Deep Sequencing Analysis of RNAs from Citrus Plants Grown in a Citrus Sudden Death-Affected Area Reveals Diverse Known and Putative Novel Viruses.

PubMed

Matsumura, Emilyn E; Coletta-Filho, Helvecio D; Nouri, Shahideh; Falk, Bryce W; Nerva, Luca; Oliveira, Tiago S; Dorta, Silvia O; Machado, Marcos A

2017-04-24

Citrus sudden death (CSD) has caused the death of approximately four million orange trees in a very important citrus region in Brazil. Although its etiology is still not completely clear, symptoms and distribution of affected plants indicate a viral disease. In a search for viruses associated with CSD, we have performed a comparative high-throughput sequencing analysis of the transcriptome and small RNAs from CSD-symptomatic and -asymptomatic plants using the Illumina platform. The data revealed mixed infections that included Citrus tristeza virus (CTV) as the most predominant virus, followed by the Citrus sudden death-associated virus (CSDaV), Citrus endogenous pararetrovirus (CitPRV) and two putative novel viruses tentatively named Citrus jingmen-like virus (CJLV), and Citrus virga-like virus (CVLV). The deep sequencing analyses were sensitive enough to differentiate two genotypes of both viruses previously associated with CSD-affected plants: CTV and CSDaV. Our data also showed a putative association of the CSD-symptomatic plants with a specific CSDaV genotype and a likely association with CitPRV as well, whereas the two putative novel viruses showed to be more associated with CSD-asymptomatic plants. This is the first high-throughput sequencing-based study of the viral sequences present in CSD-affected citrus plants, and generated valuable information for further CSD studies.

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.

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

Quantitative phenotyping via deep barcode sequencing.

PubMed

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

2009-10-01

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

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.

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.

Quantitative phenotyping via deep barcode sequencing

PubMed Central

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

2009-01-01

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

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.

A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

PubMed Central

Hanriot, Lucie; Keime, Céline; Gay, Nadine; Faure, Claudine; Dossat, Carole; Wincker, Patrick; Scoté-Blachon, Céline; Peyron, Christelle; Gandrillon, Olivier

2008-01-01

Background "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered. Results In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method. Conclusion We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method. PMID:18796152

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.

Denoising DNA deep sequencing data—high-throughput sequencing errors and their correction

PubMed Central

Laehnemann, David; Borkhardt, Arndt

2016-01-01

Characterizing the errors generated by common high-throughput sequencing platforms and telling true genetic variation from technical artefacts are two interdependent steps, essential to many analyses such as single nucleotide variant calling, haplotype inference, sequence assembly and evolutionary studies. Both random and systematic errors can show a specific occurrence profile for each of the six prominent sequencing platforms surveyed here: 454 pyrosequencing, Complete Genomics DNA nanoball sequencing, Illumina sequencing by synthesis, Ion Torrent semiconductor sequencing, Pacific Biosciences single-molecule real-time sequencing and Oxford Nanopore sequencing. There is a large variety of programs available for error removal in sequencing read data, which differ in the error models and statistical techniques they use, the features of the data they analyse, the parameters they determine from them and the data structures and algorithms they use. We highlight the assumptions they make and for which data types these hold, providing guidance which tools to consider for benchmarking with regard to the data properties. While no benchmarking results are included here, such specific benchmarks would greatly inform tool choices and future software development. The development of stand-alone error correctors, as well as single nucleotide variant and haplotype callers, could also benefit from using more of the knowledge about error profiles and from (re)combining ideas from the existing approaches presented here. PMID:26026159

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.

[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.

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.

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

Using High-Throughput Sequencing to Leverage Surveillance of Genetic Diversity and Oseltamivir Resistance: A Pilot Study during the 2009 Influenza A(H1N1) Pandemic

PubMed Central

Téllez-Sosa, Juan; Rodríguez, Mario Henry; Gómez-Barreto, Rosa E.; Valdovinos-Torres, Humberto; Hidalgo, Ana Cecilia; Cruz-Hervert, Pablo; Luna, René Santos; Carrillo-Valenzo, Erik; Ramos, Celso; García-García, Lourdes; Martínez-Barnetche, Jesús

2013-01-01

Background Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The “deep sequencing” approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples. Methodology and Principal Findings We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n  =  299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance. Conclusions NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach presented here can be scaled up for global genetic surveillance of influenza and other infectious diseases. PMID:23843978

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

From clinical sample to complete genome: Comparing methods for the extraction of HIV-1 RNA for high-throughput deep sequencing.

PubMed

Cornelissen, Marion; Gall, Astrid; Vink, Monique; Zorgdrager, Fokla; Binter, Špela; Edwards, Stephanie; Jurriaans, Suzanne; Bakker, Margreet; Ong, Swee Hoe; Gras, Luuk; van Sighem, Ard; Bezemer, Daniela; de Wolf, Frank; Reiss, Peter; Kellam, Paul; Berkhout, Ben; Fraser, Christophe; van der Kuyl, Antoinette C

2017-07-15

The BEEHIVE (Bridging the Evolution and Epidemiology of HIV in Europe) project aims to analyse nearly-complete viral genomes from >3000 HIV-1 infected Europeans using high-throughput deep sequencing techniques to investigate the virus genetic contribution to virulence. Following the development of a computational pipeline, including a new de novo assembler for RNA virus genomes, to generate larger contiguous sequences (contigs) from the abundance of short sequence reads that characterise the data, another area that determines genome sequencing success is the quality and quantity of the input RNA. A pilot experiment with 125 patient plasma samples was performed to investigate the optimal method for isolation of HIV-1 viral RNA for long amplicon genome sequencing. Manual isolation with the QIAamp Viral RNA Mini Kit (Qiagen) was superior over robotically extracted RNA using either the QIAcube robotic system, the mSample Preparation Systems RNA kit with automated extraction by the m2000sp system (Abbott Molecular), or the MagNA Pure 96 System in combination with the MagNA Pure 96 Instrument (Roche Diagnostics). We scored amplification of a set of four HIV-1 amplicons of ∼1.9, 3.6, 3.0 and 3.5kb, and subsequent recovery of near-complete viral genomes. Subsequently, 616 BEEHIVE patient samples were analysed to determine factors that influence successful amplification of the genome in four overlapping amplicons using the QIAamp Viral RNA Kit for viral RNA isolation. Both low plasma viral load and high sample age (stored before 1999) negatively influenced the amplification of viral amplicons >3kb. A plasma viral load of >100,000 copies/ml resulted in successful amplification of all four amplicons for 86% of the samples, this value dropped to only 46% for samples with viral loads of <20,000 copies/ml. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy

PubMed Central

Ulrich, Nikea; Rosenberger, Abigail; Brislawn, Colin; Wright, Justin; Kessler, Collin; Toole, David; Solomon, Caroline; Strutt, Steven; McClure, Erin

2016-01-01

ABSTRACT Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella, Campylobacter, Arcobacter, and Helicobacter, as well as bacteria of fecal origin (e.g., Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event. IMPORTANCE In order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter- and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment. PMID:27060115

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.

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

High-throughput determination of RNA structure by proximity ligation.

PubMed

Ramani, Vijay; Qiu, Ruolan; Shendure, Jay

2015-09-01

We present an unbiased method to globally resolve RNA structures through pairwise contact measurements between interacting regions. RNA proximity ligation (RPL) uses proximity ligation of native RNA followed by deep sequencing to yield chimeric reads with ligation junctions in the vicinity of structurally proximate bases. We apply RPL in both baker's yeast (Saccharomyces cerevisiae) and human cells and generate contact probability maps for ribosomal and other abundant RNAs, including yeast snoRNAs, the RNA subunit of the signal recognition particle and the yeast U2 spliceosomal RNA homolog. RPL measurements correlate with established secondary structures for these RNA molecules, including stem-loop structures and long-range pseudoknots. We anticipate that RPL will complement the current repertoire of computational and experimental approaches in enabling the high-throughput determination of secondary and tertiary RNA structures.

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.

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

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

PubMed Central

Lutsik, Pavlo; Feuerbach, Lars; Arand, Julia; Lengauer, Thomas; Walter, Jörn; Bock, Christoph

2011-01-01

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data. PMID:21565797

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

PubMed Central

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

2016-01-01

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

Rapid Fine Conformational Epitope Mapping Using Comprehensive Mutagenesis and Deep Sequencing*

PubMed Central

Kowalsky, Caitlin A.; Faber, Matthew S.; Nath, Aritro; Dann, Hailey E.; Kelly, Vince W.; Liu, Li; Shanker, Purva; Wagner, Ellen K.; Maynard, Jennifer A.; Chan, Christina; Whitehead, Timothy A.

2015-01-01

Knowledge of the fine location of neutralizing and non-neutralizing epitopes on human pathogens affords a better understanding of the structural basis of antibody efficacy, which will expedite rational design of vaccines, prophylactics, and therapeutics. However, full utilization of the wealth of information from single cell techniques and antibody repertoire sequencing awaits the development of a high throughput, inexpensive method to map the conformational epitopes for antibody-antigen interactions. Here we show such an approach that combines comprehensive mutagenesis, cell surface display, and DNA deep sequencing. We develop analytical equations to identify epitope positions and show the method effectiveness by mapping the fine epitope for different antibodies targeting TNF, pertussis toxin, and the cancer target TROP2. In all three cases, the experimentally determined conformational epitope was consistent with previous experimental datasets, confirming the reliability of the experimental pipeline. Once the comprehensive library is generated, fine conformational epitope maps can be prepared at a rate of four per day. PMID:26296891

Deep Packet/Flow Analysis using GPUs

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

Gong, Qian; Wu, Wenji; DeMar, Phil

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Sincemore » the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.« less

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

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.

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.

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.

High-Throughput Sequencing of Germline and Tumor From Men with Early-Onset Metastatic Prostate Cancer

DTIC Science & Technology

2016-12-01

AWARD NUMBER: W81XWH-13-1-0371 TITLE: High-Throughput Sequencing of Germline and Tumor From Men with Early- Onset Metastatic Prostate Cancer...DATES COVERED 30 Sep 2013 - 29 Sep 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER High-Throughput Sequencing of Germline and Tumor From Men with...presenting with metastatic prostate cancer at a young age (before age 60 years). Whole exome sequencing identified a panel of germline variants that have

Advances in high throughput DNA sequence data compression.

PubMed

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

2016-06-01

Advances in high throughput sequencing technologies and reduction in cost of sequencing have led to exponential growth in high throughput DNA sequence data. This growth has posed challenges such as storage, retrieval, and transmission of sequencing data. Data compression is used to cope with these challenges. Various methods have been developed to compress genomic and sequencing data. In this article, we present a comprehensive review of compression methods for genome and reads compression. Algorithms are categorized as referential or reference free. Experimental results and comparative analysis of various methods for data compression are presented. Finally, key challenges and research directions in DNA sequence data compression are highlighted.

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.

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.

The Peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity.

PubMed

Verde, Ignazio; Jenkins, Jerry; Dondini, Luca; Micali, Sabrina; Pagliarani, Giulia; Vendramin, Elisa; Paris, Roberta; Aramini, Valeria; Gazza, Laura; Rossini, Laura; Bassi, Daniele; Troggio, Michela; Shu, Shengqiang; Grimwood, Jane; Tartarini, Stefano; Dettori, Maria Teresa; Schmutz, Jeremy

2017-03-11

The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches. Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%. The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

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

Identification of microRNAs involved in lipid biosynthesis and seed size in developing sea buckthorn seeds using high-throughput sequencing.

PubMed

Ding, Jian; Ruan, Chengjiang; Guan, Ying; Krishna, Priti

2018-03-05

Sea buckthorn is a plant of medicinal and nutritional importance owing in part to the high levels of essential fatty acids, linoleic (up to 42%) and α-linolenic (up to 39%) acids in the seed oil. Sea buckthorn can produce seeds either via the sexual pathway or by apomixis. The seed development and maturation programs are critically dependent on miRNAs. To understand miRNA-mediated regulation of sea buckthorn seed development, eight small RNA libraries were constructed for deep sequencing from developing seeds of a low oil content line 'SJ1' and a high oil content line 'XE3'. High-throughput sequencing identified 137 known miRNA from 27 families and 264 novel miRNAs. The potential targets of the identified miRNAs were predicted based on sequence homology. Nineteen (four known and 15 novel) and 22 (six known and 16 novel) miRNAs were found to be involved in lipid biosynthesis and seed size, respectively. An integrated analysis of mRNA and miRNA transcriptome and qRT-PCR identified some key miRNAs and their targets (miR164d-ARF2, miR168b-Δ9D, novelmiRNA-108-ACC, novelmiRNA-23-GPD1, novelmiRNA-58-DGAT1, and novelmiRNA-191-DGAT2) potentially involved in seed size and lipid biosynthesis of sea buckthorn seed. These results indicate the potential importance of miRNAs in regulating lipid biosynthesis and seed size in sea buckthorn.

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.

High-throughput sequence alignment using Graphics Processing Units

PubMed Central

Schatz, Michael C; Trapnell, Cole; Delcher, Arthur L; Varshney, Amitabh

2007-01-01

Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs) in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA) from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU. PMID:18070356

Coalescent Inference Using Serially Sampled, High-Throughput Sequencing Data from Intrahost HIV Infection

PubMed Central

Dialdestoro, Kevin; Sibbesen, Jonas Andreas; Maretty, Lasse; Raghwani, Jayna; Gall, Astrid; Kellam, Paul; Pybus, Oliver G.; Hein, Jotun; Jenkins, Paul A.

2016-01-01

Human immunodeficiency virus (HIV) is a rapidly evolving pathogen that causes chronic infections, so genetic diversity within a single infection can be very high. High-throughput “deep” sequencing can now measure this diversity in unprecedented detail, particularly since it can be performed at different time points during an infection, and this offers a potentially powerful way to infer the evolutionary dynamics of the intrahost viral population. However, population genomic inference from HIV sequence data is challenging because of high rates of mutation and recombination, rapid demographic changes, and ongoing selective pressures. In this article we develop a new method for inference using HIV deep sequencing data, using an approach based on importance sampling of ancestral recombination graphs under a multilocus coalescent model. The approach further extends recent progress in the approximation of so-called conditional sampling distributions, a quantity of key interest when approximating coalescent likelihoods. The chief novelties of our method are that it is able to infer rates of recombination and mutation, as well as the effective population size, while handling sampling over different time points and missing data without extra computational difficulty. We apply our method to a data set of HIV-1, in which several hundred sequences were obtained from an infected individual at seven time points over 2 years. We find mutation rate and effective population size estimates to be comparable to those produced by the software BEAST. Additionally, our method is able to produce local recombination rate estimates. The software underlying our method, Coalescenator, is freely available. PMID:26857628

Molecular characterization of a novel Nucleorhabdovirus from black currant identified by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Contigs with sequence similarities to several nucleorhabdoviruses were identified by high-throughput sequencing analysis from a black currant (Ribes nigrum L.) cultivar. The complete genomic sequence of this new nucleorhabdovirus is 14,432 nucleotides. Its genomic organization is typical of nucleorh...

High Throughput Plasmid Sequencing with Illumina and CLC Bio (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

ScienceCinema

Athavale, Ajay

2018-01-04

Ajay Athavale (Monsanto) presents "High Throughput Plasmid Sequencing with Illumina and CLC Bio" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

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.

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.

Molecular characterization of a novel Luteovirus from peach identified by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Contigs with sequence homologies to Cherry-associated luteovirus were identified by high-throughput sequencing analysis of two peach accessions undergoing quarantine testing. The complete genomic sequences of the two isolates of this virus are 5,819 and 5,814 nucleotides. Their genome organization i...

Identification of Sequence Specificity of 5-Methylcytosine Oxidation by Tet1 Protein with High-Throughput Sequencing.

PubMed

Kizaki, Seiichiro; Chandran, Anandhakumar; Sugiyama, Hiroshi

2016-03-02

Tet (ten-eleven translocation) family proteins have the ability to oxidize 5-methylcytosine (mC) to 5-hydroxymethylcytosine (hmC), 5-formylcytosine (fC), and 5-carboxycytosine (caC). However, the oxidation reaction of Tet is not understood completely. Evaluation of genomic-level epigenetic changes by Tet protein requires unbiased identification of the highly selective oxidation sites. In this study, we used high-throughput sequencing to investigate the sequence specificity of mC oxidation by Tet1. A 6.6×10(4) -member mC-containing random DNA-sequence library was constructed. The library was subjected to Tet-reactive pulldown followed by high-throughput sequencing. Analysis of the obtained sequence data identified the Tet1-reactive sequences. We identified mCpG as a highly reactive sequence of Tet1 protein. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep-branching Novel Lineages and High Diversity of Haptophytes in the Skagerrak (Norway) Uncovered by 454 Pyrosequencing

PubMed Central

Egge, Elianne S; Eikrem, Wenche; Edvardsen, Bente

2015-01-01

Microalgae in the division Haptophyta may be difficult to identify to species by microscopy because they are small and fragile. Here, we used high-throughput sequencing to explore the diversity of haptophytes in outer Oslofjorden, Skagerrak, and supplemented this with electron microscopy. Nano- and picoplanktonic subsurface samples were collected monthly for 2 yr, and the haptophytes were targeted by amplification of RNA/cDNA with Haptophyta-specific 18S ribosomal DNA V4 primers. Pyrosequencing revealed higher species richness of haptophytes than previously observed in the Skagerrak by microscopy. From ca. 400,000 reads we obtained 156 haptophyte operational taxonomic units (OTUs) after rigorous filtering and 99.5% clustering. The majority (84%) of the OTUs matched environmental sequences not linked to a morphological species, most of which were affiliated with the order Prymnesiales. Phylogenetic analyses including Oslofjorden OTUs and available cultured and environmental haptophyte sequences showed that several of the OTUs matched sequences forming deep-branching lineages, potentially representing novel haptophyte classes. Pyrosequencing also retrieved cultured species not previously reported by microscopy in the Skagerrak. Electron microscopy revealed species not yet genetically characterised and some potentially novel taxa. This study contributes to linking genotype to phenotype within this ubiquitous and ecologically important protist group, and reveals great, unknown diversity. PMID:25099994

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

Uncovering leaf rust responsive miRNAs in wheat (Triticum aestivum L.) using high-throughput sequencing and prediction of their targets through degradome analysis.

PubMed

Kumar, Dhananjay; Dutta, Summi; Singh, Dharmendra; Prabhu, Kumble Vinod; Kumar, Manish; Mukhopadhyay, Kunal

2017-01-01

Deep sequencing identified 497 conserved and 559 novel miRNAs in wheat, while degradome analysis revealed 701 targets genes. QRT-PCR demonstrated differential expression of miRNAs during stages of leaf rust progression. Bread wheat (Triticum aestivum L.) is an important cereal food crop feeding 30 % of the world population. Major threat to wheat production is the rust epidemics. This study was targeted towards identification and functional characterizations of micro(mi)RNAs and their target genes in wheat in response to leaf rust ingression. High-throughput sequencing was used for transcriptome-wide identification of miRNAs and their expression profiling in retort to leaf rust using mock and pathogen-inoculated resistant and susceptible near-isogenic wheat plants. A total of 1056 mature miRNAs were identified, of which 497 miRNAs were conserved and 559 miRNAs were novel. The pathogen-inoculated resistant plants manifested more miRNAs compared with the pathogen infected susceptible plants. The miRNA counts increased in susceptible isoline due to leaf rust, conversely, the counts decreased in the resistant isoline in response to pathogenesis illustrating precise spatial tuning of miRNAs during compatible and incompatible interaction. Stem-loop quantitative real-time PCR was used to profile 10 highly differentially expressed miRNAs obtained from high-throughput sequencing data. The spatio-temporal profiling validated the differential expression of miRNAs between the isolines as well as in retort to pathogen infection. Degradome analysis provided 701 predicted target genes associated with defense response, signal transduction, development, metabolism, and transcriptional regulation. The obtained results indicate that wheat isolines employ diverse arrays of miRNAs that modulate their target genes during compatible and incompatible interaction. Our findings contribute to increase knowledge on roles of microRNA in wheat-leaf rust interactions and could help in rust resistance breeding programs.

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

Characterization and complete genome sequence of a previously uncharacterized panicovirus from Bermuda grass detected by high throughput sequencing

USDA-ARS?s Scientific Manuscript database

Bermuda grass samples were examined by transmission electron microscopy and 28-30 nm spherical virus particles were observed. Total RNA from these plants was subjected to high throughput sequencing (HTS). The nearly full genome sequence of a previously uncharacterized Panicovirus was identified from...

Evaluation of Methods for de novo Genome assembly from High-throughput Sequencing Reads Reveals Dependencies that Affect the Quality of the Results

USDA-ARS?s Scientific Manuscript database

Recent developments in high-throughput sequencing technology have made low-cost sequencing an attractive approach for many genome analysis tasks. Increasing read lengths, improving quality and the production of increasingly larger numbers of usable sequences per instrument-run continue to make whole...

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

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

PubMed

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

2015-08-19

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-08-01

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

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.

High Throughput Sequence Analysis for Disease Resistance in Maize

USDA-ARS?s Scientific Manuscript database

Preliminary results of a computational analysis of high throughput sequencing data from Zea mays and the fungus Aspergillus are reported. The Illumina Genome Analyzer was used to sequence RNA samples from two strains of Z. mays (Va35 and Mp313) collected over a time course as well as several specie...

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.

Loeffler 4.0: Diagnostic Metagenomics.

PubMed

Höper, Dirk; Wylezich, Claudia; Beer, Martin

2017-01-01

A new world of possibilities for "virus discovery" was opened up with high-throughput sequencing becoming available in the last decade. While scientifically metagenomic analysis was established before the start of the era of high-throughput sequencing, the availability of the first second-generation sequencers was the kick-off for diagnosticians to use sequencing for the detection of novel pathogens. Today, diagnostic metagenomics is becoming the standard procedure for the detection and genetic characterization of new viruses or novel virus variants. Here, we provide an overview about technical considerations of high-throughput sequencing-based diagnostic metagenomics together with selected examples of "virus discovery" for animal diseases or zoonoses and metagenomics for food safety or basic veterinary research. © 2017 Elsevier Inc. All rights reserved.

The impact of sampling, PCR, and sequencing replication on discerning changes in drinking water bacterial community over diurnal time-scales.

PubMed

Bautista-de Los Santos, Quyen Melina; Schroeder, Joanna L; Blakemore, Oliver; Moses, Jonathan; Haffey, Mark; Sloan, William; Pinto, Ameet J

2016-03-01

High-throughput and deep DNA sequencing, particularly amplicon sequencing, is being increasingly utilized to reveal spatial and temporal dynamics of bacterial communities in drinking water systems. Whilst the sampling and methodological biases associated with PCR and sequencing have been studied in other environments, they have not been quantified for drinking water. These biases are likely to have the greatest effect on the ability to characterize subtle spatio-temporal patterns influenced by process/environmental conditions. In such cases, intra-sample variability may swamp any underlying small, systematic variation. To evaluate this, we undertook a study with replication at multiple levels including sampling sites, sample collection, PCR amplification, and high throughput sequencing of 16S rRNA amplicons. The variability inherent to the PCR amplification and sequencing steps is significant enough to mask differences between bacterial communities from replicate samples. This was largely driven by greater variability in detection of rare bacteria (relative abundance <0.01%) across PCR/sequencing replicates as compared to replicate samples. Despite this, we captured significant changes in bacterial community over diurnal time-scales and find that the extent and pattern of diurnal changes is specific to each sampling location. Further, we find diurnal changes in bacterial community arise due to differences in the presence/absence of the low abundance bacteria and changes in the relative abundance of dominant bacteria. Finally, we show that bacterial community composition is significantly different across sampling sites for time-periods during which there are typically rapid changes in water use. This suggests hydraulic changes (driven by changes in water demand) contribute to shaping the bacterial community in bulk drinking water over diurnal time-scales. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comprehensive analysis of the T-cell receptor beta chain gene in rhesus monkey by high throughput sequencing

PubMed Central

Li, Zhoufang; Liu, Guangjie; Tong, Yin; Zhang, Meng; Xu, Ying; Qin, Li; Wang, Zhanhui; Chen, Xiaoping; He, Jiankui

2015-01-01

Profiling immune repertoires by high throughput sequencing enhances our understanding of immune system complexity and immune-related diseases in humans. Previously, cloning and Sanger sequencing identified limited numbers of T cell receptor (TCR) nucleotide sequences in rhesus monkeys, thus their full immune repertoire is unknown. We applied multiplex PCR and Illumina high throughput sequencing to study the TCRβ of rhesus monkeys. We identified 1.26 million TCRβ sequences corresponding to 643,570 unique TCRβ sequences and 270,557 unique complementarity-determining region 3 (CDR3) gene sequences. Precise measurements of CDR3 length distribution, CDR3 amino acid distribution, length distribution of N nucleotide of junctional region, and TCRV and TCRJ gene usage preferences were performed. A comprehensive profile of rhesus monkey immune repertoire might aid human infectious disease studies using rhesus monkeys. PMID:25961410

Identification and profiling of novel microRNAs in the Brassica rapa genome based on small RNA deep sequencing

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are one of the functional non-coding small RNAs involved in the epigenetic control of the plant genome. Although plants contain both evolutionary conserved miRNAs and species-specific miRNAs within their genomes, computational methods often only identify evolutionary conserved miRNAs. The recent sequencing of the Brassica rapa genome enables us to identify miRNAs and their putative target genes. In this study, we sought to provide a more comprehensive prediction of B. rapa miRNAs based on high throughput small RNA deep sequencing. Results We sequenced small RNAs from five types of tissue: seedlings, roots, petioles, leaves, and flowers. By analyzing 2.75 million unique reads that mapped to the B. rapa genome, we identified 216 novel and 196 conserved miRNAs that were predicted to target approximately 20% of the genome’s protein coding genes. Quantitative analysis of miRNAs from the five types of tissue revealed that novel miRNAs were expressed in diverse tissues but their expression levels were lower than those of the conserved miRNAs. Comparative analysis of the miRNAs between the B. rapa and Arabidopsis thaliana genomes demonstrated that redundant copies of conserved miRNAs in the B. rapa genome may have been deleted after whole genome triplication. Novel miRNA members seemed to have spontaneously arisen from the B. rapa and A. thaliana genomes, suggesting the species-specific expansion of miRNAs. We have made this data publicly available in a miRNA database of B. rapa called BraMRs. The database allows the user to retrieve miRNA sequences, their expression profiles, and a description of their target genes from the five tissue types investigated here. Conclusions This is the first report to identify novel miRNAs from Brassica crops using genome-wide high throughput techniques. The combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome. The finding of numerous novel miRNAs, many with few target genes and low expression levels, suggests the rapid evolution of miRNA genes. The development of a miRNA database, BraMRs, enables us to integrate miRNA identification, target prediction, and functional annotation of target genes. BraMRs will represent a valuable public resource with which to study the epigenetic control of B. rapa and other closely related Brassica species. The database is available at the following link: http://bramrs.rna.kr [1]. PMID:23163954

Sequencing the Connectome

PubMed Central

Zador, Anthony M.; Dubnau, Joshua; Oyibo, Hassana K.; Zhan, Huiqing; Cao, Gang; Peikon, Ian D.

2012-01-01

Connectivity determines the function of neural circuits. Historically, circuit mapping has usually been viewed as a problem of microscopy, but no current method can achieve high-throughput mapping of entire circuits with single neuron precision. Here we describe a novel approach to determining connectivity. We propose BOINC (“barcoding of individual neuronal connections”), a method for converting the problem of connectivity into a form that can be read out by high-throughput DNA sequencing. The appeal of using sequencing is that its scale—sequencing billions of nucleotides per day is now routine—is a natural match to the complexity of neural circuits. An inexpensive high-throughput technique for establishing circuit connectivity at single neuron resolution could transform neuroscience research. PMID:23109909

A high-throughput and quantitative method to assess the mutagenic potential of translesion DNA synthesis

PubMed Central

Taggart, David J.; Camerlengo, Terry L.; Harrison, Jason K.; Sherrer, Shanen M.; Kshetry, Ajay K.; Taylor, John-Stephen; Huang, Kun; Suo, Zucai

2013-01-01

Cellular genomes are constantly damaged by endogenous and exogenous agents that covalently and structurally modify DNA to produce DNA lesions. Although most lesions are mended by various DNA repair pathways in vivo, a significant number of damage sites persist during genomic replication. Our understanding of the mutagenic outcomes derived from these unrepaired DNA lesions has been hindered by the low throughput of existing sequencing methods. Therefore, we have developed a cost-effective high-throughput short oligonucleotide sequencing assay that uses next-generation DNA sequencing technology for the assessment of the mutagenic profiles of translesion DNA synthesis catalyzed by any error-prone DNA polymerase. The vast amount of sequencing data produced were aligned and quantified by using our novel software. As an example, the high-throughput short oligonucleotide sequencing assay was used to analyze the types and frequencies of mutations upstream, downstream and at a site-specifically placed cis–syn thymidine–thymidine dimer generated individually by three lesion-bypass human Y-family DNA polymerases. PMID:23470999

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

PubMed

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

2015-04-01

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

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

High-Throughput Block Optical DNA Sequence Identification.

PubMed

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-throughput sequencing methods to study neuronal RNA-protein interactions.

PubMed

Ule, Jernej

2009-12-01

UV-cross-linking and RNase protection, combined with high-throughput sequencing, have provided global maps of RNA sites bound by individual proteins or ribosomes. Using a stringent purification protocol, UV-CLIP (UV-cross-linking and immunoprecipitation) was able to identify intronic and exonic sites bound by splicing regulators in mouse brain tissue. Ribosome profiling has been used to quantify ribosome density on budding yeast mRNAs under different environmental conditions. Post-transcriptional regulation in neurons requires high spatial and temporal precision, as is evident from the role of localized translational control in synaptic plasticity. It remains to be seen if the high-throughput methods can be applied quantitatively to study the dynamics of RNP (ribonucleoprotein) remodelling in specific neuronal populations during the neurodegenerative process. It is certain, however, that applications of new biochemical techniques followed by high-throughput sequencing will continue to provide important insights into the mechanisms of neuronal post-transcriptional regulation.

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

Optimization of High-Throughput Sequencing Kinetics for determining enzymatic rate constants of thousands of RNA substrates

PubMed Central

Niland, Courtney N.; Jankowsky, Eckhard; Harris, Michael E.

2016-01-01

Quantification of the specificity of RNA binding proteins and RNA processing enzymes is essential to understanding their fundamental roles in biological processes. High Throughput Sequencing Kinetics (HTS-Kin) uses high throughput sequencing and internal competition kinetics to simultaneously monitor the processing rate constants of thousands of substrates by RNA processing enzymes. This technique has provided unprecedented insight into the substrate specificity of the tRNA processing endonuclease ribonuclease P. Here, we investigate the accuracy and robustness of measurements associated with each step of the HTS-Kin procedure. We examine the effect of substrate concentration on the observed rate constant, determine the optimal kinetic parameters, and provide guidelines for reducing error in amplification of the substrate population. Importantly, we find that high-throughput sequencing, and experimental reproducibility contribute their own sources of error, and these are the main sources of imprecision in the quantified results when otherwise optimized guidelines are followed. PMID:27296633

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

High-Resolution Whole-Genome Sequencing Reveals That Specific Chromatin Domains from Most Human Chromosomes Associate with Nucleoli

PubMed Central

van Koningsbruggen, Silvana; Gierliński, Marek; Schofield, Pietá; Martin, David; Barton, Geoffey J.; Ariyurek, Yavuz; den Dunnen, Johan T.

2010-01-01

The nuclear space is mostly occupied by chromosome territories and nuclear bodies. Although this organization of chromosomes affects gene function, relatively little is known about the role of nuclear bodies in the organization of chromosomal regions. The nucleolus is the best-studied subnuclear structure and forms around the rRNA repeat gene clusters on the acrocentric chromosomes. In addition to rDNA, other chromatin sequences also surround the nucleolar surface and may even loop into the nucleolus. These additional nucleolar-associated domains (NADs) have not been well characterized. We present here a whole-genome, high-resolution analysis of chromatin endogenously associated with nucleoli. We have used a combination of three complementary approaches, namely fluorescence comparative genome hybridization, high-throughput deep DNA sequencing and photoactivation combined with time-lapse fluorescence microscopy. The data show that specific sequences from most human chromosomes, in addition to the rDNA repeat units, associate with nucleoli in a reproducible and heritable manner. NADs have in common a high density of AT-rich sequence elements, low gene density and a statistically significant enrichment in transcriptionally repressed genes. Unexpectedly, both the direct DNA sequencing and fluorescence photoactivation data show that certain chromatin loci can specifically associate with either the nucleolus, or the nuclear envelope. PMID:20826608

High-resolution whole-genome sequencing reveals that specific chromatin domains from most human chromosomes associate with nucleoli.

PubMed

van Koningsbruggen, Silvana; Gierlinski, Marek; Schofield, Pietá; Martin, David; Barton, Geoffey J; Ariyurek, Yavuz; den Dunnen, Johan T; Lamond, Angus I

2010-11-01

The nuclear space is mostly occupied by chromosome territories and nuclear bodies. Although this organization of chromosomes affects gene function, relatively little is known about the role of nuclear bodies in the organization of chromosomal regions. The nucleolus is the best-studied subnuclear structure and forms around the rRNA repeat gene clusters on the acrocentric chromosomes. In addition to rDNA, other chromatin sequences also surround the nucleolar surface and may even loop into the nucleolus. These additional nucleolar-associated domains (NADs) have not been well characterized. We present here a whole-genome, high-resolution analysis of chromatin endogenously associated with nucleoli. We have used a combination of three complementary approaches, namely fluorescence comparative genome hybridization, high-throughput deep DNA sequencing and photoactivation combined with time-lapse fluorescence microscopy. The data show that specific sequences from most human chromosomes, in addition to the rDNA repeat units, associate with nucleoli in a reproducible and heritable manner. NADs have in common a high density of AT-rich sequence elements, low gene density and a statistically significant enrichment in transcriptionally repressed genes. Unexpectedly, both the direct DNA sequencing and fluorescence photoactivation data show that certain chromatin loci can specifically associate with either the nucleolus, or the nuclear envelope.

The Impact of Data Fragmentation on High-Throughput Clinical Phenotyping

ERIC Educational Resources Information Center

Wei, Weiqi

2012-01-01

Subject selection is essential and has become the rate-limiting step for harvesting knowledge to advance healthcare through clinical research. Present manual approaches inhibit researchers from conducting deep and broad studies and drawing confident conclusions. High-throughput clinical phenotyping (HTCP), a recently proposed approach, leverages…

Development of carbon plasma-coated multiwell plates for high-throughput mass spectrometric analysis of highly lipophilic fermentation products.

PubMed

Heinig, Uwe; Scholz, Susanne; Dahm, Pia; Grabowy, Udo; Jennewein, Stefan

2010-08-01

Classical approaches to strain improvement and metabolic engineering rely on rapid qualitative and quantitative analyses of the metabolites of interest. As an analytical tool, mass spectrometry (MS) has proven to be efficient and nearly universally applicable for timely screening of metabolites. Furthermore, gas chromatography (GC)/MS- and liquid chromatography (LC)/MS-based metabolite screens can often be adapted to high-throughput formats. We recently engineered a Saccharomyces cerevisiae strain to produce taxa-4(5),11(12)-diene, the first pathway-committing biosynthetic intermediate for the anticancer drug Taxol, through the heterologous and homologous expression of several genes related to isoprenoid biosynthesis. To date, GC/MS- and LC/MS-based high-throughput methods have been inherently difficult to adapt to the screening of isoprenoid-producing microbial strains due to the need for extensive sample preparation of these often highly lipophilic compounds. In the current work, we examined different approaches to the high-throughput analysis of taxa-4(5),11(12)-diene biosynthesizing yeast strains in a 96-deep-well format. Carbon plasma coating of standard 96-deep-well polypropylene plates allowed us to circumvent the inherent solvent instability of commonly used deep-well plates. In addition, efficient adsorption of the target isoprenoid product by the coated plates allowed rapid and simple qualitative and quantitative analyses of the individual cultures. Copyright 2010 Elsevier Inc. All rights reserved.

Integrated design, execution, and analysis of arrayed and pooled CRISPR genome-editing experiments.

PubMed

Canver, Matthew C; Haeussler, Maximilian; Bauer, Daniel E; Orkin, Stuart H; Sanjana, Neville E; Shalem, Ophir; Yuan, Guo-Cheng; Zhang, Feng; Concordet, Jean-Paul; Pinello, Luca

2018-05-01

CRISPR (clustered regularly interspaced short palindromic repeats) genome-editing experiments offer enormous potential for the evaluation of genomic loci using arrayed single guide RNAs (sgRNAs) or pooled sgRNA libraries. Numerous computational tools are available to help design sgRNAs with optimal on-target efficiency and minimal off-target potential. In addition, computational tools have been developed to analyze deep-sequencing data resulting from genome-editing experiments. However, these tools are typically developed in isolation and oftentimes are not readily translatable into laboratory-based experiments. Here, we present a protocol that describes in detail both the computational and benchtop implementation of an arrayed and/or pooled CRISPR genome-editing experiment. This protocol provides instructions for sgRNA design with CRISPOR (computational tool for the design, evaluation, and cloning of sgRNA sequences), experimental implementation, and analysis of the resulting high-throughput sequencing data with CRISPResso (computational tool for analysis of genome-editing outcomes from deep-sequencing data). This protocol allows for design and execution of arrayed and pooled CRISPR experiments in 4-5 weeks by non-experts, as well as computational data analysis that can be performed in 1-2 d by both computational and noncomputational biologists alike using web-based and/or command-line versions.

High-throughput sequencing: a failure mode analysis.

PubMed

Yang, George S; Stott, Jeffery M; Smailus, Duane; Barber, Sarah A; Balasundaram, Miruna; Marra, Marco A; Holt, Robert A

2005-01-04

Basic manufacturing principles are becoming increasingly important in high-throughput sequencing facilities where there is a constant drive to increase quality, increase efficiency, and decrease operating costs. While high-throughput centres report failure rates typically on the order of 10%, the causes of sporadic sequencing failures are seldom analyzed in detail and have not, in the past, been formally reported. Here we report the results of a failure mode analysis of our production sequencing facility based on detailed evaluation of 9,216 ESTs generated from two cDNA libraries. Two categories of failures are described; process-related failures (failures due to equipment or sample handling) and template-related failures (failures that are revealed by close inspection of electropherograms and are likely due to properties of the template DNA sequence itself). Preventative action based on a detailed understanding of failure modes is likely to improve the performance of other production sequencing pipelines.

New Challenges of the Computation of Multiple Sequence Alignments in the High-Throughput Era (2010 JGI/ANL HPC Workshop)

ScienceCinema

Notredame, Cedric

2018-05-02

Cedric Notredame from the Centre for Genomic Regulation gives a presentation on New Challenges of the Computation of Multiple Sequence Alignments in the High-Throughput Era at the JGI/Argonne HPC Workshop on January 26, 2010.

Evaluation of Sequencing Approaches for High-Throughput Transcriptomics - (BOSC)

EPA Science Inventory

Whole-genome in vitro transcriptomics has shown the capability to identify mechanisms of action and estimates of potency for chemical-mediated effects in a toxicological framework, but with limited throughput and high cost. The generation of high-throughput global gene expression...

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

PubMed

Gopakumar, G; Hari Babu, K; Mishra, Deepak; Gorthi, Sai Siva; Sai Subrahmanyam, Gorthi R K

2017-01-01

Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: microfluidics-based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep-learning algorithms effectively classify the coarsely localized cell lines. We show that the designed deep belief network as well as the deeply pretrained convolutional neural network outperform the conventionally used decision systems and are important in the medical domain, where the availability of labeled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy-based tool for disease screening/triaging, especially in resource-limited settings.

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

PubMed Central

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

2014-01-01

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

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

Pseudouridines have context-dependent mutation and stop rates in high-throughput sequencing.

PubMed

Zhou, Katherine I; Clark, Wesley C; Pan, David W; Eckwahl, Matthew J; Dai, Qing; Pan, Tao

2018-05-11

The abundant RNA modification pseudouridine (Ψ) has been mapped transcriptome-wide by chemically modifying pseudouridines with carbodiimide and detecting the resulting reverse transcription stops in high-throughput sequencing. However, these methods have limited sensitivity and specificity, in part due to the use of reverse transcription stops. We sought to use mutations rather than just stops in sequencing data to identify pseudouridine sites. Here, we identify reverse transcription conditions that allow read-through of carbodiimide-modified pseudouridine (CMC-Ψ), and we show that pseudouridines in carbodiimide-treated human ribosomal RNA have context-dependent mutation and stop rates in high-throughput sequencing libraries prepared under these conditions. Furthermore, accounting for the context-dependence of mutation and stop rates can enhance the detection of pseudouridine sites. Similar approaches could contribute to the sequencing-based detection of many RNA modifications.

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.

Discovery of viruses and virus-like pathogens in pistachio using high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Pistachio (Pistacia vera L.) trees from the National Clonal Germplasm Repository (NCGR) and orchards in California were surveyed for viruses and virus-like agents by high-throughput sequencing (HTS). Analyses of 60 trees including clonal UCB-1 hybrid rootstock (P. atlantica × P. integerrima) identif...

Microbial community composition along a 50 000-year lacustrine sediment sequence

PubMed Central

Ariztegui, Daniel; Horn, Fabian; Kallmeyer, Jens; Orsi, William D

2018-01-01

Abstract For decades, microbial community composition in subseafloor sediments has been the focus of extensive studies. In deep lacustrine sediments, however, the taxonomic composition of microbial communities remains undercharacterized. Greater knowledge on microbial diversity in lacustrine sediments would improve our understanding of how environmental factors, and resulting selective pressures, shape subsurface biospheres in marine and freshwater sediments. Using high-throughput sequencing of 16S rRNA genes across high-resolution climate intervals covering the last 50 000 years in Laguna Potrok Aike, Argentina, we identified changes in microbial populations in response to both past environmental conditions and geochemical changes of the sediment during burial. Microbial communities in Holocene sediments were most diverse, reflecting a layering of taxa linked to electron acceptors availability. In deeper intervals, the data show that salinity, organic matter and the depositional conditions over the Last Glacial-interglacial cycle were all selective pressures in the deep lacustrine assemblage resulting in a genetically distinct biosphere from the surface dominated primarily by Bathyarchaeota and Atribacteria groups. However, similar to marine sediments, some dominant taxa in the shallow subsurface persisted into the subsurface as minor fraction of the community. The subsequent establishment of a deep subsurface community likely results from a combination of paleoenvironmental factors that have shaped the pool of available substrates, together with substrate depletion and/or reworking of organic matter with depth. PMID:29471361

Investigation of Human Cancers for Retrovirus by Low-Stringency Target Enrichment and High-Throughput Sequencing.

