suspicions that we have seen arise in places such as Britain. Such consideration needs the type of processes that involve active consultation and inclusion of "the public" in government and commercial innovation, the so-called deliberative and inclusionary processes (DIPs), such as consensus conferences and citizen juries. We suggest some measures that could be tried in Australia, which would take us further down the path of participation toward technological citizenship.

High Diversity of Myocyanophage in Various Aquatic Environments Revealed by High-Throughput Sequencing of Major Capsid Protein Gene With a New Set of Primers.

PubMed

Hou, Weiguo; Wang, Shang; Briggs, Brandon R; Li, Gaoyuan; Xie, Wei; Dong, Hailiang

2018-01-01

Myocyanophages, a group of viruses infecting cyanobacteria, are abundant and play important roles in elemental cycling. Here we investigated the particle-associated viral communities retained on 0.2 μm filters and in sediment samples (representing ancient cyanophage communities) from four ocean and three lake locations, using high-throughput sequencing and a newly designed primer pair targeting a gene fragment (∼145-bp in length) encoding the cyanophage gp23 major capsid protein (MCP). Diverse viral communities were detected in all samples. The fragments of 142-, 145-, and 148-bp in length were most abundant in the amplicons, and most sequences (>92%) belonged to cyanophages. Additionally, different sequencing depths resulted in different diversity estimates of the viral community. Operational taxonomic units obtained from deep sequencing of the MCP gene covered the majority of those obtained from shallow sequencing, suggesting that deep sequencing exhibited a more complete picture of cyanophage community than shallow sequencing. Our results also revealed a wide geographic distribution of marine myocyanophages, i.e., higher dissimilarities of the myocyanophage communities corresponded with the larger distances between the sampling sites. Collectively, this study suggests that the newly designed primer pair can be effectively used to study the community and diversity of myocyanophage from different environments, and the high-throughput sequencing represents a good method to understand viral diversity.

High Diversity of Myocyanophage in Various Aquatic Environments Revealed by High-Throughput Sequencing of Major Capsid Protein Gene With a New Set of Primers

PubMed Central

Hou, Weiguo; Wang, Shang; Briggs, Brandon R.; Li, Gaoyuan; Xie, Wei; Dong, Hailiang

2018-01-01

Myocyanophages, a group of viruses infecting cyanobacteria, are abundant and play important roles in elemental cycling. Here we investigated the particle-associated viral communities retained on 0.2 μm filters and in sediment samples (representing ancient cyanophage communities) from four ocean and three lake locations, using high-throughput sequencing and a newly designed primer pair targeting a gene fragment (∼145-bp in length) encoding the cyanophage gp23 major capsid protein (MCP). Diverse viral communities were detected in all samples. The fragments of 142-, 145-, and 148-bp in length were most abundant in the amplicons, and most sequences (>92%) belonged to cyanophages. Additionally, different sequencing depths resulted in different diversity estimates of the viral community. Operational taxonomic units obtained from deep sequencing of the MCP gene covered the majority of those obtained from shallow sequencing, suggesting that deep sequencing exhibited a more complete picture of cyanophage community than shallow sequencing. Our results also revealed a wide geographic distribution of marine myocyanophages, i.e., higher dissimilarities of the myocyanophage communities corresponded with the larger distances between the sampling sites. Collectively, this study suggests that the newly designed primer pair can be effectively used to study the community and diversity of myocyanophage from different environments, and the high-throughput sequencing represents a good method to understand viral diversity.

High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.

PubMed

Stegmayer, Georgina; Yones, Cristian; Kamenetzky, Laura; Milone, Diego H

2017-01-01

The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high class-imbalance classification problem. The classical way of approaching it has been training a binary classifier in a supervised manner, using well-known pre-miRNAs as positive class and artificially defining the negative class. However, although the selection of positive labeled examples is straightforward, it is very difficult to build a set of negative examples in order to obtain a good set of training samples for a supervised method. In this work, we propose a novel and effective way of approaching this problem using machine learning, without the definition of negative examples. The proposal is based on clustering unlabeled sequences of a genome together with well-known miRNA precursors for the organism under study, which allows for the quick identification of the best candidates to miRNA as those sequences clustered with known precursors. Furthermore, we propose a deep model to overcome the problem of having very few positive class labels. They are always maintained in the deep levels as positive class while less likely pre-miRNA sequences are filtered level after level. Our approach has been compared with other methods for pre-miRNAs prediction in several species, showing effective predictivity of novel miRNAs. Additionally, we will show that our approach has a lower training time and allows for a better graphical navegability and interpretation of the results. A web-demo interface to try deepSOM is available at http://fich.unl.edu.ar/sinc/web-demo/deepsom/.

Molecular diversity and distribution pattern of ciliates in sediments from deep-sea hydrothermal vents in the Okinawa Trough and adjacent sea areas

NASA Astrophysics Data System (ADS)

Zhao, Feng; Xu, Kuidong

2016-10-01

In comparison with the macrobenthos and prokaryotes, patterns of diversity and distribution of microbial eukaryotes in deep-sea hydrothermal vents are poorly known. The widely used high-throughput sequencing of 18S rDNA has revealed a high diversity of microeukaryotes yielded from both living organisms and buried DNA in marine sediments. More recently, cDNA surveys have been utilized to uncover the diversity of active organisms. However, both methods have never been used to evaluate the diversity of ciliates in hydrothermal vents. By using high-throughput DNA and cDNA sequencing of 18S rDNA, we evaluated the molecular diversity of ciliates, a representative group of microbial eukaryotes, from the sediments of deep-sea hydrothermal vents in the Okinawa Trough and compared it with that of an adjacent deep-sea area about 15 km away and that of an offshore area of the Yellow Sea about 500 km away. The results of DNA sequencing showed that Spirotrichea and Oligohymenophorea were the most diverse and abundant groups in all the three habitats. The proportion of sequences of Oligohymenophorea was the highest in the hydrothermal vents whereas Spirotrichea was the most diverse group at all three habitats. Plagiopyleans were found only in the hydrothermal vents but with low diversity and abundance. By contrast, the cDNA sequencing showed that Plagiopylea was the most diverse and most abundant group in the hydrothermal vents, followed by Spirotrichea in terms of diversity and Oligohymenophorea in terms of relative abundance. A novel group of ciliates, distinctly separate from the 12 known classes, was detected in the hydrothermal vents, indicating undescribed, possibly highly divergent ciliates may inhabit this environment. Statistical analyses showed that: (i) the three habitats differed significantly from one another in terms of diversity of both the rare and the total ciliate taxa, and; (ii) the adjacent deep sea was more similar to the offshore area than to the hydrothermal vents. In terms of the diversity of abundant taxa, however, there was no significant difference between the hydrothermal vents and the adjacent deep sea, both of which differed significantly from the offshore area. As abundant ciliate taxa can be found in several sampling sites, they are likely adapted to large environmental variations, while rare taxa are found in specific habitat and thus are potentially more sensitive to varying environmental conditions.

Deep Sequencing Reveals a Divergent Ugandan cassava brown streak virus Isolate from Malawi

PubMed Central

Winter, Stephan; Mukasa, Settumba; Tairo, Fred; Sseruwagi, Peter; Ndunguru, Joseph; Duffy, Siobain

2017-01-01

ABSTRACT Illumina sequencing of RNA from a cassava cutting from northern Malawi produced a genome of Ugandan cassava brown streak virus (UCBSV-MW-NB7_2013). Sequence comparisons revealed stronger similarity to an isolate from nearby Tanzania (93.4% pairwise nucleotide identity) than to those previously reported from Malawi (86.9 to 87.0%). PMID:28818908

High-Throughput SNP Discovery through Deep Resequencing of a Reduced Representation Library to Anchor and Orient Scaffolds in the Soybean Whole Genome Sequence

USDA-ARS?s Scientific Manuscript database

The soybean Consensus Map 4.0 facilitated the anchoring of 95.6% of the soybean whole genome sequence developed by the Joint Genome Institute, Department of Energy but only properly oriented 66% of the sequence scaffolds. To find additional single nucleotide polymorphism (SNP) markers for additiona...

Metagenomics Reveals Microbial Community Composition And Function With Depth In Arctic Permafrost Cores

NASA Astrophysics Data System (ADS)

Jansson, J.; Tas, N.; Wu, Y.; Ulrich, C.; Kneafsey, T. J.; Torn, M. S.; Hubbard, S. S.; Chakraborty, R.; Graham, D. E.; Wullschleger, S. D.

2013-12-01

The Arctic is one of the most climatically sensitive regions on Earth and current surveys show that permafrost degradation is widespread in arctic soils. Biogeochemical feedbacks of permafrost thaw are expected to be dominated by the release of currently stored carbon back into the atmosphere as CO2 and CH4. Understanding the dynamics of C release from permafrost requires assessment of microbial functions from different soil compartments. To this end, as part of the Next Generation Ecosystem Experiment in the Arctic, we collected two replicate permafrost cores (1m and 3m deep) from a transitional polygon near Barrow, AK. At this location, permafrost starts from 0.5m in depth and is characterized by variable ice content and higher pH than surface soils. Prior to sectioning, the cores were CT-scanned to determine the physical heterogeneity throughout the cores. In addition to detailed geochemical characterization, we used Illumina MiSeq technology to sequence 16SrRNA genes throughout the depths of the cores at 1 cm intervals. Selected depths were also chosen for metagenome sequencing of total DNA (including phylogenetic and functional genes) using the Illumina HiSeq platform. The 16S rRNA gene sequence data revealed that the microbial community composition and diversity changed dramatically with depth. The microbial diversity decreased sharply below the first few centimeters of the permafrost and then gradually increased in deeper layers. Based on the metagenome sequence data, the permafrost microbial communities were found to contain members with a large metabolic potential for carbon processing, including pathways for fermentation and methanogenesis. The surface active layers had more representatives of Verrucomicrobia (potential methane oxidizers) whereas the deep permafrost layers were dominated by several different species of Actinobacteria. The latter are known to have a diverse metabolic capability and are able to adapt to stress by entering a dormant yet viable state. In addition, several isolates were obtained from different depths throughout the cores, including methanogens from some of the deeper layers. Together these data present a new view of potential geochemical cycles carried out by microorganisms in permafrost and reveal how community members and functions are distributed with depth.

Identifying active foraminifera in the Sea of Japan using metatranscriptomic approach

NASA Astrophysics Data System (ADS)

Lejzerowicz, Franck; Voltsky, Ivan; Pawlowski, Jan

2013-02-01

Metagenetics represents an efficient and rapid tool to describe environmental diversity patterns of microbial eukaryotes based on ribosomal DNA sequences. However, the results of metagenetic studies are often biased by the presence of extracellular DNA molecules that are persistent in the environment, especially in deep-sea sediment. As an alternative, short-lived RNA molecules constitute a good proxy for the detection of active species. Here, we used a metatranscriptomic approach based on RNA-derived (cDNA) sequences to study the diversity of the deep-sea benthic foraminifera and compared it to the metagenetic approach. We analyzed 257 ribosomal DNA and cDNA sequences obtained from seven sediments samples collected in the Sea of Japan at depths ranging from 486 to 3665 m. The DNA and RNA-based approaches gave a similar view of the taxonomic composition of foraminiferal assemblage, but differed in some important points. First, the cDNA dataset was dominated by sequences of rotaliids and robertiniids, suggesting that these calcareous species, some of which have been observed in Rose Bengal stained samples, are the most active component of foraminiferal community. Second, the richness of monothalamous (single-chambered) foraminifera was particularly high in DNA extracts from the deepest samples, confirming that this group of foraminifera is abundant but not necessarily very active in the deep-sea sediments. Finally, the high divergence of undetermined sequences in cDNA dataset indicate the limits of our database and lack of knowledge about some active but possibly rare species. Our study demonstrates the capability of the metatranscriptomic approach to detect active foraminiferal species and prompt its use in future high-throughput sequencing-based environmental surveys.

Carbonate sedimentation in an extensional active margin: Cretaceous history of the Haymana region, Pontides

NASA Astrophysics Data System (ADS)

Okay, Aral I.; Altiner, Demir

2016-10-01

The Haymana region in Central Anatolia is located in the southern part of the Pontides close to the İzmir-Ankara suture. During the Cretaceous, the region formed part of the south-facing active margin of the Eurasia. The area preserves a nearly complete record of the Cretaceous system. Shallow marine carbonates of earliest Cretaceous age are overlain by a 700-m-thick Cretaceous sequence, dominated by deep marine limestones. Three unconformity-bounded pelagic carbonate sequences of Berriasian, Albian-Cenomanian and Turonian-Santonian ages are recognized: Each depositional sequence is preceded by a period of tilting and submarine erosion during the Berriasian, early Albian and late Cenomanian, which corresponds to phases of local extension in the active continental margin. Carbonate breccias mark the base of the sequences and each carbonate sequence steps down on older units. The deep marine carbonate deposition ended in the late Santonian followed by tilting, erosion and folding during the Campanian. Deposition of thick siliciclastic turbidites started in the late Campanian and continued into the Tertiary. Unlike most forearc basins, the Haymana region was a site of deep marine carbonate deposition until the Campanian. This was because the Pontide arc was extensional and the volcanic detritus was trapped in the intra-arc basins and did not reach the forearc or the trench. The extensional nature of the arc is also shown by the opening of the Black Sea as a backarc basin in the Turonian-Santonian. The carbonate sedimentation in an active margin is characterized by synsedimentary vertical displacements, which results in submarine erosion, carbonate breccias and in the lateral discontinuity of the sequences, and differs from blanket like carbonate deposition in the passive margins.

Subsurface microbial diversity in deep-granitic-fracture water in Colorado

USGS Publications Warehouse

Sahl, J.W.; Schmidt, R.; Swanner, E.D.; Mandernack, K.W.; Templeton, A.S.; Kieft, Thomas L.; Smith, R.L.; Sanford, W.E.; Callaghan, R.L.; Mitton, J.B.; Spear, J.R.

2008-01-01

A microbial community analysis using 16S rRNA gene sequencing was performed on borehole water and a granite rock core from Henderson Mine, a >1,000-meter-deep molybdenum mine near Empire, CO. Chemical analysis of borehole water at two separate depths (1,044 m and 1,004 m below the mine entrance) suggests that a sharp chemical gradient exists, likely from the mixing of two distinct subsurface fluids, one metal rich and one relatively dilute; this has created unique niches for microorganisms. The microbial community analyzed from filtered, oxic borehole water indicated an abundance of sequences from iron-oxidizing bacteria (Gallionella spp.) and was compared to the community from the same borehole after 2 weeks of being plugged with an expandable packer. Statistical analyses with UniFrac revealed a significant shift in community structure following the addition of the packer. Phospholipid fatty acid (PLFA) analysis suggested that Nitrosomonadales dominated the oxic borehole, while PLFAs indicative of anaerobic bacteria were most abundant in the samples from the plugged borehole. Microbial sequences were represented primarily by Firmicutes, Proteobacteria, and a lineage of sequences which did not group with any identified bacterial division; phylogenetic analyses confirmed the presence of a novel candidate division. This "Henderson candidate division" dominated the clone libraries from the dilute anoxic fluids. Sequences obtained from the granitic rock core (1,740 m below the surface) were represented by the divisions Proteobacteria (primarily the family Ralstoniaceae) and Firmicutes. Sequences grouping within Ralstoniaceae were also found in the clone libraries from metal-rich fluids yet were absent in more dilute fluids. Lineage-specific comparisons, combined with phylogenetic statistical analyses, show that geochemical variance has an important effect on microbial community structure in deep, subsurface systems. Copyright ?? 2008, American Society for Microbiology. All Rights Reserved.

Subsurface Microbial Diversity in Deep-Granitic-Fracture Water in Colorado▿

PubMed Central

Sahl, Jason W.; Schmidt, Raleigh; Swanner, Elizabeth D.; Mandernack, Kevin W.; Templeton, Alexis S.; Kieft, Thomas L.; Smith, Richard L.; Sanford, William E.; Callaghan, Robert L.; Mitton, Jeffry B.; Spear, John R.