PubMed

Vinner, Lasse; Mourier, Tobias; Friis-Nielsen, Jens; Gniadecki, Robert; Dybkaer, Karen; Rosenberg, Jacob; Langhoff, Jill Levin; Cruz, David Flores Santa; Fonager, Jannik; Izarzugaza, Jose M G; Gupta, Ramneek; Sicheritz-Ponten, Thomas; Brunak, Søren; Willerslev, Eske; Nielsen, Lars Peter; Hansen, Anders Johannes

2015-08-19

Although nearly one fifth of all human cancers have an infectious aetiology, the causes for the majority of cancers remain unexplained. Despite the enormous data output from high-throughput shotgun sequencing, viral DNA in a clinical sample typically constitutes a proportion of host DNA that is too small to be detected. Sequence variation among virus genomes complicates application of sequence-specific, and highly sensitive, PCR methods. Therefore, we aimed to develop and characterize a method that permits sensitive detection of sequences despite considerable variation. We demonstrate that our low-stringency in-solution hybridization method enables detection of <100 viral copies. Furthermore, distantly related proviral sequences may be enriched by orders of magnitude, enabling discovery of hitherto unknown viral sequences by high-throughput sequencing. The sensitivity was sufficient to detect retroviral sequences in clinical samples. We used this method to conduct an investigation for novel retrovirus in samples from three cancer types. In accordance with recent studies our investigation revealed no retroviral infections in human B-cell lymphoma cells, cutaneous T-cell lymphoma or colorectal cancer biopsies. Nonetheless, our generally applicable method makes sensitive detection possible and permits sequencing of distantly related sequences from complex material.

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.

Bacterial diversity of the Colombian fermented milk "Suero Costeño" assessed by culturing and high-throughput sequencing and DGGE analysis of 16S rRNA gene amplicons.

PubMed

Motato, Karina Edith; Milani, Christian; Ventura, Marco; Valencia, Francia Elena; Ruas-Madiedo, Patricia; Delgado, Susana

2017-12-01

"Suero Costeño" (SC) is a traditional soured cream elaborated from raw milk in the Northern-Caribbean coast of Colombia. The natural microbiota that characterizes this popular Colombian fermented milk is unknown, although several culturing studies have previously been attempted. In this work, the microbiota associated with SC from three manufacturers in two regions, "Planeta Rica" (Córdoba) and "Caucasia" (Antioquia), was analysed by means of culturing methods in combination with high-throughput sequencing and DGGE analysis of 16S rRNA gene amplicons. The bacterial ecosystem of SC samples was revealed to be composed of lactic acid bacteria belonging to the Streptococcaceae and Lactobacillaceae families; the proportions and genera varying among manufacturers and region of elaboration. Members of the Lactobacillus acidophilus group, Lactocococcus lactis, Streptococcus infantarius and Streptococcus salivarius characterized this artisanal product. In comparison with culturing, the use of molecular in deep culture-independent techniques provides a more realistic picture of the overall bacterial communities residing in SC. Besides the descriptive purpose, these approaches will facilitate a rational strategy to follow (culture media and growing conditions) for the isolation of indigenous strains that allow standardization in the manufacture of SC. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-06-01

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

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.

Genome sequencing in microfabricated high-density picolitre reactors.

PubMed

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

2005-09-15

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

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

PubMed

Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

2018-03-09

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

Leveraging long read sequencing from a single individual to provide a comprehensive resource for benchmarking variant calling methods

PubMed Central

Mu, John C.; Tootoonchi Afshar, Pegah; Mohiyuddin, Marghoob; Chen, Xi; Li, Jian; Bani Asadi, Narges; Gerstein, Mark B.; Wong, Wing H.; Lam, Hugo Y. K.

2015-01-01

A high-confidence, comprehensive human variant set is critical in assessing accuracy of sequencing algorithms, which are crucial in precision medicine based on high-throughput sequencing. Although recent works have attempted to provide such a resource, they still do not encompass all major types of variants including structural variants (SVs). Thus, we leveraged the massive high-quality Sanger sequences from the HuRef genome to construct by far the most comprehensive gold set of a single individual, which was cross validated with deep Illumina sequencing, population datasets, and well-established algorithms. It was a necessary effort to completely reanalyze the HuRef genome as its previously published variants were mostly reported five years ago, suffering from compatibility, organization, and accuracy issues that prevent their direct use in benchmarking. Our extensive analysis and validation resulted in a gold set with high specificity and sensitivity. In contrast to the current gold sets of the NA12878 or HS1011 genomes, our gold set is the first that includes small variants, deletion SVs and insertion SVs up to a hundred thousand base-pairs. We demonstrate the utility of our HuRef gold set to benchmark several published SV detection tools. PMID:26412485

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.

Uniform, optimal signal processing of mapped deep-sequencing data.

PubMed

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

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.

Pediatric Glioblastoma Therapies Based on Patient-Derived Stem Cell Resources

DTIC Science & Technology

2014-11-01

genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate gene...and genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate...PRISM 7900 Sequence Detection System ( Genomics Resource, FHCRC). Relative transcript abundance was analyzed using the 2−ΔΔCt method. TRIzol (Invitrogen

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

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

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

High-Throughput Sequencing of RNA Silencing-Associated Small RNAs in Olive (Olea europaea L.)

PubMed Central

Donaire, Livia; Pedrola, Laia; de la Rosa, Raúl; Llave, César

2011-01-01

Small RNAs (sRNAs) of 20 to 25 nucleotides (nt) in length maintain genome integrity and control gene expression in a multitude of developmental and physiological processes. Despite RNA silencing has been primarily studied in model plants, the advent of high-throughput sequencing technologies has enabled profiling of the sRNA component of more than 40 plant species. Here, we used deep sequencing and molecular methods to report the first inventory of sRNAs in olive (Olea europaea L.). sRNA libraries prepared from juvenile and adult shoots revealed that the 24-nt class dominates the sRNA transcriptome and atypically accumulates to levels never seen in other plant species, suggesting an active role of heterochromatin silencing in the maintenance and integrity of its large genome. A total of 18 known miRNA families were identified in the libraries. Also, 5 other sRNAs derived from potential hairpin-like precursors remain as plausible miRNA candidates. RNA blots confirmed miRNA expression and suggested tissue- and/or developmental-specific expression patterns. Target mRNAs of conserved miRNAs were computationally predicted among the olive cDNA collection and experimentally validated through endonucleolytic cleavage assays. Finally, we use expression data to uncover genetic components of the miR156, miR172 and miR390/TAS3-derived trans-acting small interfering RNA (tasiRNA) regulatory nodes, suggesting that these interactive networks controlling developmental transitions are fully operational in olive. PMID:22140484

Characterization of the indigenous microflora in raw and pasteurized buffalo milk during storage at refrigeration temperature by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

The effect of refrigeration on bacterial communities within raw and pasteurized buffalo milk was studied using high-throughput sequencing. High quality samples of raw buffalo milk were obtained from five dairy farms in the Guangxi province of China. A sample of each milk was pasteurized, and both r...

Targeted Capture and High-Throughput Sequencing Using Molecular Inversion Probes (MIPs).

PubMed

Cantsilieris, Stuart; Stessman, Holly A; Shendure, Jay; Eichler, Evan E

2017-01-01

Molecular inversion probes (MIPs) in combination with massively parallel DNA sequencing represent a versatile, yet economical tool for targeted sequencing of genomic DNA. Several thousand genomic targets can be selectively captured using long oligonucleotides containing unique targeting arms and universal linkers. The ability to append sequencing adaptors and sample-specific barcodes allows large-scale pooling and subsequent high-throughput sequencing at relatively low cost per sample. Here, we describe a "wet bench" protocol detailing the capture and subsequent sequencing of >2000 genomic targets from 192 samples, representative of a single lane on the Illumina HiSeq 2000 platform.

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.

Tackling Drug Resistant Infection Outbreaks of Global Pandemic Escherichia coli ST131 Using Evolutionary and Epidemiological Genomics

PubMed Central

Downing, Tim

2015-01-01

High-throughput molecular screening is required to investigate the origin and diffusion of antimicrobial resistance in pathogen outbreaks. The most frequent cause of human infection is Escherichia coli, which is dominated by sequence type 131 (ST131)—a set of rapidly radiating pandemic clones. The highly infectious clades of ST131 originated firstly by a mutation enhancing conjugation and adhesion. Secondly, single-nucleotide polymorphisms occurred enabling fluoroquinolone-resistance, which is near-fixed in all ST131. Thirdly, broader resistance through beta-lactamases has been gained and lost frequently, symptomatic of conflicting environmental selective effects. This flexible approach to gene exchange is worrying and supports the proposition that ST131 will develop an even wider range of plasmid and chromosomal elements promoting antimicrobial resistance. To stop ST131, deep genome sequencing is required to understand the origin, evolution and spread of antimicrobial resistance genes. Phylogenetic methods that decipher past events can predict future patterns of virulence and transmission based on genetic signatures of adaptation and gene exchange. Both the effect of partial antimicrobial exposure and cell dormancy caused by variation in gene expression may accelerate the development of resistance. High-throughput sequencing can decode measurable evolution of cell populations within patients associated with systems-wide changes in gene expression during treatments. A multi-faceted approach can enhance assessment of antimicrobial resistance in E. coli ST131 by examining transmission dynamics between hosts to achieve a goal of pre-empting resistance before it emerges by optimising antimicrobial treatment protocols. PMID:27682088

Target enrichment and high-throughput sequencing of 80 ribosomal protein genes to identify mutations associated with Diamond-Blackfan anaemia.

PubMed

Gerrard, Gareth; Valgañón, Mikel; Foong, Hui En; Kasperaviciute, Dalia; Iskander, Deena; Game, Laurence; Müller, Michael; Aitman, Timothy J; Roberts, Irene; de la Fuente, Josu; Foroni, Letizia; Karadimitris, Anastasios

2013-08-01

Diamond-Blackfan anaemia (DBA) is caused by inactivating mutations in ribosomal protein (RP) genes, with mutations in 13 of the 80 RP genes accounting for 50-60% of cases. The remaining 40-50% cases may harbour mutations in one of the remaining RP genes, but the very low frequencies render conventional genetic screening as challenging. We, therefore, applied custom enrichment technology combined with high-throughput sequencing to screen all 80 RP genes. Using this approach, we identified and validated inactivating mutations in 15/17 (88%) DBA patients. Target enrichment combined with high-throughput sequencing is a robust and improved methodology for the genetic diagnosis of DBA. © 2013 John Wiley & Sons Ltd.

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

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

2010-12-10

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

A novel approach to tracking antigen-experienced CD4 T cells into functional compartments via tandem deep and shallow TCR clonotyping.

PubMed

Estorninho, Megan; Gibson, Vivienne B; Kronenberg-Versteeg, Deborah; Liu, Yuk-Fun; Ni, Chester; Cerosaletti, Karen; Peakman, Mark

2013-12-01

Extensive diversity in the human repertoire of TCRs for Ag is both a cornerstone of effective adaptive immunity that enables host protection against a multiplicity of pathogens and a weakness that gives rise to potential pathological self-reactivity. The complexity arising from diversity makes detection and tracking of single Ag-specific CD4 T cells (ASTs) involved in these immune responses challenging. We report a tandem, multistep process to quantify rare TCRβ-chain variable sequences of ASTs in large polyclonal populations. The approach combines deep high-throughput sequencing (HTS) within functional CD4 T cell compartments, such as naive/memory cells, with shallow, multiple identifier-based HTS of ASTs identified by activation marker upregulation after short-term Ag stimulation in vitro. We find that clonotypes recognizing HLA class II-restricted epitopes of both pathogen-derived Ags and self-Ags are oligoclonal and typically private. Clonotype tracking within an individual reveals private AST clonotypes resident in the memory population, as would be expected, representing clonal expansions (identical nucleotide sequence; "ultraprivate"). Other AST clonotypes share CDR3β amino acid sequences through convergent recombination and are found in memory populations of multiple individuals. Tandem HTS-based clonotyping will facilitate studying AST dynamics, epitope spreading, and repertoire changes that arise postvaccination and following Ag-specific immunotherapies for cancer and autoimmune disease.

Molecular characterization of a novel rhabdovirus infecting blackcurrant identified by high-throughput sequencing.

PubMed

Wu, L-P; Yang, T; Liu, H-W; Postman, J; Li, R

2018-05-01

A large contig with sequence similarities to several nucleorhabdoviruses was identified by high-throughput sequencing analysis from a black currant (Ribes nigrum L.) cultivar. The complete genome sequence of this new nucleorhabdovirus is 14,432 nucleotides long. Its genomic organization is very similar to those of unsegmented plant rhabdoviruses, containing six open reading frames in the order 3'-N-P-P3-M-G-L-5. The virus, which is provisionally named "black currant-associated rhabdovirus", is 41-52% identical in its genome nucleotide sequence to other nucleorhabdoviruses and may represent a new species in the genus Nucleorhabdovirus.

Quantitative Assessment of RNA-Protein Interactions with High Throughput Sequencing - RNA Affinity Profiling (HiTS-RAP)

PubMed Central

Ozer, Abdullah; Tome, Jacob M.; Friedman, Robin C.; Gheba, Dan; Schroth, Gary P.; Lis, John T.

2016-01-01

Because RNA-protein interactions play a central role in a wide-array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the High Throughput Sequencing-RNA Affinity Profiling (HiTS-RAP) assay, which couples sequencing on an Illumina GAIIx with the quantitative assessment of one or several proteins’ interactions with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of EGFP and NELF-E proteins with their corresponding canonical and mutant RNA aptamers. Here, we provide a detailed protocol for HiTS-RAP, which can be completed in about a month (8 days hands-on time) including the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, high-throughput sequencing and protein binding with GAIIx, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, RNA-MaP and RBNS. A successful HiTS-RAP experiment provides the sequence and binding curves for approximately 200 million RNAs in a single experiment. PMID:26182240

A high-throughput multiplex method adapted for GMO detection.

PubMed

Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

2008-12-24

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

Genomic analysis suggests that mRNA destabilization by the microprocessor is specialized for the auto-regulation of Dgcr8.

PubMed

Shenoy, Archana; Blelloch, Robert

2009-09-11

The Microprocessor, containing the RNA binding protein Dgcr8 and RNase III enzyme Drosha, is responsible for processing primary microRNAs to precursor microRNAs. The Microprocessor regulates its own levels by cleaving hairpins in the 5'UTR and coding region of the Dgcr8 mRNA, thereby destabilizing the mature transcript. To determine whether the Microprocessor has a broader role in directly regulating other coding mRNA levels, we integrated results from expression profiling and ultra high-throughput deep sequencing of small RNAs. Expression analysis of mRNAs in wild-type, Dgcr8 knockout, and Dicer knockout mouse embryonic stem (ES) cells uncovered mRNAs that were specifically upregulated in the Dgcr8 null background. A number of these transcripts had evolutionarily conserved predicted hairpin targets for the Microprocessor. However, analysis of deep sequencing data of 18 to 200nt small RNAs in mouse ES, HeLa, and HepG2 indicates that exonic sequence reads that map in a pattern consistent with Microprocessor activity are unique to Dgcr8. We conclude that the Microprocessor's role in directly destabilizing coding mRNAs is likely specifically targeted to Dgcr8 itself, suggesting a specialized cellular mechanism for gene auto-regulation.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

PubMed

Polishchuk, Maya; Paz, Inbal; Yakhini, Zohar; Mandel-Gutfreund, Yael

2018-05-25

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

RIKEN Integrated Sequence Analysis (RISA) System—384-Format Sequencing Pipeline with 384 Multicapillary Sequencer

PubMed Central

Shibata, Kazuhiro; Itoh, Masayoshi; Aizawa, Katsunori; Nagaoka, Sumiharu; Sasaki, Nobuya; Carninci, Piero; Konno, Hideaki; Akiyama, Junichi; Nishi, Katsuo; Kitsunai, Tokuji; Tashiro, Hideo; Itoh, Mari; Sumi, Noriko; Ishii, Yoshiyuki; Nakamura, Shin; Hazama, Makoto; Nishine, Tsutomu; Harada, Akira; Yamamoto, Rintaro; Matsumoto, Hiroyuki; Sakaguchi, Sumito; Ikegami, Takashi; Kashiwagi, Katsuya; Fujiwake, Syuji; Inoue, Kouji; Togawa, Yoshiyuki; Izawa, Masaki; Ohara, Eiji; Watahiki, Masanori; Yoneda, Yuko; Ishikawa, Tomokazu; Ozawa, Kaori; Tanaka, Takumi; Matsuura, Shuji; Kawai, Jun; Okazaki, Yasushi; Muramatsu, Masami; Inoue, Yorinao; Kira, Akira; Hayashizaki, Yoshihide

2000-01-01

The RIKEN high-throughput 384-format sequencing pipeline (RISA system) including a 384-multicapillary sequencer (the so-called RISA sequencer) was developed for the RIKEN mouse encyclopedia project. The RISA system consists of colony picking, template preparation, sequencing reaction, and the sequencing process. A novel high-throughput 384-format capillary sequencer system (RISA sequencer system) was developed for the sequencing process. This system consists of a 384-multicapillary auto sequencer (RISA sequencer), a 384-multicapillary array assembler (CAS), and a 384-multicapillary casting device. The RISA sequencer can simultaneously analyze 384 independent sequencing products. The optical system is a scanning system chosen after careful comparison with an image detection system for the simultaneous detection of the 384-capillary array. This scanning system can be used with any fluorescent-labeled sequencing reaction (chain termination reaction), including transcriptional sequencing based on RNA polymerase, which was originally developed by us, and cycle sequencing based on thermostable DNA polymerase. For long-read sequencing, 380 out of 384 sequences (99.2%) were successfully analyzed and the average read length, with more than 99% accuracy, was 654.4 bp. A single RISA sequencer can analyze 216 kb with >99% accuracy in 2.7 h (90 kb/h). For short-read sequencing to cluster the 3′ end and 5′ end sequencing by reading 350 bp, 384 samples can be analyzed in 1.5 h. We have also developed a RISA inoculator, RISA filtrator and densitometer, RISA plasmid preparator which can handle throughput of 40,000 samples in 17.5 h, and a high-throughput RISA thermal cycler which has four 384-well sites. The combination of these technologies allowed us to construct the RISA system consisting of 16 RISA sequencers, which can process 50,000 DNA samples per day. One haploid genome shotgun sequence of a higher organism, such as human, mouse, rat, domestic animals, and plants, can be revealed by seven RISA systems within one month. PMID:11076861

Increasing ecological inference from high throughput sequencing of fungi in the environment through a tagging approach

Treesearch

D. Lee Taylor; Michael G. Booth; Jack W. McFarland; Ian C. Herriott; Niall J. Lennon; Chad Nusbaum; Thomas G. Marr

2008-01-01

High throughput sequencing methods are widely used in analyses of microbial diversity but are generally applied to small numbers of samples, which precludes charaterization of patterns of microbial diversity across space and time. We have designed a primer-tagging approach that allows pooling and subsequent sorting of numerous samples, which is directed to...

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

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

PubMed Central

Gibson, Joel F.; Shokralla, Shadi; Curry, Colin; Baird, Donald J.; Monk, Wendy A.; King, Ian; Hajibabaei, Mehrdad

2015-01-01

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users. PMID:26488407

A remark on copy number variation detection methods.

PubMed

Li, Shuo; Dou, Xialiang; Gao, Ruiqi; Ge, Xinzhou; Qian, Minping; Wan, Lin

2018-01-01

Copy number variations (CNVs) are gain and loss of DNA sequence of a genome. High throughput platforms such as microarrays and next generation sequencing technologies (NGS) have been applied for genome wide copy number losses. Although progress has been made in both approaches, the accuracy and consistency of CNV calling from the two platforms remain in dispute. In this study, we perform a deep analysis on copy number losses on 254 human DNA samples, which have both SNP microarray data and NGS data publicly available from Hapmap Project and 1000 Genomes Project respectively. We show that the copy number losses reported from Hapmap Project and 1000 Genome Project only have < 30% overlap, while these reports are required to have cross-platform (e.g. PCR, microarray and high-throughput sequencing) experimental supporting by their corresponding projects, even though state-of-art calling methods were employed. On the other hand, copy number losses are found directly from HapMap microarray data by an accurate algorithm, i.e. CNVhac, almost all of which have lower read mapping depth in NGS data; furthermore, 88% of which can be supported by the sequences with breakpoint in NGS data. Our results suggest the ability of microarray calling CNVs and the possible introduction of false negatives from the unessential requirement of the additional cross-platform supporting. The inconsistency of CNV reports from Hapmap Project and 1000 Genomes Project might result from the inadequate information containing in microarray data, the inconsistent detection criteria, or the filtration effect of cross-platform supporting. The statistical test on CNVs called from CNVhac show that the microarray data can offer reliable CNV reports, and majority of CNV candidates can be confirmed by raw sequences. Therefore, the CNV candidates given by a good caller could be highly reliable without cross-platform supporting, so additional experimental information should be applied in need instead of necessarily.

Characterization and complete genome sequence of a panicovirus from Bermuda grass by high-throughput sequencing.

PubMed

Tahir, Muhammad N; Lockhart, Ben; Grinstead, Samuel; Mollov, Dimitre

2017-04-01

Bermuda grass samples were examined by transmission electron microscopy and 28-30 nm spherical virus particles were observed. Total RNA from these plants was subjected to high-throughput sequencing (HTS). The nearly full genome sequence of a panicovirus was identified from one HTS scaffold. Sanger sequencing was used to confirm the HTS results and complete the genome sequence of 4404 nt. This virus was provisionally named Bermuda grass latent virus (BGLV). Its predicted open reading frames follow the typical arrangement of the genus Panicovirus. Based on sequence comparisons and phylogenetic analyses BGLV differs from other viruses and therefore taxonomically it is a new member of the genus Panicovirus, family Tombusviridae.

Integrated digital error suppression for improved detection of circulating tumor DNA

PubMed Central

Kurtz, David M.; Chabon, Jacob J.; Scherer, Florian; Stehr, Henning; Liu, Chih Long; Bratman, Scott V.; Say, Carmen; Zhou, Li; Carter, Justin N.; West, Robert B.; Sledge, George W.; Shrager, Joseph B.; Loo, Billy W.; Neal, Joel W.; Wakelee, Heather A.; Diehn, Maximilian; Alizadeh, Ash A.

2016-01-01

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by ~3 fold, and synergize when combined to yield ~15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to clinical non-small cell lung cancer (NSCLC) samples, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and 96% specificity and detection of ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings. PMID:27018799

Combining high-throughput sequencing with fruit body surveys reveals contrasting life-history strategies in fungi

PubMed Central

Ovaskainen, Otso; Schigel, Dmitry; Ali-Kovero, Heini; Auvinen, Petri; Paulin, Lars; Nordén, Björn; Nordén, Jenni

2013-01-01

Before the recent revolution in molecular biology, field studies on fungal communities were mostly confined to fruit bodies, whereas mycelial interactions were studied in the laboratory. Here we combine high-throughput sequencing with a fruit body inventory to study simultaneously mycelial and fruit body occurrences in a community of fungi inhabiting dead wood of Norway spruce. We studied mycelial occurrence by extracting DNA from wood samples followed by 454-sequencing of the ITS1 and ITS2 regions and an automated procedure for species identification. In total, we detected 198 species as mycelia and 137 species as fruit bodies. The correlation between mycelial and fruit body occurrences was high for the majority of the species, suggesting that high-throughput sequencing can successfully characterize the dominating fungal communities, despite possible biases related to sampling, PCR, sequencing and molecular identification. We used the fruit body and molecular data to test hypothesized links between life history and population dynamic parameters. We show that the species that have on average a high mycelial abundance also have a high fruiting rate and produce large fruit bodies, leading to a positive feedback loop in their population dynamics. Earlier studies have shown that species with specialized resource requirements are rarely seen fruiting, for which reason they are often classified as red-listed. We show with the help of high-throughput sequencing that some of these species are more abundant as mycelium in wood than what could be expected from their occurrence as fruit bodies. PMID:23575372

Sources of PCR-induced distortions in high-throughput sequencing data sets

PubMed Central

Kebschull, Justus M.; Zador, Anthony M.

2015-01-01

PCR permits the exponential and sequence-specific amplification of DNA, even from minute starting quantities. PCR is a fundamental step in preparing DNA samples for high-throughput sequencing. However, there are errors associated with PCR-mediated amplification. Here we examine the effects of four important sources of error—bias, stochasticity, template switches and polymerase errors—on sequence representation in low-input next-generation sequencing libraries. We designed a pool of diverse PCR amplicons with a defined structure, and then used Illumina sequencing to search for signatures of each process. We further developed quantitative models for each process, and compared predictions of these models to our experimental data. We find that PCR stochasticity is the major force skewing sequence representation after amplification of a pool of unique DNA amplicons. Polymerase errors become very common in later cycles of PCR but have little impact on the overall sequence distribution as they are confined to small copy numbers. PCR template switches are rare and confined to low copy numbers. Our results provide a theoretical basis for removing distortions from high-throughput sequencing data. In addition, our findings on PCR stochasticity will have particular relevance to quantification of results from single cell sequencing, in which sequences are represented by only one or a few molecules. PMID:26187991

Research progress of plant population genomics based on high-throughput sequencing.

PubMed

Wang, Yun-sheng

2016-08-01

Population genomics, a new paradigm for population genetics, combine the concepts and techniques of genomics with the theoretical system of population genetics and improve our understanding of microevolution through identification of site-specific effect and genome-wide effects using genome-wide polymorphic sites genotypeing. With the appearance and improvement of the next generation high-throughput sequencing technology, the numbers of plant species with complete genome sequences increased rapidly and large scale resequencing has also been carried out in recent years. Parallel sequencing has also been done in some plant species without complete genome sequences. These studies have greatly promoted the development of population genomics and deepened our understanding of the genetic diversity, level of linking disequilibium, selection effect, demographical history and molecular mechanism of complex traits of relevant plant population at a genomic level. In this review, I briely introduced the concept and research methods of population genomics and summarized the research progress of plant population genomics based on high-throughput sequencing. I also discussed the prospect as well as existing problems of plant population genomics in order to provide references for related studies.

Mobile element biology – new possibilities with high-throughput sequencing

PubMed Central

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

2014-01-01

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

Mapping of disease-associated variants in admixed populations

PubMed Central

2011-01-01

Recent developments in high-throughput genotyping and whole-genome sequencing will enhance the identification of disease loci in admixed populations. We discuss how a more refined estimation of ancestry benefits both admixture mapping and association mapping, making disease loci identification in admixed populations more powerful. High-throughput genotyping and sequencing will enable refined estimation of ancestry, thus enhancing disease loci identification in admixed populations PMID:21635713

HTP-OligoDesigner: An Online Primer Design Tool for High-Throughput Gene Cloning and Site-Directed Mutagenesis.

PubMed

Camilo, Cesar M; Lima, Gustavo M A; Maluf, Fernando V; Guido, Rafael V C; Polikarpov, Igor

2016-01-01

Following burgeoning genomic and transcriptomic sequencing data, biochemical and molecular biology groups worldwide are implementing high-throughput cloning and mutagenesis facilities in order to obtain a large number of soluble proteins for structural and functional characterization. Since manual primer design can be a time-consuming and error-generating step, particularly when working with hundreds of targets, the automation of primer design process becomes highly desirable. HTP-OligoDesigner was created to provide the scientific community with a simple and intuitive online primer design tool for both laboratory-scale and high-throughput projects of sequence-independent gene cloning and site-directed mutagenesis and a Tm calculator for quick queries.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

PubMed Central

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G.; Rigoutsos, Isidore

2017-01-01

Abstract Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. PMID:28108659

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

PubMed Central

2014-01-01

Background RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. Results We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality. Conclusions eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory. PMID:24593312

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

PubMed

Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

2014-03-05

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

Understanding microalgal species composition and contributions in Antarctic glacial melt water through rbcL high throughput sequencing

NASA Astrophysics Data System (ADS)

Barretto, K. M.; Kalmbach, A. J.; de la Torre, J. R.; Falcón, L. I.; Carpenter, E. J.

2016-02-01

The McMurdo Dry Valleys (MDV) in Antarctica present unique research opportunities, both because of the understudied biogeochemical impact of their microbial communities, and their sensitivity to climate change. Despite harsh desiccation, pH, and salinity stress, summer glacial melt water supports life in the MDV in the form of algal mats. These mat communities are complex in structure, with a network of dominant cyanobacteria interspersed with heterotrophic diazotrophs, smaller photoautotrophs, and thick extracellular polymeric substances. Due to their complexity, standard microscopy yields a limited understanding of community assemblages. Our previous high throughput sequencing (HTS) approaches focusing on 16S rRNA have profiled communities with understudied photosynthetic phyla such as Acidobacteria, Gemmatimonadetes, and Chloroflexi. To characterize these phototrophic communities, we are interested in (1) understanding their temporal dynamics and how the dominant cyanobacterial species influence community composition, (2) modeling how pH, nutrients, soil wetness, and temperature act as multivariate drivers of community composition, and (3) establishing a pipeline for HTS of the rbcL gene - which encodes the large subunit of the ubiquitous photosynthetic protein RuBisCO. Our initial screening of community DNA from MDV algal mats has shown the presence of Form IA, IB, and IC cbbL (an rbcL ortholog), and Form ID rbcL - indicating a relatively high degree of photoautotrophic diversity. Soil wetness drives anoxic conditions and we see that it shifts overall microbial composition - we expect photoautotrophs to respond similarly. We also expect photoautotrophic assemblages to shift with pH and soil nutrients. Our deep sequencing efforts suggest an inconsistency between indexing primers and algal DNA that could underestimate cyanobacterial and overestimate eukaryotic abundance. Resolving these issues with new approaches will allow us to more fully understand the dynamics of the MDV.

Transcriptome profiling analysis of Mactra veneriformis by deep sequencing after exposure to 2,2',4,4'-tetrabromodiphenyl ether

NASA Astrophysics Data System (ADS)

Shi, Pengju; Dong, Shihang; Zhang, Huanjun; Wang, Peiliang; Niu, Zhuang; Fang, Yan

2018-03-01

Polybrominated diphenyl ethers (PBDEs) are ubiquitous global pollutants, which are known to have immune, development, reproduction, and endocrine toxicity in aquatic organisms, including bivalves. 2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) is the predominant PBDE congener detected in environmental samples and the tissues of organisms. However, the mechanism of its toxicity remains unclear. In this study, high-throughput sequencing was performed using the clam Mactra veneriformis, a good model for toxicological research, to clarify the transcriptomic response to BDE-47 and the mechanism responsible for the toxicity of BDE-47. The clams were exposed to 5 μg/L BDE-47 for 3 days and the digestive glands were sampled for high-throughput sequencing analysis. We obtained 127 648, 154 225, and 124 985 unigenes by de novo assembly of the control group reads (CG), BDE-47 group reads (BDEG), and control and BDE-47 reads (CG & BDEG), respectively. We annotated 32 176 unigenes from the CG & BDEG reads using the NR database. We categorized 24 401 unigenes into 25 functional COG clusters and 21 749 unigenes were assigned to 259 KEGG pathways. Moreover, 17 625 differentially expressed genes (DEGs) were detected, with 10 028 upregulated DEGs and 7 597 downregulated DEGs. Functional enrichment analysis showed that the DEGs were involved with detoxification, antioxidant defense, immune response, apoptosis, and other functions. The mRNA expression levels of 26 DEGs were verified by quantitative real-time PCR, which demonstrated the high agreement between the two methods. These results provide a good basis for future research using the M. veneriformis model into the mechanism of PBDEs toxicity and molecular biomarkers for BDE-47 pollution. The regulation and interaction of the DEGs would be studied in the future for clarifying the mechanism of PBDEs toxicity.

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

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

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE PAGES

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

2015-12-09

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

PubMed Central

2011-01-01

Background High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity ≥2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus. PMID:21492434

CMV reactivation drives posttransplant T-cell reconstitution and results in defects in the underlying TCRβ repertoire

PubMed Central

Suessmuth, Yvonne; Mukherjee, Rithun; Watkins, Benjamin; Koura, Divya T.; Finstermeier, Knut; Desmarais, Cindy; Stempora, Linda; Horan, John T.; Langston, Amelia; Qayed, Muna; Khoury, Hanna J.; Grizzle, Audrey; Cheeseman, Jennifer A.; Conger, Jason A.; Robertson, Jennifer; Garrett, Aneesah; Kirk, Allan D.; Waller, Edmund K.; Blazar, Bruce R.; Mehta, Aneesh K.; Robins, Harlan S.

2015-01-01

Although cytomegalovirus (CMV) reactivation has long been implicated in posttransplant immune dysfunction, the molecular mechanisms that drive this phenomenon remain undetermined. To address this, we combined multiparameter flow cytometric analysis and T-cell subpopulation sorting with high-throughput sequencing of the T-cell repertoire, to produce a thorough evaluation of the impact of CMV reactivation on T-cell reconstitution after unrelated-donor hematopoietic stem cell transplant. We observed that CMV reactivation drove a >50-fold specific expansion of Granzyme Bhigh/CD28low/CD57high/CD8+ effector memory T cells (Tem) and resulted in a linked contraction of all naive T cells, including CD31+/CD4+ putative thymic emigrants. T-cell receptor β (TCRβ) deep sequencing revealed a striking contraction of CD8+ Tem diversity due to CMV-specific clonal expansions in reactivating patients. In addition to querying the topography of the expanding CMV-specific T-cell clones, deep sequencing allowed us, for the first time, to exhaustively evaluate the underlying TCR repertoire. Our results reveal new evidence for significant defects in the underlying CD8 Tem TCR repertoire in patients who reactivate CMV, providing the first molecular evidence that, in addition to driving expansion of virus-specific cells, CMV reactivation has a detrimental impact on the integrity and heterogeneity of the rest of the T-cell repertoire. This trial was registered at www.clinicaltrials.gov as #NCT01012492. PMID:25852054

Characterization of the fecal microbiota using high-throughput sequencing reveals a stable microbial community during storage.

PubMed

Carroll, Ian M; Ringel-Kulka, Tamar; Siddle, Jennica P; Klaenhammer, Todd R; Ringel, Yehuda

2012-01-01

The handling and treatment of biological samples is critical when characterizing the composition of the intestinal microbiota between different ecological niches or diseases. Specifically, exposure of fecal samples to room temperature or long term storage in deep freezing conditions may alter the composition of the microbiota. Thus, we stored fecal samples at room temperature and monitored the stability of the microbiota over twenty four hours. We also investigated the stability of the microbiota in fecal samples during a six month storage period at -80°C. As the stability of the fecal microbiota may be affected by intestinal disease, we analyzed two healthy controls and two patients with irritable bowel syndrome (IBS). We used high-throughput pyrosequencing of the 16S rRNA gene to characterize the microbiota in fecal samples stored at room temperature or -80°C at six and seven time points, respectively. The composition of microbial communities in IBS patients and healthy controls were determined and compared using the Quantitative Insights Into Microbial Ecology (QIIME) pipeline. The composition of the microbiota in fecal samples stored for different lengths of time at room temperature or -80°C clustered strongly based on the host each sample originated from. Our data demonstrates that fecal samples exposed to room or deep freezing temperatures for up to twenty four hours and six months, respectively, exhibit a microbial composition and diversity that shares more identity with its host of origin than any other sample.

High-Throughput Sequencing for Detection of Subpopulations of Bacteria Not Previously Associated with Artisanal Cheeses

PubMed Central

Quigley, Lisa; O'Sullivan, Orla; Beresford, Tom P.; Ross, R. Paul; Fitzgerald, Gerald F.

2012-01-01

Here, high-throughput sequencing was employed to reveal the highly diverse bacterial populations present in 62 Irish artisanal cheeses and, in some cases, associated cheese rinds. Using this approach, we revealed the presence of several genera not previously associated with cheese, including Faecalibacterium, Prevotella, and Helcococcus and, for the first time, detected the presence of Arthrobacter and Brachybacterium in goats' milk cheese. Our analysis confirmed many previously observed patterns, such as the dominance of typical cheese bacteria, the fact that the microbiota of raw and pasteurized milk cheeses differ, and that the level of cheese maturation has a significant influence on Lactobacillus populations. It was also noted that cheeses containing adjunct ingredients had lower proportions of Lactococcus species. It is thus apparent that high-throughput sequencing-based investigations can provide valuable insights into the microbial populations of artisanal foods. PMID:22685131

High-throughput sequencing for detection of subpopulations of bacteria not previously associated with artisanal cheeses.

PubMed

Quigley, Lisa; O'Sullivan, Orla; Beresford, Tom P; Ross, R Paul; Fitzgerald, Gerald F; Cotter, Paul D

2012-08-01

Here, high-throughput sequencing was employed to reveal the highly diverse bacterial populations present in 62 Irish artisanal cheeses and, in some cases, associated cheese rinds. Using this approach, we revealed the presence of several genera not previously associated with cheese, including Faecalibacterium, Prevotella, and Helcococcus and, for the first time, detected the presence of Arthrobacter and Brachybacterium in goats' milk cheese. Our analysis confirmed many previously observed patterns, such as the dominance of typical cheese bacteria, the fact that the microbiota of raw and pasteurized milk cheeses differ, and that the level of cheese maturation has a significant influence on Lactobacillus populations. It was also noted that cheeses containing adjunct ingredients had lower proportions of Lactococcus species. It is thus apparent that high-throughput sequencing-based investigations can provide valuable insights into the microbial populations of artisanal foods.

Short-read, high-throughput sequencing technology for STR genotyping

PubMed Central

Bornman, Daniel M.; Hester, Mark E.; Schuetter, Jared M.; Kasoji, Manjula D.; Minard-Smith, Angela; Barden, Curt A.; Nelson, Scott C.; Godbold, Gene D.; Baker, Christine H.; Yang, Boyu; Walther, Jacquelyn E.; Tornes, Ivan E.; Yan, Pearlly S.; Rodriguez, Benjamin; Bundschuh, Ralf; Dickens, Michael L.; Young, Brian A.; Faith, Seth A.

2013-01-01

DNA-based methods for human identification principally rely upon genotyping of short tandem repeat (STR) loci. Electrophoretic-based techniques for variable-length classification of STRs are universally utilized, but are limited in that they have relatively low throughput and do not yield nucleotide sequence information. High-throughput sequencing technology may provide a more powerful instrument for human identification, but is not currently validated for forensic casework. Here, we present a systematic method to perform high-throughput genotyping analysis of the Combined DNA Index System (CODIS) STR loci using short-read (150 bp) massively parallel sequencing technology. Open source reference alignment tools were optimized to evaluate PCR-amplified STR loci using a custom designed STR genome reference. Evaluation of this approach demonstrated that the 13 CODIS STR loci and amelogenin (AMEL) locus could be accurately called from individual and mixture samples. Sensitivity analysis showed that as few as 18,500 reads, aligned to an in silico referenced genome, were required to genotype an individual (>99% confidence) for the CODIS loci. The power of this technology was further demonstrated by identification of variant alleles containing single nucleotide polymorphisms (SNPs) and the development of quantitative measurements (reads) for resolving mixed samples. PMID:25621315

A family-based probabilistic method for capturing de novo mutations from high-throughput short-read sequencing data.

PubMed

Cartwright, Reed A; Hussin, Julie; Keebler, Jonathan E M; Stone, Eric A; Awadalla, Philip

2012-01-06

Recent advances in high-throughput DNA sequencing technologies and associated statistical analyses have enabled in-depth analysis of whole-genome sequences. As this technology is applied to a growing number of individual human genomes, entire families are now being sequenced. Information contained within the pedigree of a sequenced family can be leveraged when inferring the donors' genotypes. The presence of a de novo mutation within the pedigree is indicated by a violation of Mendelian inheritance laws. Here, we present a method for probabilistically inferring genotypes across a pedigree using high-throughput sequencing data and producing the posterior probability of de novo mutation at each genomic site examined. This framework can be used to disentangle the effects of germline and somatic mutational processes and to simultaneously estimate the effect of sequencing error and the initial genetic variation in the population from which the founders of the pedigree arise. This approach is examined in detail through simulations and areas for method improvement are noted. By applying this method to data from members of a well-defined nuclear family with accurate pedigree information, the stage is set to make the most direct estimates of the human mutation rate to date.

Deep sequencing reveals complex mechanisms of diapause preparation in the invasive mosquito, Aedes albopictus.

PubMed

Poelchau, Monica F; Reynolds, Julie A; Elsik, Christine G; Denlinger, David L; Armbruster, Peter A

2013-05-22

Seasonal environments present fundamental physiological challenges to a wide range of insects. Many temperate insects surmount the exigencies of winter by undergoing photoperiodic diapause, in which photoperiod provides a token cue that initiates an alternative developmental programme leading to dormancy. Pre-diapause is a crucial preparatory phase of this process, preceding developmental arrest. However, the regulatory and physiological mechanisms of diapause preparation are largely unknown. Using high-throughput gene expression profiling in the Asian tiger mosquito, Aedes albopictus, we reveal major shifts in endocrine signalling, cell proliferation, metabolism, energy production and cellular structure across pre-diapause development. While some hallmarks of diapause, such as insulin signalling and stress response, were not important at the transcriptional level, two genes, Pepck and PCNA, appear to show diapause-induced transcriptional changes across insect taxa. These processes demonstrate physiological commonalities between Ae. albopictus pre-diapause and diapause strategies across insects, and support the idea of a genetic 'toolkit' for diapause. Observations of gene expression trends from a comparative developmental perspective suggest that individual physiological processes are delayed against a background of a fixed morphological ontogeny. Our results demonstrate how deep sequencing can provide new insights into elusive molecular bases of complex ecological adaptations.

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

PubMed

Oono, Ryoko

2017-01-01

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

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

PubMed Central

2017-01-01

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

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.

Role of APOE Isoforms in the Pathogenesis of TBI induced Alzheimer’s Disease

DTIC Science & Technology

2016-10-01

deletion, APOE targeted replacement, complex breeding, CCI model optimization, mRNA library generation, high throughput massive parallel sequencing...demonstrate that the lack of Abca1 increases amyloid plaques and decreased APOE protein levels in AD-model mice. In this proposal we will test the hypothesis...injury, inflammatory reaction, transcriptome, high throughput massive parallel sequencing, mRNA-seq., behavioral testing, memory impairment, recovery 3

History, applications, and challenges of immune repertoire research.

PubMed

Liu, Xiao; Wu, Jinghua

2018-02-27

The diversity of T and B cells in terms of their receptor sequences is huge in the vertebrate's immune system and provides broad protection against the vast diversity of pathogens. Immune repertoire is defined as the sum of T cell receptors and B cell receptors (also named immunoglobulin) that makes the organism's adaptive immune system. Before the emergence of high-throughput sequencing, the studies on immune repertoire were limited by the underdeveloped methodologies, since it was impossible to capture the whole picture by the low-throughput tools. The massive paralleled sequencing technology suits perfectly the researches on immune repertoire. In this article, we review the history of immune repertoire studies, in terms of technologies and research applications. Particularly, we discuss several aspects of challenges in this field and highlight the efforts to develop potential solutions, in the era of high-throughput sequencing of the immune repertoire.

Mapping the miRNA interactome by crosslinking ligation and sequencing of hybrids (CLASH)

PubMed Central

Helwak, Aleksandra; Tollervey, David

2014-01-01

RNA-RNA interactions play critical roles in many cellular processes but studying them is difficult and laborious. Here, we describe an experimental procedure, termed crosslinking ligation and sequencing of hybrids (CLASH), which allows high-throughput identification of sites of RNA-RNA interaction. During CLASH, a tagged bait protein is UV crosslinked in vivo to stabilise RNA interactions and purified under denaturing conditions. RNAs associated with the bait protein are partially truncated, and the ends of RNA-duplexes are ligated together. Following linker addition, cDNA library preparation and high-throughput sequencing, the ligated duplexes give rise to chimeric cDNAs, which unambiguously identify RNA-RNA interaction sites independent of bioinformatic predictions. This protocol is optimized for studying miRNA targets bound by Argonaute proteins, but should be easily adapted for other RNA-binding proteins and classes of RNA. The protocol requires around 5 days to complete, excluding the time required for high-throughput sequencing and bioinformatic analyses. PMID:24577361

High Throughput Computing Impact on Meta Genomics (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Gore, Brooklin

2018-02-01

This presentation includes a brief background on High Throughput Computing, correlating gene transcription factors, optical mapping, genotype to phenotype mapping via QTL analysis, and current work on next gen sequencing.