2008-01-01

A microbial community analysis using 16S rRNA gene sequencing was performed on borehole water and a granite rock core from Henderson Mine, a >1,000-meter-deep molybdenum mine near Empire, CO. Chemical analysis of borehole water at two separate depths (1,044 m and 1,004 m below the mine entrance) suggests that a sharp chemical gradient exists, likely from the mixing of two distinct subsurface fluids, one metal rich and one relatively dilute; this has created unique niches for microorganisms. The microbial community analyzed from filtered, oxic borehole water indicated an abundance of sequences from iron-oxidizing bacteria (Gallionella spp.) and was compared to the community from the same borehole after 2 weeks of being plugged with an expandable packer. Statistical analyses with UniFrac revealed a significant shift in community structure following the addition of the packer. Phospholipid fatty acid (PLFA) analysis suggested that Nitrosomonadales dominated the oxic borehole, while PLFAs indicative of anaerobic bacteria were most abundant in the samples from the plugged borehole. Microbial sequences were represented primarily by Firmicutes, Proteobacteria, and a lineage of sequences which did not group with any identified bacterial division; phylogenetic analyses confirmed the presence of a novel candidate division. This “Henderson candidate division” dominated the clone libraries from the dilute anoxic fluids. Sequences obtained from the granitic rock core (1,740 m below the surface) were represented by the divisions Proteobacteria (primarily the family Ralstoniaceae) and Firmicutes. Sequences grouping within Ralstoniaceae were also found in the clone libraries from metal-rich fluids yet were absent in more dilute fluids. Lineage-specific comparisons, combined with phylogenetic statistical analyses, show that geochemical variance has an important effect on microbial community structure in deep, subsurface systems. PMID:17981950

Deep sequencing of hepatitis C virus hypervariable region 1 reveals no correlation between genetic heterogeneity and antiviral treatment outcome

PubMed Central

2014-01-01

Background Hypervariable region 1 (HVR1) contained within envelope protein 2 (E2) gene is the most variable part of HCV genome and its translation product is a major target for the host immune response. Variability within HVR1 may facilitate evasion of the immune response and could affect treatment outcome. The aim of the study was to analyze the impact of HVR1 heterogeneity employing sensitive ultra-deep sequencing, on the outcome of PEG-IFN-α (pegylated interferon α) and ribavirin treatment. Methods HVR1 sequences were amplified from pretreatment serum samples of 25 patients infected with genotype 1b HCV (12 responders and 13 non-responders) and were subjected to pyrosequencing (GS Junior, 454/Roche). Reads were corrected for sequencing error using ShoRAH software, while population reconstruction was done using three different minimal variant frequency cut-offs of 1%, 2% and 5%. Statistical analysis was done using Mann–Whitney and Fisher’s exact tests. Results Complexity, Shannon entropy, nucleotide diversity per site, genetic distance and the number of genetic substitutions were not significantly different between responders and non-responders, when analyzing viral populations at any of the three frequencies (≥1%, ≥2% and ≥5%). When clonal sample was used to determine pyrosequencing error, 4% of reads were found to be incorrect and the most abundant variant was present at a frequency of 1.48%. Use of ShoRAH reduced the sequencing error to 1%, with the most abundant erroneous variant present at frequency of 0.5%. Conclusions While deep sequencing revealed complex genetic heterogeneity of HVR1 in chronic hepatitis C patients, there was no correlation between treatment outcome and any of the analyzed quasispecies parameters. PMID:25016390

Recovery of soil unicellular eukaryotes: an efficiency and activity analysis on the single cell level.

PubMed

Lentendu, Guillaume; Hübschmann, Thomas; Müller, Susann; Dunker, Susanne; Buscot, François; Wilhelm, Christian

2013-12-01

Eukaryotic unicellular organisms are an important part of the soil microbial community, but they are often neglected in soil functional microbial diversity analysis, principally due to the absence of specific investigation methods in the special soil environment. In this study we used a method based on high-density centrifugation to specifically isolate intact algal and yeast cells, with the aim to analyze them with flow cytometry and sort them for further molecular analysis such as deep sequencing. Recovery efficiency was tested at low abundance levels that fit those in natural environments (10(4) to 10(6) cells per g soil). Five algae and five yeast morphospecies isolated from soil were used for the testing. Recovery efficiency was between 1.5 to 43.16% and 2 to 30.2%, respectively, and was dependent on soil type for three of the algae. Control treatments without soil showed that the majority of cells were lost due to the method itself (58% and 55.8% respectively). However, the cell extraction technique did not much compromise cell vitality because a fluorescein di-acetate assay indicated high viability percentages (73.3% and 97.2% of cells, respectively). The low abundant algae and yeast morphospecies recovered from soil were cytometrically analyzed and sorted. Following, their DNA was isolated and amplified using specific primers. The developed workflow enables isolation and enrichment of intact autotrophic and heterotrophic soil unicellular eukaryotes from natural environments for subsequent application of deep sequencing technologies. Copyright © 2013 Elsevier B.V. All rights reserved.

Deep Sequencing Reveals Direct Targets of Gammaherpesvirus-Induced mRNA Decay and Suggests That Multiple Mechanisms Govern Cellular Transcript Escape

PubMed Central

Clyde, Karen; Glaunsinger, Britt A.

2011-01-01

One characteristic of lytic infection with gammaherpesviruses, including Kaposi's sarcoma-associated herpesvirus (KSHV), Epstein-Barr virus (EBV) and murine herpesvirus 68 (MHV68), is the dramatic suppression of cellular gene expression in a process known as host shutoff. The alkaline exonuclease proteins (KSHV SOX, MHV-68 muSOX and EBV BGLF5) have been shown to induce shutoff by destabilizing cellular mRNAs. Here we extend previous analyses of cellular mRNA abundance during lytic infection to characterize the effects of SOX and muSOX, in the absence of other viral genes, utilizing deep sequencing technology (RNA-seq). Consistent with previous observations during lytic infection, the majority of transcripts are downregulated in cells expressing either SOX or muSOX, with muSOX acting as a more potent shutoff factor than SOX. Moreover, most cellular messages fall into the same expression class in both SOX- and muSOX-expressing cells, indicating that both factors target similar pools of mRNAs. More abundant mRNAs are more efficiently downregulated, suggesting a concentration effect in transcript targeting. However, even among highly expressed genes there are mRNAs that escape host shutoff. Further characterization of select escapees reveals multiple mechanisms by which cellular genes can evade downregulation. While some mRNAs are directly refractory to SOX, the steady state levels of others remain unchanged, presumably as a consequence of downstream effects on mRNA biogenesis. Collectively, these studies lay the framework for dissecting the mechanisms underlying the susceptibility of mRNA to destruction during lytic gammaherpesvirus infection. PMID:21573023

Next-generation sequencing: the future of molecular genetics in poultry production and food safety.

PubMed

Diaz-Sanchez, S; Hanning, I; Pendleton, Sean; D'Souza, Doris

2013-02-01

The era of molecular biology and automation of the Sanger chain-terminator sequencing method has led to discovery and advances in diagnostics and biotechnology. The Sanger methodology dominated research for over 2 decades, leading to significant accomplishments and technological improvements in DNA sequencing. Next-generation high-throughput sequencing (HT-NGS) technologies were developed subsequently to overcome the limitations of this first generation technology that include higher speed, less labor, and lowered cost. Various platforms developed include sequencing-by-synthesis 454 Life Sciences, Illumina (Solexa) sequencing, SOLiD sequencing (among others), and the Ion Torrent semiconductor sequencing technologies that use different detection principles. As technology advances, progress made toward third generation sequencing technologies are being reported, which include Nanopore Sequencing and real-time monitoring of PCR activity through fluorescent resonant energy transfer. The advantages of these technologies include scalability, simplicity, with increasing DNA polymerase performance and yields, being less error prone, and even more economically feasible with the eventual goal of obtaining real-time results. These technologies can be directly applied to improve poultry production and enhance food safety. For example, sequence-based (determination of the gut microbial community, genes for metabolic pathways, or presence of plasmids) and function-based (screening for function such as antibiotic resistance, or vitamin production) metagenomic analysis can be carried out. Gut microbialflora/communities of poultry can be sequenced to determine the changes that affect health and disease along with efficacy of methods to control pathogenic growth. Thus, the purpose of this review is to provide an overview of the principles of these current technologies and their potential application to improve poultry production and food safety as well as public health.

Comparative transcriptomics of early dipteran development

PubMed Central

2013-01-01

Background Modern sequencing technologies have massively increased the amount of data available for comparative genomics. Whole-transcriptome shotgun sequencing (RNA-seq) provides a powerful basis for comparative studies. In particular, this approach holds great promise for emerging model species in fields such as evolutionary developmental biology (evo-devo). Results We have sequenced early embryonic transcriptomes of two non-drosophilid dipteran species: the moth midge Clogmia albipunctata, and the scuttle fly Megaselia abdita. Our analysis includes a third, published, transcriptome for the hoverfly Episyrphus balteatus. These emerging models for comparative developmental studies close an important phylogenetic gap between Drosophila melanogaster and other insect model systems. In this paper, we provide a comparative analysis of early embryonic transcriptomes across species, and use our data for a phylogenomic re-evaluation of dipteran phylogenetic relationships. Conclusions We show how comparative transcriptomics can be used to create useful resources for evo-devo, and to investigate phylogenetic relationships. Our results demonstrate that de novo assembly of short (Illumina) reads yields high-quality, high-coverage transcriptomic data sets. We use these data to investigate deep dipteran phylogenetic relationships. Our results, based on a concatenation of 160 orthologous genes, provide support for the traditional view of Clogmia being the sister group of Brachycera (Megaselia, Episyrphus, Drosophila), rather than that of Culicomorpha (which includes mosquitoes and blackflies). PMID:23432914

Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis.

PubMed

Kale, Shiv D; Ayubi, Tariq; Chung, Dawoon; Tubau-Juni, Nuria; Leber, Andrew; Dang, Ha X; Karyala, Saikumar; Hontecillas, Raquel; Lawrence, Christopher B; Cramer, Robert A; Bassaganya-Riera, Josep

2017-12-06

Incidences of invasive pulmonary aspergillosis, an infection caused predominantly by Aspergillus fumigatus, have increased due to the growing number of immunocompromised individuals. While A. fumigatus is reliant upon deficiencies in the host to facilitate invasive disease, the distinct mechanisms that govern the host-pathogen interaction remain enigmatic, particularly in the context of distinct immune modulating therapies. To gain insights into these mechanisms, RNA-Seq technology was utilized to sequence RNA derived from lungs of 2 clinically relevant, but immunologically distinct murine models of IPA on days 2 and 3 post inoculation when infection is established and active disease present. Our findings identify notable differences in host gene expression between the chemotherapeutic and steroid models at the interface of immunity and metabolism. RT-qPCR verified model specific and nonspecific expression of 23 immune-associated genes. Deep sequencing facilitated identification of highly expressed fungal genes. We utilized sequence similarity and gene expression to categorize the A. fumigatus putative in vivo secretome. RT-qPCR suggests model specific gene expression for nine putative fungal secreted proteins. Our analysis identifies contrasting responses by the host and fungus from day 2 to 3 between the two models. These differences may help tailor the identification, development, and deployment of host- and/or fungal-targeted therapeutics.

JPL highlights

NASA Technical Reports Server (NTRS)

1984-01-01

Deep-space exploration; information systems and space technology development; technology applications; energy and energy conversion technology; and earth observational systems and orbital applications are discussed.

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

The application of the high throughput sequencing technology in the transposable elements.

PubMed

Liu, Zhen; Xu, Jian-hong

2015-09-01

High throughput sequencing technology has dramatically improved the efficiency of DNA sequencing, and decreased the costs to a great extent. Meanwhile, this technology usually has advantages of better specificity, higher sensitivity and accuracy. Therefore, it has been applied to the research on genetic variations, transcriptomics and epigenomics. Recently, this technology has been widely employed in the studies of transposable elements and has achieved fruitful results. In this review, we summarize the application of high throughput sequencing technology in the fields of transposable elements, including the estimation of transposon content, preference of target sites and distribution, insertion polymorphism and population frequency, identification of rare copies, transposon horizontal transfers as well as transposon tagging. We also briefly introduce the major common sequencing strategies and algorithms, their advantages and disadvantages, and the corresponding solutions. Finally, we envision the developing trends of high throughput sequencing technology, especially the third generation sequencing technology, and its application in transposon studies in the future, hopefully providing a comprehensive understanding and reference for related scientific researchers.

Single-cell sequencing technologies: current and future.

PubMed

Liang, Jialong; Cai, Wanshi; Sun, Zhongsheng

2014-10-20

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

NSTAR Ion Thrusters and Power Processors

NASA Technical Reports Server (NTRS)

Bond, T. A.; Christensen, J. A.

1999-01-01

The purpose of the NASA Solar Electric Propulsion Technology Applications Readiness (NSTAR) project is to validate ion propulsion technology for use on future NASA deep space missions. This program, which was initiated in September 1995, focused on the development of two sets of flight quality ion thrusters, power processors, and controllers that provided the same performance as engineering model hardware and also met the dynamic and environmental requirements of the Deep Space 1 Project. One of the flight sets was used for primary propulsion for the Deep Space 1 spacecraft which was launched in October 1998.

Community composition of known and uncultured archaeal lineages in anaerobic or anoxic wastewater treatment sludge.

PubMed

Kuroda, Kyohei; Hatamoto, Masashi; Nakahara, Nozomi; Abe, Kenichi; Takahashi, Masanobu; Araki, Nobuo; Yamaguchi, Takashi

2015-04-01

Microbial systems are widely used to treat different types of wastewater from domestic, agricultural, and industrial sources. Community composition is an important factor in determining the successful performance of microbial treatment systems; however, a variety of uncultured and unknown lineages exist in sludge that requires identification and characterization. The present study examined the archaeal community composition in methanogenic, denitrifying, and nitrogen-/phosphate-removing wastewater treatment sludge by Archaea-specific 16S rRNA gene sequencing analysis using Illumina sequencing technology. Phylotypes belonging to Euryarchaeota, including methanogens, were most abundant in all samples except for nitrogen-/phosphate-removing wastewater treatment sludge. High levels of Deep Sea Hydrothermal Vent Group 6 (DHVEG-6), WSA2, Terrestrial Miscellaneous Euryarchaeotal Group, and Miscellaneous Crenarchaeotic Group were also detected. Interestingly, DHVEG-6 was dominant in nitrogen-/phosphate-removing wastewater treatment sludge, indicating that unclear lineages of Archaea still exist in the anaerobic wastewater treatment sludges. These results reveal a previously unknown diversity of Archaea in sludge that can potentially be exploited for the development of more efficient wastewater treatment strategies.

Characterization of H9N2 avian influenza viruses from the Middle East demonstrates heterogeneity at amino acid position 226 in the hemagglutinin and potential for transmission to mammals.

PubMed

Chrzastek, Klaudia; Lee, Dong-Hun; Gharaibeh, Saad; Zsak, Aniko; Kapczynski, Darrell R

2018-05-01

Next-generation sequencing (NGS) technologies are a valuable tool to monitor changes in viral genomes and determine the genetic heterogeneity of viruses. In this study, NGS was applied to clinical poultry samples from Jordan to detect eleven H9N2 low pathogenic avian influenza viruses (LPAIV). All of the viruses tested belonged to Middle East A genetic group of G1 lineage. Deep sequencing demonstrated a high degree of heterogeneity of glutamine and leucine residues at position 226 in the hemagglutinin (HA) gene, which increases specificity to either avian or mammalian-type receptors. Moreover, additional amino acid changes in PB1, PA, M1, M2, and NS1 were identified among the viruses tested. Compared to single gene amplification, application of NGS for surveillance and characterization of H9N2 LPAIV provides a complete genetic profile of emerging isolates and better understanding of the potential of zoonotic transmissions to mammals. Published by Elsevier Inc.

Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system.

PubMed

Yang, Fang; Lei, Yingying; Zhou, Meiling; Yao, Qili; Han, Yichao; Wu, Xiang; Zhong, Wanshun; Zhu, Chenghang; Xu, Weize; Tao, Ran; Chen, Xi; Lin, Da; Rahman, Khaista; Tyagi, Rohit; Habib, Zeshan; Xiao, Shaobo; Wang, Dang; Yu, Yang; Chen, Huanchun; Fu, Zhenfang; Cao, Gang

2018-02-16

Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based 'library vs library' Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome-lysosome fusion. This concept can also be applied to other systems to screen protein-RNA and protein-DNA interactions and delineate signaling landscape in cells.

Biostimulation of metal-resistant microbial consortium to remove zinc from contaminated environments.

PubMed

Mejias Carpio, Isis E; Franco, Diego Castillo; Zanoli Sato, Maria Inês; Sakata, Solange; Pellizari, Vivian H; Seckler Ferreira Filho, Sidney; Frigi Rodrigues, Debora

2016-04-15

Understanding the diversity and metal removal ability of microorganisms associated to contaminated aquatic environments is essential to develop metal remediation technologies in engineered environments. This study investigates through 16S rRNA deep sequencing the composition of a biostimulated microbial consortium obtained from the polluted Tietê River in São Paulo, Brazil. The bacterial diversity of the biostimulated consortium obtained from the contaminated water and sediment was compared to the original sample. The results of the comparative sequencing analyses showed that the biostimulated consortium and the natural environment had γ-Proteobacteria, Firmicutes, and uncultured bacteria as the major classes of microorganisms. The consortium optimum zinc removal capacity, evaluated in batch experiments, was achieved at pH=5 with equilibrium contact time of 120min, and a higher Zn-biomass affinity (KF=1.81) than most pure cultures previously investigated. Analysis of the functional groups found in the consortium demonstrated that amine, carboxyl, hydroxyl, and phosphate groups present in the consortium cells were responsible for zinc uptake. Copyright © 2016 Elsevier B.V. All rights reserved.

Deep Vadose Zone Treatability Test of Soil Desiccation for the Hanford Central Plateau: Final Report

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

Truex, Michael J.; Chronister, Glen B.; Strickland, Christopher E.

Some of the inorganic and radionuclide contaminants in the deep vadose zone at the Hanford Site are at depths where direct exposure pathways are not of concern, but may need to be remediated to protect groundwater. The Department of Energy developed a treatability test program for technologies to address Tc-99 and uranium in the deep vadose zone. These contaminants are mobile in the subsurface environment, have been detected at high concentrations deep in the vadose zone, and at some locations have reached groundwater. The treatability test of desiccation described herein was conducted as an element of the deep vadose zonemore » treatability test program. Desiccation was shown to be a potentially effective vadose zone remediation technology to protect groundwater when used in conjunction with a surface infiltration barrier.« less

Distribution and Diversity of Microbial Eukaryotes in Bathypelagic Waters of the South China Sea.