Low-Cost, High-Throughput Sequencing of DNA Assemblies Using a Highly Multiplexed Nextera Process.

PubMed

Shapland, Elaine B; Holmes, Victor; Reeves, Christopher D; Sorokin, Elena; Durot, Maxime; Platt, Darren; Allen, Christopher; Dean, Jed; Serber, Zach; Newman, Jack; Chandran, Sunil

2015-07-17

In recent years, next-generation sequencing (NGS) technology has greatly reduced the cost of sequencing whole genomes, whereas the cost of sequence verification of plasmids via Sanger sequencing has remained high. Consequently, industrial-scale strain engineers either limit the number of designs or take short cuts in quality control. Here, we show that over 4000 plasmids can be completely sequenced in one Illumina MiSeq run for less than $3 each (15× coverage), which is a 20-fold reduction over using Sanger sequencing (2× coverage). We reduced the volume of the Nextera tagmentation reaction by 100-fold and developed an automated workflow to prepare thousands of samples for sequencing. We also developed software to track the samples and associated sequence data and to rapidly identify correctly assembled constructs having the fewest defects. As DNA synthesis and assembly become a centralized commodity, this NGS quality control (QC) process will be essential to groups operating high-throughput pipelines for DNA construction.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

Diversity of Pico- to Mesoplankton along the 2000 km Salinity Gradient of the Baltic Sea

PubMed Central

Hu, Yue O. O.; Karlson, Bengt; Charvet, Sophie; Andersson, Anders F.

2016-01-01

Microbial plankton form the productive base of both marine and freshwater ecosystems and are key drivers of global biogeochemical cycles of carbon and nutrients. Plankton diversity is immense with representations from all major phyla within the three domains of life. So far, plankton monitoring has mainly been based on microscopic identification, which has limited sensitivity and reproducibility, not least because of the numerical majority of plankton being unidentifiable under the light microscope. High-throughput sequencing of taxonomic marker genes offers a means to identify taxa inaccessible by traditional methods; thus, recent studies have unveiled an extensive previously unknown diversity of plankton. Here, we conducted ultra-deep Illumina sequencing (average 105 sequences/sample) of rRNA gene amplicons of surface water eukaryotic and bacterial plankton communities sampled in summer along a 2000 km transect following the salinity gradient of the Baltic Sea. Community composition was strongly correlated with salinity for both bacterial and eukaryotic plankton assemblages, highlighting the importance of salinity for structuring the biodiversity within this ecosystem. In contrast, no clear trends in alpha-diversity for bacterial or eukaryotic communities could be detected along the transect. The distribution of major planktonic taxa followed expected patterns as observed in monitoring programs, but groups novel to the Baltic Sea were also identified, such as relatives to the coccolithophore Emiliana huxleyi detected in the northern Baltic Sea. This study provides the first ultra-deep sequencing-based survey on eukaryotic and bacterial plankton biogeography in the Baltic Sea. PMID:27242706

Single-cell genome sequencing at ultra-high-throughput with microfluidic droplet barcoding.

PubMed

Lan, Freeman; Demaree, Benjamin; Ahmed, Noorsher; Abate, Adam R

2017-07-01

The application of single-cell genome sequencing to large cell populations has been hindered by technical challenges in isolating single cells during genome preparation. Here we present single-cell genomic sequencing (SiC-seq), which uses droplet microfluidics to isolate, fragment, and barcode the genomes of single cells, followed by Illumina sequencing of pooled DNA. We demonstrate ultra-high-throughput sequencing of >50,000 cells per run in a synthetic community of Gram-negative and Gram-positive bacteria and fungi. The sequenced genomes can be sorted in silico based on characteristic sequences. We use this approach to analyze the distributions of antibiotic-resistance genes, virulence factors, and phage sequences in microbial communities from an environmental sample. The ability to routinely sequence large populations of single cells will enable the de-convolution of genetic heterogeneity in diverse cell populations.

High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs.

PubMed

Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus; Morling, Niels

2016-01-01

Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards with buccal swabs and compared the results with those obtained with DNA extracted using the EZ1 DNA Investigator Kit. Concordant profiles were obtained for all samples. Our protocol includes simple punch, wash, and PCR steps, reducing cost and hands-on time in the laboratory. Furthermore, it facilitates automation of DNA sequencing.

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

PubMed Central

2012-01-01

Background The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Results Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. Conclusions By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand. PMID:22276739

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis.

PubMed

Tu, Jing; Ge, Qinyu; Wang, Shengqin; Wang, Lei; Sun, Beili; Yang, Qi; Bai, Yunfei; Lu, Zuhong

2012-01-25

The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

PubMed

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G; Rigoutsos, Isidore; Kirino, Yohei

2017-05-19

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Strain diversity and host specificity in bee gut symbionts revealed by deep sampling of single copy protein-coding sequences

PubMed Central

Powell, J. Elijah; Ratnayeke, Nalin; Moran, Nancy A.

2017-01-01

High throughput rRNA amplicon surveys of bacterial communities provide a rapid snapshot of taxonomic composition. But strains with nearly identical rRNA sequences often differ in gene repertoires and metabolic capabilities. To assess strain-level variation within Snodgrassella alvi, a gut symbiont of corbiculate bees, we performed deep sequencing on amplicons of a single copy coding gene (minD) as well as the 16S rDNA V4 region. We surveyed honey bees (Apis mellifera) sampled globally and 12 bumble bee species (Bombus) sampled from two regions of the USA. The minD analyses reveal that S. alvi contains far more strain diversity than is evident from 16S rDNA analysis. Many taxa inferred on the basis of 16S rDNA are shared between A. mellifera and Bombus species, but taxa inferred on the basis of minD are never shared and often are restricted to particular Bombus species. Clustering based on minD revealed that gut communities often reflect host species and geographic location. Both minD and 16S rDNA analyses indicate that strain diversity is higher in A. mellifera than in Bombus species. The minD locus flanks a 16S gene, enabling development of strain-specific 16S fluorescent probes to illuminate the spatial relationship of strains within the bee gut. PMID:27482856

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.

High-throughput analysis of the protein sequence-stability landscape using a quantitative "yeast surface two-hybrid" system and fragment reconstitution

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

Stability evaluation of many mutants can lead to a better understanding of the sequence determinants of a structural motif and of factors governing protein stability and protein evolution. The traditional biophysical analysis of protein stability is low throughput, limiting our ability to widely explore the sequence space in a quantitative manner. In this study, we have developed a high-throughput library screening method for quantifying stability changes, which is based on protein fragment reconstitution and yeast surface display. Our method exploits the thermodynamic linkage between protein stability and fragment reconstitution and the ability of the yeast surface display technique to quantitatively evaluate protein-protein interactions. The method was applied to a fibronectin type III (FN3) domain. Characterization of fragment reconstitution was facilitated by the co-expression of two FN3 fragments, thus establishing a "yeast surface two-hybrid" method. Importantly, our method does not rely on competition between clones and thus eliminates a common limitation of high-throughput selection methods in which the most stable variants are predominantly recovered. Thus, it allows for the isolation of sequences that exhibits a desired level of stability. We identified over one hundred unique sequences for a β-bulge motif, which was significantly more informative than natural sequences of the FN3 family in revealing the sequence determinants for the β-bulge. Our method provides a powerful means to rapidly assess stability of many variants, to systematically assess contribution of different factors to protein stability and to enhance protein stability. PMID:18674545

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

PubMed

Shinozuka, Hiroshi; Forster, John W

2016-01-01

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

"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.

False positives complicate ancient pathogen identifications using high-throughput shotgun sequencing

PubMed Central

2014-01-01

Background Identification of historic pathogens is challenging since false positives and negatives are a serious risk. Environmental non-pathogenic contaminants are ubiquitous. Furthermore, public genetic databases contain limited information regarding these species. High-throughput sequencing may help reliably detect and identify historic pathogens. Results We shotgun-sequenced 8 16th-century Mixtec individuals from the site of Teposcolula Yucundaa (Oaxaca, Mexico) who are reported to have died from the huey cocoliztli (‘Great Pestilence’ in Nahautl), an unknown disease that decimated native Mexican populations during the Spanish colonial period, in order to identify the pathogen. Comparison of these sequences with those deriving from the surrounding soil and from 4 precontact individuals from the site found a wide variety of contaminant organisms that confounded analyses. Without the comparative sequence data from the precontact individuals and soil, false positives for Yersinia pestis and rickettsiosis could have been reported. Conclusions False positives and negatives remain problematic in ancient DNA analyses despite the application of high-throughput sequencing. Our results suggest that several studies claiming the discovery of ancient pathogens may need further verification. Additionally, true single molecule sequencing’s short read lengths, inability to sequence through DNA lesions, and limited ancient-DNA-specific technical development hinder its application to palaeopathology. PMID:24568097

Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

PubMed Central

Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

2015-01-01

Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

Global diversity and biogeography of deep-sea pelagic prokaryotes.

PubMed

Salazar, Guillem; Cornejo-Castillo, Francisco M; Benítez-Barrios, Verónica; Fraile-Nuez, Eugenio; Álvarez-Salgado, X Antón; Duarte, Carlos M; Gasol, Josep M; Acinas, Silvia G

2016-03-01

The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean's microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (~3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

Global diversity and biogeography of deep-sea pelagic prokaryotes

PubMed Central

Salazar, Guillem; Cornejo-Castillo, Francisco M; Benítez-Barrios, Verónica; Fraile-Nuez, Eugenio; Álvarez-Salgado, X Antón; Duarte, Carlos M; Gasol, Josep M; Acinas, Silvia G

2016-01-01

The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean's microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (~3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered. PMID:26251871

Evaluation of sequencing approaches for high-throughput toxicogenomics (SOT)

EPA Science Inventory

Whole-genome in vitro transcriptomics has shown the capability to identify mechanisms of action and estimates of potency for chemical-mediated effects in a toxicological framework, but with limited throughput and high cost. We present the evaluation of three toxicogenomics platfo...

Advances in High-Throughput Speed, Low-Latency Communication for Embedded Instrumentation (7th Annual SFAF Meeting, 2012)

ScienceCinema

Jordan, Scott

2018-01-24

Scott Jordan on "Advances in high-throughput speed, low-latency communication for embedded instrumentation" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.

High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

PubMed

Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

High-Throughput Tabular Data Processor – Platform independent graphical tool for processing large data sets

PubMed Central

Bałut, Magdalena; Buckley, Patrick G.; Ochocka, J. Renata; Bartoszewski, Rafał; Crossman, David K.; Messiaen, Ludwine M.; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp). PMID:29432475

The autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders.

PubMed

Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Lehner, Thomas; Roeder, Kathryn; State, Matthew W

2012-12-20

Research during the past decade has seen significant progress in the understanding of the genetic architecture of autism spectrum disorders (ASDs), with gene discovery accelerating as the characterization of genomic variation has become increasingly comprehensive. At the same time, this research has highlighted ongoing challenges. Here we address the enormous impact of high-throughput sequencing (HTS) on ASD gene discovery, outline a consensus view for leveraging this technology, and describe a large multisite collaboration developed to accomplish these goals. Similar approaches could prove effective for severe neurodevelopmental disorders more broadly. Copyright © 2012 Elsevier Inc. All rights reserved.

High-throughput sequencing enhanced phage display enables the identification of patient-specific epitope motifs in serum.

PubMed

Christiansen, Anders; Kringelum, Jens V; Hansen, Christian S; Bøgh, Katrine L; Sullivan, Eric; Patel, Jigar; Rigby, Neil M; Eiwegger, Thomas; Szépfalusi, Zsolt; de Masi, Federico; Nielsen, Morten; Lund, Ole; Dufva, Martin

2015-08-06

Phage display is a prominent screening technique with a multitude of applications including therapeutic antibody development and mapping of antigen epitopes. In this study, phages were selected based on their interaction with patient serum and exhaustively characterised by high-throughput sequencing. A bioinformatics approach was developed in order to identify peptide motifs of interest based on clustering and contrasting to control samples. Comparison of patient and control samples confirmed a major issue in phage display, namely the selection of unspecific peptides. The potential of the bioinformatic approach was demonstrated by identifying epitopes of a prominent peanut allergen, Ara h 1, in sera from patients with severe peanut allergy. The identified epitopes were confirmed by high-density peptide micro-arrays. The present study demonstrates that high-throughput sequencing can empower phage display by (i) enabling the analysis of complex biological samples, (ii) circumventing the traditional laborious picking and functional testing of individual phage clones and (iii) reducing the number of selection rounds.

Large-Scale Comparative Phenotypic and Genomic Analyses Reveal Ecological Preferences of Shewanella Species and Identify Metabolic Pathways Conserved at the Genus Level ▿ †

PubMed Central

Rodrigues, Jorge L. M.; Serres, Margrethe H.; Tiedje, James M.

2011-01-01

The use of comparative genomics for the study of different microbiological species has increased substantially as sequence technologies become more affordable. However, efforts to fully link a genotype to its phenotype remain limited to the development of one mutant at a time. In this study, we provided a high-throughput alternative to this limiting step by coupling comparative genomics to the use of phenotype arrays for five sequenced Shewanella strains. Positive phenotypes were obtained for 441 nutrients (C, N, P, and S sources), with N-based compounds being the most utilized for all strains. Many genes and pathways predicted by genome analyses were confirmed with the comparative phenotype assay, and three degradation pathways believed to be missing in Shewanella were confirmed as missing. A number of previously unknown gene products were predicted to be parts of pathways or to have a function, expanding the number of gene targets for future genetic analyses. Ecologically, the comparative high-throughput phenotype analysis provided insights into niche specialization among the five different strains. For example, Shewanella amazonensis strain SB2B, isolated from the Amazon River delta, was capable of utilizing 60 C compounds, whereas Shewanella sp. strain W3-18-1, isolated from deep marine sediment, utilized only 25 of them. In spite of the large number of nutrient sources yielding positive results, our study indicated that except for the N sources, they were not sufficiently informative to predict growth phenotypes from increasing evolutionary distances. Our results indicate the importance of phenotypic evaluation for confirming genome predictions. This strategy will accelerate the functional discovery of genes and provide an ecological framework for microbial genome sequencing projects. PMID:21642407

Microbial communities and their predicted metabolic characteristics in deep fracture groundwaters of the crystalline bedrock at Olkiluoto, Finland

NASA Astrophysics Data System (ADS)

Bomberg, Malin; Lamminmäki, Tiina; Itävaara, Merja

2016-11-01

The microbial diversity in oligotrophic isolated crystalline Fennoscandian Shield bedrock fracture groundwaters is high, but the core community has not been identified. Here we characterized the bacterial and archaeal communities in 12 water conductive fractures situated at depths between 296 and 798 m by high throughput amplicon sequencing using the Illumina HiSeq platform. Between 1.7 × 104 and 1.2 × 106 bacterial or archaeal sequence reads per sample were obtained. These sequences revealed that up to 95 and 99 % of the bacterial and archaeal sequences obtained from the 12 samples, respectively, belonged to only a few common species, i.e. the core microbiome. However, the remaining rare microbiome contained over 3- and 6-fold more bacterial and archaeal taxa. The metabolic properties of the microbial communities were predicted using PICRUSt. The approximate estimation showed that the metabolic pathways commonly included fermentation, fatty acid oxidation, glycolysis/gluconeogenesis, oxidative phosphorylation, and methanogenesis/anaerobic methane oxidation, but carbon fixation through the Calvin cycle, reductive TCA cycle, and the Wood-Ljungdahl pathway was also predicted. The rare microbiome is an unlimited source of genomic functionality in all ecosystems. It may consist of remnants of microbial communities prevailing in earlier environmental conditions, but could also be induced again if changes in their living conditions occur.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data.

PubMed

Luo, Guan-Zheng; Yang, Wei; Ma, Ying-Ke; Wang, Xiu-Jie

2014-02-01

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets. ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.

SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

PubMed

Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

2012-07-15

In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

Fast multiclonal clusterization of V(D)J recombinations from high-throughput sequencing.

PubMed

Giraud, Mathieu; Salson, Mikaël; Duez, Marc; Villenet, Céline; Quief, Sabine; Caillault, Aurélie; Grardel, Nathalie; Roumier, Christophe; Preudhomme, Claude; Figeac, Martin

2014-05-28

V(D)J recombinations in lymphocytes are essential for immunological diversity. They are also useful markers of pathologies. In leukemia, they are used to quantify the minimal residual disease during patient follow-up. However, the full breadth of lymphocyte diversity is not fully understood. We propose new algorithms that process high-throughput sequencing (HTS) data to extract unnamed V(D)J junctions and gather them into clones for quantification. This analysis is based on a seed heuristic and is fast and scalable because in the first phase, no alignment is performed with germline database sequences. The algorithms were applied to TR γ HTS data from a patient with acute lymphoblastic leukemia, and also on data simulating hypermutations. Our methods identified the main clone, as well as additional clones that were not identified with standard protocols. The proposed algorithms provide new insight into the analysis of high-throughput sequencing data for leukemia, and also to the quantitative assessment of any immunological profile. The methods described here are implemented in a C++ open-source program called Vidjil.

REDItools: high-throughput RNA editing detection made easy.

PubMed

Picardi, Ernesto; Pesole, Graziano

2013-07-15

The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

High throughput protein production screening

DOEpatents

Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

2009-09-08

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

High-Throughput Sequencing: A Roadmap Toward Community Ecology

PubMed Central

Poisot, Timothée; Péquin, Bérangère; Gravel, Dominique

2013-01-01

High-throughput sequencing is becoming increasingly important in microbial ecology, yet it is surprisingly under-used to generate or test biogeographic hypotheses. In this contribution, we highlight how adding these methods to the ecologist toolbox will allow the detection of new patterns, and will help our understanding of the structure and dynamics of diversity. Starting with a review of ecological questions that can be addressed, we move on to the technical and analytical issues that will benefit from an increased collaboration between different disciplines. PMID:23610649

ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data

PubMed Central

Morgan, Martin; Anders, Simon; Lawrence, Michael; Aboyoun, Patrick; Pagès, Hervé; Gentleman, Robert

2009-01-01

Summary: ShortRead is a package for input, quality assessment, manipulation and output of high-throughput sequencing data. ShortRead is provided in the R and Bioconductor environments, allowing ready access to additional facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources. Availability and Implementation: This package is implemented in R and available at the Bioconductor web site; the package contains a ‘vignette’ outlining typical work flows. Contact: mtmorgan@fhcrc.org PMID:19654119

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.

High-Throughput Sequencing of Campylobacter jejuni Insertion Mutant Libraries Reveals mapA as a Fitness Factor for Chicken Colonization

PubMed Central

Johnson, Jeremiah G.; Livny, Jonathan

2014-01-01

Campylobacter jejuni is a leading cause of gastrointestinal infections worldwide, due primarily to its ability to asymptomatically colonize the gastrointestinal tracts of agriculturally relevant animals, including chickens. Infection often occurs following consumption of meat that was contaminated by C. jejuni during harvest. Because of this, much interest lies in understanding the mechanisms that allow C. jejuni to colonize the chicken gastrointestinal tract. To address this, we generated a C. jejuni transposon mutant library that is amenable to insertion sequencing and introduced this mutant pool into day-of-hatch chicks. Following deep sequencing of C. jejuni mutants in the cecal outputs, several novel factors required for efficient colonization of the chicken gastrointestinal tract were identified, including the predicted outer membrane protein MapA. A mutant strain lacking mapA was constructed and found to be significantly reduced for chicken colonization in both competitive infections and monoinfections. Further, we found that mapA is required for in vitro competition with wild-type C. jejuni but is dispensable for growth in monoculture. PMID:24633877

High-throughput sequencing of Campylobacter jejuni insertion mutant libraries reveals mapA as a fitness factor for chicken colonization.

PubMed

Johnson, Jeremiah G; Livny, Jonathan; Dirita, Victor J

2014-06-01

Campylobacter jejuni is a leading cause of gastrointestinal infections worldwide, due primarily to its ability to asymptomatically colonize the gastrointestinal tracts of agriculturally relevant animals, including chickens. Infection often occurs following consumption of meat that was contaminated by C. jejuni during harvest. Because of this, much interest lies in understanding the mechanisms that allow C. jejuni to colonize the chicken gastrointestinal tract. To address this, we generated a C. jejuni transposon mutant library that is amenable to insertion sequencing and introduced this mutant pool into day-of-hatch chicks. Following deep sequencing of C. jejuni mutants in the cecal outputs, several novel factors required for efficient colonization of the chicken gastrointestinal tract were identified, including the predicted outer membrane protein MapA. A mutant strain lacking mapA was constructed and found to be significantly reduced for chicken colonization in both competitive infections and monoinfections. Further, we found that mapA is required for in vitro competition with wild-type C. jejuni but is dispensable for growth in monoculture.

Coupling molecules and morphology to discover new clades of ciliates.

NASA Astrophysics Data System (ADS)

Grattepanche, J. D.; Maurer-Alcalá, X. X.; Tucker, S. J.; McManus, G. B.; Katz, L. A.

2016-02-01

In a previous study using high-throughput sequencing (Grattepanche et al submitted, oral presentation?), we observe the presence of two clades of spirotrich ciliates mainly present in marine deep-water along the New England coast. These clades, clusters X1 and X2, are characterized by several deletions in their SSU-rDNA and have been observed elsewhere as both identical and similar sequences have been deposited on GenBank from other environmental studies, but lack morphological description. In order to link molecules (SSU-rDNA sequence) to their morphology, we sample below the photic zone (between 60 to 400m of depth) in the New England coast (Northeast Atlantic) in a transect crossing the continental shelf. We designed an oligonucleotide probe specific for choreotrich and oligotrich ciliates and another specific to clusters X1 and X2 to describe these clades through a combination of Fluorescence In Situ Hybridization (FISH) and light microscopy. Our aim is to increase our knowledge on the morphology of these `unknown' clades of ciliates, which will allow for future ecological studies.

Forecasting Ecological Genomics: High-Tech Animal Instrumentation Meets High-Throughput Sequencing

PubMed Central

Shafer, Aaron B. A.; Northrup, Joseph M.; Wikelski, Martin; Wittemyer, George; Wolf, Jochen B. W.

2016-01-01

Recent advancements in animal tracking technology and high-throughput sequencing are rapidly changing the questions and scope of research in the biological sciences. The integration of genomic data with high-tech animal instrumentation comes as a natural progression of traditional work in ecological genetics, and we provide a framework for linking the separate data streams from these technologies. Such a merger will elucidate the genetic basis of adaptive behaviors like migration and hibernation and advance our understanding of fundamental ecological and evolutionary processes such as pathogen transmission, population responses to environmental change, and communication in natural populations. PMID:26745372

Multiplexed fragaria chloroplast genome sequencing

Treesearch

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

2010-01-01

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

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

PubMed

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

2007-02-14

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

High-Throughput Sequencing, a Versatile Weapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

PubMed Central

Caboche, Ségolène; Audebert, Christophe; Hot, David

2014-01-01

The recent progresses of high-throughput sequencing (HTS) technologies enable easy and cost-reduced access to whole genome sequencing (WGS) or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose. PMID:25437800

[Genetic analysis of two children patients affected with CHARGE syndrome].

PubMed

Li, Guoqiang; Li, Niu; Xu, Yufei; Li, Juan; Ding, Yu; Shen, Yiping; Wang, Xiumin; Wang, Jian

2018-04-10

To analyze two Chinese pediatric patients with multiple malformations and growth and development delay. Both patients were subjected to targeted gene sequencing, and the results were analyzed with Ingenuity Variant Analysis software. Suspected pathogenic variations were verified by Sanger sequencing. High-throughput sequencing showed that both patients have carried heterozygous variants of the CHD7 gene. Patient 1 carried a nonsense mutation in exon 36 (c.7957C>T, p.Arg2653*), while patient 2 carried a nonsense mutation of exon 2 (c.718C>T, p.Gln240*). Sanger sequencing confirmed the above mutations in both patients, while their parents were of wild-type for the corresponding sites, indicating that the two mutations have happened de novo. Two patients were diagnosed with CHARGE syndrome by high-throughput sequencing.

High-throughput gene mapping in Caenorhabditis elegans.

PubMed

Swan, Kathryn A; Curtis, Damian E; McKusick, Kathleen B; Voinov, Alexander V; Mapa, Felipa A; Cancilla, Michael R

2002-07-01

Positional cloning of mutations in model genetic systems is a powerful method for the identification of targets of medical and agricultural importance. To facilitate the high-throughput mapping of mutations in Caenorhabditis elegans, we have identified a further 9602 putative new single nucleotide polymorphisms (SNPs) between two C. elegans strains, Bristol N2 and the Hawaiian mapping strain CB4856, by sequencing inserts from a CB4856 genomic DNA library and using an informatics pipeline to compare sequences with the canonical N2 genomic sequence. When combined with data from other laboratories, our marker set of 17,189 SNPs provides even coverage of the complete worm genome. To date, we have confirmed >1099 evenly spaced SNPs (one every 91 +/- 56 kb) across the six chromosomes and validated the utility of our SNP marker set and new fluorescence polarization-based genotyping methods for systematic and high-throughput identification of genes in C. elegans by cloning several proprietary genes. We illustrate our approach by recombination mapping and confirmation of the mutation in the cloned gene, dpy-18.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments.

PubMed

Burdick, David B; Cavnor, Chris C; Handcock, Jeremy; Killcoyne, Sarah; Lin, Jake; Marzolf, Bruz; Ramsey, Stephen A; Rovira, Hector; Bressler, Ryan; Shmulevich, Ilya; Boyle, John

2010-07-14

High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

PubMed Central

2010-01-01

Background High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Results Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. Conclusion The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services. PMID:20630057

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.

Library Design-Facilitated High-Throughput Sequencing of Synthetic Peptide Libraries.

PubMed

Vinogradov, Alexander A; Gates, Zachary P; Zhang, Chi; Quartararo, Anthony J; Halloran, Kathryn H; Pentelute, Bradley L

2017-11-13

A methodology to achieve high-throughput de novo sequencing of synthetic peptide mixtures is reported. The approach leverages shotgun nanoliquid chromatography coupled with tandem mass spectrometry-based de novo sequencing of library mixtures (up to 2000 peptides) as well as automated data analysis protocols to filter away incorrect assignments, noise, and synthetic side-products. For increasing the confidence in the sequencing results, mass spectrometry-friendly library designs were developed that enabled unambiguous decoding of up to 600 peptide sequences per hour while maintaining greater than 85% sequence identification rates in most cases. The reliability of the reported decoding strategy was additionally confirmed by matching fragmentation spectra for select authentic peptides identified from library sequencing samples. The methods reported here are directly applicable to screening techniques that yield mixtures of active compounds, including particle sorting of one-bead one-compound libraries and affinity enrichment of synthetic library mixtures performed in solution.

Mapping DNA polymerase errors by single-molecule sequencing

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

Lee, David F.; Lu, Jenny; Chang, Seungwoo

Genomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replicationmore » product is tagged with a unique nucleotide sequence before amplification. Here, this allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.« less

Mapping DNA polymerase errors by single-molecule sequencing

DOE PAGES

Lee, David F.; Lu, Jenny; Chang, Seungwoo; ...

2016-05-16

Genomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replicationmore » product is tagged with a unique nucleotide sequence before amplification. Here, this allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.« less

Comprehensive identification and profiling of host miRNAs in response to Singapore grouper iridovirus (SGIV) infection in grouper (Epinephelus coioides).

PubMed

Guo, Chuanyu; Cui, Huachun; Ni, Songwei; Yan, Yang; Qin, Qiwei

2015-10-01

microRNAs (miRNAs) are an evolutionarily conserved class of non-coding RNA molecules that participate in various biological processes. Employment of high-throughput screening strategies greatly prompts the investigation and profiling of miRNAs in diverse species. In recent years, grouper (Epinephelus spp.) aquaculture was severely affected by iridoviral diseases. However, knowledge regarding the host immune responses to viral infection, especially the miRNA-mediated immune regulatory roles, is rather limited. In this study, by employing Solexa deep sequencing approach, we identified 116 grouper miRNAs from grouper spleen-derived cells (GS). As expected, these miRNAs shared high sequence similarity with miRNAs identified in zebrafish (Danio rerio), pufferfish (Fugu rubripes), and other higher vertebrates. In the process of Singapore grouper iridovirus (SGIV) infection, 45 and 43 miRNAs with altered expression (>1.5-fold) were identified by miRNA microarray assays in grouper spleen tissues and GS cells, respectively. Furthermore, target prediction revealed 189 putative targets of these grouper miRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of DNA-protein interactions using high-throughput sequencing data from pulldown experiments

NASA Astrophysics Data System (ADS)

Moreland, Blythe; Oman, Kenji; Curfman, John; Yan, Pearlly; Bundschuh, Ralf

Methyl-binding domain (MBD) protein pulldown experiments have been a valuable tool in measuring the levels of methylated CpG dinucleotides. Due to the frequent use of this technique, high-throughput sequencing data sets are available that allow a detailed quantitative characterization of the underlying interaction between methylated DNA and MBD proteins. Analyzing such data sets, we first found that two such proteins cannot bind closer to each other than 2 bp, consistent with structural models of the DNA-protein interaction. Second, the large amount of sequencing data allowed us to find rather weak but nevertheless clearly statistically significant sequence preferences for several bases around the required CpG. These results demonstrate that pulldown sequencing is a high-precision tool in characterizing DNA-protein interactions. This material is based upon work supported by the National Science Foundation under Grant No. DMR-1410172.

High-throughput sequencing of complete human mtDNA genomes from the Caucasus and West Asia: high diversity and demographic inferences.

PubMed

Schönberg, Anna; Theunert, Christoph; Li, Mingkun; Stoneking, Mark; Nasidze, Ivan

2011-09-01

To investigate the demographic history of human populations from the Caucasus and surrounding regions, we used high-throughput sequencing to generate 147 complete mtDNA genome sequences from random samples of individuals from three groups from the Caucasus (Armenians, Azeri and Georgians), and one group each from Iran and Turkey. Overall diversity is very high, with 144 different sequences that fall into 97 different haplogroups found among the 147 individuals. Bayesian skyline plots (BSPs) of population size change through time show a population expansion around 40-50 kya, followed by a constant population size, and then another expansion around 15-18 kya for the groups from the Caucasus and Iran. The BSP for Turkey differs the most from the others, with an increase from 35 to 50 kya followed by a prolonged period of constant population size, and no indication of a second period of growth. An approximate Bayesian computation approach was used to estimate divergence times between each pair of populations; the oldest divergence times were between Turkey and the other four groups from the South Caucasus and Iran (~400-600 generations), while the divergence time of the three Caucasus groups from each other was comparable to their divergence time from Iran (average of ~360 generations). These results illustrate the value of random sampling of complete mtDNA genome sequences that can be obtained with high-throughput sequencing platforms.

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; Bae, Jingi; Kim, Hokeun; Oh, Se Yeon; Park, Young Soo; Lee, Jae-Hyuk; Lee, Sang-Won

2015-08-21

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results.

PubMed

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-02-09

BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform-independent, easily configurable and capable of comprehensive expansion, and user-intuitive. PLAN is freely available to academic users at http://bioinfo.noble.org/plan/. The source code for local deployment is provided under free license. Full support on system utilization, installation, configuration and customization are provided to academic users.

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

PubMed Central

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-01-01

Background BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform-independent, easily configurable and capable of comprehensive expansion, and user-intuitive. PLAN is freely available to academic users at . The source code for local deployment is provided under free license. Full support on system utilization, installation, configuration and customization are provided to academic users. PMID:17291345

Microbial community profiles and microbial carbon cycling in Orca Basin

NASA Astrophysics Data System (ADS)

Hyde, A.; Teske, A.; Joye, S. B.; Montoya, J. P.; Nigro, L.

2016-12-01

Orca Basin is the largest seafloor brine pools in the world, covering over 400 km2 and reaching brine layer depths of 200 m. The brine pool contains water 8 times denser than the overlying seawater and is separated from the overlying water column by a sharp pycnocline that prevents vertical mixing. The transition from ambient seawater to brine occurs over 100 m [2150 to 2250 m] and is characterized by distinct changes in temperature, salinity, chemical conditions, oxygen, and organic matter concentration. The sharp brine-seawater interface results in a sharp pycnocline, which serves as a particle trap for sinking marine organic matter. Previous studies have used lipids to show that this organic-rich interface is host to an active microbial community which is potentially involved in deep-sea carbon remineralization and metal-cycling. Additionally, previous work on methane, ethane, and propane concentrations and 13C-isotopic signatures has also implicated the brine pool, as well as the interface, as sources for biogenic low-molecular weight hydrocarbons, resulting from the high concentration of suspended organic matter above and within the brine pool. Here we investigate the profiles of microbial community composition and metabolic potential in Orca Basin, ranging from seawater through the Orca Basin chemocline and into the deep Orca Basin brine. To characterize the microbial community and stratification, we used high-throughput bacterial and archaeal 16S rRNA gene sequencing of filtered water above, within, and below the Orca Basin chemocline. Our sequence data shows that three distinct and unique communities exist in the Orca Basin water column. We also use thermodynamic modeling of hydrocarbon degradation to investigate the favorability of C1-C3 hydrocarbon oxidation at the brine-seawater interface and the potential for Orca Basin to serve as a deep-sea hydrocarbon sink.

Spatial scales of bacterial community diversity at cold seeps (Eastern Mediterranean Sea)

PubMed Central

Pop Ristova, Petra; Wenzhöfer, Frank; Ramette, Alban; Felden, Janine; Boetius, Antje

2015-01-01

Cold seeps are highly productive, fragmented marine ecosystems that form at the seafloor around hydrocarbon emission pathways. The products of microbial utilization of methane and other hydrocarbons fuel rich chemosynthetic communities at these sites, with much higher respiration rates compared with the surrounding deep-sea floor. Yet little is known as to the richness, composition and spatial scaling of bacterial communities of cold seeps compared with non-seep communities. Here we assessed the bacterial diversity across nine different cold seeps in the Eastern Mediterranean deep-sea and surrounding seafloor areas. Community similarity analyses were carried out based on automated ribosomal intergenic spacer analysis (ARISA) fingerprinting and high-throughput 454 tag sequencing and were combined with in situ and ex situ geochemical analyses across spatial scales of a few tens of meters to hundreds of kilometers. Seep communities were dominated by Deltaproteobacteria, Epsilonproteobacteria and Gammaproteobacteria and shared, on average, 36% of bacterial types (ARISA OTUs (operational taxonomic units)) with communities from nearby non-seep deep-sea sediments. Bacterial communities of seeps were significantly different from those of non-seep sediments. Within cold seep regions on spatial scales of only tens to hundreds of meters, the bacterial communities differed considerably, sharing <50% of types at the ARISA OTU level. Their variations reflected differences in porewater sulfide concentrations from anaerobic degradation of hydrocarbons. This study shows that cold seep ecosystems contribute substantially to the microbial diversity of the deep-sea. PMID:25500510

High-Throughput Next-Generation Sequencing of Polioviruses

PubMed Central

Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

2016-01-01

ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

Whole-Genome Sequencing and Assembly with High-Throughput, Short-Read Technologies

PubMed Central

Sundquist, Andreas; Ronaghi, Mostafa; Tang, Haixu; Pevzner, Pavel; Batzoglou, Serafim

2007-01-01

While recently developed short-read sequencing technologies may dramatically reduce the sequencing cost and eventually achieve the $1000 goal for re-sequencing, their limitations prevent the de novo sequencing of eukaryotic genomes with the standard shotgun sequencing protocol. We present SHRAP (SHort Read Assembly Protocol), a sequencing protocol and assembly methodology that utilizes high-throughput short-read technologies. We describe a variation on hierarchical sequencing with two crucial differences: (1) we select a clone library from the genome randomly rather than as a tiling path and (2) we sample clones from the genome at high coverage and reads from the clones at low coverage. We assume that 200 bp read lengths with a 1% error rate and inexpensive random fragment cloning on whole mammalian genomes is feasible. Our assembly methodology is based on first ordering the clones and subsequently performing read assembly in three stages: (1) local assemblies of regions significantly smaller than a clone size, (2) clone-sized assemblies of the results of stage 1, and (3) chromosome-sized assemblies. By aggressively localizing the assembly problem during the first stage, our method succeeds in assembling short, unpaired reads sampled from repetitive genomes. We tested our assembler using simulated reads from D. melanogaster and human chromosomes 1, 11, and 21, and produced assemblies with large sets of contiguous sequence and a misassembly rate comparable to other draft assemblies. Tested on D. melanogaster and the entire human genome, our clone-ordering method produces accurate maps, thereby localizing fragment assembly and enabling the parallelization of the subsequent steps of our pipeline. Thus, we have demonstrated that truly inexpensive de novo sequencing of mammalian genomes will soon be possible with high-throughput, short-read technologies using our methodology. PMID:17534434

A new arenavirus in a cluster of fatal transplant-associated diseases.

PubMed

Palacios, Gustavo; Druce, Julian; Du, Lei; Tran, Thomas; Birch, Chris; Briese, Thomas; Conlan, Sean; Quan, Phenix-Lan; Hui, Jeffrey; Marshall, John; Simons, Jan Fredrik; Egholm, Michael; Paddock, Christopher D; Shieh, Wun-Ju; Goldsmith, Cynthia S; Zaki, Sherif R; Catton, Mike; Lipkin, W Ian

2008-03-06

Three patients who received visceral-organ transplants from a single donor on the same day died of a febrile illness 4 to 6 weeks after transplantation. Culture, polymerase-chain-reaction (PCR) and serologic assays, and oligonucleotide microarray analysis for a wide range of infectious agents were not informative. We evaluated RNA obtained from the liver and kidney transplant recipients. Unbiased high-throughput sequencing was used to identify microbial sequences not found by means of other methods. The specificity of sequences for a new candidate pathogen was confirmed by means of culture and by means of PCR, immunohistochemical, and serologic analyses. High-throughput sequencing yielded 103,632 sequences, of which 14 represented an Old World arenavirus. Additional sequence analysis showed that this new arenavirus was related to lymphocytic choriomeningitis viruses. Specific PCR assays based on a unique sequence confirmed the presence of the virus in the kidneys, liver, blood, and cerebrospinal fluid of the recipients. Immunohistochemical analysis revealed arenavirus antigen in the liver and kidney transplants in the recipients. IgM and IgG antiviral antibodies were detected in the serum of the donor. Seroconversion was evident in serum specimens obtained from one recipient at two time points. Unbiased high-throughput sequencing is a powerful tool for the discovery of pathogens. The use of this method during an outbreak of disease facilitated the identification of a new arenavirus transmitted through solid-organ transplantation. Copyright 2008 Massachusetts Medical Society.

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

PubMed

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

2013-08-01

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

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

PubMed Central

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

2013-01-01

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

Deep Sequencing of Plant and Animal DNA Contained within Traditional Chinese Medicines Reveals Legality Issues and Health Safety Concerns

PubMed Central

Coghlan, Megan L.; Haile, James; Houston, Jayne; Murray, Dáithí C.; White, Nicole E.; Moolhuijzen, Paula; Bellgard, Matthew I.; Bunce, Michael

2012-01-01

Traditional Chinese medicine (TCM) has been practiced for thousands of years, but only within the last few decades has its use become more widespread outside of Asia. Concerns continue to be raised about the efficacy, legality, and safety of many popular complementary alternative medicines, including TCMs. Ingredients of some TCMs are known to include derivatives of endangered, trade-restricted species of plants and animals, and therefore contravene the Convention on International Trade in Endangered Species (CITES) legislation. Chromatographic studies have detected the presence of heavy metals and plant toxins within some TCMs, and there are numerous cases of adverse reactions. It is in the interests of both biodiversity conservation and public safety that techniques are developed to screen medicinals like TCMs. Targeting both the p-loop region of the plastid trnL gene and the mitochondrial 16S ribosomal RNA gene, over 49,000 amplicon sequence reads were generated from 15 TCM samples presented in the form of powders, tablets, capsules, bile flakes, and herbal teas. Here we show that second-generation, high-throughput sequencing (HTS) of DNA represents an effective means to genetically audit organic ingredients within complex TCMs. Comparison of DNA sequence data to reference databases revealed the presence of 68 different plant families and included genera, such as Ephedra and Asarum, that are potentially toxic. Similarly, animal families were identified that include genera that are classified as vulnerable, endangered, or critically endangered, including Asiatic black bear (Ursus thibetanus) and Saiga antelope (Saiga tatarica). Bovidae, Cervidae, and Bufonidae DNA were also detected in many of the TCM samples and were rarely declared on the product packaging. This study demonstrates that deep sequencing via HTS is an efficient and cost-effective way to audit highly processed TCM products and will assist in monitoring their legality and safety especially when plant reference databases become better established. PMID:22511890

Rapid molecular diagnostics of severe primary immunodeficiency determined by using targeted next-generation sequencing.

PubMed

Yu, Hui; Zhang, Victor Wei; Stray-Pedersen, Asbjørg; Hanson, Imelda Celine; Forbes, Lisa R; de la Morena, M Teresa; Chinn, Ivan K; Gorman, Elizabeth; Mendelsohn, Nancy J; Pozos, Tamara; Wiszniewski, Wojciech; Nicholas, Sarah K; Yates, Anne B; Moore, Lindsey E; Berge, Knut Erik; Sorte, Hanne; Bayer, Diana K; ALZahrani, Daifulah; Geha, Raif S; Feng, Yanming; Wang, Guoli; Orange, Jordan S; Lupski, James R; Wang, Jing; Wong, Lee-Jun

2016-10-01

Primary immunodeficiency diseases (PIDDs) are inherited disorders of the immune system. The most severe form, severe combined immunodeficiency (SCID), presents with profound deficiencies of T cells, B cells, or both at birth. If not treated promptly, affected patients usually do not live beyond infancy because of infections. Genetic heterogeneity of SCID frequently delays the diagnosis; a specific diagnosis is crucial for life-saving treatment and optimal management. We developed a next-generation sequencing (NGS)-based multigene-targeted panel for SCID and other severe PIDDs requiring rapid therapeutic actions in a clinical laboratory setting. The target gene capture/NGS assay provides an average read depth of approximately 1000×. The deep coverage facilitates simultaneous detection of single nucleotide variants and exonic copy number variants in one comprehensive assessment. Exons with insufficient coverage (<20× read depth) or high sequence homology (pseudogenes) are complemented by amplicon-based sequencing with specific primers to ensure 100% coverage of all targeted regions. Analysis of 20 patient samples with low T-cell receptor excision circle numbers on newborn screening or a positive family history or clinical suspicion of SCID or other severe PIDD identified deleterious mutations in 14 of them. Identified pathogenic variants included both single nucleotide variants and exonic copy number variants, such as hemizygous nonsense, frameshift, and missense changes in IL2RG; compound heterozygous changes in ATM, RAG1, and CIITA; homozygous changes in DCLRE1C and IL7R; and a heterozygous nonsense mutation in CHD7. High-throughput deep sequencing analysis with complete clinical validation greatly increases the diagnostic yield of severe primary immunodeficiency. Establishing a molecular diagnosis enables early immune reconstitution through prompt therapeutic intervention and guides management for improved long-term quality of life. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Actinobacterial diversity across a marine transgression in the deep subsurface off Shimokita Peninsula, Japan

NASA Astrophysics Data System (ADS)

Harrison, B. K.; Bailey, J. V.