PubMed

Xu, Dapeng; Jiao, Nianzhi; Ren, Rui; Warren, Alan

2017-05-01

Little is known about the biodiversity of microbial eukaryotes in the South China Sea, especially in waters at bathyal depths. Here, we employed SSU rDNA gene sequencing to reveal the diversity and community structure across depth and distance gradients in the South China Sea. Vertically, the highest alpha diversity was found at 75-m depth. The communities of microbial eukaryotes were clustered into shallow-, middle-, and deep-water groups according to the depth from which they were collected, indicating a depth-related diversity and distribution pattern. Rhizaria sequences dominated the microeukaryote community and occurred in all samples except those from less than 50-m deep, being most abundant near the sea floor where they contributed ca. 64-97% and 40-74% of the total sequences and OTUs recovered, respectively. A large portion of rhizarian OTUs has neither a nearest named neighbor nor a nearest neighbor in the GenBank database which indicated the presence of new phylotypes in the South China Sea. Given their overwhelming abundance and richness, further phylogenetic analysis of rhizarians were performed and three new genetic clusters were revealed containing sequences retrieved from the deep waters of the South China Sea. Our results shed light on the diversity and community structure of microbial eukaryotes in this not yet fully explored area. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

PubMed Central

Vernick, Kenneth D.

2017-01-01

Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions. PMID:28045932

Complete genome sequence of the aerobic, heterotroph Marinithermus hydrothermalis type strain (T1T) from a deep-sea hydrothermal vent chimney

PubMed Central

Copeland, Alex; Gu, Wei; Yasawong, Montri; Lapidus, Alla; Lucas, Susan; Deshpande, Shweta; Pagani, Ioanna; Tapia, Roxanne; Cheng, Jan-Fang; Goodwin, Lynne A.; Pitluck, Sam; Liolios, Konstantinos; Ivanova, Natalia; Mavromatis, Konstantinos; Mikhailova, Natalia; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Pan, Chongle; Brambilla, Evelyne-Marie; Rohde, Manfred; Tindall, Brian J.; Sikorski, Johannes; Göker, Markus; Detter, John C.; Bristow, James; Eisen, Jonathan A.; Markowitz, Victor; Hugenholtz, Philip; Kyrpides, Nikos C.; Klenk, Hans-Peter; Woyke, Tanja

2012-01-01

Marinithermus hydrothermalis Sako et al. 2003 is the type species of the monotypic genus Marinithermus. M. hydrothermalis T1T was the first isolate within the phylum “Thermus-Deinococcus” to exhibit optimal growth under a salinity equivalent to that of sea water and to have an absolute requirement for NaCl for growth. M. hydrothermalis T1T is of interest because it may provide a new insight into the ecological significance of the aerobic, thermophilic decomposers in the circulation of organic compounds in deep-sea hydrothermal vent ecosystems. This is the first completed genome sequence of a member of the genus Marinithermus and the seventh sequence from the family Thermaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,269,167 bp long genome with its 2,251 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project. PMID:22675595

Brain Tumor Segmentation Using Deep Belief Networks and Pathological Knowledge.

PubMed

Zhan, Tianming; Chen, Yi; Hong, Xunning; Lu, Zhenyu; Chen, Yunjie

2017-01-01

In this paper, we propose an automatic brain tumor segmentation method based on Deep Belief Networks (DBNs) and pathological knowledge. The proposed method is targeted against gliomas (both low and high grade) obtained in multi-sequence magnetic resonance images (MRIs). Firstly, a novel deep architecture is proposed to combine the multi-sequences intensities feature extraction with classification to get the classification probabilities of each voxel. Then, graph cut based optimization is executed on the classification probabilities to strengthen the spatial relationships of voxels. At last, pathological knowledge of gliomas is applied to remove some false positives. Our method was validated in the Brain Tumor Segmentation Challenge 2012 and 2013 databases (BRATS 2012, 2013). The performance of segmentation results demonstrates our proposal providing a competitive solution with stateof- the-art methods. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The seismic stratigraphy of Okanagan Lake, British Columbia; a record of rapid deglaciation in a deep 'fiord-lake' basin

NASA Astrophysics Data System (ADS)

Eyles, Nicholas; Mullins, Henry T.; Hine, Albert C.

1991-09-01

This paper presents the first detailed data regarding the newly discovered deep infill of Okanagan Lake. Okanagan Lake (50°00'N, 119°30'W) is 120 km long, ˜ 3-5 km wide and occupies a glacially overdeepened bedrock basin in the southern interior of British Columbia. This basin, and other elongate lakes of the region (e.g. Shuswap, Kootenay, Kalamalka, Canim and Mahood lakes), mark the site of westward flowing ice streams within successive Cordilleran ice sheets. An air gun seismic survey of Okanagan Lake shows that the bedrock floor is nearly 650 m below sea-level, more than 2000 m below the rim of the surrounding plateau. The maximum thickness of Pleistocene sediment in Okanagan Lake basin approaches 800 m. Forty-six seismic reflection traverses and an axial profile show a relatively simple stratigraphy composed of three seismic sequences argued to be no older than the last glacial cycle (< 30 ka). A discontinuous basal unit (sequence I) characterized by large-scale diffractions, and up to 460 m thick, infills the narrow, V-shaped bedrock floor of the basin and is interpreted as a boulder gravel deposited by subglacial meltwaters. Overlying seismic sequence II is composed of two sub-sequences. Sub-sequence IIa is a chaotic to massive facies up to 736 m thick. Lakeshore exposures close to where this unit reaches lake level show deformed and chaotically-bedded glaciolacustrine silts containing gravel lens and large ice-rafted boulders. The surface topography of this sub-sequence is irregular and in general mimics the form of the underlying bedrock as a result of compaction. This sequence passes laterally into stratified facies (sub-sequence IIb) at the northern end of the basin. Seismic sequence II appears to record rapid ice-proximal dumping of glaciolacustrine silt as the Okanagan glacier backwasted upvalley in a deep lake. A thin (60 m max.) laminated seismic sequence (III) drapes the hummocky surface of sequence II and represents postglacial sedimentation from fan-deltas. The extreme thickness of sequences I and II in Okanagan Lake reflects the focussing of large volumes of meltwater and sediment into the basin during deglaciation; pre-existing sediments that pre-date the last glacial cycle appear to have been completely eroded. Glaciological conditions during sedimentation may have been similar to marine-based outlet glaciers calving in deep water in fiord basins. In contrast to marine settings where ice bergs are free to disperse, large volumes of dead ice were trapped within the basin; structural evidence for sedimentation around dead ice blocks has been previously used to argue that the Cordilleran Ice Sheet downwasted in situ. We emphasize in contrast, the trapping of dead ice left behind by rapidly calving lake-based outlet glaciers.

Maryanne Wolf: Balance Technology and Deep Reading to Create Biliterate Children

ERIC Educational Resources Information Center

Richardson, Joan

2014-01-01

Reading scholar Maryanne Wolf believes that every child needs an array of digital skills in their learning repertoire. Her research focuses on how best to introduce technology in terms of reading acquisition so children can develop deep reading skills over time. Educators must focus on a carefully considered trajectory in order to develop a truly…

The Telecommunications and Data Acquisition Report. [Deep Space Network

NASA Technical Reports Server (NTRS)

Posner, E. C. (Editor)

1986-01-01

This publication, one of a series formerly titled The Deep Space Network Progress Report, documents DSN progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported.

Technology Development for High Efficiency Optical Communications

NASA Technical Reports Server (NTRS)

Farr, William H.

2012-01-01

Deep space optical communications is a significantly more challenging operational domain than near Earth space optical communications, primarily due to effects resulting from the vastly increased range between transmitter and receiver. The NASA Game Changing Development Program Deep Space Optical Communications Project is developing four key technologies for the implementation of a high efficiency telecommunications system that will enable greater than 10X the data rate of a state-of-the-art deep space RF system (Ka-band) for similar transceiver mass and power burden on the spacecraft. These technologies are a low mass spacecraft disturbance isolation assembly, a flight qualified photon counting detector array, a high efficiency flight laser amplifier and a high efficiency photon counting detector array for the ground-based receiver.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Deep Space 1 Ion Engine Completed a 3-Year Journey

NASA Technical Reports Server (NTRS)

Sovey, James S.; Patterson, Michael J.; Rawlin, Vincent K.; Hamley, John A.

2001-01-01

A xenon ion engine and power processor system, which was developed by the NASA Glenn Research Center in partnership with the Jet Propulsion Laboratory and Boeing Electron Dynamic Devices, completed nearly 3 years of operation aboard the Deep Space 1 spacecraft. The 2.3-kW ion engine, which provided primary propulsion and two-axis attitude control, thrusted for more than 16,000 hr and consumed more than 70 kg of xenon propellant. The Deep Space 1 spacecraft was launched on October 24, 1998, to validate 12 futuristic technologies, including the ion-propulsion system. After the technology validation process was successfully completed, the Deep Space 1 spacecraft flew by the small asteroid Braille on July 29, 1999. The final objective of this mission was to encounter the active comet Borrelly, which is about 6 miles long. The ion engine was on a thrusting schedule to navigate the Deep Space 1 spacecraft to within 1400 miles of the comet. Since the hydrazine used for spacecraft attitude control was in short supply, the ion engine also provided two-axis attitude control to conserve the hydrazine supply for the Borrelly encounter. The comet encounter took place on September 22, 2001. Dr. Marc Rayman, project manager of Deep Space 1 at the Jet Propulsion Laboratory said, "Deep Space 1 plunged into the heart of the comet Borrelly and has lived to tell every detail of its spinetingling adventure! The images are even better than the impressive images of comet Halley taken by Europe's Giotto spacecraft in 1986." The Deep Space 1 mission, which successfully tested the 12 high-risk, advanced technologies and captured the best images ever taken of a comet, was voluntarily terminated on December 18, 2001. The successful demonstration of the 2-kW-class ion propulsion system technology is now providing mission planners with off-the-shelf flight hardware. Higher power, next generation ion propulsion systems are being developed for large flagship missions, such as outer planet explorers and sample-return missions.

Joint deep shape and appearance learning: application to optic pathway glioma segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Li, Ien; Packer, Roger J.; Avery, Robert A.; Linguraru, Marius George

2017-03-01

Automated tissue characterization is one of the major applications of computer-aided diagnosis systems. Deep learning techniques have recently demonstrated impressive performance for the image patch-based tissue characterization. However, existing patch-based tissue classification techniques struggle to exploit the useful shape information. Local and global shape knowledge such as the regional boundary changes, diameter, and volumetrics can be useful in classifying the tissues especially in scenarios where the appearance signature does not provide significant classification information. In this work, we present a deep neural network-based method for the automated segmentation of the tumors referred to as optic pathway gliomas (OPG) located within the anterior visual pathway (AVP; optic nerve, chiasm or tracts) using joint shape and appearance learning. Voxel intensity values of commonly used MRI sequences are generally not indicative of OPG. To be considered an OPG, current clinical practice dictates that some portion of AVP must demonstrate shape enlargement. The method proposed in this work integrates multiple sequence magnetic resonance image (T1, T2, and FLAIR) along with local boundary changes to train a deep neural network. For training and evaluation purposes, we used a dataset of multiple sequence MRI obtained from 20 subjects (10 controls, 10 NF1+OPG). To our best knowledge, this is the first deep representation learning-based approach designed to merge shape and multi-channel appearance data for the glioma detection. In our experiments, mean misclassification errors of 2:39% and 0:48% were observed respectively for glioma and control patches extracted from the AVP. Moreover, an overall dice similarity coefficient of 0:87+/-0:13 (0:93+/-0:06 for healthy tissue, 0:78+/-0:18 for glioma tissue) demonstrates the potential of the proposed method in the accurate localization and early detection of OPG.

Integrated Atmosphere Resource Recovery and Environmental Monitoring Technology Demonstration for Deep Space Exploration

NASA Technical Reports Server (NTRS)

Perry, Jay L.; Abney, Morgan B.; Knox, James C.; Parrish, Keith J.; Roman, Monserrate C.; Jan, Darrell L.

2012-01-01

Exploring the frontiers of deep space continues to be defined by the technological challenges presented by safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires highly reliable and efficient life support systems that employ robust, proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity's deep space exploration missions begin. The ISS ECLS system Atmosphere Revitalization (AR) subsystem and environmental monitoring (EM) technical architecture aboard the ISS is evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project.. An evolutionary approach is employed by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an ISS-derived subsystem architecture suitable for use for crewed deep space exploration missions. The most promising technical approaches to an ISS-derived subsystem design architecture that incorporates promising core process technology upgrades will be matured through a series of integrated tests and architectural trade studies encompassing expected exploration mission requirements and constraints.

RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproduction-related genes.

PubMed

Lan, DaoLiang; Xiong, XianRong; Wei, YanLi; Xu, Tong; Zhong, JinCheng; Zhi, XiangDong; Wang, Yong; Li, Jian

2014-09-01

RNA-Seq, a high-throughput (HT) sequencing technique, has been used effectively in large-scale transcriptomic studies, and is particularly useful for improving gene structure information and mining of new genes. In this study, RNA-Seq HT technology was employed to analyze the transcriptome of yak ovary. After Illumina-Solexa deep sequencing, 26826516 clean reads with a total of 4828772880 bp were obtained from the ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome and 3734 of these genes were involved in alternative splicing. Gene structure refinement analysis showed that 7340 genes that were annotated in the yak genome could be extended at the 5' or 3' ends based on the alignments been the transcripts and the genome sequence. Novel transcript prediction analysis identified 6321 new transcripts with lengths ranging from 180 to 14884 bp, and 2267 of them were predicted to code proteins. BLAST analysis of the new transcripts showed that 1200?4933 mapped to the non-redundant (nr), nucleotide (nt) and/or SwissProt sequence databases. Comparative statistical analysis of the new mapped transcripts showed that the majority of them were similar to genes in Bos taurus (41.4%), Bos grunniens mutus (33.0%), Ovis aries (6.3%), Homo sapiens (2.8%), Mus musculus (1.6%) and other species. Functional analysis showed that these expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes pathways. GO analysis of the new transcripts found that the largest proportion of them was associated with reproduction. The results of this study will provide a basis for describing the normal transcriptome map of yak ovary and for future studies on yak breeding performance. Moreover, the results confirmed that RNA-Seq HT technology is highly advantageous in improving gene structure information and mining of new genes, as well as in providing valuable data to expand the yak genome information.

Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

PubMed

Williams, Philip H; Eyles, Rod; Weiller, Georg

2012-01-01

MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments.

PubMed

Hackenberg, Michael; Sturm, Martin; Langenberger, David; Falcón-Pérez, Juan Manuel; Aransay, Ana M

2009-07-01

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/.

Monitoring technologies for ocean disposal of radioactive waste

NASA Astrophysics Data System (ADS)

Triplett, M. B.; Solomon, K. A.; Bishop, C. B.; Tyce, R. C.

1982-01-01

The feasibility of using carefully selected subseabed locations to permanently isolate high level radioactive wastes at ocean depths greater than 4000 meters is discussed. Disposal at several candidate subseabed areas is being studied because of the long term geologic stability of the sediments, remoteness from human activity, and lack of useful natural resources. While the deep sea environment is remote, it also poses some significant challenges for the technology required to survey and monitor these sites, to identify and pinpoint container leakage should it occur, and to provide the environmental information and data base essential to determining the probable impacts of any such occurrence. Objectives and technical approaches to aid in the selective development of advanced technologies for the future monitoring of nuclear low level and high level waste disposal in the deep seabed are presented. Detailed recommendations for measurement and sampling technology development needed for deep seabed nuclear waste monitoring are also presented.

Study of alternative probe technologies

NASA Technical Reports Server (NTRS)

1977-01-01

A number of implied technologies for a deep probe mission was examined; i.e., one that would provide the capability to scientifically examine planetary atmospheres at the 1000 bar level. Conditions imposed by current Jupiter, Saturn, and Uranus atmospheric models were considered. The major thrust of the measurements was to determine lower atmosphere composition, even to trace constituents of one part per billion. Two types of instruments having the necessary accuracy to meet the science objectives were considered and integrated into a deep probe configuration. One deep probe option that resulted was identified as a Minimum Technology Development approach. The significant feature of this option is that only three technology developments are required to enable the mission, i.e., (1) science instrument development, (2) advanced data processing, and (3) external high pressure/thermal insulation. It is concluded that a probe designed for a Jupiter mission could, with minor changes, be used for a Saturn or Uranus mission.

Distinguishing friends, foes, and freeloaders in giant genomes.

PubMed

Bennetzen, Jeffrey L; Park, Minkyu

2018-04-01

Most annotations of large eukaryotic genomes initially find transposable elements (TEs) and other repeats, then mask them so that subsequent efforts can be concentrated on the annotation and study of non-TE genes. However, TEs often contribute to host biology, and their community biologies are of intrinsic interest. This review discusses the challenges, rationale and technologies for comprehensive TE annotation in the commonly giant genomes of animals and plants. Complete discovery of the TEs in a fully sequenced genome is laborious, but feasible, with current strategies in the hands of a careful researcher. These deep TE studies have begun to provide important perspectives on how genomes evolve and the degree to which genome changes do and do not affect eukaryotic biology. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multi-disciplinary methods to define RNA-protein interactions and regulatory networks.

PubMed

Ascano, Manuel; Gerstberger, Stefanie; Tuschl, Thomas

2013-02-01

The advent of high-throughput technologies including deep-sequencing and protein mass spectrometry is facilitating the acquisition of large and precise data sets toward the definition of post-transcriptional regulatory networks. While early studies that investigated specific RNA-protein interactions in isolation laid the foundation for our understanding of the existence of molecular machines to assemble and process RNAs, there is a more recent appreciation of the importance of individual RNA-protein interactions that contribute to post-transcriptional gene regulation. The multitude of RNA-binding proteins (RBPs) and their many RNA targets has only been captured experimentally in recent times. In this review, we will examine current multidisciplinary approaches toward elucidating RNA-protein networks and their regulation. Copyright © 2013 Elsevier Ltd. All rights reserved.

An introduction to deep learning on biological sequence data: examples and solutions.

PubMed

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. 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

The deep space network

NASA Technical Reports Server (NTRS)

1977-01-01

Presented is Deep Space Network (DSN) progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations.

The deep space network

NASA Technical Reports Server (NTRS)

1975-01-01

Summaries are given of Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

Draft Genome Sequence of Thermus scotoductus Strain K1, Isolated from a Geothermal Spring in Karvachar, Nagorno Karabakh

PubMed Central

Saghatelyan, Ani; Poghosyan, Lianna

2015-01-01

The 2,379,636-bp draft genome sequence of Thermus scotoductus strain K1, isolated from geothermal spring outlet located in the Karvachar region in Nagorno Karabakh is presented. Strain K1 shares about 80% genome sequence similarity with T. scotoductus strain SA-01, recovered from a deep gold mine in South Africa. PMID:26564055

Transcriptomics of In Vitro Immune-Stimulated Hemocytes from the Manila Clam Ruditapes philippinarum Using High-Throughput Sequencing

PubMed Central

Moreira, Rebeca; Balseiro, Pablo; Planas, Josep V.; Fuste, Berta; Beltran, Sergi; Novoa, Beatriz; Figueras, Antonio

2012-01-01

Background The Manila clam (Ruditapes philippinarum) is a worldwide cultured bivalve species with important commercial value. Diseases affecting this species can result in large economic losses. Because knowledge of the molecular mechanisms of the immune response in bivalves, especially clams, is scarce and fragmentary, we sequenced RNA from immune-stimulated R. philippinarum hemocytes by 454-pyrosequencing to identify genes involved in their immune defense against infectious diseases. Methodology and Principal Findings High-throughput deep sequencing of R. philippinarum using 454 pyrosequencing technology yielded 974,976 high-quality reads with an average read length of 250 bp. The reads were assembled into 51,265 contigs and the 44.7% of the translated nucleotide sequences into protein were annotated successfully. The 35 most frequently found contigs included a large number of immune-related genes, and a more detailed analysis showed the presence of putative members of several immune pathways and processes like the apoptosis, the toll like signaling pathway and the complement cascade. We have found sequences from molecules never described in bivalves before, especially in the complement pathway where almost all the components are present. Conclusions This study represents the first transcriptome analysis using 454-pyrosequencing conducted on R. philippinarum focused on its immune system. Our results will provide a rich source of data to discover and identify new genes, which will serve as a basis for microarray construction and the study of gene expression as well as for the identification of genetic markers. The discovery of new immune sequences was very productive and resulted in a large variety of contigs that may play a role in the defense mechanisms of Ruditapes philippinarum. PMID:22536348

Applications and Case Studies of the Next-Generation Sequencing Technologies in Food, Nutrition and Agriculture.

USDA-ARS?s Scientific Manuscript database

Next-generation sequencing technologies are able to produce high-throughput short sequence reads in a cost-effective fashion. The emergence of these technologies has not only facilitated genome sequencing but also changed the landscape of life sciences. Here I survey their major applications ranging...

Recent Applications of DNA Sequencing Technologies in Food, Nutrition and Agriculture

USDA-ARS?s Scientific Manuscript database

Next-generation DNA sequencing technologies are able to produce millions of short sequence reads in a high-throughput, cost-effective fashion. The emergence of these technologies has not only facilitated genome sequencing but also changed the landscape of life sciences. This review surveys their rec...

[Sequencing technology in gene diagnosis and its application].

PubMed

Yibin, Guo

2014-11-01

The study of gene mutation is one of the hot topics in the field of life science nowadays, and the related detection methods and diagnostic technology have been developed rapidly. Sequencing technology plays an indispensable role in the definite diagnosis and classification of genetic diseases. In this review, we summarize the research progress in sequencing technology, evaluate the advantages and disadvantages of 1(st) ~3(rd) generation of sequencing technology, and describe its application in gene diagnosis. Also we made forecasts and prospects on its development trend.

The deep space network

NASA Technical Reports Server (NTRS)

1974-01-01

The progress is reported of Deep Space Network (DSN) research in the following areas: (1) flight project support, (2) spacecraft/ground communications, (3) station control and operations technology, (4) network control and processing, and (5) deep space stations. A description of the DSN functions and facilities is included.

Arthropod phylogenetics in light of three novel millipede (myriapoda: diplopoda) mitochondrial genomes with comments on the appropriateness of mitochondrial genome sequence data for inferring deep level relationships.

PubMed

Brewer, Michael S; Swafford, Lynn; Spruill, Chad L; Bond, Jason E

2013-01-01

Arthropods are the most diverse group of eukaryotic organisms, but their phylogenetic relationships are poorly understood. Herein, we describe three mitochondrial genomes representing orders of millipedes for which complete genomes had not been characterized. Newly sequenced genomes are combined with existing data to characterize the protein coding regions of myriapods and to attempt to reconstruct the evolutionary relationships within the Myriapoda and Arthropoda. The newly sequenced genomes are similar to previously characterized millipede sequences in terms of synteny and length. Unique translocations occurred within the newly sequenced taxa, including one half of the Appalachioria falcifera genome, which is inverted with respect to other millipede genomes. Across myriapods, amino acid conservation levels are highly dependent on the gene region. Additionally, individual loci varied in the level of amino acid conservation. Overall, most gene regions showed low levels of conservation at many sites. Attempts to reconstruct the evolutionary relationships suffered from questionable relationships and low support values. Analyses of phylogenetic informativeness show the lack of signal deep in the trees (i.e., genes evolve too quickly). As a result, the myriapod tree resembles previously published results but lacks convincing support, and, within the arthropod tree, well established groups were recovered as polyphyletic. The novel genome sequences described herein provide useful genomic information concerning millipede groups that had not been investigated. Taken together with existing sequences, the variety of compositions and evolution of myriapod mitochondrial genomes are shown to be more complex than previously thought. Unfortunately, the use of mitochondrial protein-coding regions in deep arthropod phylogenetics appears problematic, a result consistent with previously published studies. Lack of phylogenetic signal renders the resulting tree topologies as suspect. As such, these data are likely inappropriate for investigating such ancient relationships.

Transcriptome Analysis in Venom Gland of the Predatory Giant Ant Dinoponera quadriceps: Insights into the Polypeptide Toxin Arsenal of Hymenopterans

PubMed Central

Chong, Cheong-Meng; Leung, Siu Wai; Prieto-da-Silva, Álvaro R. B.; Havt, Alexandre; Quinet, Yves P.; Martins, Alice M. C.; Lee, Simon M. Y.; Rádis-Baptista, Gandhi

2014-01-01

Background Dinoponera quadriceps is a predatory giant ant that inhabits the Neotropical region and subdues its prey (insects) with stings that deliver a toxic cocktail of molecules. Human accidents occasionally occur and cause local pain and systemic symptoms. A comprehensive study of the D. quadriceps venom gland transcriptome is required to advance our knowledge about the toxin repertoire of the giant ant venom and to understand the physiopathological basis of Hymenoptera envenomation. Results We conducted a transcriptome analysis of a cDNA library from the D. quadriceps venom gland with Sanger sequencing in combination with whole-transcriptome shotgun deep sequencing. From the cDNA library, a total of 420 independent clones were analyzed. Although the proportion of dinoponeratoxin isoform precursors was high, the first giant ant venom inhibitor cysteine-knot (ICK) toxin was found. The deep next generation sequencing yielded a total of 2,514,767 raw reads that were assembled into 18,546 contigs. A BLAST search of the assembled contigs against non-redundant and Swiss-Prot databases showed that 6,463 contigs corresponded to BLASTx hits and indicated an interesting diversity of transcripts related to venom gene expression. The majority of these venom-related sequences code for a major polypeptide core, which comprises venom allergens, lethal-like proteins and esterases, and a minor peptide framework composed of inter-specific structurally conserved cysteine-rich toxins. Both the cDNA library and deep sequencing yielded large proportions of contigs that showed no similarities with known sequences. Conclusions To our knowledge, this is the first report of the venom gland transcriptome of the New World giant ant D. quadriceps. The glandular venom system was dissected, and the toxin arsenal was revealed; this process brought to light novel sequences that included an ICK-folded toxins, allergen proteins, esterases (phospholipases and carboxylesterases), and lethal-like toxins. These findings contribute to the understanding of the ecology, behavior and venomics of hymenopterans. PMID:24498135

Applications of nanotechnology, next generation sequencing and microarrays in biomedical research.

PubMed

Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

2013-07-01

Next-generation sequencing technologies, microarrays and advances in bio nanotechnology have had an enormous impact on research within a short time frame. This impact appears certain to increase further as many biomedical institutions are now acquiring these prevailing new technologies. Beyond conventional sampling of genome content, wide-ranging applications are rapidly evolving for next-generation sequencing, microarrays and nanotechnology. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted re sequencing and discovery of transcription factor binding sites, noncoding RNA expression profiling and molecular diagnostics. This paper thus discusses current applications of nanotechnology, next-generation sequencing technologies and microarrays in biomedical research and highlights the transforming potential these technologies offer.

Complete genome sequence of the Antarctic Halorubrum lacusprofundi type strain ACAM 34

DOE PAGES

Anderson, Iain J.; DasSarma, Priya; Lucas, Susan; ...

2016-09-10

Halorubrum lacusprofundi is an extreme halophile within the archaeal phylum Euryarchaeota. The type strain ACAM 34 was isolated from Deep Lake, Antarctica. H. lacusprofundi is of phylogenetic interest because it is distantly related to the haloarchaea that have previously been sequenced. It is also of interest because of its psychrotolerance. We report here the complete genome sequence of H. lacusprofundi type strain ACAM 34 and its annotation. In conclusion, this genome is part of a 2006 Joint Genome Institute Community Sequencing Program project to sequence genomes of diverse Archaea.

Complete genome sequence of the Antarctic Halorubrum lacusprofundi type strain ACAM 34

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

Anderson, Iain J.; DasSarma, Priya; Lucas, Susan

Halorubrum lacusprofundi is an extreme halophile within the archaeal phylum Euryarchaeota. The type strain ACAM 34 was isolated from Deep Lake, Antarctica. H. lacusprofundi is of phylogenetic interest because it is distantly related to the haloarchaea that have previously been sequenced. It is also of interest because of its psychrotolerance. We report here the complete genome sequence of H. lacusprofundi type strain ACAM 34 and its annotation. In conclusion, this genome is part of a 2006 Joint Genome Institute Community Sequencing Program project to sequence genomes of diverse Archaea.

MRI markers of small vessel disease in lobar and deep hemispheric intracerebral hemorrhage

PubMed Central

Smith, Eric E.; Nandigam, Kaveer R.N.; Chen, Yu-Wei; Jeng, Jed; Salat, David; Halpin, Amy; Frosch, Matthew; Wendell, Lauren; Fazen, Louis; Rosand, Jonathan; Viswanathan, Anand; Greenberg, Steven M.

2014-01-01

Background MRI evidence of small vessel disease is common in intracerebral hemorrhage (ICH). We hypothesized that ICH caused by cerebral amyloid angiopathy (CAA) or hypertensive vasculopathy would have different distributions of MRI T2 white matter hyperintensity (WMH) and microbleeds (MB). Methods Data were analyzed from 133 consecutive patients with primary supratentorial ICH and adequate MRI sequences. CAA was diagnosed using the Boston criteria. WMH segmentation was performed using a validated semi-automated method. WMH and MB were compared according to site of symptomatic hematoma origin (lobar vs. deep) or by pattern of hemorrhages, including both hematomas and MB, on MRI GRE sequence (grouped as lobar only--probable CAA, lobar only--possible CAA, deep hemispheric only, or mixed lobar and deep hemorrhages). Results Lobar and deep hemispheric hematoma patients had similar median nWMH volumes (19.5 cm vs. 19.9 cm3, p=0.74) and prevalence of ≥1 MB (54% vs. 52%, p=0.99). The supratentorial WMH distribution was similar according to hemorrhage location category, however the prevalence of brainstem T2 hyperintensity was lower in lobar hematoma vs. deep hematoma (54% vs. 70%, p=0.004). Mixed ICH was common (23%). Mixed ICH patients had large nWMH volumes and a posterior distribution of cortical hemorrhages similar to that seen in CAA. Conclusions WMH distribution is largely similar between CAA-related and non-CAA-related ICH. Mixed lobar and deep hemorrhages are seen on MRI GRE in up to one quarter of patients; in these patients both hypertension and CAA may be contributing to the burden of WMH. PMID:20689084

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PubMed

Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

2017-01-01

Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have much better quality than template-based models especially for membrane proteins. The 3D models built from our contact prediction have TMscore>0.5 for 208 of the 398 membrane proteins, while those from homology modeling have TMscore>0.5 for only 10 of them. Further, even if trained mostly by soluble proteins, our deep learning method works very well on membrane proteins. In the recent blind CAMEO benchmark, our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0.3L-2.3L effective sequence homologs, including one β protein of 182 residues, one α+β protein of 125 residues, one α protein of 140 residues, one α protein of 217 residues, one α/β of 260 residues and one α protein of 462 residues. Our method also achieved the highest F1 score on free-modeling targets in the latest CASP (Critical Assessment of Structure Prediction), although it was not fully implemented back then. http://raptorx.uchicago.edu/ContactMap/.

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

PubMed Central

Li, Zhen; Zhang, Renyu

2017-01-01

Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have much better quality than template-based models especially for membrane proteins. The 3D models built from our contact prediction have TMscore>0.5 for 208 of the 398 membrane proteins, while those from homology modeling have TMscore>0.5 for only 10 of them. Further, even if trained mostly by soluble proteins, our deep learning method works very well on membrane proteins. In the recent blind CAMEO benchmark, our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0.3L-2.3L effective sequence homologs, including one β protein of 182 residues, one α+β protein of 125 residues, one α protein of 140 residues, one α protein of 217 residues, one α/β of 260 residues and one α protein of 462 residues. Our method also achieved the highest F1 score on free-modeling targets in the latest CASP (Critical Assessment of Structure Prediction), although it was not fully implemented back then. Availability http://raptorx.uchicago.edu/ContactMap/ PMID:28056090

Deep Bore Storage of Nuclear Waste Using MMW (Millimeter Wave) Technology. Full Project Final Report

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

Oglesby, Kenneth D.; Woskov, Paul; Einstein, Herbert

This DOE Nuclear STTR project DE-SC001238 investigated the use of MMW directed energy to form rock melt and steel plugs in deep wellbores to further isolate highly radioactive nuclear waste in ultra-deep basement rocks for long term storage. This current project builds upon a prior DOE project, DE-EE0005504, which developed the basic low power, low 28 GHz frequency waveguide setup, process and instruments. This research adds to our understanding of using MMW power to melt and vaporize rocks and steel/ metals and laid plans for future higher power field prototype testing. This technology also has potential for deep well drillingmore » for nuclear storage, geothermal and oil and gas industries. It also has the potential for simultaneously sealing and securing the wellbore with a thick rock melt liner as the wellbore is drilled, called 'mono-bore drilling'. This allows for higher levels of safety and protection of the environment during deep drilling operations while providing vast cost savings. The larger purpose of this project was to find answers to key questions in developing MMW technology for its many subsurface applications.« less

Application of acoustic surface wave filter-beam lead component technology to deep space multimission hardware design

NASA Technical Reports Server (NTRS)

Kermode, A. W.; Boreham, J. F.

1974-01-01

This paper discusses the utilization of acoustic surface wave filters, beam lead components, and thin film metallized ceramic substrate technology as applied to the design of deep space, long-life, multimission transponder. The specific design to be presented is for a second mixer local oscillator module, operating at frequencies as high as 249 MHz.

Assessing Oil Spill Impacts to Cold-Water Corals of the Deep Gulf of Mexico

NASA Astrophysics Data System (ADS)

DeLeo, D. M.; Lengyel, S. D.; Cordes, E. E.