2013-12-01

Sediment horizons represent a significant - but not permanent - barrier to microbial transport. Cells commonly attach to mineral surfaces in unconsolidated sediments. However, by taxis, growth, or passive migration under advecting fluids, some portion of the microbial community may transgress sedimentary boundaries. Few studies have attempted to constrain such transport of community signatures in the marine subsurface and its potential impact on biogeography. Integrated Ocean Drilling Program (IODP) Expedition 337 off the Shimokita Peninsula recovered sediments over a greater than 1km interval representing a gradual decrease of terrestrial influence, from tidal to continental shelf depositional settings. This sequence represents a key opportunity to link subsurface microbial communities to lithological variability and investigate the permanence of community signatures characteristic of distinct depositional regimes. The phylogenetic connectivity between marine and terrestrially-influenced deposits may demonstrate to what degree sediments offer a substantial barrier to cell transport in the subsurface. Previous work has demonstrated that the Actinobacterial phylum is broadly distributed in marine sediments (Maldonado et al., 2005), present and active in the deep subsurface (Orsi et al., 2013), and that marine and terrestrial lineages may potentially be distinguished by 16S rRNA gene sequencing (e.g. Prieto-Davó et al., 2013). We report on Actinobacteria-specific 16S rRNA gene diversity recovered between 1370 and 2642 mbsf with high-throughput sequencing using the Illumina MiSeq platform, as well as selective assembly and analysis of environmental clone libraries.

Some New Windows into Terrestrial Deep Subsurface Microbial Ecosystems

NASA Astrophysics Data System (ADS)

Moser, D. P.

2011-12-01

Over the past several years, our group has surveyed the microbial ecology and biogeochemistry of a range of fracture rock subsurface ecosystems via deep mine boreholes in South Africa, the United States, and Canada; and boreholes from surface or deeply-sourced natural springs of the U.S. Great Basin. Collectively, these mostly unexplored habitats represent a wide range of geologic provinces, host rock types, aquatic chemistries, and the vast potential for biogeographic isolation. Thus, patterns of microbial diversity are of interest from the perspective of filling a fundamental knowledge gap; and while not necessarily expected, the detection of closely related microorganisms from geographically isolated settings would be noteworthy. Across these sample sets, microbial communities were invariably very low in biomass (e.g. 10e3 - 10e4 cells per mL) and dominated by deeply-branching bacterial lineages, particularly from the phyla Firmicutes and Nitrospira. In several cases, the Firmicutes have shown very close phylogenetic affiliations to lineages detected at divergent locations. For example, one abundant lineage from a new artesian well drilled into the Furnace Creek Fault of Death Valley, CA bears a very close phylogenetic relatedness to environmental DNA sequences (SSU rRNA gene) detected in one of the world's deepest mines (Tau Tona of South Africa) and what was North America's deepest gold mine (Homestake of South Dakota). Several radioactive wells from the Nevada National Security Site have produced rRNA gene sequences very close (e.g. greater than 99% identity) to that of Desulforudis audaxviator, a rarely detected microorganism thought to subsist as a single species ecosystem on the products of radiochemical reactions in deep crustal rocks from the South African Witwatersrand Basin. These sequences, along with more distantly related sequences from the marine subsurface (ridge flank basalt and mud volcanoes) and groundwater in Europe, hint at a role in certain hydrogen-rich subsurface settings for this group. Likewise, patterns of archaeal diversity across many of our Great Basin sites suggest shared deep lineages, particularly with the phylum, Thaumarchaeota. Here we will explore the possible significance of these patterns of diversity and discuss future research plans involving high throughput molecular techniques.

HybPiper: Extracting coding sequence and introns for phylogenetics from high-throughput sequencing reads using target enrichment1

PubMed Central

Johnson, Matthew G.; Gardner, Elliot M.; Liu, Yang; Medina, Rafael; Goffinet, Bernard; Shaw, A. Jonathan; Zerega, Nyree J. C.; Wickett, Norman J.

2016-01-01

Premise of the study: Using sequence data generated via target enrichment for phylogenetics requires reassembly of high-throughput sequence reads into loci, presenting a number of bioinformatics challenges. We developed HybPiper as a user-friendly platform for assembly of gene regions, extraction of exon and intron sequences, and identification of paralogous gene copies. We test HybPiper using baits designed to target 333 phylogenetic markers and 125 genes of functional significance in Artocarpus (Moraceae). Methods and Results: HybPiper implements parallel execution of sequence assembly in three phases: read mapping, contig assembly, and target sequence extraction. The pipeline was able to recover nearly complete gene sequences for all genes in 22 species of Artocarpus. HybPiper also recovered more than 500 bp of nontargeted intron sequence in over half of the phylogenetic markers and identified paralogous gene copies in Artocarpus. Conclusions: HybPiper was designed for Linux and Mac OS X and is freely available at https://github.com/mossmatters/HybPiper. PMID:27437175

High-throughput sequencing reveals unprecedented diversities of Aspergillus species in outdoor air.

PubMed

Lee, S; An, C; Xu, S; Lee, S; Yamamoto, N

2016-09-01

This study used the Illumina MiSeq to analyse compositions and diversities of Aspergillus species in outdoor air. The seasonal air samplings were performed at two locations in Seoul, South Korea. The results showed the relative abundances of all Aspergillus species combined ranging from 0·20 to 18% and from 0·19 to 21% based on the number of the internal transcribed spacer 1 (ITS1) and β-tubulin (BenA) gene sequences respectively. Aspergillus fumigatus was the most dominant species with the mean relative abundances of 1·2 and 5·5% based on the number of the ITS1 and BenA sequences respectively. A total of 29 Aspergillus species were detected and identified down to the species rank, among which nine species were known opportunistic pathogens. Remarkably, eight of the nine pathogenic species were detected by either one of the two markers, suggesting the need of using multiple markers and/or primer pairs when the assessments are made based on the high-throughput sequencing. Due to diversity of species within the genus Aspergillus, the high-throughput sequencing was useful to characterize their compositions and diversities in outdoor air, which are thought to be difficult to be accurately characterized by conventional culture and/or Sanger sequencing-based techniques. Aspergillus is a diverse genus of fungi with more than 300 species reported in literature. Aspergillus is important since some species are known allergens and opportunistic human pathogens. Traditionally, growth-dependent methods have been used to detect Aspergillus species in air. However, these methods are limited in the number of isolates that can be analysed for their identities, resulting in inaccurate characterizations of Aspergillus diversities. This study used the high-throughput sequencing to explore Aspergillus diversities in outdoor, which are thought to be difficult to be accurately characterized by traditional growth-dependent techniques. © 2016 The Society for Applied Microbiology.

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

Athavale, Ajay

Ajay Athavale (Monsanto) presents "High Throughput Plasmid Sequencing with Illumina and CLC Bio" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

High-Throughput Sequencing of Arabidopsis microRNAs: Evidence for Frequent Birth and Death of MIRNA Genes

PubMed Central

Fahlgren, Noah; Howell, Miya D.; Kasschau, Kristin D.; Chapman, Elisabeth J.; Sullivan, Christopher M.; Cumbie, Jason S.; Givan, Scott A.; Law, Theresa F.; Grant, Sarah R.; Dangl, Jeffery L.; Carrington, James C.

2007-01-01

In plants, microRNAs (miRNAs) comprise one of two classes of small RNAs that function primarily as negative regulators at the posttranscriptional level. Several MIRNA genes in the plant kingdom are ancient, with conservation extending between angiosperms and the mosses, whereas many others are more recently evolved. Here, we use deep sequencing and computational methods to identify, profile and analyze non-conserved MIRNA genes in Arabidopsis thaliana. 48 non-conserved MIRNA families, nearly all of which were represented by single genes, were identified. Sequence similarity analyses of miRNA precursor foldback arms revealed evidence for recent evolutionary origin of 16 MIRNA loci through inverted duplication events from protein-coding gene sequences. Interestingly, these recently evolved MIRNA genes have taken distinct paths. Whereas some non-conserved miRNAs interact with and regulate target transcripts from gene families that donated parental sequences, others have drifted to the point of non-interaction with parental gene family transcripts. Some young MIRNA loci clearly originated from one gene family but form miRNAs that target transcripts in another family. We suggest that MIRNA genes are undergoing relatively frequent birth and death, with only a subset being stabilized by integration into regulatory networks. PMID:17299599

Environmental microbiology through the lens of high-throughput DNA sequencing: synopsis of current platforms and bioinformatics approaches.

PubMed

Logares, Ramiro; Haverkamp, Thomas H A; Kumar, Surendra; Lanzén, Anders; Nederbragt, Alexander J; Quince, Christopher; Kauserud, Håvard

2012-10-01

The incursion of High-Throughput Sequencing (HTS) in environmental microbiology brings unique opportunities and challenges. HTS now allows a high-resolution exploration of the vast taxonomic and metabolic diversity present in the microbial world, which can provide an exceptional insight on global ecosystem functioning, ecological processes and evolution. This exploration has also economic potential, as we will have access to the evolutionary innovation present in microbial metabolisms, which could be used for biotechnological development. HTS is also challenging the research community, and the current bottleneck is present in the data analysis side. At the moment, researchers are in a sequence data deluge, with sequencing throughput advancing faster than the computer power needed for data analysis. However, new tools and approaches are being developed constantly and the whole process could be depicted as a fast co-evolution between sequencing technology, informatics and microbiologists. In this work, we examine the most popular and recently commercialized HTS platforms as well as bioinformatics methods for data handling and analysis used in microbial metagenomics. This non-exhaustive review is intended to serve as a broad state-of-the-art guide to researchers expanding into this rapidly evolving field. Copyright © 2012 Elsevier B.V. All rights reserved.

Improved Selection of Internal Transcribed Spacer-Specific Primers Enables Quantitative, Ultra-High-Throughput Profiling of Fungal Communities

PubMed Central

Bokulich, Nicholas A.

2013-01-01

Ultra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predicted in silico and by sequencing a “mock community” of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities. PMID:23377949

Detecting DNA double-stranded breaks in mammalian genomes by linear amplification-mediated high-throughput genome-wide translocation sequencing.

PubMed

Hu, Jiazhi; Meyers, Robin M; Dong, Junchao; Panchakshari, Rohit A; Alt, Frederick W; Frock, Richard L

2016-05-01

Unbiased, high-throughput assays for detecting and quantifying DNA double-stranded breaks (DSBs) across the genome in mammalian cells will facilitate basic studies of the mechanisms that generate and repair endogenous DSBs. They will also enable more applied studies, such as those to evaluate the on- and off-target activities of engineered nucleases. Here we describe a linear amplification-mediated high-throughput genome-wide sequencing (LAM-HTGTS) method for the detection of genome-wide 'prey' DSBs via their translocation in cultured mammalian cells to a fixed 'bait' DSB. Bait-prey junctions are cloned directly from isolated genomic DNA using LAM-PCR and unidirectionally ligated to bridge adapters; subsequent PCR steps amplify the single-stranded DNA junction library in preparation for Illumina Miseq paired-end sequencing. A custom bioinformatics pipeline identifies prey sequences that contribute to junctions and maps them across the genome. LAM-HTGTS differs from related approaches because it detects a wide range of broken end structures with nucleotide-level resolution. Familiarity with nucleic acid methods and next-generation sequencing analysis is necessary for library generation and data interpretation. LAM-HTGTS assays are sensitive, reproducible, relatively inexpensive, scalable and straightforward to implement with a turnaround time of <1 week.

High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

PubMed

Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

2016-09-07

Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of whole genome shotgun sequencing for detection and characterization of genetically modified organisms and derived products.

PubMed

Holst-Jensen, Arne; Spilsberg, Bjørn; Arulandhu, Alfred J; Kok, Esther; Shi, Jianxin; Zel, Jana

2016-07-01

The emergence of high-throughput, massive or next-generation sequencing technologies has created a completely new foundation for molecular analyses. Various selective enrichment processes are commonly applied to facilitate detection of predefined (known) targets. Such approaches, however, inevitably introduce a bias and are prone to miss unknown targets. Here we review the application of high-throughput sequencing technologies and the preparation of fit-for-purpose whole genome shotgun sequencing libraries for the detection and characterization of genetically modified and derived products. The potential impact of these new sequencing technologies for the characterization, breeding selection, risk assessment, and traceability of genetically modified organisms and genetically modified products is yet to be fully acknowledged. The published literature is reviewed, and the prospects for future developments and use of the new sequencing technologies for these purposes are discussed.

Development of a high-throughput SNP resource to advance genomic, genetic and breeding research in carrot (Daucus carota L.)

USDA-ARS?s Scientific Manuscript database

The rapid advancement in high-throughput SNP genotyping technologies along with next generation sequencing (NGS) platforms has decreased the cost, improved the quality of large-scale genome surveys, and allowed specialty crops with limited genomic resources such as carrot (Daucus carota) to access t...

High-throughput tetrad analysis.

PubMed

Ludlow, Catherine L; Scott, Adrian C; Cromie, Gareth A; Jeffery, Eric W; Sirr, Amy; May, Patrick; Lin, Jake; Gilbert, Teresa L; Hays, Michelle; Dudley, Aimée M

2013-07-01

Tetrad analysis has been a gold-standard genetic technique for several decades. Unfortunately, the need to manually isolate, disrupt and space tetrads has relegated its application to small-scale studies and limited its integration with high-throughput DNA sequencing technologies. We have developed a rapid, high-throughput method, called barcode-enabled sequencing of tetrads (BEST), that uses (i) a meiosis-specific GFP fusion protein to isolate tetrads by FACS and (ii) molecular barcodes that are read during genotyping to identify spores derived from the same tetrad. Maintaining tetrad information allows accurate inference of missing genetic markers and full genotypes of missing (and presumably nonviable) individuals. An individual researcher was able to isolate over 3,000 yeast tetrads in 3 h, an output equivalent to that of almost 1 month of manual dissection. BEST is transferable to other microorganisms for which meiotic mapping is significantly more laborious.

A Robust Framework for Microbial Archaeology

PubMed Central

Warinner, Christina; Herbig, Alexander; Mann, Allison; Yates, James A. Fellows; Weiβ, Clemens L.; Burbano, Hernán A.; Orlando, Ludovic; Krause, Johannes

2017-01-01

Microbial archaeology is flourishing in the era of high-throughput sequencing, revealing the agents behind devastating historical plagues, identifying the cryptic movements of pathogens in prehistory, and reconstructing the ancestral microbiota of humans. Here, we introduce the fundamental concepts and theoretical framework of the discipline, then discuss applied methodologies for pathogen identification and microbiome characterization from archaeological samples. We give special attention to the process of identifying, validating, and authenticating ancient microbes using high-throughput DNA sequencing data. Finally, we outline standards and precautions to guide future research in the field. PMID:28460196

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.

High throughput 16SrRNA gene sequencing reveals the correlation between Propionibacterium acnes and sarcoidosis.

PubMed

Zhao, Meng-Meng; Du, Shan-Shan; Li, Qiu-Hong; Chen, Tao; Qiu, Hui; Wu, Qin; Chen, Shan-Shan; Zhou, Ying; Zhang, Yuan; Hu, Yang; Su, Yi-Liang; Shen, Li; Zhang, Fen; Weng, Dong; Li, Hui-Ping

2017-02-01

This study aims to use high throughput 16SrRNA gene sequencing to examine the bacterial profile of lymph node biopsy samples of patients with sarcoidosis and to further verify the association between Propionibacterium acnes (P. acnes) and sarcoidosis. A total of 36 mediastinal lymph node biopsy specimens were collected from 17 cases of sarcoidosis, 8 tuberculosis (TB group), and 11 non-infectious lung diseases (control group). The V4 region of the bacterial 16SrRNA gene in the specimens was amplified and sequenced using the high throughput sequencing platform MiSeq, and bacterial profile was established. The data analysis software QIIME and Metastats were used to compare bacterial relative abundance in the three patient groups. Overall, 545 genera were identified; 38 showed significantly lower and 29 had significantly higher relative abundance in the sarcoidosis group than in the TB and control groups (P < 0.01). P. acnes 16SrRNA was exclusively found in all the 17 samples of the sarcoidosis group, whereas was not detected in the TB and control groups. The relative abundance of P. acnes in the sarcoidosis group (0.16% ± 0. 11%) was significantly higher than that in the TB (Metastats analysis: P = 0.0010, q = 0.0044) and control groups (Metastats analysis: P = 0.0010, q = 0.0038). The relative abundance of P. granulosum was only 0.0022% ± 0. 0044% in the sarcoidosis group. P. granulosum 16SrRNA was not detected in the other two groups. High throughput 16SrRNA gene sequencing appears to be a useful tool to investigate the bacterial profile of sarcoidosis specimens. The results suggest that P. acnes may be involved in sarcoidosis development.

High-throughput sequencing in veterinary infection biology and diagnostics.

PubMed

Belák, S; Karlsson, O E; Leijon, M; Granberg, F

2013-12-01

Sequencing methods have improved rapidly since the first versions of the Sanger techniques, facilitating the development of very powerful tools for detecting and identifying various pathogens, such as viruses, bacteria and other microbes. The ongoing development of high-throughput sequencing (HTS; also known as next-generation sequencing) technologies has resulted in a dramatic reduction in DNA sequencing costs, making the technology more accessible to the average laboratory. In this White Paper of the World Organisation for Animal Health (OIE) Collaborating Centre for the Biotechnology-based Diagnosis of Infectious Diseases in Veterinary Medicine (Uppsala, Sweden), several approaches and examples of HTS are summarised, and their diagnostic applicability is briefly discussed. Selected future aspects of HTS are outlined, including the need for bioinformatic resources, with a focus on improving the diagnosis and control of infectious diseases in veterinary medicine.

DnaSAM: Software to perform neutrality testing for large datasets with complex null models.

PubMed

Eckert, Andrew J; Liechty, John D; Tearse, Brandon R; Pande, Barnaly; Neale, David B

2010-05-01

Patterns of DNA sequence polymorphisms can be used to understand the processes of demography and adaptation within natural populations. High-throughput generation of DNA sequence data has historically been the bottleneck with respect to data processing and experimental inference. Advances in marker technologies have largely solved this problem. Currently, the limiting step is computational, with most molecular population genetic software allowing a gene-by-gene analysis through a graphical user interface. An easy-to-use analysis program that allows both high-throughput processing of multiple sequence alignments along with the flexibility to simulate data under complex demographic scenarios is currently lacking. We introduce a new program, named DnaSAM, which allows high-throughput estimation of DNA sequence diversity and neutrality statistics from experimental data along with the ability to test those statistics via Monte Carlo coalescent simulations. These simulations are conducted using the ms program, which is able to incorporate several genetic parameters (e.g. recombination) and demographic scenarios (e.g. population bottlenecks). The output is a set of diversity and neutrality statistics with associated probability values under a user-specified null model that are stored in easy to manipulate text file. © 2009 Blackwell Publishing Ltd.

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.

A comprehensive insight into bacterial virulence in drinking water using 454 pyrosequencing and Illumina high-throughput sequencing.

PubMed

Huang, Kailong; Zhang, Xu-Xiang; Shi, Peng; Wu, Bing; Ren, Hongqiang

2014-11-01

In order to comprehensively investigate bacterial virulence in drinking water, 454 pyrosequencing and Illumina high-throughput sequencing were used to detect potential pathogenic bacteria and virulence factors (VFs) in a full-scale drinking water treatment and distribution system. 16S rRNA gene pyrosequencing revealed high bacterial diversity in the drinking water (441-586 operational taxonomic units). Bacterial diversity decreased after chlorine disinfection, but increased after pipeline distribution. α-Proteobacteria was the most dominant taxonomic class. Alignment against the established pathogen database showed that several types of putative pathogens were present in the drinking water and Pseudomonas aeruginosa had the highest abundance (over 11‰ of total sequencing reads). Many pathogens disappeared after chlorine disinfection, but P. aeruginosa and Leptospira interrogans were still detected in the tap water. High-throughput sequencing revealed prevalence of various pathogenicity islands and virulence proteins in the drinking water, and translocases, transposons, Clp proteases and flagellar motor switch proteins were the predominant VFs. Both diversity and abundance of the detectable VFs increased after the chlorination, and decreased after the pipeline distribution. This study indicates that joint use of 454 pyrosequencing and Illumina sequencing can comprehensively characterize environmental pathogenesis, and several types of putative pathogens and various VFs are prevalent in drinking water. Copyright © 2014 Elsevier Inc. All rights reserved.

On the design of turbo codes

NASA Technical Reports Server (NTRS)

Divsalar, D.; Pollara, F.

1995-01-01

In this article, we design new turbo codes that can achieve near-Shannon-limit performance. The design criterion for random interleavers is based on maximizing the effective free distance of the turbo code, i.e., the minimum output weight of codewords due to weight-2 input sequences. An upper bound on the effective free distance of a turbo code is derived. This upper bound can be achieved if the feedback connection of convolutional codes uses primitive polynomials. We review multiple turbo codes (parallel concatenation of q convolutional codes), which increase the so-called 'interleaving gain' as q and the interleaver size increase, and a suitable decoder structure derived from an approximation to the maximum a posteriori probability decision rule. We develop new rate 1/3, 2/3, 3/4, and 4/5 constituent codes to be used in the turbo encoder structure. These codes, for from 2 to 32 states, are designed by using primitive polynomials. The resulting turbo codes have rates b/n (b = 1, 2, 3, 4 and n = 2, 3, 4, 5, 6), and include random interleavers for better asymptotic performance. These codes are suitable for deep-space communications with low throughput and for near-Earth communications where high throughput is desirable. The performance of these codes is within 1 dB of the Shannon limit at a bit-error rate of 10(exp -6) for throughputs from 1/15 up to 4 bits/s/Hz.

Assembly and diploid architecture of an individual human genome via single-molecule technologies

PubMed Central

Pendleton, Matthew; Sebra, Robert; Pang, Andy Wing Chun; Ummat, Ajay; Franzen, Oscar; Rausch, Tobias; Stütz, Adrian M; Stedman, William; Anantharaman, Thomas; Hastie, Alex; Dai, Heng; Fritz, Markus Hsi-Yang; Cao, Han; Cohain, Ariella; Deikus, Gintaras; Durrett, Russell E; Blanchard, Scott C; Altman, Roger; Chin, Chen-Shan; Guo, Yan; Paxinos, Ellen E; Korbel, Jan O; Darnell, Robert B; McCombie, W Richard; Kwok, Pui-Yan; Mason, Christopher E; Schadt, Eric E; Bashir, Ali

2015-01-01

We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality. PMID:26121404

Assembly and diploid architecture of an individual human genome via single-molecule technologies.

PubMed

Pendleton, Matthew; Sebra, Robert; Pang, Andy Wing Chun; Ummat, Ajay; Franzen, Oscar; Rausch, Tobias; Stütz, Adrian M; Stedman, William; Anantharaman, Thomas; Hastie, Alex; Dai, Heng; Fritz, Markus Hsi-Yang; Cao, Han; Cohain, Ariella; Deikus, Gintaras; Durrett, Russell E; Blanchard, Scott C; Altman, Roger; Chin, Chen-Shan; Guo, Yan; Paxinos, Ellen E; Korbel, Jan O; Darnell, Robert B; McCombie, W Richard; Kwok, Pui-Yan; Mason, Christopher E; Schadt, Eric E; Bashir, Ali

2015-08-01

We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality.

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

PubMed

David, Fabrice P A; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

HTSstation: A Web Application and Open-Access Libraries for High-Throughput Sequencing Data Analysis

PubMed Central

David, Fabrice P. A.; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J.; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch. PMID:24475057

Heterotrophic Proteobacteria in the vicinity of diffuse hydrothermal venting.

PubMed

Meier, Dimitri V; Bach, Wolfgang; Girguis, Peter R; Gruber-Vodicka, Harald R; Reeves, Eoghan P; Richter, Michael; Vidoudez, Charles; Amann, Rudolf; Meyerdierks, Anke

2016-12-01

Deep-sea hydrothermal vents are highly dynamic habitats characterized by steep temperature and chemical gradients. The oxidation of reduced compounds dissolved in the venting fluids fuels primary production providing the basis for extensive life. Until recently studies of microbial vent communities have focused primarily on chemolithoautotrophic organisms. In our study, we targeted the change of microbial community compositions along mixing gradients, focusing on distribution and capabilities of heterotrophic microorganisms. Samples were retrieved from different venting areas within the Menez Gwen hydrothermal field, taken along mixing gradients, including diffuse fluid discharge points, their immediate surroundings and the buoyant parts of hydrothermal plumes. High throughput 16S rRNA gene amplicon sequencing, fluorescence in situ hybridization, and targeted metagenome analysis were combined with geochemical analyses. Close to diffuse venting orifices dominated by chemolithoautotrophic Epsilonproteobacteria, in areas where environmental conditions still supported chemolithoautotrophic processes, we detected microbial communities enriched for versatile heterotrophic Alpha- and Gammaproteobacteria. The potential for alkane degradation could be shown for several genera and yet uncultured clades. We propose that hotspots of chemolithoautotrophic life support a 'belt' of heterotrophic bacteria significantly different from the dominating oligotrophic microbiota of the deep sea. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

High-Throughput rRNA Gene Sequencing Reveals High
and Complex Bacterial Diversity Associated with
Brazilian Coffee Bean Fermentation

PubMed Central

Vinícius de Melo, Gilberto

2018-01-01

Summary Coffee bean fermentation is a spontaneous, on-farm process involving the action of different microbial groups, including bacteria and fungi. In this study, high-throughput sequencing approach was employed to study the diversity and dynamics of bacteria associated with Brazilian coffee bean fermentation. The total DNA from fermenting coffee samples was extracted at different time points, and the 16S rRNA gene with segments around the V4 variable region was sequenced by Illumina high-throughput platform. Using this approach, the presence of over eighty bacterial genera was determined, many of which have been detected for the first time during coffee bean fermentation, including Fructobacillus, Pseudonocardia, Pedobacter, Sphingomonas and Hymenobacter. The presence of Fructobacillus suggests an influence of these bacteria on fructose metabolism during coffee fermentation. Temporal analysis showed a strong dominance of lactic acid bacteria with over 97% of read sequences at the end of fermentation, mainly represented by the Leuconostoc and Lactococcus. Metabolism of lactic acid bacteria was associated with the high formation of lactic acid during fermentation, as determined by HPLC analysis. The results reported in this study confirm the underestimation of bacterial diversity associated with coffee fermentation. New microbial groups reported in this study may be explored as functional starter cultures for on-farm coffee processing.

Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

PubMed

Devailly, Guillaume; Mantsoki, Anna; Joshi, Anagha

2016-11-01

Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Web application: http://www.heatstarseq.roslin.ed.ac.uk/ Source code: https://github.com/gdevailly CONTACT: Guillaume.Devailly@roslin.ed.ac.uk or Anagha.Joshi@roslin.ed.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Ultra-barcoding in cacao (Theobroma spp.; malvaceae) using whole chloroplast genomes and nuclear ribosomal DNA

USDA-ARS?s Scientific Manuscript database

High-throughput next-generation sequencing was used to scan the genome and generate reliable sequence of high copy number regions. Using this method, we examined whole plastid genomes as well as nearly 6000 bases of nuclear ribosomal DNA sequences for nine genotypes of Theobroma cacao and an indivi...

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

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

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

LSGermOPA, a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (Lactuca sativa L.) germplasm fingerprinting

USDA-ARS?s Scientific Manuscript database

We assessed the genetic diversity and population structure among 148 cultivated lettuce (Lactuca sativa L.) accessions using the high-throughput GoldenGate assay and 384 EST (Expressed Sequence Tag)-derived SNP (single nucleotide polymorphism) markers. A custom OPA (Oligo Pool All), LSGermOPA was fo...

Microbial co-occurrence patterns in deep Precambrian bedrock fracture fluids

NASA Astrophysics Data System (ADS)

Purkamo, Lotta; Bomberg, Malin; Kietäväinen, Riikka; Salavirta, Heikki; Nyyssönen, Mari; Nuppunen-Puputti, Maija; Ahonen, Lasse; Kukkonen, Ilmo; Itävaara, Merja

2016-05-01

The bacterial and archaeal community composition and the possible carbon assimilation processes and energy sources of microbial communities in oligotrophic, deep, crystalline bedrock fractures is yet to be resolved. In this study, intrinsic microbial communities from groundwater of six fracture zones from 180 to 2300 m depths in Outokumpu bedrock were characterized using high-throughput amplicon sequencing and metagenomic prediction. Comamonadaceae-, Anaerobrancaceae- and Pseudomonadaceae-related operational taxonomic units (OTUs) form the core community in deep crystalline bedrock fractures in Outokumpu. Archaeal communities were mainly composed of Methanobacteriaceae-affiliating OTUs. The predicted bacterial metagenomes showed that pathways involved in fatty acid and amino sugar metabolism were common. In addition, relative abundance of genes coding the enzymes of autotrophic carbon fixation pathways in predicted metagenomes was low. This indicates that heterotrophic carbon assimilation is more important for microbial communities of the fracture zones. Network analysis based on co-occurrence of OTUs revealed possible "keystone" genera of the microbial communities belonging to Burkholderiales and Clostridiales. Bacterial communities in fractures resemble those found in oligotrophic, hydrogen-enriched environments. Serpentinization reactions of ophiolitic rocks in Outokumpu assemblage may provide a source of energy and organic carbon compounds for the microbial communities in the fractures. Sulfate reducers and methanogens form a minority of the total microbial communities, but OTUs forming these minor groups are similar to those found in other deep Precambrian terrestrial bedrock environments.

The keystone species of Precambrian deep bedrock biosphere belong to Burkholderiales and Clostridiales

NASA Astrophysics Data System (ADS)

Purkamo, L.; Bomberg, M.; Kietäväinen, R.; Salavirta, H.; Nyyssönen, M.; Nuppunen-Puputti, M.; Ahonen, L.; Kukkonen, I.; Itävaara, M.

2015-11-01

The bacterial and archaeal community composition and the possible carbon assimilation processes and energy sources of microbial communities in oligotrophic, deep, crystalline bedrock fractures is yet to be resolved. In this study, intrinsic microbial communities from six fracture zones from 180-2300 m depths in Outokumpu bedrock were characterized using high-throughput amplicon sequencing and metagenomic prediction. Comamonadaceae-, Anaerobrancaceae- and Pseudomonadaceae-related OTUs form the core community in deep crystalline bedrock fractures in Outokumpu. Archaeal communities were mainly composed of Methanobacteraceae-affiliating OTUs. The predicted bacterial metagenomes showed that pathways involved in fatty acid and amino sugar metabolism were common. In addition, relative abundance of genes coding the enzymes of autotrophic carbon fixation pathways in predicted metagenomes was low. This indicates that heterotrophic carbon assimilation is more important for microbial communities of the fracture zones. Network analysis based on co-occurrence of OTUs revealed the keystone genera of the microbial communities belonging to Burkholderiales and Clostridiales. Bacterial communities in fractures resemble those found from oligotrophic, hydrogen-enriched environments. Serpentinization reactions of ophiolitic rocks in Outokumpu assemblage may provide a source of energy and organic carbon compounds for the microbial communities in the fractures. Sulfate reducers and methanogens form a minority of the total microbial communities, but OTUs forming these minor groups are similar to those found from other deep Precambrian terrestrial bedrock environments.

Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms.

PubMed

Yamamoto, Toshio; Nagasaki, Hideki; Yonemaru, Jun-ichi; Ebana, Kaworu; Nakajima, Maiko; Shibaya, Taeko; Yano, Masahiro

2010-04-27

To create useful gene combinations in crop breeding, it is necessary to clarify the dynamics of the genome composition created by breeding practices. A large quantity of single-nucleotide polymorphism (SNP) data is required to permit discrimination of chromosome segments among modern cultivars, which are genetically related. Here, we used a high-throughput sequencer to conduct whole-genome sequencing of an elite Japanese rice cultivar, Koshihikari, which is closely related to Nipponbare, whose genome sequencing has been completed. Then we designed a high-throughput typing array based on the SNP information by comparison of the two sequences. Finally, we applied this array to analyze historical representative rice cultivars to understand the dynamics of their genome composition. The total 5.89-Gb sequence for Koshihikari, equivalent to 15.7 x the entire rice genome, was mapped using the Pseudomolecules 4.0 database for Nipponbare. The resultant Koshihikari genome sequence corresponded to 80.1% of the Nipponbare sequence and led to the identification of 67,051 SNPs. A high-throughput typing array consisting of 1917 SNP sites distributed throughout the genome was designed to genotype 151 representative Japanese cultivars that have been grown during the past 150 years. We could identify the ancestral origin of the pedigree haplotypes in 60.9% of the Koshihikari genome and 18 consensus haplotype blocks which are inherited from traditional landraces to current improved varieties. Moreover, it was predicted that modern breeding practices have generally decreased genetic diversity Detection of genome-wide SNPs by both high-throughput sequencer and typing array made it possible to evaluate genomic composition of genetically related rice varieties. With the aid of their pedigree information, we clarified the dynamics of chromosome recombination during the historical rice breeding process. We also found several genomic regions decreasing genetic diversity which might be caused by a recent human selection in rice breeding. The definition of pedigree haplotypes by means of genome-wide SNPs will facilitate next-generation breeding of rice and other crops.

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

PubMed

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

2014-08-08

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

TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data.

PubMed

Fimereli, Danai; Detours, Vincent; Konopka, Tomasz

2013-04-01

High-throughput sequencing is becoming a popular research tool but carries with it considerable costs in terms of computation time, data storage and bandwidth. Meanwhile, some research applications focusing on individual genes or pathways do not necessitate processing of a full sequencing dataset. Thus, it is desirable to partition a large dataset into smaller, manageable, but relevant pieces. We present a toolkit for partitioning raw sequencing data that includes a method for extracting reads that are likely to map onto pre-defined regions of interest. We show the method can be used to extract information about genes of interest from DNA or RNA sequencing samples in a fraction of the time and disk space required to process and store a full dataset. We report speedup factors between 2.6 and 96, depending on settings and samples used. The software is available at http://www.sourceforge.net/projects/triagetools/.

Measuring Sister Chromatid Cohesion Protein Genome Occupancy in Drosophila melanogaster by ChIP-seq.

PubMed

Dorsett, Dale; Misulovin, Ziva

2017-01-01

This chapter presents methods to conduct and analyze genome-wide chromatin immunoprecipitation of the cohesin complex and the Nipped-B cohesin loading factor in Drosophila cells using high-throughput DNA sequencing (ChIP-seq). Procedures for isolation of chromatin, immunoprecipitation, and construction of sequencing libraries for the Ion Torrent Proton high throughput sequencer are detailed, and computational methods to calculate occupancy as input-normalized fold-enrichment are described. The results obtained by ChIP-seq are compared to those obtained by ChIP-chip (genomic ChIP using tiling microarrays), and the effects of sequencing depth on the accuracy are analyzed. ChIP-seq provides similar sensitivity and reproducibility as ChIP-chip, and identifies the same broad regions of occupancy. The locations of enrichment peaks, however, can differ between ChIP-chip and ChIP-seq, and low sequencing depth can splinter broad regions of occupancy into distinct peaks.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning.

PubMed

Zhang, Sai; Hu, Hailin; Zhou, Jingtian; He, Xuan; Jiang, Tao; Zeng, Jianyang

2017-09-27

Ribosome stalling is manifested by the local accumulation of ribosomes at specific codon positions of mRNAs. Here, we present ROSE, a deep learning framework to analyze high-throughput ribosome profiling data and estimate the probability of a ribosome stalling event occurring at each genomic location. Extensive validation tests on independent data demonstrated that ROSE possessed higher prediction accuracy than conventional prediction models, with an increase in the area under the receiver operating characteristic curve by up to 18.4%. In addition, genome-wide statistical analyses showed that ROSE predictions can be well correlated with diverse putative regulatory factors of ribosome stalling. Moreover, the genome-wide ribosome stalling landscapes of both human and yeast computed by ROSE recovered the functional interplays between ribosome stalling and cotranslational events in protein biogenesis, including protein targeting by the signal recognition particles and protein secondary structure formation. Overall, our study provides a novel method to complement the ribosome profiling techniques and further decipher the complex regulatory mechanisms underlying translation elongation dynamics encoded in the mRNA sequence. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification and functional analysis of flowering related microRNAs in common wild rice (Oryza rufipogon Griff.).

PubMed

Chen, Zongxiang; Li, Fuli; Yang, Songnan; Dong, Yibo; Yuan, Qianhua; Wang, Feng; Li, Weimin; Jiang, Ying; Jia, Shirong; Pei, Xinwu

2013-01-01

MicroRNAs (miRNAs) is a class of non-coding RNAs involved in post- transcriptional control of gene expression, via degradation and/or translational inhibition. Six-hundred sixty-one rice miRNAs are known that are important in plant development. However, flowering-related miRNAs have not been characterized in Oryza rufipogon Griff. It was approved by supervision department of Guangdong wild rice protection. We analyzed flowering-related miRNAs in O. rufipogon using high-throughput sequencing (deep sequencing) to understand the changes that occurred during rice domestication, and to elucidate their functions in flowering. Three O. rufipogon sRNA libraries, two vegetative stage (CWR-V1 and CWR-V2) and one flowering stage (CWR-F2) were sequenced using Illumina deep sequencing. A total of 20,156,098, 21,531,511 and 20,995,942 high quality sRNA reads were obtained from CWR-V1, CWR-V2 and CWR-F2, respectively, of which 3,448,185, 4,265,048 and 2,833,527 reads matched known miRNAs. We identified 512 known rice miRNAs in 214 miRNA families and predicted 290 new miRNAs. Targeted functional annotation, GO and KEGG pathway analyses predicted that 187 miRNAs regulate expression of flowering-related genes. Differential expression analysis of flowering-related miRNAs showed that: expression of 95 miRNAs varied significantly between the libraries, 66 are flowering-related miRNAs, such as oru-miR97, oru-miR117, oru-miR135, oru-miR137, et al. 17 are early-flowering -related miRNAs, including osa-miR160f, osa-miR164d, osa-miR167d, osa-miR169a, osa-miR172b, oru-miR4, et al., induced during the floral transition. Real-time PCR revealed the same expression patterns as deep sequencing. miRNAs targets were confirmed for cleavage by 5'-RACE in vivo, and were negatively regulated by miRNAs. This is the first investigation of flowering miRNAs in wild rice. The result indicates that variation in miRNAs occurred during rice domestication and lays a foundation for further study of phase change and flowering in O. rufipogon. Complicated regulatory networks mediated by multiple miRNAs regulate the expression of flowering genes that control the induction of flowering.

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

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...

Next generation sequencers: methods and applications in food-borne pathogens

USDA-ARS?s Scientific Manuscript database

Next generation sequencers are able to produce millions of short sequence reads in a high-throughput, low-cost way. The emergence of these technologies has not only facilitated genome sequencing but also started to change the landscape of life sciences. This chapter will survey their methods and app...

Genome-wide identification of conserved microRNA and their response to drought stress in Dongxiang wild rice (Oryza rufipogon Griff.).

PubMed

Zhang, Fantao; Luo, Xiangdong; Zhou, Yi; Xie, Jiankun

2016-04-01

To identify drought stress-responsive conserved microRNA (miRNA) from Dongxiang wild rice (Oryza rufipogon Griff., DXWR) on a genome-wide scale, high-throughput sequencing technology was used to sequence libraries of DXWR samples, treated with and without drought stress. 505 conserved miRNAs corresponding to 215 families were identified. 17 were significantly down-regulated and 16 were up-regulated under drought stress. Stem-loop qRT-PCR revealed the same expression patterns as high-throughput sequencing, suggesting the accuracy of the sequencing result was high. Potential target genes of the drought-responsive miRNA were predicted to be involved in diverse biological processes. Furthermore, 16 miRNA families were first identified to be involved in drought stress response from plants. These results present a comprehensive view of the conserved miRNA and their expression patterns under drought stress for DXWR, which will provide valuable information and sequence resources for future basis studies.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

PubMed

Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

2014-05-01

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data.

PubMed

Massouras, Andreas; Decouttere, Frederik; Hens, Korneel; Deplancke, Bart

2010-07-01

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users.

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data

PubMed Central

Massouras, Andreas; Decouttere, Frederik; Hens, Korneel; Deplancke, Bart

2010-01-01

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users. PMID:20501601

Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation

USDA-ARS?s Scientific Manuscript database

Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry). Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker d...

A technological update of molecular diagnostics for infectious diseases

PubMed Central

Liu, Yu-Tsueng

2008-01-01

Identification of a causative pathogen is essential for the choice of treatment for most infectious diseases. Many FDA approved molecular assays; usually more sensitive and specific compared to traditional tests, have been developed in the last decade. A new trend of high throughput and multiplexing assays are emerging thanks to technological developments for the human genome sequencing project. The applications of microarray and ultra high throughput sequencing technologies for diagnostic microbiology are reviewed. The race for the $1000 genome technology by 2014 will have a profound impact in diagnosis and treatment of infectious diseases in the near future. PMID:18782035

GENETIC-BASED ANALYTICAL METHODS FOR BACTERIA AND FUNGI

EPA Science Inventory

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

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

In silico assessment of primers for eDNA studies using PrimerTree and application to characterize the biodiversity surrounding the Cuyahoga River

NASA Astrophysics Data System (ADS)

Cannon, M. V.; Hester, J.; Shalkhauser, A.; Chan, E. R.; Logue, K.; Small, S. T.; Serre, D.

2016-03-01

Analysis of environmental DNA (eDNA) enables the detection of species of interest from water and soil samples, typically using species-specific PCR. Here, we describe a method to characterize the biodiversity of a given environment by amplifying eDNA using primer pairs targeting a wide range of taxa and high-throughput sequencing for species identification. We tested this approach on 91 water samples of 40 mL collected along the Cuyahoga River (Ohio, USA). We amplified eDNA using 12 primer pairs targeting mammals, fish, amphibians, birds, bryophytes, arthropods, copepods, plants and several microorganism taxa and sequenced all PCR products simultaneously by high-throughput sequencing. Overall, we identified DNA sequences from 15 species of fish, 17 species of mammals, 8 species of birds, 15 species of arthropods, one turtle and one salamander. Interestingly, in addition to aquatic and semi-aquatic animals, we identified DNA from terrestrial species that live near the Cuyahoga River. We also identified DNA from one Asian carp species invasive to the Great Lakes but that had not been previously reported in the Cuyahoga River. Our study shows that analysis of eDNA extracted from small water samples using wide-range PCR amplification combined with high-throughput sequencing can provide a broad perspective on biological diversity.

In silico assessment of primers for eDNA studies using PrimerTree and application to characterize the biodiversity surrounding the Cuyahoga River

PubMed Central

Cannon, M. V.; Hester, J.; Shalkhauser, A.; Chan, E. R.; Logue, K.; Small, S. T.; Serre, D.

2016-01-01

Analysis of environmental DNA (eDNA) enables the detection of species of interest from water and soil samples, typically using species-specific PCR. Here, we describe a method to characterize the biodiversity of a given environment by amplifying eDNA using primer pairs targeting a wide range of taxa and high-throughput sequencing for species identification. We tested this approach on 91 water samples of 40 mL collected along the Cuyahoga River (Ohio, USA). We amplified eDNA using 12 primer pairs targeting mammals, fish, amphibians, birds, bryophytes, arthropods, copepods, plants and several microorganism taxa and sequenced all PCR products simultaneously by high-throughput sequencing. Overall, we identified DNA sequences from 15 species of fish, 17 species of mammals, 8 species of birds, 15 species of arthropods, one turtle and one salamander. Interestingly, in addition to aquatic and semi-aquatic animals, we identified DNA from terrestrial species that live near the Cuyahoga River. We also identified DNA from one Asian carp species invasive to the Great Lakes but that had not been previously reported in the Cuyahoga River. Our study shows that analysis of eDNA extracted from small water samples using wide-range PCR amplification combined with high-throughput sequencing can provide a broad perspective on biological diversity. PMID:26965911

Novel genetic tools for studying food-borne Salmonella.

PubMed

Andrews-Polymenis, Helene L; Santiviago, Carlos A; McClelland, Michael

2009-04-01

Nontyphoidal Salmonellae are highly prevalent food-borne pathogens. High-throughput sequencing of Salmonella genomes is expanding our knowledge of the evolution of serovars and epidemic isolates. Genome sequences have also allowed the creation of complete microarrays. Microarrays have improved the throughput of in vivo expression technology (IVET) used to uncover promoters active during infection. In another method, signature tagged mutagenesis (STM), pools of mutants are subjected to selection. Changes in the population are monitored on a microarray, revealing genes under selection. Complete genome sequences permit the construction of pools of targeted in-frame deletions that have improved STM by minimizing the number of clones and the polarity of each mutant. Together, genome sequences and the continuing development of new tools for functional genomics will drive a revolution in the understanding of Salmonellae in many different niches that are critical for food safety.

Personalized Oncology Through Integrative High-Throughput Sequencing: A Pilot Study

PubMed Central

Roychowdhury, Sameek; Iyer, Matthew K.; Robinson, Dan R.; Lonigro, Robert J.; Wu, Yi-Mi; Cao, Xuhong; Kalyana-Sundaram, Shanker; Sam, Lee; Balbin, O. Alejandro; Quist, Michael J.; Barrette, Terrence; Everett, Jessica; Siddiqui, Javed; Kunju, Lakshmi P.; Navone, Nora; Araujo, John C.; Troncoso, Patricia; Logothetis, Christopher J.; Innis, Jeffrey W.; Smith, David C.; Lao, Christopher D.; Kim, Scott Y.; Roberts, J. Scott; Gruber, Stephen B.; Pienta, Kenneth J.; Talpaz, Moshe; Chinnaiyan, Arul M.

2012-01-01

Individual cancers harbor a set of genetic aberrations that can be informative for identifying rational therapies currently available or in clinical trials. We implemented a pilot study to explore the practical challenges of applying high-throughput sequencing in clinical oncology. We enrolled patients with advanced or refractory cancer who were eligible for clinical trials. For each patient, we performed whole-genome sequencing of the tumor, targeted whole-exome sequencing of tumor and normal DNA, and transcriptome sequencing (RNA-Seq) of the tumor to identify potentially informative mutations in a clinically relevant time frame of 3 to 4 weeks. With this approach, we detected several classes of cancer mutations including structural rearrangements, copy number alterations, point mutations, and gene expression alterations. A multidisciplinary Sequencing Tumor Board (STB) deliberated on the clinical interpretation of the sequencing results obtained. We tested our sequencing strategy on human prostate cancer xenografts. Next, we enrolled two patients into the clinical protocol and were able to review the results at our STB within 24 days of biopsy. The first patient had metastatic colorectal cancer in which we identified somatic point mutations in NRAS, TP53, AURKA, FAS, and MYH11, plus amplification and overexpression of cyclin-dependent kinase 8 (CDK8). The second patient had malignant melanoma, in which we identified a somatic point mutation in HRAS and a structural rearrangement affecting CDKN2C. The STB identified the CDK8 amplification and Ras mutation as providing a rationale for clinical trials with CDK inhibitors or MEK (mitogenactivated or extracellular signal–regulated protein kinase kinase) and PI3K (phosphatidylinositol 3-kinase) inhibitors, respectively. Integrative high-throughput sequencing of patients with advanced cancer generates a comprehensive, individual mutational landscape to facilitate biomarker-driven clinical trials in oncology. PMID:22133722

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.

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.

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

PubMed

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

2017-10-24

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

High-Throughput Analysis of T-DNA Location and Structure Using Sequence Capture.

PubMed

Inagaki, Soichi; Henry, Isabelle M; Lieberman, Meric C; Comai, Luca

2015-01-01

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA-genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously, using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. Our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.

Improved Protocols for Illumina Sequencing

PubMed Central

Bronner, Iraad F.; Quail, Michael A.; Turner, Daniel J.; Swerdlow, Harold

2013-01-01

In this unit, we describe a set of improvements we have made to the standard Illumina protocols to make the sequencing process more reliable in a high-throughput environment, reduce amplification bias, narrow the distribution of insert sizes, and reliably obtain high yields of data. PMID:19582764

Appliation of rad-sequencing to linkage mapping in citrus

USDA-ARS?s Scientific Manuscript database

High density linkage maps can be developed for modest cost using high-throughput DNA sequencing to genotype a defined fraction (representation) of the genome. We developed linkage maps in two citrus populations using the RAD (Restriction site Associated DNA) genotyping method which involves restrict...

MToolBox: a highly automated pipeline for heteroplasmy annotation and prioritization analysis of human mitochondrial variants in high-throughput sequencing

PubMed Central

Diroma, Maria Angela; Santorsola, Mariangela; Guttà, Cristiano; Gasparre, Giuseppe; Picardi, Ernesto; Pesole, Graziano; Attimonelli, Marcella

2014-01-01

Motivation: The increasing availability of mitochondria-targeted and off-target sequencing data in whole-exome and whole-genome sequencing studies (WXS and WGS) has risen the demand of effective pipelines to accurately measure heteroplasmy and to easily recognize the most functionally important mitochondrial variants among a huge number of candidates. To this purpose, we developed MToolBox, a highly automated pipeline to reconstruct and analyze human mitochondrial DNA from high-throughput sequencing data. Results: MToolBox implements an effective computational strategy for mitochondrial genomes assembling and haplogroup assignment also including a prioritization analysis of detected variants. MToolBox provides a Variant Call Format file featuring, for the first time, allele-specific heteroplasmy and annotation files with prioritized variants. MToolBox was tested on simulated samples and applied on 1000 Genomes WXS datasets. Availability and implementation: MToolBox package is available at https://sourceforge.net/projects/mtoolbox/. Contact: marcella.attimonelli@uniba.it Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25028726

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

NASA Astrophysics Data System (ADS)

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-06-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs.

Deep COI sequencing of standardized benthic samples unveils overlooked diversity of Jordanian coral reefs in the northern Red Sea.

PubMed

Al-Rshaidat, Mamoon M D; Snider, Allison; Rosebraugh, Sydney; Devine, Amanda M; Devine, Thomas D; Plaisance, Laetitia; Knowlton, Nancy; Leray, Matthieu

2016-09-01

High-throughput sequencing (HTS) of DNA barcodes (metabarcoding), particularly when combined with standardized sampling protocols, is one of the most promising approaches for censusing overlooked cryptic invertebrate communities. We present biodiversity estimates based on sequencing of the cytochrome c oxidase subunit 1 (COI) gene for coral reefs of the Gulf of Aqaba, a semi-enclosed system in the northern Red Sea. Samples were obtained from standardized sampling devices (Autonomous Reef Monitoring Structures (ARMS)) deployed for 18 months. DNA barcoding of non-sessile specimens >2 mm revealed 83 OTUs in six phyla, of which only 25% matched a reference sequence in public databases. Metabarcoding of the 2 mm - 500 μm and sessile bulk fractions revealed 1197 OTUs in 15 animal phyla, of which only 4.9% matched reference barcodes. These results highlight the scarcity of COI data for cryptobenthic organisms of the Red Sea. Compared with data obtained using similar methods, our results suggest that Gulf of Aqaba reefs are less diverse than two Pacific coral reefs but much more diverse than an Atlantic oyster reef at a similar latitude. The standardized approaches used here show promise for establishing baseline data on biodiversity, monitoring the impacts of environmental change, and quantifying patterns of diversity at regional and global scales.

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

PubMed Central

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-01-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs. PMID:26047353

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

PubMed

Liu, Qiao; Xia, Fei; Yin, Qijin; Jiang, Rui

2018-03-01

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies. We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases. Deopen is freely available at https://github.com/kimmo1019/Deopen. ruijiang@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

A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection

PubMed Central

Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike

2018-01-01

ABSTRACT Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection. PMID:29564396

A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection.

PubMed

Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike; Khan, Arifa S

2018-01-01

Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection.

A map of human genome variation from population-scale sequencing.

PubMed

Abecasis, Gonçalo R; Altshuler, David; Auton, Adam; Brooks, Lisa D; Durbin, Richard M; Gibbs, Richard A; Hurles, Matt E; McVean, Gil A

2010-10-28

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

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

USDA-ARS?s Scientific Manuscript database

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

Diff-seq: A high throughput sequencing-based mismatch detection assay for DNA variant enrichment and discovery

PubMed Central

Karas, Vlad O; Sinnott-Armstrong, Nicholas A; Varghese, Vici; Shafer, Robert W; Greenleaf, William J; Sherlock, Gavin

2018-01-01

Abstract Much of the within species genetic variation is in the form of single nucleotide polymorphisms (SNPs), typically detected by whole genome sequencing (WGS) or microarray-based technologies. However, WGS produces mostly uninformative reads that perfectly match the reference, while microarrays require genome-specific reagents. We have developed Diff-seq, a sequencing-based mismatch detection assay for SNP discovery without the requirement for specialized nucleic-acid reagents. Diff-seq leverages the Surveyor endonuclease to cleave mismatched DNA molecules that are generated after cross-annealing of a complex pool of DNA fragments. Sequencing libraries enriched for Surveyor-cleaved molecules result in increased coverage at the variant sites. Diff-seq detected all mismatches present in an initial test substrate, with specific enrichment dependent on the identity and context of the variation. Application to viral sequences resulted in increased observation of variant alleles in a biologically relevant context. Diff-Seq has the potential to increase the sensitivity and efficiency of high-throughput sequencing in the detection of variation. PMID:29361139

FMLRC: Hybrid long read error correction using an FM-index.

PubMed

Wang, Jeremy R; Holt, James; McMillan, Leonard; Jones, Corbin D

2018-02-09

Long read sequencing is changing the landscape of genomic research, especially de novo assembly. Despite the high error rate inherent to long read technologies, increased read lengths dramatically improve the continuity and accuracy of genome assemblies. However, the cost and throughput of these technologies limits their application to complex genomes. One solution is to decrease the cost and time to assemble novel genomes by leveraging "hybrid" assemblies that use long reads for scaffolding and short reads for accuracy. We describe a novel method leveraging a multi-string Burrows-Wheeler Transform with auxiliary FM-index to correct errors in long read sequences using a set of complementary short reads. We demonstrate that our method efficiently produces significantly more high quality corrected sequence than existing hybrid error-correction methods. We also show that our method produces more contiguous assemblies, in many cases, than existing state-of-the-art hybrid and long-read only de novo assembly methods. Our method accurately corrects long read sequence data using complementary short reads. We demonstrate higher total throughput of corrected long reads and a corresponding increase in contiguity of the resulting de novo assemblies. Improved throughput and computational efficiency than existing methods will help better economically utilize emerging long read sequencing technologies.

Analysis of Illumina Microbial Assemblies

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

Clum, Alicia; Foster, Brian; Froula, Jeff

2010-05-28

Since the emerging of second generation sequencing technologies, the evaluation of different sequencing approaches and their assembly strategies for different types of genomes has become an important undertaken. Next generation sequencing technologies dramatically increase sequence throughput while decreasing cost, making them an attractive tool for whole genome shotgun sequencing. To compare different approaches for de-novo whole genome assembly, appropriate tools and a solid understanding of both quantity and quality of the underlying sequence data are crucial. Here, we performed an in-depth analysis of short-read Illumina sequence assembly strategies for bacterial and archaeal genomes. Different types of Illumina libraries as wellmore » as different trim parameters and assemblers were evaluated. Results of the comparative analysis and sequencing platforms will be presented. The goal of this analysis is to develop a cost-effective approach for the increased throughput of the generation of high quality microbial genomes.« less

Next Generation Sequencing at the University of Chicago Genomics Core

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

Faber, Pieter

2013-04-24

The University of Chicago Genomics Core provides University of Chicago investigators (and external clients) access to State-of-the-Art genomics capabilities: next generation sequencing, Sanger sequencing / genotyping and micro-arrays (gene expression, genotyping, and methylation). The current presentation will highlight our capabilities in the area of ultra-high throughput sequencing analysis.

Mutation detection using automated fluorescence-based sequencing.

PubMed

Montgomery, Kate T; Iartchouck, Oleg; Li, Li; Perera, Anoja; Yassin, Yosuf; Tamburino, Alex; Loomis, Stephanie; Kucherlapati, Raju

2008-04-01

The development of high-throughput DNA sequencing techniques has made direct DNA sequencing of PCR-amplified genomic DNA a rapid and economical approach to the identification of polymorphisms that may play a role in disease. Point mutations as well as small insertions or deletions are readily identified by DNA sequencing. The mutations may be heterozygous (occurring in one allele while the other allele retains the normal sequence) or homozygous (occurring in both alleles). Sequencing alone cannot discriminate between true homozygosity and apparent homozygosity due to the loss of one allele due to a large deletion. In this unit, strategies are presented for using PCR amplification and automated fluorescence-based sequencing to identify sequence variation. The size of the project and laboratory preference and experience will dictate how the data is managed and which software tools are used for analysis. A high-throughput protocol is given that has been used to search for mutations in over 200 different genes at the Harvard Medical School - Partners Center for Genetics and Genomics (HPCGG, http://www.hpcgg.org/). Copyright 2008 by John Wiley & Sons, Inc.

A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments.

PubMed

Bansal, Vikas

2017-03-14

PCR amplification is an important step in the preparation of DNA sequencing libraries prior to high-throughput sequencing. PCR amplification introduces redundant reads in the sequence data and estimating the PCR duplication rate is important to assess the frequency of such reads. Existing computational methods do not distinguish PCR duplicates from "natural" read duplicates that represent independent DNA fragments and therefore, over-estimate the PCR duplication rate for DNA-seq and RNA-seq experiments. In this paper, we present a computational method to estimate the average PCR duplication rate of high-throughput sequence datasets that accounts for natural read duplicates by leveraging heterozygous variants in an individual genome. Analysis of simulated data and exome sequence data from the 1000 Genomes project demonstrated that our method can accurately estimate the PCR duplication rate on paired-end as well as single-end read datasets which contain a high proportion of natural read duplicates. Further, analysis of exome datasets prepared using the Nextera library preparation method indicated that 45-50% of read duplicates correspond to natural read duplicates likely due to fragmentation bias. Finally, analysis of RNA-seq datasets from individuals in the 1000 Genomes project demonstrated that 70-95% of read duplicates observed in such datasets correspond to natural duplicates sampled from genes with high expression and identified outlier samples with a 2-fold greater PCR duplication rate than other samples. The method described here is a useful tool for estimating the PCR duplication rate of high-throughput sequence datasets and for assessing the fraction of read duplicates that correspond to natural read duplicates. An implementation of the method is available at https://github.com/vibansal/PCRduplicates .

Isolating Viral and Host RNA Sequences from Archival Material and Production of cDNA Libraries for High-Throughput DNA Sequencing

PubMed Central

Xiao, Yongli; Sheng, Zong-Mei; Taubenberger, Jeffery K.

2015-01-01

The vast majority of surgical biopsy and post-mortem tissue samples are formalin-fixed and paraffin-embedded (FFPE), but this process leads to RNA degradation that limits gene expression analysis. As an example, the viral RNA genome of the 1918 pandemic influenza A virus was previously determined in a 9-year effort by overlapping RT-PCR from post-mortem samples. Using the protocols described here, the full genome of the 1918 virus at high coverage was determined in one high-throughput sequencing run of a cDNA library derived from total RNA of a 1918 FFPE sample after duplex-specific nuclease treatments. This basic methodological approach should assist in the analysis of FFPE tissue samples isolated over the past century from a variety of infectious diseases. PMID:26344216

An Updated Collection of Sequence Barcoded Temperature-Sensitive Alleles of Yeast Essential Genes

PubMed Central

Kofoed, Megan; Milbury, Karissa L.; Chiang, Jennifer H.; Sinha, Sunita; Ben-Aroya, Shay; Giaever, Guri; Nislow, Corey; Hieter, Philip; Stirling, Peter C.

2015-01-01

Systematic analyses of essential gene function using mutant collections in Saccharomyces cerevisiae have been conducted using collections of heterozygous diploids, promoter shut-off alleles, through alleles with destabilized mRNA, destabilized protein, or bearing mutations that lead to a temperature-sensitive (ts) phenotype. We previously described a method for construction of barcoded ts alleles in a systematic fashion. Here we report the completion of this collection of alleles covering 600 essential yeast genes. This resource covers a larger gene repertoire than previous collections and provides a complementary set of strains suitable for single gene and genomic analyses. We use deep sequencing to characterize the amino acid changes leading to the ts phenotype in half of the alleles. We also use high-throughput approaches to describe the relative ts behavior of the alleles. Finally, we demonstrate the experimental usefulness of the collection in a high-content, functional genomic screen for ts alleles that increase spontaneous P-body formation. By increasing the number of alleles and improving the annotation, this ts collection will serve as a community resource for probing new aspects of biology for essential yeast genes. PMID:26175450

An Updated Collection of Sequence Barcoded Temperature-Sensitive Alleles of Yeast Essential Genes.

PubMed

Kofoed, Megan; Milbury, Karissa L; Chiang, Jennifer H; Sinha, Sunita; Ben-Aroya, Shay; Giaever, Guri; Nislow, Corey; Hieter, Philip; Stirling, Peter C

2015-07-14

Systematic analyses of essential gene function using mutant collections in Saccharomyces cerevisiae have been conducted using collections of heterozygous diploids, promoter shut-off alleles, through alleles with destabilized mRNA, destabilized protein, or bearing mutations that lead to a temperature-sensitive (ts) phenotype. We previously described a method for construction of barcoded ts alleles in a systematic fashion. Here we report the completion of this collection of alleles covering 600 essential yeast genes. This resource covers a larger gene repertoire than previous collections and provides a complementary set of strains suitable for single gene and genomic analyses. We use deep sequencing to characterize the amino acid changes leading to the ts phenotype in half of the alleles. We also use high-throughput approaches to describe the relative ts behavior of the alleles. Finally, we demonstrate the experimental usefulness of the collection in a high-content, functional genomic screen for ts alleles that increase spontaneous P-body formation. By increasing the number of alleles and improving the annotation, this ts collection will serve as a community resource for probing new aspects of biology for essential yeast genes. Copyright © 2015 Kofoed et al.

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

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

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

Impact of sequencing depth in ChIP-seq experiments

PubMed Central

Jung, Youngsook L.; Luquette, Lovelace J.; Ho, Joshua W.K.; Ferrari, Francesco; Tolstorukov, Michael; Minoda, Aki; Issner, Robbyn; Epstein, Charles B.; Karpen, Gary H.; Kuroda, Mitzi I.; Park, Peter J.

2014-01-01

In a chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiment, an important consideration in experimental design is the minimum number of sequenced reads required to obtain statistically significant results. We present an extensive evaluation of the impact of sequencing depth on identification of enriched regions for key histone modifications (H3K4me3, H3K36me3, H3K27me3 and H3K9me2/me3) using deep-sequenced datasets in human and fly. We propose to define sufficient sequencing depth as the number of reads at which detected enrichment regions increase <1% for an additional million reads. Although the required depth depends on the nature of the mark and the state of the cell in each experiment, we observe that sufficient depth is often reached at <20 million reads for fly. For human, there are no clear saturation points for the examined datasets, but our analysis suggests 40–50 million reads as a practical minimum for most marks. We also devise a mathematical model to estimate the sufficient depth and total genomic coverage of a mark. Lastly, we find that the five algorithms tested do not agree well for broad enrichment profiles, especially at lower depths. Our findings suggest that sufficient sequencing depth and an appropriate peak-calling algorithm are essential for ensuring robustness of conclusions derived from ChIP-seq data. PMID:24598259

First report of Beet western yellows virus infecting Epiphyllum spp

USDA-ARS?s Scientific Manuscript database

Beet western yellow virus (BWYV) was identified from an orchid cactus (Epiphyllum spp.) hybrid without obvious symptoms by high-throughput sequencing. The nearly complete genomic sequence of 5,458 nucleotides of the virus was determined. The isolate has the highest nucleotide sequence identity (93%)...

High-throughput DNA separation in nanofilter arrays.

PubMed

Choi, Sungup; Kim, Ju Min; Ahn, Kyung Hyun; Lee, Seung Jong

2014-08-01

We numerically investigated the dynamics of short double-stranded DNA molecules moving through a deep-shallow alternating nanofilter, by utilizing Brownian dynamics simulation. We propose a novel mechanism for high-throughput DNA separation with a high electric field, which was originally predicted by Laachi et al. [Phys. Rev. Lett. 2007, 98, 098106]. In this work, we show that DNA molecules deterministically move along different electrophoretic streamlines according to their length, owing to geometric constraint at the exit of the shallow region. Consequently, it is more probable that long DNA molecules pass over a deep well region without significant lateral migration toward the bottom of the deep well, which is in contrast to the long dwelling time for short DNA molecules. We investigated the dynamics of DNA passage through a nanofilter facilitating electrophoretic field kinematics. The statistical distribution of the DNA molecules according to their size clearly corroborates our assumption. On the other hand, it was also found that the tapering angle between the shallow and deep regions significantly affects the DNA separation performance. The current results show that the nonuniform field effect combined with geometric constraint plays a key role in nanofilter-based DNA separation. We expect that our results will be helpful in designing and operating nanofluidics-based DNA separation devices and in understanding the polymer dynamics in confined geometries. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Polymerase chain reaction-hybridization method using urease gene sequences for high-throughput Ureaplasma urealyticum and Ureaplasma parvum detection and differentiation.

PubMed

Xu, Chen; Zhang, Nan; Huo, Qianyu; Chen, Minghui; Wang, Rengfeng; Liu, Zhili; Li, Xue; Liu, Yunde; Bao, Huijing

2016-04-15

In this article, we discuss the polymerase chain reaction (PCR)-hybridization assay that we developed for high-throughput simultaneous detection and differentiation of Ureaplasma urealyticum and Ureaplasma parvum using one set of primers and two specific DNA probes based on urease gene nucleotide sequence differences. First, U. urealyticum and U. parvum DNA samples were specifically amplified using one set of biotin-labeled primers. Furthermore, amine-modified DNA probes, which can specifically react with U. urealyticum or U. parvum DNA, were covalently immobilized to a DNA-BIND plate surface. The plate was then incubated with the PCR products to facilitate sequence-specific DNA binding. Horseradish peroxidase-streptavidin conjugation and a colorimetric assay were used. Based on the results, the PCR-hybridization assay we developed can specifically differentiate U. urealyticum and U. parvum with high sensitivity (95%) compared with cultivation (72.5%). Hence, this study demonstrates a new method for high-throughput simultaneous differentiation and detection of U. urealyticum and U. parvum with high sensitivity. Based on these observations, the PCR-hybridization assay developed in this study is ideal for detecting and discriminating U. urealyticum and U. parvum in clinical applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Genome-Wide Identification of Different Dormant Medicago sativa L. MicroRNAs in Response to Fall Dormancy

PubMed Central

Du, Hongqi; Sun, Xiaoge; Shi, Yinghua; Wang, Chengzhang

2014-01-01

Background MicroRNAs (miRNAs) are a class of regulatory small RNAs (sRNAs) that regulate gene post-transcriptional expression in plants and animals. High-throughput sequencing technology is capable of identifying small RNAs in plant species. Alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage legumes worldwide, and fall dormancy is an adaptive characteristic related to the biomass production and winter survival in alfalfa. Here, we applied high-throughput sRNA sequencing to identify some miRNAs that were responsive to fall dormancy in standard variety (Maverick and CUF101) of alfalfa. Results Four sRNA libraries were generated and sequenced from alfalfa leaves in two typical varieties at distinct seasons. Through integrative analysis, we identified 51 novel miRNA candidates of 206 families. Additionally, we identified 28 miRNAs associated with fall dormancy in standard variety (Maverick and CUF101), including 20 known miRNAs and eight novel miRNAs. Both high-throughput sequencing and RT-qPCR confirmed that eight known miRNA members were up-regulated and six known miRNA members were down-regulated in response to fall dormancy in standard variety (Maverick and CUF101). Among the 51 novel miRNA candidates, five miRNAs were up-regulated and three miRNAs were down-regulated in response to fall dormancy in standard variety (Maverick and CUF101), and five of them were confirmed by Northern blot analysis. Conclusion We identified 20 known miRNAs and eight new miRNA candidates that were responsive to fall dormancy in standard variety (Maverick and CUF101) by high-throughput sequencing of small RNAs from Medicago sativa. Our data provide a useful resource for investigating miRNA-mediated regulatory mechanisms of fall dormancy in alfalfa, and these findings are important for our understanding of the roles played by miRNAs in the response of plants to abiotic stress in general and fall dormancy in alfalfa. PMID:25473944

Genome-wide identification of different dormant Medicago sativa L. MicroRNAs in response to fall dormancy.

PubMed

Fan, Wenna; Zhang, Senhao; Du, Hongqi; Sun, Xiaoge; Shi, Yinghua; Wang, Chengzhang

2014-01-01

MicroRNAs (miRNAs) are a class of regulatory small RNAs (sRNAs) that regulate gene post-transcriptional expression in plants and animals. High-throughput sequencing technology is capable of identifying small RNAs in plant species. Alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage legumes worldwide, and fall dormancy is an adaptive characteristic related to the biomass production and winter survival in alfalfa. Here, we applied high-throughput sRNA sequencing to identify some miRNAs that were responsive to fall dormancy in standard variety (Maverick and CUF101) of alfalfa. Four sRNA libraries were generated and sequenced from alfalfa leaves in two typical varieties at distinct seasons. Through integrative analysis, we identified 51 novel miRNA candidates of 206 families. Additionally, we identified 28 miRNAs associated with fall dormancy in standard variety (Maverick and CUF101), including 20 known miRNAs and eight novel miRNAs. Both high-throughput sequencing and RT-qPCR confirmed that eight known miRNA members were up-regulated and six known miRNA members were down-regulated in response to fall dormancy in standard variety (Maverick and CUF101). Among the 51 novel miRNA candidates, five miRNAs were up-regulated and three miRNAs were down-regulated in response to fall dormancy in standard variety (Maverick and CUF101), and five of them were confirmed by Northern blot analysis. We identified 20 known miRNAs and eight new miRNA candidates that were responsive to fall dormancy in standard variety (Maverick and CUF101) by high-throughput sequencing of small RNAs from Medicago sativa. Our data provide a useful resource for investigating miRNA-mediated regulatory mechanisms of fall dormancy in alfalfa, and these findings are important for our understanding of the roles played by miRNAs in the response of plants to abiotic stress in general and fall dormancy in alfalfa.

Direct AUC optimization of regulatory motifs.

PubMed

Zhu, Lin; Zhang, Hong-Bo; Huang, De-Shuang

2017-07-15

The discovery of transcription factor binding site (TFBS) motifs is essential for untangling the complex mechanism of genetic variation under different developmental and environmental conditions. Among the huge amount of computational approaches for de novo identification of TFBS motifs, discriminative motif learning (DML) methods have been proven to be promising for harnessing the discovery power of accumulated huge amount of high-throughput binding data. However, they have to sacrifice accuracy for speed and could fail to fully utilize the information of the input sequences. We propose a novel algorithm called CDAUC for optimizing DML-learned motifs based on the area under the receiver-operating characteristic curve (AUC) criterion, which has been widely used in the literature to evaluate the significance of extracted motifs. We show that when the considered AUC loss function is optimized in a coordinate-wise manner, the cost function of each resultant sub-problem is a piece-wise constant function, whose optimal value can be found exactly and efficiently. Further, a key step of each iteration of CDAUC can be efficiently solved as a computational geometry problem. Experimental results on real world high-throughput datasets illustrate that CDAUC outperforms competing methods for refining DML motifs, while being one order of magnitude faster. Meanwhile, preliminary results also show that CDAUC may also be useful for improving the interpretability of convolutional kernels generated by the emerging deep learning approaches for predicting TF sequences specificities. CDAUC is available at: https://drive.google.com/drive/folders/0BxOW5MtIZbJjNFpCeHlBVWJHeW8 . dshuang@tongji.edu.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

Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens.

PubMed

Paul, Fiona; Otte, Jürgen; Schmitt, Imke; Dal Grande, Francesco

2018-06-05

The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallus in several lichen species. This differs from Sanger technology, which typically yields a single, unambiguous algal sequence per individual. Here we compared HTS and Sanger methods for estimating the diversity of green algal symbionts within lichen thalli using 240 lichen individuals belonging to two species of lichen-forming fungi. According to HTS data, Sanger technology consistently yielded the most abundant photobiont sequence in the sample. However, if the second most abundant photobiont exceeded 30% of the total HTS reads in a sample, Sanger sequencing generally failed. Our results suggest that most lichen individuals in the two analyzed species, Lasallia hispanica and L. pustulata, indeed contain a single, predominant green algal photobiont. We conclude that Sanger sequencing is a valid approach to detect the dominant photobionts in lichen individuals and populations. We discuss which research areas in lichen ecology and evolution will continue to benefit from Sanger sequencing, and which areas will profit from HTS approaches to assessing symbiont diversity.

Genome-derived vaccines.

PubMed

De Groot, Anne S; Rappuoli, Rino

2004-02-01

Vaccine research entered a new era when the complete genome of a pathogenic bacterium was published in 1995. Since then, more than 97 bacterial pathogens have been sequenced and at least 110 additional projects are now in progress. Genome sequencing has also dramatically accelerated: high-throughput facilities can draft the sequence of an entire microbe (two to four megabases) in 1 to 2 days. Vaccine developers are using microarrays, immunoinformatics, proteomics and high-throughput immunology assays to reduce the truly unmanageable volume of information available in genome databases to a manageable size. Vaccines composed by novel antigens discovered from genome mining are already in clinical trials. Within 5 years we can expect to see a novel class of vaccines composed by genome-predicted, assembled and engineered T- and Bcell epitopes. This article addresses the convergence of three forces--microbial genome sequencing, computational immunology and new vaccine technologies--that are shifting genome mining for vaccines onto the forefront of immunology research.

Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

PubMed Central

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-01-01

Summary It has long been the dream of biologists to map gene expression at the single cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after LIF withdrawal. The reproducibility of these high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships. PMID:26000487

A High-Throughput Process for the Solid-Phase Purification of Synthetic DNA Sequences

PubMed Central

Grajkowski, Andrzej; Cieślak, Jacek; Beaucage, Serge L.

2017-01-01

An efficient process for the purification of synthetic phosphorothioate and native DNA sequences is presented. The process is based on the use of an aminopropylated silica gel support functionalized with aminooxyalkyl functions to enable capture of DNA sequences through an oximation reaction with the keto function of a linker conjugated to the 5′-terminus of DNA sequences. Deoxyribonucleoside phosphoramidites carrying this linker, as a 5′-hydroxyl protecting group, have been synthesized for incorporation into DNA sequences during the last coupling step of a standard solid-phase synthesis protocol executed on a controlled pore glass (CPG) support. Solid-phase capture of the nucleobase- and phosphate-deprotected DNA sequences released from the CPG support is demonstrated to proceed near quantitatively. Shorter than full-length DNA sequences are first washed away from the capture support; the solid-phase purified DNA sequences are then released from this support upon reaction with tetra-n-butylammonium fluoride in dry dimethylsulfoxide (DMSO) and precipitated in tetrahydrofuran (THF). The purity of solid-phase-purified DNA sequences exceeds 98%. The simulated high-throughput and scalability features of the solid-phase purification process are demonstrated without sacrificing purity of the DNA sequences. PMID:28628204

Illumina GA IIx& HiSeq 2000 Production Sequenccing and QC Analysis Pipelines at the DOE Joint Genome Institute

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

Daum, Christopher; Zane, Matthew; Han, James

2011-01-31

The U.S. Department of Energy (DOE) Joint Genome Institute's (JGI) Production Sequencing group is committed to the generation of high-quality genomic DNA sequence to support the mission areas of renewable energy generation, global carbon management, and environmental characterization and clean-up. Within the JGI's Production Sequencing group, a robust Illumina Genome Analyzer and HiSeq pipeline has been established. Optimization of the sesequencer pipelines has been ongoing with the aim of continual process improvement of the laboratory workflow, reducing operational costs and project cycle times to increases ample throughput, and improving the overall quality of the sequence generated. A sequence QC analysismore » pipeline has been implemented to automatically generate read and assembly level quality metrics. The foremost of these optimization projects, along with sequencing and operational strategies, throughput numbers, and sequencing quality results will be presented.« less

Genotyping-by-sequencing (GBS) revealed molecular genetic diversity of Iranian wheat landraces and cultivars

USDA-ARS?s Scientific Manuscript database

Genetic diversity is an essential resource for breeders to improve new cultivars with desirable characteristics. Recently genotyping-by-sequencing (GBS), a next generation sequencing (NGS) based technology that can simplify complex genomes, has been used as a high-throughput and cost-effective molec...

High-Throughput resequencing of maize landraces at genomic regions associated with flowering time

USDA-ARS?s Scientific Manuscript database

Despite the reduction in the price of sequencing, it remains expensive to sequence and assemble whole, complex genomes of multiple samples for population studies, particularly for large genomes like those of many crop species. Enrichment of target genome regions coupled with next generation sequenci...

A generic assay for whole-genome amplification and deep sequencing of enterovirus A71

PubMed Central

Tan, Le Van; Tuyen, Nguyen Thi Kim; Thanh, Tran Tan; Ngan, Tran Thuy; Van, Hoang Minh Tu; Sabanathan, Saraswathy; Van, Tran Thi My; Thanh, Le Thi My; Nguyet, Lam Anh; Geoghegan, Jemma L.; Ong, Kien Chai; Perera, David; Hang, Vu Thi Ty; Ny, Nguyen Thi Han; Anh, Nguyen To; Ha, Do Quang; Qui, Phan Tu; Viet, Do Chau; Tuan, Ha Manh; Wong, Kum Thong; Holmes, Edward C.; Chau, Nguyen Van Vinh; Thwaites, Guy; van Doorn, H. Rogier

2015-01-01

Enterovirus A71 (EV-A71) has emerged as the most important cause of large outbreaks of severe and sometimes fatal hand, foot and mouth disease (HFMD) across the Asia-Pacific region. EV-A71 outbreaks have been associated with (sub)genogroup switches, sometimes accompanied by recombination events. Understanding EV-A71 population dynamics is therefore essential for understanding this emerging infection, and may provide pivotal information for vaccine development. Despite the public health burden of EV-A71, relatively few EV-A71 complete-genome sequences are available for analysis and from limited geographical localities. The availability of an efficient procedure for whole-genome sequencing would stimulate effort to generate more viral sequence data. Herein, we report for the first time the development of a next-generation sequencing based protocol for whole-genome sequencing of EV-A71 directly from clinical specimens. We were able to sequence viruses of subgenogroup C4 and B5, while RNA from culture materials of diverse EV-A71 subgenogroups belonging to both genogroup B and C was successfully amplified. The nature of intra-host genetic diversity was explored in 22 clinical samples, revealing 107 positions carrying minor variants (ranging from 0 to 15 variants per sample). Our analysis of EV-A71 strains sampled in 2013 showed that they all belonged to subgenogroup B5, representing the first report of this subgenogroup in Vietnam. In conclusion, we have successfully developed a high-throughput next-generation sequencing-based assay for whole-genome sequencing of EV-A71 from clinical samples. PMID:25704598

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

Microbial stratification and microbially catalyzed processes along a hypersaline chemocline

NASA Astrophysics Data System (ADS)

Hyde, A.; Joye, S. B.; Teske, A.

2017-12-01

Orca Basin is the largest deep hypersaline anoxic basin in the world, covering over 400 km2. Located at the bottom of the Gulf of Mexico, this body of water reaches depths of 200 meters and is 8 times denser (and more saline) than the overlying seawater. The sharp pycnocline prevents any significant vertical mixing and serves as a particle trap for sinking organic matter. These rapid changes in salinity, oxygen, organic matter, and other geochemical parameters present unique conditions for the microbial communities present. We collected samples in 10m intervals throughout the chemocline. After filtering the water, we used high-throughput bacterial and archaeal 16S rRNA gene sequencing to characterize the changing microbial community along the Orca Basin chemocline. The results reveal a dominance of microbial taxa whose biogeochemical function is entirely unknown. We then used metagenomic sequencing and reconstructed genomes for select samples, revealing the potential dominant metabolic processes in the Orca Basin chemocline. Understanding how these unique geochemical conditions shape microbial communities and metabolic capabilities will have implications for the ocean's biogeochemical cycles and the consequences of expanding oxygen minimum zones.

Deep sequencing analysis of viral short RNAs from an infected Pinot Noir grapevine.

PubMed

Pantaleo, Vitantonio; Saldarelli, Pasquale; Miozzi, Laura; Giampetruzzi, Annalisa; Gisel, Andreas; Moxon, Simon; Dalmay, Tamas; Bisztray, György; Burgyan, Jozsef

2010-12-05

Virus-derived short interfering RNAs (vsiRNAs) isolated from grapevine V. vinifera Pinot Noir clone ENTAV 115 were analyzed by high-throughput sequencing using the Illumina Solexa platform. We identified and characterized vsiRNAs derived from grapevine field plants naturally infected with different viruses belonging to the genera Foveavirus, Maculavirus, Marafivirus and Nepovirus. These vsiRNAs were mainly of 21 and 22 nucleotides (nt) in size and were discontinuously distributed throughout Grapevine rupestris stem-pitting associated virus (GRSPaV) and Grapevine fleck virus (GFkV) genomic RNAs. Among the studied viruses, GRSPaV and GFkV vsiRNAs had a 5' terminal nucleotide bias, which differed from that described for experimental viral infections in Arabidopsis thaliana. VsiRNAs were found to originate from both genomic and antigenomic GRSPaV RNA strands, whereas with the grapevine tymoviruses GFkV and Grapevine Red Globe associated virus (GRGV), the large majority derived from the antigenomic viral strand, a feature never observed in other plant-virus interactions. Copyright © 2010 Elsevier Inc. All rights reserved.

Comparison of illumina and 454 deep sequencing in participants failing raltegravir-based antiretroviral therapy.

PubMed

Li, Jonathan Z; Chapman, Brad; Charlebois, Patrick; Hofmann, Oliver; Weiner, Brian; Porter, Alyssa J; Samuel, Reshmi; Vardhanabhuti, Saran; Zheng, Lu; Eron, Joseph; Taiwo, Babafemi; Zody, Michael C; Henn, Matthew R; Kuritzkes, Daniel R; Hide, Winston; Wilson, Cara C; Berzins, Baiba I; Acosta, Edward P; Bastow, Barbara; Kim, Peter S; Read, Sarah W; Janik, Jennifer; Meres, Debra S; Lederman, Michael M; Mong-Kryspin, Lori; Shaw, Karl E; Zimmerman, Louis G; Leavitt, Randi; De La Rosa, Guy; Jennings, Amy

2014-01-01

The impact of raltegravir-resistant HIV-1 minority variants (MVs) on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs. A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser. Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001). Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454. In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls.

High-Throughput Gene Mapping in Caenorhabditis elegans

PubMed Central

Swan, Kathryn A.; Curtis, Damian E.; McKusick, Kathleen B.; Voinov, Alexander V.; Mapa, Felipa A.; Cancilla, Michael R.

2002-01-01

Positional cloning of mutations in model genetic systems is a powerful method for the identification of targets of medical and agricultural importance. To facilitate the high-throughput mapping of mutations in Caenorhabditis elegans, we have identified a further 9602 putative new single nucleotide polymorphisms (SNPs) between two C. elegans strains, Bristol N2 and the Hawaiian mapping strain CB4856, by sequencing inserts from a CB4856 genomic DNA library and using an informatics pipeline to compare sequences with the canonical N2 genomic sequence. When combined with data from other laboratories, our marker set of 17,189 SNPs provides even coverage of the complete worm genome. To date, we have confirmed >1099 evenly spaced SNPs (one every 91 ± 56 kb) across the six chromosomes and validated the utility of our SNP marker set and new fluorescence polarization-based genotyping methods for systematic and high-throughput identification of genes in C. elegans by cloning several proprietary genes. We illustrate our approach by recombination mapping and confirmation of the mutation in the cloned gene, dpy-18. [The sequence data described in this paper have been submitted to the NCBI dbSNP data library under accession nos. 4388625–4389689 and GenBank dbSTS under accession nos. 973810–974874. The following individuals and institutions kindly provided reagents, samples, or unpublished information as indicated in the paper: The C. elegans Sequencing Consortium and The Caenorhabditis Genetics Center.] PMID:12097347

LOCATE: a mouse protein subcellular localization database

PubMed Central

Fink, J. Lynn; Aturaliya, Rajith N.; Davis, Melissa J.; Zhang, Fasheng; Hanson, Kelly; Teasdale, Melvena S.; Kai, Chikatoshi; Kawai, Jun; Carninci, Piero; Hayashizaki, Yoshihide; Teasdale, Rohan D.

2006-01-01

We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set. Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing >1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for ∼40% of the mouse proteome. It is available at . PMID:16381849

Investigation of rare and low-frequency variants using high-throughput sequencing with pooled DNA samples

PubMed Central

Wang, Jingwen; Skoog, Tiina; Einarsdottir, Elisabet; Kaartokallio, Tea; Laivuori, Hannele; Grauers, Anna; Gerdhem, Paul; Hytönen, Marjo; Lohi, Hannes; Kere, Juha; Jiao, Hong

2016-01-01

High-throughput sequencing using pooled DNA samples can facilitate genome-wide studies on rare and low-frequency variants in a large population. Some major questions concerning the pooling sequencing strategy are whether rare and low-frequency variants can be detected reliably, and whether estimated minor allele frequencies (MAFs) can represent the actual values obtained from individually genotyped samples. In this study, we evaluated MAF estimates using three variant detection tools with two sets of pooled whole exome sequencing (WES) and one set of pooled whole genome sequencing (WGS) data. Both GATK and Freebayes displayed high sensitivity, specificity and accuracy when detecting rare or low-frequency variants. For the WGS study, 56% of the low-frequency variants in Illumina array have identical MAFs and 26% have one allele difference between sequencing and individual genotyping data. The MAF estimates from WGS correlated well (r = 0.94) with those from Illumina arrays. The MAFs from the pooled WES data also showed high concordance (r = 0.88) with those from the individual genotyping data. In conclusion, the MAFs estimated from pooled DNA sequencing data reflect the MAFs in individually genotyped samples well. The pooling strategy can thus be a rapid and cost-effective approach for the initial screening in large-scale association studies. PMID:27633116

Novel Method for High-Throughput Full-Length IGHV-D-J Sequencing of the Immune Repertoire from Bulk B-Cells with Single-Cell Resolution.

PubMed

Vergani, Stefano; Korsunsky, Ilya; Mazzarello, Andrea Nicola; Ferrer, Gerardo; Chiorazzi, Nicholas; Bagnara, Davide

2017-01-01

Efficient and accurate high-throughput DNA sequencing of the adaptive immune receptor repertoire (AIRR) is necessary to study immune diversity in healthy subjects and disease-related conditions. The high complexity and diversity of the AIRR coupled with the limited amount of starting material, which can compromise identification of the full biological diversity makes such sequencing particularly challenging. AIRR sequencing protocols often fail to fully capture the sampled AIRR diversity, especially for samples containing restricted numbers of B lymphocytes. Here, we describe a library preparation method for immunoglobulin sequencing that results in an exhaustive full-length repertoire where virtually every sampled B-cell is sequenced. This maximizes the likelihood of identifying and quantifying the entire IGHV-D-J repertoire of a sample, including the detection of rearrangements present in only one cell in the starting population. The methodology establishes the importance of circumventing genetic material dilution in the preamplification phases and incorporates the use of certain described concepts: (1) balancing the starting material amount and depth of sequencing, (2) avoiding IGHV gene-specific amplification, and (3) using Unique Molecular Identifier. Together, this methodology is highly efficient, in particular for detecting rare rearrangements in the sampled population and when only a limited amount of starting material is available.