2016-02-01

The Deepwater Horizon (DWH) disaster and subsequent cleanup efforts resulted in the release of an unprecedented amount of oil and chemical dispersants in the deep waters of the Gulf of Mexico (GoM). Over the years, numerous detrimental effects have been documented including impacts to cold-water coral ecosystems. Assessing and quantifying these effects is crucial to understanding the long-term consequences to affected coral populations as well as their resilience. We conducted live exposure experiments to investigate the toxicity of oil and dispersants on two deep-sea corals, Callogorgia delta and Paramuricea type B3. For both species, the treatments containing dispersants had a more pronounced effect than oil treatments alone. In addition, RNA from unexposed and DWH spill-impacted Paramuricea biscaya was extracted and sequenced using Illumina technology. A de novo reference transcriptome was produced and used to explore stress-induced variations in gene expression. Current findings show overexpression of genes coding for Cytochrome p450 (CYP1A1), Tumor necrosis factor receptor-associated factors (TRAFs), Peroxidasin and additional genes involved in innate immunity and apoptotic pathways. CYP1A1 is involved in the metabolism of xenobiotics and has been previously used as a diagnostic tool for aquatic pollution. TRAFs are responsible for regulating pathways involved in immune and inflammatory responses and were likewise overexpressed in thermally stressed shallow-water corals. Ribosomal proteins were also significantly underexpressed. These genes among others found in our expression data serve as useful biomarker candidates for assessing and monitoring future spill impacts as resource extraction continues in the deep waters of the GoM. Our results also provide insights into the responses of deep-sea corals to toxin exposure, implications of applying dispersants to oil spills and a novel reference assembly for a relatively under-studied group of cold-water corals.

The deep space network

NASA Technical Reports Server (NTRS)

1977-01-01

A Deep Space Network progress report is presented dealing with in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

Draft Genome Sequence of Aldehyde-Degrading Strain Halomonas axialensis ACH-L-8

PubMed Central

Ye, Jun; Ren, Chong; Shan, Xiexie

2016-01-01

Halomonas axialensis ACH-L-8, a deep-sea strain isolated from the South China Sea, has the ability to degrade aldehydes. Here, we present an annotated draft genome sequence of this species, which could provide fundamental molecular information on the aldehydes-degrading mechanism. PMID:27081145

Microbial diversity in methane hydrate-bearing deep marine sediments core preserved in the original pressure.

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Hata, T.; Nishida, H.

2017-12-01

In normal coring of deep marine sediments, the sampled cores are exposed to the pressure of the atmosphere, which results in dissociation of gas-hydrates and might change microbial diversity. In this study, we analyzed microbial composition in methane hydrate-bearing sediment core sampled and preserved by Hybrid-PCS (Pressure Coring System). We sliced core into three layers; (i) outside layer, which were most affected by drilling fluids, (ii) middle layer, and (iii) inner layer, which were expected to be most preserved as the original state. From each layer, we directly extracted DNA, and amplified V3-V4 region of 16S rRNA gene. We determined at least 5000 of nucleotide sequences of the partial 16S rDNA from each layer by Miseq (Illumina). In the all layers, facultative anaerobes, which can grow with or without oxygen because they can metabolize energy aerobically or anaerobically, were detected as majority. However, the genera which are often detected anaerobic environment is abundant in the inner layer compared to the outside layer, indicating that condition of drilling and preservation affect the microbial composition in the deep marine sediment core. This study was conducted as a part of the activity of the Research Consortium for Methane Hydrate Resources in Japan [MH21 consortium], and supported by JOGMEC (Japan Oil, Gas and Metals National Corporation). The sample was provided by AIST (National Institute of Advanced Industrial Science and Technology).

Use of the Minion nanopore sequencer for rapid sequencing of avian influenza virus isolates

USDA-ARS?s Scientific Manuscript database

A relatively new sequencing technology, the MinION nanopore sequencer, provides a platform that is smaller, faster, and cheaper than existing Next Generation Sequence (NGS) technologies. The MinION sequences of individual strands of DNA and can produce millions of sequencing reads. The cost of the s...

How to study deep roots—and why it matters

PubMed Central

Maeght, Jean-Luc; Rewald, Boris; Pierret, Alain

2013-01-01

The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of “deep roots” is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydraulic lift (HL). Subterranean fauna and microbial communities are highly influenced by resources provided in the deep rhizosphere and deep roots can influence soil pedogenesis and carbon storage.Despite recent technological advances, the study of deep roots and their rhizosphere remains inherently time-consuming, technically demanding and costly, which explains why deep roots have yet to be given the attention they deserve. While state-of-the-art technologies are promising for laboratory studies involving relatively small soil volumes, they remain of limited use for the in situ observation of deep roots. Thus, basic techniques such as destructive sampling or observations at transparent interfaces with the soil (e.g., root windows) which have been known and used for decades to observe roots near the soil surface, must be adapted to the specific requirements of deep root observation. In this review, we successively address major physical, biogeochemical and ecological functions of deep roots to emphasize the significance of deep roots and to illustrate the yet limited knowledge. In the second part we describe the main methodological options to observe and measure deep roots, providing researchers interested in the field of deep root/rhizosphere studies with a comprehensive overview. Addressed methodologies are: excavations, trenches and soil coring approaches, minirhizotrons (MR), access shafts, caves and mines, and indirect approaches such as tracer-based techniques. PMID:23964281

What Advances Are Being Made in DNA Sequencing?

MedlinePlus

... to identify genetic variations; both methods rely on new technologies that allow rapid sequencing of large amounts of ... describes the different sequencing technologies and what the new technologies have meant for the study of the genetic ...

Optical Communications in Support of Science from the Moon, Mars, and Beyond

NASA Technical Reports Server (NTRS)

Edwards, Bernard L.

2005-01-01

Optical communications can provide high speed communications throughout the solar system. Enable new science missions and human exploration. The technology suitable for near-earth optical communications, including communications to and from the Moon, is different than for deep space optical. NASA could leverage DoD investments for near-earth applications, including the moon. NASA will have to develop its own technology for deep space. The Mars laser communication demonstration is a pathfinder. NASA,s science mission directorate, under the leadership of Dr. Barry Geldzahler, is developing a roadmap for the development of deep space optical communications.

NASA light emitting diode medical applications from deep space to deep sea

NASA Astrophysics Data System (ADS)

Whelan, Harry T.; Buchmann, Ellen V.; Whelan, Noel T.; Turner, Scott G.; Cevenini, Vita; Stinson, Helen; Ignatius, Ron; Martin, Todd; Cwiklinski, Joan; Meyer, Glenn A.; Hodgson, Brian; Gould, Lisa; Kane, Mary; Chen, Gina; Caviness, James

2001-02-01

This work is supported and managed through the NASA Marshall Space Flight Center-SBIR Program. LED-technology developed for NASA plant growth experiments in space shows promise for delivering light deep into tissues of the body to promote wound healing and human tissue growth. We present the results of LED-treatment of cells grown in culture and the effects of LEDs on patients' chronic and acute wounds. LED-technology is also biologically optimal for photodynamic therapy of cancer and we discuss our successes using LEDs in conjunction with light-activated chemotherapeutic drugs. .

Suboxic deep seawater in the late Paleoproterozoic: Evidence from hematitic chert and iron formation related to seafloor-hydrothermal sulfide deposits, central Arizona, USA

USGS Publications Warehouse

Slack, J.F.; Grenne, Tor; Bekker, A.; Rouxel, O.J.; Lindberg, P.A.

2007-01-01

A current model for the evolution of Proterozoic deep seawater composition involves a change from anoxic sulfide-free to sulfidic conditions 1.8??Ga. In an earlier model the deep ocean became oxic at that time. Both models are based on the secular distribution of banded iron formation (BIF) in shallow marine sequences. We here present a new model based on rare earth elements, especially redox-sensitive Ce, in hydrothermal silica-iron oxide sediments from deeper-water, open-marine settings related to volcanogenic massive sulfide (VMS) deposits. In contrast to Archean, Paleozoic, and modern hydrothermal iron oxide sediments, 1.74 to 1.71??Ga hematitic chert (jasper) and iron formation in central Arizona, USA, show moderate positive to small negative Ce anomalies, suggesting that the redox state of the deep ocean then was at a transitional, suboxic state with low concentrations of dissolved O2 but no H2S. The presence of jasper and/or iron formation related to VMS deposits in other volcanosedimentary sequences ca. 1.79-1.69??Ga, 1.40??Ga, and 1.24??Ga also reflects oxygenated and not sulfidic deep ocean waters during these time periods. Suboxic conditions in the deep ocean are consistent with the lack of shallow-marine BIF ??? 1.8 to 0.8??Ga, and likely limited nutrient concentrations in seawater and, consequently, may have constrained biological evolution. ?? 2006 Elsevier B.V. All rights reserved.

Towards testing quantum physics in deep space

NASA Astrophysics Data System (ADS)

Kaltenbaek, Rainer

2016-07-01

MAQRO is a proposal for a medium-sized space mission to use the unique environment of deep space in combination with novel developments in space technology and quantum technology to test the foundations of physics. The goal is to perform matter-wave interferometry with dielectric particles of up to 10^{11} atomic mass units and testing for deviations from the predictions of quantum theory. Novel techniques from quantum optomechanics with optically trapped particles are to be used for preparing the test particles for these experiments. The core elements of the instrument are placed outside the spacecraft and insulated from the hot spacecraft via multiple thermal shields allowing to achieve cryogenic temperatures via passive cooling and ultra-high vacuum levels by venting to deep space. In combination with low force-noise microthrusters and inertial sensors, this allows realizing an environment well suited for long coherence times of macroscopic quantum superpositions and long integration times. Since the original proposal in 2010, significant progress has been made in terms of technology development and in refining the instrument design. Based on these new developments, we submitted/will submit updated versions of the MAQRO proposal in 2015 and 2016 in response to Cosmic-Vision calls of ESA for a medium-sized mission. A central goal has been to address and overcome potentially critical issues regarding the readiness of core technologies and to provide realistic concepts for further technology development. We present the progress on the road towards realizing this ground-breaking mission harnessing deep space in novel ways for testing the foundations of physics, a technology pathfinder for macroscopic quantum technology and quantum optomechanics in space.

Understanding social collaboration between actors and technology in an automated and digitised deep mining environment.

PubMed

Sanda, M-A; Johansson, J; Johansson, B; Abrahamsson, L

2011-10-01

The purpose of this article is to develop knowledge and learning on the best way to automate organisational activities in deep mines that could lead to the creation of harmony between the human, technical and the social system, towards increased productivity. The findings showed that though the introduction of high-level technological tools in the work environment disrupted the social relations developed over time amongst the employees in most situations, the technological tools themselves became substitute social collaborative partners to the employees. It is concluded that, in developing a digitised mining production system, knowledge of the social collaboration between the humans (miners) and the technology they use for their work must be developed. By implication, knowledge of the human's subject-oriented and object-oriented activities should be considered as an important integral resource for developing a better technological, organisational and human interactive subsystem when designing the intelligent automation and digitisation systems for deep mines. STATEMENT OF RELEVANCE: This study focused on understanding the social collaboration between humans and the technologies they use to work in underground mines. The learning provides an added knowledge in designing technologies and work organisations that could better enhance the human-technology interactive and collaborative system in the automation and digitisation of underground mines.

High-Throughput Sequence Analysis of Turbot (Scophthalmus maximus) Transcriptome Using 454-Pyrosequencing for the Discovery of Antiviral Immune Genes

PubMed Central

Pereiro, Patricia; Balseiro, Pablo; Romero, Alejandro; Dios, Sonia; Forn-Cuni, Gabriel; Fuste, Berta; Planas, Josep V.; Beltran, Sergi; Novoa, Beatriz; Figueras, Antonio

2012-01-01

Background Turbot (Scophthalmus maximus L.) is an important aquacultural resource both in Europe and Asia. However, there is little information on gene sequences available in public databases. Currently, one of the main problems affecting the culture of this flatfish is mortality due to several pathogens, especially viral diseases which are not treatable. In order to identify new genes involved in immune defense, we conducted 454-pyrosequencing of the turbot transcriptome after different immune stimulations. Methodology/Principal Findings Turbot were injected with viral stimuli to increase the expression level of immune-related genes. High-throughput deep sequencing using 454-pyrosequencing technology yielded 915,256 high-quality reads. These sequences were assembled into 55,404 contigs that were subjected to annotation steps. Intriguingly, 55.16% of the deduced protein was not significantly similar to any sequences in the databases used for the annotation and only 0.85% of the BLASTx top-hits matched S. maximus protein sequences. This relatively low level of annotation is possibly due to the limited information for this specie and other flatfish in the database. These results suggest the identification of a large number of new genes in turbot and in fish in general. A more detailed analysis showed the presence of putative members of several innate and specific immune pathways. Conclusions/Significance To our knowledge, this study is the first transcriptome analysis using 454-pyrosequencing for turbot. Previously, there were only 12,471 EST and less of 1,500 nucleotide sequences for S. maximus in NCBI database. Our results provide a rich source of data (55,404 contigs and 181,845 singletons) for discovering and identifying new genes, which will serve as a basis for microarray construction, gene expression characterization and for identification of genetic markers to be used in several applications. Immune stimulation in turbot was very effective, obtaining an enormous variety of sequences belonging to genes involved in the defense mechanisms. PMID:22629298

The future scalability of pH-based genome sequencers: A theoretical perspective

NASA Astrophysics Data System (ADS)

Go, Jonghyun; Alam, Muhammad A.

2013-10-01

Sequencing of human genome is an essential prerequisite for personalized medicine and early prognosis of various genetic diseases. The state-of-art, high-throughput genome sequencing technologies provide improved sequencing; however, their reliance on relatively expensive optical detection schemes has prevented wide-spread adoption of the technology in routine care. In contrast, the recently announced pH-based electronic genome sequencers achieve fast sequencing at low cost because of the compatibility with the current microelectronics technology. While the progress in technology development has been rapid, the physics of the sequencing chips and the potential for future scaling (and therefore, cost reduction) remain unexplored. In this article, we develop a theoretical framework and a scaling theory to explain the principle of operation of the pH-based sequencing chips and use the framework to explore various perceived scaling limits of the technology related to signal to noise ratio, well-to-well crosstalk, and sequencing accuracy. We also address several limitations inherent to the key steps of pH-based genome sequencers, which are widely shared by many other sequencing platforms in the market but remained unexplained properly so far.

The dynamics of genome replication using deep sequencing

PubMed Central

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

2014-01-01

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

RNA deep sequencing as a tool for selection of cell lines for systematic subcellular localization of all human proteins.

PubMed

Danielsson, Frida; Wiking, Mikaela; Mahdessian, Diana; Skogs, Marie; Ait Blal, Hammou; Hjelmare, Martin; Stadler, Charlotte; Uhlén, Mathias; Lundberg, Emma

2013-01-04

One of the major challenges of a chromosome-centric proteome project is to explore in a systematic manner the potential proteins identified from the chromosomal genome sequence, but not yet characterized on a protein level. Here, we describe the use of RNA deep sequencing to screen human cell lines for RNA profiles and to use this information to select cell lines suitable for characterization of the corresponding gene product. In this manner, the subcellular localization of proteins can be analyzed systematically using antibody-based confocal microscopy. We demonstrate the usefulness of selecting cell lines with high expression levels of RNA transcripts to increase the likelihood of high quality immunofluorescence staining and subsequent successful subcellular localization of the corresponding protein. The results show a path to combine transcriptomics with affinity proteomics to characterize the proteins in a gene- or chromosome-centric manner.

Deep sequencing reveals persistence of cell-associated mumps vaccine virus in chronic encephalitis.

PubMed

Morfopoulou, Sofia; Mee, Edward T; Connaughton, Sarah M; Brown, Julianne R; Gilmour, Kimberly; Chong, W K 'Kling'; Duprex, W Paul; Ferguson, Deborah; Hubank, Mike; Hutchinson, Ciaran; Kaliakatsos, Marios; McQuaid, Stephen; Paine, Simon; Plagnol, Vincent; Ruis, Christopher; Virasami, Alex; Zhan, Hong; Jacques, Thomas S; Schepelmann, Silke; Qasim, Waseem; Breuer, Judith

2017-01-01

Routine childhood vaccination against measles, mumps and rubella has virtually abolished virus-related morbidity and mortality. Notwithstanding this, we describe here devastating neurological complications associated with the detection of live-attenuated mumps virus Jeryl Lynn (MuV JL5 ) in the brain of a child who had undergone successful allogeneic transplantation for severe combined immunodeficiency (SCID). This is the first confirmed report of MuV JL5 associated with chronic encephalitis and highlights the need to exclude immunodeficient individuals from immunisation with live-attenuated vaccines. The diagnosis was only possible by deep sequencing of the brain biopsy. Sequence comparison of the vaccine batch to the MuV JL5 isolated from brain identified biased hypermutation, particularly in the matrix gene, similar to those found in measles from cases of SSPE. The findings provide unique insights into the pathogenesis of paramyxovirus brain infections.

Optical Communications from Planetary Distances

NASA Technical Reports Server (NTRS)

Davarian, F.; Farr, W.; Hemmati, H.; Piazzolla, S.