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

PubMed

Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

High throughput deep degradome sequencing reveals microRNAs and their targets in response to drought stress in mulberry (Morus alba).

PubMed

Li, Ruixue; Chen, Dandan; Wang, Taichu; Wan, Yizhen; Li, Rongfang; Fang, Rongjun; Wang, Yuting; Hu, Fei; Zhou, Hong; Li, Long; Zhao, Weiguo

2017-01-01

MicroRNAs (miRNAs) play important regulatory roles by targeting mRNAs for cleavage or translational repression. Identification of miRNA targets is essential to better understanding the roles of miRNAs. miRNA targets have not been well characterized in mulberry (Morus alba). To anatomize miRNA guided gene regulation under drought stress, transcriptome-wide high throughput degradome sequencing was used in this study to directly detect drought stress responsive miRNA targets in mulberry. A drought library (DL) and a contrast library (CL) were constructed to capture the cleaved mRNAs for sequencing. In CL, 409 target genes of 30 conserved miRNA families and 990 target genes of 199 novel miRNAs were identified. In DL, 373 target genes of 30 conserved miRNA families and 950 target genes of 195 novel miRNAs were identified. Of the conserved miRNA families in DL, mno-miR156, mno-miR172, and mno-miR396 had the highest number of targets with 54, 52 and 41 transcripts, respectively, indicating that these three miRNA families and their target genes might play important functions in response to drought stress in mulberry. Additionally, we found that many of the target genes were transcription factors. By analyzing the miRNA-target molecular network, we found that the DL independent networks consisted of 838 miRNA-mRNA pairs (63.34%). The expression patterns of 11 target genes and 12 correspondent miRNAs were detected using qRT-PCR. Six miRNA targets were further verified by RNA ligase-mediated 5' rapid amplification of cDNA ends (RLM-5' RACE). Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these target transcripts were implicated in a broad range of biological processes and various metabolic pathways. This is the first study to comprehensively characterize target genes and their associated miRNAs in response to drought stress by degradome sequencing in mulberry. This study provides a framework for understanding the molecular mechanisms of drought resistance in mulberry.

High-Throughput, Data-Rich Cellular RNA Device Engineering

PubMed Central

Townshend, Brent; Kennedy, Andrew B.; Xiang, Joy S.; Smolke, Christina D.

2015-01-01

Methods for rapidly assessing sequence-structure-function landscapes and developing conditional gene-regulatory devices are critical to our ability to manipulate and interface with biology. We describe a framework for engineering RNA devices from preexisting aptamers that exhibit ligand-responsive ribozyme tertiary interactions. Our methodology utilizes cell sorting, high-throughput sequencing, and statistical data analyses to enable parallel measurements of the activities of hundreds of thousands of sequences from RNA device libraries in the absence and presence of ligands. Our tertiary interaction RNA devices exhibit improved performance in terms of gene silencing, activation ratio, and ligand sensitivity as compared to optimized RNA devices that rely on secondary structure changes. We apply our method to building biosensors for diverse ligands and determine consensus sequences that enable ligand-responsive tertiary interactions. These methods advance our ability to develop broadly applicable genetic tools and to elucidate understanding of the underlying sequence-structure-function relationships that empower rational design of complex biomolecules. PMID:26258292

Nanowire-nanopore transistor sensor for DNA detection during translocation

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Identification of miRNA from Bouteloua gracilis, a drought tolerant grass, by deep sequencing and their in silico analysis.

PubMed

Ordóñez-Baquera, Perla Lucía; González-Rodríguez, Everardo; Aguado-Santacruz, Gerardo Armando; Rascón-Cruz, Quintín; Conesa, Ana; Moreno-Brito, Verónica; Echavarria, Raquel; Dominguez-Viveros, Joel

2017-02-01

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate signal transduction, development, metabolism, and stress responses in plants through post-transcriptional degradation and/or translational repression of target mRNAs. Several studies have addressed the role of miRNAs in model plant species, but miRNA expression and function in economically important forage crops, such as Bouteloua gracilis (Poaceae), a high-quality and drought-resistant grass distributed in semiarid regions of the United States and northern Mexico remain unknown. We applied high-throughput sequencing technology and bioinformatics analysis and identified 31 conserved miRNA families and 53 novel putative miRNAs with different abundance of reads in chlorophyllic cell cultures derived from B. gracilis. Some conserved miRNA families were highly abundant and possessed predicted targets involved in metabolism, plant growth and development, and stress responses. We also predicted additional identified novel miRNAs with specific targets, including B. gracilis ESTs, which were detected under drought stress conditions. Here we report 31 conserved miRNA families and 53 putative novel miRNAs in B. gracilis. Our results suggested the presence of regulatory miRNAs involved in modulating physiological and stress responses in this grass species. Copyright © 2016 Elsevier Ltd. All rights reserved.

High-throughput assays for DNA gyrase and other topoisomerases

PubMed Central

Maxwell, Anthony; Burton, Nicolas P.; O'Hagan, Natasha

2006-01-01

We have developed high-throughput microtitre plate-based assays for DNA gyrase and other DNA topoisomerases. These assays exploit the fact that negatively supercoiled plasmids form intermolecular triplexes more efficiently than when they are relaxed. Two assays are presented, one using capture of a plasmid containing a single triplex-forming sequence by an oligonucleotide tethered to the surface of a microtitre plate and subsequent detection by staining with a DNA-specific fluorescent dye. The other uses capture of a plasmid containing two triplex-forming sequences by an oligonucleotide tethered to the surface of a microtitre plate and subsequent detection by a second oligonucleotide that is radiolabelled. The assays are shown to be appropriate for assaying DNA supercoiling by Escherichia coli DNA gyrase and DNA relaxation by eukaryotic topoisomerases I and II, and E.coli topoisomerase IV. The assays are readily adaptable to other enzymes that change DNA supercoiling (e.g. restriction enzymes) and are suitable for use in a high-throughput format. PMID:16936317

High-throughput assays for DNA gyrase and other topoisomerases.

PubMed

Maxwell, Anthony; Burton, Nicolas P; O'Hagan, Natasha

2006-01-01

We have developed high-throughput microtitre plate-based assays for DNA gyrase and other DNA topoisomerases. These assays exploit the fact that negatively supercoiled plasmids form intermolecular triplexes more efficiently than when they are relaxed. Two assays are presented, one using capture of a plasmid containing a single triplex-forming sequence by an oligonucleotide tethered to the surface of a microtitre plate and subsequent detection by staining with a DNA-specific fluorescent dye. The other uses capture of a plasmid containing two triplex-forming sequences by an oligonucleotide tethered to the surface of a microtitre plate and subsequent detection by a second oligonucleotide that is radiolabelled. The assays are shown to be appropriate for assaying DNA supercoiling by Escherichia coli DNA gyrase and DNA relaxation by eukaryotic topoisomerases I and II, and E.coli topoisomerase IV. The assays are readily adaptable to other enzymes that change DNA supercoiling (e.g. restriction enzymes) and are suitable for use in a high-throughput format.

High-throughput analysis of T-DNA location and structure using sequence capture

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

Inagaki, Soichi; Henry, Isabelle M.; Lieberman, Meric C.

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA—genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously,more » using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. As a result, our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.« less

High-throughput analysis of T-DNA location and structure using sequence capture

DOE PAGES

Inagaki, Soichi; Henry, Isabelle M.; Lieberman, Meric C.; ...

2015-10-07

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA—genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously,more » using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. As a result, our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.« less

Human genetics and genomics a decade after the release of the draft sequence of the human genome.

PubMed

Naidoo, Nasheen; Pawitan, Yudi; Soong, Richie; Cooper, David N; Ku, Chee-Seng

2011-10-01

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade.

Human genetics and genomics a decade after the release of the draft sequence of the human genome

PubMed Central

2011-01-01

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade. PMID:22155605

Identification and characterization of lipid metabolism-related microRNAs in the liver of genetically improved farmed tilapia (GIFT, Oreochromis niloticus) by deep sequencing.

PubMed

Tao, Yi-Fan; Qiang, Jun; Yin, Guo-Jun; Xu, Pao; Shi, Qiong; Bao, Jing-Wen

2017-10-01

MicroRNAs (miRNAs) play vital roles in modulating diverse metabolic processes in the liver, including lipid metabolism. Genetically improved farmed tilapia (GIFT, Oreochromis niloticus), an important aquaculture species in China, is susceptible to hepatic steatosis when reared in intensive culture systems. To investigate the miRNAs involved in GIFT lipid metabolism, two hepatic small RNA libraries from high-fat diet-fed and normal-fat diet-fed GIFT were constructed and sequenced using high-throughput sequencing technology. A total of 204 known and 56 novel miRNAs were identified by aligning the sequencing data with known Danio rerio miRNAs listed in miRBase 21.0. Six known miRNAs (miR-30a-5p, miR-34a, miR-145-5p, miR-29a, miR-205-5p, and miR-23a-3p) that were differentially expressed between the high-fat diet and normal-fat diet groups were validated by quantitative real-time PCR. Bioinformatics tools were used to predict the potential target genes of these differentially expressed miRNAs, and Gene Ontology enrichment analysis indicated that these miRNAs may play important roles in diet-induced hepatic steatosis in GIFT. Our results provide a foundation for further studies of the role of miRNAs in tilapia lipid homeostasis regulation, and may help to identify novel targets for therapeutic interventions to reduce the occurrence of fatty liver disease in farmed tilapia. Copyright © 2017. Published by Elsevier Ltd.

Delving into the Deep Biosphere

NASA Astrophysics Data System (ADS)

Grim, S. L.; Sogin, M. L.; Boetius, A.; Briggs, B. R.; Brazelton, W. J.; D'Hondt, S. L.; Edwards, K. J.; Fisk, M. R.; Gaidos, E.; Gralnick, J.; Hinrichs, K.; Lazar, C.; Lavalleur, H.; Lever, M. A.; Marteinsson, V.; Moser, D. P.; Orcutt, B.; Pedersen, K.; Popa, R.; Ramette, A.; Schrenk, M. O.; Sylvan, J. B.; Smith, A. R.; Teske, A.; Walsh, E. A.; Colwell, F. S.

2013-12-01

The Census of Deep Life organized an international survey of microbial community diversity in terrestrial and marine deep subsurface environments. Habitats included subsurface continental fractured rock aquifers, volcanic and metamorphic subseafloor sedimentary units from the open ocean, subsurface oxic and anoxic sediments and underlying basaltic oceanic crust, and their overlying water columns. Our survey employed high-throughput pyrosequencing of the hypervariable V4-V6 16S rRNA gene of bacteria and archaea. We detected 1292 bacterial genera representing 40 phyla, and 99 archaeal genera from 30 phyla. Of these, a core group of thirteen bacterial genera occurred in every environment. A genus of the South African Goldmine Group (Euryarchaeota) was always present whenever archaea were detected. Members of the rare biosphere in one system often represented highly abundant taxa in other environments. Dispersal could account for this observation but mechanisms of transport remain elusive. Ralstonia (Betaproteobacteria) represented highly abundant taxa in marine communities and terrestrial rock, but generally low abundance organisms in groundwater. Some of these taxa could represent sample contamination, and their extensive distribution in several systems requires further assessment. An unknown Sphingobacteriales (Bacteroidetes) genus, Stenotrophomonas (Gammaproteobacteria), Acidovorax and Aquabacterium (both Betaproteobacteria), a Chlorobiales genus, and a TM7 genus were in the core group as well but more prevalent in terrestrial environments. Similarly, Bacillus (Firmicutes), a new cyanobacterial genus, Bradyrhizobium and Sphingomonas (both Alphaproteobacteria), a novel Acidobacteriaceae genus, and Variovorax (Betaproteobacteria) frequently occurred in marine systems but represented low abundance taxa in other environments. Communities tended to cluster by biome and material, and many genera were unique to systems. For example, certain Rhizobiales (Alphaproteobacteria) only occurred in groundwater, and select Firmicutes and actinobacterial taxa were specific to rock environments. We continue to investigate the ecological and physiological context of these organisms. By combining deep sequencing of microbial communities and geochemical and physical evaluations of their environments, we bring to light the diversity and scope of the deep biosphere and insight into the factors that determine the nature of these communities.

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

PCR Primers to Study the Diversity of Expressed Fungal Genes Encoding Lignocellulolytic Enzymes in Soils Using High-Throughput Sequencing

PubMed Central

Barbi, Florian; Bragalini, Claudia; Vallon, Laurent; Prudent, Elsa; Dubost, Audrey; Fraissinet-Tachet, Laurence; Marmeisse, Roland; Luis, Patricia

2014-01-01

Plant biomass degradation in soil is one of the key steps of carbon cycling in terrestrial ecosystems. Fungal saprotrophic communities play an essential role in this process by producing hydrolytic enzymes active on the main components of plant organic matter. Open questions in this field regard the diversity of the species involved, the major biochemical pathways implicated and how these are affected by external factors such as litter quality or climate changes. This can be tackled by environmental genomic approaches involving the systematic sequencing of key enzyme-coding gene families using soil-extracted RNA as material. Such an approach necessitates the design and evaluation of gene family-specific PCR primers producing sequence fragments compatible with high-throughput sequencing approaches. In the present study, we developed and evaluated PCR primers for the specific amplification of fungal CAZy Glycoside Hydrolase gene families GH5 (subfamily 5) and GH11 encoding endo-β-1,4-glucanases and endo-β-1,4-xylanases respectively as well as Basidiomycota class II peroxidases, corresponding to the CAZy Auxiliary Activity family 2 (AA2), active on lignin. These primers were experimentally validated using DNA extracted from a wide range of Ascomycota and Basidiomycota species including 27 with sequenced genomes. Along with the published primers for Glycoside Hydrolase GH7 encoding enzymes active on cellulose, the newly design primers were shown to be compatible with the Illumina MiSeq sequencing technology. Sequences obtained from RNA extracted from beech or spruce forest soils showed a high diversity and were uniformly distributed in gene trees featuring the global diversity of these gene families. This high-throughput sequencing approach using several degenerate primers constitutes a robust method, which allows the simultaneous characterization of the diversity of different fungal transcripts involved in plant organic matter degradation and may lead to the discovery of complex patterns in gene expression of soil fungal communities. PMID:25545363

Discovery of DNA viruses in wild-caught mosquitoes using small RNA high throughput sequencing.

PubMed

Ma, Maijuan; Huang, Yong; Gong, Zhengda; Zhuang, Lu; Li, Cun; Yang, Hong; Tong, Yigang; Liu, Wei; Cao, Wuchun

2011-01-01

Mosquito-borne infectious diseases pose a severe threat to public health in many areas of the world. Current methods for pathogen detection and surveillance are usually dependent on prior knowledge of the etiologic agents involved. Hence, efficient approaches are required for screening wild mosquito populations to detect known and unknown pathogens. In this study, we explored the use of Next Generation Sequencing to identify viral agents in wild-caught mosquitoes. We extracted total RNA from different mosquito species from South China. Small 18-30 bp length RNA molecules were purified, reverse-transcribed into cDNA and sequenced using Illumina GAIIx instrumentation. Bioinformatic analyses to identify putative viral agents were conducted and the results confirmed by PCR. We identified a non-enveloped single-stranded DNA densovirus in the wild-caught Culex pipiens molestus mosquitoes. The majority of the viral transcripts (.>80% of the region) were covered by the small viral RNAs, with a few peaks of very high coverage obtained. The +/- strand sequence ratio of the small RNAs was approximately 7∶1, indicating that the molecules were mainly derived from the viral RNA transcripts. The small viral RNAs overlapped, enabling contig assembly of the viral genome sequence. We identified some small RNAs in the reverse repeat regions of the viral 5'- and 3' -untranslated regions where no transcripts were expected. Our results demonstrate for the first time that high throughput sequencing of small RNA is feasible for identifying viral agents in wild-caught mosquitoes. Our results show that it is possible to detect DNA viruses by sequencing the small RNAs obtained from insects, although the underlying mechanism of small viral RNA biogenesis is unclear. Our data and those of other researchers show that high throughput small RNA sequencing can be used for pathogen surveillance in wild mosquito vectors.

Microbial community analysis of the hypersaline water of the Dead Sea using high-throughput amplicon sequencing.

PubMed

Jacob, Jacob H; Hussein, Emad I; Shakhatreh, Muhamad Ali K; Cornelison, Christopher T

2017-10-01

Amplicon sequencing using next-generation technology (bTEFAP ® ) has been utilized in describing the diversity of Dead Sea microbiota. The investigated area is a well-known salt lake in the western part of Jordan found in the lowest geographical location in the world (more than 420 m below sea level) and characterized by extreme salinity (approximately, 34%) in addition to other extreme conditions (low pH, unique ionic composition different from sea water). DNA was extracted from Dead Sea water. A total of 314,310 small subunit RNA (SSU rRNA) sequences were parsed, and 288,452 sequences were then clustered. For alpha diversity analysis, sample was rarefied to 3,000 sequences. The Shannon-Wiener index curve plot reached a plateau at approximately 3,000 sequences indicating that sequencing depth was sufficient to capture the full scope of microbial diversity. Archaea was found to be dominating the sequences (52%), whereas Bacteria constitute 45% of the sequences. Altogether, prokaryotic sequences (which constitute 97% of all sequences) were found to predominate. The findings expand on previous studies by using high-throughput amplicon sequencing to describe the microbial community in an environment which in recent years has been shown to hide some interesting diversity. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Quick, sensitive and specific detection and evaluation of quantification of minor variants by high-throughput sequencing.

PubMed

Leung, Ross Ka-Kit; Dong, Zhi Qiang; Sa, Fei; Chong, Cheong Meng; Lei, Si Wan; Tsui, Stephen Kwok-Wing; Lee, Simon Ming-Yuen

2014-02-01

Minor variants have significant implications in quasispecies evolution, early cancer detection and non-invasive fetal genotyping but their accurate detection by next-generation sequencing (NGS) is hampered by sequencing errors. We generated sequencing data from mixtures at predetermined ratios in order to provide insight into sequencing errors and variations that can arise for which simulation cannot be performed. The information also enables better parameterization in depth of coverage, read quality and heterogeneity, library preparation techniques, technical repeatability for mathematical modeling, theory development and simulation experimental design. We devised minor variant authentication rules that achieved 100% accuracy in both testing and validation experiments. The rules are free from tedious inspection of alignment accuracy, sequencing read quality or errors introduced by homopolymers. The authentication processes only require minor variants to: (1) have minimum depth of coverage larger than 30; (2) be reported by (a) four or more variant callers, or (b) DiBayes or LoFreq, plus SNVer (or BWA when no results are returned by SNVer), and with the interassay coefficient of variation (CV) no larger than 0.1. Quantification accuracy undermined by sequencing errors could neither be overcome by ultra-deep sequencing, nor recruiting more variant callers to reach a consensus, such that consistent underestimation and overestimation (i.e. low CV) were observed. To accommodate stochastic error and adjust the observed ratio within a specified accuracy, we presented a proof of concept for the use of a double calibration curve for quantification, which provides an important reference towards potential industrial-scale fabrication of calibrants for NGS.

Evolutionary dynamics of retrotransposons assessed by high-throughput sequencing in wild relatives of wheat.

PubMed

Senerchia, Natacha; Wicker, Thomas; Felber, François; Parisod, Christian

2013-01-01

Transposable elements (TEs) represent a major fraction of plant genomes and drive their evolution. An improved understanding of genome evolution requires the dynamics of a large number of TE families to be considered. We put forward an approach bypassing the required step of a complete reference genome to assess the evolutionary trajectories of high copy number TE families from genome snapshot with high-throughput sequencing. Low coverage sequencing of the complex genomes of Aegilops cylindrica and Ae. geniculata using 454 identified more than 70% of the sequences as known TEs, mainly long terminal repeat (LTR) retrotransposons. Comparing the abundance of reads as well as patterns of sequence diversity and divergence within and among genomes assessed the dynamics of 44 major LTR retrotransposon families of the 165 identified. In particular, molecular population genetics on individual TE copies distinguished recently active from quiescent families and highlighted different evolutionary trajectories of retrotransposons among related species. This work presents a suite of tools suitable for current sequencing data, allowing to address the genome-wide evolutionary dynamics of TEs at the family level and advancing our understanding of the evolution of nonmodel genomes.

Characterizing ncRNAs in Human Pathogenic Protists Using High-Throughput Sequencing Technology

PubMed Central

Collins, Lesley Joan

2011-01-01

ncRNAs are key genes in many human diseases including cancer and viral infection, as well as providing critical functions in pathogenic organisms such as fungi, bacteria, viruses, and protists. Until now the identification and characterization of ncRNAs associated with disease has been slow or inaccurate requiring many years of testing to understand complicated RNA and protein gene relationships. High-throughput sequencing now offers the opportunity to characterize miRNAs, siRNAs, small nucleolar RNAs (snoRNAs), and long ncRNAs on a genomic scale, making it faster and easier to clarify how these ncRNAs contribute to the disease state. However, this technology is still relatively new, and ncRNA discovery is not an application of high priority for streamlined bioinformatics. Here we summarize background concepts and practical approaches for ncRNA analysis using high-throughput sequencing, and how it relates to understanding human disease. As a case study, we focus on the parasitic protists Giardia lamblia and Trichomonas vaginalis, where large evolutionary distance has meant difficulties in comparing ncRNAs with those from model eukaryotes. A combination of biological, computational, and sequencing approaches has enabled easier classification of ncRNA classes such as snoRNAs, but has also aided the identification of novel classes. It is hoped that a higher level of understanding of ncRNA expression and interaction may aid in the development of less harsh treatment for protist-based diseases. PMID:22303390

Phased genotyping-by-sequencing enhances analysis of genetic diversity and reveals divergent copy number variants in maize

USDA-ARS?s Scientific Manuscript database

High-throughput sequencing of reduced representation genomic libraries has ushered in an era of genotyping-by-sequencing (GBS), where genome-wide genotype data can be obtained for nearly any species. However, there remains a need for imputation-free GBS methods for genotyping large samples taken fr...

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

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.

OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid.

PubMed

Poehlman, William L; Rynge, Mats; Branton, Chris; Balamurugan, D; Feltus, Frank A

2016-01-01

High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments.

OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid

PubMed Central

Poehlman, William L.; Rynge, Mats; Branton, Chris; Balamurugan, D.; Feltus, Frank A.

2016-01-01

High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments. PMID:27499617

A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.

PubMed

Turetschek, Reinhard; Lyon, David; Desalegn, Getinet; Kaul, Hans-Peter; Wienkoop, Stefanie

2016-01-01

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

Identification of antigen-specific human monoclonal antibodies using high-throughput sequencing of the antibody repertoire.

PubMed

Liu, Ju; Li, Ruihua; Liu, Kun; Li, Liangliang; Zai, Xiaodong; Chi, Xiangyang; Fu, Ling; Xu, Junjie; Chen, Wei

2016-04-22

High-throughput sequencing of the antibody repertoire provides a large number of antibody variable region sequences that can be used to generate human monoclonal antibodies. However, current screening methods for identifying antigen-specific antibodies are inefficient. In the present study, we developed an antibody clone screening strategy based on clone dynamics and relative frequency, and used it to identify antigen-specific human monoclonal antibodies. Enzyme-linked immunosorbent assay showed that at least 52% of putative positive immunoglobulin heavy chains composed antigen-specific antibodies. Combining information on dynamics and relative frequency improved identification of positive clones and elimination of negative clones. and increase the credibility of putative positive clones. Therefore the screening strategy could simplify the subsequent experimental screening and may facilitate the generation of antigen-specific antibodies. Copyright © 2016 Elsevier Inc. All rights reserved.

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

PubMed Central

Budavari, Tamas; Langmead, Ben; Wheelan, Sarah J.; Salzberg, Steven L.; Szalay, Alexander S.

2015-01-01

When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU) hardware.We followed this approach in implementing a read aligner called Arioc that uses GPU-based parallel sort and reduction techniques to identify high-priority locations where potential alignments may be found. We then carried out a read-by-read comparison of Arioc’s reported alignments with the alignments found by several leading read aligners. With simulated reads, Arioc has comparable or better accuracy than the other read aligners we tested. With human sequencing reads, Arioc demonstrates significantly greater throughput than the other aligners we evaluated across a wide range of sensitivity settings. The Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license. PMID:25780763

Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding

PubMed Central

Lu, Rong; Neff, Norma F.; Quake, Stephen R.; Weissman, Irving L.

2011-01-01

Disentangling cellular heterogeneity is a challenge in many fields, particularly in the stem cell and cancer biology fields. Here, we demonstrate how to combine viral genetic barcoding with high-throughput sequencing to track single cells in a heterogeneous population. We use this technique to track the in vivo differentiation of unitary hematopoietic stem cells (HSCs). The results are consistent with single cell transplantation studies, but require two orders of magnitude fewer mice. In addition to its high throughput, the high sensitivity of the technique allows for a direct examination of the clonality of sparse cell populations such as HSCs. We show how these capabilities offer a clonal perspective of the HSC differentiation process. In particular, our data suggests that HSCs do not equally contribute to blood cells after irradiation-mediated transplantation, and that two distinct HSC differentiation patterns co-exist in the same recipient mouse post irradiation. This technique can be applied to any viral accessible cell type for both in vitro and in vivo processes. PMID:21964413

Process in manufacturing high efficiency AlGaAs/GaAs solar cells by MO-CVD

NASA Technical Reports Server (NTRS)

Yeh, Y. C. M.; Chang, K. I.; Tandon, J.

1984-01-01

Manufacturing technology for mass producing high efficiency GaAs solar cells is discussed. A progress using a high throughput MO-CVD reactor to produce high efficiency GaAs solar cells is discussed. Thickness and doping concentration uniformity of metal oxide chemical vapor deposition (MO-CVD) GaAs and AlGaAs layer growth are discussed. In addition, new tooling designs are given which increase the throughput of solar cell processing. To date, 2cm x 2cm AlGaAs/GaAs solar cells with efficiency up to 16.5% were produced. In order to meet throughput goals for mass producing GaAs solar cells, a large MO-CVD system (Cambridge Instrument Model MR-200) with a susceptor which was initially capable of processing 20 wafers (up to 75 mm diameter) during a single growth run was installed. In the MR-200, the sequencing of the gases and the heating power are controlled by a microprocessor-based programmable control console. Hence, operator errors can be reduced, leading to a more reproducible production sequence.

Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

PubMed Central

Zhang, Xi

2015-01-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834

Developing High-Throughput HIV Incidence Assay with Pyrosequencing Platform

PubMed Central

Park, Sung Yong; Goeken, Nolan; Lee, Hyo Jin; Bolan, Robert; Dubé, Michael P.

2014-01-01

ABSTRACT Human immunodeficiency virus (HIV) incidence is an important measure for monitoring the epidemic and evaluating the efficacy of intervention and prevention trials. This study developed a high-throughput, single-measure incidence assay by implementing a pyrosequencing platform. We devised a signal-masking bioinformatics pipeline, which yielded a process error rate of 5.8 × 10−4 per base. The pipeline was then applied to analyze 18,434 envelope gene segments (HXB2 7212 to 7601) obtained from 12 incident and 24 chronic patients who had documented HIV-negative and/or -positive tests. The pyrosequencing data were cross-checked by using the single-genome-amplification (SGA) method to independently obtain 302 sequences from 13 patients. Using two genomic biomarkers that probe for the presence of similar sequences, the pyrosequencing platform correctly classified all 12 incident subjects (100% sensitivity) and 23 of 24 chronic subjects (96% specificity). One misclassified subject's chronic infection was correctly classified by conducting the same analysis with SGA data. The biomarkers were statistically associated across the two platforms, suggesting the assay's reproducibility and robustness. Sampling simulations showed that the biomarkers were tolerant of sequencing errors and template resampling, two factors most likely to affect the accuracy of pyrosequencing results. We observed comparable biomarker scores between AIDS and non-AIDS chronic patients (multivariate analysis of variance [MANOVA], P = 0.12), indicating that the stage of HIV disease itself does not affect the classification scheme. The high-throughput genomic HIV incidence marks a significant step toward determining incidence from a single measure in cross-sectional surveys. IMPORTANCE Annual HIV incidence, the number of newly infected individuals within a year, is the key measure of monitoring the epidemic's rise and decline. Developing reliable assays differentiating recent from chronic infections has been a long-standing quest in the HIV community. Over the past 15 years, these assays have traditionally measured various HIV-specific antibodies, but recent technological advancements have expanded the diversity of proposed accurate, user-friendly, and financially viable tools. Here we designed a high-throughput genomic HIV incidence assay based on the signature imprinted in the HIV gene sequence population. By combining next-generation sequencing techniques with bioinformatics analysis, we demonstrated that genomic fingerprints are capable of distinguishing recently infected patients from chronically infected patients with high precision. Our high-throughput platform is expected to allow us to process many patients' samples from a single experiment, permitting the assay to be cost-effective for routine surveillance. PMID:24371062

High-throughput identification of miRNAs of Taenia ovis, a cestode threatening sheep industry.

PubMed

Zheng, Yadong

2017-07-01

Taenia ovis is a tapeworm that is mainly transmitted between dogs and sheep or goats and has an adverse effect on sheep industry. miRNAs are short regulatory non-coding RNAs, involved in parasite development and growth as well as parasite infection. The miRNA profile of T. ovis remains to be established. Herein, 33 known miRNAs belonging to 23 different families were identified in T. ovis metacestodes using deep sequencing approach. Of them, expression of some miRNAs such as tov-miR-10 and -let-7 was absolutely predominant. Moreover, comparative analysis revealed the presence of a miR-71/2b/2c cluster in T. ovis, which was also completely conserved in other 6 cestodes. The study provides rich data for further understandings of T. ovis biology. Copyright © 2017 Elsevier B.V. All rights reserved.

CrossCheck: an open-source web tool for high-throughput screen data analysis.

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

PubMed Central

2010-01-01

Background High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to avoid database contamination with artefactual sequences. The arrival of pyrosequencing enhances this problem and necessitates customisable pre-processing algorithms. Results SeqTrim has been implemented both as a Web and as a standalone command line application. Already-published and newly-designed algorithms have been included to identify sequence inserts, to remove low quality, vector, adaptor, low complexity and contaminant sequences, and to detect chimeric reads. The availability of several input and output formats allows its inclusion in sequence processing workflows. Due to its specific algorithms, SeqTrim outperforms other pre-processors implemented as Web services or standalone applications. It performs equally well with sequences from EST libraries, SSH libraries, genomic DNA libraries and pyrosequencing reads and does not lead to over-trimming. Conclusions SeqTrim is an efficient pipeline designed for pre-processing of any type of sequence read, including next-generation sequencing. It is easily configurable and provides a friendly interface that allows users to know what happened with sequences at every pre-processing stage, and to verify pre-processing of an individual sequence if desired. The recommended pipeline reveals more information about each sequence than previously described pre-processors and can discard more sequencing or experimental artefacts. PMID:20089148

RAD sequencing yields a high success rate for westslope cutthroat and rainbow trout species-diagnostic SNP assays

USGS Publications Warehouse

Stephen J. Amish,; Paul A. Hohenlohe,; Sally Painter,; Robb F. Leary,; Muhlfeld, Clint C.; Fred W. Allendorf,; Luikart, Gordon

2012-01-01

Hybridization with introduced rainbow trout threatens most native westslope cutthroat trout populations. Understanding the genetic effects of hybridization and introgression requires a large set of high-throughput, diagnostic genetic markers to inform conservation and management. Recently, we identified several thousand candidate single-nucleotide polymorphism (SNP) markers based on RAD sequencing of 11 westslope cutthroat trout and 13 rainbow trout individuals. Here, we used flanking sequence for 56 of these candidate SNP markers to design high-throughput genotyping assays. We validated the assays on a total of 92 individuals from 22 populations and seven hatchery strains. Forty-six assays (82%) amplified consistently and allowed easy identification of westslope cutthroat and rainbow trout alleles as well as heterozygote controls. The 46 SNPs will provide high power for early detection of population admixture and improved identification of hybrid and nonhybridized individuals. This technique shows promise as a very low-cost, reliable and relatively rapid method for developing and testing SNP markers for nonmodel organisms with limited genomic resources.

Identification and Functional Analysis of Flowering Related microRNAs in Common Wild Rice (Oryza rufipogon Griff.)

PubMed Central

Dong, Yibo; Yuan, Qianhua; Wang, Feng; Li, Weimin; Jiang, Ying; Jia, Shirong; Pei, XinWu

2013-01-01

Background MicroRNAs (miRNAs) is a class of non-coding RNAs involved in post- transcriptional control of gene expression, via degradation and/or translational inhibition. Six-hundred sixty-one rice miRNAs are known that are important in plant development. However, flowering-related miRNAs have not been characterized in Oryza rufipogon Griff. It was approved by supervision department of Guangdong wild rice protection. We analyzed flowering-related miRNAs in O. rufipogon using high-throughput sequencing (deep sequencing) to understand the changes that occurred during rice domestication, and to elucidate their functions in flowering. Results Three O. rufipogon sRNA libraries, two vegetative stage (CWR-V1 and CWR-V2) and one flowering stage (CWR-F2) were sequenced using Illumina deep sequencing. A total of 20,156,098, 21,531,511 and 20,995,942 high quality sRNA reads were obtained from CWR-V1, CWR-V2 and CWR-F2, respectively, of which 3,448,185, 4,265,048 and 2,833,527 reads matched known miRNAs. We identified 512 known rice miRNAs in 214 miRNA families and predicted 290 new miRNAs. Targeted functional annotation, GO and KEGG pathway analyses predicted that 187 miRNAs regulate expression of flowering-related genes. Differential expression analysis of flowering-related miRNAs showed that: expression of 95 miRNAs varied significantly between the libraries, 66 are flowering-related miRNAs, such as oru-miR97, oru-miR117, oru-miR135, oru-miR137, et al. 17 are early-flowering -related miRNAs, including osa-miR160f, osa-miR164d, osa-miR167d, osa-miR169a, osa-miR172b, oru-miR4, et al., induced during the floral transition. Real-time PCR revealed the same expression patterns as deep sequencing. miRNAs targets were confirmed for cleavage by 5′-RACE in vivo, and were negatively regulated by miRNAs. Conclusions This is the first investigation of flowering miRNAs in wild rice. The result indicates that variation in miRNAs occurred during rice domestication and lays a foundation for further study of phase change and flowering in O. rufipogon. Complicated regulatory networks mediated by multiple miRNAs regulate the expression of flowering genes that control the induction of flowering. PMID:24386120

Calculating the quality of public high-throughput sequencing data to obtain a suitable subset for reanalysis from the Sequence Read Archive

PubMed Central

Nakazato, Takeru; Bono, Hidemasa

2017-01-01

Abstract It is important for public data repositories to promote the reuse of archived data. In the growing field of omics science, however, the increasing number of submissions of high-throughput sequencing (HTSeq) data to public repositories prevents users from choosing a suitable data set from among the large number of search results. Repository users need to be able to set a threshold to reduce the number of results to obtain a suitable subset of high-quality data for reanalysis. We calculated the quality of sequencing data archived in a public data repository, the Sequence Read Archive (SRA), by using the quality control software FastQC. We obtained quality values for 1 171 313 experiments, which can be used to evaluate the suitability of data for reuse. We also visualized the data distribution in SRA by integrating the quality information and metadata of experiments and samples. We provide quality information of all of the archived sequencing data, which enable users to obtain sufficient quality sequencing data for reanalyses. The calculated quality data are available to the public in various formats. Our data also provide an example of enhancing the reuse of public data by adding metadata to published research data by a third party. PMID:28449062

Using high throughput sequencing to explore the biodiversity in oral bacterial communities.

PubMed

Diaz, P I; Dupuy, A K; Abusleme, L; Reese, B; Obergfell, C; Choquette, L; Dongari-Bagtzoglou, A; Peterson, D E; Terzi, E; Strausbaugh, L D

2012-06-01

High throughput sequencing of 16S ribosomal RNA gene amplicons is a cost-effective method for characterization of oral bacterial communities. However, before undertaking large-scale studies, it is necessary to understand the technique-associated limitations and intrinsic variability of the oral ecosystem. In this work we evaluated bias in species representation using an in vitro-assembled mock community of oral bacteria. We then characterized the bacterial communities in saliva and buccal mucosa of five healthy subjects to investigate the power of high throughput sequencing in revealing their diversity and biogeography patterns. Mock community analysis showed primer and DNA isolation biases and an overestimation of diversity that was reduced after eliminating singleton operational taxonomic units (OTUs). Sequencing of salivary and mucosal communities found a total of 455 OTUs (0.3% dissimilarity) with only 78 of these present in all subjects. We demonstrate that this variability was partly the result of incomplete richness coverage even at great sequencing depths, and so comparing communities by their structure was more effective than comparisons based solely on membership. With respect to oral biogeography, we found inter-subject variability in community structure was lower than site differences between salivary and mucosal communities within subjects. These differences were evident at very low sequencing depths and were mostly caused by the abundance of Streptococcus mitis and Gemella haemolysans in mucosa. In summary, we present an experimental and data analysis framework that will facilitate design and interpretation of pyrosequencing-based studies. Despite challenges associated with this technique, we demonstrate its power for evaluation of oral diversity and biogeography patterns. © 2012 John Wiley & Sons A/S.

Ancient genomics

PubMed Central

Der Sarkissian, Clio; Allentoft, Morten E.; Ávila-Arcos, María C.; Barnett, Ross; Campos, Paula F.; Cappellini, Enrico; Ermini, Luca; Fernández, Ruth; da Fonseca, Rute; Ginolhac, Aurélien; Hansen, Anders J.; Jónsson, Hákon; Korneliussen, Thorfinn; Margaryan, Ashot; Martin, Michael D.; Moreno-Mayar, J. Víctor; Raghavan, Maanasa; Rasmussen, Morten; Velasco, Marcela Sandoval; Schroeder, Hannes; Schubert, Mikkel; Seguin-Orlando, Andaine; Wales, Nathan; Gilbert, M. Thomas P.; Willerslev, Eske; Orlando, Ludovic

2015-01-01

The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence throughput of next generation sequencing platforms and the ability to target short and degraded DNA molecules. Many ancient specimens previously unsuitable for DNA analyses because of extensive degradation can now successfully be used as source materials. Additionally, the analytical power obtained by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when testing specific hypotheses related to the past. PMID:25487338

Applications of Deep Learning in Biomedicine.

PubMed

Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

2016-05-02

Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

ToTem: a tool for variant calling pipeline optimization.

PubMed

Tom, Nikola; Tom, Ondrej; Malcikova, Jitka; Pavlova, Sarka; Kubesova, Blanka; Rausch, Tobias; Kolarik, Miroslav; Benes, Vladimir; Bystry, Vojtech; Pospisilova, Sarka

2018-06-26

High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at  https://totem.software .

Diversity and distribution of unicellular opisthokonts along the European coast analyzed using high-throughput sequencing

PubMed Central

del Campo, Javier; Mallo, Diego; Massana, Ramon; de Vargas, Colomban; Richards, Thomas A.; Ruiz-Trillo, Iñaki

2015-01-01

Summary The opisthokonts are one of the major super-groups of eukaryotes. It comprises two major clades: 1) the Metazoa and their unicellular relatives and 2) the Fungi and their unicellular relatives. There is, however, little knowledge of the role of opisthokont microbes in many natural environments, especially among non-metazoan and non-fungal opisthokonts. Here we begin to address this gap by analyzing high throughput 18S rDNA and 18S rRNA sequencing data from different European coastal sites, sampled at different size fractions and depths. In particular, we analyze the diversity and abundance of choanoflagellates, filastereans, ichthyosporeans, nucleariids, corallochytreans and their related lineages. Our results show the great diversity of choanoflagellates in coastal waters as well as a relevant role of the ichthyosporeans and the uncultured marine opisthokonts (MAOP). Furthermore, we describe a new lineage of marine fonticulids (MAFO) that appears to be abundant in sediments. Therefore, our work points to a greater potential ecological role for unicellular opisthokonts than previously appreciated in marine environments, both in water column and sediments, and also provides evidence of novel opisthokont phylogenetic lineages. This study highlights the importance of high throughput sequencing approaches to unravel the diversity and distribution of both known and novel eukaryotic lineages. PMID:25556908

Networking Omic Data to Envisage Systems Biological Regulation.

PubMed

Kalapanulak, Saowalak; Saithong, Treenut; Thammarongtham, Chinae

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

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

PubMed

Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

2017-02-01

The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

High-throughput sequencing of TCR repertoires in multiple sclerosis reveals intrathecal enrichment of EBV-reactive CD8+ T cells.

PubMed

Lossius, Andreas; Johansen, Jorunn N; Vartdal, Frode; Robins, Harlan; Jūratė Šaltytė, Benth; Holmøy, Trygve; Olweus, Johanna

2014-11-01

Epstein-Barr virus (EBV) has long been suggested as a pathogen in multiple sclerosis (MS). Here, we used high-throughput sequencing to determine the diversity, compartmentalization, persistence, and EBV-reactivity of the T-cell receptor (TCR) repertoires in MS. TCR-β genes were sequenced in paired samples of cerebrospinal fluid (CSF) and blood from patients with MS and controls with other inflammatory neurological diseases. The TCR repertoires were highly diverse in both compartments and patient groups. Expanded T-cell clones, represented by TCR-β sequences >0.1%, were of different identity in CSF and blood of MS patients, and persisted for more than a year. Reference TCR-β libraries generated from peripheral blood T cells reactive against autologous EBV-transformed B cells were highly enriched for public EBV-specific sequences and were used to quantify EBV-reactive TCR-β sequences in CSF. TCR-β sequences of EBV-reactive CD8+ T cells, including several public EBV-specific sequences, were intrathecally enriched in MS patients only, whereas those of EBV-reactive CD4+ T cells were also enriched in CSF of controls. These data provide evidence for a clonally diverse, yet compartmentalized and persistent, intrathecal T-cell response in MS. The presented strategy links TCR sequence to intrathecal T-cell specificity, demonstrating enrichment of EBV-reactive CD8+ T cells in MS. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Treesearch

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

2018-01-01

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

A re-sequencing based assessment of genomic heterogeneity and fast neutron-induced deletions in a common bean cultivar

USDA-ARS?s Scientific Manuscript database

A small fast neutron mutant population has been established from Phaseolus vulgaris cv. Red Hawk. We leveraged the available P. vulgaris genome sequence and high throughput next generation DNA sequencing to examine the genomic structure of five Phaseolus vulgaris cv. Red Hawk fast neutron mutants wi...

A fungal mock community control for amplicon sequencing experiments

USDA-ARS?s Scientific Manuscript database

The field of microbial ecology has been profoundly advanced by the ability to profile the composition of complex microbial communities by means of high throughput amplicon sequencing of marker genes amplified directly from environmental genomic DNA extracts. However, it has become increasingly clear...

HTSeq--a Python framework to work with high-throughput sequencing data.

PubMed

Anders, Simon; Pyl, Paul Theodor; Huber, Wolfgang

2015-01-15

A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. © The Author 2014. Published by Oxford University Press.

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

PubMed

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-05-21

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Viruses associated with Antarctic wildlife: From serology based detection to identification of genomes using high throughput sequencing.

PubMed

Smeele, Zoe E; Ainley, David G; Varsani, Arvind

2018-01-02

The Antarctic, sub-Antarctic islands and surrounding sea-ice provide a unique environment for the existence of organisms. Nonetheless, birds and seals of a variety of species inhabit them, particularly during their breeding seasons. Early research on Antarctic wildlife health, using serology-based assays, showed exposure to viruses in the families Birnaviridae, Flaviviridae, Herpesviridae, Orthomyxoviridae and Paramyxoviridae circulating in seals (Phocidae), penguins (Spheniscidae), petrels (Procellariidae) and skuas (Stercorariidae). It is only during the last decade or so that polymerase chain reaction-based assays have been used to characterize viruses associated with Antarctic animals. Furthermore, it is only during the last five years that full/whole genomes of viruses (adenoviruses, anelloviruses, orthomyxoviruses, a papillomavirus, paramyoviruses, polyomaviruses and a togavirus) have been sequenced using Sanger sequencing or high throughput sequencing (HTS) approaches. This review summaries the knowledge of animal Antarctic virology and discusses potential future directions with the advent of HTS in virus discovery and ecology. Copyright © 2017 Elsevier B.V. All rights reserved.

High-purity circular RNA isolation method (RPAD) reveals vast collection of intronic circRNAs.

PubMed

Panda, Amaresh C; De, Supriyo; Grammatikakis, Ioannis; Munk, Rachel; Yang, Xiaoling; Piao, Yulan; Dudekula, Dawood B; Abdelmohsen, Kotb; Gorospe, Myriam

2017-07-07

High-throughput RNA sequencing methods coupled with specialized bioinformatic analyses have recently uncovered tens of thousands of unique circular (circ)RNAs, but their complete sequences, genes of origin and functions are largely unknown. Given that circRNAs lack free ends and are thus relatively stable, their association with microRNAs (miRNAs) and RNA-binding proteins (RBPs) can influence gene expression programs. While exoribonuclease treatment is widely used to degrade linear RNAs and enrich circRNAs in RNA samples, it does not efficiently eliminate all linear RNAs. Here, we describe a novel method for the isolation of highly pure circRNA populations involving RNase R treatment followed by Polyadenylation and poly(A)+ RNA Depletion (RPAD), which removes linear RNA to near completion. High-throughput sequencing of RNA prepared using RPAD from human cervical carcinoma HeLa cells and mouse C2C12 myoblasts led to two surprising discoveries: (i) many exonic circRNA (EcircRNA) isoforms share an identical backsplice sequence but have different body sizes and sequences, and (ii) thousands of novel intronic circular RNAs (IcircRNAs) are expressed in cells. In sum, isolating high-purity circRNAs using the RPAD method can enable quantitative and qualitative analyses of circRNA types and sequence composition, paving the way for the elucidation of circRNA functions. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

High-purity circular RNA isolation method (RPAD) reveals vast collection of intronic circRNAs

PubMed Central

De, Supriyo; Grammatikakis, Ioannis; Munk, Rachel; Yang, Xiaoling; Piao, Yulan; Dudekula, Dawood B.; Gorospe, Myriam

2017-01-01

Abstract High-throughput RNA sequencing methods coupled with specialized bioinformatic analyses have recently uncovered tens of thousands of unique circular (circ)RNAs, but their complete sequences, genes of origin and functions are largely unknown. Given that circRNAs lack free ends and are thus relatively stable, their association with microRNAs (miRNAs) and RNA-binding proteins (RBPs) can influence gene expression programs. While exoribonuclease treatment is widely used to degrade linear RNAs and enrich circRNAs in RNA samples, it does not efficiently eliminate all linear RNAs. Here, we describe a novel method for the isolation of highly pure circRNA populations involving RNase R treatment followed by Polyadenylation and poly(A)+ RNA Depletion (RPAD), which removes linear RNA to near completion. High-throughput sequencing of RNA prepared using RPAD from human cervical carcinoma HeLa cells and mouse C2C12 myoblasts led to two surprising discoveries: (i) many exonic circRNA (EcircRNA) isoforms share an identical backsplice sequence but have different body sizes and sequences, and (ii) thousands of novel intronic circular RNAs (IcircRNAs) are expressed in cells. In sum, isolating high-purity circRNAs using the RPAD method can enable quantitative and qualitative analyses of circRNA types and sequence composition, paving the way for the elucidation of circRNA functions. PMID:28444238

Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing

PubMed Central

Kingsford, Carl

2017-01-01

With the rapidly increasing volume of deep sequencing data, more efficient algorithms and data structures are needed. Minimizers are a central recent paradigm that has improved various sequence analysis tasks, including hashing for faster read overlap detection, sparse suffix arrays for creating smaller indexes, and Bloom filters for speeding up sequence search. Here, we propose an alternative paradigm that can lead to substantial further improvement in these and other tasks. For integers k and L > k, we say that a set of k-mers is a universal hitting set (UHS) if every possible L-long sequence must contain a k-mer from the set. We develop a heuristic called DOCKS to find a compact UHS, which works in two phases: The first phase is solved optimally, and for the second we propose several efficient heuristics, trading set size for speed and memory. The use of heuristics is motivated by showing the NP-hardness of a closely related problem. We show that DOCKS works well in practice and produces UHSs that are very close to a theoretical lower bound. We present results for various values of k and L and by applying them to real genomes show that UHSs indeed improve over minimizers. In particular, DOCKS uses less than 30% of the 10-mers needed to span the human genome compared to minimizers. The software and computed UHSs are freely available at github.com/Shamir-Lab/DOCKS/ and acgt.cs.tau.ac.il/docks/, respectively. PMID:28968408

Molecular Diet Analysis of Two African Free-Tailed Bats (Molossidae) Using High Throughput Sequencing

PubMed Central

Bohmann, Kristine; Monadjem, Ara; Lehmkuhl Noer, Christina; Rasmussen, Morten; Zeale, Matt R. K.; Clare, Elizabeth; Jones, Gareth; Willerslev, Eske; Gilbert, M. Thomas P.

2011-01-01

Given the diversity of prey consumed by insectivorous bats, it is difficult to discern the composition of their diet using morphological or conventional PCR-based analyses of their faeces. We demonstrate the use of a powerful alternate tool, the use of the Roche FLX sequencing platform to deep-sequence uniquely 5′ tagged insect-generic barcode cytochrome c oxidase I (COI) fragments, that were PCR amplified from faecal pellets of two free-tailed bat species Chaerephon pumilus and Mops condylurus (family: Molossidae). Although the analyses were challenged by the paucity of southern African insect COI sequences in the GenBank and BOLD databases, similarity to existing collections allowed the preliminary identification of 25 prey families from six orders of insects within the diet of C. pumilus, and 24 families from seven orders within the diet of M. condylurus. Insects identified to families within the orders Lepidoptera and Diptera were widely present among the faecal samples analysed. The two families that were observed most frequently were Noctuidae and Nymphalidae (Lepidoptera). Species-level analysis of the data was accomplished using novel bioinformatics techniques for the identification of molecular operational taxonomic units (MOTU). Based on these analyses, our data provide little evidence of resource partitioning between sympatric M. condylurus and C. pumilus in the Simunye region of Swaziland at the time of year when the samples were collected, although as more complete databases against which to compare the sequences are generated this may have to be re-evaluated. PMID:21731749

The draft genome sequence of cork oak

PubMed Central

Ramos, António Marcos; Usié, Ana; Barbosa, Pedro; Barros, Pedro M.; Capote, Tiago; Chaves, Inês; Simões, Fernanda; Abreu, Isabl; Carrasquinho, Isabel; Faro, Carlos; Guimarães, Joana B.; Mendonça, Diogo; Nóbrega, Filomena; Rodrigues, Leandra; Saibo, Nelson J. M.; Varela, Maria Carolina; Egas, Conceição; Matos, José; Miguel, Célia M.; Oliveira, M. Margarida; Ricardo, Cândido P.; Gonçalves, Sónia

2018-01-01

Cork oak (Quercus suber) is native to southwest Europe and northwest Africa where it plays a crucial environmental and economical role. To tackle the cork oak production and industrial challenges, advanced research is imperative but dependent on the availability of a sequenced genome. To address this, we produced the first draft version of the cork oak genome. We followed a de novo assembly strategy based on high-throughput sequence data, which generated a draft genome comprising 23,347 scaffolds and 953.3 Mb in size. A total of 79,752 genes and 83,814 transcripts were predicted, including 33,658 high-confidence genes. An InterPro signature assignment was detected for 69,218 transcripts, which represented 82.6% of the total. Validation studies demonstrated the genome assembly and annotation completeness and highlighted the usefulness of the draft genome for read mapping of high-throughput sequence data generated using different protocols. All data generated is available through the public databases where it was deposited, being therefore ready to use by the academic and industry communities working on cork oak and/or related species. PMID:29786699

The draft genome sequence of cork oak.

PubMed

Ramos, António Marcos; Usié, Ana; Barbosa, Pedro; Barros, Pedro M; Capote, Tiago; Chaves, Inês; Simões, Fernanda; Abreu, Isabl; Carrasquinho, Isabel; Faro, Carlos; Guimarães, Joana B; Mendonça, Diogo; Nóbrega, Filomena; Rodrigues, Leandra; Saibo, Nelson J M; Varela, Maria Carolina; Egas, Conceição; Matos, José; Miguel, Célia M; Oliveira, M Margarida; Ricardo, Cândido P; Gonçalves, Sónia

2018-05-22

Cork oak (Quercus suber) is native to southwest Europe and northwest Africa where it plays a crucial environmental and economical role. To tackle the cork oak production and industrial challenges, advanced research is imperative but dependent on the availability of a sequenced genome. To address this, we produced the first draft version of the cork oak genome. We followed a de novo assembly strategy based on high-throughput sequence data, which generated a draft genome comprising 23,347 scaffolds and 953.3 Mb in size. A total of 79,752 genes and 83,814 transcripts were predicted, including 33,658 high-confidence genes. An InterPro signature assignment was detected for 69,218 transcripts, which represented 82.6% of the total. Validation studies demonstrated the genome assembly and annotation completeness and highlighted the usefulness of the draft genome for read mapping of high-throughput sequence data generated using different protocols. All data generated is available through the public databases where it was deposited, being therefore ready to use by the academic and industry communities working on cork oak and/or related species.

Using high-throughput barcode sequencing to efficiently map connectomes.

PubMed

Peikon, Ian D; Kebschull, Justus M; Vagin, Vasily V; Ravens, Diana I; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R; Bressan, Dario; Zador, Anthony M

2017-07-07

The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics

PubMed Central

Chen, Dana; Orenstein, Yaron; Golodnitsky, Rada; Pellach, Michal; Avrahami, Dorit; Wachtel, Chaim; Ovadia-Shochat, Avital; Shir-Shapira, Hila; Kedmi, Adi; Juven-Gershon, Tamar; Shamir, Ron; Gerber, Doron

2016-01-01

Transcription factors (TFs) alter gene expression in response to changes in the environment through sequence-specific interactions with the DNA. These interactions are best portrayed as a landscape of TF binding affinities. Current methods to study sequence-specific binding preferences suffer from limited dynamic range, sequence bias, lack of specificity and limited throughput. We have developed a microfluidic-based device for SELEX Affinity Landscape MAPping (SELMAP) of TF binding, which allows high-throughput measurement of 16 proteins in parallel. We used it to measure the relative affinities of Pho4, AtERF2 and Btd full-length proteins to millions of different DNA binding sites, and detected both high and low-affinity interactions in equilibrium conditions, generating a comprehensive landscape of the relative TF affinities to all possible DNA 6-mers, and even DNA10-mers with increased sequencing depth. Low quantities of both the TFs and DNA oligomers were sufficient for obtaining high-quality results, significantly reducing experimental costs. SELMAP allows in-depth screening of hundreds of TFs, and provides a means for better understanding of the regulatory processes that govern gene expression. PMID:27628341

PANGEA: pipeline for analysis of next generation amplicons

PubMed Central

Giongo, Adriana; Crabb, David B; Davis-Richardson, Austin G; Chauliac, Diane; Mobberley, Jennifer M; Gano, Kelsey A; Mukherjee, Nabanita; Casella, George; Roesch, Luiz FW; Walts, Brandon; Riva, Alberto; King, Gary; Triplett, Eric W

2010-01-01

High-throughput DNA sequencing can identify organisms and describe population structures in many environmental and clinical samples. Current technologies generate millions of reads in a single run, requiring extensive computational strategies to organize, analyze and interpret those sequences. A series of bioinformatics tools for high-throughput sequencing analysis, including preprocessing, clustering, database matching and classification, have been compiled into a pipeline called PANGEA. The PANGEA pipeline was written in Perl and can be run on Mac OSX, Windows or Linux. With PANGEA, sequences obtained directly from the sequencer can be processed quickly to provide the files needed for sequence identification by BLAST and for comparison of microbial communities. Two different sets of bacterial 16S rRNA sequences were used to show the efficiency of this workflow. The first set of 16S rRNA sequences is derived from various soils from Hawaii Volcanoes National Park. The second set is derived from stool samples collected from diabetes-resistant and diabetes-prone rats. The workflow described here allows the investigator to quickly assess libraries of sequences on personal computers with customized databases. PANGEA is provided for users as individual scripts for each step in the process or as a single script where all processes, except the χ2 step, are joined into one program called the ‘backbone’. PMID:20182525

PANGEA: pipeline for analysis of next generation amplicons.

PubMed

Giongo, Adriana; Crabb, David B; Davis-Richardson, Austin G; Chauliac, Diane; Mobberley, Jennifer M; Gano, Kelsey A; Mukherjee, Nabanita; Casella, George; Roesch, Luiz F W; Walts, Brandon; Riva, Alberto; King, Gary; Triplett, Eric W

2010-07-01

High-throughput DNA sequencing can identify organisms and describe population structures in many environmental and clinical samples. Current technologies generate millions of reads in a single run, requiring extensive computational strategies to organize, analyze and interpret those sequences. A series of bioinformatics tools for high-throughput sequencing analysis, including pre-processing, clustering, database matching and classification, have been compiled into a pipeline called PANGEA. The PANGEA pipeline was written in Perl and can be run on Mac OSX, Windows or Linux. With PANGEA, sequences obtained directly from the sequencer can be processed quickly to provide the files needed for sequence identification by BLAST and for comparison of microbial communities. Two different sets of bacterial 16S rRNA sequences were used to show the efficiency of this workflow. The first set of 16S rRNA sequences is derived from various soils from Hawaii Volcanoes National Park. The second set is derived from stool samples collected from diabetes-resistant and diabetes-prone rats. The workflow described here allows the investigator to quickly assess libraries of sequences on personal computers with customized databases. PANGEA is provided for users as individual scripts for each step in the process or as a single script where all processes, except the chi(2) step, are joined into one program called the 'backbone'.

Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

PubMed Central

Bodenmiller, Bernd; Zunder, Eli R.; Finck, Rachel; Chen, Tiffany J.; Savig, Erica S.; Bruggner, Robert V.; Simonds, Erin F.; Bendall, Sean C.; Sachs, Karen; Krutzik, Peter O.; Nolan, Garry P.

2013-01-01

The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease. PMID:22902532

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.

Repeat-aware modeling and correction of short read errors.

PubMed

Yang, Xiao; Aluru, Srinivas; Dorman, Karin S

2011-02-15

High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.

High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing.

PubMed

Lagarde, Julien; Uszczynska-Ratajczak, Barbara; Carbonell, Silvia; Pérez-Lluch, Sílvia; Abad, Amaya; Davis, Carrie; Gingeras, Thomas R; Frankish, Adam; Harrow, Jennifer; Guigo, Roderic; Johnson, Rory

2017-12-01

Accurate annotation of genes and their transcripts is a foundation of genomics, but currently no annotation technique combines throughput and accuracy. As a result, reference gene collections remain incomplete-many gene models are fragmentary, and thousands more remain uncataloged, particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), which combines targeted RNA capture with third-generation long-read sequencing. Here we present an experimental reannotation of the GENCODE intergenic lncRNA populations in matched human and mouse tissues that resulted in novel transcript models for 3,574 and 561 gene loci, respectively. CLS approximately doubled the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enabled us to definitively characterize the genomic features of lncRNAs, including promoter and gene structure, and protein-coding potential. Thus, CLS removes a long-standing bottleneck in transcriptome annotation and generates manual-quality full-length transcript models at high-throughput scales.

'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

PubMed

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-04-12

Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

'PACLIMS': A component LIM system for high-throughput functional genomic analysis

PubMed Central

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-01-01

Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors. PMID:15826298

Whole Wiskott‑Aldrich syndrome protein gene deletion identified by high throughput sequencing.

PubMed

He, Xiangling; Zou, Runying; Zhang, Bing; You, Yalan; Yang, Yang; Tian, Xin

2017-11-01

Wiskott‑Aldrich syndrome (WAS) is a rare X‑linked recessive immunodeficiency disorder, characterized by thrombocytopenia, small platelets, eczema and recurrent infections associated with increased risk of autoimmunity and malignancy disorders. Mutations in the WAS protein (WASP) gene are responsible for WAS. To date, WASP mutations, including missense/nonsense, splicing, small deletions, small insertions, gross deletions, and gross insertions have been identified in patients with WAS. In addition, WASP‑interacting proteins are suspected in patients with clinical features of WAS, in whom the WASP gene sequence and mRNA levels are normal. The present study aimed to investigate the application of next generation sequencing in definitive diagnosis and clinical therapy for WAS. A 5 month‑old child with WAS who displayed symptoms of thrombocytopenia was examined. Whole exome sequence analysis of genomic DNA showed that the coverage and depth of WASP were extremely low. Quantitative polymerase chain reaction indicated total WASP gene deletion in the proband. In conclusion, high throughput sequencing is useful for the verification of WAS on the genetic profile, and has implications for family planning guidance and establishment of clinical programs.

The use of museum specimens with high-throughput DNA sequencers

PubMed Central

Burrell, Andrew S.; Disotell, Todd R.; Bergey, Christina M.

2015-01-01

Natural history collections have long been used by morphologists, anatomists, and taxonomists to probe the evolutionary process and describe biological diversity. These biological archives also offer great opportunities for genetic research in taxonomy, conservation, systematics, and population biology. They allow assays of past populations, including those of extinct species, giving context to present patterns of genetic variation and direct measures of evolutionary processes. Despite this potential, museum specimens are difficult to work with because natural postmortem processes and preservation methods fragment and damage DNA. These problems have restricted geneticists’ ability to use natural history collections primarily by limiting how much of the genome can be surveyed. Recent advances in DNA sequencing technology, however, have radically changed this, making truly genomic studies from museum specimens possible. We review the opportunities and drawbacks of the use of museum specimens, and suggest how to best execute projects when incorporating such samples. Several high-throughput (HT) sequencing methodologies, including whole genome shotgun sequencing, sequence capture, and restriction digests (demonstrated here), can be used with archived biomaterials. PMID:25532801

Rapid and reliable high-throughput methods of DNA extraction for use in barcoding and molecular systematics of mushrooms.

PubMed

Dentinger, Bryn T M; Margaritescu, Simona; Moncalvo, Jean-Marc

2010-07-01

We present two methods for DNA extraction from fresh and dried mushrooms that are adaptable to high-throughput sequencing initiatives, such as DNA barcoding. Our results show that these protocols yield ∼85% sequencing success from recently collected materials. Tests with both recent (<2 year) and older (>100 years) specimens reveal that older collections have low success rates and may be an inefficient resource for populating a barcode database. However, our method of extracting DNA from herbarium samples using small amount of tissue is reliable and could be used for important historical specimens. The application of these protocols greatly reduces time, and therefore cost, of generating DNA sequences from mushrooms and other fungi vs. traditional extraction methods. The efficiency of these methods illustrates that standardization and streamlining of sample processing should be shifted from the laboratory to the field. © 2009 Blackwell Publishing Ltd.

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

PubMed

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

2018-01-01

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

Genetic legacy of the deep subsurface recorded in the outflow channel of a terrestrial serpentinizing seep (Luzon, the Philippines)

NASA Astrophysics Data System (ADS)

Woycheese, K. M.; Meyer-Dombard, D. R.; Cardace, D.; Arcilla, C. A.

2014-12-01

The deep subsurface microbial community represents the largest biome on Earth, yet accessing this deep biosphere is challenging. Fluids seep along fractures from aquifers that may support diverse microbial communities, living off hydrogen gas generated by radiolysis, serpentinization, or thermogenic reactions. A serpentinizing seep, emanating fluids as high as pH 11.27, was found to accrete meters-long carbonate terraces in the Zambales ophiolite range (Luzon, the Philippines). Samples were collected at several locations along the Poon Bato (PB) River, focusing primarily on the pools and terraces formed by carbonate rimstone (Figure 1). As serpentinizing fluids are exposed to the atmosphere, dynamic niches are established in surface sediments. We propose that the high pH, reducing, high Ca+2 fluid pool terraces reflect remnants of deep subsurface microbial communities, based on high-throughput 16S rRNA sequencing data. In total, eight samples were collected for environmental DNA analysis. Post-sequence analysis revealed a total of 927126 counts, with an average of 115890.75 counts per sample. Many taxa aligned with cultured representatives of serpentinizing seep-associated taxa, including Bacteroidetes, Clostrida, Chloroflexi, Methylococcales, and Xanthomonadales. Geochemical data indicates an average fluid temperature of 28.9°C, and pH that varies from 9.22-11.27. Total carbon wt.% of solids was highest in a shallow pool shaped by boulders, where calcite precipitation occurred over nearly every surface. Dissolved oxygen (DO%) was highest at PB1 main pool (60%), although a calcite skin had formed along the air-water interface. Dissolved inorganic carbon (DIC) at PB1 main pool was 1.3 ppm, while at PB2 main pool, the DIC was higher (6.0 ppm). The lack of calcite skin may allow more direct access to atmospheric carbon dioxide at PB2. The isotopic value of carbon-13 was depleted at PB1 relative to PB2 (δ13C VPDB -25.4 ‰ versus δ13C VPDB ‰ -17.5, respectively). The DOC concentration at PB1 main pool was 0.3 ppm and 1.15 ppm at PB2. Given the low DIC concentrations at PB1, it is suggested that heterotrophy may dominate over autotrophy in the system. This suggests that the highly reducing, high pH fluids emanating from fluid seeps at Poon Bato influence surface communities via inundation with serpentinizing fluid.

Epigenetics and Epigenomics of Plants.

PubMed

Yadav, Chandra Bhan; Pandey, Garima; Muthamilarasan, Mehanathan; Prasad, Manoj

2018-01-23

The genetic material DNA in association with histone proteins forms the complex structure called chromatin, which is prone to undergo modification through certain epigenetic mechanisms including cytosine DNA methylation, histone modifications, and small RNA-mediated methylation. Alterations in chromatin structure lead to inaccessibility of genomic DNA to various regulatory proteins such as transcription factors, which eventually modulates gene expression. Advancements in high-throughput sequencing technologies have provided the opportunity to study the epigenetic mechanisms at genome-wide levels. Epigenomic studies using high-throughput technologies will widen the understanding of mechanisms as well as functions of regulatory pathways in plant genomes, which will further help in manipulating these pathways using genetic and biochemical approaches. This technology could be a potential research tool for displaying the systematic associations of genetic and epigenetic variations, especially in terms of cytosine methylation onto the genomic region in a specific cell or tissue. A comprehensive study of plant populations to correlate genotype to epigenotype and to phenotype, and also the study of methyl quantitative trait loci (QTL) or epiGWAS, is possible by using high-throughput sequencing methods, which will further accelerate molecular breeding programs for crop improvement. Graphical Abstract.

Development and use of molecular markers: past and present.

PubMed

Grover, Atul; Sharma, P C

2016-01-01

Molecular markers, due to their stability, cost-effectiveness and ease of use provide an immensely popular tool for a variety of applications including genome mapping, gene tagging, genetic diversity diversity, phylogenetic analysis and forensic investigations. In the last three decades, a number of molecular marker techniques have been developed and exploited worldwide in different systems. However, only a handful of these techniques, namely RFLPs, RAPDs, AFLPs, ISSRs, SSRs and SNPs have received global acceptance. A recent revolution in DNA sequencing techniques has taken the discovery and application of molecular markers to high-throughput and ultrahigh-throughput levels. Although, the choice of marker will obviously depend on the targeted use, microsatellites, SNPs and genotyping by sequencing (GBS) largely fulfill most of the user requirements. Further, modern transcriptomic and functional markers will lead the ventures onto high-density genetic map construction, identification of QTLs, breeding and conservation strategies in times to come in combination with other high throughput techniques. This review presents an overview of different marker technologies and their variants with a comparative account of their characteristic features and applications.

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.

Filling reference gaps via assembling DNA barcodes using high-throughput sequencing-moving toward barcoding the world.

PubMed

Liu, Shanlin; Yang, Chentao; Zhou, Chengran; Zhou, Xin

2017-12-01

Over the past decade, biodiversity researchers have dedicated tremendous efforts to constructing DNA reference barcodes for rapid species registration and identification. Although analytical cost for standard DNA barcoding has been significantly reduced since early 2000, further dramatic reduction in barcoding costs is unlikely because Sanger sequencing is approaching its limits in throughput and chemistry cost. Constraints in barcoding cost not only led to unbalanced barcoding efforts around the globe, but also prevented high-throughput sequencing (HTS)-based taxonomic identification from applying binomial species names, which provide crucial linkages to biological knowledge. We developed an Illumina-based pipeline, HIFI-Barcode, to produce full-length Cytochrome c oxidase subunit I (COI) barcodes from pooled polymerase chain reaction amplicons generated by individual specimens. The new pipeline generated accurate barcode sequences that were comparable to Sanger standards, even for different haplotypes of the same species that were only a few nucleotides different from each other. Additionally, the new pipeline was much more sensitive in recovering amplicons at low quantity. The HIFI-Barcode pipeline successfully recovered barcodes from more than 78% of the polymerase chain reactions that didn't show clear bands on the electrophoresis gel. Moreover, sequencing results based on the single molecular sequencing platform Pacbio confirmed the accuracy of the HIFI-Barcode results. Altogether, the new pipeline can provide an improved solution to produce full-length reference barcodes at about one-tenth of the current cost, enabling construction of comprehensive barcode libraries for local fauna, leading to a feasible direction for DNA barcoding global biomes. © The Authors 2017. Published by Oxford University Press.

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

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

Shi, CY; Yang, H; Wei, CL

Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from poly (A){sup +} RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled intomore » 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real time PCR (qRT-PCR). An extensive transcriptome dataset has been obtained from the deep sequencing of tea plant. The coverage of the transcriptome is comprehensive enough to discover all known genes of several major metabolic pathways. This transcriptome dataset can serve as an important public information platform for gene expression, genomics, and functional genomic studies in C. sinensis.« less

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

PubMed Central

2011-01-01

Background Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Results Using high-throughput Illumina RNA-seq, the transcriptome from poly (A)+ RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real time PCR (qRT-PCR). Conclusions An extensive transcriptome dataset has been obtained from the deep sequencing of tea plant. The coverage of the transcriptome is comprehensive enough to discover all known genes of several major metabolic pathways. This transcriptome dataset can serve as an important public information platform for gene expression, genomics, and functional genomic studies in C. sinensis. PMID:21356090

Transcription profile of boar spermatozoa as revealed by RNA-sequencing

USDA-ARS?s Scientific Manuscript database

High-throughput RNA sequencing (RNA-Seq) overcomes the limitations of the current hybridization-based techniques to detect the actual pool of RNA transcripts in spermatozoa. The application of this technology in livestock can speed the discovery of potential predictors of male fertility. As a first ...

Biofilm-Growing Bacteria Involved in the Corrosion of Concrete Wastewater Pipes: Protocols for Comparative Metagenomic Analyses

EPA Science Inventory

Advances in high-throughput next-generation sequencing (NGS) technology for direct sequencing of environmental DNA (i.e. shotgun metagenomics) is transforming the field of microbiology. NGS technologies are now regularly being applied in comparative metagenomic studies, which pr...

Response of Bacterial Communities to Different Detritus Compositions in Arctic Deep-Sea Sediments.

PubMed

Hoffmann, Katy; Hassenrück, Christiane; Salman-Carvalho, Verena; Holtappels, Moritz; Bienhold, Christina

2017-01-01

Benthic deep-sea communities are largely dependent on particle flux from surface waters. In the Arctic Ocean, environmental changes occur more rapidly than in other ocean regions, and have major effects on the export of organic matter to the deep sea. Because bacteria constitute the majority of deep-sea benthic biomass and influence global element cycles, it is important to better understand how changes in organic matter input will affect bacterial communities at the Arctic seafloor. In a multidisciplinary ex situ experiment, benthic bacterial deep-sea communities from the Long-Term Ecological Research Observatory HAUSGARTEN were supplemented with different types of habitat-related detritus (chitin, Arctic algae) and incubated for 23 days under in situ conditions. Chitin addition caused strong changes in community activity, while community structure remained similar to unfed control incubations. In contrast, the addition of phytodetritus resulted in strong changes in community composition, accompanied by increased community activity, indicating the need for adaptation in these treatments. High-throughput sequencing of the 16S rRNA gene and 16S rRNA revealed distinct taxonomic groups of potentially fast-growing, opportunistic bacteria in the different detritus treatments. Compared to the unfed control, Colwelliaceae, Psychromonadaceae , and Oceanospirillaceae increased in relative abundance in the chitin treatment, whereas Flavobacteriaceae, Marinilabiaceae , and Pseudoalteromonadaceae increased in the phytodetritus treatments. Hence, these groups may constitute indicator taxa for the different organic matter sources at this study site. In summary, differences in community structure and in the uptake and remineralization of carbon in the different treatments suggest an effect of organic matter quality on bacterial diversity as well as on carbon turnover at the seafloor, an important feedback mechanism to be considered in future climate change scenarios.

Response of Bacterial Communities to Different Detritus Compositions in Arctic Deep-Sea Sediments

PubMed Central

Hoffmann, Katy; Hassenrück, Christiane; Salman-Carvalho, Verena; Holtappels, Moritz; Bienhold, Christina

2017-01-01

Benthic deep-sea communities are largely dependent on particle flux from surface waters. In the Arctic Ocean, environmental changes occur more rapidly than in other ocean regions, and have major effects on the export of organic matter to the deep sea. Because bacteria constitute the majority of deep-sea benthic biomass and influence global element cycles, it is important to better understand how changes in organic matter input will affect bacterial communities at the Arctic seafloor. In a multidisciplinary ex situ experiment, benthic bacterial deep-sea communities from the Long-Term Ecological Research Observatory HAUSGARTEN were supplemented with different types of habitat-related detritus (chitin, Arctic algae) and incubated for 23 days under in situ conditions. Chitin addition caused strong changes in community activity, while community structure remained similar to unfed control incubations. In contrast, the addition of phytodetritus resulted in strong changes in community composition, accompanied by increased community activity, indicating the need for adaptation in these treatments. High-throughput sequencing of the 16S rRNA gene and 16S rRNA revealed distinct taxonomic groups of potentially fast-growing, opportunistic bacteria in the different detritus treatments. Compared to the unfed control, Colwelliaceae, Psychromonadaceae, and Oceanospirillaceae increased in relative abundance in the chitin treatment, whereas Flavobacteriaceae, Marinilabiaceae, and Pseudoalteromonadaceae increased in the phytodetritus treatments. Hence, these groups may constitute indicator taxa for the different organic matter sources at this study site. In summary, differences in community structure and in the uptake and remineralization of carbon in the different treatments suggest an effect of organic matter quality on bacterial diversity as well as on carbon turnover at the seafloor, an important feedback mechanism to be considered in future climate change scenarios. PMID:28286496

High-Throughput Sequencing and Metagenomics: Moving Forward in the Culture-Independent Analysis of Food Microbial Ecology

PubMed Central

2013-01-01

Following recent trends in environmental microbiology, food microbiology has benefited from the advances in molecular biology and adopted novel strategies to detect, identify, and monitor microbes in food. An in-depth study of the microbial diversity in food can now be achieved by using high-throughput sequencing (HTS) approaches after direct nucleic acid extraction from the sample to be studied. In this review, the workflow of applying culture-independent HTS to food matrices is described. The current scenario and future perspectives of HTS uses to study food microbiota are presented, and the decision-making process leading to the best choice of working conditions to fulfill the specific needs of food research is described. PMID:23475615

Using high-throughput barcode sequencing to efficiently map connectomes

PubMed Central

Peikon, Ian D.; Kebschull, Justus M.; Vagin, Vasily V.; Ravens, Diana I.; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R.; Bressan, Dario

2017-01-01

Abstract The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision—a ‘connectome’—is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence—an RNA ‘barcode’—which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. PMID:28449067

RIPiT-Seq: A high-throughput approach for footprinting RNA:protein complexes

PubMed Central

Singh, Guramrit; Ricci, Emiliano P.; Moore, Melissa J.

2013-01-01

Development of high-throughput approaches to map the RNA interaction sites of individual RNA binding proteins (RBPs) transcriptome-wide is rapidly transforming our understanding of post-transcriptional gene regulatory mechanisms. Here we describe a ribonucleoprotein (RNP) footprinting approach we recently developed for identifying occupancy sites of both individual RBPs and multi-subunit RNP complexes. RNA:protein immunoprecipitation in tandem (RIPiT) yields highly specific RNA footprints of cellular RNPs isolated via two sequential purifications; the resulting RNA footprints can then be identified by high-throughput sequencing (Seq). RIPiT-Seq is broadly applicable to all RBPs regardless of their RNA binding mode and thus provides a means to map the RNA binding sites of RBPs with poor inherent ultraviolet (UV) crosslinkability. Further, among current high-throughput approaches, RIPiT has the unique capacity to differentiate binding sites of RNPs with overlapping protein composition. It is therefore particularly suited for studying dynamic RNP assemblages whose composition evolves as gene expression proceeds. PMID:24096052

Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array.

PubMed

Devault, Alison M; McLoughlin, Kevin; Jaing, Crystal; Gardner, Shea; Porter, Teresita M; Enk, Jacob M; Thissen, James; Allen, Jonathan; Borucki, Monica; DeWitte, Sharon N; Dhody, Anna N; Poinar, Hendrik N

2014-03-06

Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.

BarraCUDA - a fast short read sequence aligner using graphics processing units

PubMed Central

2012-01-01

Background With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. Findings Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. Conclusions BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available from http://seqbarracuda.sf.net PMID:22244497

Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease

PubMed Central

Ghodsi, Mohammad; Sommer, Daniel D.; Gibbons, Theodore R.; Treangen, Todd J.; Chang, Yi-Chien; Li, Shan; Stine, O. Colin; Hasturk, Hatice; Kasif, Simon; Segrè, Daniel; Pop, Mihai; Amar, Salomon

2012-01-01

The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes. PMID:22675498

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

Comparison of Burrows-Wheeler transform-based mapping algorithms used in high-throughput whole-genome sequencing: application to Illumina data for livestock genomes

USDA-ARS?s Scientific Manuscript database

Ongoing developments and cost decreases in next-generation sequencing (NGS) technologies have led to an increase in their application, which has greatly enhanced the fields of genetics and genomics. Mapping sequence reads onto a reference genome is a fundamental step in the analysis of NGS data. Eff...

PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data.

PubMed

Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho

2017-11-01

High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.

Incorporating deep learning into the analysis of diverse livestock data

USDA-ARS?s Scientific Manuscript database

Technological advances in high-throughput phenotyping and multiple omics fields have led to an explosion in the volume of data across the whole spectrum of biology, allowing researchers to integrate data of different types to inform hypotheses and expand the scope of their research questions. Howeve...

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

Davenport, Karen

Karen Davenport of Los Alamos National Laboratory discusses a high-throughput next generation genome finishing pipeline on June 3, 2010 at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.

Single Nucleobase Identification Using Biophysical Signatures from Nanoelectronic Quantum Tunneling.

PubMed

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

2017-03-01

Nanoelectronic DNA sequencing can provide an important alternative to sequencing-by-synthesis by reducing sample preparation time, cost, and complexity as a high-throughput next-generation technique with accurate single-molecule identification. However, sample noise and signature overlap continue to prevent high-resolution and accurate sequencing results. Probing the molecular orbitals of chemically distinct DNA nucleobases offers a path for facile sequence identification, but molecular entropy (from nucleotide conformations) makes such identification difficult when relying only on the energies of lowest-unoccupied and highest-occupied molecular orbitals (LUMO and HOMO). Here, nine biophysical parameters are developed to better characterize molecular orbitals of individual nucleobases, intended for single-molecule DNA sequencing using quantum tunneling of charges. For this analysis, theoretical models for quantum tunneling are combined with transition voltage spectroscopy to obtain measurable parameters unique to the molecule within an electronic junction. Scanning tunneling spectroscopy is then used to measure these nine biophysical parameters for DNA nucleotides, and a modified machine learning algorithm identified nucleobases. The new parameters significantly improve base calling over merely using LUMO and HOMO frontier orbital energies. Furthermore, high accuracies for identifying DNA nucleobases were observed at different pH conditions. These results have significant implications for developing a robust and accurate high-throughput nanoelectronic DNA sequencing technique. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lights, camera, action: high-throughput plant phenotyping is ready for a close-up

USDA-ARS?s Scientific Manuscript database

Modern techniques for crop improvement rely on both DNA sequencing and accurate quantification of plant traits to identify genes and germplasm of interest. With rapid advances in DNA sequencing technologies, plant phenotyping is now a bottleneck in advancing crop yields [1,2]. Furthermore, the envir...

Alfalfa virus S, a new species in the family Alphaflexiviridae

USDA-ARS?s Scientific Manuscript database

A new species of the family Alphaflexiviridae provisionally named alfalfa virus S (AVS) was discovered in alfalfa samples originating from Sudan. A complete nucleotide sequence of the viral genome consisting of 8,349 nucleotides excluding the 3’ poly(A) tail was determined by high throughput sequenc...

High-throughput illumina strand-specific RNA sequencing library preparation

USDA-ARS?s Scientific Manuscript database

Conventional Illumina RNA-Seq does not have the resolution to decode the complex eukaryote transcriptome due to the lack of RNA polarity information. Strand-specific RNA sequencing (ssRNA-Seq) can overcome these limitations and as such is better suited for genome annotation, de novo transcriptome as...

Application of genotyping-by-sequencing for mapping disease resistance in grapevine breeding families

USDA-ARS?s Scientific Manuscript database

Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput, method for genome-wide polymorphism discovery and genotyping adjacent to restriction sites. Since 2010, GBS has been applied for the genotyping of over 12,000 grape breeding lines, with a primary focus on identifying markers predictive ...

Effort versus reward: preparing samples for fungal community characterization in high-throughput sequencing surveys of soils

USDA-ARS?s Scientific Manuscript database

Next generation fungal amplicon sequencing is being used with increasing frequency to study fungal diversity in various ecosystems; however, the influence of sample preparation on the characterization of fungal community is poorly understood. We investigated the effects of four procedural modificati...

High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE

USDA-ARS?s Scientific Manuscript database

We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE (“Assessing Changes to Exons”) converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detect...

SNP-based genotyping in lentil: linking sequence information with phenotypes

USDA-ARS?s Scientific Manuscript database

Lentil (Lens culinaris) has been late to enter the world of high throughput molecular analysis due to a general lack of genomic resources. Using a 454 sequencing-based approach, SNPs have been identified in genes across the lentil genome. Several hundred have been turned into single SNP KASP assay...

Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform

USDA-ARS?s Scientific Manuscript database

Next-generation sequencing (NGS) technologies are revolutionizing both medical and biological research through generation of massive SNP data sets for identifying heritable genome variation underlying key traits, from rare human diseases to important agronomic phenotypes in crop species. We evaluate...

Ultra high-throughput nucleic acid sequencing as a tool for virus discovery in the turkey gut.

USDA-ARS?s Scientific Manuscript database

Recently, the use of the next generation of nucleic acid sequencing technology (i.e., 454 pyrosequencing, as developed by Roche/454 Life Sciences) has allowed an in-depth look at the uncultivated microorganisms present in complex environmental samples, including samples with agricultural importance....

Maize HapMap2 identifies extant variation from a genome in flux

USDA-ARS?s Scientific Manuscript database

The maize genome is the largest, most diverse and complex plant genome sequenced to date. Using high-throughput sequencing to access genetic variation and a population genetics model to score the polymorphisms, we characterize and unite the diversity of the world’s key breeding germplasm, wild rela...

[Community composition and diversity of endophytic fungi from roots of Sinopodophyllum hexandrum in forest of Upper-north mountain of Qinghai province].

PubMed

Ning, Yi; Li, Yan-Ling; Zhou, Guo-Ying; Yang, Lu-Cun; Xu, Wen-Hua

2016-04-01

High throughput sequencing technology is also called Next Generation Sequencing (NGS), which can sequence hundreds and thousands sequences in different samples at the same time. In the present study, the culture-independent high throughput sequencing technology was applied to sequence the fungi metagenomic DNA of the fungal internal transcribed spacer 1(ITS 1) in the root of Sinopodophyllum hexandrum. Sequencing data suggested that after the quality control, 22 565 reads were remained. Cluster similarity analysis was done based on 97% sequence similarity, which obtained 517 OTUs for the three samples (LD1, LD2 and LD3). All the fungi which identified from all the reads of OTUs based on 0.8 classification thresholds using the software of RDP classifier were classified as 13 classes, 35 orders, 44 family, 55 genera. Among these genera, the genus of Tetracladium was the dominant genera in all samples(35.49%, 68.55% and 12.96%).The Shannon's diversity indices and the Simpson indices of the endophytic fungi in the samples ranged from 1.75-2.92, 0.11-0.32, respectively.This is the first time for applying high through put sequencing technol-ogyto analyze the community composition and diversity of endophytic fungi in the medicinal plant, and the results showed that there were hyper diver sity and high community composition complexity of endophytic fungi in the root of S. hexandrum. It is also proved that the high through put sequencing technology has great advantage for analyzing ecommunity composition and diversity of endophtye in the plant. Copyright© by the Chinese Pharmaceutical Association.

Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

Cancer.gov

The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Coding Complete Genome for the Mogiana Tick Virus, a Jingmenvirus Isolated from Ticks in Brazil

DTIC Science & Technology

2017-05-04

sequences for all four genome segments. We downloaded the raw Illumina sequence reads from the NCBI Short Read Archive (GenBank...MGTV genome segments through sequence similarity (BLASTN) to the published genome of Jingmen tick virus (JMTV) isolate SY84 (GenBank: KJ001579-KJ001582...2014. Standards for sequencing viral genomes in the era of high-throughput sequencing . MBio 5:e01360–14. 8. Bankevich A, Nurk S, Antipov

Transcriptome-based differentiation of closely-related Miscanthus lines.

PubMed

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

2012-01-01

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

Accounting for Errors in Low Coverage High-Throughput Sequencing Data When Constructing Genetic Maps Using Biparental Outcrossed Populations

PubMed Central

Bilton, Timothy P.; Schofield, Matthew R.; Black, Michael A.; Chagné, David; Wilcox, Phillip L.; Dodds, Ken G.

2018-01-01

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species’ genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander–Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model. PMID:29487138

Accounting for Errors in Low Coverage High-Throughput Sequencing Data When Constructing Genetic Maps Using Biparental Outcrossed Populations.

PubMed

Bilton, Timothy P; Schofield, Matthew R; Black, Michael A; Chagné, David; Wilcox, Phillip L; Dodds, Ken G

2018-05-01

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology ( e.g. , genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model. Copyright © 2018 Bilton et al.