2008-01-01

Future planetary campaigns, including human missions, will require data rates difficult to realize by microwave links. Optical channels not only provide an abundance of bandwidth, they also allow for significant size, weight, and power reduction. Moreover, optical-based tracking may enhance spacecraft navigation with respect to microwave-based tracking. With all its advantages, optical communications from deep space is not without its challenges. Due to the extreme distance between the two ends of the link, specialized technologies are needed to enable communications in the deep space environment. Although some of the relevant technologies have been developed in the last decade, they remain to be validated in an appropriate domain. The required assets include efficient pulsed laser sources, modulators, transmitters, receivers, detectors, channel encoders, precise beam pointing technologies for the flight transceiver and large apertures for the ground receiver. Clearly, space qualification is required for the systems that are installed on a deep space probe. Another challenge is atmospheric effects on the optical beam. Typical candidate locations on the ground have a cloud-free line of sight only on the order of 60-70% of the time. Furthermore, atmospheric losses and background light can be problematic even during cloud-free periods. Lastly, operational methodologies are needed for efficient and cost effective management of optical links. For more than a decade, the National Aeronautics and Space Administration (NASA) has invested in relevant technologies and procedures to enable deep space optical communications capable of providing robust links with rates in the order of 1 Gb/s from Mars distance. A recent publication indicates that potential exists for 30-dB improvement in performance through technology development with respect to the state-of-the-art in the early years of this decade. The goal is to fulfill the deep space community needs from about 2020 to the foreseeable future. It is envisioned that, at least initially, optical links will be complemented by microwave assets for added robustness, especially for human missions. However, it is expected that as optical techniques mature, laser communications may be operated without conventional radio frequency links. The purpose of this paper is to briefly review the state-of-the-art in deep space laser communications and its challenges and discuss NASA-supported technology development efforts and plans for deep space optical communications at JPL.

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

None Available

To make the web work better for science, OSTI has developed state-of-the-art technologies and services including a deep web search capability. The deep web includes content in searchable databases available to web users but not accessible by popular search engines, such as Google. This video provides an introduction to the deep web search engine.

Draft Genome Sequence of Thermus scotoductus Strain K1, Isolated from a Geothermal Spring in Karvachar, Nagorno Karabakh.

PubMed

Saghatelyan, Ani; Poghosyan, Lianna; Panosyan, Hovik; Birkeland, Nils-Kåre

2015-11-12

The 2,379,636-bp draft genome sequence of Thermus scotoductus strain K1, isolated from geothermal spring outlet located in the Karvachar region in Nagorno Karabakh is presented. Strain K1 shares about 80% genome sequence similarity with T. scotoductus strain SA-01, recovered from a deep gold mine in South Africa. Copyright © 2015 Saghatelyan et al.

Error Analysis of Deep Sequencing of Phage Libraries: Peptides Censored in Sequencing

PubMed Central

Matochko, Wadim L.; Derda, Ratmir

2013-01-01

Next-generation sequencing techniques empower selection of ligands from phage-display libraries because they can detect low abundant clones and quantify changes in the copy numbers of clones without excessive selection rounds. Identification of errors in deep sequencing data is the most critical step in this process because these techniques have error rates >1%. Mechanisms that yield errors in Illumina and other techniques have been proposed, but no reports to date describe error analysis in phage libraries. Our paper focuses on error analysis of 7-mer peptide libraries sequenced by Illumina method. Low theoretical complexity of this phage library, as compared to complexity of long genetic reads and genomes, allowed us to describe this library using convenient linear vector and operator framework. We describe a phage library as N × 1 frequency vector n = ||ni||, where ni is the copy number of the ith sequence and N is the theoretical diversity, that is, the total number of all possible sequences. Any manipulation to the library is an operator acting on n. Selection, amplification, or sequencing could be described as a product of a N × N matrix and a stochastic sampling operator (S a). The latter is a random diagonal matrix that describes sampling of a library. In this paper, we focus on the properties of S a and use them to define the sequencing operator (S e q). Sequencing without any bias and errors is S e q = S a IN, where IN is a N × N unity matrix. Any bias in sequencing changes IN to a nonunity matrix. We identified a diagonal censorship matrix (C E N), which describes elimination or statistically significant downsampling, of specific reads during the sequencing process. PMID:24416071

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

PubMed

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

2018-03-01

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

Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort.

PubMed

Crespo, Bibiana G; Wallhead, Philip J; Logares, Ramiro; Pedrós-Alió, Carlos

2016-01-01

High-throughput sequencing (HTS) techniques have suggested the existence of a wealth of species with very low relative abundance: the rare biosphere. We attempted to exhaustively map this rare biosphere in two water samples by performing an exceptionally deep pyrosequencing analysis (~500,000 final reads per sample). Species data were derived by a 97% identity criterion and various parametric distributions were fitted to the observed counts. Using the best-fitting Sichel distribution we estimate a total species richness of 1,568-1,669 (95% Credible Interval) and 5,027-5,196 for surface and deep water samples respectively, implying that 84-89% of the total richness in those two samples was sequenced, and we predict that a quadrupling of the present sequencing effort would suffice to observe 90% of the total richness in both samples. Comparing the HTS results with a culturing approach we found that most of the cultured taxa were not obtained by HTS, despite the high sequencing effort. Culturing therefore remains a useful tool for uncovering marine bacterial diversity, in addition to its other uses for studying the ecology of marine bacteria.

Integrated sequence stratigraphy of the postimpact sediments from the Eyreville core holes, Chesapeake Bay impact structure inner basin

USGS Publications Warehouse

Browning, J.V.; Miller, K.G.; McLaughlin, P.P.; Edwards, L.E.; Kulpecz, A.A.; Powars, D.S.; Wade, B.S.; Feigenson, M.D.; Wright, J.D.

2009-01-01

The Eyreville core holes provide the first continuously cored record of postimpact sequences from within the deepest part of the central Chesapeake Bay impact crater. We analyzed the upper Eocene to Pliocene postimpact sediments from the Eyreville A and C core holes for lithology (semiquantitative measurements of grain size and composition), sequence stratigraphy, and chronostratigraphy. Age is based primarily on Sr isotope stratigraphy supplemented by biostratigraphy (dinocysts, nannofossils, and planktonic foraminifers); age resolution is approximately ??0.5 Ma for early Miocene sequences and approximately ??1.0 Ma for younger and older sequences. Eocene-lower Miocene sequences are subtle, upper middle to lower upper Miocene sequences are more clearly distinguished, and upper Miocene- Pliocene sequences display a distinct facies pattern within sequences. We recognize two upper Eocene, two Oligocene, nine Miocene, three Pliocene, and one Pleistocene sequence and correlate them with those in New Jersey and Delaware. The upper Eocene through Pleistocene strata at Eyreville record changes from: (1) rapidly deposited, extremely fi ne-grained Eocene strata that probably represent two sequences deposited in a deep (>200 m) basin; to (2) highly dissected Oligocene (two very thin sequences) to lower Miocene (three thin sequences) with a long hiatus; to (3) a thick, rapidly deposited (43-73 m/Ma), very fi ne-grained, biosiliceous middle Miocene (16.5-14 Ma) section divided into three sequences (V5-V3) deposited in middle neritic paleoenvironments; to (4) a 4.5-Ma-long hiatus (12.8-8.3 Ma); to (5) sandy, shelly upper Miocene to Pliocene strata (8.3-2.0 Ma) divided into six sequences deposited in shelf and shoreface environments; and, last, to (6) a sandy middle Pleistocene paralic sequence (~400 ka). The Eyreville cores thus record the fi lling of a deep impact-generated basin where the timing of sequence boundaries is heavily infl uenced by eustasy. ?? 2009 The Geological Society of America.

Sequence Capture versus Restriction Site Associated DNA Sequencing for Shallow Systematics.

PubMed

Harvey, Michael G; Smith, Brian Tilston; Glenn, Travis C; Faircloth, Brant C; Brumfield, Robb T

2016-09-01

Sequence capture and restriction site associated DNA sequencing (RAD-Seq) are two genomic enrichment strategies for applying next-generation sequencing technologies to systematics studies. At shallow timescales, such as within species, RAD-Seq has been widely adopted among researchers, although there has been little discussion of the potential limitations and benefits of RAD-Seq and sequence capture. We discuss a series of issues that may impact the utility of sequence capture and RAD-Seq data for shallow systematics in non-model species. We review prior studies that used both methods, and investigate differences between the methods by re-analyzing existing RAD-Seq and sequence capture data sets from a Neotropical bird (Xenops minutus). We suggest that the strengths of RAD-Seq data sets for shallow systematics are the wide dispersion of markers across the genome, the relative ease and cost of laboratory work, the deep coverage and read overlap at recovered loci, and the high overall information that results. Sequence capture's benefits include flexibility and repeatability in the genomic regions targeted, success using low-quality samples, more straightforward read orthology assessment, and higher per-locus information content. The utility of a method in systematics, however, rests not only on its performance within a study, but on the comparability of data sets and inferences with those of prior work. In RAD-Seq data sets, comparability is compromised by low overlap of orthologous markers across species and the sensitivity of genetic diversity in a data set to an interaction between the level of natural heterozygosity in the samples examined and the parameters used for orthology assessment. In contrast, sequence capture of conserved genomic regions permits interrogation of the same loci across divergent species, which is preferable for maintaining comparability among data sets and studies for the purpose of drawing general conclusions about the impact of historical processes across biotas. We argue that sequence capture should be given greater attention as a method of obtaining data for studies in shallow systematics and comparative phylogeography. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Ultra-Deep Sequencing Analysis of the Hepatitis A Virus 5'-Untranslated Region among Cases of the Same Outbreak from a Single Source

PubMed Central

Wu, Shuang; Nakamoto, Shingo; Kanda, Tatsuo; Jiang, Xia; Nakamura, Masato; Miyamura, Tatsuo; Shirasawa, Hiroshi; Sugiura, Nobuyuki; Takahashi-Nakaguchi, Azusa; Gonoi, Tohru; Yokosuka, Osamu

2014-01-01

Hepatitis A virus (HAV) is a causative agent of acute viral hepatitis for which an effective vaccine has been developed. Here we describe ultra-deep pyrosequences (UDPSs) of HAV 5'-untranslated region (5'UTR) among cases of the same outbreak, which arose from a single source, associated with a revolving sushi bar. We determined the reference sequence from HAV-derived clone from an attendant by the Sanger method. Sixteen UDPSs from this outbreak and one from another sporadic case were compared with this reference. Nucleotide errors yielded a UDPS error rate of < 1%. This study confirmed that nucleotide substitutions of this region are transition mutations in outbreak cases, that insertion was observed only in non-severe cases, and that these nucleotide substitutions were different from those of the sporadic case. Analysis of UDPSs detected low-prevalence HAV variations in 5'UTR, but no specific mutations associated with severity in these outbreak cases. To our surprise, HAV strains in this outbreak conserved HAV IRES sequence even if we performed analysis of UDPSs. UDPS analysis of HAV 5'UTR gave us no association between the disease severity of hepatitis A and HAV 5'UTR substitutions. It might be more interesting to perform ultra-deep sequencing of full length HAV genome in order to reveal possible unknown genomic determinants associated with disease severity. Further studies will be needed. PMID:24396287

Concentrators Enhance Solar Power Systems

NASA Technical Reports Server (NTRS)

2013-01-01

"Right now, solar electric propulsion is being looked at very seriously," says Michael Piszczor, chief of the photovoltaic and power technologies branch at Glen Research Center. The reason, he explains, originates with a unique NASA mission from the late 1990s. In 1998, the Deep Space 1 spacecraft launched from Kennedy Space Center to test a dozen different space technologies, including SCARLET, or the Solar Concentrator Array with Refractive Linear Element Technology. As a solar array that focused sunlight on a smaller solar cell to generate electric power, SCARLET not only powered Deep Space 1 s instruments but also powered its ion engine, which propelled the spacecraft throughout its journey. Deep Space 1 was the first spacecraft powered by a refractive concentrator design like SCARLET, and also utilized multi-junction solar cells, or cells made of multiple layers of different materials. For the duration of its 38-month mission, SCARLET performed flawlessly, even as Deep Space 1 flew by Comet Borrelly and Asteroid Braille. "Everyone remembers the ion engine on Deep Space 1, but they tend to forget that the SCARLET array powered it," says Piszczor. "Not only did both technologies work as designed, but the synergy between the two, solar power and propulsion together, is really the important aspect of this technology demonstration mission. It was the first successful use of solar electric propulsion for primary propulsion." More than a decade later, NASA is keenly interested in using solar electric propulsion (SEP) for future space missions. A key issue is cost, and SEP has the potential to substantially reduce cost compared to conventional chemical propulsion technology. "SEP allows you to use spacecraft that are smaller, lighter, and less costly," says Piszczor. "Even though it might take longer to get somewhere using SEP, if you are willing to trade time for cost and smaller vehicles, it s a good trade." Potentially, SEP could be used on future science missions in orbit around the Earth or Moon, to planets or asteroids, on deep space science missions, and even on exploration missions. In fact, electric propulsion is already being used on Earth-orbiting satellites for positioning.

Low endemism, continued deep-shallow interchanges, and evidence for cosmopolitan distributions in free-living marine nematodes (order Enoplida)

PubMed Central

2010-01-01

Background Nematodes represent the most abundant benthic metazoa in one of the largest habitats on earth, the deep sea. Characterizing major patterns of biodiversity within this dominant group is a critical step towards understanding evolutionary patterns across this vast ecosystem. The present study has aimed to place deep-sea nematode species into a phylogenetic framework, investigate relationships between shallow water and deep-sea taxa, and elucidate phylogeographic patterns amongst the deep-sea fauna. Results Molecular data (18 S and 28 S rRNA) confirms a high diversity amongst deep-sea Enoplids. There is no evidence for endemic deep-sea lineages in Maximum Likelihood or Bayesian phylogenies, and Enoplids do not cluster according to depth or geographic location. Tree topologies suggest frequent interchanges between deep-sea and shallow water habitats, as well as a mixture of early radiations and more recently derived lineages amongst deep-sea taxa. This study also provides convincing evidence of cosmopolitan marine species, recovering a subset of Oncholaimid nematodes with identical gene sequences (18 S, 28 S and cox1) at trans-Atlantic sample sites. Conclusions The complex clade structures recovered within the Enoplida support a high global species richness for marine nematodes, with phylogeographic patterns suggesting the existence of closely related, globally distributed species complexes in the deep sea. True cosmopolitan species may additionally exist within this group, potentially driven by specific life history traits of Enoplids. Although this investigation aimed to intensively sample nematodes from the order Enoplida, specimens were only identified down to genus (at best) and our sampling regime focused on an infinitesimal small fraction of the deep-sea floor. Future nematode studies should incorporate an extended sample set covering a wide depth range (shelf, bathyal, and abyssal sites), utilize additional genetic loci (e.g. mtDNA) that are informative at the species level, and apply high-throughput sequencing methods to fully assay community diversity. Finally, further molecular studies are needed to determine whether phylogeographic patterns observed in Enoplids are common across other ubiquitous marine groups (e.g. Chromadorida, Monhysterida). PMID:21167065

The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation.

PubMed

Mavromatis, Konstantinos; Land, Miriam L; Brettin, Thomas S; Quest, Daniel J; Copeland, Alex; Clum, Alicia; Goodwin, Lynne; Woyke, Tanja; Lapidus, Alla; Klenk, Hans Peter; Cottingham, Robert W; Kyrpides, Nikos C

2012-01-01

The emergence of next generation sequencing (NGS) has provided the means for rapid and high throughput sequencing and data generation at low cost, while concomitantly creating a new set of challenges. The number of available assembled microbial genomes continues to grow rapidly and their quality reflects the quality of the sequencing technology used, but also of the analysis software employed for assembly and annotation. In this work, we have explored the quality of the microbial draft genomes across various sequencing technologies. We have compared the draft and finished assemblies of 133 microbial genomes sequenced at the Department of Energy-Joint Genome Institute and finished at the Los Alamos National Laboratory using a variety of combinations of sequencing technologies, reflecting the transition of the institute from Sanger-based sequencing platforms to NGS platforms. The quality of the public assemblies and of the associated gene annotations was evaluated using various metrics. Results obtained with the different sequencing technologies, as well as their effects on downstream processes, were analyzed. Our results demonstrate that the Illumina HiSeq 2000 sequencing system, the primary sequencing technology currently used for de novo genome sequencing and assembly at JGI, has various advantages in terms of total sequence throughput and cost, but it also introduces challenges for the downstream analyses. In all cases assembly results although on average are of high quality, need to be viewed critically and consider sources of errors in them prior to analysis. These data follow the evolution of microbial sequencing and downstream processing at the JGI from draft genome sequences with large gaps corresponding to missing genes of significant biological role to assemblies with multiple small gaps (Illumina) and finally to assemblies that generate almost complete genomes (Illumina+PacBio).

Genome Sequence of Aeribacillus pallidus Strain GS3372, an Endospore-Forming Bacterium Isolated in a Deep Geothermal Reservoir

PubMed Central

Filippidou, Sevasti; Jaussi, Marion; Junier, Thomas; Wunderlin, Tina; Jeanneret, Nicole; Regenspurg, Simona; Li, Po-E; Lo, Chien-Chi; McMurry, Kim; Gleasner, Cheryl D.; Vuyisich, Momchilo; Chain, Patrick S.

2015-01-01

The genome of strain GS3372 is the first publicly available strain of Aeribacillus pallidus. This endospore-forming thermophilic strain was isolated from a deep geothermal reservoir. The availability of this genome can contribute to the clarification of the taxonomy of the closely related Anoxybacillus, Geobacillus, and Aeribacillus genera. PMID:26316637

Bacterial community diversity of the deep-sea octocoral Paramuricea placomus.