Calculating the quality of public high-throughput sequencing data to obtain a suitable subset for reanalysis from the Sequence Read Archive.

PubMed

Ohta, Tazro; Nakazato, Takeru; Bono, Hidemasa

2017-06-01

It is important for public data repositories to promote the reuse of archived data. In the growing field of omics science, however, the increasing number of submissions of high-throughput sequencing (HTSeq) data to public repositories prevents users from choosing a suitable data set from among the large number of search results. Repository users need to be able to set a threshold to reduce the number of results to obtain a suitable subset of high-quality data for reanalysis. We calculated the quality of sequencing data archived in a public data repository, the Sequence Read Archive (SRA), by using the quality control software FastQC. We obtained quality values for 1 171 313 experiments, which can be used to evaluate the suitability of data for reuse. We also visualized the data distribution in SRA by integrating the quality information and metadata of experiments and samples. We provide quality information of all of the archived sequencing data, which enable users to obtain sufficient quality sequencing data for reanalyses. The calculated quality data are available to the public in various formats. Our data also provide an example of enhancing the reuse of public data by adding metadata to published research data by a third party. © The Authors 2017. Published by Oxford University Press.

Discovery of precursor and mature microRNAs and their putative gene targets using high-throughput sequencing in pineapple (Ananas comosus var. comosus).

PubMed

Yusuf, Noor Hydayaty Md; Ong, Wen Dee; Redwan, Raimi Mohamed; Latip, Mariam Abd; Kumar, S Vijay

2015-10-15

MicroRNAs (miRNAs) are a class of small, endogenous non-coding RNAs that negatively regulate gene expression, resulting in the silencing of target mRNA transcripts through mRNA cleavage or translational inhibition. MiRNAs play significant roles in various biological and physiological processes in plants. However, the miRNA-mediated gene regulatory network in pineapple, the model tropical non-climacteric fruit, remains largely unexplored. Here, we report a complete list of pineapple mature miRNAs obtained from high-throughput small RNA sequencing and precursor miRNAs (pre-miRNAs) obtained from ESTs. Two small RNA libraries were constructed from pineapple fruits and leaves, respectively, using Illumina's Solexa technology. Sequence similarity analysis using miRBase revealed 579,179 reads homologous to 153 miRNAs from 41 miRNA families. In addition, a pineapple fruit transcriptome library consisting of approximately 30,000 EST contigs constructed using Solexa sequencing was used for the discovery of pre-miRNAs. In all, four pre-miRNAs were identified (MIR156, MIR399, MIR444 and MIR2673). Furthermore, the same pineapple transcriptome was used to dissect the function of the miRNAs in pineapple by predicting their putative targets in conjunction with their regulatory networks. In total, 23 metabolic pathways were found to be regulated by miRNAs in pineapple. The use of high-throughput sequencing in pineapples to unveil the presence of miRNAs and their regulatory pathways provides insight into the repertoire of miRNA regulation used exclusively in this non-climacteric model plant. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a High-Throughput Resequencing Array for the Detection of Pathogenic Mutations in Osteogenesis Imperfecta

PubMed Central

Wang, Yao; Cui, Yazhou; Zhou, Xiaoyan; Han, Jinxiang

2015-01-01

Objective Osteogenesis imperfecta (OI) is a rare inherited skeletal disease, characterized by bone fragility and low bone density. The mutations in this disorder have been widely reported to be on various exonal hotspots of the candidate genes, including COL1A1, COL1A2, CRTAP, LEPRE1, and FKBP10, thus creating a great demand for precise genetic tests. However, large genome sizes make the process daunting and the analyses, inefficient and expensive. Therefore, we aimed at developing a fast, accurate, efficient, and cheaper sequencing platform for OI diagnosis; and to this end, use of an advanced array-based technique was proposed. Method A CustomSeq Affymetrix Resequencing Array was established for high-throughput sequencing of five genes simultaneously. Genomic DNA extraction from 13 OI patients and 85 normal controls and amplification using long-range PCR (LR-PCR) were followed by DNA fragmentation and chip hybridization, according to standard Affymetrix protocols. Hybridization signals were determined using GeneChip Sequence Analysis Software (GSEQ). To examine the feasibility, the outcome from new resequencing approach was validated by conventional capillary sequencing method. Result Overall call rates using resequencing array was 96–98% and the agreement between microarray and capillary sequencing was 99.99%. 11 out of 13 OI patients with pathogenic mutations were successfully detected by the chip analysis without adjustment, and one mutation could also be identified using manual visual inspection. Conclusion A high-throughput resequencing array was developed that detects the disease-associated mutations in OI, providing a potential tool to facilitate large-scale genetic screening for OI patients. Through this method, a novel mutation was also found. PMID:25742658

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 .

Scalable SCPPM Decoder

NASA Technical Reports Server (NTRS)

Quir, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy; Nakashima, Michael A.; Moision, Bruce E.

2012-01-01

A decoder was developed that decodes a serial concatenated pulse position modulation (SCPPM) encoded information sequence. The decoder takes as input a sequence of four bit log-likelihood ratios (LLR) for each PPM slot in a codeword via a XAUI 10-Gb/s quad optical fiber interface. If the decoder is unavailable, it passes the LLRs on to the next decoder via a XAUI 10-Gb/s quad optical fiber interface. Otherwise, it decodes the sequence and outputs information bits through a 1-GB/s Ethernet UDP/IP (User Datagram Protocol/Internet Protocol) interface. The throughput for a single decoder unit is 150-Mb/s at an average of four decoding iterations; by connecting a number of decoder units in series, a decoding rate equal to that of the aggregate rate is achieved. The unit is controlled through a 1-GB/s Ethernet UDP/IP interface. This ground station decoder was developed to demonstrate a deep space optical communication link capability, and is unique in the scalable design to achieve real-time SCPP decoding at the aggregate data rate.

Microbiome analysis shows enrichment for specific bacteria in separate anatomical regions of the deep-sea carnivorous sponge Chondrocladia grandis.

PubMed

Verhoeven, Joost T P; Kavanagh, Alana N; Dufour, Suzanne C

2017-01-01

The Cladorhizidae is a unique family of carnivorous marine sponges characterised by either the absence or reduction of the aquiferous system and by the presence of specialised structures to trap and digest mesoplanktonic prey. Previous studies have postulated a key role of host-associated bacteria in enabling carnivory in this family of sponges. In this study, we employed high-throughput Illumina-based sequencing to identify the bacterial community associated with four individuals of the deep-sea sponge Chondrocladia grandis sampled in the Gulf of Maine. By characterising the V6 through V8 region of the 16S rRNA gene, we compared the bacterial community composition and diversity in three distinct anatomical regions with predicted involvement in prey capture (sphere), support (axis) and benthic substrate attachment (root). A high abundance of Tenacibaculum, a known siderophore producing bacterial genus, was present in all anatomical regions and specimens. The abundance of Colwellia and Roseobacter was greater in sphere and axis samples, and bacteria from the hydrocarbon-degrading Robiginitomaculum genus were most abundant in the root. This first description of the bacterial community associated with C. grandis provides novel insights into the contribution of bacteria to the carnivorous lifestyle while laying foundations for future cladorhizid symbiosis studies. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Diversity and characterization of bacteria associated with the deep-sea hydrothermal vent crab Austinograea sp. comparing with those of two shallow-water crabs by 16S ribosomal DNA analysis

PubMed Central

Wang, Minxiao; Liu, Yuan; Hui, Min

2017-01-01

For deep-sea hydrothermal vent crabs, recent investigations have revealed some epibiotic bacteria, but no study has described the bacterial community associated with the gill and intestine. In this study, the microbiota attached to the gill and intestine of the hydrothermal vent crab Austinograea sp. and two shallow-water crab species (Eriocheir sinensis and Portunus trituberculatus) were compared by high-throughput sequencing of 16S rDNA genes. The highest and lowest diversity in bacterial communities were observed in the gill and intestine of Austinograea sp., respectively. Non-metric multidimensional scaling (NMDS) analysis indicated that Austinograea sp. harbored a distinct microbial community. Operational taxonomic units (OTUs) for phylum Fusobacteria, class Epsilonproteobacteria, and genera Leucothrix, Polaribacter, Fusibacter, etc. were dominant in Austinograea sp. Of these, Leucothrix, Sulfurospirillum, and Arcobacter may be involved in oxidizing reduced sulfur compounds and sulfur metabolism; Marinomonas, Polaribacter adapted to the low temperature, and Fusibacter and Psychrilyobacter may survive well under hypoxic conditions. Bacteria commonly present in seawater were dominant in the gill, whereas anaerobic bacteria showed strikingly high abundance in the intestine. Interestingly, Firmicutes and Epsilonproteobacteria may complement each other in Austinograea sp., forming an internal environment. The diversified microbial community of Austinograea sp. reveals adaptation to the hydrothermal vent environment. PMID:29121118

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

PubMed

Kuhn, Alexandre; Ong, Yao Min; Quake, Stephen R; Burkholder, William F

2015-07-08

Like other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed. We describe a high-throughput method for genotyping transposable element insertions and other types of structural variants that can be assayed by breakpoint PCR. The method relies on next-generation sequencing of multiplex, site-specific PCR amplification products and read count-based genotype calls. We show that this method is flexible, efficient (it does not require rounds of optimization), cost-effective and highly accurate. This method can benefit a wide range of applications from the routine genotyping of animal and plant populations to the functional study of structural variants in humans.

NCBI GEO: archive for high-throughput functional genomic data.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron

2009-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

A high-throughput Sanger strategy for human mitochondrial genome sequencing

PubMed Central

2013-01-01

Background A population reference database of complete human mitochondrial genome (mtGenome) sequences is needed to enable the use of mitochondrial DNA (mtDNA) coding region data in forensic casework applications. However, the development of entire mtGenome haplotypes to forensic data quality standards is difficult and laborious. A Sanger-based amplification and sequencing strategy that is designed for automated processing, yet routinely produces high quality sequences, is needed to facilitate high-volume production of these mtGenome data sets. Results We developed a robust 8-amplicon Sanger sequencing strategy that regularly produces complete, forensic-quality mtGenome haplotypes in the first pass of data generation. The protocol works equally well on samples representing diverse mtDNA haplogroups and DNA input quantities ranging from 50 pg to 1 ng, and can be applied to specimens of varying DNA quality. The complete workflow was specifically designed for implementation on robotic instrumentation, which increases throughput and reduces both the opportunities for error inherent to manual processing and the cost of generating full mtGenome sequences. Conclusions The described strategy will assist efforts to generate complete mtGenome haplotypes which meet the highest data quality expectations for forensic genetic and other applications. Additionally, high-quality data produced using this protocol can be used to assess mtDNA data developed using newer technologies and chemistries. Further, the amplification strategy can be used to enrich for mtDNA as a first step in sample preparation for targeted next-generation sequencing. PMID:24341507

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.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PubMed Central

Kutchukian, Peter S.; Li, Jing; Tudor, Matthew

2017-01-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

Diversity and distribution of unicellular opisthokonts along the European coast analysed using high-throughput sequencing.

PubMed

Del Campo, Javier; Mallo, Diego; Massana, Ramon; de Vargas, Colomban; Richards, Thomas A; Ruiz-Trillo, Iñaki

2015-09-01

The opisthokonts are one of the major super groups of eukaryotes. It comprises two major clades: (i) the Metazoa and their unicellular relatives and (ii) the Fungi and their unicellular relatives. There is, however, little knowledge of the role of opisthokont microbes in many natural environments, especially among non-metazoan and non-fungal opisthokonts. Here, we begin to address this gap by analysing high-throughput 18S rDNA and 18S rRNA sequencing data from different European coastal sites, sampled at different size fractions and depths. In particular, we analyse the diversity and abundance of choanoflagellates, filastereans, ichthyosporeans, nucleariids, corallochytreans and their related lineages. Our results show the great diversity of choanoflagellates in coastal waters as well as a relevant representation of the ichthyosporeans and the uncultured marine opisthokonts (MAOP). Furthermore, we describe a new lineage of marine fonticulids (MAFO) that appears to be abundant in sediments. Taken together, our work points to a greater potential ecological role for unicellular opisthokonts than previously appreciated in marine environments, both in water column and sediments, and also provides evidence of novel opisthokont phylogenetic lineages. This study highlights the importance of high-throughput sequencing approaches to unravel the diversity and distribution of both known and novel eukaryotic lineages. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

PubMed

Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

2015-08-01

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

Methods for processing high-throughput RNA sequencing data.

PubMed

Ares, Manuel

2014-11-03

High-throughput sequencing (HTS) methods for analyzing RNA populations (RNA-Seq) are gaining rapid application to many experimental situations. The steps in an RNA-Seq experiment require thought and planning, especially because the expense in time and materials is currently higher and the protocols are far less routine than those used for other high-throughput methods, such as microarrays. As always, good experimental design will make analysis and interpretation easier. Having a clear biological question, an idea about the best way to do the experiment, and an understanding of the number of replicates needed will make the entire process more satisfying. Whether the goal is capturing transcriptome complexity from a tissue or identifying small fragments of RNA cross-linked to a protein of interest, conversion of the RNA to cDNA followed by direct sequencing using the latest methods is a developing practice, with new technical modifications and applications appearing every day. Even more rapid are the development and improvement of methods for analysis of the very large amounts of data that arrive at the end of an RNA-Seq experiment, making considerations regarding reproducibility, validation, visualization, and interpretation increasingly important. This introduction is designed to review and emphasize a pathway of analysis from experimental design through data presentation that is likely to be successful, with the recognition that better methods are right around the corner. © 2014 Cold Spring Harbor Laboratory Press.

Identification of microRNAs in the Toxigenic Dinoflagellate Alexandrium catenella by High-Throughput Illumina Sequencing and Bioinformatic Analysis

PubMed Central

Geng, Huili; Sui, Zhenghong; Zhang, Shu; Du, Qingwei; Ren, Yuanyuan; Liu, Yuan; Kong, Fanna; Zhong, Jie; Ma, Qingxia

2015-01-01

Micro-ribonucleic acids (miRNAs) are a large group of endogenous, tiny, non-coding RNAs consisting of 19–25 nucleotides that regulate gene expression at either the transcriptional or post-transcriptional level by mediating gene silencing in eukaryotes. They are considered to be important regulators that affect growth, development, and response to various stresses in plants. Alexandrium catenella is an important marine toxic phytoplankton species that can cause harmful algal blooms (HABs). To date, identification and function analysis of miRNAs in A. catenella remain largely unexamined. In this study, high-throughput sequencing was performed on A. catenella to identify and quantitatively profile the repertoire of small RNAs from two different growth phases. A total of 38,092,056 and 32,969,156 raw reads were obtained from the two small RNA libraries, respectively. In total, 88 mature miRNAs belonging to 32 miRNA families were identified. Significant differences were found in the member number, expression level of various families, and expression abundance of each member within a family. A total of 15 potentially novel miRNAs were identified. Comparative profiling showed that 12 known miRNAs exhibited differential expression between the lag phase and the logarithmic phase. Real-time quantitative RT-PCR (qPCR) was performed to confirm the expression of two differentially expressed miRNAs that were one up-regulated novel miRNA (aca-miR-3p-456915), and one down-regulated conserved miRNA (tae-miR159a). The expression trend of the qPCR assay was generally consistent with the deep sequencing result. Target predictions of the 12 differentially expressed miRNAs resulted in 1813target genes. Gene ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) annotations revealed that some miRNAs were associated with growth and developmental processes of the alga. These results provide insights into the roles that miRNAs play in the growth of A. catenella, and they provide the basis for further studies of the molecular mechanisms that underlie bloom growth in red tides species. PMID:26398216

Detection and Tracking of NY-ESO-1-Specific CD8+ T Cells by High-Throughput T Cell Receptor β (TCRB) Gene Rearrangements Sequencing in a Peptide-Vaccinated Patient.

PubMed

Miyai, Manami; Eikawa, Shingo; Hosoi, Akihiro; Iino, Tamaki; Matsushita, Hirokazu; Isobe, Midori; Uenaka, Akiko; Udono, Heiichiro; Nakajima, Jun; Nakayama, Eiichi; Kakimi, Kazuhiro

2015-01-01

Comprehensive immunological evaluation is crucial for monitoring patients undergoing antigen-specific cancer immunotherapy. The identification and quantification of T cell responses is most important for the further development of such therapies. Using well-characterized clinical samples from a high responder patient (TK-f01) in an NY-ESO-1f peptide vaccine study, we performed high-throughput T cell receptor β-chain (TCRB) gene next generation sequencing (NGS) to monitor the frequency of NY-ESO-1-specific CD8+ T cells. We compared these results with those of conventional immunological assays, such as IFN-γ capture, tetramer binding and limiting dilution clonality assays. We sequenced human TCRB complementarity-determining region 3 (CDR3) rearrangements of two NY-ESO-1f-specific CD8+ T cell clones, 6-8L and 2F6, as well as PBMCs over the course of peptide vaccination. Clone 6-8L possessed the TCRB CDR3 gene TCRBV11-03*01 and BJ02-01*01 with amino acid sequence CASSLRGNEQFF, whereas 2F6 possessed TCRBV05-08*01 and BJ02-04*01 (CASSLVGTNIQYF). Using these two sequences as models, we evaluated the frequency of NY-ESO-1-specific CD8+ T cells in PBMCs ex vivo. The 6-8L CDR3 sequence was the second most frequent in PBMC and was present at high frequency (0.7133%) even prior to vaccination, and sustained over the course of vaccination. Despite a marked expansion of NY-ESO-1-specific CD8+ T cells detected from the first through 6th vaccination by tetramer staining and IFN-γ capture assays, as evaluated by CDR3 sequencing the frequency did not increase with increasing rounds of peptide vaccination. By clonal analysis using 12 day in vitro stimulation, the frequency of B*52:01-restricted NY-ESO-1f peptide-specific CD8+ T cells in PBMCs was estimated as only 0.0023%, far below the 0.7133% by NGS sequencing. Thus, assays requiring in vitro stimulation might be underestimating the frequency of clones with lower proliferation potential. High-throughput TCRB sequencing using NGS can potentially better estimate the actual frequency of antigen-specific T cells and thus provide more accurate patient monitoring.

Detection and Tracking of NY-ESO-1-Specific CD8+ T Cells by High-Throughput T Cell Receptor β (TCRB) Gene Rearrangements Sequencing in a Peptide-Vaccinated Patient

PubMed Central

Miyai, Manami; Eikawa, Shingo; Hosoi, Akihiro; Iino, Tamaki; Matsushita, Hirokazu; Isobe, Midori; Uenaka, Akiko; Udono, Heiichiro; Nakajima, Jun; Nakayama, Eiichi; Kakimi, Kazuhiro

2015-01-01

Comprehensive immunological evaluation is crucial for monitoring patients undergoing antigen-specific cancer immunotherapy. The identification and quantification of T cell responses is most important for the further development of such therapies. Using well-characterized clinical samples from a high responder patient (TK-f01) in an NY-ESO-1f peptide vaccine study, we performed high-throughput T cell receptor β-chain (TCRB) gene next generation sequencing (NGS) to monitor the frequency of NY-ESO-1-specific CD8+ T cells. We compared these results with those of conventional immunological assays, such as IFN-γ capture, tetramer binding and limiting dilution clonality assays. We sequenced human TCRB complementarity-determining region 3 (CDR3) rearrangements of two NY-ESO-1f-specific CD8+ T cell clones, 6-8L and 2F6, as well as PBMCs over the course of peptide vaccination. Clone 6-8L possessed the TCRB CDR3 gene TCRBV11-03*01 and BJ02-01*01 with amino acid sequence CASSLRGNEQFF, whereas 2F6 possessed TCRBV05-08*01 and BJ02-04*01 (CASSLVGTNIQYF). Using these two sequences as models, we evaluated the frequency of NY-ESO-1-specific CD8+ T cells in PBMCs ex vivo. The 6-8L CDR3 sequence was the second most frequent in PBMC and was present at high frequency (0.7133%) even prior to vaccination, and sustained over the course of vaccination. Despite a marked expansion of NY-ESO-1-specific CD8+ T cells detected from the first through 6th vaccination by tetramer staining and IFN-γ capture assays, as evaluated by CDR3 sequencing the frequency did not increase with increasing rounds of peptide vaccination. By clonal analysis using 12 day in vitro stimulation, the frequency of B*52:01-restricted NY-ESO-1f peptide-specific CD8+ T cells in PBMCs was estimated as only 0.0023%, far below the 0.7133% by NGS sequencing. Thus, assays requiring in vitro stimulation might be underestimating the frequency of clones with lower proliferation potential. High-throughput TCRB sequencing using NGS can potentially better estimate the actual frequency of antigen-specific T cells and thus provide more accurate patient monitoring. PMID:26291626

The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision.

PubMed

Perreault, Andrea A; Venters, Bryan J

2016-12-23

Chromatin immunoprecipitation (ChIP) is an indispensable tool in the fields of epigenetics and gene regulation that isolates specific protein-DNA interactions. ChIP coupled to high throughput sequencing (ChIP-seq) is commonly used to determine the genomic location of proteins that interact with chromatin. However, ChIP-seq is hampered by relatively low mapping resolution of several hundred base pairs and high background signal. The ChIP-exo method is a refined version of ChIP-seq that substantially improves upon both resolution and noise. The key distinction of the ChIP-exo methodology is the incorporation of lambda exonuclease digestion in the library preparation workflow to effectively footprint the left and right 5' DNA borders of the protein-DNA crosslink site. The ChIP-exo libraries are then subjected to high throughput sequencing. The resulting data can be leveraged to provide unique and ultra-high resolution insights into the functional organization of the genome. Here, we describe the ChIP-exo method that we have optimized and streamlined for mammalian systems and next-generation sequencing-by-synthesis platform.

High-Throughput Screening for a Moderately Halophilic Phenol-Degrading Strain and Its Salt Tolerance Response

PubMed Central

Lu, Zhi-Yan; Guo, Xiao-Jue; Li, Hui; Huang, Zhong-Zi; Lin, Kuang-Fei; Liu, Yong-Di

2015-01-01

A high-throughput screening system for moderately halophilic phenol-degrading bacteria from various habitats was developed to replace the conventional strain screening owing to its high efficiency. Bacterial enrichments were cultivated in 48 deep well microplates instead of shake flasks or tubes. Measurement of phenol concentrations was performed in 96-well microplates instead of using the conventional spectrophotometric method or high-performance liquid chromatography (HPLC). The high-throughput screening system was used to cultivate forty-three bacterial enrichments and gained a halophilic bacterial community E3 with the best phenol-degrading capability. Halomonas sp. strain 4-5 was isolated from the E3 community. Strain 4-5 was able to degrade more than 94% of the phenol (500 mg·L−1 starting concentration) over a range of 3%–10% NaCl. Additionally, the strain accumulated the compatible solute, ectoine, with increasing salt concentrations. PCR detection of the functional genes suggested that the largest subunit of multicomponent phenol hydroxylase (LmPH) and catechol 1,2-dioxygenase (C12O) were active in the phenol degradation process. PMID:26020478

Polymorphism discovery and allele frequency estimation using high-throughput DNA sequencing of target-enriched pooled DNA samples

PubMed Central

2012-01-01

Background The central role of the somatotrophic axis in animal post-natal growth, development and fertility is well established. Therefore, the identification of genetic variants affecting quantitative traits within this axis is an attractive goal. However, large sample numbers are a pre-requisite for the identification of genetic variants underlying complex traits and although technologies are improving rapidly, high-throughput sequencing of large numbers of complete individual genomes remains prohibitively expensive. Therefore using a pooled DNA approach coupled with target enrichment and high-throughput sequencing, the aim of this study was to identify polymorphisms and estimate allele frequency differences across 83 candidate genes of the somatotrophic axis, in 150 Holstein-Friesian dairy bulls divided into two groups divergent for genetic merit for fertility. Results In total, 4,135 SNPs and 893 indels were identified during the resequencing of the 83 candidate genes. Nineteen percent (n = 952) of variants were located within 5' and 3' UTRs. Seventy-two percent (n = 3,612) were intronic and 9% (n = 464) were exonic, including 65 indels and 236 SNPs resulting in non-synonymous substitutions (NSS). Significant (P < 0.01) mean allele frequency differentials between the low and high fertility groups were observed for 720 SNPs (58 NSS). Allele frequencies for 43 of the SNPs were also determined by genotyping the 150 individual animals (Sequenom® MassARRAY). No significant differences (P > 0.1) were observed between the two methods for any of the 43 SNPs across both pools (i.e., 86 tests in total). Conclusions The results of the current study support previous findings of the use of DNA sample pooling and high-throughput sequencing as a viable strategy for polymorphism discovery and allele frequency estimation. Using this approach we have characterised the genetic variation within genes of the somatotrophic axis and related pathways, central to mammalian post-natal growth and development and subsequent lactogenesis and fertility. We have identified a large number of variants segregating at significantly different frequencies between cattle groups divergent for calving interval plausibly harbouring causative variants contributing to heritable variation. To our knowledge, this is the first report describing sequencing of targeted genomic regions in any livestock species using groups with divergent phenotypes for an economically important trait. PMID:22235840

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

PubMed

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

2011-08-30

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

Coprolites as a source of information on the genome and diet of the cave hyena

PubMed Central

Bon, Céline; Berthonaud, Véronique; Maksud, Frédéric; Labadie, Karine; Poulain, Julie; Artiguenave, François; Wincker, Patrick; Aury, Jean-Marc; Elalouf, Jean-Marc

2012-01-01

We performed high-throughput sequencing of DNA from fossilized faeces to evaluate this material as a source of information on the genome and diet of Pleistocene carnivores. We analysed coprolites derived from the extinct cave hyena (Crocuta crocuta spelaea), and sequenced 90 million DNA fragments from two specimens. The DNA reads enabled a reconstruction of the cave hyena mitochondrial genome with up to a 158-fold coverage. This genome, and those sequenced from extant spotted (Crocuta crocuta) and striped (Hyaena hyaena) hyena specimens, allows for the establishment of a robust phylogeny that supports a close relationship between the cave and the spotted hyena. We also demonstrate that high-throughput sequencing yields data for cave hyena multi-copy and single-copy nuclear genes, and that about 50 per cent of the coprolite DNA can be ascribed to this species. Analysing the data for additional species to indicate the cave hyena diet, we retrieved abundant sequences for the red deer (Cervus elaphus), and characterized its mitochondrial genome with up to a 3.8-fold coverage. In conclusion, we have demonstrated the presence of abundant ancient DNA in the coprolites surveyed. Shotgun sequencing of this material yielded a wealth of DNA sequences for a Pleistocene carnivore and allowed unbiased identification of diet. PMID:22456883

Characterization of a new apple luteovirus identified by high-throughput sequencing.

PubMed

Liu, Huawei; Wu, Liping; Nikolaeva, Ekaterina; Peter, Kari; Liu, Zongrang; Mollov, Dimitre; Cao, Mengji; Li, Ruhui

2018-05-15

'Rapid Apple Decline' (RAD) is a newly emerging problem of young, dwarf apple trees in the Northeastern USA. The affected trees show trunk necrosis, cracking and canker before collapse in summer. In this study, we discovered and characterized a new luteovirus from apple trees in RAD-affected orchards using high-throughput sequencing (HTS) technology and subsequent Sanger sequencing. Illumina NextSeq sequencing was applied to total RNAs prepared from three diseased apple trees. Sequence reads were de novo assembled, and contigs were annotated by BLASTx. RT-PCR and 5'/3' RACE sequencing were used to obtain the complete genome of a new virus. RT-PCR was used to detect the virus. Three common apple viruses and a new luteovirus were identified from the diseased trees by HTS and RT-PCR. Sequence analyses of the complete genome of the new virus show that it is a new species of the genus Luteovirus in the family Luteoviridae. The virus is graft transmissible and detected by RT-PCR in apple trees in a couple of orchards. A new luteovirus and/or three known viruses were found to be associated with RAD. Molecular characterization of the new luteovirus provides important information for further investigation of its distribution and etiological role.

Evaluation of the Telecommunications Protocol Processing Subsystem Using Reconfigurable Interoperable Gate Array

NASA Technical Reports Server (NTRS)

Pang, Jackson; Liddicoat, Albert; Ralston, Jesse; Pingree, Paula

2006-01-01

The current implementation of the Telecommunications Protocol Processing Subsystem Using Reconfigurable Interoperable Gate Arrays (TRIGA) is equipped with CFDP protocol and CCSDS Telemetry and Telecommand framing schemes to replace the CPU intensive software counterpart implementation for reliable deep space communication. We present the hardware/software co-design methodology used to accomplish high data rate throughput. The hardware CFDP protocol stack implementation is then compared against the two recent flight implementations. The results from our experiments show that TRIGA offers more than 3 orders of magnitude throughput improvement with less than one-tenth of the power consumption.

Alignment of high-throughput sequencing data inside in-memory databases.

PubMed

Firnkorn, Daniel; Knaup-Gregori, Petra; Lorenzo Bermejo, Justo; Ganzinger, Matthias

2014-01-01

In times of high-throughput DNA sequencing techniques, performance-capable analysis of DNA sequences is of high importance. Computer supported DNA analysis is still an intensive time-consuming task. In this paper we explore the potential of a new In-Memory database technology by using SAP's High Performance Analytic Appliance (HANA). We focus on read alignment as one of the first steps in DNA sequence analysis. In particular, we examined the widely used Burrows-Wheeler Aligner (BWA) and implemented stored procedures in both, HANA and the free database system MySQL, to compare execution time and memory management. To ensure that the results are comparable, MySQL has been running in memory as well, utilizing its integrated memory engine for database table creation. We implemented stored procedures, containing exact and inexact searching of DNA reads within the reference genome GRCh37. Due to technical restrictions in SAP HANA concerning recursion, the inexact matching problem could not be implemented on this platform. Hence, performance analysis between HANA and MySQL was made by comparing the execution time of the exact search procedures. Here, HANA was approximately 27 times faster than MySQL which means, that there is a high potential within the new In-Memory concepts, leading to further developments of DNA analysis procedures in the future.

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

PubMed

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

2017-07-12

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

Assessment of the cPAS-based BGISEQ-500 platform for metagenomic sequencing.

PubMed

Fang, Chao; Zhong, Huanzi; Lin, Yuxiang; Chen, Bing; Han, Mo; Ren, Huahui; Lu, Haorong; Luber, Jacob M; Xia, Min; Li, Wangsheng; Stein, Shayna; Xu, Xun; Zhang, Wenwei; Drmanac, Radoje; Wang, Jian; Yang, Huanming; Hammarström, Lennart; Kostic, Aleksandar D; Kristiansen, Karsten; Li, Junhua

2018-03-01

More extensive use of metagenomic shotgun sequencing in microbiome research relies on the development of high-throughput, cost-effective sequencing. Here we present a comprehensive evaluation of the performance of the new high-throughput sequencing platform BGISEQ-500 for metagenomic shotgun sequencing and compare its performance with that of 2 Illumina platforms. Using fecal samples from 20 healthy individuals, we evaluated the intra-platform reproducibility for metagenomic sequencing on the BGISEQ-500 platform in a setup comprising 8 library replicates and 8 sequencing replicates. Cross-platform consistency was evaluated by comparing 20 pairwise replicates on the BGISEQ-500 platform vs the Illumina HiSeq 2000 platform and the Illumina HiSeq 4000 platform. In addition, we compared the performance of the 2 Illumina platforms against each other. By a newly developed overall accuracy quality control method, an average of 82.45 million high-quality reads (96.06% of raw reads) per sample, with 90.56% of bases scoring Q30 and above, was obtained using the BGISEQ-500 platform. Quantitative analyses revealed extremely high reproducibility between BGISEQ-500 intra-platform replicates. Cross-platform replicates differed slightly more than intra-platform replicates, yet a high consistency was observed. Only a low percentage (2.02%-3.25%) of genes exhibited significant differences in relative abundance comparing the BGISEQ-500 and HiSeq platforms, with a bias toward genes with higher GC content being enriched on the HiSeq platforms. Our study provides the first set of performance metrics for human gut metagenomic sequencing data using BGISEQ-500. The high accuracy and technical reproducibility confirm the applicability of the new platform for metagenomic studies, though caution is still warranted when combining metagenomic data from different platforms.

Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway.

PubMed

Li, Gang; Diogo, Dorothée; Wu, Di; Spoonamore, Jim; Dancik, Vlado; Franke, Lude; Kurreeman, Fina; Rossin, Elizabeth J; Duclos, Grant; Hartland, Cathy; Zhou, Xuezhong; Li, Kejie; Liu, Jun; De Jager, Philip L; Siminovitch, Katherine A; Zhernakova, Alexandra; Raychaudhuri, Soumya; Bowes, John; Eyre, Steve; Padyukov, Leonid; Gregersen, Peter K; Worthington, Jane; Gupta, Namrata; Clemons, Paul A; Stahl, Eli; Tolliday, Nicola; Plenge, Robert M

2013-05-01

Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10(-9)). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10(-9)), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA-approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.

Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

PubMed

Zhang, Xi

2015-09-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2017-01-01

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

Deep sampling of the Palomero maize transcriptome by a high throughput strategy of pyrosequencing.

PubMed

Vega-Arreguín, Julio C; Ibarra-Laclette, Enrique; Jiménez-Moraila, Beatriz; Martínez, Octavio; Vielle-Calzada, Jean Philippe; Herrera-Estrella, Luis; Herrera-Estrella, Alfredo

2009-07-06

In-depth sequencing analysis has not been able to determine the overall complexity of transcriptional activity of a plant organ or tissue sample. In some cases, deep parallel sequencing of Expressed Sequence Tags (ESTs), although not yet optimized for the sequencing of cDNAs, has represented an efficient procedure for validating gene prediction and estimating overall gene coverage. This approach could be very valuable for complex plant genomes. In addition, little emphasis has been given to efforts aiming at an estimation of the overall transcriptional universe found in a multicellular organism at a specific developmental stage. To explore, in depth, the transcriptional diversity in an ancient maize landrace, we developed a protocol to optimize the sequencing of cDNAs and performed 4 consecutive GS20-454 pyrosequencing runs of a cDNA library obtained from 2 week-old Palomero Toluqueño maize plants. The protocol reported here allowed obtaining over 90% of informative sequences. These GS20-454 runs generated over 1.5 Million reads, representing the largest amount of sequences reported from a single plant cDNA library. A collection of 367,391 quality-filtered reads (30.09 Mb) from a single run was sufficient to identify transcripts corresponding to 34% of public maize ESTs databases; total sequences generated after 4 filtered runs increased this coverage to 50%. Comparisons of all 1.5 Million reads to the Maize Assembled Genomic Islands (MAGIs) provided evidence for the transcriptional activity of 11% of MAGIs. We estimate that 5.67% (86,069 sequences) do not align with public ESTs or annotated genes, potentially representing new maize transcripts. Following the assembly of 74.4% of the reads in 65,493 contigs, real-time PCR of selected genes confirmed a predicted correlation between the abundance of GS20-454 sequences and corresponding levels of gene expression. A protocol was developed that significantly increases the number, length and quality of cDNA reads using massive 454 parallel sequencing. We show that recurrent 454 pyrosequencing of a single cDNA sample is necessary to attain a thorough representation of the transcriptional universe present in maize, that can also be used to estimate transcript abundance of specific genes. This data suggests that the molecular and functional diversity contained in the vast native landraces remains to be explored, and that large-scale transcriptional sequencing of a presumed ancestor of the modern maize varieties represents a valuable approach to characterize the functional diversity of maize for future agricultural and evolutionary studies.

Development of a Rapid Identification Method for a Variety of Antibody Candidates Using High-throughput Sequencing.

PubMed

Ito, Yuji

2017-01-01

As an alternative to hybridoma technology, the antibody phage library system can also be used for antibody selection. This method enables the isolation of antigen-specific binders through an in vitro selection process known as biopanning. While it has several advantages, such as an avoidance of animal immunization, the phage cloning and screening steps of biopanning are time-consuming and problematic. Here, we introduce a novel biopanning method combined with high-throughput sequencing (HTS) using a next-generation sequencer (NGS) to save time and effort in antibody selection, and to increase the diversity of acquired antibody sequences. Biopannings against a target antigen were performed using a human single chain Fv (scFv) antibody phage library. VH genes in pooled phages at each round of biopanning were analyzed by HTS on a NGS. The obtained data were trimmed, merged, and translated into amino acid sequences. The frequencies (%) of the respective VH sequences at each biopanning step were calculated, and the amplification factor (change of frequency through biopanning) was obtained to estimate the potential for antigen binding. A phylogenetic tree was drawn using the top 50 VH sequences with high amplification factors. Representative VH sequences forming the cluster were then picked up and used to reconstruct scFv genes harboring these VHs. Their derived scFv-Fc fusion proteins showed clear antigen binding activity. These results indicate that a combination of biopanning and HTS enables the rapid and comprehensive identification of specific binders from antibody phage libraries.

Filling reference gaps via assembling DNA barcodes using high-throughput sequencing—moving toward barcoding the world

PubMed Central

Zhou, Chengran

2017-01-01

Abstract Over the past decade, biodiversity researchers have dedicated tremendous efforts to constructing DNA reference barcodes for rapid species registration and identification. Although analytical cost for standard DNA barcoding has been significantly reduced since early 2000, further dramatic reduction in barcoding costs is unlikely because Sanger sequencing is approaching its limits in throughput and chemistry cost. Constraints in barcoding cost not only led to unbalanced barcoding efforts around the globe, but also prevented high-throughput sequencing (HTS)–based taxonomic identification from applying binomial species names, which provide crucial linkages to biological knowledge. We developed an Illumina-based pipeline, HIFI-Barcode, to produce full-length Cytochrome c oxidase subunit I (COI) barcodes from pooled polymerase chain reaction amplicons generated by individual specimens. The new pipeline generated accurate barcode sequences that were comparable to Sanger standards, even for different haplotypes of the same species that were only a few nucleotides different from each other. Additionally, the new pipeline was much more sensitive in recovering amplicons at low quantity. The HIFI-Barcode pipeline successfully recovered barcodes from more than 78% of the polymerase chain reactions that didn’t show clear bands on the electrophoresis gel. Moreover, sequencing results based on the single molecular sequencing platform Pacbio confirmed the accuracy of the HIFI-Barcode results. Altogether, the new pipeline can provide an improved solution to produce full-length reference barcodes at about one-tenth of the current cost, enabling construction of comprehensive barcode libraries for local fauna, leading to a feasible direction for DNA barcoding global biomes. PMID:29077841

Report for the NGFA-5 project.

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

Jaing, C; Jackson, P; Thissen, J

The objective of this project is to provide DHS a comprehensive evaluation of the current genomic technologies including genotyping, TaqMan PCR, multiple locus variable tandem repeat analysis (MLVA), microarray and high-throughput DNA sequencing in the analysis of biothreat agents from complex environmental samples. To effectively compare the sensitivity and specificity of the different genomic technologies, we used SNP TaqMan PCR, MLVA, microarray and high-throughput illumine and 454 sequencing to test various strains from B. anthracis, B. thuringiensis, BioWatch aerosol filter extracts or soil samples that were spiked with B. anthracis, and samples that were previously collected during DHS and EPAmore » environmental release exercises that were known to contain B. thuringiensis spores. The results of all the samples against the various assays are discussed in this report.« less

Insights into the microbial diversity and community dynamics of Chinese traditional fermented foods from using high-throughput sequencing approaches*

PubMed Central

He, Guo-qing; Liu, Tong-jie; Sadiq, Faizan A.; Gu, Jing-si; Zhang, Guo-hua

2017-01-01

Chinese traditional fermented foods have a very long history dating back thousands of years and have become an indispensable part of Chinese dietary culture. A plethora of research has been conducted to unravel the composition and dynamics of microbial consortia associated with Chinese traditional fermented foods using culture-dependent as well as culture-independent methods, like different high-throughput sequencing (HTS) techniques. These HTS techniques enable us to understand the relationship between a food product and its microbes to a greater extent than ever before. Considering the importance of Chinese traditional fermented products, the objective of this paper is to review the diversity and dynamics of microbiota in Chinese traditional fermented foods revealed by HTS approaches. PMID:28378567

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

NASA Astrophysics Data System (ADS)

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

2011-10-01

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

Deep sequencing identification of miRNAs in pigeon ovaries illuminated with monochromatic light.

PubMed

Wang, Ying; Yang, Hai-Ming; Cao, Wei; Li, Yang-Bai; Wang, Zhi-Yue

2018-06-08

The use of light of different wavelengths has grown popular in the poultry industry. An optimum wavelength is believed to improve pigeon egg production, but little is known about the role of microRNAs (miRNAs) in the effects of monochromatic light on ovarian pigeon function. Herein, we harvested ovaries from pigeons reared under monochromatic light of different wavelength and performed deep sequencing on various tissues using an Illumina Solexa high-throughput instrument. We obtained 66,148,548, 67,873,805, and 71,661,771 clean reads from ovaries of pigeons reared under red light (RL), blue light (BL), and white light (WL), respectively. We identified 1917 known miRNAs in nine libraries, of which 524 were novel. Three and five differentially expressed miRNAs were identified in BL vs. WL and RL vs. WL groups, respectively. Quantitative reverse transcription PCR was used to validate differentially expressed miRNAs (miR-200, miR-122, and miR-205b). In addition, 5824 target genes were annotated as differentially expressed miRNAs, most of which are involved in reproductive pathways including oestrogen signalling, cell cycle, and oocyte maturation. Notably, ovarian miR-205b expression was significantly negatively correlated with its target 11β-hydroxysteroid dehydrogenase type 1 (HSD11B1). miRNA-mRNA network analysis suggests that miR-205b targeting of HSD11B1 plays a key role in the effects of monochromatic light on pigeon egg production. These findings indicate that monochromatic light shortens the oviposition interval of pigeons, which may be useful for egg production and pigeon breeding.

A Dual-Mode Large-Arrayed CMOS ISFET Sensor for Accurate and High-Throughput pH Sensing in Biomedical Diagnosis.

PubMed

Huang, Xiwei; Yu, Hao; Liu, Xu; Jiang, Yu; Yan, Mei; Wu, Dongping

2015-09-01

The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.

Pathogenic bacteria in sewage treatment plants as revealed by 454 pyrosequencing.

PubMed

Ye, Lin; Zhang, Tong

2011-09-01

This study applied 454 high-throughput pyrosequencing to analyze potentially pathogenic bacteria in activated sludge from 14 municipal wastewater treatment plants (WWTPs) across four countries (China, U.S., Canada, and Singapore), plus the influent and effluent of one of the 14 WWTPs. A total of 370,870 16S rRNA gene sequences with average length of 207 bps were obtained and all of them were assigned to corresponding taxonomic ranks by using RDP classifier and MEGAN. It was found that the most abundant potentially pathogenic bacteria in the WWTPs were affiliated with the genera of Aeromonas and Clostridium. Aeromonas veronii, Aeromonas hydrophila, and Clostridium perfringens were species most similar to the potentially pathogenic bacteria found in this study. Some sequences highly similar (>99%) to Corynebacterium diphtheriae were found in the influent and activated sludge samples from a saline WWTP. Overall, the percentage of the sequences closely related (>99%) to known pathogenic bacteria sequences was about 0.16% of the total sequences. Additionally, a platform-independent Java application (BAND) was developed for graphical visualization of the data of microbial abundance generated by high-throughput pyrosequencing. The approach demonstrated in this study could examine most of the potentially pathogenic bacteria simultaneously instead of one-by-one detection by other methods.