PubMed

Kellogg, Christina A; Ross, Steve W; Brooke, Sandra D

2016-01-01

Compared to tropical corals, much less is known about deep-sea coral biology and ecology. Although the microbial communities of some deep-sea corals have been described, this is the first study to characterize the bacterial community associated with the deep-sea octocoral, Paramuricea placomus . Samples from five colonies of P. placomus were collected from Baltimore Canyon (379-382 m depth) in the Atlantic Ocean off the east coast of the United States of America. DNA was extracted from the coral samples and 16S rRNA gene amplicons were pyrosequenced using V4-V5 primers. Three samples sequenced deeply (>4,000 sequences each) and were further analyzed. The dominant microbial phylum was Proteobacteria, but other major phyla included Firmicutes and Planctomycetes. A conserved community of bacterial taxa held in common across the three P. placomus colonies was identified, comprising 68-90% of the total bacterial community depending on the coral individual. The bacterial community of P. placomus does not appear to include the genus Endozoicomonas , which has been found previously to be the dominant bacterial associate in several temperate and tropical gorgonians. Inferred functionality suggests the possibility of nitrogen cycling by the core bacterial community.

Bacterial community diversity of the deep-sea octocoral Paramuricea placomus

USGS Publications Warehouse

Kellogg, Christina A.; Ross, Steve W.; Brooke, Sandra D.

2016-01-01

Compared to tropical corals, much less is known about deep-sea coral biology and ecology. Although the microbial communities of some deep-sea corals have been described, this is the first study to characterize the bacterial community associated with the deep-sea octocoral, Paramuricea placomus. Samples from five colonies of P. placomus were collected from Baltimore Canyon (379–382 m depth) in the Atlantic Ocean off the east coast of the United States of America. DNA was extracted from the coral samples and 16S rRNA gene amplicons were pyrosequenced using V4-V5 primers. Three samples sequenced deeply (>4,000 sequences each) and were further analyzed. The dominant microbial phylum was Proteobacteria, but other major phyla included Firmicutes and Planctomycetes. A conserved community of bacterial taxa held in common across the three P. placomuscolonies was identified, comprising 68–90% of the total bacterial community depending on the coral individual. The bacterial community of P. placomusdoes not appear to include the genus Endozoicomonas, which has been found previously to be the dominant bacterial associate in several temperate and tropical gorgonians. Inferred functionality suggests the possibility of nitrogen cycling by the core bacterial community.

NASA's In-Space Propulsion Technology Program: A Step Toward Interstellar Exploration

NASA Technical Reports Server (NTRS)

Johnson, Les; James, Bonnie; Baggett, Randy; Montgomery, Sandy

2005-01-01

NASA's In-Space Propulsion Technology Program is investing in technologies that have the potential to revolutionize the robotic exploration of deep space. For robotic exploration and science missions, increased efficiencies of future propulsion systems are critical to reduce overall life-cycle costs and, in some cases, enable missions previously considered impossible. Continued reliance on conventional chemical propulsion alone will not enable the robust exploration of deep space. The maximum theoretical efficiencies have almost been reached and are insufficient to meet needs for many ambitious science missions currently being considered. By developing the capability to support mid-term robotic mission needs, the program is laying the technological foundation for travel to nearby interstellar space. The In-Space Propulsion Technology Program s technology portfolio includes many advanced propulsion systems. From the next-generation ion propulsion systems operating in the 5-10 kW range, to solar sail propulsion, substantial advances in spacecraft propulsion performance are anticipated. Some of the most promising technologies for achieving these goals use the environment of space itself for energy and propulsion and are generically called "propellantless" because they do not require onboard fuel to achieve thrust. Propellantless propulsion technologies include scientific innovations, such as solar sails, electrodynamic and momentum transfer tethers, and aerocapture. This paper will provide an overview of those propellantless and propellant-based advanced propulsion technologies that will most significantly advance our exploration of deep space.

Subglacial Lake Vostok (Antarctica) Accretion Ice Contains a Diverse Set of Sequences from Aquatic, Marine and Sediment-Inhabiting Bacteria and Eukarya

PubMed Central

Edgar, Robyn; Veerapaneni, Ram S.; D’Elia, Tom; Morris, Paul F.; Rogers, Scott O.

2013-01-01

Lake Vostok, the 7th largest (by volume) and 4th deepest lake on Earth, is covered by more than 3,700 m of ice, making it the largest subglacial lake known. The combination of cold, heat (from possible hydrothermal activity), pressure (from the overriding glacier), limited nutrients and complete darkness presents extreme challenges to life. Here, we report metagenomic/metatranscriptomic sequence analyses from four accretion ice sections from the Vostok 5G ice core. Two sections accreted in the vicinity of an embayment on the southwestern end of the lake, and the other two represented part of the southern main basin. We obtained 3,507 unique gene sequences from concentrates of 500 ml of 0.22 µm-filtered accretion ice meltwater. Taxonomic classifications (to genus and/or species) were possible for 1,623 of the sequences. Species determinations in combination with mRNA gene sequence results allowed deduction of the metabolic pathways represented in the accretion ice and, by extension, in the lake. Approximately 94% of the sequences were from Bacteria and 6% were from Eukarya. Only two sequences were from Archaea. In general, the taxa were similar to organisms previously described from lakes, brackish water, marine environments, soil, glaciers, ice, lake sediments, deep-sea sediments, deep-sea thermal vents, animals and plants. Sequences from aerobic, anaerobic, psychrophilic, thermophilic, halophilic, alkaliphilic, acidophilic, desiccation-resistant, autotrophic and heterotrophic organisms were present, including a number from multicellular eukaryotes. PMID:23843994

Subglacial Lake Vostok (Antarctica) accretion ice contains a diverse set of sequences from aquatic, marine and sediment-inhabiting bacteria and eukarya.

PubMed

Shtarkman, Yury M; Koçer, Zeynep A; Edgar, Robyn; Veerapaneni, Ram S; D'Elia, Tom; Morris, Paul F; Rogers, Scott O

2013-01-01

Lake Vostok, the 7(th) largest (by volume) and 4(th) deepest lake on Earth, is covered by more than 3,700 m of ice, making it the largest subglacial lake known. The combination of cold, heat (from possible hydrothermal activity), pressure (from the overriding glacier), limited nutrients and complete darkness presents extreme challenges to life. Here, we report metagenomic/metatranscriptomic sequence analyses from four accretion ice sections from the Vostok 5G ice core. Two sections accreted in the vicinity of an embayment on the southwestern end of the lake, and the other two represented part of the southern main basin. We obtained 3,507 unique gene sequences from concentrates of 500 ml of 0.22 µm-filtered accretion ice meltwater. Taxonomic classifications (to genus and/or species) were possible for 1,623 of the sequences. Species determinations in combination with mRNA gene sequence results allowed deduction of the metabolic pathways represented in the accretion ice and, by extension, in the lake. Approximately 94% of the sequences were from Bacteria and 6% were from Eukarya. Only two sequences were from Archaea. In general, the taxa were similar to organisms previously described from lakes, brackish water, marine environments, soil, glaciers, ice, lake sediments, deep-sea sediments, deep-sea thermal vents, animals and plants. Sequences from aerobic, anaerobic, psychrophilic, thermophilic, halophilic, alkaliphilic, acidophilic, desiccation-resistant, autotrophic and heterotrophic organisms were present, including a number from multicellular eukaryotes.

Space Suit Technologies Protect Deep-Sea Divers

NASA Technical Reports Server (NTRS)

2008-01-01

Working on NASA missions allows engineers and scientists to hone their skills. Creating devices for the high-stress rigors of space travel pushes designers to their limits, and the results often far exceed the original concepts. The technologies developed for the extreme environment of space are often applicable here on Earth. Some of these NASA technologies, for example, have been applied to the breathing apparatuses worn by firefighters, the fire-resistant suits worn by racecar crews, and, most recently, the deep-sea gear worn by U.S. Navy divers.

Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

PubMed

Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry

2014-12-05

Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

The deep space network

NASA Technical Reports Server (NTRS)

1980-01-01

The functions and facilities of the Deep Space Network are considered. Progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations is reported.

The deep space network

NASA Technical Reports Server (NTRS)

1979-01-01

Progress is reported in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. The functions and facilities of the Deep Space Network are emphasized.

Challenging Oil Bioremediation at Deep-Sea Hydrostatic Pressure

PubMed Central

Scoma, Alberto; Yakimov, Michail M.; Boon, Nico

2016-01-01

The Deepwater Horizon accident has brought oil contamination of deep-sea environments to worldwide attention. The risk for new deep-sea spills is not expected to decrease in the future, as political pressure mounts to access deep-water fossil reserves, and poorly tested technologies are used to access oil. This also applies to the response to oil-contamination events, with bioremediation the only (bio)technology presently available to combat deep-sea spills. Many questions about the fate of petroleum-hydrocarbons within deep-sea environments remain unanswered, as well as the main constraints limiting bioremediation under increased hydrostatic pressures and low temperatures. The microbial pathways fueling oil bioassimilation are unclear, and the mild upregulation observed for beta-oxidation-related genes in both water and sediments contrasts with the high amount of alkanes present in the spilled oil. The fate of solid alkanes (tar), hydrocarbon degradation rates and the reason why the most predominant hydrocarbonoclastic genera were not enriched at deep-sea despite being present at hydrocarbon seeps at the Gulf of Mexico have been largely overlooked. This mini-review aims at highlighting the missing information in the field, proposing a holistic approach where in situ and ex situ studies are integrated to reveal the principal mechanisms accounting for deep-sea oil bioremediation. PMID:27536290

Attomole-level Genomics with Single-molecule Direct DNA, cDNA and RNA Sequencing Technologies.

PubMed

Ozsolak, Fatih

2016-01-01

With the introduction of next-generation sequencing (NGS) technologies in 2005, the domination of microarrays in genomics quickly came to an end due to NGS's superior technical performance and cost advantages. By enabling genetic analysis capabilities that were not possible previously, NGS technologies have started to play an integral role in all areas of biomedical research. This chapter outlines the low-quantity DNA and cDNA sequencing capabilities and applications developed with the Helicos single molecule DNA sequencing technology.

Using small RNA (sRNA) deep sequencing to understand global virus distribution in plants

USDA-ARS?s Scientific Manuscript database

Small RNAs (sRNAs), a class of regulatory RNAs, have been used to serve as the specificity determinants of suppressing gene expression in plants and animals. Next generation sequencing (NGS) uncovered the sRNA landscape in most organisms including their associated microbes. In the current study, w...

Fatal Metacestode Infection in Bornean Orangutan Caused by Unknown Versteria Species

PubMed Central

Gendron-Fitzpatrick, Annette; Deering, Kathleen M.; Wallace, Roberta S.; Clyde, Victoria L.; Lauck, Michael; Rosen, Gail E.; Bennett, Andrew J.; Greiner, Ellis C.; O’Connor, David H.

2014-01-01

A captive juvenile Bornean orangutan (Pongo pygmaeus) died from an unknown disseminated parasitic infection. Deep sequencing of DNA from infected tissues, followed by gene-specific PCR and sequencing, revealed a divergent species within the newly proposed genus Versteria (Cestoda: Taeniidae). Versteria may represent a previously unrecognized risk to primate health. PMID:24377497

Testing deep reticulate evolution in Amaryllidaceae Tribe Hippeastreae (Asparagales) with ITS and chloroplast sequence data

USDA-ARS?s Scientific Manuscript database

The phylogeny of Amaryllidaceae tribe Hippeastreae was inferred using chloroplast (3’ycf1, ndhF, trnL-F) and nuclear (ITS rDNA) sequence data under maximum parsimony and maximum likelihood frameworks. Network analyses were applied to resolve conflicting signals among data sets and putative scenarios...

BIOCHEMICAL AND PHYLOGENETIC CHARACTERIZATION OF TWO NOVEL DEEP-SEA THERMOCOCCUS ISOLATES WITH POTENTIALLY BIOTECHNOLOGICAL APPLICATIONS

EPA Science Inventory

The partial 16S rDNA gene sequences of two thermophilic archaeal strains, TY and TYS, previously isolated from the Guaymas Basin hydrothermal vent site were determined. Lipid analyses and a comparative analysis performed with 16S rDNA sequences of similar thermophilic species sho...

Analysis of alterative cleavage and polyadenylation by 3′ region extraction and deep sequencing

PubMed Central

Hoque, Mainul; Ji, Zhe; Zheng, Dinghai; Luo, Wenting; Li, Wencheng; You, Bei; Park, Ji Yeon; Yehia, Ghassan; Tian, Bin

2012-01-01

Alternative cleavage and polyadenylation (APA) leads to mRNA isoforms with different coding sequences (CDS) and/or 3′ untranslated regions (3′UTRs). Using 3′ Region Extraction And Deep Sequencing (3′READS), a method which addresses the internal priming and oligo(A) tail issues that commonly plague polyA site (pA) identification, we comprehensively mapped pAs in the mouse genome, thoroughly annotating 3′ ends of genes and revealing over five thousand pAs (~8% of total) flanked by A-rich sequences, which have hitherto been overlooked. About 79% of mRNA genes and 66% of long non-coding RNA (lncRNA) genes have APA; but these two gene types have distinct usage patterns for pAs in introns and upstream exons. Promoter-distal pAs become relatively more abundant during embryonic development and cell differentiation, a trend affecting pAs in both 3′-most exons and upstream regions. Upregulated isoforms generally have stronger pAs, suggesting global modulation of the 3′ end processing activity in development and differentiation. PMID:23241633

Microbes in deep marine sediments viewed through amplicon sequencing and metagenomics

NASA Astrophysics Data System (ADS)

Biddle, J.; Leon, Z. R.; Russell, J. A., III; Martino, A. J.

2016-12-01

Nearly twenty percent of microbial biomass on Earth can be found in the marine subsurface. The majority of this is concentrated on continental margins, which have been investigated by scientific drilling. On the Costa Rica Margin, Iberian Margin and Peru Margins, sediment samples have been investigated through DNA extraction followed by amplicon and metagenomic sequencing. Overall samples show a high degree of microbial diversity, including many lineages of newly defined groups. In this talk, metagenome assembled genomes of unusual lineages will be presented, including their relationships to shallower relatives. From Costa Rica, in particular, we have retrieved deep relatives of Lokiarchaeota and Thorarchaeota, as well as other deeply branching archaeal relatives. We discuss their genome similarities to both other archaea and eukaryotes. From the Iberian Margin, relatives of Atribacteria and Aerophobetes will be discussed. Finally, we will detail the knowledge lost or gained depending on whether samples are studied via amplicon sequencing or total metagenomics, as studies in other environments have shown that up to 15% of microbial diversity is ignored when samples are studied via amplicon sequencing alone.

Characterization of skin ulceration syndrome associated microRNAs in sea cucumber Apostichopus japonicus by deep sequencing.

PubMed

Li, Chenghua; Feng, Weida; Qiu, Lihua; Xia, Changge; Su, Xiurong; Jin, Chunhua; Zhou, Tingting; Zeng, Yuan; Li, Taiwu

2012-08-01

MicroRNAs (miRNAs) constitute a family of small RNA species which have been demonstrated to be one of key effectors in mediating host-pathogen interaction. In this study, two haemocytes miRNA libraries were constructed with deep sequenced by illumina Hiseq2000 from healthy (L1) and skin ulceration syndrome Apostichopus japonicus (L2). The high throughput solexa sequencing resulted in 9,579,038 and 7,742,558 clean data from L1 and L2, respectively. Sequences analysis revealed that 40 conserved miRNAs were found in both libraries, in which let-7 and mir-125 were speculated to be clustered together and expressed accordingly. Eighty-six miRNA candidates were also identified by reference genome search and stem-loop structure prediction. Importantly, mir-31 and mir-2008 displayed significant differential expression between the two libraries according to FPKM model, which might be considered as promising targets for elucidating the intrinsic mechanism of skin ulceration syndrome outbreak in the species. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analysis of deep learning methods for blind protein contact prediction in CASP12.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2018-03-01

Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median family size of around 58 effective sequences, our server obtained an average top L/5 long- and medium-range contact accuracy of 47% and 44%, respectively (L = length). A complete implementation has an average accuracy of 59% and 57%, respectively. Our deep learning method formulates contact prediction as a pixel-level image labeling problem and simultaneously predicts all residue pairs of a protein using a combination of two deep residual neural networks, taking as input the residue conservation information, predicted secondary structure and solvent accessibility, contact potential, and coevolution information. Our approach differs from existing methods mainly in (1) formulating contact prediction as a pixel-level image labeling problem instead of an image-level classification problem; (2) simultaneously predicting all contacts of an individual protein to make effective use of contact occurrence patterns; and (3) integrating both one-dimensional and two-dimensional deep convolutional neural networks to effectively learn complex sequence-structure relationship including high-order residue correlation. This paper discusses the RaptorX-Contact pipeline, both contact prediction and contact-based folding results, and finally the strength and weakness of our method. © 2017 Wiley Periodicals, Inc.

Diversity and Biogeography of Bathyal and Abyssal Seafloor Bacteria

PubMed Central

Bienhold, Christina; Zinger, Lucie; Boetius, Antje; Ramette, Alban

2016-01-01

The deep ocean floor covers more than 60% of the Earth’s surface, and hosts diverse bacterial communities with important functions in carbon and nutrient cycles. The identification of key bacterial members remains a challenge and their patterns of distribution in seafloor sediment yet remain poorly described. Previous studies were either regionally restricted or included few deep-sea sediments, and did not specifically test biogeographic patterns across the vast oligotrophic bathyal and abyssal seafloor. Here we define the composition of this deep seafloor microbiome by describing those bacterial operational taxonomic units (OTU) that are specifically associated with deep-sea surface sediments at water depths ranging from 1000–5300 m. We show that the microbiome of the surface seafloor is distinct from the subsurface seafloor. The cosmopolitan bacterial OTU were affiliated with the clades JTB255 (class Gammaproteobacteria, order Xanthomonadales) and OM1 (Actinobacteria, order Acidimicrobiales), comprising 21% and 7% of their respective clades, and about 1% of all sequences in the study. Overall, few sequence-abundant bacterial types were globally dispersed and displayed positive range-abundance relationships. Most bacterial populations were rare and exhibited a high degree of endemism, explaining the substantial differences in community composition observed over large spatial scales. Despite the relative physicochemical uniformity of deep-sea sediments, we identified indicators of productivity regimes, especially sediment organic matter content, as factors significantly associated with changes in bacterial community structure across the globe. PMID:26814838

Diverse deep-sea fungi from the South China Sea and their antimicrobial activity.

PubMed

Zhang, Xiao-Yong; Zhang, Yun; Xu, Xin-Ya; Qi, Shu-Hua

2013-11-01

We investigated the diversity of fungal communities in nine different deep-sea sediment samples of the South China Sea by culture-dependent methods followed by analysis of fungal internal transcribed spacer (ITS) sequences. Although 14 out of 27 identified species were reported in a previous study, 13 species were isolated from sediments of deep-sea environments for the first report. Moreover, these ITS sequences of six isolates shared 84-92 % similarity with their closest matches in GenBank, which suggested that they might be novel phylotypes of genera Ajellomyces, Podosordaria, Torula, and Xylaria. The antimicrobial activities of these fungal isolates were explored using a double-layer technique. A relatively high proportion (56 %) of fungal isolates exhibited antimicrobial activity against at least one pathogenic bacterium or fungus among four marine pathogenic microbes (Micrococcus luteus, Pseudoaltermonas piscida, Aspergerillus versicolor, and A. sydowii). Out of these antimicrobial fungi, the genera Arthrinium, Aspergillus, and Penicillium exhibited antibacterial and antifungal activities, while genus Aureobasidium displayed only antibacterial activity, and genera Acremonium, Cladosporium, Geomyces, and Phaeosphaeriopsis displayed only antifungal activity. To our knowledge, this is the first report to investigate the diversity and antimicrobial activity of culturable deep-sea-derived fungi in the South China Sea. These results suggest that diverse deep-sea fungi from the South China Sea are a potential source for antibiotics' discovery and further increase the pool of fungi available for natural bioactive product screening.

High fungal diversity and abundance recovered in the deep-sea sediments of the Pacific Ocean.

PubMed

Xu, Wei; Pang, Ka-Lai; Luo, Zhu-Hua

2014-11-01

Knowledge about the presence and ecological significance of bacteria and archaea in the deep-sea environments has been well recognized, but the eukaryotic microorganisms, such as fungi, have rarely been reported. The present study investigated the composition and abundance of fungal community in the deep-sea sediments of the Pacific Ocean. In this study, a total of 1,947 internal transcribed spacer (ITS) regions of fungal rRNA gene clones were recovered from five sediment samples at the Pacific Ocean (water depths ranging from 5,017 to 6,986 m) using three different PCR primer sets. There were 16, 17, and 15 different operational taxonomic units (OTUs) identified from fungal-universal, Ascomycota-, and Basidiomycota-specific clone libraries, respectively. Majority of the recovered sequences belonged to diverse phylotypes of Ascomycota (25 phylotypes) and Basidiomycota (18 phylotypes). The multiple primer approach totally recovered 27 phylotypes which showed low similarities (≤97 %) with available fungal sequences in the GenBank, suggesting possible new fungal taxa occurring in the deep-sea environments or belonging to taxa not represented in the GenBank. Our results also recovered high fungal LSU rRNA gene copy numbers (3.52 × 10(6) to 5.23 × 10(7)copies/g wet sediment) from the Pacific Ocean sediment samples, suggesting that the fungi might be involved in important ecological functions in the deep-sea environments.

Advanced Virus Detection Technologies Interest Group (AVDTIG): Efforts on High Throughput Sequencing (HTS) for Virus Detection.

PubMed

Khan, Arifa S; Vacante, Dominick A; Cassart, Jean-Pol; Ng, Siemon H S; Lambert, Christophe; Charlebois, Robert L; King, Kathryn E

Several nucleic-acid based technologies have recently emerged with capabilities for broad virus detection. One of these, high throughput sequencing, has the potential for novel virus detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics. Thus, the Advanced Virus Detection Technologies Users Group was formed as a joint effort by regulatory and industry scientists to facilitate discussions and provide a forum for sharing data and experiences using advanced new virus detection technologies, with a focus on high throughput sequencing technologies. The group was initiated as a task force that was coordinated by the Parenteral Drug Association and subsequently became the Advanced Virus Detection Technologies Interest Group to continue efforts for using new technologies for detection of adventitious viruses with broader participation, including international government agencies, academia, and technology service providers. © PDA, Inc. 2016.

Degradation of CMOS image sensors in deep-submicron technology due to γ-irradiation

NASA Astrophysics Data System (ADS)

Rao, Padmakumar R.; Wang, Xinyang; Theuwissen, Albert J. P.

2008-09-01

In this work, radiation induced damage mechanisms in deep submicron technology is resolved using finger gated-diodes (FGDs) as a radiation sensitive tool. It is found that these structures are simple yet efficient structures to resolve radiation induced damage in advanced CMOS processes. The degradation of the CMOS image sensors in deep-submicron technology due to γ-ray irradiation is studied by developing a model for the spectral response of the sensor and also by the dark-signal degradation as a function of STI (shallow-trench isolation) parameters. It is found that threshold shifts in the gate-oxide/silicon interface as well as minority carrier life-time variations in the silicon bulk are minimal. The top-layer material properties and the photodiode Si-SiO2 interface quality are degraded due to γ-ray irradiation. Results further suggest that p-well passivated structures are inevitable for radiation-hard designs. It was found that high electrical fields in submicron technologies pose a threat to high quality imaging in harsh environments.

Deep Sequencing-Identified Kanamycin-Resistant Paenibacillus sp. Strain KS1 Isolated from Epiphyte Tillandsia usneoides (Spanish Moss) in Central Florida, USA

PubMed Central

Govindarajan, Subramaniam S.; Qi, Feng; Li, Jian-Liang; Sahoo, Malaya K.

2017-01-01

ABSTRACT Paenibacillus sp. strain KS1 was isolated from an epiphyte, Tillandsia usneoides (Spanish moss), in central Florida, USA. Here, we report a draft genome sequence of this strain, which consists of a total of 398 contigs spanning 6,508,195 bp, with a G+C content of 46.5% and comprising 5,401 predicted coding sequences. PMID:28153888

A simple and novel method for RNA-seq library preparation of single cell cDNA analysis by hyperactive Tn5 transposase.

PubMed

Brouilette, Scott; Kuersten, Scott; Mein, Charles; Bozek, Monika; Terry, Anna; Dias, Kerith-Rae; Bhaw-Rosun, Leena; Shintani, Yasunori; Coppen, Steven; Ikebe, Chiho; Sawhney, Vinit; Campbell, Niall; Kaneko, Masahiro; Tano, Nobuko; Ishida, Hidekazu; Suzuki, Ken; Yashiro, Kenta

2012-10-01

Deep sequencing of single cell-derived cDNAs offers novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-seq analysis requires multiple steps with consequent sample loss and stochastic variation at each step significantly affecting output. Thus, a simpler and better protocol is desirable. The recently developed hyperactive Tn5-mediated library preparation, which brings high quality libraries, is likely one of the solutions. Here, we tested the applicability of hyperactive Tn5-mediated library preparation to deep sequencing of single cell cDNA, optimized the protocol, and compared it with the conventional method based on sonication. This new technique does not require any expensive or special equipment, which secures wider availability. A library was constructed from only 100 ng of cDNA, which enables the saving of precious specimens. Only a few steps of robust enzymatic reaction resulted in saved time, enabling more specimens to be prepared at once, and with a more reproducible size distribution among the different specimens. The obtained RNA-seq results were comparable to the conventional method. Thus, this Tn5-mediated preparation is applicable for anyone who aims to carry out deep sequencing for single cell cDNAs. Copyright © 2012 Wiley Periodicals, Inc.

Detailed investigation of the microbial community in foaming activated sludge reveals novel foam formers

PubMed Central

Guo, Feng; Wang, Zhi-Ping; Yu, Ke; Zhang, T.

2015-01-01

Foaming of activated sludge (AS) causes adverse impacts on wastewater treatment operation and hygiene. In this study, we investigated the microbial communities of foam, foaming AS and non-foaming AS in a sewage treatment plant via deep-sequencing of the taxonomic marker genes 16S rRNA and mycobacterial rpoB and a metagenomic approach. In addition to Actinobacteria, many genera (e.g., Clostridium XI, Arcobacter, Flavobacterium) were more abundant in the foam than in the AS. On the other hand, deep-sequencing of rpoB did not detect any obligate pathogenic mycobacteria in the foam. We found that unknown factors other than the abundance of Gordonia sp. could determine the foaming process, because abundance of the same species was stable before and after a foaming event over six months. More interestingly, although the dominant Gordonia foam former was the closest with G. amarae, it was identified as an undescribed Gordonia species by referring to the 16S rRNA gene, gyrB and, most convincingly, the reconstructed draft genome from metagenomic reads. Our results, based on metagenomics and deep sequencing, reveal that foams are derived from diverse taxa, which expands previous understanding and provides new insight into the underlying complications of the foaming phenomenon in AS. PMID:25560234

Oasis 2: improved online analysis of small RNA-seq data.

PubMed

Rahman, Raza-Ur; Gautam, Abhivyakti; Bethune, Jörn; Sattar, Abdul; Fiosins, Maksims; Magruder, Daniel Sumner; Capece, Vincenzo; Shomroni, Orr; Bonn, Stefan

2018-02-14

Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing. Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment. Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de.

Identification of microRNA-like RNAs from Curvularia lunata associated with maize leaf spot by bioinformation analysis and deep sequencing.

PubMed

Liu, Tong; Hu, John; Zuo, Yuhu; Jin, Yazhong; Hou, Jumei

2016-04-01

Deep sequencing of small RNAs is a useful tool to identify novel small RNAs that may be involved in fungal growth and pathogenesis. In this study, we used HiSeq deep sequencing to identify 747,487 unique small RNAs from Curvularia lunata. Among these small RNAs were 1012 microRNA-like RNAs (milRNAs), which are similar to other known microRNAs, and 48 potential novel milRNAs without homologs in other organisms have been identified using the miRBase© database. We used quantitative PCR to analyze the expression of four of these milRNAs from C. lunata at different developmental stages. The analysis revealed several changes associated with germinating conidia and mycelial growth, suggesting that these milRNAs may play a role in pathogen infection and mycelial growth. A total of 8334 target mRNAs for the 1012 milRNAs that were identified, and 256 target mRNAs for the 48 novel milRNAs were predicted by computational analysis. These target mRNAs of milRNAs were also performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our knowledge, this study is the first report of C. lunata's milRNA profiles. This information will provide a better understanding of pathogen development and infection mechanism.

Acute West Nile Virus Meningoencephalitis Diagnosed Via Metagenomic Deep Sequencing of Cerebrospinal Fluid in a Renal Transplant Patient.

PubMed

Wilson, M R; Zimmermann, L L; Crawford, E D; Sample, H A; Soni, P R; Baker, A N; Khan, L M; DeRisi, J L

2017-03-01

Solid organ transplant patients are vulnerable to suffering neurologic complications from a wide array of viral infections and can be sentinels in the population who are first to get serious complications from emerging infections like the recent waves of arboviruses, including West Nile virus, Chikungunya virus, Zika virus, and Dengue virus. The diverse and rapidly changing landscape of possible causes of viral encephalitis poses great challenges for traditional candidate-based infectious disease diagnostics that already fail to identify a causative pathogen in approximately 50% of encephalitis cases. We present the case of a 14-year-old girl on immunosuppression for a renal transplant who presented with acute meningoencephalitis. Traditional diagnostics failed to identify an etiology. RNA extracted from her cerebrospinal fluid was subjected to unbiased metagenomic deep sequencing, enhanced with the use of a Cas9-based technique for host depletion. This analysis identified West Nile virus (WNV). Convalescent serum serologies subsequently confirmed WNV seroconversion. These results support a clear clinical role for metagenomic deep sequencing in the setting of suspected viral encephalitis, especially in the context of the high-risk transplant patient population. © 2016 The Authors. American Journal of Transplantation published by Wiley Periodicals, Inc. on behalf of American Society of Transplant Surgeons.

A deep learning framework for causal shape transformation.

PubMed

Lore, Kin Gwn; Stoecklein, Daniel; Davies, Michael; Ganapathysubramanian, Baskar; Sarkar, Soumik

2018-02-01

Recurrent neural network (RNN) and Long Short-term Memory (LSTM) networks are the common go-to architecture for exploiting sequential information where the output is dependent on a sequence of inputs. However, in most considered problems, the dependencies typically lie in the latent domain which may not be suitable for applications involving the prediction of a step-wise transformation sequence that is dependent on the previous states only in the visible domain with a known terminal state. We propose a hybrid architecture of convolution neural networks (CNN) and stacked autoencoders (SAE) to learn a sequence of causal actions that nonlinearly transform an input visual pattern or distribution into a target visual pattern or distribution with the same support and demonstrated its practicality in a real-world engineering problem involving the physics of fluids. We solved a high-dimensional one-to-many inverse mapping problem concerning microfluidic flow sculpting, where the use of deep learning methods as an inverse map is very seldom explored. This work serves as a fruitful use-case to applied scientists and engineers in how deep learning can be beneficial as a solution for high-dimensional physical problems, and potentially opening doors to impactful advance in fields such as material sciences and medical biology where multistep topological transformations is a key element. Copyright © 2017 Elsevier Ltd. All rights reserved.

Link monitor and control operator assistant: A prototype demonstrating semiautomated monitor and control

NASA Technical Reports Server (NTRS)

Lee, L. F.; Cooper, L. P.

1993-01-01

This article describes the approach, results, and lessons learned from an applied research project demonstrating how artificial intelligence (AI) technology can be used to improve Deep Space Network operations. Configuring antenna and associated equipment necessary to support a communications link is a time-consuming process. The time spent configuring the equipment is essentially overhead and results in reduced time for actual mission support operations. The NASA Office of Space Communications (Code O) and the NASA Office of Advanced Concepts and Technology (Code C) jointly funded an applied research project to investigate technologies which can be used to reduce configuration time. This resulted in the development and application of AI-based automated operations technology in a prototype system, the Link Monitor and Control Operator Assistant (LMC OA). The LMC OA was tested over the course of three months in a parallel experimental mode on very long baseline interferometry (VLBI) operations at the Goldstone Deep Space Communications Center. The tests demonstrated a 44 percent reduction in pre-calibration time for a VLBI pass on the 70-m antenna. Currently, this technology is being developed further under Research and Technology Operating Plan (RTOP)-72 to demonstrate the applicability of the technology to operations in the entire Deep Space Network.

The deep space network

NASA Technical Reports Server (NTRS)

1979-01-01

A report is given of the Deep Space Networks progress in (1) flight project support, (2) tracking and data acquisition research and technology, (3) network engineering, (4) hardware and software implementation, and (5) operations.

Molecular characterization of an adiponectin receptor homolog in the white leg shrimp, Litopenaeus vannamei

PubMed Central

Kim, Ah Ran; Alam, Md Jobaidul; Yoon, Tae-ho; Lee, Soo Rin; Park, Hyun; Kim, Doo-Nam; An, Doo-Hae; Lee, Jae-Bong; Lee, Chung Il

2016-01-01

Adiponectin (AdipoQ) and its receptors (AdipoRs) are strongly related to growth and development of skeletal muscle, as well as glucose and lipid metabolism in vertebrates. Herein we report the identification of the first full-length cDNA encoding an AdipoR homolog (Liv-AdipoR) from the decapod crustacean Litopenaeus vannamei using a combination of next generation sequencing (NGS) technology and bioinformatics analysis. The full-length Liv-AdipoR (1,245 bp) encoded a protein that exhibited the canonical seven transmembrane domains (7TMs) and the inversed topology that characterize members of the progestin and adipoQ receptor (PAQR) family. Based on the obtained sequence information, only a single orthologous AdipoR gene appears to exist in arthropods, whereas two paralogs, AdipoR1 and AdipoR2, have evolved in vertebrates. Transcriptional analysis suggested that the single Liv-AdipoR gene appears to serve the functions of two mammalian AdipoRs. At 72 h after injection of 50 pmol Liv-AdipoR dsRNA (340 bp) into L. vannamei thoracic muscle and deep abdominal muscle, transcription levels of Liv-AdipoR decreased by 93% and 97%, respectively. This confirmed optimal conditions for RNAi of Liv-AdipoR. Knockdown of Liv-AdipoR resulted in significant changes in the plasma levels of ammonia, 3-methylhistine, and ornithine, but not plasma glucose, suggesting that that Liv-AdipoR is important for maintaining muscle fibers. The chronic effect of Liv-AdipoR dsRNA injection was increased mortality. Transcriptomic analysis showed that 804 contigs were upregulated and 212 contigs were downregulated by the knockdown of Liv-AdipoR in deep abdominal muscle. The significantly upregulated genes were categorized as four main functional groups: RNA-editing and transcriptional regulators, molecular chaperones, metabolic regulators, and channel proteins. PMID:27478708